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600 Commits
half ... v0.7.3

Author SHA1 Message Date
Andrew Kane
4733cf253b Version bump to 0.7.3 [skip ci] 2024-07-22 09:16:59 -07:00
Andrew Kane
06d1fa1402 Added alignment check to ensure consistency with PageIndexTupleOverwrite 2024-07-19 15:50:24 -07:00
Andrew Kane
8c5a4bfb6c Fixed failed to add index item error with sparsevec - fixes #625 2024-07-19 13:54:36 -07:00
Andrew Kane
8772c8de68 Fixed compilation error with FreeBSD ARM 2024-06-30 11:23:39 -07:00
Andrew Kane
d1694a93af Added ubuntu-24.04 to CI [skip ci] 2024-06-17 10:45:58 -07:00
Andrew Kane
61870a0244 Fixed compilation warning with MSVC and Postgres 16 - fixes #598
Co-authored-by: Xing Guo <higuoxing@gmail.com>
2024-06-16 12:09:01 -07:00
Andrew Kane
9b89bed701 Version bump to 0.7.2 [skip ci] 2024-06-11 17:26:51 -07:00
Andrew Kane
ad7cad5ecd Improved HnswSearchLayer code 2024-06-11 16:29:14 -07:00
Andrew Kane
2a8b9d689e Moved check 2024-06-11 15:45:03 -07:00
Andrew Kane
18cd8a60c3 Updated comment [skip ci] 2024-06-10 22:02:40 -07:00
Andrew Kane
8c91a9f56a Fixed initialization fork for IVFFlat indexes on unlogged tables - #591 2024-06-10 21:55:17 -07:00
Andrew Kane
9249e7e2de Updated changelog [skip ci] 2024-06-10 21:33:49 -07:00
Andrew Kane
9e91af5989 Added checks for invalid indexes - #591 2024-06-10 21:20:54 -07:00
Narek Galstyan
9dcf1bdc80 Fix init_fork WAL-logging on unlogged indexes (#591)
Currently pgvector does not create any WAL records for unlogged tables

Postgres assumes INIT_FORK of unlogged tables is persistent and uses it
to reset the table index to its default empty state after a server
crash.

This patch makes INIT_FORK of unlogged table WAL-tracked, which ensures
an unlogged table is usable after a crash-restart
2024-06-10 21:16:32 -07:00
Andrew Kane
0eceaa3966 Version bump to 0.7.1 [skip ci] 2024-06-03 13:48:51 -07:00
Andrew Kane
49c1f13095 Improved performance of on-disk HNSW index builds - #570 2024-05-29 12:03:58 -07:00
Andrew Kane
ff9b22977e Updated FAQ [skip ci] 2024-05-20 16:48:38 -04:00
Andrew Kane
0468cbf6e6 Added --pull to Docker build instructions [skip ci] 2024-05-20 11:42:11 -04:00
Andrew Kane
258eaf58fd Added halfvec and sparsevec opclasses to readme - closes #540 [skip ci] 2024-05-08 10:40:55 -07:00
Andrew Kane
fa8d2df1cc Added note about ascending order to troubleshooting docs - #548 [skip ci] 2024-05-08 08:36:24 -07:00
Andrew Kane
69f49290fb Fixed compilation warning with Clang < 14 - closes #546 2024-05-07 20:53:41 -07:00
Andrew Kane
ad91451266 Updated changelog and comment [skip ci] 2024-05-07 18:03:21 -07:00
Andrew Kane
cafd2f6641 Updated comment [skip ci] 2024-05-07 17:53:35 -07:00
Andrew Kane
7923c44efe Switched to __apple_build_version__ [skip ci] 2024-05-07 17:41:16 -07:00
Andrew Kane
9b269e2612 Added separate define for __get_cpuid 2024-05-07 16:55:21 -07:00
Andrew Kane
9894ca3e4e Fixed error with cross-compiling / universal binaries on Mac - #544 [skip ci] 2024-05-07 16:46:47 -07:00
Andrew Kane
19cbbfdd69 Fixed undefined symbol error with GCC 8 - fixes #538 2024-05-02 07:50:06 -07:00
Andrew Kane
24c8a2ff40 Fixed flaky tests [skip ci] 2024-04-29 13:54:30 -07:00
Andrew Kane
6df583a6f6 Fixed regression test for vector type 2024-04-29 13:48:04 -07:00
Andrew Kane
999a2e53dd Updated readme [skip ci] 2024-04-29 10:41:40 -07:00
Andrew Kane
3849f0fd3d Version bump to 0.7.0 [skip ci] 2024-04-29 09:26:06 -07:00
Andrew Kane
df178472d1 Updated readme for 0.7.0 [skip ci] 2024-04-29 09:15:24 -07:00
Andrew Kane
a72511db7f Removed unneeded comments [skip ci] 2024-04-27 11:43:45 -07:00
Andrew Kane
b52beefbc6 Added basic fuzz testing for input functions 2024-04-27 10:49:45 -07:00
Andrew Kane
1cc66543be Reordered types in sql files [skip ci] 2024-04-26 17:50:26 -07:00
Andrew Kane
b15930c9c0 Added comment [skip ci] 2024-04-26 17:43:41 -07:00
Andrew Kane
6f2afb16ff Use consistent error message for sparsevec index out of bounds [skip ci] 2024-04-26 17:27:09 -07:00
Andrew Kane
0959e69529 Added comments [skip ci] 2024-04-26 17:24:15 -07:00
Andrew Kane
1e94907179 Improved sparsevec error messages [skip ci] 2024-04-26 17:11:11 -07:00
Andrew Kane
c9fb66d54d Fixed flaky tests 2024-04-26 13:20:27 -07:00
Andrew Kane
48e68e5e42 Improved HNSW recall tests - #535 2024-04-26 13:08:48 -07:00
Andrew Kane
78d32943ac Added test for halfvec sum 2024-04-25 22:03:34 -07:00
Andrew Kane
ee29c51a49 Added comment [skip ci] 2024-04-25 21:45:26 -07:00
Andrew Kane
cf494f15ac Added aggregate test for halfvec [skip ci] 2024-04-25 21:42:10 -07:00
Andrew Kane
13bd194d00 Added comment [skip ci] 2024-04-25 21:35:04 -07:00
Andrew Kane
0ddf65c2a3 Added separate SQL function for halfvec_combine [skip ci] 2024-04-25 21:31:43 -07:00
Andrew Kane
1475c06902 Reordered TAP tests [skip ci] 2024-04-25 21:08:55 -07:00
Andrew Kane
7140a18283 Reordered TAP tests [skip ci] 2024-04-25 21:04:23 -07:00
Andrew Kane
7dcdaef96c Renamed TAP tests [skip ci] 2024-04-25 20:57:41 -07:00
Andrew Kane
abad3d81cc Added comment [skip ci] 2024-04-25 19:51:47 -07:00
Andrew Kane
d516c9bd3f Improved code [skip ci] 2024-04-25 19:49:21 -07:00
Andrew Kane
a172b7cafd Moved include [skip ci] 2024-04-25 19:42:56 -07:00
Andrew Kane
3cbffb0e45 Updated comment [skip ci] 2024-04-25 19:42:10 -07:00
Andrew Kane
5e98f455e3 Moved dispatching defines to halfvec.h [skip ci] 2024-04-25 19:39:00 -07:00
Andrew Kane
498a39d79b Added comment [skip ci] 2024-04-25 18:57:08 -07:00
Andrew Kane
d9e22a31ca Fixed regression test list for Windows 2024-04-25 18:32:05 -07:00
Andrew Kane
5ecf02f07b Added comment [skip ci] 2024-04-25 18:00:45 -07:00
Andrew Kane
d188b56173 Removed header [skip ci] 2024-04-25 17:58:32 -07:00
Andrew Kane
6247b302fc Removed unneeded headers [skip ci] 2024-04-25 17:52:35 -07:00
Andrew Kane
7f15221fb4 Updated define [skip ci] 2024-04-25 17:50:14 -07:00
Andrew Kane
f23d7184e9 Moved version check to first header [skip ci] 2024-04-25 17:49:25 -07:00
Andrew Kane
cd95d6dfa4 Improved CheckCenters code [skip ci] 2024-04-25 17:41:53 -07:00
Andrew Kane
dc88135515 Updated comment [skip ci] 2024-04-25 17:30:46 -07:00
Andrew Kane
c91fc7e0f7 Changed VectorArrayGet and VectorArraySet to functions [skip ci] 2024-04-25 17:27:10 -07:00
Andrew Kane
708da0e058 Improved copy test [skip ci] 2024-04-25 15:39:47 -07:00
Andrew Kane
80d34830f6 Condensed regression tests [skip ci] 2024-04-25 15:35:36 -07:00
Andrew Kane
68ac05e11e Condensed regression tests [skip ci] 2024-04-25 15:30:38 -07:00
Andrew Kane
8daa581f42 Improved memory context for k-means [skip ci] 2024-04-25 14:22:24 -07:00
Andrew Kane
ebc76114ad Fixed item size [skip ci] 2024-04-25 14:03:42 -07:00
Andrew Kane
5dec500879 Reduced support functions for IVFFlat - #527 2024-04-25 13:56:20 -07:00
Andrew Kane
1fdfff7349 Restored collation for consistency [skip ci] 2024-04-25 13:46:45 -07:00
Andrew Kane
38e365ed58 Restored HnswNormValue [skip ci] 2024-04-25 13:35:17 -07:00
Andrew Kane
58ec5296b0 Reduced support functions for HNSW - #527 2024-04-25 13:21:24 -07:00
Andrew Kane
47d5b2896e Improved support functions for HNSW - #527 2024-04-25 13:00:40 -07:00
Andrew Kane
2bf1175ab0 Removed unused fields from IvfflatTypeInfo [skip ci] 2024-04-25 12:36:15 -07:00
Andrew Kane
ec640f3b57 Switched to static const for IVFFlat type info 2024-04-25 12:30:49 -07:00
Andrew Kane
91cf4d223e Added comment [skip ci] 2024-04-25 12:13:43 -07:00
Andrew Kane
96fdf63787 Improved function name [skip ci] 2024-04-25 12:05:15 -07:00
Andrew Kane
914f9aa04a Fixed flaky test [skip ci] 2024-04-25 11:57:40 -07:00
Andrew Kane
e9c3c42e1c Reduced support functions for ivfflat - #527 2024-04-25 11:49:48 -07:00
Andrew Kane
c67dc6f9b0 Added test for bit with duplicate centers 2024-04-25 10:29:28 -07:00
Andrew Kane
c39cb25c32 Fixed flaky tests [skip ci] 2024-04-24 22:26:08 -07:00
Andrew Kane
8f00d679d6 Removed type-specific code from IVFFlat - #527 2024-04-24 22:19:53 -07:00
Andrew Kane
52bfedddc2 Improved naming [skip ci] 2024-04-24 18:16:54 -07:00
Andrew Kane
0f4c2407dd Removed IvfflatType from CheckCenters [skip ci] 2024-04-24 18:13:01 -07:00
Andrew Kane
3e924ab7ad Added checkDuplicates to KmeansState [skip ci] 2024-04-24 18:04:26 -07:00
Andrew Kane
cd8a25bc9a Removed IvfflatType from more functions [skip ci] 2024-04-24 17:45:48 -07:00
Andrew Kane
6bb5de3d1b Added KmeansState [skip ci] 2024-04-24 17:40:21 -07:00
Andrew Kane
15ee38456f Improved initialization of new centers [skip ci] 2024-04-24 16:45:16 -07:00
Andrew Kane
25b98540c9 Improved QuickCenters [skip ci] 2024-04-24 16:38:14 -07:00
Andrew Kane
c4484c90d9 Switched to Pointer [skip ci] 2024-04-24 16:27:54 -07:00
Andrew Kane
1129d23df9 Updated SumCenters and SetNewCenters to use float [skip ci] 2024-04-24 16:08:19 -07:00
Andrew Kane
cf46c3f651 Improved code [skip ci] 2024-04-24 15:57:29 -07:00
Andrew Kane
fb6683ade7 Improved SetNewCenters [skip ci] 2024-04-24 15:56:50 -07:00
Andrew Kane
558953ca6b Improved SumCenters [skip ci] 2024-04-24 15:50:23 -07:00
Andrew Kane
b24ec26025 Improved SortVectorArray [skip ci] 2024-04-24 15:38:04 -07:00
Andrew Kane
8b6eab25a3 Moved IvfflatGetType [skip ci] 2024-04-24 15:34:10 -07:00
Andrew Kane
69c3e719f7 Added support functions for max dimensions for ivfflat 2024-04-24 15:27:10 -07:00
Andrew Kane
e81547847f Updated comment [skip ci] 2024-04-24 15:09:04 -07:00
Andrew Kane
6ad81fc60d Moved functions and synced upgrade script [skip ci] 2024-04-24 15:08:30 -07:00
Andrew Kane
7ac0ac5a7f Renamed functions [skip ci] 2024-04-24 15:00:36 -07:00
Andrew Kane
3eef1ff5c2 Removed type-specific code from HNSW [skip ci] 2024-04-24 14:53:45 -07:00
Heikki Linnakangas
b8bdf317f0 Add comment to 'unused' fields
I just guessed that these exist for future extendability.
2024-04-24 13:05:02 -07:00
Andrew Kane
78e5bcf229 Switched to 0-based numbering for sparsevec on-disk format 2024-04-24 12:51:24 -07:00
Andrew Kane
4d21eea6f1 Updated comments [skip ci] 2024-04-24 11:27:09 -07:00
Andrew Kane
03ca9adc4c Added comments [skip ci] 2024-04-24 11:26:05 -07:00
Andrew Kane
d244a040e1 Increased max sparsevec dimensions to 1B [skip ci] 2024-04-24 11:17:25 -07:00
Andrew Kane
c3448a25e2 Improved error messages for sparsevec input 2024-04-24 11:12:28 -07:00
Andrew Kane
053ce2ddae Improved CI for Windows [skip ci] 2024-04-24 10:22:31 -07:00
Andrew Kane
24c1b51099 Added comment [skip ci] 2024-04-24 10:13:50 -07:00
Andrew Kane
9696835a19 Improved tests for sparsevec input [skip ci] 2024-04-24 09:58:27 -07:00
Andrew Kane
b2a5259607 Switched to strtoint for sparsevec input 2024-04-24 09:56:09 -07:00
Andrew Kane
c198fd58ee Added more tests for subvector function [skip ci] 2024-04-24 01:31:50 -07:00
Andrew Kane
8c408759dc Added more tests for subvector function [skip ci] 2024-04-24 01:28:25 -07:00
Heikki Linnakangas
14b351bc92 Fix integer overflow in subvector() function (#530)
`end = start + count` can overflow if `start` is very large. That
leads to a segfault later in the function. Add test case for it.
2024-04-24 01:20:16 -07:00
Andrew Kane
ad3f811fa3 Use VARSIZE_ANY instead of itemsize to avoid uninitialized bytes 2024-04-23 23:52:02 -07:00
Andrew Kane
281a74f54e Improved consistency of sparsevec_l1_distance with vector [skip ci] 2024-04-23 21:24:02 -07:00
Andrew Kane
034713c803 Improved consistency with vector [skip ci] 2024-04-23 21:13:00 -07:00
Andrew Kane
ed2e460f00 Improved consistency with vector [skip ci] 2024-04-23 21:11:27 -07:00
Andrew Kane
d136615874 Improved test [skip ci] 2024-04-23 20:42:30 -07:00
Andrew Kane
d70b160e0a Improved test [skip ci] 2024-04-23 20:41:11 -07:00
Andrew Kane
d1affcc667 Improved tests for l2_norm [skip ci] 2024-04-23 20:38:22 -07:00
Andrew Kane
158481ff2a Improved tests for sparsevec distance functions [skip ci] 2024-04-23 20:29:04 -07:00
Andrew Kane
794bbaecc7 Removed padding for sparsevec - #529
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2024-04-23 20:07:24 -07:00
Andrew Kane
8eddcfbd1d Increased max sparsevec dimensions to 1M [skip ci] 2024-04-23 17:47:11 -07:00
Andrew Kane
b609c343b4 Moved type-specific code to separate functions 2024-04-23 16:32:10 -07:00
Andrew Kane
bbfb3f200a DRY code for sorting vector arrays [skip ci] 2024-04-23 15:59:42 -07:00
Andrew Kane
99d367edc0 Improved code [skip ci] 2024-04-23 15:53:12 -07:00
Andrew Kane
991743786a Set length for newCenters and aggCenters [skip ci] 2024-04-23 15:47:04 -07:00
Andrew Kane
60ceaea4f2 Added safety check to NormCenters [skip ci] 2024-04-23 15:43:04 -07:00
Andrew Kane
9cd789fe06 Switched to support function for normalizing centers for k-means 2024-04-23 15:39:58 -07:00
Andrew Kane
0da6213a60 Moved type lookup to support functions - #527 2024-04-23 13:02:47 -07:00
Heikki Linnakangas
d1b83991af Forbid zero values in sparsevec's binary input function (#528)
The text input function simply left out any zero values, but the
binary input function did not. That's problematic because you end up
with an "unnormalized" sparse vector, which behaves in weird ways.  At
least sparsevec_cmp_internal() expects both inputs to not contain
zeros.

The binary send function never produces such zero values, but an
external tool could. Or to test, you can use COPY TO (FORMAT BINARY),
use a hex editor to edit one of the values to be zero, and copy it
back with COPY FROM (FORMAT BINARY).
2024-04-23 09:13:53 -07:00
Andrew Kane
6c247a38d3 Updated readme [skip ci] 2024-04-22 21:56:05 -07:00
Andrew Kane
6639cde19d Updated readme [skip ci] 2024-04-22 21:32:59 -07:00
Andrew Kane
bd409f0c6a Moved HnswGetType call [skip ci] 2024-04-22 19:22:09 -07:00
Andrew Kane
1994fd003a Removed unneeded headers [skip ci] 2024-04-22 19:10:50 -07:00
Andrew Kane
bd62561a19 Added support function for l2_normalize to ivfflat 2024-04-22 19:06:06 -07:00
Andrew Kane
f14c21748b Added support function for l2_normalize [skip ci] 2024-04-22 18:36:47 -07:00
Andrew Kane
2b77005610 Removed type-specific code from ivfscan 2024-04-22 18:12:18 -07:00
Andrew Kane
e884b3aa69 Added opclasses to readme [skip ci] 2024-04-22 16:29:34 -07:00
Andrew Kane
ab71c12a28 Added comments on dispatching [skip ci] 2024-04-22 16:18:57 -07:00
Andrew Kane
1804c63e27 Added more tests for vector distance functions [skip ci] 2024-04-22 15:53:13 -07:00
Andrew Kane
4e6aa2f0c1 Added DISABLE_DISPATCH option [skip ci] 2024-04-22 15:43:07 -07:00
Andrew Kane
40e86251c3 Added VECTOR_TARGET_CLONES to VectorL1Distance [skip ci] 2024-04-22 15:15:57 -07:00
Andrew Kane
0c9ae4b187 Added CPU dispatching for L1 distance for halfvec 2024-04-22 15:02:17 -07:00
Andrew Kane
d83af48e70 Improved tests for halfvec l1_distance [skip ci] 2024-04-22 14:43:54 -07:00
Andrew Kane
b2f7dad8a7 Removed support for L1 distance and Jaccard distance from ivfflat due to non-optimal clustering 2024-04-22 14:11:29 -07:00
Andrew Kane
881fbc15ef Added L1 distance operator to docs [skip ci] 2024-04-22 13:22:28 -07:00
Andrew Kane
f9941c2992 Moved L1 distance to halfutils [skip ci] 2024-04-22 13:19:42 -07:00
Andrew Kane
f9c071a761 Improved tests for L1 distance with halfvec 2024-04-22 13:14:45 -07:00
Andrew Kane
9f4b770db3 Added support for indexing sparsevec with L1 distance [skip ci] 2024-04-22 13:08:12 -07:00
Andrew Kane
70b299a7ff Added support for indexing halfvec with L1 distance [skip ci] 2024-04-22 13:00:59 -07:00
Andrew Kane
d46d014234 Updated test name [skip ci] 2024-04-22 12:57:01 -07:00
Andrew Kane
655adc535a Added bit examples for ivfflat [skip ci] 2024-04-22 12:51:38 -07:00
Andrew Kane
47f0a5e9ac Updated test name [skip ci] 2024-04-22 12:48:22 -07:00
Andrew Kane
af9d50481d Added support for indexing L1 distance 2024-04-22 12:44:03 -07:00
Andrew Kane
6dad8460a6 Updated readme [skip ci] 2024-04-22 10:45:41 -07:00
Andrew Kane
ed4837cc4f Renamed bit files 2024-04-22 10:22:18 -07:00
Andrew Kane
3df5655b30 Removed unneeded headers [skip ci] 2024-04-19 18:09:38 -07:00
Andrew Kane
e4c4ac9648 Added more tests for sparsevec to halfvec cast [skip ci] 2024-04-19 18:05:03 -07:00
Andrew Kane
fb77671d05 Added casts between halfvec and sparsevec 2024-04-19 18:03:07 -07:00
Andrew Kane
fd4fbd238c Updated sparsevec input to support indices in any order [skip ci] 2024-04-19 16:54:19 -07:00
Andrew Kane
4e093f95be Improved consistency of CPU dispatching code 2024-04-18 14:13:12 -07:00
Andrew Kane
fb3c964ac2 Improved performance of bit distance functions - #519
Co-authored-by: Nathan Bossart <nathan@postgresql.org>
Co-authored-by: "Jonathan S. Katz" <jkatz@users.noreply.github.com>
2024-04-18 13:45:00 -07:00
Andrew Kane
0b938f8328 Improved halfvec dispatching code [skip ci] 2024-04-17 20:22:14 -07:00
Andrew Kane
6153e173f3 Updated comments [skip ci] 2024-04-17 18:57:59 -07:00
Andrew Kane
eb48b9eec4 Added comments [skip ci] 2024-04-17 18:53:58 -07:00
Andrew Kane
fb6af03361 Fixed CPU dispatching check for halfvec distance functions 2024-04-17 18:27:27 -07:00
Andrew Kane
e2d8907180 Added todo [skip ci] 2024-04-17 17:25:53 -07:00
Andrew Kane
09ea1b0d5c Improved target_clones logic [skip ci] 2024-04-17 15:05:47 -07:00
Andrew Kane
8d68f88507 Improved target_clones logic [skip ci] 2024-04-17 15:05:19 -07:00
Andrew Kane
301c8083f5 Added check for undefined behavior to CI [skip ci] 2024-04-17 02:03:46 -07:00
Andrew Kane
8b33a359ce Updated VECTOR_ARRAY_SIZE for alignment [skip ci] 2024-04-17 00:55:28 -07:00
Andrew Kane
77ec24641e Fixed flaky test [skip ci] 2024-04-17 00:27:37 -07:00
Andrew Kane
576a37e975 Ensure items are always aligned 2024-04-17 00:17:40 -07:00
Andrew Kane
cf570810eb Fixed alignment for bit in IVFFlat - fixes #520 2024-04-17 00:05:31 -07:00
Andrew Kane
c361f80465 Synced recall test [skip ci] 2024-04-16 17:27:06 -07:00
Andrew Kane
e730fef99d Fixed flaky test [skip ci] 2024-04-16 17:25:50 -07:00
Andrew Kane
4e2b76e627 Skip duplicate center check for bit [skip ci] 2024-04-16 17:20:48 -07:00
Andrew Kane
04af15c9d6 Added support for bit to IVFFlat 2024-04-16 17:12:27 -07:00
Andrew Kane
819b6cf312 Added comments to vector.sql [skip ci] 2024-04-16 15:47:25 -07:00
Andrew Kane
31dfd3d1a6 Added type to assertion message [skip ci] 2024-04-16 13:11:37 -07:00
Andrew Kane
8df8dd01b9 Added halfvec to distance functions TAP test 2024-04-16 13:09:44 -07:00
Andrew Kane
b9b30cc16e Added function name to assertion message [skip ci] 2024-04-16 12:20:22 -07:00
Andrew Kane
e1565af0dc Added TAP test for sparsevec distance functions 2024-04-16 12:11:54 -07:00
Andrew Kane
26d6fbb1d0 Updated comment [skip ci] 2024-04-16 11:45:19 -07:00
Andrew Kane
6c61b5ce6f Updated comment [skip ci] 2024-04-16 11:45:03 -07:00
Andrew Kane
588873e145 Added comment [skip ci] 2024-04-16 11:38:59 -07:00
Andrew Kane
7adb8a6e0e Fixed sparsevec comparison function and added test for consistency 2024-04-16 11:36:45 -07:00
Andrew Kane
5b0eff9dae Updated comment [skip ci] 2024-04-15 15:53:07 -07:00
Andrew Kane
5cf75c0b83 Added comment [skip ci] 2024-04-15 15:50:59 -07:00
Andrew Kane
5215c28923 Moved norm check to separate function 2024-04-15 15:32:08 -07:00
Andrew Kane
342d82be65 Improved l2_normalize test for sparsevec [skip ci] 2024-04-15 14:59:11 -07:00
Andrew Kane
bf3ef4de56 Improved safety check [skip ci] 2024-04-15 14:55:32 -07:00
Andrew Kane
2c82f05503 Improved safety check [skip ci] 2024-04-15 14:51:24 -07:00
Andrew Kane
f655166639 Improved safety check [skip ci] 2024-04-15 14:50:28 -07:00
Andrew Kane
7580e99205 Improved safety check [skip ci] 2024-04-15 14:49:40 -07:00
Andrew Kane
a415420a1c Updated l2_normalize to remove zeros for sparsevec 2024-04-15 14:42:53 -07:00
Andrew Kane
cadfc72b75 Fixed compilation on Windows 2024-04-15 14:14:25 -07:00
Andrew Kane
ceeba6a134 Added todo [skip ci] 2024-04-15 14:11:17 -07:00
Andrew Kane
127ecdd650 Added l2_normalize function for sparsevec 2024-04-15 14:05:18 -07:00
Andrew Kane
10dacfd991 Updated indexes to use l2_normalize functions 2024-04-15 13:56:50 -07:00
Andrew Kane
c282627ce5 Improved cosine distance tests for halfvec [skip ci] 2024-04-15 10:51:52 -07:00
Andrew Kane
312da84536 Added CPU dispatching for vector cosine distance [skip ci] 2024-04-15 10:47:06 -07:00
Andrew Kane
2913c9f0b6 Moved vector L1 distance to separate function [skip ci] 2024-04-15 10:35:16 -07:00
Andrew Kane
fac88d0fd4 Moved vector cosine similarity to separate function [skip ci] 2024-04-15 10:33:23 -07:00
Andrew Kane
ba99255bbb Switched to float for consistency with other distance functions 2024-04-15 10:20:27 -07:00
Andrew Kane
55845bfd5f Added SIMD version of cosine distance 2024-04-15 10:01:05 -07:00
Andrew Kane
2d33e95a73 Added tests for operators [skip ci] 2024-04-15 01:04:16 -07:00
Andrew Kane
d3e5a87df6 Improved sparsevec test [skip ci] 2024-04-15 00:58:47 -07:00
Andrew Kane
f1a46f1025 Improved sparsevec tests [skip ci] 2024-04-15 00:57:53 -07:00
Andrew Kane
df56e9f95f Improved sparsevec tests [skip ci] 2024-04-15 00:55:52 -07:00
Andrew Kane
0f2b7c3afa Improved tests [skip ci] 2024-04-15 00:53:44 -07:00
Andrew Kane
dffb061e89 Improved tests [skip ci] 2024-04-15 00:46:19 -07:00
Andrew Kane
ac29024f10 Improved tests [skip ci] 2024-04-15 00:41:30 -07:00
Andrew Kane
5f739e97e0 Improved tests for l1_distance [skip ci] 2024-04-15 00:37:38 -07:00
Andrew Kane
b12cd121a5 Use fabsf for l1_distance 2024-04-14 23:33:27 -07:00
Andrew Kane
2a2c57db23 Fixed flaky tests [skip ci] 2024-04-14 23:32:54 -07:00
Andrew Kane
bdeb125a97 Simplified concat tests [skip ci] 2024-04-14 23:18:07 -07:00
Andrew Kane
38b223b4bd Added concatenate operator for vectors 2024-04-14 23:12:07 -07:00
Andrew Kane
4f6c4850d9 Added l1_distance function for sparsevec [skip ci] 2024-04-14 22:59:28 -07:00
Andrew Kane
b70fb2b3f4 Added l2_normalize function - closes #220 2024-04-14 20:53:05 -07:00
Andrew Kane
00308491d3 Added CPU dispatching for distance functions on Linux x86-64 - closes #311
Co-authored-by: Arda Aytekin <arda.aytekin@microsoft.com>
2024-04-14 19:30:41 -07:00
Andrew Kane
fe9a9a0d0f Renamed quantize_binary to binary_quantize 2024-04-14 16:57:28 -07:00
Andrew Kane
3e48a3f69d Fixed upgrade script [skip ci] 2024-04-14 16:41:20 -07:00
Andrew Kane
8751404a94 Renamed halfvec_dims to vector_dims [skip ci] 2024-04-14 16:40:16 -07:00
Andrew Kane
8118d65b48 Moved functions [skip ci] 2024-04-14 16:36:27 -07:00
Andrew Kane
3cc227da87 Moved functions [skip ci] 2024-04-14 16:33:46 -07:00
Andrew Kane
44e536b4ae Renamed functions to l2_norm [skip ci] 2024-04-14 16:29:27 -07:00
Andrew Kane
bc199a33cd Added sum for half vectors 2024-04-14 15:16:17 -07:00
Andrew Kane
e146f3cfb6 Added avg for half vectors [skip ci] 2024-04-14 15:11:11 -07:00
Andrew Kane
92d08bb6f5 Fixed regression test list for Windows [skip ci] 2024-04-14 14:14:18 -07:00
Andrew Kane
00d7c8b724 Fixed regression test list for Windows 2024-04-14 14:05:44 -07:00
Andrew Kane
b4b914a580 Fixed sparsevec_cmp_internal 2024-04-14 14:04:03 -07:00
Andrew Kane
fc3ebf4d7d Updated casts [skip ci] 2024-04-14 14:02:29 -07:00
Andrew Kane
0507fc9369 Added support for ordering halfvec and sparsevec columns 2024-04-14 13:58:54 -07:00
Andrew Kane
a5d51ed539 Updated readme [skip ci] 2024-04-14 13:43:15 -07:00
Andrew Kane
88788472ba Added comparison operators for sparsevec 2024-04-14 13:40:37 -07:00
Andrew Kane
c68c2867fd Added more functions for halfvec 2024-04-14 13:12:08 -07:00
Andrew Kane
45cea30943 Updated pkg instructions [skip ci] 2024-04-14 09:24:18 -07:00
Andrew Kane
31a007933c Updated readme [skip ci] 2024-04-14 08:40:27 -07:00
Andrew Kane
0c9ad67a1c Added section on subvector indexing [skip ci] 2024-04-13 18:18:12 -07:00
Andrew Kane
8a4845b52e Fixed CI 2024-04-13 16:09:42 -07:00
Andrew Kane
e14fdba8b3 Improved sparsevec input tests [skip ci] 2024-04-13 16:00:14 -07:00
Andrew Kane
5abf83c415 Improved sparsevec input tests [skip ci] 2024-04-13 15:58:00 -07:00
Andrew Kane
96b30fd25d Improved error message and tests for sparsevec_in 2024-04-13 15:50:40 -07:00
Andrew Kane
1c791480ff Fixed flaky test [skip ci] 2024-04-13 15:49:20 -07:00
Andrew Kane
545ae30057 Improved performance of sparsevec_in 2024-04-13 15:42:16 -07:00
Andrew Kane
20fb2e0797 Improved sparsevec_in [skip ci] 2024-04-13 15:13:08 -07:00
Andrew Kane
89629abc08 Removed unneeded check [skip ci] 2024-04-13 15:06:17 -07:00
Andrew Kane
db112862a5 Improved performance of halfvec_in 2024-04-13 15:04:52 -07:00
Andrew Kane
bb84d69e57 Removed todo [skip ci] 2024-04-13 15:02:14 -07:00
Andrew Kane
7ea1590ea3 Removed todo [skip ci] 2024-04-13 15:01:23 -07:00
Andrew Kane
d98eb0a28d Fixed flaky test [skip ci] 2024-04-13 15:00:58 -07:00
Andrew Kane
72eee91d00 Fixed test 2024-04-13 14:55:14 -07:00
Andrew Kane
f5e6e58359 Improved performance of vector_in 2024-04-13 14:49:00 -07:00
Andrew Kane
8f93d02c71 Updated comments [skip ci] 2024-04-13 14:06:10 -07:00
Andrew Kane
c5c82bafda Updated invalid input syntax messages to be consistent [skip ci] 2024-04-13 11:32:47 -07:00
Andrew Kane
f627e69c5f Fixed test [skip ci] 2024-04-13 11:21:25 -07:00
Andrew Kane
23944302fe Improved input functions [skip ci] 2024-04-13 11:09:59 -07:00
Andrew Kane
9957ba6817 Improved input tests [skip ci] 2024-04-13 10:56:34 -07:00
Andrew Kane
aed463dbad Fixed headers 2024-04-12 11:58:27 -07:00
Andrew Kane
f64abe3aae Fixed performance of halfvec 2024-04-12 11:50:34 -07:00
Andrew Kane
06d90fdc76 Updated comments [skip ci] 2024-04-11 22:35:11 -07:00
Andrew Kane
cc4b01bd49 Moved code [skip ci] 2024-04-11 22:25:53 -07:00
Andrew Kane
3621a84ef8 Moved code to separate function [skip ci] 2024-04-11 22:23:16 -07:00
Andrew Kane
b9d5269547 Improved IVFFlat build recall test 2024-04-11 21:47:49 -07:00
Andrew Kane
fbc96bb488 Added comments [skip ci] 2024-04-11 21:38:09 -07:00
Andrew Kane
5510ae5b8c Better account for equal distances [skip ci] 2024-04-11 21:34:46 -07:00
Andrew Kane
70eee06e83 Fixed CI 2024-04-11 21:17:23 -07:00
Andrew Kane
f2bffff460 Improved code for item size [skip ci] 2024-04-11 21:14:48 -07:00
Andrew Kane
af7d9b74a9 Fixed max dimensions for halfvec for IVFFlat [skip ci] 2024-04-11 21:07:45 -07:00
Andrew Kane
f1a71524f0 Added comment [skip ci] 2024-04-11 20:35:41 -07:00
Andrew Kane
7710cc8c28 Added comments [skip ci] 2024-04-11 20:34:15 -07:00
Andrew Kane
fea2eb262e Moved type check out of loop [skip ci] 2024-04-11 20:31:27 -07:00
Andrew Kane
1bc6f954f4 Fixed flaky test [skip ci] 2024-04-11 20:15:14 -07:00
Andrew Kane
6fd6b0bd5f Fixed CI 2024-04-11 20:09:10 -07:00
Andrew Kane
546006b7ca Added comment [skip ci] 2024-04-11 20:03:12 -07:00
Andrew Kane
cca0edf458 Improved k-means types [skip ci] 2024-04-11 20:00:07 -07:00
Andrew Kane
8d9400bae3 Added support for halfvec to IVFFlat 2024-04-11 19:56:39 -07:00
Andrew Kane
a4531ca51f Fixed halfvec_cmp_internal function [skip ci] 2024-04-11 19:43:25 -07:00
Andrew Kane
94ee6b13c3 Show memory from outer context [skip ci] 2024-04-11 18:38:35 -07:00
Andrew Kane
e6a591275a Added halfvec_cmp_internal function [skip ci] 2024-04-11 18:33:54 -07:00
Andrew Kane
7fddd296ee Improved k-means code [skip ci] 2024-04-11 17:16:54 -07:00
Andrew Kane
c581db9f98 Improved k-means code [skip ci] 2024-04-11 17:15:20 -07:00
Andrew Kane
626bc053e5 Improved k-means code [skip ci] 2024-04-11 16:54:43 -07:00
Andrew Kane
66a29dbdf3 Switched to Datum for ApplyNorm [skip ci] 2024-04-11 16:50:21 -07:00
Andrew Kane
1c26da6ef5 Mark type-specific code [skip ci] 2024-04-11 16:44:10 -07:00
Andrew Kane
000cc13c29 Switched to datumIsEqual for duplicate check in IVFFlat [skip ci] 2024-04-11 16:37:34 -07:00
Andrew Kane
bbfe1e8b61 Removed more vector-specific code from IVFFlat [skip ci] 2024-04-11 14:05:41 -07:00
Andrew Kane
7e8be16e37 Improved code [skip ci] 2024-04-11 14:01:21 -07:00
Andrew Kane
17c2f9c0b6 Removed more vector-specific code from IVFFlat 2024-04-11 13:59:20 -07:00
Andrew Kane
bd52ed29e0 Added halfvec_spherical_distance function [skip ci] 2024-04-11 13:52:59 -07:00
Andrew Kane
245bac5e8e Removed vector-specific code from IVFFlat [skip ci] 2024-04-11 13:50:23 -07:00
Andrew Kane
d84fc303ee Removed vector-specific code from IVFFlat [skip ci] 2024-04-11 13:49:28 -07:00
Andrew Kane
4ff36af67e Added itemsize to VectorArray [skip ci] 2024-04-11 13:47:36 -07:00
Andrew Kane
5834b58c5a Moved VECTOR_SIZE out of IVFFLAT_LIST_SIZE [skip ci] 2024-04-11 09:43:35 -07:00
Andrew Kane
381216a956 Improved variable scoping 2024-04-11 09:41:47 -07:00
Andrew Kane
c3c6af8a84 Improved variable scoping [skip ci] 2024-04-11 09:38:54 -07:00
Andrew Kane
d45f561d75 Use memory context for k-means [skip ci] 2024-04-11 09:34:05 -07:00
Andrew Kane
e1647473c9 Updated IvfflatGetType [skip ci] 2024-04-11 09:25:07 -07:00
Andrew Kane
e8bd7cd2f5 Updated test to be independent of order [skip ci] 2024-04-11 09:22:03 -07:00
Andrew Kane
bed40ec0b5 Moved code to get scan value to separate function for IVFFlat [skip ci] 2024-04-11 09:20:10 -07:00
Andrew Kane
d64295dfd7 Improved test SQL [skip ci] 2024-04-10 16:38:07 -07:00
Andrew Kane
8178a902ce Fixed flaky test [skip ci] 2024-04-10 16:34:56 -07:00
Andrew Kane
f9f53b64e8 Added tests for HNSW vacuum recall for bit, halfvec, and sparsevec 2024-04-10 16:29:48 -07:00
Andrew Kane
fc83cd8d12 Fixed flaky tests [skip ci] 2024-04-10 14:06:50 -07:00
Andrew Kane
1e41ed6f15 Added more cast tests [skip ci] 2024-04-10 14:05:51 -07:00
Andrew Kane
e6ca831f3d Store very small values as zero for halfvec 2024-04-10 13:59:51 -07:00
Andrew Kane
a824af42fb Improved error message for out of range values for halfvec [skip ci] 2024-04-10 13:47:45 -07:00
Andrew Kane
8a29bf4619 Added more cast tests [skip ci] 2024-04-10 13:42:30 -07:00
Andrew Kane
33369e0744 Added tests for HNSW duplicates for bit, halfvec, and sparsevec 2024-04-10 13:23:20 -07:00
Andrew Kane
34b09cc062 Added test for HNSW insert recall with sparsevec 2024-04-10 13:10:37 -07:00
Andrew Kane
d8f3e18db6 Added test for HNSW insert recall with halfvec [skip ci] 2024-04-10 13:06:56 -07:00
Andrew Kane
e6e7d7c1bc Added test for HNSW insert recall with bit [skip ci] 2024-04-10 13:03:48 -07:00
Andrew Kane
bf355792b2 Added tests for sparsevec_norm [skip ci] 2024-04-10 11:37:11 -07:00
Andrew Kane
12f4a34708 Added tests for halfvec_norm [skip ci] 2024-04-09 18:00:42 -07:00
Andrew Kane
f6becf01aa Improved input tests [skip ci] 2024-04-09 17:34:11 -07:00
Andrew Kane
dd5b856f68 Improved cast tests [skip ci] 2024-04-09 17:10:52 -07:00
Andrew Kane
9c96164f2c Improved cast tests [skip ci] 2024-04-09 17:05:42 -07:00
Andrew Kane
b583803b2c Improved cast tests [skip ci] 2024-04-09 17:02:21 -07:00
Andrew Kane
a04bf7fce2 Moved cast test [skip ci] 2024-04-09 16:48:45 -07:00
Andrew Kane
62b411f94c Improved sparsevec input test [skip ci] 2024-04-09 16:44:34 -07:00
Andrew Kane
82a17b81f5 Improved sparsevec input test [skip ci] 2024-04-09 16:41:48 -07:00
Andrew Kane
3b2ca7df7a Added sparsevec to copy test [skip ci] 2024-04-09 16:35:06 -07:00
Andrew Kane
21d125abed Improved tests [skip ci] 2024-04-09 16:31:52 -07:00
Andrew Kane
f42ccd451d Improved sparsevec input tests [skip ci] 2024-04-09 16:29:23 -07:00
Andrew Kane
85345e3f8c Removed todo [skip ci] 2024-04-09 14:41:49 -07:00
Andrew Kane
05ce20990c Added test for bit dimensions [skip ci] 2024-04-09 14:31:33 -07:00
Andrew Kane
f3477cf28d DRY vector_spherical_distance [skip ci] 2024-04-08 16:45:08 -07:00
Andrew Kane
434f3f5e88 DRY vector distance functions 2024-04-08 16:41:50 -07:00
Andrew Kane
bd6fdb73eb Improved naming [skip ci] 2024-04-08 16:35:57 -07:00
Andrew Kane
ab382a2053 Improved code [skip ci] 2024-04-08 15:32:16 -07:00
Andrew Kane
191c8e1cca Use consistent naming [skip ci] 2024-04-08 14:56:59 -07:00
Andrew Kane
3eba34e5e3 Improved code for feature detection 2024-04-08 14:40:12 -07:00
Andrew Kane
862f17c1de Removed unneeded initialization [skip ci] 2024-04-08 14:15:34 -07:00
Andrew Kane
21bcff6722 Added CPU dispatching for halfvec distance functions - #311
Co-authored-by: Arda Aytekin <arda.aytekin@microsoft.com>
2024-04-08 13:50:18 -07:00
Andrew Kane
60b4bb2ad1 Moved halfvec distance functions to separate file [skip ci] 2024-04-08 10:00:34 -07:00
Andrew Kane
c27363fbf7 Improved halfvec tests 2024-04-08 00:31:44 -07:00
Andrew Kane
06309f5d07 Updated comments [skip ci] 2024-04-07 21:55:44 -07:00
Andrew Kane
39b8bd1816 Switched to storeu [skip ci] 2024-04-07 21:04:59 -07:00
Andrew Kane
925aa4e048 Added SIMD version of L2 distance 2024-04-07 20:22:19 -07:00
Andrew Kane
9ed39cee67 Added SIMD version of inner product 2024-04-07 20:10:54 -07:00
Andrew Kane
494087222f Removed note [skip ci] 2024-04-07 20:02:17 -07:00
Andrew Kane
4c0b10451f Fixed flaky test [skip ci] 2024-04-07 19:11:16 -07:00
Andrew Kane
3bd67fef54 DRY halfvec distance functions 2024-04-07 19:03:20 -07:00
Andrew Kane
d861a0304e Removed extra space [skip ci] 2024-04-07 19:02:30 -07:00
Andrew Kane
d8719d59a3 Improved halfvec performance with F16C support 2024-04-07 18:53:50 -07:00
Andrew Kane
98d4b1a364 Updated docs on halfvec performance [skip ci] 2024-04-07 16:16:39 -07:00
Andrew Kane
33daf87fcb Improved performance of HalfToFloat4 2024-04-07 13:01:58 -07:00
Andrew Kane
faa33c32d9 Added link to halfvec performance section [skip ci] 2024-04-07 10:55:46 -07:00
Andrew Kane
0df30c12a7 Added section on halfvec performance [skip ci] 2024-04-07 10:54:28 -07:00
Andrew Kane
8d7e0e693c Fixed vector to sparsevec conversion 2024-04-07 10:30:54 -07:00
Andrew Kane
457adcbbdb Added TAP test for sparsevec 2024-04-07 10:20:19 -07:00
Andrew Kane
bada41484f Improved bit function tests [skip ci] 2024-04-06 18:21:37 -07:00
Andrew Kane
60104264d5 Improved error message [skip ci] 2024-04-06 15:52:26 -07:00
Andrew Kane
53c4faaf72 Updated readme [skip ci] 2024-04-06 14:52:26 -07:00
Andrew Kane
5fa3da5400 Fixed flaky test [skip ci] 2024-04-06 14:21:10 -07:00
Andrew Kane
4450029bdc Changed indices to start at 1 for sparse vectors to match SQL 2024-04-06 14:02:07 -07:00
Andrew Kane
aec853dc68 Added memory usage for HNSW index scans [skip ci] 2024-04-04 14:37:39 -07:00
Andrew Kane
2d24d65f1c Added sparse vectors section [skip ci] 2024-04-04 00:00:54 -07:00
Andrew Kane
abd9963e66 Added half vectors section [skip ci] 2024-04-03 23:55:08 -07:00
Andrew Kane
7e5df3c9fe Updated binary vectors section [skip ci] 2024-04-03 23:36:43 -07:00
Andrew Kane
61e803a4dc Updated readme [skip ci] 2024-04-03 23:26:25 -07:00
Andrew Kane
2e5cbf611a Simplified bit test 2024-04-03 23:26:03 -07:00
Andrew Kane
d28b2cfccf Added binary vectors section [skip ci] 2024-04-03 23:23:52 -07:00
Andrew Kane
6c4a115ebf Updated readme [skip ci] 2024-04-03 23:17:27 -07:00
Andrew Kane
c421dc6483 Added binary quantization section [skip ci] 2024-04-03 23:15:28 -07:00
Andrew Kane
8961de6179 Improved halfvec input check [skip ci] 2024-04-03 22:23:23 -07:00
Andrew Kane
9f61dcff5d Improved error messages for halfvec input [skip ci] 2024-04-03 22:20:13 -07:00
Andrew Kane
7667abe9a0 Improved test [skip ci] 2024-04-03 22:08:48 -07:00
Andrew Kane
3219a30290 Raise error for varbit 2024-04-03 21:30:43 -07:00
Andrew Kane
483e42b9c4 Added tests for varbit [skip ci] 2024-04-03 21:15:57 -07:00
Andrew Kane
41b4bf79ba Updated readme [skip ci] 2024-04-03 21:08:45 -07:00
Andrew Kane
fc1aeee62c Added SPARSEVEC_MAX_NNZ 2024-04-03 21:05:35 -07:00
Andrew Kane
35d0fe88b9 Added IvfflatType [skip ci] 2024-04-03 16:40:27 -07:00
Andrew Kane
aaa2d644ce Added quantize_binary and subvector functions for halfvec 2024-04-03 14:53:03 -07:00
Andrew Kane
253acbccf4 Updated readme [skip ci] 2024-04-03 11:05:55 -07:00
Andrew Kane
060d299e4b Improved error message for out of range elements 2024-04-03 10:12:17 -07:00
Andrew Kane
d7354a86a8 Updated readme [skip ci] 2024-04-02 14:45:25 -07:00
Andrew Kane
daba71694b Updated readme [skip ci] 2024-04-02 14:39:14 -07:00
Andrew Kane
506dd2b44a Updated changelog [skip ci] 2024-04-02 14:33:57 -07:00
Andrew Kane
bcf41f5f66 Fixed flaky test [skip ci] 2024-04-02 14:31:05 -07:00
Andrew Kane
abac7a3f77 Added sparsevec type 2024-04-02 14:25:09 -07:00
Andrew Kane
32a502c838 Added halfvec type 2024-04-02 13:55:45 -07:00
Andrew Kane
1134e52762 Renamed regression tests [skip ci] 2024-04-02 13:33:44 -07:00
Andrew Kane
3ef632e042 Added Mac arm64 to CI [skip ci] 2024-04-02 12:48:19 -07:00
Andrew Kane
e2a527ffda Fixed flaky test [skip ci] 2024-04-02 12:23:48 -07:00
Andrew Kane
835f010257 Fixed missing header for Postgres 12 2024-04-02 12:17:41 -07:00
Andrew Kane
d6044dd423 Added subvector function 2024-04-02 12:13:04 -07:00
Andrew Kane
c75634a03c Fixed type check [skip ci] 2024-04-01 22:31:02 -07:00
Andrew Kane
ab7b2ed39e Updated comparison operators to support vectors with different dimensions - #451 2024-04-01 22:12:06 -07:00
Andrew Kane
499b6bc2c9 Fixed regression test list for Windows [skip ci] 2024-04-01 21:32:28 -07:00
Andrew Kane
741c6a8a7b Renamed tests [skip ci] 2024-04-01 20:51:21 -07:00
Andrew Kane
1c82bdd932 Updated comments [skip ci] 2024-04-01 20:33:12 -07:00
Andrew Kane
94a444f029 Added support for bit vectors to HNSW 2024-04-01 20:30:55 -07:00
Andrew Kane
7ee9074a9c Updated comment [skip ci] 2024-03-31 18:33:26 -07:00
Andrew Kane
2f2f3631a8 Improved vector_out code 2024-03-31 09:55:07 -07:00
Andrew Kane
4b22851bbd Added more vector input tests [skip ci] 2024-03-30 10:17:55 -07:00
Andrew Kane
3acdbf99e8 Added casting to distance functions in tests [skip ci] 2024-03-30 09:05:15 -07:00
Andrew Kane
11ea3d8483 Updated SQL comments [skip ci] 2024-03-30 08:29:01 -07:00
Andrew Kane
2c48e3edc2 Mark type-specific code 2024-03-29 14:01:48 -07:00
Andrew Kane
7d63bb4b98 Fixed flaky test [skip ci] 2024-03-29 11:00:16 -07:00
Andrew Kane
de410a2915 Use variable for max dimemsions [skip ci] 2024-03-29 10:57:16 -07:00
Andrew Kane
64aa99aa31 Added todo [skip ci] 2024-03-29 10:56:24 -07:00
Andrew Kane
997fa167da Removed vector-specific code from HNSW 2024-03-29 10:50:06 -07:00
Andrew Kane
67eec4edbf Improved tuning section [skip ci] 2024-03-27 22:04:28 -07:00
Andrew Kane
396090d8e0 Improved code [skip ci] 2024-03-27 21:38:22 -07:00
Andrew Kane
ba18942fcf Removed normvec from IVFFlat for simplicity (no difference in performance) 2024-03-27 16:41:17 -07:00
Andrew Kane
8e59455c3c Removed normvec for simplicity (no difference in performance) 2024-03-27 16:33:11 -07:00
Andrew Kane
bd50e3067d Updated readme [skip ci] 2024-03-27 14:14:49 -07:00
Andrew Kane
af9d4ad659 Updated readme [skip ci] 2024-03-27 14:12:08 -07:00
Andrew Kane
08abb63cbe Added notes about NULL vectors [skip ci] 2024-03-27 11:50:37 -07:00
Andrew Kane
06b8556a49 Revert "Updated readme [skip ci]"
This reverts commit 3f674c9994.
2024-03-25 23:33:46 -07:00
Andrew Kane
3f674c9994 Updated readme [skip ci] 2024-03-25 23:33:17 -07:00
Andrew Kane
31e41b3ba9 Added FAQ about binary vectors [skip ci] 2024-03-24 11:07:34 -07:00
Andrew Kane
903a925662 Improved type modifier tests 2024-03-21 17:31:08 -07:00
Andrew Kane
96ff19be44 Version bump to 0.6.2 [skip ci] 2024-03-18 10:21:04 -07:00
Andrew Kane
6c969bebad Updated changelog [skip ci] 2024-03-18 10:11:45 -07:00
Andrew Kane
b64a1482d9 Moved example [skip ci] 2024-03-16 15:20:26 -07:00
Andrew Kane
a5f2d70bc2 Use temp directory for installation instructions on Windows [skip ci] 2024-03-16 12:02:45 -07:00
Andrew Kane
f3fcb5e005 Moved installation notes for Windows [skip ci] 2024-03-16 11:47:18 -07:00
Andrew Kane
3a6e0afb9c Added installation notes for Windows [skip ci] 2024-03-16 11:35:55 -07:00
Andrew Kane
183d50bdbd Added note about creating indexes concurrently [skip ci] 2024-03-16 10:45:09 -07:00
Andrew Kane
bd776fee68 Updated readme [skip ci] 2024-03-16 10:44:45 -07:00
Andrew Kane
d30b113e4b Updated readme [skip ci] 2024-03-15 21:54:58 -07:00
Andrew Kane
fd3200f718 Updated readme [skip ci] 2024-03-15 21:47:57 -07:00
Andrew Kane
02c815d876 Added docs on tuning, monitoring, and scaling [skip ci] 2024-03-15 19:00:49 -07:00
Andrew Kane
4b2a7cc49d Improved performance section [skip ci] 2024-03-15 17:54:14 -07:00
Andrew Kane
da0ff998e9 Updated readme [skip ci] 2024-03-15 14:23:56 -07:00
Andrew Kane
cb36e24289 Improved portability section [skip ci] 2024-03-15 14:23:04 -07:00
Andrew Kane
b1d0d4c7a3 Improved troubleshooting docs [skip ci] 2024-03-15 14:01:24 -07:00
Andrew Kane
1dc6514b66 Updated comment [skip ci] 2024-03-15 12:38:14 -07:00
Andrew Kane
6c53f7ca02 Updated comment [skip ci] 2024-03-15 12:37:47 -07:00
Heikki Linnakangas
0d35a14198 Fix compiler warnings in strict C99 mode (#487)
Redefining a typedef is a C11 feature:

    In file included from src/hnsw.c:10:
    src/hnsw.h:147:5: warning: redefinition of typedef 'HnswElementData' is a C11 feature [-Wtypedef-redefinition]
    }                       HnswElementData;
                            ^
    src/hnsw.h:118:32: note: previous definition is here
    typedef struct HnswElementData HnswElementData;
                                   ^
    src/hnsw.h:163:5: warning: redefinition of typedef 'HnswNeighborArray' is a C11 feature [-Wtypedef-redefinition]
    }                       HnswNeighborArray;
                            ^
    src/hnsw.h:119:34: note: previous definition is here
    typedef struct HnswNeighborArray HnswNeighborArray;
                                     ^
    2 warnings generated.

I got these warnings when I built PostgreSQL with "CC=clang
CFLAGS=-std=gnu99"; other similar options would surely produce the
warnings too.
2024-03-12 02:02:33 -07:00
Andrew Kane
3ea2ce89be Reduced lock contention with parallel HNSW index builds 2024-03-11 20:16:55 -07:00
Andrew Kane
62350b1589 Added note about IVFFlat results [skip ci] 2024-03-06 00:29:55 -08:00
Andrew Kane
dd57309281 Added section about HNSW results - #480 [skip ci] 2024-03-06 00:27:50 -08:00
Andrew Kane
c6ddf62a29 Version bump to 0.6.1 [skip ci] 2024-03-04 10:27:59 -08:00
Andrew Kane
801be04d8b Updated CI [skip ci] 2024-03-02 17:06:11 -08:00
Andrew Kane
587e9ba97c Added link to bulk loading example [skip ci] 2024-02-29 21:25:11 -08:00
Andrew Kane
d57047a935 Moved COPY example and added FORMAT [skip ci] 2024-02-29 20:35:01 -08:00
oneturkmen
f1db1f17e3 Update README.md (#472) 2024-02-29 20:27:53 -08:00
Andrew Kane
2f48c0fac4 Updated changelog [skip ci] 2024-02-29 18:10:19 -08:00
Andrew Kane
84a8aa8176 Added note about HNSW build time [skip ci] 2024-02-29 16:25:58 -08:00
Andrew Kane
f64ebbef50 Added OPTFLAGS to readme [skip ci] 2024-02-29 16:15:22 -08:00
Andrew Kane
ac8156509b Updated vector operators for <= and >= 2024-02-29 15:43:29 -08:00
Andrew Kane
82bf69b479 Fixed vector subtraction being marked as commutative - fixes #475 2024-02-29 14:36:18 -08:00
Andrew Kane
4be2f57916 Updated license year [skip ci] 2024-02-29 13:44:58 -08:00
Andrew Kane
91e3d2905f Fixed sort function for Postgres 12 2024-02-28 16:26:41 -08:00
Andrew Kane
fe2406564f Replaced pairing heap with array in SelectNeighbors - closes #447
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2024-02-28 15:47:26 -08:00
Andrew Kane
fa52511eaa Fixed closer caching for Postgres 12 2024-02-28 15:44:38 -08:00
Andrew Kane
447ef4d27a Specify Postgres version for Valgrind [skip ci] 2024-02-28 14:16:48 -08:00
Andrew Kane
b36cd22ccc Enable assertions on CI 2024-02-28 14:15:34 -08:00
Andrew Kane
b447ae4989 Avoid base address for relptr for Postgres < 14.5 2024-02-28 14:10:14 -08:00
Andrew Kane
efed873a3e Revert "Replaced pairing heap with array in SelectNeighbors - closes #447"
This reverts commit 14b278dec9.
2024-02-28 11:33:14 -08:00
Andrew Kane
14b278dec9 Replaced pairing heap with array in SelectNeighbors - closes #447
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2024-02-28 11:25:12 -08:00
Andrew Kane
133a728e48 Updated changelog [skip ci] 2024-02-20 16:38:05 -08:00
Andrew Kane
ca10cbaa7d Revert "Remove offsethash"
This reverts commit 1cbd204f52.
2024-02-20 16:07:32 -08:00
Andrew Kane
eb29019a14 Revert "Eliminate a few HnswPtrAccess invocations"
This reverts commit 334c386a45.
2024-02-20 16:07:21 -08:00
Heikki Linnakangas
334c386a45 Eliminate a few HnswPtrAccess invocations
HnswPtrAccess() is pretty cheap, but it stills seems worthwhile to
avoid repeated calls in the hot paths when it can be easily avoided.
2024-02-19 14:13:18 +02:00
Heikki Linnakangas
1cbd204f52 Remove offsethash
The original motivation was to eliminate the superfluous HnswPtrAccess
call from AddToVisited. The caller has to call HnswPtrAccess() anyway,
so it makes sense to pass the HnswElement rather than HnswElementPtr
to AddToVisited(). But then I realized that we can use the
pointer-variant even with shared memory, because the visited-hash is
backend-private, and the addresses where the elements are mapped to in
shared memory are stable within the backend.
2024-02-19 14:12:26 +02:00
Andrew Kane
5ba62fca84 Fixed crash with shared_preload_libraries - fixes #460 2024-02-14 17:13:30 -08:00
Andrew Kane
22cb2a3fe7 Simplified Docker tasks [skip ci] 2024-02-07 12:03:33 -08:00
Andrew Kane
72b144906a Added Valgrind to CI 2024-02-07 09:43:01 -08:00
Andrew Kane
a618c1bc78 Updated port name [skip ci] 2024-02-06 12:43:20 -08:00
Andrew Kane
f43cd0ed98 Improved type [skip ci] 2024-02-05 19:38:52 -08:00
Andrew Kane
51df640961 Added instructions for pkg [skip ci] 2024-02-05 17:01:36 -08:00
Andrew Kane
2716a223a6 Fixed error with ANALYZE and vectors with different dimensions - fixes #451 2024-02-02 10:47:48 -08:00
Andrew Kane
3697043898 Added note about vacuuming - closes #450 [skip ci] 2024-01-31 14:35:27 -08:00
Andrew Kane
c22740962c Added note for Docker [skip ci] 2024-01-29 15:33:29 -08:00
Andrew Kane
a55ecf3281 Updated changelog [skip ci] 2024-01-29 11:20:33 -08:00
Andrew Kane
fecdd5794e Updated readme [skip ci] 2024-01-29 10:57:54 -08:00
Andrew Kane
281d4fcf60 Version bump to 0.6.0 [skip ci] 2024-01-29 10:54:44 -08:00
Andrew Kane
5b43aaad5a Removed unneeded item ids 2024-01-28 23:14:52 -08:00
Andrew Kane
797ce8034c Ran pgindent [skip ci] 2024-01-28 23:03:48 -08:00
Andrew Kane
cad9e22d9a Updated variable name to be consistent with CreateGraphPages [skip ci] 2024-01-28 23:02:13 -08:00
Andrew Kane
a7d43904f7 Zero memory for each element 2024-01-28 23:00:39 -08:00
Andrew Kane
ded649891b DRY HNSW tuple alloc size [skip ci] 2024-01-28 22:58:38 -08:00
Heikki Linnakangas
2d092016fc Remove unnecessary PageIndexTupleOverwrite calls that caused UB (#438)
These places called PageIndexTupleOverwrite(), with the new tuple
pointing directly to the original page. The PageIndexTupleOverwrite()
call is unnecessary in these cases, as we have already modified the
tuple on the page directly. Moreover, PageIndexTupleOverWrite() will
call memcpy with same src and dst arguments, which is undefined
behavior.

It's OK to modify the pages on disk directly, and we don't need
critical sections, because we either use the generic xlog functions
which create a temporary copy of the page, or we are building a new
index so if we crash the whole index is invisible and will be dropped
anyway.
2024-01-28 22:52:56 -08:00
Andrew Kane
86b31fdf96 Revert "Update neighbor tuples in-place for HNSW index build"
This reverts commit 270dd8189a.
2024-01-28 22:18:22 -08:00
Andrew Kane
5023269f0d Updated changelog [skip ci] 2024-01-28 21:42:30 -08:00
Andrew Kane
642ee1f423 Improved function names 2024-01-28 21:00:12 -08:00
Andrew Kane
270dd8189a Update neighbor tuples in-place for HNSW index build 2024-01-28 20:53:56 -08:00
Andrew Kane
ba2776850b Fixed Valgrind check for HNSW in-memory, parallel index builds - closes #441 2024-01-28 16:19:32 -08:00
Andrew Kane
0cc883b944 Removed checking neighbors for cached distance 2024-01-28 02:11:24 -08:00
Andrew Kane
e8e69278eb Fixed test name [skip ci] 2024-01-27 21:18:49 -08:00
Andrew Kane
a4893d9d5f Updated Postgres for Mac TAP tests on CI [skip ci] 2024-01-27 20:28:03 -08:00
Andrew Kane
10416b841f Fixed uninitialized memory in scan->xs_recheck [skip ci] 2024-01-27 19:54:16 -08:00
Andrew Kane
d0f13d4e7f Fixed possibly uninitialized memory in lists [skip ci] 2024-01-27 19:51:34 -08:00
Andrew Kane
705e71015f Fixed uninitialized entry point level - fixes #439 and closes #440 2024-01-27 19:49:40 -08:00
Heikki Linnakangas
121f53b8ff Remove unused heapRel arguments (#443) 2024-01-26 12:45:10 -08:00
Andrew Kane
8765e79ec2 Added note about max_parallel_maintenance_workers for HNSW [skip ci] 2024-01-25 13:32:35 -08:00
Andrew Kane
7fff6cd138 Moved Windows instructions [skip ci] 2024-01-25 02:11:21 -08:00
Heikki Linnakangas
571697fee7 Remove unnecessary UpdateProgress() wrappers (#433)
Now that we require PostgreSQL v12, we can use
pgstat_progress_update_param directly.
2024-01-25 00:07:57 -08:00
Andrew Kane
f7eda7bd20 DRY neighbor array size [skip ci] 2024-01-24 17:54:33 -08:00
Andrew Kane
2260e13315 Condensed code [skip ci] 2024-01-24 16:20:00 -08:00
Andrew Kane
90e0a14bda Moved allocating neighbor array to separate function [skip ci] 2024-01-24 16:17:34 -08:00
Andrew Kane
c816b5d0d1 Added note about --shm-size [skip ci] 2024-01-24 14:49:38 -08:00
Andrew Kane
b7b11cd8d5 Updated changelog [skip ci] 2024-01-24 14:31:41 -08:00
Andrew Kane
54c560c5cb Removed previous upgrade notes [skip ci] 2024-01-24 14:25:58 -08:00
Andrew Kane
8a6c52f649 Moved Docker image to pgvector org and added tags for each supported version of Postgres [skip ci] 2024-01-24 14:18:44 -08:00
Heikki Linnakangas
c8be3a369b Include generic_xlog.h directly in the .c files where it's needed
There are no references to anything that's in generic_xlog.h in the
header files.
2024-01-23 13:04:03 +02:00
Heikki Linnakangas
e5d1a6bdbb Include reloptions.h directly in the .c files where it's needed
There are no references to anything that's in reloptions.h in the
header files. They need to include genam.h instead, which defines
IndexScanDesc.
2024-01-23 13:02:24 +02:00
Heikki Linnakangas
f31d708c2b Add direct include to pairingheap.h in headers
ivfflat.h and hnsw.h have references to pairingheap_node, so they need
to include lib/pairingheap.h. It happened to work, because
lib/pairingheap.h was being included indirectly through
nodes/execnodes.h, but let's be explicit.

Remove the include from hnswbuild.c, because there are no calls to
pairingheap functions in that file. Instead, add the includes to
hnswutils.c and ivfscan.c, which do have such calls. They are not
strictly necessary again because of the indirect include from hnsw.h
and ivfflat.h, but let's be explicit while we're messing with this.
2024-01-23 12:53:22 +02:00
Heikki Linnakangas
a1b1c99ff7 Remove unused #include
pg_list.h has not been used in hnswbuild.c since commit cb4c770df2.
2024-01-23 12:53:13 +02:00
Andrew Kane
3ace98add6 Changed storage for vector from extended to external 2024-01-23 00:00:12 -08:00
Andrew Kane
083008c21e Added validation for GUC parameters 2024-01-22 23:55:30 -08:00
Andrew Kane
a1e526ef82 Dropped support for Postgres 11 2024-01-22 23:52:54 -08:00
Andrew Kane
8ffb3718a4 Leave more space for other shared memory 2024-01-22 23:31:55 -08:00
Andrew Kane
2d0f162bd7 Added support for in-memory parallel index builds for HNSW
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2024-01-22 23:19:10 -08:00
Heikki Linnakangas
4c6928bd3c Remove HnswSpool
It was just used to pass heap/index relations to
HnswParallelScanAndInsert. I think it was copied from nbtsort.c, which
is more complicated. I don't think we need a struct like this.

(That said, I actually think that we should have a state object that
would hold fields like 'heap', 'index', 'procinfo', 'collation'
etc. Passing that object around would simplify the signatures of many
functions. But that's a different story).
2024-01-22 23:11:25 -08:00
Heikki Linnakangas
6fd05dd6f6 Remove unused 'scantuplesortstates' field 2024-01-22 23:08:20 -08:00
Andrew Kane
70106f5413 Use assert checking for scan-build [skip ci] 2024-01-22 23:05:49 -08:00
Andrew Kane
44b90be452 Made variable name consistent across functions [skip ci] 2024-01-22 19:02:33 -08:00
Andrew Kane
31572a7b28 Removed unused parameter [skip ci] 2024-01-22 19:00:45 -08:00
Andrew Kane
2427290ea9 Pass hash by reference 2024-01-22 18:34:40 -08:00
Andrew Kane
ca71ef7a51 Added analyze to filtering tests 2024-01-21 18:08:16 -08:00
Andrew Kane
8bd01ff006 Added filtering tests for like [skip ci] 2024-01-21 18:01:42 -08:00
Andrew Kane
cdb1c9a6d3 Fixed test logic [skip ci] 2024-01-21 16:07:44 -08:00
Andrew Kane
bf34ceef7c Added more filtering tests 2024-01-21 16:03:22 -08:00
Andrew Kane
61b1566ea2 Updated CI to Debian 12 [skip ci] 2024-01-21 12:40:55 -08:00
Andrew Kane
91acc3c178 Added test for filtering with IVFFlat 2024-01-20 21:38:40 -08:00
Andrew Kane
885dd5b665 Fixed test warning [skip ci] 2024-01-20 21:10:24 -08:00
Andrew Kane
2a7b38bf1f Added test for filtering with few rows removed 2024-01-20 21:09:14 -08:00
Andrew Kane
4bd4a0996b Improved filtering test [skip ci] 2024-01-20 21:01:57 -08:00
Andrew Kane
490522b883 Added test for filtering with HNSW 2024-01-20 18:06:54 -08:00
Andrew Kane
a1a38156d7 Removed unneeded test [skip ci] 2024-01-20 15:28:48 -08:00
Andrew Kane
042ddfdc8a Updated readme [skip ci] 2024-01-20 11:40:49 -08:00
Andrew Kane
56870ce04d Added common paths on Mac [skip ci] 2024-01-19 21:43:55 -08:00
Andrew Kane
4ab77f3d24 Added section on missing SDK [skip ci] 2024-01-19 20:47:23 -08:00
Andrew Kane
cc9e6a6778 Added section on max_parallel_maintenance_workers [skip ci] 2024-01-18 21:57:38 -08:00
Andrew Kane
8f1b669c4f Added IVFFLAT_KMEANS_DEBUG to readme [skip ci] 2024-01-17 22:12:39 -08:00
Andrew Kane
1ff9ab5133 Revert "Improved vector_in"
This reverts commit 4894dc5da1.
2024-01-17 17:14:42 -08:00
Andrew Kane
4894dc5da1 Improved vector_in 2024-01-17 16:57:16 -08:00
Andrew Kane
7390f31261 Updated changelog [skip ci] 2024-01-17 10:50:07 -08:00
Heikki Linnakangas
b7304a3a4a Don't modify input string in vector_in() (#413)
Fixes issue #399
2024-01-17 10:49:04 -08:00
Andrew Kane
018ceb7a46 Updated PG_CONFIG example [skip ci] 2024-01-16 22:26:28 -08:00
Andrew Kane
0b2be00622 Added more defines to contributing docs [skip ci] 2024-01-16 17:21:33 -08:00
Andrew Kane
0ce497a1b1 Updated Homebrew note [skip ci] 2024-01-15 12:12:04 -08:00
Andrew Kane
c7d60346d8 Improved macro [skip ci] 2024-01-13 20:02:41 -08:00
Andrew Kane
597bfdc76b Added HnswGetNeighbors macro 2024-01-13 20:00:34 -08:00
Andrew Kane
cbf3eb4fa5 Improved HNSW build and insert code 2024-01-13 10:07:42 -08:00
Andrew Kane
cacd389f6d Improved pattern for duplicates 2024-01-12 14:30:13 -08:00
Andrew Kane
423cc2b06c Homebrew now adds to postgresql@15 as well [skip ci] 2024-01-11 16:45:50 -08:00
Andrew Kane
85c4ef6a14 Updated Postgres versions in readme [skip ci] 2024-01-11 12:36:24 -08:00
Andrew Kane
c6160a783a Homebrew now adds to postgresql@16 [skip ci] 2024-01-11 12:32:14 -08:00
Andrew Kane
1881b857f9 Simplified code 2024-01-09 18:53:31 -08:00
Andrew Kane
51bde5fb22 Updated readme [skip ci] 2024-01-09 14:38:25 -08:00
Andrew Kane
10e65ce349 Added note about maintenance_work_mem [skip ci] 2024-01-09 14:31:54 -08:00
Andrew Kane
61279f5a59 Updated readme [skip ci] 2024-01-09 14:26:55 -08:00
Andrew Kane
72b3889e26 Updated readme [skip ci] 2024-01-09 14:22:19 -08:00
Andrew Kane
bb21b2decf Updated readme [skip ci] 2024-01-09 14:19:01 -08:00
Andrew Kane
8a65c0e831 Moved section [skip ci] 2024-01-09 13:33:03 -08:00
Andrew Kane
7d75d423e4 Added section on index build time [skip ci] 2024-01-09 13:27:27 -08:00
Andrew Kane
6cad1f5de0 Updated example [skip ci] 2024-01-09 13:04:47 -08:00
Andrew Kane
67eeade63c Moved HNSW first in readme [skip ci] 2024-01-09 13:04:18 -08:00
Andrew Kane
108fb09d7b Improved code [skip ci] 2024-01-08 17:54:49 -08:00
Andrew Kane
65d060ac86 Reverted FlushPages pattern for parallel builds 2024-01-08 10:45:31 -08:00
Andrew Kane
62ee33bb92 Improved locking code 2024-01-08 09:05:12 -08:00
Andrew Kane
520e274dde Improved locking code 2024-01-07 22:34:41 -08:00
Andrew Kane
9e680884bd Moved indtuples to HnswGraph 2024-01-07 22:23:49 -08:00
Andrew Kane
19a0e1b341 Moved graph to separate struct 2024-01-07 20:15:30 -08:00
Andrew Kane
c7fe1571ee Improved code 2024-01-07 18:30:51 -08:00
Andrew Kane
cb4c770df2 Switched to slist for elements to reduce allocations and remove limit 2024-01-07 18:26:19 -08:00
Andrew Kane
85fdecd79b Moved FlushPages before HnswEndParallel 2024-01-07 17:50:46 -08:00
Andrew Kane
6132428914 Improved number of parallel workers for HNSW index builds - closes #397 2024-01-05 19:46:08 -08:00
Andrew Kane
81d13bd40f Improved code [skip ci] 2024-01-03 13:53:23 -05:00
Andrew Kane
8ee37b60a0 Improved memory estimate for HNSW index builds 2024-01-03 13:47:50 -05:00
Andrew Kane
9b73b3d1a6 Reduced memory and allocations for heap TIDs - closes #385 2024-01-03 13:41:34 -05:00
Andrew Kane
cae630784b Improved BuildCallback [skip ci] 2023-12-30 20:55:29 -05:00
Andrew Kane
d87bcd2deb Added comments [skip ci] 2023-12-30 18:29:01 -05:00
Andrew Kane
736576220a Improved BuildCallback 2023-12-30 18:24:03 -05:00
Andrew Kane
a508b120c1 Added IVFFLAT_MEMORY flag to show memory usage [skip ci] 2023-12-24 09:27:09 -05:00
Andrew Kane
9a782d29f8 Use consistent style [skip ci] 2023-12-22 16:41:25 -05:00
Andrew Kane
1e422cd62b Improved readability [skip ci] 2023-12-22 16:39:13 -05:00
Andrew Kane
569c69580a Improved InsertTuple code - #384
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2023-12-22 15:08:28 -05:00
Andrew Kane
59509c3a17 Added extra 5% to memory estimate 2023-12-22 14:04:05 -05:00
Andrew Kane
61738846af Updated comment [skip ci] 2023-12-22 14:03:33 -05:00
Andrew Kane
e8c3bf0cef Improved memory tracking for HNSW index builds - #384 2023-12-22 13:35:43 -05:00
Andrew Kane
50d1aed3d8 Improved memory usage logging [skip ci] 2023-12-22 13:09:11 -05:00
Andrew Kane
66e14d2434 Updated indentation [skip ci] 2023-12-22 12:59:50 -05:00
Andrew Kane
42cd4c6833 Fixed call to GenerationContextCreate for Postgres < 15 2023-12-22 12:49:07 -05:00
Andrew Kane
dcbe0b6f0d Reduced memory usage for HNSW index builds - #384
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2023-12-22 12:41:47 -05:00
Andrew Kane
f61d4087b5 Slightly improved memory estimation [skip ci] 2023-12-21 10:31:36 -05:00
Andrew Kane
57554e5b46 Added todo [skip ci] 2023-12-20 17:52:31 -05:00
Andrew Kane
6738fa0bd7 Added HNSW_MEMORY flag to show memory usage - #384 [skip ci] 2023-12-20 16:49:16 -05:00
Andrew Kane
9ab10aa674 Fixed CI 2023-12-20 16:29:13 -05:00
Andrew Kane
ec41dfa1d7 Mark meta buffer contents as dirty when not logging 2023-12-20 16:20:15 -05:00
Andrew Kane
43e0b3d9d4 Mark buffer contents as dirty when not logging 2023-12-20 16:16:25 -05:00
Andrew Kane
2bff7ccaa2 Improved memory estimation - #384 [skip ci] 2023-12-20 11:10:27 -05:00
Andrew Kane
e88a425c9b Reduced WAL generation for HNSW index builds - thanks @hlinnaka 2023-12-19 20:37:32 -05:00
Andrew Kane
921427ee03 Replace dynahash hash table in HNSW with simplehash for speed - #378
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2023-12-17 11:24:13 -05:00
Andrew Kane
a59aa02dd9 Only show message if flushed due to memory [skip ci] 2023-12-04 15:29:23 -08:00
Andrew Kane
2fef497b7e Fixed check 2023-12-04 15:22:12 -08:00
Andrew Kane
0e19a984fb Updated changelog [skip ci] 2023-12-04 15:15:20 -08:00
Andrew Kane
a156f6c7ae Fixed invalid memory alloc request size error with HNSW - fixes #43 2023-12-04 15:00:32 -08:00
Andrew Kane
c653ac524f Simplified code [skip ci] 2023-12-04 12:19:38 -08:00
Andrew Kane
bf0d56e78e Updated comment [skip ci] 2023-12-03 13:09:57 -08:00
128 changed files with 13694 additions and 2451 deletions

View File

@@ -9,9 +9,9 @@ jobs:
matrix:
include:
- postgres: 17
os: ubuntu-22.04
os: ubuntu-24.04
- postgres: 16
os: ubuntu-22.04
os: ubuntu-24.04
- postgres: 15
os: ubuntu-22.04
- postgres: 14
@@ -20,8 +20,6 @@ jobs:
os: ubuntu-20.04
- postgres: 12
os: ubuntu-20.04
- postgres: 11
os: ubuntu-20.04
steps:
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
@@ -30,7 +28,7 @@ jobs:
dev-files: true
- run: make
env:
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
- run: |
export PG_CONFIG=`which pg_config`
sudo --preserve-env=PG_CONFIG make install
@@ -42,27 +40,43 @@ jobs:
sudo apt-get install libipc-run-perl
- run: make prove_installcheck
mac:
runs-on: macos-latest
runs-on: ${{ matrix.os }}
if: ${{ !startsWith(github.ref_name, 'windows') }}
strategy:
fail-fast: false
matrix:
include:
- postgres: 16
os: macos-14
- postgres: 14
os: macos-12
steps:
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14
postgres-version: ${{ matrix.postgres }}
- run: make
env:
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter
- run: make install
- run: make installcheck
- if: ${{ failure() }}
run: cat regression.diffs
# Homebrew Postgres does not enable TAP tests, so need to download
- run: |
brew install cpanm
cpanm --notest IPC::Run
wget -q https://github.com/postgres/postgres/archive/refs/tags/REL_14_5.tar.gz
tar xf REL_14_5.tar.gz
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres-REL_14_5/src/test/perl" PERL5LIB="/Users/runner/perl5/lib/perl5"
- run: make clean && /usr/local/opt/llvm@15/bin/scan-build --status-bugs make
wget -q https://github.com/postgres/postgres/archive/refs/tags/$TAG.tar.gz
tar xf $TAG.tar.gz
mv postgres-$TAG postgres
env:
TAG: ${{ matrix.postgres == 16 && 'REL_16_2' || 'REL_14_11' }}
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres/src/test/perl -I ./test/perl"
env:
PERL5LIB: /Users/runner/perl5/lib/perl5
- run: make clean && $(brew --prefix llvm@15)/bin/scan-build --status-bugs make
env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING
windows:
runs-on: windows-latest
if: ${{ !startsWith(github.ref_name, 'mac') }}
@@ -79,14 +93,16 @@ jobs:
nmake /NOLOGO /F Makefile.win clean && ^
nmake /NOLOGO /F Makefile.win uninstall
shell: cmd
- if: ${{ failure() }}
run: cat regression.diffs
i386:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest
container:
image: debian:11
image: debian:12
options: --platform linux/386
steps:
- run: apt-get update && apt-get install -y build-essential git libipc-run-perl postgresql-13 postgresql-server-dev-13 sudo
- run: apt-get update && apt-get install -y build-essential git libipc-run-perl postgresql-15 postgresql-server-dev-15 sudo
- run: service postgresql start
- run: |
git clone https://github.com/${{ github.repository }}.git pgvector
@@ -99,4 +115,18 @@ jobs:
sudo -u postgres make installcheck
sudo -u postgres make prove_installcheck
env:
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
- if: ${{ failure() }}
run: cat pgvector/regression.diffs
valgrind:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: ankane/setup-postgres-valgrind@v1
with:
postgres-version: 16
check-ub: yes
- run: make OPTFLAGS=""
- run: sudo --preserve-env=PG_CONFIG make install
- run: make installcheck

View File

@@ -1,6 +1,60 @@
## 0.5.2 (unreleased)
## 0.7.3 (2024-07-22)
- Added support for on-disk parallel index builds for HNSW
- Fixed `failed to add index item` error with `sparsevec`
- Fixed compilation error with FreeBSD ARM
- Fixed compilation warning with MSVC and Postgres 16
## 0.7.2 (2024-06-11)
- Fixed initialization fork for indexes on unlogged tables
## 0.7.1 (2024-06-03)
- Improved performance of on-disk HNSW index builds
- Fixed `undefined symbol` error with GCC 8
- Fixed compilation error with universal binaries on Mac
- Fixed compilation warning with Clang < 14
## 0.7.0 (2024-04-29)
- Added `halfvec` type
- Added `sparsevec` type
- Added support for indexing `bit` type
- Added support for indexing L1 distance with HNSW
- Added `binary_quantize` function
- Added `hamming_distance` function
- Added `jaccard_distance` function
- Added `l2_normalize` function
- Added `subvector` function
- Added concatenate operator for vectors
- Added CPU dispatching for distance functions on Linux x86-64
- Updated comparison operators to support vectors with different dimensions
## 0.6.2 (2024-03-18)
- Reduced lock contention with parallel HNSW index builds
## 0.6.1 (2024-03-04)
- Fixed error with `ANALYZE` and vectors with different dimensions
- Fixed segmentation fault with `shared_preload_libraries`
- Fixed vector subtraction being marked as commutative
## 0.6.0 (2024-01-29)
If upgrading with Postgres 12 or Docker, see [these notes](https://github.com/pgvector/pgvector#060).
- Added support for parallel index builds for HNSW
- Added validation for GUC parameters
- Changed storage for vector from `extended` to `external`
- Improved performance of HNSW
- Reduced memory usage for HNSW index builds
- Reduced WAL generation for HNSW index builds
- Fixed error with logical replication
- Fixed `invalid memory alloc request size` error with HNSW index builds
- Moved Docker image to `pgvector` org
- Added Docker tags for each supported version of Postgres
- Dropped support for Postgres 11
## 0.5.1 (2023-10-10)
@@ -48,7 +102,7 @@
## 0.4.0 (2023-01-11)
If upgrading with Postgres < 13, see [this note](https://github.com/pgvector/pgvector#040).
If upgrading with Postgres < 13, see [this note](https://github.com/pgvector/pgvector/blob/v0.4.0/README.md#040).
- Changed text representation for vector elements to match `real`
- Changed storage for vector from `plain` to `extended`
@@ -65,7 +119,7 @@ If upgrading with Postgres < 13, see [this note](https://github.com/pgvector/pgv
## 0.3.1 (2022-11-02)
If upgrading from 0.2.7 or 0.3.0, [recreate](https://github.com/pgvector/pgvector#031) all `ivfflat` indexes after upgrading to ensure all data is indexed.
If upgrading from 0.2.7 or 0.3.0, [recreate](https://github.com/pgvector/pgvector/blob/v0.3.1/README.md#031) all `ivfflat` indexes after upgrading to ensure all data is indexed.
- Fixed issue with inserts silently corrupting `ivfflat` indexes (introduced in 0.2.7)
- Fixed segmentation fault with index creation when lists > 6500

View File

@@ -1,4 +1,4 @@
ARG PG_MAJOR=15
ARG PG_MAJOR=16
FROM postgres:$PG_MAJOR
ARG PG_MAJOR

View File

@@ -1,4 +1,4 @@
Portions Copyright (c) 1996-2023, PostgreSQL Global Development Group
Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
Portions Copyright (c) 1994, The Regents of the University of California

View File

@@ -2,7 +2,7 @@
"name": "vector",
"abstract": "Open-source vector similarity search for Postgres",
"description": "Supports L2 distance, inner product, and cosine distance",
"version": "0.5.1",
"version": "0.7.3",
"maintainer": [
"Andrew Kane <andrew@ankane.org>"
],
@@ -12,7 +12,7 @@
"prereqs": {
"runtime": {
"requires": {
"PostgreSQL": "11.0.0"
"PostgreSQL": "12.0.0"
}
}
},
@@ -20,7 +20,7 @@
"vector": {
"file": "sql/vector.sql",
"docfile": "README.md",
"version": "0.5.1",
"version": "0.7.3",
"abstract": "Open-source vector similarity search for Postgres"
}
},

View File

@@ -1,18 +1,19 @@
EXTENSION = vector
EXTVERSION = 0.5.1
EXTVERSION = 0.7.3
MODULE_big = vector
DATA = $(wildcard sql/*--*.sql)
OBJS = src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
HEADERS = src/vector.h
OBJS = src/bitutils.o src/bitvec.o src/halfutils.o src/halfvec.o src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/sparsevec.o src/vector.o
HEADERS = src/halfvec.h src/sparsevec.h src/vector.h
TESTS = $(wildcard test/sql/*.sql)
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
# To compile for portability, run: make OPTFLAGS=""
OPTFLAGS = -march=native
# Mac ARM doesn't support -march=native
# Mac ARM doesn't always support -march=native
ifeq ($(shell uname -s), Darwin)
ifeq ($(shell uname -p), arm)
# no difference with -march=armv8.5-a
@@ -65,13 +66,15 @@ dist:
mkdir -p dist
git archive --format zip --prefix=$(EXTENSION)-$(EXTVERSION)/ --output dist/$(EXTENSION)-$(EXTVERSION).zip master
# for Docker
PG_MAJOR ?= 16
.PHONY: docker
docker:
docker build --pull --no-cache --platform linux/amd64 -t ankane/pgvector:latest .
docker build --pull --no-cache --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .
.PHONY: docker-release
docker-release:
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 -t ankane/pgvector:latest .
docker buildx build --push --platform linux/amd64,linux/arm64 -t ankane/pgvector:v$(EXTVERSION) .
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .

View File

@@ -1,10 +1,10 @@
EXTENSION = vector
EXTVERSION = 0.5.1
EXTVERSION = 0.7.3
OBJS = src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
HEADERS = src\vector.h
OBJS = src\bitutils.obj src\bitvec.obj src\halfutils.obj src\halfvec.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\sparsevec.obj src\vector.obj
HEADERS = src\halfvec.h src\sparsevec.h src\vector.h
REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
REGRESS = bit btree cast copy halfvec hnsw_bit hnsw_halfvec hnsw_sparsevec hnsw_vector ivfflat_bit ivfflat_halfvec ivfflat_vector sparsevec vector_type
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
# For /arch flags

733
README.md
View File

@@ -5,7 +5,8 @@ Open-source vector similarity search for Postgres
Store your vectors with the rest of your data. Supports:
- exact and approximate nearest neighbor search
- L2 distance, inner product, and cosine distance
- single-precision, half-precision, binary, and sparse vectors
- L2 distance, inner product, cosine distance, L1 distance, Hamming distance, and Jaccard distance
- any [language](#languages) with a Postgres client
Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recovery, JOINs, and all of the other [great features](https://www.postgresql.org/about/) of Postgres
@@ -14,19 +15,46 @@ Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recove
## Installation
Compile and install the extension (supports Postgres 11+)
### Linux and Mac
Compile and install the extension (supports Postgres 12+)
```sh
cd /tmp
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.7.3 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo
```
See the [installation notes](#installation-notes) if you run into issues
See the [installation notes](#installation-notes---linux-and-mac) if you run into issues
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [pkg](#pkg), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
### Windows
Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/build/building-on-the-command-line?view=msvc-170#download-and-install-the-tools) is installed, and run:
```cmd
call "C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvars64.bat"
```
Note: The exact path will vary depending on your Visual Studio version and edition
Then use `nmake` to build:
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16"
cd %TEMP%
git clone --branch v0.7.3 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
```
See the [installation notes](#installation-notes---windows) if you run into issues
You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
## Getting Started
@@ -54,7 +82,7 @@ Get the nearest neighbors by L2 distance
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
Also supports inner product (`<#>`) and cosine distance (`<=>`)
Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`, added in 0.7.0)
Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators
@@ -78,6 +106,12 @@ Insert vectors
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
```
Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py))
```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
```
Upsert vectors
```sql
@@ -105,6 +139,13 @@ Get the nearest neighbors to a vector
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
Supported distance functions are:
- `<->` - L2 distance
- `<#>` - (negative) inner product
- `<=>` - cosine distance
- `<+>` - L1 distance (added in 0.7.0)
Get the nearest neighbors to a row
```sql
@@ -161,80 +202,12 @@ You can add an index to use approximate nearest neighbor search, which trades so
Supported index types are:
- [IVFFlat](#ivfflat)
- [HNSW](#hnsw) - added in 0.5.0
## IVFFlat
An IVFFlat index divides vectors into lists, and then searches a subset of those lists that are closest to the query vector. It has faster build times and uses less memory than HNSW, but has lower query performance (in terms of speed-recall tradeoff).
Three keys to achieving good recall are:
1. Create the index *after* the table has some data
2. Choose an appropriate number of lists - a good place to start is `rows / 1000` for up to 1M rows and `sqrt(rows)` for over 1M rows
3. When querying, specify an appropriate number of [probes](#query-options) (higher is better for recall, lower is better for speed) - a good place to start is `sqrt(lists)`
Add an index for each distance function you want to use.
L2 distance
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100);
```
Inner product
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_ip_ops) WITH (lists = 100);
```
Cosine distance
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
```
Vectors with up to 2,000 dimensions can be indexed.
### Query Options
Specify the number of probes (1 by default)
```sql
SET ivfflat.probes = 10;
```
A higher value provides better recall at the cost of speed, and it can be set to the number of lists for exact nearest neighbor search (at which point the planner wont use the index)
Use `SET LOCAL` inside a transaction to set it for a single query
```sql
BEGIN;
SET LOCAL ivfflat.probes = 10;
SELECT ...
COMMIT;
```
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases for IVFFlat are:
1. `initializing`
2. `performing k-means`
3. `assigning tuples`
4. `loading tuples`
Note: `%` is only populated during the `loading tuples` phase
- [IVFFlat](#ivfflat)
## HNSW
An HNSW index creates a multilayer graph. It has slower build times and uses more memory than IVFFlat, but has better query performance (in terms of speed-recall tradeoff). Theres no training step like IVFFlat, so the index can be created without any data in the table.
An HNSW index creates a multilayer graph. It has better query performance than IVFFlat (in terms of speed-recall tradeoff), but has slower build times and uses more memory. Also, an index can be created without any data in the table since there isnt a training step like IVFFlat.
Add an index for each distance function you want to use.
@@ -244,6 +217,8 @@ L2 distance
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops);
```
Note: Use `halfvec_l2_ops` for `halfvec` and `sparsevec_l2_ops` for `sparsevec` (and similar with the other distance functions)
Inner product
```sql
@@ -256,7 +231,30 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
```
Vectors with up to 2,000 dimensions can be indexed.
L1 distance - added in 0.7.0
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l1_ops);
```
Hamming distance - added in 0.7.0
```sql
CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
```
Jaccard distance - added in 0.7.0
```sql
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
```
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
- `sparsevec` - up to 1,000 non-zero elements (added in 0.7.0)
### Index Options
@@ -290,6 +288,34 @@ SELECT ...
COMMIT;
```
### Index Build Time
Indexes build significantly faster when the graph fits into `maintenance_work_mem`
```sql
SET maintenance_work_mem = '8GB';
```
A notice is shown when the graph no longer fits
```text
NOTICE: hnsw graph no longer fits into maintenance_work_mem after 100000 tuples
DETAIL: Building will take significantly more time.
HINT: Increase maintenance_work_mem to speed up builds.
```
Note: Do not set `maintenance_work_mem` so high that it exhausts the memory on the server
Like other index types, its faster to create an index after loading your initial data
Starting with 0.6.0, you can also speed up index creation by increasing the number of parallel workers (2 by default)
```sql
SET max_parallel_maintenance_workers = 7; -- plus leader
```
For a large number of workers, you may also need to increase `max_parallel_workers` (8 by default)
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
@@ -303,6 +329,96 @@ The phases for HNSW are:
1. `initializing`
2. `loading tuples`
## IVFFlat
An IVFFlat index divides vectors into lists, and then searches a subset of those lists that are closest to the query vector. It has faster build times and uses less memory than HNSW, but has lower query performance (in terms of speed-recall tradeoff).
Three keys to achieving good recall are:
1. Create the index *after* the table has some data
2. Choose an appropriate number of lists - a good place to start is `rows / 1000` for up to 1M rows and `sqrt(rows)` for over 1M rows
3. When querying, specify an appropriate number of [probes](#query-options) (higher is better for recall, lower is better for speed) - a good place to start is `sqrt(lists)`
Add an index for each distance function you want to use.
L2 distance
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100);
```
Note: Use `halfvec_l2_ops` for `halfvec` (and similar with the other distance functions)
Inner product
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_ip_ops) WITH (lists = 100);
```
Cosine distance
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
```
Hamming distance - added in 0.7.0
```sql
CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100);
```
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
### Query Options
Specify the number of probes (1 by default)
```sql
SET ivfflat.probes = 10;
```
A higher value provides better recall at the cost of speed, and it can be set to the number of lists for exact nearest neighbor search (at which point the planner wont use the index)
Use `SET LOCAL` inside a transaction to set it for a single query
```sql
BEGIN;
SET LOCAL ivfflat.probes = 10;
SELECT ...
COMMIT;
```
### Index Build Time
Speed up index creation on large tables by increasing the number of parallel workers (2 by default)
```sql
SET max_parallel_maintenance_workers = 7; -- plus leader
```
For a large number of workers, you may also need to increase `max_parallel_workers` (8 by default)
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases for IVFFlat are:
1. `initializing`
2. `performing k-means`
3. `assigning tuples`
4. `loading tuples`
Note: `%` is only populated during the `loading tuples` phase
## Filtering
There are a few ways to index nearest neighbor queries with a `WHERE` clause
@@ -320,8 +436,7 @@ CREATE INDEX ON items (category_id);
Or a [partial index](https://www.postgresql.org/docs/current/indexes-partial.html) on the vector column for approximate search
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100)
WHERE (category_id = 123);
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops) WHERE (category_id = 123);
```
Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html) for approximate search on many different values of the `WHERE` columns
@@ -330,6 +445,103 @@ Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
```
## Half-Precision Vectors
*Added in 0.7.0*
Use the `halfvec` type to store half-precision vectors
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));
```
## Half-Precision Indexing
*Added in 0.7.0*
Index vectors at half precision for smaller indexes
```sql
CREATE INDEX ON items USING hnsw ((embedding::halfvec(3)) halfvec_l2_ops);
```
Get the nearest neighbors
```sql
SELECT * FROM items ORDER BY embedding::halfvec(3) <-> '[1,2,3]' LIMIT 5;
```
## Binary Vectors
Use the `bit` type to store binary vectors ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py))
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES ('000'), ('111');
```
Get the nearest neighbors by Hamming distance (added in 0.7.0)
```sql
SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
```
Or (before 0.7.0)
```sql
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Also supports Jaccard distance (`<%>`)
## Binary Quantization
*Added in 0.7.0*
Use expression indexing for binary quantization
```sql
CREATE INDEX ON items USING hnsw ((binary_quantize(embedding)::bit(3)) bit_hamming_ops);
```
Get the nearest neighbors by Hamming distance
```sql
SELECT * FROM items ORDER BY binary_quantize(embedding)::bit(3) <~> binary_quantize('[1,-2,3]') LIMIT 5;
```
Re-rank by the original vectors for better recall
```sql
SELECT * FROM (
SELECT * FROM items ORDER BY binary_quantize(embedding)::bit(3) <~> binary_quantize('[1,-2,3]') LIMIT 20
) ORDER BY embedding <=> '[1,-2,3]' LIMIT 5;
```
## Sparse Vectors
*Added in 0.7.0*
Use the `sparsevec` type to store sparse vectors
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding sparsevec(5));
```
Insert vectors
```sql
INSERT INTO items (embedding) VALUES ('{1:1,3:2,5:3}/5'), ('{1:4,3:5,5:6}/5');
```
The format is `{index1:value1,index2:value2}/dimensions` and indices start at 1 like SQL arrays
Get the nearest neighbors by L2 distance
```sql
SELECT * FROM items ORDER BY embedding <-> '{1:3,3:1,5:2}/5' LIMIT 5;
```
## Hybrid Search
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search.
@@ -341,15 +553,77 @@ SELECT id, content FROM items, plainto_tsquery('hello search') query
You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search_rrf.py) or a [cross-encoder](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search.py) to combine results.
## Indexing Subvectors
*Added in 0.7.0*
Use expression indexing to index subvectors
```sql
CREATE INDEX ON items USING hnsw ((subvector(embedding, 1, 3)::vector(3)) vector_cosine_ops);
```
Get the nearest neighbors by cosine distance
```sql
SELECT * FROM items ORDER BY subvector(embedding, 1, 3)::vector(3) <=> subvector('[1,2,3,4,5]'::vector, 1, 3) LIMIT 5;
```
Re-rank by the full vectors for better recall
```sql
SELECT * FROM (
SELECT * FROM items ORDER BY subvector(embedding, 1, 3)::vector(3) <=> subvector('[1,2,3,4,5]'::vector, 1, 3) LIMIT 20
) ORDER BY embedding <=> '[1,2,3,4,5]' LIMIT 5;
```
## Performance
### Tuning
Use a tool like [PgTune](https://pgtune.leopard.in.ua/) to set initial values for Postgres server parameters. For instance, `shared_buffers` should typically be 25% of the servers memory. You can find the config file with:
```sql
SHOW config_file;
```
And check individual settings with:
```sql
SHOW shared_buffers;
```
Be sure to restart Postgres for changes to take effect.
### Loading
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py)).
```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
```
Add any indexes *after* loading the initial data for best performance.
### Indexing
See index build time for [HNSW](#index-build-time) and [IVFFlat](#index-build-time-1).
In production environments, create indexes concurrently to avoid blocking writes.
```sql
CREATE INDEX CONCURRENTLY ...
```
### Querying
Use `EXPLAIN ANALYZE` to debug performance.
```sql
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
### Exact Search
#### Exact Search
To speed up queries without an index, increase `max_parallel_workers_per_gather`.
@@ -363,7 +637,7 @@ If vectors are normalized to length 1 (like [OpenAI embeddings](https://platform
SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5;
```
### Approximate Search
#### Approximate Search
To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
@@ -371,6 +645,50 @@ To speed up queries with an IVFFlat index, increase the number of inverted lists
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 1000);
```
### Vacuuming
Vacuuming can take a while for HNSW indexes. Speed it up by reindexing first.
```sql
REINDEX INDEX CONCURRENTLY index_name;
VACUUM table_name;
```
## Monitoring
Monitor performance with [pg_stat_statements](https://www.postgresql.org/docs/current/pgstatstatements.html) (be sure to add it to `shared_preload_libraries`).
```sql
CREATE EXTENSION pg_stat_statements;
```
Get the most time-consuming queries with:
```sql
SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_time_ms,
ROUND((total_plan_time + total_exec_time) / 60000) AS total_time_min
FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20;
```
Note: Replace `total_plan_time + total_exec_time` with `total_time` for Postgres < 13
Monitor recall by comparing results from approximate search with exact search.
```sql
BEGIN;
SET LOCAL enable_indexscan = off; -- use exact search
SELECT ...
COMMIT;
```
## Scaling
Scale pgvector the same way you scale Postgres.
Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus.py)).
## Languages
Use pgvector from any language with a Postgres client. You can even generate and store vectors in one language and query them in another.
@@ -413,7 +731,7 @@ Yes, pgvector uses the write-ahead log (WAL), which allows for replication and p
#### What if I want to index vectors with more than 2,000 dimensions?
Youll need to use [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction) at the moment.
You can use [half-precision indexing](#half-precision-indexing) to index up to 4,000 dimensions or [binary quantization](#binary-quantization) to index up to 64,000 dimensions. Another option is [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction).
#### Can I store vectors with different dimensions in the same column?
@@ -476,7 +794,17 @@ SELECT pg_size_pretty(pg_relation_size('index_name'));
#### Why isnt a query using an index?
The cost estimation in pgvector < 0.4.3 does not always work well with the planner. You can encourage the planner to use an index for a query with:
The query needs to have an `ORDER BY` and `LIMIT`, and the `ORDER BY` must be the result of a distance operator (not an expression) in ascending order.
```sql
-- index
ORDER BY embedding <=> '[3,1,2]' LIMIT 5;
-- no index
ORDER BY 1 - (embedding <=> '[3,1,2]') DESC LIMIT 5;
```
You can encourage the planner to use an index for a query with:
```sql
BEGIN;
@@ -505,6 +833,12 @@ or choose to store vectors inline:
ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
```
#### Why are there less results for a query after adding an HNSW index?
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead.
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
#### Why are there less results for a query after adding an IVFFlat index?
The index was likely created with too little data for the number of lists. Drop the index until the table has more data.
@@ -513,11 +847,20 @@ The index was likely created with too little data for the number of lists. Drop
DROP INDEX index_name;
```
Results can also be limited by the number of probes (`ivfflat.probes`).
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
## Reference
- [Vector](#vector-type)
- [Halfvec](#halfvec-type)
- [Bit](#bit-type)
- [Sparsevec](#sparsevec-type)
### Vector Type
Each vector takes `4 * dimensions + 8` bytes of storage. Each element is a single precision floating-point number (like the `real` type in Postgres), and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Vectors can have up to 16,000 dimensions.
Each vector takes `4 * dimensions + 8` bytes of storage. Each element is a single-precision floating-point number (like the `real` type in Postgres), and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Vectors can have up to 16,000 dimensions.
### Vector Operators
@@ -526,36 +869,121 @@ Operator | Description | Added
\+ | element-wise addition |
\- | element-wise subtraction |
\* | element-wise multiplication | 0.5.0
\|\| | concatenate | 0.7.0
<-> | Euclidean distance |
<#> | negative inner product |
<=> | cosine distance |
<+> | taxicab distance | 0.7.0
### Vector Functions
Function | Description | Added
--- | --- | ---
binary_quantize(vector) → bit | binary quantize | 0.7.0
cosine_distance(vector, vector) → double precision | cosine distance |
inner_product(vector, vector) → double precision | inner product |
l2_distance(vector, vector) → double precision | Euclidean distance |
l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
l2_distance(vector, vector) → double precision | Euclidean distance |
l2_normalize(vector) → vector | Normalize with Euclidean norm | 0.7.0
subvector(vector, integer, integer) → vector | subvector | 0.7.0
vector_dims(vector) → integer | number of dimensions |
vector_norm(vector) → double precision | Euclidean norm |
### Aggregate Functions
### Vector Aggregate Functions
Function | Description | Added
--- | --- | ---
avg(vector) → vector | average |
sum(vector) → vector | sum | 0.5.0
## Installation Notes
### Halfvec Type
Each half vector takes `2 * dimensions + 8` bytes of storage. Each element is a half-precision floating-point number, and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Half vectors can have up to 16,000 dimensions.
### Halfvec Operators
Operator | Description | Added
--- | --- | ---
\+ | element-wise addition | 0.7.0
\- | element-wise subtraction | 0.7.0
\* | element-wise multiplication | 0.7.0
\|\| | concatenate | 0.7.0
<-> | Euclidean distance | 0.7.0
<#> | negative inner product | 0.7.0
<=> | cosine distance | 0.7.0
<+> | taxicab distance | 0.7.0
### Halfvec Functions
Function | Description | Added
--- | --- | ---
binary_quantize(halfvec) → bit | binary quantize | 0.7.0
cosine_distance(halfvec, halfvec) → double precision | cosine distance | 0.7.0
inner_product(halfvec, halfvec) → double precision | inner product | 0.7.0
l1_distance(halfvec, halfvec) → double precision | taxicab distance | 0.7.0
l2_distance(halfvec, halfvec) → double precision | Euclidean distance | 0.7.0
l2_norm(halfvec) → double precision | Euclidean norm | 0.7.0
l2_normalize(halfvec) → halfvec | Normalize with Euclidean norm | 0.7.0
subvector(halfvec, integer, integer) → halfvec | subvector | 0.7.0
vector_dims(halfvec) → integer | number of dimensions | 0.7.0
### Halfvec Aggregate Functions
Function | Description | Added
--- | --- | ---
avg(halfvec) → halfvec | average | 0.7.0
sum(halfvec) → halfvec | sum | 0.7.0
### Bit Type
Each bit vector takes `dimensions / 8 + 8` bytes of storage. See the [Postgres docs](https://www.postgresql.org/docs/current/datatype-bit.html) for more info.
### Bit Operators
Operator | Description | Added
--- | --- | ---
<~> | Hamming distance | 0.7.0
<%> | Jaccard distance | 0.7.0
### Bit Functions
Function | Description | Added
--- | --- | ---
hamming_distance(bit, bit) → double precision | Hamming distance | 0.7.0
jaccard_distance(bit, bit) → double precision | Jaccard distance | 0.7.0
### Sparsevec Type
Each sparse vector takes `8 * non-zero elements + 16` bytes of storage. Each element is a single-precision floating-point number, and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Sparse vectors can have up to 16,000 non-zero elements.
### Sparsevec Operators
Operator | Description | Added
--- | --- | ---
<-> | Euclidean distance | 0.7.0
<#> | negative inner product | 0.7.0
<=> | cosine distance | 0.7.0
<+> | taxicab distance | 0.7.0
### Sparsevec Functions
Function | Description | Added
--- | --- | ---
cosine_distance(sparsevec, sparsevec) → double precision | cosine distance | 0.7.0
inner_product(sparsevec, sparsevec) → double precision | inner product | 0.7.0
l1_distance(sparsevec, sparsevec) → double precision | taxicab distance | 0.7.0
l2_distance(sparsevec, sparsevec) → double precision | Euclidean distance | 0.7.0
l2_norm(sparsevec) → double precision | Euclidean norm | 0.7.0
l2_normalize(sparsevec) → sparsevec | Normalize with Euclidean norm | 0.7.0
## Installation Notes - Linux and Mac
### Postgres Location
If your machine has multiple Postgres installations, specify the path to [pg_config](https://www.postgresql.org/docs/current/app-pgconfig.html) with:
```sh
export PG_CONFIG=/Applications/Postgres.app/Contents/Versions/latest/bin/pg_config
export PG_CONFIG=/Library/PostgreSQL/16/bin/pg_config
```
Then re-run the installation instructions (run `make clean` before `make` if needed). If `sudo` is needed for `make install`, use:
@@ -564,6 +992,14 @@ Then re-run the installation instructions (run `make clean` before `make` if nee
sudo --preserve-env=PG_CONFIG make install
```
A few common paths on Mac are:
- EDB installer - `/Library/PostgreSQL/16/bin/pg_config`
- Homebrew (arm64) - `/opt/homebrew/opt/postgresql@16/bin/pg_config`
- Homebrew (x86-64) - `/usr/local/opt/postgresql@16/bin/pg_config`
Note: Replace `16` with your Postgres server version
### Missing Header
If compilation fails with `fatal error: postgres.h: No such file or directory`, make sure Postgres development files are installed on the server.
@@ -571,49 +1007,53 @@ If compilation fails with `fatal error: postgres.h: No such file or directory`,
For Ubuntu and Debian, use:
```sh
sudo apt install postgresql-server-dev-15
sudo apt install postgresql-server-dev-16
```
Note: Replace `15` with your Postgres server version
Note: Replace `16` with your Postgres server version
### Windows
### Missing SDK
Support for Windows is currently experimental. Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/build/building-on-the-command-line?view=msvc-170#download-and-install-the-tools) is installed, and run:
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, reinstall Xcode Command Line Tools.
```cmd
call "C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvars64.bat"
### Portability
By default, pgvector compiles with `-march=native` on some platforms for best performance. However, this can lead to `Illegal instruction` errors if trying to run the compiled extension on a different machine.
To compile for portability, use:
```sh
make OPTFLAGS=""
```
Note: The exact path will vary depending on your Visual Studio version and edition
## Installation Notes - Windows
Then use `nmake` to build:
### Missing Header
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\15"
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
```
If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct.
### Permissions
If installation fails with `Access is denied`, re-run the installation instructions as an administrator.
## Additional Installation Methods
### Docker
Get the [Docker image](https://hub.docker.com/r/ankane/pgvector) with:
Get the [Docker image](https://hub.docker.com/r/pgvector/pgvector) with:
```sh
docker pull ankane/pgvector
docker pull pgvector/pgvector:pg16
```
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (run it the same way).
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `16` with your Postgres server version, and run it the same way).
You can also build the image manually:
```sh
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.7.3 https://github.com/pgvector/pgvector.git
cd pgvector
docker build --build-arg PG_MAJOR=15 -t myuser/pgvector .
docker build --pull --build-arg PG_MAJOR=16 -t myuser/pgvector .
```
### Homebrew
@@ -639,22 +1079,37 @@ pgxn install vector
Debian and Ubuntu packages are available from the [PostgreSQL APT Repository](https://wiki.postgresql.org/wiki/Apt). Follow the [setup instructions](https://wiki.postgresql.org/wiki/Apt#Quickstart) and run:
```sh
sudo apt install postgresql-15-pgvector
sudo apt install postgresql-16-pgvector
```
Note: Replace `15` with your Postgres server version
Note: Replace `16` with your Postgres server version
### Yum
RPM packages are available from the [PostgreSQL Yum Repository](https://yum.postgresql.org/). Follow the [setup instructions](https://www.postgresql.org/download/linux/redhat/) for your distribution and run:
```sh
sudo yum install pgvector_15
sudo yum install pgvector_16
# or
sudo dnf install pgvector_15
sudo dnf install pgvector_16
```
Note: Replace `15` with your Postgres server version
Note: Replace `16` with your Postgres server version
### pkg
Install the FreeBSD package with:
```sh
pkg install postgresql15-pgvector
```
or the port with:
```sh
cd /usr/ports/databases/pgvector
make install
```
### conda-forge
@@ -690,28 +1145,32 @@ SELECT extversion FROM pg_extension WHERE extname = 'vector';
## Upgrade Notes
### 0.4.0
### 0.6.0
If upgrading with Postgres < 13, remove this line from `sql/vector--0.3.2--0.4.0.sql`:
#### Postgres 12
If upgrading with Postgres 12, remove this line from `sql/vector--0.5.1--0.6.0.sql`:
```sql
ALTER TYPE vector SET (STORAGE = extended);
ALTER TYPE vector SET (STORAGE = external);
```
Then run `make install` and `ALTER EXTENSION vector UPDATE;`.
### 0.3.1
#### Docker
If upgrading from 0.2.7 or 0.3.0, recreate all `ivfflat` indexes after upgrading to ensure all data is indexed.
The Docker image is now published in the `pgvector` org, and there are tags for each supported version of Postgres (rather than a `latest` tag).
```sql
-- Postgres 12+
REINDEX INDEX CONCURRENTLY index_name;
```sh
docker pull pgvector/pgvector:pg16
# or
docker pull pgvector/pgvector:0.6.0-pg16
```
-- Postgres < 12
CREATE INDEX CONCURRENTLY temp_name ON table USING ivfflat (column opclass);
DROP INDEX CONCURRENTLY index_name;
ALTER INDEX temp_name RENAME TO index_name;
Also, if youve increased `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
```sh
docker run --shm-size=1g ...
```
## Thanks
@@ -757,14 +1216,32 @@ make prove_installcheck # TAP tests
To run single tests:
```sh
make installcheck REGRESS=functions # regression test
make prove_installcheck PROVE_TESTS=test/t/001_wal.pl # TAP test
make installcheck REGRESS=functions # regression test
make prove_installcheck PROVE_TESTS=test/t/001_ivfflat_wal.pl # TAP test
```
To enable assertions:
```sh
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
```
To enable benchmarking:
```sh
make clean && PG_CFLAGS=-DIVFFLAT_BENCH make && make install
make clean && PG_CFLAGS="-DIVFFLAT_BENCH" make && make install
```
To show memory usage:
```sh
make clean && PG_CFLAGS="-DHNSW_MEMORY -DIVFFLAT_MEMORY" make && make install
```
To get k-means metrics:
```sh
make clean && PG_CFLAGS="-DIVFFLAT_KMEANS_DEBUG" make && make install
```
Resources for contributors

View File

@@ -0,0 +1,5 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.6.0'" to load this file. \quit
-- remove this single line for Postgres < 13
ALTER TYPE vector SET (STORAGE = external);

View File

@@ -0,0 +1,16 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.6.1'" to load this file. \quit
DROP OPERATOR - (vector, vector);
CREATE OPERATOR - (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub
);
ALTER OPERATOR <= (vector, vector) SET (
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
ALTER OPERATOR >= (vector, vector) SET (
RESTRICT = scalargesel, JOIN = scalargejoinsel
);

View File

@@ -0,0 +1,2 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.6.2'" to load this file. \quit

View File

@@ -0,0 +1,569 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.0'" to load this file. \quit
CREATE FUNCTION l2_normalize(vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION binary_quantize(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(vector, int, int) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_concat(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <+> (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l1_distance,
COMMUTATOR = '<+>'
);
CREATE OPERATOR || (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_concat
);
CREATE FUNCTION ivfflat_halfvec_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION ivfflat_bit_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION hnsw_halfvec_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION hnsw_bit_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION hnsw_sparsevec_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE OPERATOR CLASS vector_l1_ops
FOR TYPE vector USING hnsw AS
OPERATOR 1 <+> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(vector, vector);
CREATE TYPE halfvec;
CREATE FUNCTION halfvec_in(cstring, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_out(halfvec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_recv(internal, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_send(halfvec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE halfvec (
INPUT = halfvec_in,
OUTPUT = halfvec_out,
TYPMOD_IN = halfvec_typmod_in,
RECEIVE = halfvec_recv,
SEND = halfvec_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_dims(halfvec) RETURNS integer
AS 'MODULE_PATHNAME', 'halfvec_vector_dims' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_norm(halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_norm' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_normalize(halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_l2_normalize' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION binary_quantize(halfvec) RETURNS bit
AS 'MODULE_PATHNAME', 'halfvec_binary_quantize' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(halfvec, int, int) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_add(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_sub(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_mul(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_concat(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_lt(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_le(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_eq(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_ne(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_ge(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_gt(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_cmp(halfvec, halfvec) RETURNS int4
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_spherical_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_accum(double precision[], halfvec) RETURNS double precision[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_avg(double precision[]) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_combine(double precision[], double precision[]) RETURNS double precision[]
AS 'MODULE_PATHNAME', 'vector_combine' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE AGGREGATE avg(halfvec) (
SFUNC = halfvec_accum,
STYPE = double precision[],
FINALFUNC = halfvec_avg,
COMBINEFUNC = halfvec_combine,
INITCOND = '{0}',
PARALLEL = SAFE
);
CREATE AGGREGATE sum(halfvec) (
SFUNC = halfvec_add,
STYPE = halfvec,
COMBINEFUNC = halfvec_add,
PARALLEL = SAFE
);
CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_vector(halfvec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_halfvec(vector, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(integer[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(real[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(double precision[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(numeric[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_float4(halfvec, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (halfvec AS halfvec)
WITH FUNCTION halfvec(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS vector)
WITH FUNCTION halfvec_to_vector(halfvec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (vector AS halfvec)
WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS real[])
WITH FUNCTION halfvec_to_float4(halfvec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (integer[] AS halfvec)
WITH FUNCTION array_to_halfvec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS halfvec)
WITH FUNCTION array_to_halfvec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS halfvec)
WITH FUNCTION array_to_halfvec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS halfvec)
WITH FUNCTION array_to_halfvec(numeric[], integer, boolean) AS ASSIGNMENT;
CREATE OPERATOR <-> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR <+> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l1_distance,
COMMUTATOR = '<+>'
);
CREATE OPERATOR + (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_add,
COMMUTATOR = +
);
CREATE OPERATOR - (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_sub
);
CREATE OPERATOR * (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_mul,
COMMUTATOR = *
);
CREATE OPERATOR || (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_concat
);
CREATE OPERATOR < (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_lt,
COMMUTATOR = > , NEGATOR = >= ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
);
CREATE OPERATOR <= (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_le,
COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
CREATE OPERATOR = (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_eq,
COMMUTATOR = = , NEGATOR = <> ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR <> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_ne,
COMMUTATOR = <> , NEGATOR = = ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR >= (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_ge,
COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargesel, JOIN = scalargejoinsel
);
CREATE OPERATOR > (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_gt,
COMMUTATOR = < , NEGATOR = <= ,
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
);
CREATE OPERATOR CLASS halfvec_ops
DEFAULT FOR TYPE halfvec USING btree AS
OPERATOR 1 < ,
OPERATOR 2 <= ,
OPERATOR 3 = ,
OPERATOR 4 >= ,
OPERATOR 5 > ,
FUNCTION 1 halfvec_cmp(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec),
FUNCTION 3 l2_distance(halfvec, halfvec),
FUNCTION 5 ivfflat_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 l2_norm(halfvec),
FUNCTION 5 ivfflat_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 l2_norm(halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 l2_norm(halfvec),
FUNCTION 5 ivfflat_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 l2_norm(halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_l1_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <+> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(halfvec, halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
);
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING ivfflat AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit),
FUNCTION 3 hamming_distance(bit, bit),
FUNCTION 5 ivfflat_bit_support(internal);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit),
FUNCTION 3 hnsw_bit_support(internal);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit),
FUNCTION 3 hnsw_bit_support(internal);
CREATE TYPE sparsevec;
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE sparsevec (
INPUT = sparsevec_in,
OUTPUT = sparsevec_out,
TYPMOD_IN = sparsevec_typmod_in,
RECEIVE = sparsevec_recv,
SEND = sparsevec_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_norm(sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_norm' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_normalize(sparsevec) RETURNS sparsevec
AS 'MODULE_PATHNAME', 'sparsevec_l2_normalize' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_lt(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_le(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_eq(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_ne(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_ge(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_gt(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_cmp(sparsevec, sparsevec) RETURNS int4
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_sparsevec(halfvec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_halfvec(sparsevec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (sparsevec AS sparsevec)
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS vector)
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (vector AS sparsevec)
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS halfvec)
WITH FUNCTION sparsevec_to_halfvec(sparsevec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (halfvec AS sparsevec)
WITH FUNCTION halfvec_to_sparsevec(halfvec, integer, boolean) AS IMPLICIT;
CREATE OPERATOR <-> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR <+> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l1_distance,
COMMUTATOR = '<+>'
);
CREATE OPERATOR < (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_lt,
COMMUTATOR = > , NEGATOR = >= ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
);
CREATE OPERATOR <= (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_le,
COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
CREATE OPERATOR = (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_eq,
COMMUTATOR = = , NEGATOR = <> ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR <> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_ne,
COMMUTATOR = <> , NEGATOR = = ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR >= (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_ge,
COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargesel, JOIN = scalargejoinsel
);
CREATE OPERATOR > (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_gt,
COMMUTATOR = < , NEGATOR = <= ,
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
);
CREATE OPERATOR CLASS sparsevec_ops
DEFAULT FOR TYPE sparsevec USING btree AS
OPERATOR 1 < ,
OPERATOR 2 <= ,
OPERATOR 3 = ,
OPERATOR 4 >= ,
OPERATOR 5 > ,
FUNCTION 1 sparsevec_cmp(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_l2_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);
CREATE OPERATOR CLASS sparsevec_ip_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);
CREATE OPERATOR CLASS sparsevec_cosine_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 2 l2_norm(sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);
CREATE OPERATOR CLASS sparsevec_l1_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <+> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(sparsevec, sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);

View File

@@ -0,0 +1,2 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.1'" to load this file. \quit

View File

@@ -0,0 +1,2 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.2'" to load this file. \quit

View File

@@ -0,0 +1,2 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.3'" to load this file. \quit

View File

@@ -1,7 +1,7 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "CREATE EXTENSION vector" to load this file. \quit
-- type
-- vector type
CREATE TYPE vector;
@@ -26,10 +26,10 @@ CREATE TYPE vector (
TYPMOD_IN = vector_typmod_in,
RECEIVE = vector_recv,
SEND = vector_send,
STORAGE = extended
STORAGE = external
);
-- functions
-- vector functions
CREATE FUNCTION l2_distance(vector, vector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -49,6 +49,17 @@ CREATE FUNCTION vector_dims(vector) RETURNS integer
CREATE FUNCTION vector_norm(vector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_normalize(vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION binary_quantize(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(vector, int, int) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- vector private functions
CREATE FUNCTION vector_add(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -58,7 +69,8 @@ CREATE FUNCTION vector_sub(vector, vector) RETURNS vector
CREATE FUNCTION vector_mul(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- private functions
CREATE FUNCTION vector_concat(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_lt(vector, vector) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -99,7 +111,7 @@ CREATE FUNCTION vector_avg(double precision[]) RETURNS vector
CREATE FUNCTION vector_combine(double precision[], double precision[]) RETURNS double precision[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- aggregates
-- vector aggregates
CREATE AGGREGATE avg(vector) (
SFUNC = vector_accum,
@@ -117,7 +129,7 @@ CREATE AGGREGATE sum(vector) (
PARALLEL = SAFE
);
-- cast functions
-- vector cast functions
CREATE FUNCTION vector(vector, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -137,7 +149,7 @@ CREATE FUNCTION array_to_vector(numeric[], integer, boolean) RETURNS vector
CREATE FUNCTION vector_to_float4(vector, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- casts
-- vector casts
CREATE CAST (vector AS vector)
WITH FUNCTION vector(vector, integer, boolean) AS IMPLICIT;
@@ -157,7 +169,7 @@ CREATE CAST (double precision[] AS vector)
CREATE CAST (numeric[] AS vector)
WITH FUNCTION array_to_vector(numeric[], integer, boolean) AS ASSIGNMENT;
-- operators
-- vector operators
CREATE OPERATOR <-> (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l2_distance,
@@ -174,14 +186,18 @@ CREATE OPERATOR <=> (
COMMUTATOR = '<=>'
);
CREATE OPERATOR <+> (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l1_distance,
COMMUTATOR = '<+>'
);
CREATE OPERATOR + (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_add,
COMMUTATOR = +
);
CREATE OPERATOR - (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub,
COMMUTATOR = -
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub
);
CREATE OPERATOR * (
@@ -189,17 +205,20 @@ CREATE OPERATOR * (
COMMUTATOR = *
);
CREATE OPERATOR || (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_concat
);
CREATE OPERATOR < (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_lt,
COMMUTATOR = > , NEGATOR = >= ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
);
-- should use scalarlesel and scalarlejoinsel, but not supported in Postgres < 11
CREATE OPERATOR <= (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_le,
COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
CREATE OPERATOR = (
@@ -214,11 +233,10 @@ CREATE OPERATOR <> (
RESTRICT = eqsel, JOIN = eqjoinsel
);
-- should use scalargesel and scalargejoinsel, but not supported in Postgres < 11
CREATE OPERATOR >= (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_ge,
COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
RESTRICT = scalargesel, JOIN = scalargejoinsel
);
CREATE OPERATOR > (
@@ -243,7 +261,24 @@ CREATE ACCESS METHOD hnsw TYPE INDEX HANDLER hnswhandler;
COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method';
-- opclasses
-- access method private functions
CREATE FUNCTION ivfflat_halfvec_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION ivfflat_bit_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION hnsw_halfvec_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION hnsw_bit_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION hnsw_sparsevec_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
-- vector opclasses
CREATE OPERATOR CLASS vector_ops
DEFAULT FOR TYPE vector USING btree AS
@@ -290,3 +325,570 @@ CREATE OPERATOR CLASS vector_cosine_ops
OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_negative_inner_product(vector, vector),
FUNCTION 2 vector_norm(vector);
CREATE OPERATOR CLASS vector_l1_ops
FOR TYPE vector USING hnsw AS
OPERATOR 1 <+> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(vector, vector);
-- halfvec type
CREATE TYPE halfvec;
CREATE FUNCTION halfvec_in(cstring, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_out(halfvec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_recv(internal, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_send(halfvec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE halfvec (
INPUT = halfvec_in,
OUTPUT = halfvec_out,
TYPMOD_IN = halfvec_typmod_in,
RECEIVE = halfvec_recv,
SEND = halfvec_send,
STORAGE = external
);
-- halfvec functions
CREATE FUNCTION l2_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_dims(halfvec) RETURNS integer
AS 'MODULE_PATHNAME', 'halfvec_vector_dims' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_norm(halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_norm' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_normalize(halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_l2_normalize' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION binary_quantize(halfvec) RETURNS bit
AS 'MODULE_PATHNAME', 'halfvec_binary_quantize' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(halfvec, int, int) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec private functions
CREATE FUNCTION halfvec_add(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_sub(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_mul(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_concat(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_lt(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_le(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_eq(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_ne(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_ge(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_gt(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_cmp(halfvec, halfvec) RETURNS int4
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_spherical_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_accum(double precision[], halfvec) RETURNS double precision[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_avg(double precision[]) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_combine(double precision[], double precision[]) RETURNS double precision[]
AS 'MODULE_PATHNAME', 'vector_combine' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec aggregates
CREATE AGGREGATE avg(halfvec) (
SFUNC = halfvec_accum,
STYPE = double precision[],
FINALFUNC = halfvec_avg,
COMBINEFUNC = halfvec_combine,
INITCOND = '{0}',
PARALLEL = SAFE
);
CREATE AGGREGATE sum(halfvec) (
SFUNC = halfvec_add,
STYPE = halfvec,
COMBINEFUNC = halfvec_add,
PARALLEL = SAFE
);
-- halfvec cast functions
CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_vector(halfvec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_halfvec(vector, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(integer[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(real[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(double precision[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(numeric[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_float4(halfvec, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec casts
CREATE CAST (halfvec AS halfvec)
WITH FUNCTION halfvec(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS vector)
WITH FUNCTION halfvec_to_vector(halfvec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (vector AS halfvec)
WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS real[])
WITH FUNCTION halfvec_to_float4(halfvec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (integer[] AS halfvec)
WITH FUNCTION array_to_halfvec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS halfvec)
WITH FUNCTION array_to_halfvec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS halfvec)
WITH FUNCTION array_to_halfvec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS halfvec)
WITH FUNCTION array_to_halfvec(numeric[], integer, boolean) AS ASSIGNMENT;
-- halfvec operators
CREATE OPERATOR <-> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR <+> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l1_distance,
COMMUTATOR = '<+>'
);
CREATE OPERATOR + (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_add,
COMMUTATOR = +
);
CREATE OPERATOR - (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_sub
);
CREATE OPERATOR * (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_mul,
COMMUTATOR = *
);
CREATE OPERATOR || (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_concat
);
CREATE OPERATOR < (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_lt,
COMMUTATOR = > , NEGATOR = >= ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
);
CREATE OPERATOR <= (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_le,
COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
CREATE OPERATOR = (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_eq,
COMMUTATOR = = , NEGATOR = <> ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR <> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_ne,
COMMUTATOR = <> , NEGATOR = = ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR >= (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_ge,
COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargesel, JOIN = scalargejoinsel
);
CREATE OPERATOR > (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_gt,
COMMUTATOR = < , NEGATOR = <= ,
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
);
-- halfvec opclasses
CREATE OPERATOR CLASS halfvec_ops
DEFAULT FOR TYPE halfvec USING btree AS
OPERATOR 1 < ,
OPERATOR 2 <= ,
OPERATOR 3 = ,
OPERATOR 4 >= ,
OPERATOR 5 > ,
FUNCTION 1 halfvec_cmp(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec),
FUNCTION 3 l2_distance(halfvec, halfvec),
FUNCTION 5 ivfflat_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 l2_norm(halfvec),
FUNCTION 5 ivfflat_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 l2_norm(halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 l2_norm(halfvec),
FUNCTION 5 ivfflat_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 l2_norm(halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_l1_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <+> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(halfvec, halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
-- bit functions
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- bit operators
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
);
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
-- bit opclasses
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING ivfflat AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit),
FUNCTION 3 hamming_distance(bit, bit),
FUNCTION 5 ivfflat_bit_support(internal);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit),
FUNCTION 3 hnsw_bit_support(internal);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit),
FUNCTION 3 hnsw_bit_support(internal);
--- sparsevec type
CREATE TYPE sparsevec;
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE sparsevec (
INPUT = sparsevec_in,
OUTPUT = sparsevec_out,
TYPMOD_IN = sparsevec_typmod_in,
RECEIVE = sparsevec_recv,
SEND = sparsevec_send,
STORAGE = external
);
-- sparsevec functions
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_norm(sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_norm' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_normalize(sparsevec) RETURNS sparsevec
AS 'MODULE_PATHNAME', 'sparsevec_l2_normalize' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec private functions
CREATE FUNCTION sparsevec_lt(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_le(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_eq(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_ne(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_ge(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_gt(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_cmp(sparsevec, sparsevec) RETURNS int4
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec cast functions
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_sparsevec(halfvec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_halfvec(sparsevec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec casts
CREATE CAST (sparsevec AS sparsevec)
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS vector)
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (vector AS sparsevec)
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS halfvec)
WITH FUNCTION sparsevec_to_halfvec(sparsevec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (halfvec AS sparsevec)
WITH FUNCTION halfvec_to_sparsevec(halfvec, integer, boolean) AS IMPLICIT;
-- sparsevec operators
CREATE OPERATOR <-> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR <+> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l1_distance,
COMMUTATOR = '<+>'
);
CREATE OPERATOR < (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_lt,
COMMUTATOR = > , NEGATOR = >= ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
);
CREATE OPERATOR <= (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_le,
COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
CREATE OPERATOR = (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_eq,
COMMUTATOR = = , NEGATOR = <> ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR <> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_ne,
COMMUTATOR = <> , NEGATOR = = ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR >= (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_ge,
COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargesel, JOIN = scalargejoinsel
);
CREATE OPERATOR > (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_gt,
COMMUTATOR = < , NEGATOR = <= ,
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
);
-- sparsevec opclasses
CREATE OPERATOR CLASS sparsevec_ops
DEFAULT FOR TYPE sparsevec USING btree AS
OPERATOR 1 < ,
OPERATOR 2 <= ,
OPERATOR 3 = ,
OPERATOR 4 >= ,
OPERATOR 5 > ,
FUNCTION 1 sparsevec_cmp(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_l2_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);
CREATE OPERATOR CLASS sparsevec_ip_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);
CREATE OPERATOR CLASS sparsevec_cosine_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 2 l2_norm(sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);
CREATE OPERATOR CLASS sparsevec_l1_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <+> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(sparsevec, sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);

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src/bitutils.c Normal file
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#include "postgres.h"
#include "bitutils.h"
#include "halfvec.h" /* for USE_DISPATCH and USE_TARGET_CLONES */
#include "port/pg_bitutils.h"
#if defined(USE_DISPATCH)
#define BIT_DISPATCH
#endif
#ifdef BIT_DISPATCH
#include <immintrin.h>
#if defined(USE__GET_CPUID)
#include <cpuid.h>
#else
#include <intrin.h>
#endif
#ifdef _MSC_VER
#define TARGET_AVX512_POPCOUNT
#else
#define TARGET_AVX512_POPCOUNT __attribute__((target("avx512f,avx512vpopcntdq")))
#endif
#endif
/* Disable for LLVM due to crash with bitcode generation */
#if defined(USE_TARGET_CLONES) && !defined(__POPCNT__) && !defined(__llvm__)
#define BIT_TARGET_CLONES __attribute__((target_clones("default", "popcnt")))
#else
#define BIT_TARGET_CLONES
#endif
/* Use built-ins when possible for inlining */
#if defined(HAVE__BUILTIN_POPCOUNT) && defined(HAVE_LONG_INT_64)
#define popcount64(x) __builtin_popcountl(x)
#elif defined(HAVE__BUILTIN_POPCOUNT) && defined(HAVE_LONG_LONG_INT_64)
#define popcount64(x) __builtin_popcountll(x)
#elif !defined(_MSC_VER)
/* Fails to resolve with MSVC */
#define popcount64(x) pg_popcount64(x)
#endif
uint64 (*BitHammingDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance);
double (*BitJaccardDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 ab, uint64 aa, uint64 bb);
BIT_TARGET_CLONES static uint64
BitHammingDistanceDefault(uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance)
{
#ifdef popcount64
for (; bytes >= sizeof(uint64); bytes -= sizeof(uint64))
{
uint64 axs;
uint64 bxs;
/* Ensure aligned */
memcpy(&axs, ax, sizeof(uint64));
memcpy(&bxs, bx, sizeof(uint64));
distance += popcount64(axs ^ bxs);
ax += sizeof(uint64);
bx += sizeof(uint64);
}
#endif
for (uint32 i = 0; i < bytes; i++)
distance += pg_number_of_ones[ax[i] ^ bx[i]];
return distance;
}
#ifdef BIT_DISPATCH
TARGET_AVX512_POPCOUNT static uint64
BitHammingDistanceAvx512Popcount(uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance)
{
__m512i dist = _mm512_setzero_si512();
for (; bytes >= sizeof(__m512i); bytes -= sizeof(__m512i))
{
__m512i axs = _mm512_loadu_si512((const __m512i *) ax);
__m512i bxs = _mm512_loadu_si512((const __m512i *) bx);
dist = _mm512_add_epi64(dist, _mm512_popcnt_epi64(_mm512_xor_si512(axs, bxs)));
ax += sizeof(__m512i);
bx += sizeof(__m512i);
}
distance += _mm512_reduce_add_epi64(dist);
return BitHammingDistanceDefault(bytes, ax, bx, distance);
}
#endif
BIT_TARGET_CLONES static double
BitJaccardDistanceDefault(uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 ab, uint64 aa, uint64 bb)
{
#ifdef popcount64
for (; bytes >= sizeof(uint64); bytes -= sizeof(uint64))
{
uint64 axs;
uint64 bxs;
/* Ensure aligned */
memcpy(&axs, ax, sizeof(uint64));
memcpy(&bxs, bx, sizeof(uint64));
ab += popcount64(axs & bxs);
aa += popcount64(axs);
bb += popcount64(bxs);
ax += sizeof(uint64);
bx += sizeof(uint64);
}
#endif
for (uint32 i = 0; i < bytes; i++)
{
ab += pg_number_of_ones[ax[i] & bx[i]];
aa += pg_number_of_ones[ax[i]];
bb += pg_number_of_ones[bx[i]];
}
if (ab == 0)
return 1;
else
return 1 - (ab / ((double) (aa + bb - ab)));
}
#ifdef BIT_DISPATCH
TARGET_AVX512_POPCOUNT static double
BitJaccardDistanceAvx512Popcount(uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 ab, uint64 aa, uint64 bb)
{
__m512i abx = _mm512_setzero_si512();
__m512i aax = _mm512_setzero_si512();
__m512i bbx = _mm512_setzero_si512();
for (; bytes >= sizeof(__m512i); bytes -= sizeof(__m512i))
{
__m512i axs = _mm512_loadu_si512((const __m512i *) ax);
__m512i bxs = _mm512_loadu_si512((const __m512i *) bx);
abx = _mm512_add_epi64(abx, _mm512_popcnt_epi64(_mm512_and_si512(axs, bxs)));
aax = _mm512_add_epi64(aax, _mm512_popcnt_epi64(axs));
bbx = _mm512_add_epi64(bbx, _mm512_popcnt_epi64(bxs));
ax += sizeof(__m512i);
bx += sizeof(__m512i);
}
ab += _mm512_reduce_add_epi64(abx);
aa += _mm512_reduce_add_epi64(aax);
bb += _mm512_reduce_add_epi64(bbx);
return BitJaccardDistanceDefault(bytes, ax, bx, ab, aa, bb);
}
#endif
#ifdef BIT_DISPATCH
#define CPU_FEATURE_OSXSAVE (1 << 27) /* F1 ECX */
#define CPU_FEATURE_AVX512F (1 << 16) /* F7,0 EBX */
#define CPU_FEATURE_AVX512VPOPCNTDQ (1 << 14) /* F7,0 ECX */
#ifdef _MSC_VER
#define TARGET_XSAVE
#else
#define TARGET_XSAVE __attribute__((target("xsave")))
#endif
TARGET_XSAVE static bool
SupportsAvx512Popcount()
{
unsigned int exx[4] = {0, 0, 0, 0};
#if defined(USE__GET_CPUID)
__get_cpuid(1, &exx[0], &exx[1], &exx[2], &exx[3]);
#else
__cpuid(exx, 1);
#endif
/* Check OS supports XSAVE */
if ((exx[2] & CPU_FEATURE_OSXSAVE) != CPU_FEATURE_OSXSAVE)
return false;
/* Check XMM, YMM, and ZMM registers are enabled */
if ((_xgetbv(0) & 0xe6) != 0xe6)
return false;
#if defined(USE__GET_CPUID)
__get_cpuid_count(7, 0, &exx[0], &exx[1], &exx[2], &exx[3]);
#else
__cpuidex(exx, 7, 0);
#endif
/* Check AVX512F */
if ((exx[1] & CPU_FEATURE_AVX512F) != CPU_FEATURE_AVX512F)
return false;
/* Check AVX512VPOPCNTDQ */
return (exx[2] & CPU_FEATURE_AVX512VPOPCNTDQ) == CPU_FEATURE_AVX512VPOPCNTDQ;
}
#endif
void
BitvecInit(void)
{
/*
* Could skip pointer when single function, but no difference in
* performance
*/
BitHammingDistance = BitHammingDistanceDefault;
BitJaccardDistance = BitJaccardDistanceDefault;
#ifdef BIT_DISPATCH
if (SupportsAvx512Popcount())
{
BitHammingDistance = BitHammingDistanceAvx512Popcount;
BitJaccardDistance = BitJaccardDistanceAvx512Popcount;
}
#endif
}

16
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#ifndef BITUTILS_H
#define BITUTILS_H
#include "postgres.h"
/* Check version in first header */
#if PG_VERSION_NUM < 120000
#error "Requires PostgreSQL 12+"
#endif
extern uint64 (*BitHammingDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance);
extern double (*BitJaccardDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 ab, uint64 aa, uint64 bb);
void BitvecInit(void);
#endif

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#include "postgres.h"
#include "bitutils.h"
#include "bitvec.h"
#include "utils/varbit.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/*
* Allocate and initialize a new bit vector
*/
VarBit *
InitBitVector(int dim)
{
VarBit *result;
int size;
size = VARBITTOTALLEN(dim);
result = (VarBit *) palloc0(size);
SET_VARSIZE(result, size);
VARBITLEN(result) = dim;
return result;
}
/*
* Ensure same dimensions
*/
static inline void
CheckDims(VarBit *a, VarBit *b)
{
if (VARBITLEN(a) != VARBITLEN(b))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different bit lengths %u and %u", VARBITLEN(a), VARBITLEN(b))));
}
/*
* Get the Hamming distance between two bit vectors
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hamming_distance);
Datum
hamming_distance(PG_FUNCTION_ARGS)
{
VarBit *a = PG_GETARG_VARBIT_P(0);
VarBit *b = PG_GETARG_VARBIT_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8((double) BitHammingDistance(VARBITBYTES(a), VARBITS(a), VARBITS(b), 0));
}
/*
* Get the Jaccard distance between two bit vectors
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(jaccard_distance);
Datum
jaccard_distance(PG_FUNCTION_ARGS)
{
VarBit *a = PG_GETARG_VARBIT_P(0);
VarBit *b = PG_GETARG_VARBIT_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(BitJaccardDistance(VARBITBYTES(a), VARBITS(a), VARBITS(b), 0, 0, 0));
}

8
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#ifndef BITVEC_H
#define BITVEC_H
#include "utils/varbit.h"
VarBit *InitBitVector(int dim);
#endif

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#include "postgres.h"
#include "halfutils.h"
#include "halfvec.h"
#ifdef HALFVEC_DISPATCH
#include <immintrin.h>
#if defined(USE__GET_CPUID)
#include <cpuid.h>
#else
#include <intrin.h>
#endif
#ifdef _MSC_VER
#define TARGET_F16C
#else
#define TARGET_F16C __attribute__((target("avx,f16c,fma")))
#endif
#endif
float (*HalfvecL2SquaredDistance) (int dim, half * ax, half * bx);
float (*HalfvecInnerProduct) (int dim, half * ax, half * bx);
double (*HalfvecCosineSimilarity) (int dim, half * ax, half * bx);
float (*HalfvecL1Distance) (int dim, half * ax, half * bx);
static float
HalfvecL2SquaredDistanceDefault(int dim, half * ax, half * bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
return distance;
}
#ifdef HALFVEC_DISPATCH
TARGET_F16C static float
HalfvecL2SquaredDistanceF16c(int dim, half * ax, half * bx)
{
float distance;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 dist = _mm256_setzero_ps();
for (i = 0; i < count; i += 8)
{
__m128i axi = _mm_loadu_si128((__m128i *) (ax + i));
__m128i bxi = _mm_loadu_si128((__m128i *) (bx + i));
__m256 axs = _mm256_cvtph_ps(axi);
__m256 bxs = _mm256_cvtph_ps(bxi);
__m256 diff = _mm256_sub_ps(axs, bxs);
dist = _mm256_fmadd_ps(diff, diff, dist);
}
_mm256_storeu_ps(s, dist);
distance = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
for (; i < dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
return distance;
}
#endif
static float
HalfvecInnerProductDefault(int dim, half * ax, half * bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
return distance;
}
#ifdef HALFVEC_DISPATCH
TARGET_F16C static float
HalfvecInnerProductF16c(int dim, half * ax, half * bx)
{
float distance;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 dist = _mm256_setzero_ps();
for (i = 0; i < count; i += 8)
{
__m128i axi = _mm_loadu_si128((__m128i *) (ax + i));
__m128i bxi = _mm_loadu_si128((__m128i *) (bx + i));
__m256 axs = _mm256_cvtph_ps(axi);
__m256 bxs = _mm256_cvtph_ps(bxi);
dist = _mm256_fmadd_ps(axs, bxs, dist);
}
_mm256_storeu_ps(s, dist);
distance = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
for (; i < dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
return distance;
}
#endif
static double
HalfvecCosineSimilarityDefault(int dim, half * ax, half * bx)
{
float similarity = 0.0;
float norma = 0.0;
float normb = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float axi = HalfToFloat4(ax[i]);
float bxi = HalfToFloat4(bx[i]);
similarity += axi * bxi;
norma += axi * axi;
normb += bxi * bxi;
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
return (double) similarity / sqrt((double) norma * (double) normb);
}
#ifdef HALFVEC_DISPATCH
TARGET_F16C static double
HalfvecCosineSimilarityF16c(int dim, half * ax, half * bx)
{
float similarity;
float norma;
float normb;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 sim = _mm256_setzero_ps();
__m256 na = _mm256_setzero_ps();
__m256 nb = _mm256_setzero_ps();
for (i = 0; i < count; i += 8)
{
__m128i axi = _mm_loadu_si128((__m128i *) (ax + i));
__m128i bxi = _mm_loadu_si128((__m128i *) (bx + i));
__m256 axs = _mm256_cvtph_ps(axi);
__m256 bxs = _mm256_cvtph_ps(bxi);
sim = _mm256_fmadd_ps(axs, bxs, sim);
na = _mm256_fmadd_ps(axs, axs, na);
nb = _mm256_fmadd_ps(bxs, bxs, nb);
}
_mm256_storeu_ps(s, sim);
similarity = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
_mm256_storeu_ps(s, na);
norma = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
_mm256_storeu_ps(s, nb);
normb = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
/* Auto-vectorized */
for (; i < dim; i++)
{
float axi = HalfToFloat4(ax[i]);
float bxi = HalfToFloat4(bx[i]);
similarity += axi * bxi;
norma += axi * axi;
normb += bxi * bxi;
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
return (double) similarity / sqrt((double) norma * (double) normb);
}
#endif
static float
HalfvecL1DistanceDefault(int dim, half * ax, half * bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += fabsf(HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]));
return distance;
}
#ifdef HALFVEC_DISPATCH
/* Does not require FMA, but keep logic simple */
TARGET_F16C static float
HalfvecL1DistanceF16c(int dim, half * ax, half * bx)
{
float distance;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 dist = _mm256_setzero_ps();
__m256 sign = _mm256_set1_ps(-0.0);
for (i = 0; i < count; i += 8)
{
__m128i axi = _mm_loadu_si128((__m128i *) (ax + i));
__m128i bxi = _mm_loadu_si128((__m128i *) (bx + i));
__m256 axs = _mm256_cvtph_ps(axi);
__m256 bxs = _mm256_cvtph_ps(bxi);
dist = _mm256_add_ps(dist, _mm256_andnot_ps(sign, _mm256_sub_ps(axs, bxs)));
}
_mm256_storeu_ps(s, dist);
distance = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
for (; i < dim; i++)
distance += fabsf(HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]));
return distance;
}
#endif
#ifdef HALFVEC_DISPATCH
#define CPU_FEATURE_FMA (1 << 12)
#define CPU_FEATURE_OSXSAVE (1 << 27)
#define CPU_FEATURE_AVX (1 << 28)
#define CPU_FEATURE_F16C (1 << 29)
#ifdef _MSC_VER
#define TARGET_XSAVE
#else
#define TARGET_XSAVE __attribute__((target("xsave")))
#endif
TARGET_XSAVE static bool
SupportsCpuFeature(unsigned int feature)
{
unsigned int exx[4] = {0, 0, 0, 0};
#if defined(USE__GET_CPUID)
__get_cpuid(1, &exx[0], &exx[1], &exx[2], &exx[3]);
#else
__cpuid(exx, 1);
#endif
/* Check OS supports XSAVE */
if ((exx[2] & CPU_FEATURE_OSXSAVE) != CPU_FEATURE_OSXSAVE)
return false;
/* Check XMM and YMM registers are enabled */
if ((_xgetbv(0) & 6) != 6)
return false;
/* Now check features */
return (exx[2] & feature) == feature;
}
#endif
void
HalfvecInit(void)
{
/*
* Could skip pointer when single function, but no difference in
* performance
*/
HalfvecL2SquaredDistance = HalfvecL2SquaredDistanceDefault;
HalfvecInnerProduct = HalfvecInnerProductDefault;
HalfvecCosineSimilarity = HalfvecCosineSimilarityDefault;
HalfvecL1Distance = HalfvecL1DistanceDefault;
#ifdef HALFVEC_DISPATCH
if (SupportsCpuFeature(CPU_FEATURE_AVX | CPU_FEATURE_F16C | CPU_FEATURE_FMA))
{
HalfvecL2SquaredDistance = HalfvecL2SquaredDistanceF16c;
HalfvecInnerProduct = HalfvecInnerProductF16c;
HalfvecCosineSimilarity = HalfvecCosineSimilarityF16c;
/* Does not require FMA, but keep logic simple */
HalfvecL1Distance = HalfvecL1DistanceF16c;
}
#endif
}

263
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@@ -0,0 +1,263 @@
#ifndef HALFUTILS_H
#define HALFUTILS_H
#include <math.h>
#include "common/shortest_dec.h"
#include "halfvec.h"
#ifdef F16C_SUPPORT
#include <immintrin.h>
#endif
extern float (*HalfvecL2SquaredDistance) (int dim, half * ax, half * bx);
extern float (*HalfvecInnerProduct) (int dim, half * ax, half * bx);
extern double (*HalfvecCosineSimilarity) (int dim, half * ax, half * bx);
extern float (*HalfvecL1Distance) (int dim, half * ax, half * bx);
void HalfvecInit(void);
/*
* Check if half is NaN
*/
static inline bool
HalfIsNan(half num)
{
#ifdef FLT16_SUPPORT
return isnan(num);
#else
return (num & 0x7C00) == 0x7C00 && (num & 0x7FFF) != 0x7C00;
#endif
}
/*
* Check if half is infinite
*/
static inline bool
HalfIsInf(half num)
{
#ifdef FLT16_SUPPORT
return isinf(num);
#else
return (num & 0x7FFF) == 0x7C00;
#endif
}
/*
* Check if half is zero
*/
static inline bool
HalfIsZero(half num)
{
#ifdef FLT16_SUPPORT
return num == 0;
#else
return (num & 0x7FFF) == 0x0000;
#endif
}
/*
* Convert a half to a float4
*/
static inline float
HalfToFloat4(half num)
{
#if defined(F16C_SUPPORT)
return _cvtsh_ss(num);
#elif defined(FLT16_SUPPORT)
return (float) num;
#else
union
{
float f;
uint32 i;
} swapfloat;
union
{
half h;
uint16 i;
} swaphalf;
uint16 bin;
uint32 exponent;
uint32 mantissa;
uint32 result;
swaphalf.h = num;
bin = swaphalf.i;
exponent = (bin & 0x7C00) >> 10;
mantissa = bin & 0x03FF;
/* Sign */
result = (bin & 0x8000) << 16;
if (unlikely(exponent == 31))
{
if (mantissa == 0)
{
/* Infinite */
result |= 0x7F800000;
}
else
{
/* NaN */
result |= 0x7FC00000;
}
}
else if (unlikely(exponent == 0))
{
/* Subnormal */
if (mantissa != 0)
{
exponent = -14;
for (int i = 0; i < 10; i++)
{
mantissa <<= 1;
exponent -= 1;
if ((mantissa >> 10) % 2 == 1)
{
mantissa &= 0x03ff;
break;
}
}
result |= (exponent + 127) << 23;
}
}
else
{
/* Normal */
result |= (exponent - 15 + 127) << 23;
}
result |= mantissa << 13;
swapfloat.i = result;
return swapfloat.f;
#endif
}
/*
* Convert a float4 to a half
*/
static inline half
Float4ToHalfUnchecked(float num)
{
#if defined(F16C_SUPPORT)
return _cvtss_sh(num, 0);
#elif defined(FLT16_SUPPORT)
return (_Float16) num;
#else
union
{
float f;
uint32 i;
} swapfloat;
union
{
half h;
uint16 i;
} swaphalf;
uint32 bin;
int exponent;
int mantissa;
uint16 result;
swapfloat.f = num;
bin = swapfloat.i;
exponent = (bin & 0x7F800000) >> 23;
mantissa = bin & 0x007FFFFF;
/* Sign */
result = (bin & 0x80000000) >> 16;
if (isinf(num))
{
/* Infinite */
result |= 0x7C00;
}
else if (isnan(num))
{
/* NaN */
result |= 0x7E00;
result |= mantissa >> 13;
}
else if (exponent > 98)
{
int m;
int gr;
int s;
exponent -= 127;
s = mantissa & 0x00000FFF;
/* Subnormal */
if (exponent < -14)
{
int diff = -exponent - 14;
mantissa >>= diff;
mantissa += 1 << (23 - diff);
s |= mantissa & 0x00000FFF;
}
m = mantissa >> 13;
/* Round */
gr = (mantissa >> 12) % 4;
if (gr == 3 || (gr == 1 && s != 0))
m += 1;
if (m == 1024)
{
m = 0;
exponent += 1;
}
if (exponent > 15)
{
/* Infinite */
result |= 0x7C00;
}
else
{
if (exponent >= -14)
result |= (exponent + 15) << 10;
result |= m;
}
}
swaphalf.i = result;
return swaphalf.h;
#endif
}
/*
* Convert a float4 to a half
*/
static inline half
Float4ToHalf(float num)
{
half result = Float4ToHalfUnchecked(num);
if (unlikely(HalfIsInf(result)) && !isinf(num))
{
char *buf = palloc(FLOAT_SHORTEST_DECIMAL_LEN);
float_to_shortest_decimal_buf(num, buf);
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type halfvec", buf)));
}
return result;
}
#endif

1212
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70
src/halfvec.h Normal file
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@@ -0,0 +1,70 @@
#ifndef HALFVEC_H
#define HALFVEC_H
#define __STDC_WANT_IEC_60559_TYPES_EXT__
#include <float.h>
/* We use two types of dispatching: intrinsics and target_clones */
/* TODO Move to better place */
#ifndef DISABLE_DISPATCH
/* Only enable for more recent compilers to keep build process simple */
#if defined(__x86_64__) && defined(__GNUC__) && __GNUC__ >= 9
#define USE_DISPATCH
#elif defined(__x86_64__) && defined(__clang_major__) && __clang_major__ >= 7
#define USE_DISPATCH
#elif defined(_M_AMD64) && defined(_MSC_VER) && _MSC_VER >= 1920
#define USE_DISPATCH
#endif
#endif
/* target_clones requires glibc */
#if defined(USE_DISPATCH) && defined(__gnu_linux__) && defined(__has_attribute)
/* Use separate line for portability */
#if __has_attribute(target_clones)
#define USE_TARGET_CLONES
#endif
#endif
/* Apple clang check needed for universal binaries on Mac */
#if defined(USE_DISPATCH) && (defined(HAVE__GET_CPUID) || defined(__apple_build_version__))
#define USE__GET_CPUID
#endif
#if defined(USE_DISPATCH)
#define HALFVEC_DISPATCH
#endif
/* F16C has better performance than _Float16 (on x86-64) */
#if defined(__F16C__)
#define F16C_SUPPORT
#elif defined(__FLT16_MAX__) && !defined(HALFVEC_DISPATCH) && !defined(__FreeBSD__)
#define FLT16_SUPPORT
#endif
#ifdef FLT16_SUPPORT
#define half _Float16
#define HALF_MAX FLT16_MAX
#else
#define half uint16
#define HALF_MAX 65504
#endif
#define HALFVEC_MAX_DIM 16000
#define HALFVEC_SIZE(_dim) (offsetof(HalfVector, x) + sizeof(half)*(_dim))
#define DatumGetHalfVector(x) ((HalfVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_HALFVEC_P(x) DatumGetHalfVector(PG_GETARG_DATUM(x))
#define PG_RETURN_HALFVEC_P(x) PG_RETURN_POINTER(x)
typedef struct HalfVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int16 dim; /* number of dimensions */
int16 unused; /* reserved for future use, always zero */
half x[FLEXIBLE_ARRAY_MEMBER];
} HalfVector;
HalfVector *InitHalfVector(int dim);
#endif

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@@ -4,25 +4,59 @@
#include <math.h>
#include "access/amapi.h"
#include "access/reloptions.h"
#include "commands/progress.h"
#include "commands/vacuum.h"
#include "hnsw.h"
#include "miscadmin.h"
#include "utils/guc.h"
#include "utils/selfuncs.h"
#if PG_VERSION_NUM >= 120000
#include "commands/progress.h"
#if PG_VERSION_NUM < 150000
#define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
#endif
int hnsw_ef_search;
bool hnsw_enable_parallel_build;
int hnsw_lock_tranche_id;
static relopt_kind hnsw_relopt_kind;
/*
* Assign a tranche ID for our LWLocks. This only needs to be done by one
* backend, as the tranche ID is remembered in shared memory.
*
* This shared memory area is very small, so we just allocate it from the
* "slop" that PostgreSQL reserves for small allocations like this. If
* this grows bigger, we should use a shmem_request_hook and
* RequestAddinShmemSpace() to pre-reserve space for this.
*/
void
HnswInitLockTranche(void)
{
int *tranche_ids;
bool found;
LWLockAcquire(AddinShmemInitLock, LW_EXCLUSIVE);
tranche_ids = ShmemInitStruct("hnsw LWLock ids",
sizeof(int) * 1,
&found);
if (!found)
tranche_ids[0] = LWLockNewTrancheId();
hnsw_lock_tranche_id = tranche_ids[0];
LWLockRelease(AddinShmemInitLock);
/* Per-backend registration of the tranche ID */
LWLockRegisterTranche(hnsw_lock_tranche_id, "HnswBuild");
}
/*
* Initialize index options and variables
*/
void
HnswInit(void)
{
if (!process_shared_preload_libraries_in_progress)
HnswInitLockTranche();
hnsw_relopt_kind = add_reloption_kind();
add_int_reloption(hnsw_relopt_kind, "m", "Max number of connections",
HNSW_DEFAULT_M, HNSW_MIN_M, HNSW_MAX_M
@@ -41,16 +75,12 @@ HnswInit(void)
"Valid range is 1..1000.", &hnsw_ef_search,
HNSW_DEFAULT_EF_SEARCH, HNSW_MIN_EF_SEARCH, HNSW_MAX_EF_SEARCH, PGC_USERSET, 0, NULL, NULL, NULL);
/* Behind a variable for now since can be slower than building in memory */
DefineCustomBoolVariable("hnsw.enable_parallel_build", "Enables or disables building indexes in parallel",
NULL, &hnsw_enable_parallel_build,
false, PGC_USERSET, 0, NULL, NULL, NULL);
MarkGUCPrefixReserved("hnsw");
}
/*
* Get the name of index build phase
*/
#if PG_VERSION_NUM >= 120000
static char *
hnswbuildphasename(int64 phasenum)
{
@@ -64,7 +94,6 @@ hnswbuildphasename(int64 phasenum)
return NULL;
}
}
#endif
/*
* Estimate the cost of an index scan
@@ -79,9 +108,6 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
int m;
int entryLevel;
Relation index;
#if PG_VERSION_NUM < 120000
List *qinfos;
#endif
/* Never use index without order */
if (path->indexorderbys == NULL)
@@ -107,12 +133,7 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
/* Account for number of tuples (or entry level), m, and ef_search */
costs.numIndexTuples = (entryLevel + 2) * m;
#if PG_VERSION_NUM >= 120000
genericcostestimate(root, path, loop_count, &costs);
#else
qinfos = deconstruct_indexquals(path);
genericcostestimate(root, path, loop_count, qinfos, &costs);
#endif
/* Use total cost since most work happens before first tuple is returned */
*indexStartupCost = costs.indexTotalCost;
@@ -166,14 +187,14 @@ hnswvalidate(Oid opclassoid)
*
* See https://www.postgresql.org/docs/current/index-api.html
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(hnswhandler);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnswhandler);
Datum
hnswhandler(PG_FUNCTION_ARGS)
{
IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0;
amroutine->amsupport = 2;
amroutine->amsupport = 3;
#if PG_VERSION_NUM >= 130000
amroutine->amoptsprocnum = 0;
#endif
@@ -206,9 +227,7 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amcostestimate = hnswcostestimate;
amroutine->amoptions = hnswoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
#if PG_VERSION_NUM >= 120000
amroutine->ambuildphasename = hnswbuildphasename;
#endif
amroutine->amvalidate = hnswvalidate;
#if PG_VERSION_NUM >= 140000
amroutine->amadjustmembers = NULL;

View File

@@ -3,27 +3,22 @@
#include "postgres.h"
#include "access/generic_xlog.h"
#include "access/genam.h"
#include "access/parallel.h"
#include "access/reloptions.h"
#include "lib/pairingheap.h"
#include "nodes/execnodes.h"
#include "port.h" /* for random() */
#include "utils/relptr.h"
#include "utils/sampling.h"
#include "vector.h"
#if PG_VERSION_NUM < 110000
#error "Requires PostgreSQL 11+"
#endif
#if PG_VERSION_NUM < 120000
#include "access/relscan.h"
#endif
#define HNSW_MAX_DIM 2000
#define HNSW_MAX_NNZ 1000
/* Support functions */
#define HNSW_DISTANCE_PROC 1
#define HNSW_NORM_PROC 2
#define HNSW_TYPE_INFO_PROC 3
#define HNSW_VERSION 1
#define HNSW_MAGIC_NUMBER 0xA953A953
@@ -63,22 +58,27 @@
#define PROGRESS_HNSW_PHASE_LOAD 2
#define HNSW_MAX_SIZE (BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - sizeof(ItemIdData))
#define HNSW_TUPLE_ALLOC_SIZE BLCKSZ
#define HNSW_ELEMENT_TUPLE_SIZE(size) MAXALIGN(offsetof(HnswElementTupleData, data) + (size))
#define HNSW_NEIGHBOR_TUPLE_SIZE(level, m) MAXALIGN(offsetof(HnswNeighborTupleData, indextids) + ((level) + 2) * (m) * sizeof(ItemPointerData))
#define HNSW_NEIGHBOR_ARRAY_SIZE(lm) (offsetof(HnswNeighborArray, items) + sizeof(HnswCandidate) * (lm))
#define HnswPageGetOpaque(page) ((HnswPageOpaque) PageGetSpecialPointer(page))
#define HnswPageGetMeta(page) ((HnswMetaPageData *) PageGetContents(page))
#if PG_VERSION_NUM >= 150000
#define RandomDouble() pg_prng_double(&pg_global_prng_state)
#define SeedRandom(seed) pg_prng_seed(&pg_global_prng_state, seed)
#else
#define RandomDouble() (((double) random()) / MAX_RANDOM_VALUE)
#define SeedRandom(seed) srandom(seed)
#endif
#if PG_VERSION_NUM < 130000
#define list_delete_last(list) list_truncate(list, list_length(list) - 1)
#define list_sort(list, cmp) list_qsort(list, cmp)
#define list_sort(list, cmp) ((list) = list_qsort(list, cmp))
#endif
#define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
@@ -91,42 +91,74 @@
#define HnswGetMl(m) (1 / log(m))
/* Ensure fits on page and in uint8 */
#define HnswGetMaxLevel(m) Min(((BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - offsetof(HnswNeighborTupleData, indextids) - sizeof(ItemIdData)) / (sizeof(ItemPointerData)) / m) - 2, 255)
#define HnswGetMaxLevel(m) Min(((BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - offsetof(HnswNeighborTupleData, indextids) - sizeof(ItemIdData)) / (sizeof(ItemPointerData)) / (m)) - 2, 255)
#define HnswGetValue(base, element) PointerGetDatum(HnswPtrAccess(base, (element)->value))
#if PG_VERSION_NUM < 140005
#define relptr_offset(rp) ((rp).relptr_off - 1)
#endif
/* Pointer macros */
#define HnswPtrAccess(base, hp) ((base) == NULL ? (hp).ptr : relptr_access(base, (hp).relptr))
#define HnswPtrStore(base, hp, value) ((base) == NULL ? (void) ((hp).ptr = (value)) : (void) relptr_store(base, (hp).relptr, value))
#define HnswPtrIsNull(base, hp) ((base) == NULL ? (hp).ptr == NULL : relptr_is_null((hp).relptr))
#define HnswPtrEqual(base, hp1, hp2) ((base) == NULL ? (hp1).ptr == (hp2).ptr : relptr_offset((hp1).relptr) == relptr_offset((hp2).relptr))
/* For code paths dedicated to each type */
#define HnswPtrPointer(hp) (hp).ptr
#define HnswPtrOffset(hp) relptr_offset((hp).relptr)
/* Variables */
extern int hnsw_ef_search;
extern bool hnsw_enable_parallel_build;
extern int hnsw_lock_tranche_id;
typedef struct HnswElementData HnswElementData;
typedef struct HnswNeighborArray HnswNeighborArray;
typedef struct HnswElementData
#define HnswPtrDeclare(type, relptrtype, ptrtype) \
relptr_declare(type, relptrtype); \
typedef union { type *ptr; relptrtype relptr; } ptrtype;
/* Pointers that can be absolute or relative */
/* Use char for DatumPtr so works with Pointer */
HnswPtrDeclare(HnswElementData, HnswElementRelptr, HnswElementPtr);
HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr);
HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
HnswPtrDeclare(char, DatumRelptr, DatumPtr);
struct HnswElementData
{
List *heaptids;
HnswElementPtr next;
ItemPointerData heaptids[HNSW_HEAPTIDS];
uint8 heaptidsLength;
uint8 level;
uint8 deleted;
HnswNeighborArray *neighbors;
uint32 hash;
HnswNeighborsPtr neighbors;
BlockNumber blkno;
OffsetNumber offno;
OffsetNumber neighborOffno;
BlockNumber neighborPage;
Datum value;
} HnswElementData;
DatumPtr value;
LWLock lock;
};
typedef HnswElementData * HnswElement;
typedef struct HnswCandidate
{
HnswElement element;
HnswElementPtr element;
float distance;
bool closer;
} HnswCandidate;
typedef struct HnswNeighborArray
struct HnswNeighborArray
{
int length;
bool closerSet;
HnswCandidate *items;
} HnswNeighborArray;
HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
};
typedef struct HnswPairingHeapNode
{
@@ -142,11 +174,27 @@ typedef struct HnswOptions
int efConstruction; /* size of dynamic candidate list */
} HnswOptions;
typedef struct HnswSpool
typedef struct HnswGraph
{
Relation heap;
Relation index;
} HnswSpool;
/* Graph state */
slock_t lock;
HnswElementPtr head;
double indtuples;
/* Entry state */
LWLock entryLock;
LWLock entryWaitLock;
HnswElementPtr entryPoint;
/* Allocations state */
LWLock allocatorLock;
long memoryUsed;
long memoryTotal;
/* Flushed state */
LWLock flushLock;
bool flushed;
} HnswGraph;
typedef struct HnswShared
{
@@ -154,7 +202,6 @@ typedef struct HnswShared
Oid heaprelid;
Oid indexrelid;
bool isconcurrent;
int scantuplesortstates;
/* Worker progress */
ConditionVariable workersdonecv;
@@ -165,17 +212,11 @@ typedef struct HnswShared
/* Mutable state */
int nparticipantsdone;
double reltuples;
double indtuples;
#if PG_VERSION_NUM < 120000
ParallelHeapScanDescData heapdesc; /* must come last */
#endif
HnswGraph graphData;
} HnswShared;
#if PG_VERSION_NUM >= 120000
#define ParallelTableScanFromHnswShared(shared) \
(ParallelTableScanDesc) ((char *) (shared) + BUFFERALIGN(sizeof(HnswShared)))
#endif
typedef struct HnswLeader
{
@@ -183,8 +224,22 @@ typedef struct HnswLeader
int nparticipanttuplesorts;
HnswShared *hnswshared;
Snapshot snapshot;
char *hnswarea;
} HnswLeader;
typedef struct HnswAllocator
{
void *(*alloc) (Size size, void *state);
void *state;
} HnswAllocator;
typedef struct HnswTypeInfo
{
int maxDimensions;
Datum (*normalize) (PG_FUNCTION_ARGS);
void (*checkValue) (Pointer v);
} HnswTypeInfo;
typedef struct HnswBuildState
{
/* Info */
@@ -192,6 +247,7 @@ typedef struct HnswBuildState
Relation index;
IndexInfo *indexInfo;
ForkNumber forkNum;
const HnswTypeInfo *typeInfo;
/* Settings */
int dimensions;
@@ -208,20 +264,20 @@ typedef struct HnswBuildState
Oid collation;
/* Variables */
List *elements;
HnswElement entryPoint;
HnswGraph graphData;
HnswGraph *graph;
double ml;
int maxLevel;
long memoryLeft;
bool flushed;
Vector *normvec;
/* Memory */
MemoryContext graphCtx;
MemoryContext tmpCtx;
HnswAllocator allocator;
/* Parallel builds */
HnswLeader *hnswleader;
HnswShared *hnswshared;
char *hnswarea;
} HnswBuildState;
typedef struct HnswMetaPageData
@@ -274,6 +330,7 @@ typedef HnswNeighborTupleData * HnswNeighborTuple;
typedef struct HnswScanOpaqueData
{
const HnswTypeInfo *typeInfo;
bool first;
List *w;
MemoryContext tmpCtx;
@@ -303,7 +360,7 @@ typedef struct HnswVacuumState
Oid collation;
/* Variables */
HTAB *deleted;
struct tidhash_hash *deleted;
BufferAccessStrategy bas;
HnswNeighborTuple ntup;
HnswElementData highestPoint;
@@ -316,32 +373,32 @@ typedef struct HnswVacuumState
int HnswGetM(Relation index);
int HnswGetEfConstruction(Relation index);
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
void HnswCommitBuffer(Buffer buf, GenericXLogState *state);
Datum HnswNormValue(const HnswTypeInfo * typeInfo, Oid collation, Datum value);
bool HnswCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value);
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
void HnswInitPage(Buffer buf, Page page);
void HnswInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state);
void HnswInit(void);
List *HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement);
List *HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement);
HnswElement HnswGetEntryPoint(Relation index);
void HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint);
HnswElement HnswInitElement(ItemPointer tid, int m, double ml, int maxLevel);
void HnswFreeElement(HnswElement element);
void *HnswAlloc(HnswAllocator * allocator, Size size);
HnswElement HnswInitElement(char *base, ItemPointer tid, int m, double ml, int maxLevel, HnswAllocator * alloc);
HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno);
void HnswInsertElement(HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing);
HnswElement HnswFindDuplicate(HnswElement e);
HnswCandidate *HnswEntryCandidate(HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum);
void HnswSetNeighborTuple(HnswNeighborTuple ntup, HnswElement e, int m);
void HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing);
HnswCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum, bool building);
void HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m);
void HnswAddHeapTid(HnswElement element, ItemPointer heaptid);
void HnswInitNeighbors(HnswElement element, int m);
bool HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel);
void HnswUpdateNeighborPages(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting);
void HnswInitNeighbors(char *base, HnswElement element, int m, HnswAllocator * alloc);
bool HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building);
void HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building);
void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec);
void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswSetElementTuple(HnswElementTuple etup, HnswElement element);
void HnswUpdateConnection(HnswElement element, HnswCandidate * hc, int m, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance);
void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element);
void HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
void HnswLoadNeighbors(HnswElement element, Relation index, int m);
void HnswInitLockTranche(void);
const HnswTypeInfo *HnswGetTypeInfo(Relation index);
PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);
/* Index access methods */
@@ -360,4 +417,54 @@ void hnswrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys,
bool hnswgettuple(IndexScanDesc scan, ScanDirection dir);
void hnswendscan(IndexScanDesc scan);
static inline HnswNeighborArray *
HnswGetNeighbors(char *base, HnswElement element, int lc)
{
HnswNeighborArrayPtr *neighborList = HnswPtrAccess(base, element->neighbors);
Assert(element->level >= lc);
return HnswPtrAccess(base, neighborList[lc]);
}
/* Hash tables */
typedef struct TidHashEntry
{
ItemPointerData tid;
char status;
} TidHashEntry;
#define SH_PREFIX tidhash
#define SH_ELEMENT_TYPE TidHashEntry
#define SH_KEY_TYPE ItemPointerData
#define SH_SCOPE extern
#define SH_DECLARE
#include "lib/simplehash.h"
typedef struct PointerHashEntry
{
uintptr_t ptr;
char status;
} PointerHashEntry;
#define SH_PREFIX pointerhash
#define SH_ELEMENT_TYPE PointerHashEntry
#define SH_KEY_TYPE uintptr_t
#define SH_SCOPE extern
#define SH_DECLARE
#include "lib/simplehash.h"
typedef struct OffsetHashEntry
{
Size offset;
char status;
} OffsetHashEntry;
#define SH_PREFIX offsethash
#define SH_ELEMENT_TYPE OffsetHashEntry
#define SH_KEY_TYPE Size
#define SH_SCOPE extern
#define SH_DECLARE
#include "lib/simplehash.h"
#endif

File diff suppressed because it is too large Load Diff

View File

@@ -2,9 +2,11 @@
#include <math.h>
#include "access/generic_xlog.h"
#include "hnsw.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
#include "utils/datum.h"
#include "utils/memutils.h"
/*
@@ -34,14 +36,15 @@ GetInsertPage(Relation index)
* Check for a free offset
*/
static bool
HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size ntupSize, Buffer *nbuf, Page *npage, OffsetNumber *freeOffno, OffsetNumber *freeNeighborOffno, BlockNumber *newInsertPage)
HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size etupSize, Size ntupSize, Buffer *nbuf, Page *npage, OffsetNumber *freeOffno, OffsetNumber *freeNeighborOffno, BlockNumber *newInsertPage)
{
OffsetNumber offno;
OffsetNumber maxoffno = PageGetMaxOffsetNumber(page);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
ItemId eitemid = PageGetItemId(page, offno);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, eitemid);
/* Skip neighbor tuples */
if (!HnswIsElementTuple(etup))
@@ -52,7 +55,9 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
BlockNumber elementPage = BufferGetBlockNumber(buf);
BlockNumber neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
OffsetNumber neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
ItemId itemid;
ItemId nitemid;
Size pageFree;
Size npageFree;
if (!BlockNumberIsValid(*newInsertPage))
*newInsertPage = elementPage;
@@ -71,10 +76,25 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
*npage = BufferGetPage(*nbuf);
}
itemid = PageGetItemId(*npage, neighborOffno);
nitemid = PageGetItemId(*npage, neighborOffno);
/* Check for space on neighbor tuple page */
if (PageGetFreeSpace(*npage) + ItemIdGetLength(itemid) - sizeof(ItemIdData) >= ntupSize)
/* Ensure aligned for space check */
Assert(etupSize == MAXALIGN(etupSize));
Assert(ntupSize == MAXALIGN(ntupSize));
/*
* Calculate free space individually since tuples are overwritten
* individually (in separate calls to PageIndexTupleOverwrite)
*/
pageFree = ItemIdGetLength(eitemid) + PageGetExactFreeSpace(page);
npageFree = ItemIdGetLength(nitemid);
if (neighborPage != elementPage)
npageFree += PageGetExactFreeSpace(*npage);
else if (pageFree >= etupSize)
npageFree += pageFree - etupSize;
/* Check for space */
if (pageFree >= etupSize && npageFree >= ntupSize)
{
*freeOffno = offno;
*freeNeighborOffno = neighborOffno;
@@ -92,7 +112,7 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
* Add a new page
*/
static void
HnswInsertAppendPage(Relation index, Buffer *nbuf, Page *npage, GenericXLogState *state, Page page)
HnswInsertAppendPage(Relation index, Buffer *nbuf, Page *npage, GenericXLogState *state, Page page, bool building)
{
/* Add a new page */
LockRelationForExtension(index, ExclusiveLock);
@@ -100,7 +120,11 @@ HnswInsertAppendPage(Relation index, Buffer *nbuf, Page *npage, GenericXLogState
UnlockRelationForExtension(index, ExclusiveLock);
/* Init new page */
*npage = GenericXLogRegisterBuffer(state, *nbuf, GENERIC_XLOG_FULL_IMAGE);
if (building)
*npage = BufferGetPage(*nbuf);
else
*npage = GenericXLogRegisterBuffer(state, *nbuf, GENERIC_XLOG_FULL_IMAGE);
HnswInitPage(*nbuf, *npage);
/* Update previous buffer */
@@ -111,7 +135,7 @@ HnswInsertAppendPage(Relation index, Buffer *nbuf, Page *npage, GenericXLogState
* Add to element and neighbor pages
*/
static void
WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPage, BlockNumber *updatedInsertPage)
AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, BlockNumber *updatedInsertPage, bool building)
{
Buffer buf;
Page page;
@@ -129,9 +153,10 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
OffsetNumber freeOffno = InvalidOffsetNumber;
OffsetNumber freeNeighborOffno = InvalidOffsetNumber;
BlockNumber newInsertPage = InvalidBlockNumber;
char *base = NULL;
/* Calculate sizes */
etupSize = HNSW_ELEMENT_TUPLE_SIZE(VARSIZE_ANY(DatumGetPointer(e->value)));
etupSize = HNSW_ELEMENT_TUPLE_SIZE(VARSIZE_ANY(HnswPtrAccess(base, e->value)));
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
maxSize = HNSW_MAX_SIZE;
@@ -139,11 +164,11 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
/* Prepare element tuple */
etup = palloc0(etupSize);
HnswSetElementTuple(etup, e);
HnswSetElementTuple(base, etup, e);
/* Prepare neighbor tuple */
ntup = palloc0(ntupSize);
HnswSetNeighborTuple(ntup, e, m);
HnswSetNeighborTuple(base, ntup, e, m);
/* Find a page (or two if needed) to insert the tuples */
for (;;)
@@ -151,8 +176,16 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
buf = ReadBuffer(index, currentPage);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
if (building)
{
state = NULL;
page = BufferGetPage(buf);
}
else
{
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
}
/* Keep track of first page where element at level 0 can fit */
if (!BlockNumberIsValid(newInsertPage) && PageGetFreeSpace(page) >= minCombinedSize)
@@ -169,10 +202,15 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
}
/* Next, try space from a deleted element */
if (HnswFreeOffset(index, buf, page, e, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage))
if (HnswFreeOffset(index, buf, page, e, etupSize, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage))
{
if (nbuf != buf)
npage = GenericXLogRegisterBuffer(state, nbuf, 0);
{
if (building)
npage = BufferGetPage(nbuf);
else
npage = GenericXLogRegisterBuffer(state, nbuf, 0);
}
break;
}
@@ -181,7 +219,7 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
/* Skip if both tuples can fit on the same page */
if (combinedSize > maxSize && PageGetFreeSpace(page) >= etupSize && !BlockNumberIsValid(HnswPageGetOpaque(page)->nextblkno))
{
HnswInsertAppendPage(index, &nbuf, &npage, state, page);
HnswInsertAppendPage(index, &nbuf, &npage, state, page, building);
break;
}
@@ -190,7 +228,8 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
if (BlockNumberIsValid(currentPage))
{
/* Move to next page */
GenericXLogAbort(state);
if (!building)
GenericXLogAbort(state);
UnlockReleaseBuffer(buf);
}
else
@@ -198,22 +237,33 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
Buffer newbuf;
Page newpage;
HnswInsertAppendPage(index, &newbuf, &newpage, state, page);
HnswInsertAppendPage(index, &newbuf, &newpage, state, page, building);
/* Commit */
GenericXLogFinish(state);
if (building)
MarkBufferDirty(buf);
else
GenericXLogFinish(state);
/* Unlock previous buffer */
UnlockReleaseBuffer(buf);
/* Prepare new buffer */
state = GenericXLogStart(index);
buf = newbuf;
page = GenericXLogRegisterBuffer(state, buf, 0);
if (building)
{
state = NULL;
page = BufferGetPage(buf);
}
else
{
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
}
/* Create new page for neighbors if needed */
if (PageGetFreeSpace(page) < combinedSize)
HnswInsertAppendPage(index, &nbuf, &npage, state, page);
HnswInsertAppendPage(index, &nbuf, &npage, state, page, building);
else
{
nbuf = buf;
@@ -267,7 +317,14 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
}
/* Commit */
GenericXLogFinish(state);
if (building)
{
MarkBufferDirty(buf);
if (nbuf != buf)
MarkBufferDirty(nbuf);
}
else
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
if (nbuf != buf)
UnlockReleaseBuffer(nbuf);
@@ -301,12 +358,14 @@ ConnectionExists(HnswElement e, HnswNeighborTuple ntup, int startIdx, int lm)
* Update neighbors
*/
void
HnswUpdateNeighborPages(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting)
HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building)
{
char *base = NULL;
for (int lc = e->level; lc >= 0; lc--)
{
int lm = HnswGetLayerM(m, lc);
HnswNeighborArray *neighbors = &e->neighbors[lc];
HnswNeighborArray *neighbors = HnswGetNeighbors(base, e, lc);
for (int i = 0; i < neighbors->length; i++)
{
@@ -314,16 +373,15 @@ HnswUpdateNeighborPages(Relation index, FmgrInfo *procinfo, Oid collation, HnswE
Buffer buf;
Page page;
GenericXLogState *state;
ItemId itemid;
HnswNeighborTuple ntup;
Size ntupSize;
int idx = -1;
int startIdx;
OffsetNumber offno = hc->element->neighborOffno;
HnswElement neighborElement = HnswPtrAccess(base, hc->element);
OffsetNumber offno = neighborElement->neighborOffno;
/* Get latest neighbors since they may have changed */
/* Do not lock yet since selecting neighbors can take time */
HnswLoadNeighbors(hc->element, index, m);
HnswLoadNeighbors(neighborElement, index, m);
/*
* Could improve performance for vacuuming by checking neighbors
@@ -333,25 +391,31 @@ HnswUpdateNeighborPages(Relation index, FmgrInfo *procinfo, Oid collation, HnswE
*/
/* Select neighbors */
HnswUpdateConnection(e, hc, lm, lc, &idx, index, procinfo, collation);
HnswUpdateConnection(NULL, e, hc, lm, lc, &idx, index, procinfo, collation);
/* New element was not selected as a neighbor */
if (idx == -1)
continue;
/* Register page */
buf = ReadBuffer(index, hc->element->neighborPage);
buf = ReadBuffer(index, neighborElement->neighborPage);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
if (building)
{
state = NULL;
page = BufferGetPage(buf);
}
else
{
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
}
/* Get tuple */
itemid = PageGetItemId(page, offno);
ntup = (HnswNeighborTuple) PageGetItem(page, itemid);
ntupSize = ItemIdGetLength(itemid);
ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, offno));
/* Calculate index for update */
startIdx = (hc->element->level - lc) * m;
startIdx = (neighborElement->level - lc) * m;
/* Check for existing connection */
if (checkExisting && ConnectionExists(e, ntup, startIdx, lm))
@@ -377,17 +441,16 @@ HnswUpdateNeighborPages(Relation index, FmgrInfo *procinfo, Oid collation, HnswE
{
ItemPointer indextid = &ntup->indextids[idx];
/* Update neighbor */
/* Update neighbor on the buffer */
ItemPointerSet(indextid, e->blkno, e->offno);
/* Overwrite tuple */
if (!PageIndexTupleOverwrite(page, offno, (Item) ntup, ntupSize))
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Commit */
GenericXLogFinish(state);
if (building)
MarkBufferDirty(buf);
else
GenericXLogFinish(state);
}
else
else if (!building)
GenericXLogAbort(state);
UnlockReleaseBuffer(buf);
@@ -399,26 +462,30 @@ HnswUpdateNeighborPages(Relation index, FmgrInfo *procinfo, Oid collation, HnswE
* Add a heap TID to an existing element
*/
static bool
HnswAddDuplicate(Relation index, HnswElement element, HnswElement dup)
AddDuplicateOnDisk(Relation index, HnswElement element, HnswElement dup, bool building)
{
Buffer buf;
Page page;
GenericXLogState *state;
ItemId itemid;
HnswElementTuple etup;
Size etupSize;
int i;
/* Read page */
buf = ReadBuffer(index, dup->blkno);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
if (building)
{
state = NULL;
page = BufferGetPage(buf);
}
else
{
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
}
/* Find space */
itemid = PageGetItemId(page, dup->offno);
etup = (HnswElementTuple) PageGetItem(page, itemid);
etupSize = ItemIdGetLength(itemid);
etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, dup->offno));
for (i = 0; i < HNSW_HEAPTIDS; i++)
{
if (!ItemPointerIsValid(&etup->heaptids[i]))
@@ -428,82 +495,93 @@ HnswAddDuplicate(Relation index, HnswElement element, HnswElement dup)
/* Either being deleted or we lost our chance to another backend */
if (i == 0 || i == HNSW_HEAPTIDS)
{
GenericXLogAbort(state);
if (!building)
GenericXLogAbort(state);
UnlockReleaseBuffer(buf);
return false;
}
/* Add heap TID */
etup->heaptids[i] = *((ItemPointer) linitial(element->heaptids));
/* Overwrite tuple */
if (!PageIndexTupleOverwrite(page, dup->offno, (Item) etup, etupSize))
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Add heap TID, modifying the tuple on the page directly */
etup->heaptids[i] = element->heaptids[0];
/* Commit */
GenericXLogFinish(state);
if (building)
MarkBufferDirty(buf);
else
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
return true;
}
/*
* Write changes to disk
* Find duplicate element
*/
static bool
FindDuplicateOnDisk(Relation index, HnswElement element, bool building)
{
char *base = NULL;
HnswNeighborArray *neighbors = HnswGetNeighbors(base, element, 0);
Datum value = HnswGetValue(base, element);
for (int i = 0; i < neighbors->length; i++)
{
HnswCandidate *neighbor = &neighbors->items[i];
HnswElement neighborElement = HnswPtrAccess(base, neighbor->element);
Datum neighborValue = HnswGetValue(base, neighborElement);
/* Exit early since ordered by distance */
if (!datumIsEqual(value, neighborValue, false, -1))
return false;
if (AddDuplicateOnDisk(index, element, neighborElement, building))
return true;
}
return false;
}
/*
* Update graph on disk
*/
static void
WriteElement(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement element, int m, int efConstruction, HnswElement dup, HnswElement entryPoint)
UpdateGraphOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement element, int m, int efConstruction, HnswElement entryPoint, bool building)
{
BlockNumber newInsertPage = InvalidBlockNumber;
/* Try to add to existing page */
if (dup != NULL)
{
if (HnswAddDuplicate(index, element, dup))
return;
}
/* Look for duplicate */
if (FindDuplicateOnDisk(index, element, building))
return;
/* Write element and neighbor tuples */
WriteNewElementPages(index, element, m, GetInsertPage(index), &newInsertPage);
/* Add element */
AddElementOnDisk(index, element, m, GetInsertPage(index), &newInsertPage, building);
/* Update insert page if needed */
if (BlockNumberIsValid(newInsertPage))
HnswUpdateMetaPage(index, 0, NULL, newInsertPage, MAIN_FORKNUM);
HnswUpdateMetaPage(index, 0, NULL, newInsertPage, MAIN_FORKNUM, building);
/* Update neighbors */
HnswUpdateNeighborPages(index, procinfo, collation, element, m, false);
HnswUpdateNeighborsOnDisk(index, procinfo, collation, element, m, false, building);
/* Update metapage if needed */
/* Update entry point if needed */
if (entryPoint == NULL || element->level > entryPoint->level)
HnswUpdateMetaPage(index, HNSW_UPDATE_ENTRY_GREATER, element, InvalidBlockNumber, MAIN_FORKNUM);
HnswUpdateMetaPage(index, HNSW_UPDATE_ENTRY_GREATER, element, InvalidBlockNumber, MAIN_FORKNUM, building);
}
/*
* Insert a tuple into the index
*/
bool
HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building)
{
Datum value;
FmgrInfo *normprocinfo;
HnswElement entryPoint;
HnswElement element;
int m;
int efConstruction = HnswGetEfConstruction(index);
FmgrInfo *procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
Oid collation = index->rd_indcollation[0];
HnswElement dup;
LOCKMODE lockmode = ShareLock;
/* Detoast once for all calls */
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Normalize if needed */
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
if (normprocinfo != NULL)
{
if (!HnswNormValue(normprocinfo, collation, &value, NULL))
return false;
}
char *base = NULL;
/*
* Get a shared lock. This allows vacuum to ensure no in-flight inserts
@@ -516,8 +594,8 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
HnswGetMetaPageInfo(index, &m, &entryPoint);
/* Create an element */
element = HnswInitElement(heap_tid, m, HnswGetMl(m), HnswGetMaxLevel(m));
element->value = value;
element = HnswInitElement(base, heap_tid, m, HnswGetMl(m), HnswGetMaxLevel(m), NULL);
HnswPtrStore(base, element->value, DatumGetPointer(value));
/* Prevent concurrent inserts when likely updating entry point */
if (entryPoint == NULL || element->level > entryPoint->level)
@@ -533,14 +611,11 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
entryPoint = HnswGetEntryPoint(index);
}
/* Insert element in graph */
HnswInsertElement(element, entryPoint, index, procinfo, collation, m, efConstruction, false);
/* Find neighbors for element */
HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, false);
/* Look for duplicate */
dup = HnswFindDuplicate(element);
/* Write to disk */
WriteElement(index, procinfo, collation, element, m, efConstruction, dup, entryPoint);
/* Update graph on disk */
UpdateGraphOnDisk(index, procinfo, collation, element, m, efConstruction, entryPoint, building);
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
@@ -548,6 +623,37 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
return true;
}
/*
* Insert a tuple into the index
*/
static void
HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid)
{
Datum value;
const HnswTypeInfo *typeInfo = HnswGetTypeInfo(index);
FmgrInfo *normprocinfo;
Oid collation = index->rd_indcollation[0];
/* Detoast once for all calls */
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Check value */
if (typeInfo->checkValue != NULL)
typeInfo->checkValue(DatumGetPointer(value));
/* Normalize if needed */
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
if (normprocinfo != NULL)
{
if (!HnswCheckNorm(normprocinfo, collation, value))
return;
value = HnswNormValue(typeInfo, collation, value);
}
HnswInsertTupleOnDisk(index, value, values, isnull, heap_tid, false);
}
/*
* Insert a tuple into the index
*/
@@ -574,7 +680,7 @@ hnswinsert(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid,
oldCtx = MemoryContextSwitchTo(insertCtx);
/* Insert tuple */
HnswInsertTuple(index, values, isnull, heap_tid, heap);
HnswInsertTuple(index, values, isnull, heap_tid);
/* Delete memory context */
MemoryContextSwitchTo(oldCtx);

View File

@@ -21,6 +21,7 @@ GetScanItems(IndexScanDesc scan, Datum q)
List *w;
int m;
HnswElement entryPoint;
char *base = NULL;
/* Get m and entry point */
HnswGetMetaPageInfo(index, &m, &entryPoint);
@@ -28,38 +29,15 @@ GetScanItems(IndexScanDesc scan, Datum q)
if (entryPoint == NULL)
return NIL;
ep = list_make1(HnswEntryCandidate(entryPoint, q, index, procinfo, collation, false));
ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, procinfo, collation, false));
for (int lc = entryPoint->level; lc >= 1; lc--)
{
w = HnswSearchLayer(q, ep, 1, lc, index, procinfo, collation, m, false, NULL);
w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, false, NULL);
ep = w;
}
return HnswSearchLayer(q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
}
/*
* Get dimensions from metapage
*/
static int
GetDimensions(Relation index)
{
Buffer buf;
Page page;
HnswMetaPage metap;
int dimensions;
buf = ReadBuffer(index, HNSW_METAPAGE_BLKNO);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
metap = HnswPageGetMeta(page);
dimensions = metap->dimensions;
UnlockReleaseBuffer(buf);
return dimensions;
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
}
/*
@@ -72,7 +50,7 @@ GetScanValue(IndexScanDesc scan)
Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
value = PointerGetDatum(NULL);
else
{
value = scan->orderByData->sk_argument;
@@ -81,9 +59,9 @@ GetScanValue(IndexScanDesc scan)
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Fine if normalization fails */
/* Normalize if needed */
if (so->normprocinfo != NULL)
HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
value = HnswNormValue(so->typeInfo, so->collation, value);
}
return value;
@@ -101,6 +79,7 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
scan = RelationGetIndexScan(index, nkeys, norderbys);
so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData));
so->typeInfo = HnswGetTypeInfo(index);
so->first = true;
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw scan temporary context",
@@ -180,32 +159,32 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
so->first = false;
#if defined(HNSW_MEMORY) && PG_VERSION_NUM >= 130000
elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(so->tmpCtx, false) / (1024 * 1024));
#endif
}
while (list_length(so->w) > 0)
{
char *base = NULL;
HnswCandidate *hc = llast(so->w);
HnswElement element = HnswPtrAccess(base, hc->element);
ItemPointer heaptid;
/* Move to next element if no valid heap TIDs */
if (list_length(hc->element->heaptids) == 0)
if (element->heaptidsLength == 0)
{
so->w = list_delete_last(so->w);
continue;
}
heaptid = llast(hc->element->heaptids);
hc->element->heaptids = list_delete_last(hc->element->heaptids);
heaptid = &element->heaptids[--element->heaptidsLength];
MemoryContextSwitchTo(oldCtx);
#if PG_VERSION_NUM >= 120000
scan->xs_heaptid = *heaptid;
#else
scan->xs_ctup.t_self = *heaptid;
#endif
scan->xs_recheck = false;
scan->xs_recheckorderby = false;
return true;
}

File diff suppressed because it is too large Load Diff

View File

@@ -2,6 +2,7 @@
#include <math.h>
#include "access/generic_xlog.h"
#include "commands/vacuum.h"
#include "hnsw.h"
#include "storage/bufmgr.h"
@@ -12,12 +13,9 @@
* Check if deleted list contains an index TID
*/
static bool
DeletedContains(HTAB *deleted, ItemPointer indextid)
DeletedContains(tidhash_hash * deleted, ItemPointer indextid)
{
bool found;
hash_search(deleted, indextid, HASH_FIND, &found);
return found;
return tidhash_lookup(deleted, *indextid) != NULL;
}
/*
@@ -62,8 +60,7 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
/* Iterate over nodes */
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
ItemId itemid = PageGetItemId(page, offno);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, itemid);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
int idx = 0;
bool itemUpdated = false;
@@ -94,15 +91,10 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
if (itemUpdated)
{
Size etupSize = ItemIdGetLength(itemid);
/* Mark rest as invalid */
for (int i = idx; i < HNSW_HEAPTIDS; i++)
ItemPointerSetInvalid(&etup->heaptids[i]);
if (!PageIndexTupleOverwrite(page, offno, (Item) etup, etupSize))
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
updated = true;
}
}
@@ -110,11 +102,13 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
if (!ItemPointerIsValid(&etup->heaptids[0]))
{
ItemPointerData ip;
bool found;
/* Add to deleted list */
ItemPointerSet(&ip, blkno, offno);
(void) hash_search(vacuumstate->deleted, &ip, HASH_ENTER, NULL);
tidhash_insert(vacuumstate->deleted, ip, &found);
Assert(!found);
}
else if (etup->level > highestLevel && !(entryPoint != NULL && blkno == entryPoint->blkno && offno == entryPoint->offno))
{
@@ -200,21 +194,25 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
BufferAccessStrategy bas = vacuumstate->bas;
HnswNeighborTuple ntup = vacuumstate->ntup;
Size ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, m);
char *base = NULL;
/* Skip if element is entry point */
if (entryPoint != NULL && element->blkno == entryPoint->blkno && element->offno == entryPoint->offno)
return;
/* Init fields */
HnswInitNeighbors(element, m);
element->heaptids = NIL;
HnswInitNeighbors(base, element, m, NULL);
element->heaptidsLength = 0;
/* Add element to graph, skipping itself */
HnswInsertElement(element, entryPoint, index, procinfo, collation, m, efConstruction, true);
/* Find neighbors for element, skipping itself */
HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, true);
/* Zero memory for each element */
MemSet(ntup, 0, HNSW_TUPLE_ALLOC_SIZE);
/* Update neighbor tuple */
/* Do this before getting page to minimize locking */
HnswSetNeighborTuple(ntup, element, m);
HnswSetNeighborTuple(base, ntup, element, m);
/* Get neighbor page */
buf = ReadBufferExtended(index, MAIN_FORKNUM, element->neighborPage, RBM_NORMAL, bas);
@@ -231,7 +229,7 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
UnlockReleaseBuffer(buf);
/* Update neighbors */
HnswUpdateNeighborPages(index, procinfo, collation, element, m, true);
HnswUpdateNeighborsOnDisk(index, procinfo, collation, element, m, true, false);
}
/*
@@ -258,7 +256,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
LockPage(index, HNSW_UPDATE_LOCK, ShareLock);
/* Load element */
HnswLoadElement(highestPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true);
HnswLoadElement(highestPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true, NULL);
/* Repair if needed */
if (NeedsUpdated(vacuumstate, highestPoint))
@@ -287,7 +285,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
* point is outdated and empty, the entry point will be empty
* until an element is repaired.
*/
HnswUpdateMetaPage(index, HNSW_UPDATE_ENTRY_ALWAYS, highestPoint, InvalidBlockNumber, MAIN_FORKNUM);
HnswUpdateMetaPage(index, HNSW_UPDATE_ENTRY_ALWAYS, highestPoint, InvalidBlockNumber, MAIN_FORKNUM, false);
}
else
{
@@ -296,13 +294,13 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
* is outdated, this can remove connections at higher levels in
* the graph until they are repaired, but this should be fine.
*/
HnswLoadElement(entryPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true);
HnswLoadElement(entryPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true, NULL);
if (NeedsUpdated(vacuumstate, entryPoint))
{
/* Reset neighbors from previous update */
if (highestPoint != NULL)
highestPoint->neighbors = NULL;
HnswPtrStore((char *) NULL, highestPoint->neighbors, (HnswNeighborArrayPtr *) NULL);
RepairGraphElement(vacuumstate, entryPoint, highestPoint);
}
@@ -420,7 +418,7 @@ RepairGraph(HnswVacuumState * vacuumstate)
* was replaced and highest point was outdated.
*/
if (entryPoint == NULL || element->level > entryPoint->level)
HnswUpdateMetaPage(index, HNSW_UPDATE_ENTRY_GREATER, element, InvalidBlockNumber, MAIN_FORKNUM);
HnswUpdateMetaPage(index, HNSW_UPDATE_ENTRY_GREATER, element, InvalidBlockNumber, MAIN_FORKNUM, false);
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
@@ -478,11 +476,8 @@ MarkDeleted(HnswVacuumState * vacuumstate)
/* Update element and neighbors together */
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
ItemId itemid = PageGetItemId(page, offno);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, itemid);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
HnswNeighborTuple ntup;
Size etupSize;
Size ntupSize;
Buffer nbuf;
Page npage;
BlockNumber neighborPage;
@@ -506,10 +501,6 @@ MarkDeleted(HnswVacuumState * vacuumstate)
if (ItemPointerIsValid(&etup->heaptids[0]))
continue;
/* Calculate sizes */
etupSize = ItemIdGetLength(itemid);
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(etup->level, vacuumstate->m);
/* Get neighbor page */
neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
@@ -536,13 +527,10 @@ MarkDeleted(HnswVacuumState * vacuumstate)
for (int i = 0; i < ntup->count; i++)
ItemPointerSetInvalid(&ntup->indextids[i]);
/* Overwrite element tuple */
if (!PageIndexTupleOverwrite(page, offno, (Item) etup, etupSize))
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Overwrite neighbor tuple */
if (!PageIndexTupleOverwrite(npage, neighborOffno, (Item) ntup, ntupSize))
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/*
* We modified the tuples in place, no need to call
* PageIndexTupleOverwrite
*/
/* Commit */
GenericXLogFinish(state);
@@ -565,7 +553,7 @@ MarkDeleted(HnswVacuumState * vacuumstate)
}
/* Update insert page last, after everything has been marked as deleted */
HnswUpdateMetaPage(index, 0, NULL, insertPage, MAIN_FORKNUM);
HnswUpdateMetaPage(index, 0, NULL, insertPage, MAIN_FORKNUM, false);
}
/*
@@ -575,7 +563,6 @@ static void
InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkDeleteResult *stats, IndexBulkDeleteCallback callback, void *callback_state)
{
Relation index = info->index;
HASHCTL hash_ctl;
if (stats == NULL)
stats = (IndexBulkDeleteResult *) palloc0(sizeof(IndexBulkDeleteResult));
@@ -588,7 +575,7 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
vacuumstate->bas = GetAccessStrategy(BAS_BULKREAD);
vacuumstate->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
vacuumstate->collation = index->rd_indcollation[0];
vacuumstate->ntup = palloc0(BLCKSZ);
vacuumstate->ntup = palloc0(HNSW_TUPLE_ALLOC_SIZE);
vacuumstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw vacuum temporary context",
ALLOCSET_DEFAULT_SIZES);
@@ -597,10 +584,7 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
HnswGetMetaPageInfo(index, &vacuumstate->m, NULL);
/* Create hash table */
hash_ctl.keysize = sizeof(ItemPointerData);
hash_ctl.entrysize = sizeof(ItemPointerData);
hash_ctl.hcxt = CurrentMemoryContext;
vacuumstate->deleted = hash_create("hnswbulkdelete indextids", 256, &hash_ctl, HASH_ELEM | HASH_BLOBS | HASH_CONTEXT);
vacuumstate->deleted = tidhash_create(CurrentMemoryContext, 256, NULL);
}
/*
@@ -609,7 +593,7 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
static void
FreeVacuumState(HnswVacuumState * vacuumstate)
{
hash_destroy(vacuumstate->deleted);
tidhash_destroy(vacuumstate->deleted);
FreeAccessStrategy(vacuumstate->bas);
pfree(vacuumstate->ntup);
MemoryContextDelete(vacuumstate->tmpCtx);

View File

@@ -2,30 +2,28 @@
#include <float.h>
#include "access/table.h"
#include "access/tableam.h"
#include "access/parallel.h"
#include "access/xact.h"
#include "bitvec.h"
#include "catalog/index.h"
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
#include "commands/progress.h"
#include "halfvec.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "optimizer/optimizer.h"
#include "storage/bufmgr.h"
#include "tcop/tcopprot.h"
#include "utils/memutils.h"
#include "vector.h"
#if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h"
#elif PG_VERSION_NUM >= 120000
#include "pgstat.h"
#endif
#if PG_VERSION_NUM >= 120000
#include "access/tableam.h"
#include "commands/progress.h"
#else
#define PROGRESS_CREATEIDX_SUBPHASE 0
#define PROGRESS_CREATEIDX_TUPLES_TOTAL 0
#define PROGRESS_CREATEIDX_TUPLES_DONE 0
#include "pgstat.h"
#endif
#if PG_VERSION_NUM >= 130000
@@ -34,26 +32,11 @@
#define CALLBACK_ITEM_POINTER HeapTuple hup
#endif
#if PG_VERSION_NUM >= 120000
#define UpdateProgress(index, val) pgstat_progress_update_param(index, val)
#else
#define UpdateProgress(index, val) ((void)val)
#endif
#if PG_VERSION_NUM >= 140000
#include "utils/backend_status.h"
#include "utils/wait_event.h"
#endif
#if PG_VERSION_NUM >= 120000
#include "access/table.h"
#include "optimizer/optimizer.h"
#else
#include "access/heapam.h"
#include "optimizer/planner.h"
#include "pgstat.h"
#endif
#define PARALLEL_KEY_IVFFLAT_SHARED UINT64CONST(0xA000000000000001)
#define PARALLEL_KEY_TUPLESORT UINT64CONST(0xA000000000000002)
#define PARALLEL_KEY_IVFFLAT_CENTERS UINT64CONST(0xA000000000000003)
@@ -77,13 +60,15 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
*/
if (buildstate->kmeansnormprocinfo != NULL)
{
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->normvec))
if (!IvfflatCheckNorm(buildstate->kmeansnormprocinfo, buildstate->collation, value))
return;
value = IvfflatNormValue(buildstate->typeInfo, buildstate->collation, value);
}
if (samples->length < targsamples)
{
VectorArraySet(samples, samples->length, DatumGetVector(value));
VectorArraySet(samples, samples->length, DatumGetPointer(value));
samples->length++;
}
else
@@ -100,7 +85,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
#endif
Assert(k >= 0 && k < targsamples);
VectorArraySet(samples, k, DatumGetVector(value));
VectorArraySet(samples, k, DatumGetPointer(value));
}
buildstate->rowstoskip -= 1;
@@ -125,7 +110,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
/* Add sample */
AddSample(values, state);
AddSample(values, buildstate);
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
@@ -150,13 +135,8 @@ SampleRows(IvfflatBuildState * buildstate)
{
BlockNumber targblock = BlockSampler_Next(&buildstate->bs);
#if PG_VERSION_NUM >= 120000
table_index_build_range_scan(buildstate->heap, buildstate->index, buildstate->indexInfo,
false, true, false, targblock, 1, SampleCallback, (void *) buildstate, NULL);
#else
IndexBuildHeapRangeScan(buildstate->heap, buildstate->index, buildstate->indexInfo,
false, true, targblock, 1, SampleCallback, (void *) buildstate, NULL);
#endif
}
}
@@ -178,8 +158,10 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
/* Normalize if needed */
if (buildstate->normprocinfo != NULL)
{
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
if (!IvfflatCheckNorm(buildstate->normprocinfo, buildstate->collation, value))
return;
value = IvfflatNormValue(buildstate->typeInfo, buildstate->collation, value);
}
/* Find the list that minimizes the distance */
@@ -282,16 +264,12 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
IndexTuple itup = NULL; /* silence compiler warning */
int64 inserted = 0;
#if PG_VERSION_NUM >= 120000
TupleTableSlot *slot = MakeSingleTupleTableSlot(buildstate->tupdesc, &TTSOpsMinimalTuple);
#else
TupleTableSlot *slot = MakeSingleTupleTableSlot(buildstate->tupdesc);
#endif
TupleDesc tupdesc = RelationGetDescr(index);
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_LOAD);
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_LOAD);
UpdateProgress(PROGRESS_CREATEIDX_TUPLES_TOTAL, buildstate->indtuples);
pgstat_progress_update_param(PROGRESS_CREATEIDX_TUPLES_TOTAL, buildstate->indtuples);
GetNextTuple(buildstate->sortstate, tupdesc, slot, &itup, &list);
@@ -327,7 +305,7 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
pfree(itup);
UpdateProgress(PROGRESS_CREATEIDX_TUPLES_DONE, ++inserted);
pgstat_progress_update_param(PROGRESS_CREATEIDX_TUPLES_DONE, ++inserted);
GetNextTuple(buildstate->sortstate, tupdesc, slot, &itup, &list);
}
@@ -350,16 +328,21 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->heap = heap;
buildstate->index = index;
buildstate->indexInfo = indexInfo;
buildstate->typeInfo = IvfflatGetTypeInfo(index);
buildstate->lists = IvfflatGetLists(index);
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
/* Disallow varbit since require fixed dimensions */
if (TupleDescAttr(index->rd_att, 0)->atttypid == VARBITOID)
elog(ERROR, "type not supported for ivfflat index");
/* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0)
elog(ERROR, "column does not have dimensions");
if (buildstate->dimensions > IVFFLAT_MAX_DIM)
elog(ERROR, "column cannot have more than %d dimensions for ivfflat index", IVFFLAT_MAX_DIM);
if (buildstate->dimensions > buildstate->typeInfo->maxDimensions)
elog(ERROR, "column cannot have more than %d dimensions for ivfflat index", buildstate->typeInfo->maxDimensions);
buildstate->reltuples = 0;
buildstate->indtuples = 0;
@@ -375,27 +358,16 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
elog(ERROR, "dimensions must be greater than one for this opclass");
/* Create tuple description for sorting */
#if PG_VERSION_NUM >= 120000
buildstate->tupdesc = CreateTemplateTupleDesc(3);
#else
buildstate->tupdesc = CreateTemplateTupleDesc(3, false);
#endif
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 1, "list", INT4OID, -1, 0);
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 3, "vector", RelationGetDescr(index)->attrs[0].atttypid, -1, 0);
#if PG_VERSION_NUM >= 120000
buildstate->slot = MakeSingleTupleTableSlot(buildstate->tupdesc, &TTSOpsVirtual);
#else
buildstate->slot = MakeSingleTupleTableSlot(buildstate->tupdesc);
#endif
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions);
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, buildstate->typeInfo->itemSize(buildstate->dimensions));
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
/* Reuse for each tuple */
buildstate->normvec = InitVector(buildstate->dimensions);
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat build temporary context",
ALLOCSET_DEFAULT_SIZES);
@@ -417,7 +389,6 @@ FreeBuildState(IvfflatBuildState * buildstate)
{
VectorArrayFree(buildstate->centers);
pfree(buildstate->listInfo);
pfree(buildstate->normvec);
#ifdef IVFFLAT_KMEANS_DEBUG
pfree(buildstate->listSums);
@@ -435,7 +406,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
{
int numSamples;
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_KMEANS);
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_KMEANS);
/* Target 50 samples per list, with at least 10000 samples */
/* The number of samples has a large effect on index build time */
@@ -449,7 +420,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
/* Sample rows */
/* TODO Ensure within maintenance_work_mem */
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions);
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions, buildstate->centers->itemsize);
if (buildstate->heap != NULL)
{
SampleRows(buildstate);
@@ -464,7 +435,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
}
/* Calculate centers */
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers));
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers, buildstate->typeInfo));
/* Free samples before we allocate more memory */
VectorArrayFree(buildstate->samples);
@@ -509,8 +480,8 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
Size listSize;
IvfflatList list;
listSize = MAXALIGN(IVFFLAT_LIST_SIZE(dimensions));
list = palloc(listSize);
listSize = MAXALIGN(IVFFLAT_LIST_SIZE(centers->itemsize));
list = palloc0(listSize);
buf = IvfflatNewBuffer(index, forkNum);
IvfflatInitRegisterPage(index, &buf, &page, &state);
@@ -519,10 +490,13 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
{
OffsetNumber offno;
/* Zero memory for each list */
MemSet(list, 0, listSize);
/* Load list */
list->startPage = InvalidBlockNumber;
list->insertPage = InvalidBlockNumber;
memcpy(&list->center, VectorArrayGet(centers, i), VECTOR_SIZE(dimensions));
memcpy(&list->center, VectorArrayGet(centers, i), VARSIZE_ANY(VectorArrayGet(centers, i)));
/* Ensure free space */
if (PageGetFreeSpace(page) < listSize)
@@ -543,10 +517,10 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
pfree(list);
}
#ifdef IVFFLAT_KMEANS_DEBUG
/*
* Print k-means metrics
*/
#ifdef IVFFLAT_KMEANS_DEBUG
static void
PrintKmeansMetrics(IvfflatBuildState * buildstate)
{
@@ -627,15 +601,11 @@ ParallelHeapScan(IvfflatBuildState * buildstate)
* Perform a worker's portion of a parallel sort
*/
static void
IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, Sharedsort *sharedsort, Vector * ivfcenters, int sortmem, bool progress)
IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, Sharedsort *sharedsort, char *ivfcenters, int sortmem, bool progress)
{
SortCoordinate coordinate;
IvfflatBuildState buildstate;
#if PG_VERSION_NUM >= 120000
TableScanDesc scan;
#else
HeapScanDesc scan;
#endif
double reltuples;
IndexInfo *indexInfo;
@@ -655,22 +625,15 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
indexInfo = BuildIndexInfo(ivfspool->index);
indexInfo->ii_Concurrent = ivfshared->isconcurrent;
InitBuildState(&buildstate, ivfspool->heap, ivfspool->index, indexInfo);
memcpy(buildstate.centers->items, ivfcenters, VECTOR_SIZE(buildstate.centers->dim) * buildstate.centers->maxlen);
memcpy(buildstate.centers->items, ivfcenters, buildstate.centers->itemsize * buildstate.centers->maxlen);
buildstate.centers->length = buildstate.centers->maxlen;
ivfspool->sortstate = tuplesort_begin_heap(buildstate.tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, sortmem, coordinate, false);
buildstate.sortstate = ivfspool->sortstate;
#if PG_VERSION_NUM >= 120000
scan = table_beginscan_parallel(ivfspool->heap,
ParallelTableScanFromIvfflatShared(ivfshared));
reltuples = table_index_build_scan(ivfspool->heap, ivfspool->index, indexInfo,
true, progress, BuildCallback,
(void *) &buildstate, scan);
#else
scan = heap_beginscan_parallel(ivfspool->heap, &ivfshared->heapdesc);
reltuples = IndexBuildHeapScan(ivfspool->heap, ivfspool->index, indexInfo,
true, BuildCallback,
(void *) &buildstate, scan);
#endif
/* Execute this worker's part of the sort */
tuplesort_performsort(ivfspool->sortstate);
@@ -710,7 +673,7 @@ IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc)
IvfflatSpool *ivfspool;
IvfflatShared *ivfshared;
Sharedsort *sharedsort;
Vector *ivfcenters;
char *ivfcenters;
Relation heapRel;
Relation indexRel;
LOCKMODE heapLockmode;
@@ -740,11 +703,7 @@ IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc)
}
/* Open relations within worker */
#if PG_VERSION_NUM >= 120000
heapRel = table_open(ivfshared->heaprelid, heapLockmode);
#else
heapRel = heap_open(ivfshared->heaprelid, heapLockmode);
#endif
indexRel = index_open(ivfshared->indexrelid, indexLockmode);
/* Initialize worker's own spool */
@@ -764,11 +723,7 @@ IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc)
/* Close relations within worker */
index_close(indexRel, indexLockmode);
#if PG_VERSION_NUM >= 120000
table_close(heapRel, heapLockmode);
#else
heap_close(heapRel, heapLockmode);
#endif
}
/*
@@ -793,19 +748,7 @@ IvfflatEndParallel(IvfflatLeader * ivfleader)
static Size
ParallelEstimateShared(Relation heap, Snapshot snapshot)
{
#if PG_VERSION_NUM >= 120000
return add_size(BUFFERALIGN(sizeof(IvfflatShared)), table_parallelscan_estimate(heap, snapshot));
#else
if (!IsMVCCSnapshot(snapshot))
{
Assert(snapshot == SnapshotAny);
return sizeof(IvfflatShared);
}
return add_size(offsetof(IvfflatShared, heapdesc) +
offsetof(ParallelHeapScanDescData, phs_snapshot_data),
EstimateSnapshotSpace(snapshot));
#endif
}
/*
@@ -844,7 +787,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
Size estcenters;
IvfflatShared *ivfshared;
Sharedsort *sharedsort;
Vector *ivfcenters;
char *ivfcenters;
IvfflatLeader *ivfleader = (IvfflatLeader *) palloc0(sizeof(IvfflatLeader));
bool leaderparticipates = true;
int querylen;
@@ -856,11 +799,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
/* Enter parallel mode and create context */
EnterParallelMode();
Assert(request > 0);
#if PG_VERSION_NUM >= 120000
pcxt = CreateParallelContext("vector", "IvfflatParallelBuildMain", request);
#else
pcxt = CreateParallelContext("vector", "IvfflatParallelBuildMain", request, true);
#endif
scantuplesortstates = leaderparticipates ? request + 1 : request;
@@ -875,7 +814,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
shm_toc_estimate_chunk(&pcxt->estimator, estivfshared);
estsort = tuplesort_estimate_shared(scantuplesortstates);
shm_toc_estimate_chunk(&pcxt->estimator, estsort);
estcenters = VECTOR_SIZE(buildstate->dimensions) * buildstate->lists;
estcenters = buildstate->centers->itemsize * buildstate->centers->maxlen;
shm_toc_estimate_chunk(&pcxt->estimator, estcenters);
shm_toc_estimate_keys(&pcxt->estimator, 3);
@@ -918,20 +857,16 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
#ifdef IVFFLAT_KMEANS_DEBUG
ivfshared->inertia = 0;
#endif
#if PG_VERSION_NUM >= 120000
table_parallelscan_initialize(buildstate->heap,
ParallelTableScanFromIvfflatShared(ivfshared),
snapshot);
#else
heap_parallelscan_initialize(&ivfshared->heapdesc, buildstate->heap, snapshot);
#endif
/* Store shared tuplesort-private state, for which we reserved space */
sharedsort = (Sharedsort *) shm_toc_allocate(pcxt->toc, estsort);
tuplesort_initialize_shared(sharedsort, scantuplesortstates,
pcxt->seg);
ivfcenters = (Vector *) shm_toc_allocate(pcxt->toc, estcenters);
ivfcenters = shm_toc_allocate(pcxt->toc, estcenters);
memcpy(ivfcenters, buildstate->centers->items, estcenters);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_IVFFLAT_SHARED, ivfshared);
@@ -995,7 +930,7 @@ AssignTuples(IvfflatBuildState * buildstate)
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_ASSIGN);
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_ASSIGN);
/* Calculate parallel workers */
if (buildstate->heap != NULL)
@@ -1023,15 +958,8 @@ AssignTuples(IvfflatBuildState * buildstate)
if (buildstate->ivfleader)
buildstate->reltuples = ParallelHeapScan(buildstate);
else
{
#if PG_VERSION_NUM >= 120000
buildstate->reltuples = table_index_build_scan(buildstate->heap, buildstate->index, buildstate->indexInfo,
true, true, BuildCallback, (void *) buildstate, NULL);
#else
buildstate->reltuples = IndexBuildHeapScan(buildstate->heap, buildstate->index, buildstate->indexInfo,
true, BuildCallback, (void *) buildstate, NULL);
#endif
}
#ifdef IVFFLAT_KMEANS_DEBUG
PrintKmeansMetrics(buildstate);
@@ -1078,6 +1006,10 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo);
CreateEntryPages(buildstate, forkNum);
/* Write WAL for initialization fork since GenericXLog functions do not */
if (forkNum == INIT_FORKNUM)
log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true);
FreeBuildState(buildstate);
}

View File

@@ -3,14 +3,16 @@
#include <float.h>
#include "access/amapi.h"
#include "access/reloptions.h"
#include "commands/progress.h"
#include "commands/vacuum.h"
#include "ivfflat.h"
#include "utils/guc.h"
#include "utils/selfuncs.h"
#include "utils/spccache.h"
#if PG_VERSION_NUM >= 120000
#include "commands/progress.h"
#if PG_VERSION_NUM < 150000
#define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
#endif
int ivfflat_probes;
@@ -33,12 +35,13 @@ IvfflatInit(void)
DefineCustomIntVariable("ivfflat.probes", "Sets the number of probes",
"Valid range is 1..lists.", &ivfflat_probes,
IVFFLAT_DEFAULT_PROBES, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
MarkGUCPrefixReserved("ivfflat");
}
/*
* Get the name of index build phase
*/
#if PG_VERSION_NUM >= 120000
static char *
ivfflatbuildphasename(int64 phasenum)
{
@@ -56,7 +59,6 @@ ivfflatbuildphasename(int64 phasenum)
return NULL;
}
}
#endif
/*
* Estimate the cost of an index scan
@@ -72,9 +74,6 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
double ratio;
double spc_seq_page_cost;
Relation index;
#if PG_VERSION_NUM < 120000
List *qinfos;
#endif
/* Never use index without order */
if (path->indexorderbys == NULL)
@@ -105,12 +104,7 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
*/
costs.numIndexTuples = path->indexinfo->tuples * ratio;
#if PG_VERSION_NUM >= 120000
genericcostestimate(root, path, loop_count, &costs);
#else
qinfos = deconstruct_indexquals(path);
genericcostestimate(root, path, loop_count, qinfos, &costs);
#endif
get_tablespace_page_costs(path->indexinfo->reltablespace, NULL, &spc_seq_page_cost);
@@ -187,14 +181,14 @@ ivfflatvalidate(Oid opclassoid)
*
* See https://www.postgresql.org/docs/current/index-api.html
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(ivfflathandler);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflathandler);
Datum
ivfflathandler(PG_FUNCTION_ARGS)
{
IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0;
amroutine->amsupport = 4;
amroutine->amsupport = 5;
#if PG_VERSION_NUM >= 130000
amroutine->amoptsprocnum = 0;
#endif
@@ -227,9 +221,7 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amcostestimate = ivfflatcostestimate;
amroutine->amoptions = ivfflatoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
#if PG_VERSION_NUM >= 120000
amroutine->ambuildphasename = ivfflatbuildphasename;
#endif
amroutine->amvalidate = ivfflatvalidate;
#if PG_VERSION_NUM >= 140000
amroutine->amadjustmembers = NULL;

View File

@@ -3,9 +3,10 @@
#include "postgres.h"
#include "access/genam.h"
#include "access/generic_xlog.h"
#include "access/parallel.h"
#include "access/reloptions.h"
#include "lib/pairingheap.h"
#include "nodes/execnodes.h"
#include "port.h" /* for random() */
#include "utils/sampling.h"
@@ -16,10 +17,6 @@
#include "common/pg_prng.h"
#endif
#if PG_VERSION_NUM < 120000
#include "access/relscan.h"
#endif
#ifdef IVFFLAT_BENCH
#include "portability/instr_time.h"
#endif
@@ -31,6 +28,7 @@
#define IVFFLAT_NORM_PROC 2
#define IVFFLAT_KMEANS_DISTANCE_PROC 3
#define IVFFLAT_KMEANS_NORM_PROC 4
#define IVFFLAT_TYPE_INFO_PROC 5
#define IVFFLAT_VERSION 1
#define IVFFLAT_MAGIC_NUMBER 0x14FF1A7
@@ -52,7 +50,7 @@
#define PROGRESS_IVFFLAT_PHASE_ASSIGN 3
#define PROGRESS_IVFFLAT_PHASE_LOAD 4
#define IVFFLAT_LIST_SIZE(_dim) (offsetof(IvfflatListData, center) + VECTOR_SIZE(_dim))
#define IVFFLAT_LIST_SIZE(size) (offsetof(IvfflatListData, center) + size)
#define IvfflatPageGetOpaque(page) ((IvfflatPageOpaque) PageGetSpecialPointer(page))
#define IvfflatPageGetMeta(page) ((IvfflatMetaPageData *) PageGetContents(page))
@@ -88,7 +86,8 @@ typedef struct VectorArrayData
int length;
int maxlen;
int dim;
Vector *items;
Size itemsize;
char *items;
} VectorArrayData;
typedef VectorArrayData * VectorArray;
@@ -135,16 +134,10 @@ typedef struct IvfflatShared
#ifdef IVFFLAT_KMEANS_DEBUG
double inertia;
#endif
#if PG_VERSION_NUM < 120000
ParallelHeapScanDescData heapdesc; /* must come last */
#endif
} IvfflatShared;
#if PG_VERSION_NUM >= 120000
#define ParallelTableScanFromIvfflatShared(shared) \
(ParallelTableScanDesc) ((char *) (shared) + BUFFERALIGN(sizeof(IvfflatShared)))
#endif
typedef struct IvfflatLeader
{
@@ -153,15 +146,25 @@ typedef struct IvfflatLeader
IvfflatShared *ivfshared;
Sharedsort *sharedsort;
Snapshot snapshot;
Vector *ivfcenters;
char *ivfcenters;
} IvfflatLeader;
typedef struct IvfflatTypeInfo
{
int maxDimensions;
Datum (*normalize) (PG_FUNCTION_ARGS);
Size (*itemSize) (int dimensions);
void (*updateCenter) (Pointer v, int dimensions, float *x);
void (*sumCenter) (Pointer v, float *x);
} IvfflatTypeInfo;
typedef struct IvfflatBuildState
{
/* Info */
Relation heap;
Relation index;
IndexInfo *indexInfo;
const IvfflatTypeInfo *typeInfo;
/* Settings */
int dimensions;
@@ -181,7 +184,6 @@ typedef struct IvfflatBuildState
VectorArray samples;
VectorArray centers;
ListInfo *listInfo;
Vector *normvec;
#ifdef IVFFLAT_KMEANS_DEBUG
double inertia;
@@ -243,6 +245,7 @@ typedef struct IvfflatScanList
typedef struct IvfflatScanOpaqueData
{
const IvfflatTypeInfo *typeInfo;
int probes;
int dimensions;
bool first;
@@ -257,6 +260,7 @@ typedef struct IvfflatScanOpaqueData
FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
Oid collation;
Datum (*distfunc) (FmgrInfo *flinfo, Oid collation, Datum arg1, Datum arg2);
/* Lists */
pairingheap *listQueue;
@@ -265,18 +269,29 @@ typedef struct IvfflatScanOpaqueData
typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
#define VECTOR_ARRAY_SIZE(_length, _dim) (sizeof(VectorArrayData) + (_length) * VECTOR_SIZE(_dim))
#define VECTOR_ARRAY_OFFSET(_arr, _offset) ((char*) (_arr)->items + (_offset) * VECTOR_SIZE((_arr)->dim))
#define VectorArrayGet(_arr, _offset) ((Vector *) VECTOR_ARRAY_OFFSET(_arr, _offset))
#define VectorArraySet(_arr, _offset, _val) memcpy(VECTOR_ARRAY_OFFSET(_arr, _offset), _val, VECTOR_SIZE((_arr)->dim))
#define VECTOR_ARRAY_SIZE(_length, _size) (sizeof(VectorArrayData) + (_length) * MAXALIGN(_size))
/* Use functions instead of macros to avoid double evaluation */
static inline Pointer
VectorArrayGet(VectorArray arr, int offset)
{
return ((char *) arr->items) + (offset * arr->itemsize);
}
static inline void
VectorArraySet(VectorArray arr, int offset, Pointer val)
{
memcpy(VectorArrayGet(arr, offset), val, VARSIZE_ANY(val));
}
/* Methods */
VectorArray VectorArrayInit(int maxlen, int dimensions);
VectorArray VectorArrayInit(int maxlen, int dimensions, Size itemsize);
void VectorArrayFree(VectorArray arr);
void PrintVectorArray(char *msg, VectorArray arr);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo);
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
Datum IvfflatNormValue(const IvfflatTypeInfo * typeInfo, Oid collation, Datum value);
bool IvfflatCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value);
int IvfflatGetLists(Relation index);
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);
@@ -286,6 +301,7 @@ Buffer IvfflatNewBuffer(Relation index, ForkNumber forkNum);
void IvfflatInitPage(Buffer buf, Page page);
void IvfflatInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state);
void IvfflatInit(void);
const IvfflatTypeInfo *IvfflatGetTypeInfo(Relation index);
PGDLLEXPORT void IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc);
/* Index access methods */

View File

@@ -2,6 +2,7 @@
#include <float.h>
#include "access/generic_xlog.h"
#include "ivfflat.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
@@ -66,6 +67,7 @@ FindInsertPage(Relation index, Datum *values, BlockNumber *insertPage, ListInfo
static void
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
{
const IvfflatTypeInfo *typeInfo = IvfflatGetTypeInfo(index);
IndexTuple itup;
Datum value;
FmgrInfo *normprocinfo;
@@ -84,10 +86,17 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL)
{
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
Oid collation = index->rd_indcollation[0];
if (!IvfflatCheckNorm(normprocinfo, collation, value))
return;
value = IvfflatNormValue(typeInfo, collation, value);
}
/* Ensure index is valid */
IvfflatGetMetaPageInfo(index, NULL, NULL);
/* Find the insert page - sets the page and list info */
FindInsertPage(index, values, &insertPage, &listInfo);
Assert(BlockNumberIsValid(insertPage));

View File

@@ -3,8 +3,15 @@
#include <float.h>
#include <math.h>
#include "bitvec.h"
#include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "utils/builtins.h"
#include "utils/datum.h"
#include "utils/memutils.h"
#include "vector.h"
/*
* Initialize with kmeans++
@@ -42,12 +49,12 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
for (j = 0; j < numSamples; j++)
{
Vector *vec = VectorArrayGet(samples, j);
Datum vec = PointerGetDatum(VectorArrayGet(samples, j));
double distance;
/* Only need to compute distance for new center */
/* TODO Use triangle inequality to reduce distance calculations */
distance = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, i))));
distance = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, i))));
/* Set lower bound */
lowerBound[j * numCenters + i] = distance;
@@ -82,73 +89,166 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
}
/*
* Apply norm to vector
*/
static inline void
ApplyNorm(FmgrInfo *normprocinfo, Oid collation, Vector * vec)
{
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(vec)));
/* TODO Handle zero norm */
if (norm > 0)
{
for (int i = 0; i < vec->dim; i++)
vec->x[i] /= norm;
}
}
/*
* Compare vectors
*/
static int
CompareVectors(const void *a, const void *b)
{
return vector_cmp_internal((Vector *) a, (Vector *) b);
}
/*
* Quick approach if we have little data
* Norm centers
*/
static void
QuickCenters(Relation index, VectorArray samples, VectorArray centers)
NormCenters(const IvfflatTypeInfo * typeInfo, Oid collation, VectorArray centers)
{
int dimensions = centers->dim;
Oid collation = index->rd_indcollation[0];
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
MemoryContext normCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat norm temporary context",
ALLOCSET_DEFAULT_SIZES);
MemoryContext oldCtx = MemoryContextSwitchTo(normCtx);
/* Copy existing vectors while avoiding duplicates */
if (samples->length > 0)
for (int j = 0; j < centers->length; j++)
{
qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
for (int i = 0; i < samples->length; i++)
{
Vector *vec = VectorArrayGet(samples, i);
Datum center = PointerGetDatum(VectorArrayGet(centers, j));
Datum newCenter = IvfflatNormValue(typeInfo, collation, center);
Size size = VARSIZE_ANY(DatumGetPointer(newCenter));
if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
{
VectorArraySet(centers, centers->length, vec);
centers->length++;
}
}
if (size > centers->itemsize)
elog(ERROR, "safety check failed");
memcpy(DatumGetPointer(center), DatumGetPointer(newCenter), size);
MemoryContextReset(normCtx);
}
/* Fill remaining with random data */
MemoryContextSwitchTo(oldCtx);
MemoryContextDelete(normCtx);
}
/*
* Quick approach if we have no data
*/
static void
RandomCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeInfo)
{
int dimensions = centers->dim;
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
Oid collation = index->rd_indcollation[0];
float *x = (float *) palloc(sizeof(float) * dimensions);
/* Fill with random data */
while (centers->length < centers->maxlen)
{
Vector *vec = VectorArrayGet(centers, centers->length);
Pointer center = VectorArrayGet(centers, centers->length);
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
for (int i = 0; i < dimensions; i++)
x[i] = (float) RandomDouble();
for (int j = 0; j < dimensions; j++)
vec->x[j] = RandomDouble();
/* Normalize if needed (only needed for random centers) */
if (normprocinfo != NULL)
ApplyNorm(normprocinfo, collation, vec);
typeInfo->updateCenter(center, dimensions, x);
centers->length++;
}
if (normprocinfo != NULL)
NormCenters(typeInfo, collation, centers);
}
#ifdef IVFFLAT_MEMORY
/*
* Show memory usage
*/
static void
ShowMemoryUsage(MemoryContext context, Size estimatedSize)
{
#if PG_VERSION_NUM >= 130000
elog(INFO, "total memory: %zu MB",
MemoryContextMemAllocated(context, true) / (1024 * 1024));
#else
MemoryContextStats(context);
#endif
elog(INFO, "estimated memory: %zu MB", estimatedSize / (1024 * 1024));
}
#endif
/*
* Sum centers
*/
static void
SumCenters(VectorArray samples, float *agg, int *closestCenters, const IvfflatTypeInfo * typeInfo)
{
for (int j = 0; j < samples->length; j++)
{
float *x = agg + ((int64) closestCenters[j] * samples->dim);
typeInfo->sumCenter(VectorArrayGet(samples, j), x);
}
}
/*
* Update centers
*/
static void
UpdateCenters(float *agg, VectorArray centers, const IvfflatTypeInfo * typeInfo)
{
for (int j = 0; j < centers->length; j++)
{
float *x = agg + ((int64) j * centers->dim);
typeInfo->updateCenter(VectorArrayGet(centers, j), centers->dim, x);
}
}
/*
* Compute new centers
*/
static void
ComputeNewCenters(VectorArray samples, float *agg, VectorArray newCenters, int *centerCounts, int *closestCenters, FmgrInfo *normprocinfo, Oid collation, const IvfflatTypeInfo * typeInfo)
{
int dimensions = newCenters->dim;
int numCenters = newCenters->length;
int numSamples = samples->length;
/* Reset sum and count */
for (int j = 0; j < numCenters; j++)
{
float *x = agg + ((int64) j * dimensions);
for (int k = 0; k < dimensions; k++)
x[k] = 0.0;
centerCounts[j] = 0;
}
/* Increment sum of closest center */
SumCenters(samples, agg, closestCenters, typeInfo);
/* Increment count of closest center */
for (int j = 0; j < numSamples; j++)
centerCounts[closestCenters[j]] += 1;
/* Divide sum by count */
for (int j = 0; j < numCenters; j++)
{
float *x = agg + ((int64) j * dimensions);
if (centerCounts[j] > 0)
{
/* Double avoids overflow, but requires more memory */
/* TODO Update bounds */
for (int k = 0; k < dimensions; k++)
{
if (isinf(x[k]))
x[k] = x[k] > 0 ? FLT_MAX : -FLT_MAX;
}
for (int k = 0; k < dimensions; k++)
x[k] /= centerCounts[j];
}
else
{
/* TODO Handle empty centers properly */
for (int k = 0; k < dimensions; k++)
x[k] = RandomDouble();
}
}
/* Set new centers */
UpdateCenters(agg, newCenters, typeInfo);
/* Normalize if needed */
if (normprocinfo != NULL)
NormCenters(typeInfo, collation, newCenters);
}
/*
@@ -160,19 +260,16 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
* https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
*/
static void
ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo)
{
FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
Oid collation;
Vector *vec;
Vector *newCenter;
int64 j;
int64 k;
int dimensions = centers->dim;
int numCenters = centers->maxlen;
int numSamples = samples->length;
VectorArray newCenters;
float *agg;
int *centerCounts;
int *closestCenters;
float *lowerBound;
@@ -182,9 +279,10 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
float *newcdist;
/* Calculate allocation sizes */
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->dim);
Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->dim);
Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, dimensions);
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->itemsize);
Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->itemsize);
Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, centers->itemsize);
Size aggSize = sizeof(float) * (int64) numCenters * dimensions;
Size centerCountsSize = sizeof(int) * numCenters;
Size closestCentersSize = sizeof(int) * numSamples;
Size lowerBoundSize = sizeof(float) * numSamples * numCenters;
@@ -194,7 +292,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
Size newcdistSize = sizeof(float) * numCenters;
/* Calculate total size */
Size totalSize = samplesSize + centersSize + newCentersSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
Size totalSize = samplesSize + centersSize + newCentersSize + aggSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
/* Check memory requirements */
/* Add one to error message to ceil */
@@ -215,6 +313,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Allocate space */
/* Use float instead of double to save memory */
agg = palloc(aggSize);
centerCounts = palloc(centerCountsSize);
closestCenters = palloc(closestCentersSize);
lowerBound = palloc_extended(lowerBoundSize, MCXT_ALLOC_HUGE);
@@ -223,25 +322,25 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
halfcdist = palloc_extended(halfcdistSize, MCXT_ALLOC_HUGE);
newcdist = palloc(newcdistSize);
newCenters = VectorArrayInit(numCenters, dimensions);
for (j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(newCenters, j);
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
}
/* Initialize new centers */
newCenters = VectorArrayInit(numCenters, dimensions, centers->itemsize);
newCenters->length = numCenters;
#ifdef IVFFLAT_MEMORY
ShowMemoryUsage(MemoryContextGetParent(CurrentMemoryContext));
#endif
/* Pick initial centers */
InitCenters(index, samples, centers, lowerBound);
/* Assign each x to its closest initial center c(x) = argmin d(x,c) */
for (j = 0; j < numSamples; j++)
for (int64 j = 0; j < numSamples; j++)
{
float minDistance = FLT_MAX;
int closestCenter = 0;
/* Find closest center */
for (k = 0; k < numCenters; k++)
for (int64 k = 0; k < numCenters; k++)
{
/* TODO Use Lemma 1 in k-means++ initialization */
float distance = lowerBound[j * numCenters + k];
@@ -267,13 +366,13 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
CHECK_FOR_INTERRUPTS();
/* Step 1: For all centers, compute distance */
for (j = 0; j < numCenters; j++)
for (int64 j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(centers, j);
Datum vec = PointerGetDatum(VectorArrayGet(centers, j));
for (k = j + 1; k < numCenters; k++)
for (int64 k = j + 1; k < numCenters; k++)
{
float distance = 0.5 * DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
float distance = 0.5 * DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, k))));
halfcdist[j * numCenters + k] = distance;
halfcdist[k * numCenters + j] = distance;
@@ -281,11 +380,11 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
}
/* For all centers c, compute s(c) */
for (j = 0; j < numCenters; j++)
for (int64 j = 0; j < numCenters; j++)
{
float minDistance = FLT_MAX;
for (k = 0; k < numCenters; k++)
for (int64 k = 0; k < numCenters; k++)
{
float distance;
@@ -302,7 +401,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
rjreset = iteration != 0;
for (j = 0; j < numSamples; j++)
for (int64 j = 0; j < numSamples; j++)
{
bool rj;
@@ -312,8 +411,9 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
rj = rjreset;
for (k = 0; k < numCenters; k++)
for (int64 k = 0; k < numCenters; k++)
{
Datum vec;
float dxcx;
/* Step 3: For all remaining points x and centers c */
@@ -326,12 +426,12 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
if (upperBound[j] <= halfcdist[closestCenters[j] * numCenters + k])
continue;
vec = VectorArrayGet(samples, j);
vec = PointerGetDatum(VectorArrayGet(samples, j));
/* Step 3a */
if (rj)
{
dxcx = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, closestCenters[j]))));
dxcx = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, closestCenters[j]))));
/* d(x,c(x)) computed, which is a form of d(x,c) */
lowerBound[j * numCenters + closestCenters[j]] = dxcx;
@@ -345,7 +445,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Step 3b */
if (dxcx > lowerBound[j * numCenters + k] || dxcx > halfcdist[closestCenters[j] * numCenters + k])
{
float dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
float dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, k))));
/* d(x,c) calculated */
lowerBound[j * numCenters + k] = dxc;
@@ -364,66 +464,15 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
}
/* Step 4: For each center c, let m(c) be mean of all points assigned */
for (j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(newCenters, j);
for (k = 0; k < dimensions; k++)
vec->x[k] = 0.0;
centerCounts[j] = 0;
}
for (j = 0; j < numSamples; j++)
{
int closestCenter;
vec = VectorArrayGet(samples, j);
closestCenter = closestCenters[j];
/* Increment sum and count of closest center */
newCenter = VectorArrayGet(newCenters, closestCenter);
for (k = 0; k < dimensions; k++)
newCenter->x[k] += vec->x[k];
centerCounts[closestCenter] += 1;
}
for (j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(newCenters, j);
if (centerCounts[j] > 0)
{
/* Double avoids overflow, but requires more memory */
/* TODO Update bounds */
for (k = 0; k < dimensions; k++)
{
if (isinf(vec->x[k]))
vec->x[k] = vec->x[k] > 0 ? FLT_MAX : -FLT_MAX;
}
for (k = 0; k < dimensions; k++)
vec->x[k] /= centerCounts[j];
}
else
{
/* TODO Handle empty centers properly */
for (k = 0; k < dimensions; k++)
vec->x[k] = RandomDouble();
}
/* Normalize if needed */
if (normprocinfo != NULL)
ApplyNorm(normprocinfo, collation, vec);
}
ComputeNewCenters(samples, agg, newCenters, centerCounts, closestCenters, normprocinfo, collation, typeInfo);
/* Step 5 */
for (j = 0; j < numCenters; j++)
for (int j = 0; j < numCenters; j++)
newcdist[j] = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(VectorArrayGet(centers, j)), PointerGetDatum(VectorArrayGet(newCenters, j))));
for (j = 0; j < numSamples; j++)
for (int64 j = 0; j < numSamples; j++)
{
for (k = 0; k < numCenters; k++)
for (int64 k = 0; k < numCenters; k++)
{
float distance = lowerBound[j * numCenters + k] - newcdist[k];
@@ -436,77 +485,78 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Step 6 */
/* We reset r(x) before Step 3 in the next iteration */
for (j = 0; j < numSamples; j++)
for (int j = 0; j < numSamples; j++)
upperBound[j] += newcdist[closestCenters[j]];
/* Step 7 */
for (j = 0; j < numCenters; j++)
for (int j = 0; j < numCenters; j++)
VectorArraySet(centers, j, VectorArrayGet(newCenters, j));
if (changes == 0 && iteration != 0)
break;
}
}
VectorArrayFree(newCenters);
pfree(centerCounts);
pfree(closestCenters);
pfree(lowerBound);
pfree(upperBound);
pfree(s);
pfree(halfcdist);
pfree(newcdist);
/*
* Ensure no NaN or infinite values
*/
static void
CheckElements(VectorArray centers, const IvfflatTypeInfo * typeInfo)
{
float *scratch = palloc(sizeof(float) * centers->dim);
for (int i = 0; i < centers->length; i++)
{
for (int j = 0; j < centers->dim; j++)
scratch[j] = 0;
/* /fp:fast may not propagate NaN with MSVC, but that's alright */
typeInfo->sumCenter(VectorArrayGet(centers, i), scratch);
for (int j = 0; j < centers->dim; j++)
{
if (isnan(scratch[j]))
elog(ERROR, "NaN detected. Please report a bug.");
if (isinf(scratch[j]))
elog(ERROR, "Infinite value detected. Please report a bug.");
}
}
}
/*
* Ensure no zero vectors for cosine distance
*/
static void
CheckNorms(VectorArray centers, Relation index)
{
/* Check NORM_PROC instead of KMEANS_NORM_PROC */
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
Oid collation = index->rd_indcollation[0];
if (normprocinfo == NULL)
return;
for (int i = 0; i < centers->length; i++)
{
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(VectorArrayGet(centers, i))));
if (norm == 0)
elog(ERROR, "Zero norm detected. Please report a bug.");
}
}
/*
* Detect issues with centers
*/
static void
CheckCenters(Relation index, VectorArray centers)
CheckCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeInfo)
{
FmgrInfo *normprocinfo;
if (centers->length != centers->maxlen)
elog(ERROR, "Not enough centers. Please report a bug.");
/* Ensure no NaN or infinite values */
for (int i = 0; i < centers->length; i++)
{
Vector *vec = VectorArrayGet(centers, i);
for (int j = 0; j < vec->dim; j++)
{
if (isnan(vec->x[j]))
elog(ERROR, "NaN detected. Please report a bug.");
if (isinf(vec->x[j]))
elog(ERROR, "Infinite value detected. Please report a bug.");
}
}
/* Ensure no duplicate centers */
/* Fine to sort in-place */
qsort(centers->items, centers->length, VECTOR_SIZE(centers->dim), CompareVectors);
for (int i = 1; i < centers->length; i++)
{
if (CompareVectors(VectorArrayGet(centers, i), VectorArrayGet(centers, i - 1)) == 0)
elog(ERROR, "Duplicate centers detected. Please report a bug.");
}
/* Ensure no zero vectors for cosine distance */
/* Check NORM_PROC instead of KMEANS_NORM_PROC */
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL)
{
Oid collation = index->rd_indcollation[0];
for (int i = 0; i < centers->length; i++)
{
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(VectorArrayGet(centers, i))));
if (norm == 0)
elog(ERROR, "Zero norm detected. Please report a bug.");
}
}
CheckElements(centers, typeInfo);
CheckNorms(centers, index);
}
/*
@@ -514,12 +564,20 @@ CheckCenters(Relation index, VectorArray centers)
* We use spherical k-means for inner product and cosine
*/
void
IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers)
IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo)
{
if (samples->length <= centers->maxlen)
QuickCenters(index, samples, centers);
else
ElkanKmeans(index, samples, centers);
MemoryContext kmeansCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat kmeans temporary context",
ALLOCSET_DEFAULT_SIZES);
MemoryContext oldCtx = MemoryContextSwitchTo(kmeansCtx);
CheckCenters(index, centers);
if (samples->length == 0)
RandomCenters(index, centers, typeInfo);
else
ElkanKmeans(index, samples, centers, typeInfo);
CheckCenters(index, centers, typeInfo);
MemoryContextSwitchTo(oldCtx);
MemoryContextDelete(kmeansCtx);
}

View File

@@ -5,6 +5,7 @@
#include "access/relscan.h"
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
#include "lib/pairingheap.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "pgstat.h"
@@ -55,7 +56,7 @@ GetScanLists(IndexScanDesc scan, Datum value)
double distance;
/* Use procinfo from the index instead of scan key for performance */
distance = DatumGetFloat8(FunctionCall2Coll(so->procinfo, so->collation, PointerGetDatum(&list->center), value));
distance = DatumGetFloat8(so->distfunc(so->procinfo, so->collation, PointerGetDatum(&list->center), value));
if (listCount < so->probes)
{
@@ -105,12 +106,7 @@ GetScanItems(IndexScanDesc scan, Datum value)
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
TupleDesc tupdesc = RelationGetDescr(scan->indexRelation);
double tuples = 0;
#if PG_VERSION_NUM >= 120000
TupleTableSlot *slot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsVirtual);
#else
TupleTableSlot *slot = MakeSingleTupleTableSlot(so->tupdesc);
#endif
/*
* Reuse same set of shared buffers for scan
@@ -153,7 +149,7 @@ GetScanItems(IndexScanDesc scan, Datum value)
* performance
*/
ExecClearTuple(slot);
slot->tts_values[0] = FunctionCall2Coll(so->procinfo, so->collation, datum, value);
slot->tts_values[0] = so->distfunc(so->procinfo, so->collation, datum, value);
slot->tts_isnull[0] = false;
slot->tts_values[1] = PointerGetDatum(&itup->t_tid);
slot->tts_isnull[1] = false;
@@ -181,6 +177,46 @@ GetScanItems(IndexScanDesc scan, Datum value)
tuplesort_performsort(so->sortstate);
}
/*
* Zero distance
*/
static Datum
ZeroDistance(FmgrInfo *flinfo, Oid collation, Datum arg1, Datum arg2)
{
return Float8GetDatum(0.0);
}
/*
* Get scan value
*/
static Datum
GetScanValue(IndexScanDesc scan)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL)
{
value = PointerGetDatum(NULL);
so->distfunc = ZeroDistance;
}
else
{
value = scan->orderByData->sk_argument;
so->distfunc = FunctionCall2Coll;
/* Value should not be compressed or toasted */
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Normalize if needed */
if (so->normprocinfo != NULL)
value = IvfflatNormValue(so->typeInfo, so->collation, value);
}
return value;
}
/*
* Prepare for an index scan
*/
@@ -206,6 +242,7 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
probes = lists;
so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
so->typeInfo = IvfflatGetTypeInfo(index);
so->first = true;
so->probes = probes;
so->dimensions = dimensions;
@@ -216,22 +253,14 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
so->collation = index->rd_indcollation[0];
/* Create tuple description for sorting */
#if PG_VERSION_NUM >= 120000
so->tupdesc = CreateTemplateTupleDesc(2);
#else
so->tupdesc = CreateTemplateTupleDesc(2, false);
#endif
TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
/* Prep sort */
so->sortstate = tuplesort_begin_heap(so->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
#if PG_VERSION_NUM >= 120000
so->slot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsMinimalTuple);
#else
so->slot = MakeSingleTupleTableSlot(so->tupdesc);
#endif
so->listQueue = pairingheap_allocate(CompareLists, scan);
@@ -293,21 +322,7 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
if (!IsMVCCSnapshot(scan->xs_snapshot))
elog(ERROR, "non-MVCC snapshots are not supported with ivfflat");
if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(so->dimensions));
else
{
value = scan->orderByData->sk_argument;
/* Value should not be compressed or toasted */
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Fine if normalization fails */
if (so->normprocinfo != NULL)
IvfflatNormValue(so->normprocinfo, so->collation, &value, NULL);
}
value = GetScanValue(scan);
IvfflatBench("GetScanLists", GetScanLists(scan, value));
IvfflatBench("GetScanItems", GetScanItems(scan, value));
so->first = false;
@@ -321,12 +336,8 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
{
ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
#if PG_VERSION_NUM >= 120000
scan->xs_heaptid = *heaptid;
#else
scan->xs_ctup.t_self = *heaptid;
#endif
scan->xs_recheck = false;
scan->xs_recheckorderby = false;
return true;
}

View File

@@ -1,21 +1,30 @@
#include "postgres.h"
#include "access/generic_xlog.h"
#include "bitvec.h"
#include "catalog/pg_type.h"
#include "fmgr.h"
#include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h"
#include "storage/bufmgr.h"
#include "vector.h"
/*
* Allocate a vector array
*/
VectorArray
VectorArrayInit(int maxlen, int dimensions)
VectorArrayInit(int maxlen, int dimensions, Size itemsize)
{
VectorArray res = palloc(sizeof(VectorArrayData));
/* Ensure items are aligned to prevent UB */
itemsize = MAXALIGN(itemsize);
res->length = 0;
res->maxlen = maxlen;
res->dim = dimensions;
res->items = palloc_extended(maxlen * VECTOR_SIZE(dimensions), MCXT_ALLOC_ZERO | MCXT_ALLOC_HUGE);
res->itemsize = itemsize;
res->items = palloc_extended(maxlen * itemsize, MCXT_ALLOC_ZERO | MCXT_ALLOC_HUGE);
return res;
}
@@ -29,16 +38,6 @@ VectorArrayFree(VectorArray arr)
pfree(arr);
}
/*
* Print vector array - useful for debugging
*/
void
PrintVectorArray(char *msg, VectorArray arr)
{
for (int i = 0; i < arr->length; i++)
PrintVector(msg, VectorArrayGet(arr, i));
}
/*
* Get the number of lists in the index
*/
@@ -66,34 +65,21 @@ IvfflatOptionalProcInfo(Relation index, uint16 procnum)
}
/*
* Divide by the norm
*
* Returns false if value should not be indexed
*
* The caller needs to free the pointer stored in value
* if it's different than the original value
* Normalize value
*/
Datum
IvfflatNormValue(const IvfflatTypeInfo * typeInfo, Oid collation, Datum value)
{
return DirectFunctionCall1Coll(typeInfo->normalize, collation, value);
}
/*
* Check if non-zero norm
*/
bool
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
IvfflatCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value)
{
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0)
{
Vector *v = DatumGetVector(*value);
if (result == NULL)
result = InitVector(v->dim);
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
*value = PointerGetDatum(result);
return true;
}
return false;
return DatumGetFloat8(FunctionCall1Coll(procinfo, collation, value)) > 0;
}
/*
@@ -184,7 +170,11 @@ IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions)
page = BufferGetPage(buf);
metap = IvfflatPageGetMeta(page);
*lists = metap->lists;
if (unlikely(metap->magicNumber != IVFFLAT_MAGIC_NUMBER))
elog(ERROR, "ivfflat index is not valid");
if (lists != NULL)
*lists = metap->lists;
if (dimensions != NULL)
*dimensions = metap->dimensions;
@@ -238,3 +228,146 @@ IvfflatUpdateList(Relation index, ListInfo listInfo,
UnlockReleaseBuffer(buf);
}
}
PGDLLEXPORT Datum l2_normalize(PG_FUNCTION_ARGS);
PGDLLEXPORT Datum halfvec_l2_normalize(PG_FUNCTION_ARGS);
PGDLLEXPORT Datum sparsevec_l2_normalize(PG_FUNCTION_ARGS);
static Size
VectorItemSize(int dimensions)
{
return VECTOR_SIZE(dimensions);
}
static Size
HalfvecItemSize(int dimensions)
{
return HALFVEC_SIZE(dimensions);
}
static Size
BitItemSize(int dimensions)
{
return VARBITTOTALLEN(dimensions);
}
static void
VectorUpdateCenter(Pointer v, int dimensions, float *x)
{
Vector *vec = (Vector *) v;
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
for (int k = 0; k < dimensions; k++)
vec->x[k] = x[k];
}
static void
HalfvecUpdateCenter(Pointer v, int dimensions, float *x)
{
HalfVector *vec = (HalfVector *) v;
SET_VARSIZE(vec, HALFVEC_SIZE(dimensions));
vec->dim = dimensions;
for (int k = 0; k < dimensions; k++)
vec->x[k] = Float4ToHalfUnchecked(x[k]);
}
static void
BitUpdateCenter(Pointer v, int dimensions, float *x)
{
VarBit *vec = (VarBit *) v;
unsigned char *nx = VARBITS(vec);
SET_VARSIZE(vec, VARBITTOTALLEN(dimensions));
VARBITLEN(vec) = dimensions;
for (uint32 k = 0; k < VARBITBYTES(vec); k++)
nx[k] = 0;
for (int k = 0; k < dimensions; k++)
nx[k / 8] |= (x[k] > 0.5 ? 1 : 0) << (7 - (k % 8));
}
static void
VectorSumCenter(Pointer v, float *x)
{
Vector *vec = (Vector *) v;
for (int k = 0; k < vec->dim; k++)
x[k] += vec->x[k];
}
static void
HalfvecSumCenter(Pointer v, float *x)
{
HalfVector *vec = (HalfVector *) v;
for (int k = 0; k < vec->dim; k++)
x[k] += HalfToFloat4(vec->x[k]);
}
static void
BitSumCenter(Pointer v, float *x)
{
VarBit *vec = (VarBit *) v;
for (int k = 0; k < VARBITLEN(vec); k++)
x[k] += (float) (((VARBITS(vec)[k / 8]) >> (7 - (k % 8))) & 0x01);
}
/*
* Get type info
*/
const IvfflatTypeInfo *
IvfflatGetTypeInfo(Relation index)
{
FmgrInfo *procinfo = IvfflatOptionalProcInfo(index, IVFFLAT_TYPE_INFO_PROC);
if (procinfo == NULL)
{
static const IvfflatTypeInfo typeInfo = {
.maxDimensions = IVFFLAT_MAX_DIM,
.normalize = l2_normalize,
.itemSize = VectorItemSize,
.updateCenter = VectorUpdateCenter,
.sumCenter = VectorSumCenter
};
return (&typeInfo);
}
else
return (const IvfflatTypeInfo *) DatumGetPointer(FunctionCall0Coll(procinfo, InvalidOid));
}
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_halfvec_support);
Datum
ivfflat_halfvec_support(PG_FUNCTION_ARGS)
{
static const IvfflatTypeInfo typeInfo = {
.maxDimensions = IVFFLAT_MAX_DIM * 2,
.normalize = halfvec_l2_normalize,
.itemSize = HalfvecItemSize,
.updateCenter = HalfvecUpdateCenter,
.sumCenter = HalfvecSumCenter
};
PG_RETURN_POINTER(&typeInfo);
};
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_bit_support);
Datum
ivfflat_bit_support(PG_FUNCTION_ARGS)
{
static const IvfflatTypeInfo typeInfo = {
.maxDimensions = IVFFLAT_MAX_DIM * 32,
.normalize = NULL,
.itemSize = BitItemSize,
.updateCenter = BitUpdateCenter,
.sumCenter = BitSumCenter
};
PG_RETURN_POINTER(&typeInfo);
};

View File

@@ -1,5 +1,6 @@
#include "postgres.h"
#include "access/generic_xlog.h"
#include "commands/vacuum.h"
#include "ivfflat.h"
#include "storage/bufmgr.h"

1129
src/sparsevec.c Normal file

File diff suppressed because it is too large Load Diff

40
src/sparsevec.h Normal file
View File

@@ -0,0 +1,40 @@
#ifndef SPARSEVEC_H
#define SPARSEVEC_H
#define SPARSEVEC_MAX_DIM 1000000000
#define SPARSEVEC_MAX_NNZ 16000
#define DatumGetSparseVector(x) ((SparseVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_SPARSEVEC_P(x) DatumGetSparseVector(PG_GETARG_DATUM(x))
#define PG_RETURN_SPARSEVEC_P(x) PG_RETURN_POINTER(x)
/*
* Indices use 0-based numbering for the on-disk (and binary) format (consistent with C)
* and are always sorted. Values come after indices.
*/
typedef struct SparseVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int32 dim; /* number of dimensions */
int32 nnz; /* number of non-zero elements */
int32 unused; /* reserved for future use, always zero */
int32 indices[FLEXIBLE_ARRAY_MEMBER];
} SparseVector;
/* Use functions instead of macros to avoid double evaluation */
static inline Size
SPARSEVEC_SIZE(int nnz)
{
return offsetof(SparseVector, indices) + (nnz * sizeof(int32)) + (nnz * sizeof(float));
}
static inline float *
SPARSEVEC_VALUES(SparseVector * x)
{
return (float *) (((char *) x) + offsetof(SparseVector, indices) + (x->nnz * sizeof(int32)));
}
SparseVector *InitSparseVector(int dim, int nnz);
#endif

View File

@@ -2,15 +2,22 @@
#include <math.h>
#include "bitutils.h"
#include "bitvec.h"
#include "catalog/pg_type.h"
#include "common/shortest_dec.h"
#include "fmgr.h"
#include "halfutils.h"
#include "halfvec.h"
#include "hnsw.h"
#include "ivfflat.h"
#include "lib/stringinfo.h"
#include "libpq/pqformat.h"
#include "port.h" /* for strtof() */
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
#include "utils/lsyscache.h"
#include "utils/numeric.h"
#include "vector.h"
@@ -19,13 +26,6 @@
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 120000
#include "common/shortest_dec.h"
#include "utils/float.h"
#else
#include <float.h>
#endif
#if PG_VERSION_NUM < 130000
#define TYPALIGN_DOUBLE 'd'
#define TYPALIGN_INT 'i'
@@ -34,6 +34,12 @@
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
#if defined(USE_TARGET_CLONES) && !defined(__FMA__)
#define VECTOR_TARGET_CLONES __attribute__((target_clones("default", "fma")))
#else
#define VECTOR_TARGET_CLONES
#endif
PG_MODULE_MAGIC;
/*
@@ -43,6 +49,8 @@ PGDLLEXPORT void _PG_init(void);
void
_PG_init(void)
{
BitvecInit();
HalfvecInit();
HnswInit();
IvfflatInit();
}
@@ -173,34 +181,41 @@ float_underflow_error(void)
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_in);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_in);
Datum
vector_in(PG_FUNCTION_ARGS)
{
char *str = PG_GETARG_CSTRING(0);
char *lit = PG_GETARG_CSTRING(0);
int32 typmod = PG_GETARG_INT32(2);
float x[VECTOR_MAX_DIM];
int dim = 0;
char *pt;
char *stringEnd;
char *pt = lit;
Vector *result;
char *lit = pstrdup(str);
while (vector_isspace(*str))
str++;
while (vector_isspace(*pt))
pt++;
if (*str != '[')
if (*pt != '[')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit),
errmsg("invalid input syntax for type vector: \"%s\"", lit),
errdetail("Vector contents must start with \"[\".")));
str++;
pt = strtok(str, ",");
stringEnd = pt;
pt++;
while (pt != NULL && *stringEnd != ']')
while (vector_isspace(*pt))
pt++;
if (*pt == ']')
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
for (;;)
{
float val;
char *stringEnd;
if (dim == VECTOR_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
@@ -215,61 +230,55 @@ vector_in(PG_FUNCTION_ARGS)
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
errno = 0;
/* Use strtof like float4in to avoid a double-rounding problem */
x[dim] = strtof(pt, &stringEnd);
CheckElement(x[dim]);
dim++;
/* Postgres sets LC_NUMERIC to C on startup */
val = strtof(pt, &stringEnd);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
while (vector_isspace(*stringEnd))
stringEnd++;
/* Check for range error like float4in */
if (errno == ERANGE && isinf(val))
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type vector", pnstrdup(pt, stringEnd - pt))));
if (*stringEnd != '\0' && *stringEnd != ']')
CheckElement(val);
x[dim++] = val;
pt = stringEnd;
while (vector_isspace(*pt))
pt++;
if (*pt == ',')
pt++;
else if (*pt == ']')
{
pt++;
break;
}
else
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
pt = strtok(NULL, ",");
}
if (stringEnd == NULL || *stringEnd != ']')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit),
errdetail("Unexpected end of input.")));
stringEnd++;
/* Only whitespace is allowed after the closing brace */
while (vector_isspace(*stringEnd))
stringEnd++;
while (vector_isspace(*pt))
pt++;
if (*stringEnd != '\0')
if (*pt != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit),
errmsg("invalid input syntax for type vector: \"%s\"", lit),
errdetail("Junk after closing right brace.")));
/* Ensure no consecutive delimiters since strtok skips */
for (pt = lit + 1; *pt != '\0'; pt++)
{
if (pt[-1] == ',' && *pt == ',')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit)));
}
if (dim < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
pfree(lit);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitVector(dim);
@@ -279,10 +288,13 @@ vector_in(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
#define AppendChar(ptr, c) (*(ptr)++ = (c))
#define AppendFloat(ptr, f) ((ptr) += float_to_shortest_decimal_bufn((f), (ptr)))
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_out);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_out);
Datum
vector_out(PG_FUNCTION_ARGS)
{
@@ -290,16 +302,6 @@ vector_out(PG_FUNCTION_ARGS)
int dim = vector->dim;
char *buf;
char *ptr;
int n;
#if PG_VERSION_NUM < 120000
int ndig = FLT_DIG + extra_float_digits;
if (ndig < 1)
ndig = 1;
#define FLOAT_SHORTEST_DECIMAL_LEN (ndig + 10)
#endif
/*
* Need:
@@ -314,25 +316,17 @@ vector_out(PG_FUNCTION_ARGS)
buf = (char *) palloc(FLOAT_SHORTEST_DECIMAL_LEN * dim + 2);
ptr = buf;
*ptr = '[';
ptr++;
AppendChar(ptr, '[');
for (int i = 0; i < dim; i++)
{
if (i > 0)
{
*ptr = ',';
ptr++;
}
AppendChar(ptr, ',');
#if PG_VERSION_NUM >= 120000
n = float_to_shortest_decimal_bufn(vector->x[i], ptr);
#else
n = sprintf(ptr, "%.*g", ndig, vector->x[i]);
#endif
ptr += n;
AppendFloat(ptr, vector->x[i]);
}
*ptr = ']';
ptr++;
AppendChar(ptr, ']');
*ptr = '\0';
PG_FREE_IF_COPY(vector, 0);
@@ -354,7 +348,7 @@ PrintVector(char *msg, Vector * vector)
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_typmod_in);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_typmod_in);
Datum
vector_typmod_in(PG_FUNCTION_ARGS)
{
@@ -385,7 +379,7 @@ vector_typmod_in(PG_FUNCTION_ARGS)
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_recv);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_recv);
Datum
vector_recv(PG_FUNCTION_ARGS)
{
@@ -419,7 +413,7 @@ vector_recv(PG_FUNCTION_ARGS)
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_send);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_send);
Datum
vector_send(PG_FUNCTION_ARGS)
{
@@ -439,7 +433,7 @@ vector_send(PG_FUNCTION_ARGS)
* Convert vector to vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector);
Datum
vector(PG_FUNCTION_ARGS)
{
@@ -454,7 +448,7 @@ vector(PG_FUNCTION_ARGS)
/*
* Convert array to vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(array_to_vector);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(array_to_vector);
Datum
array_to_vector(PG_FUNCTION_ARGS)
{
@@ -528,7 +522,7 @@ array_to_vector(PG_FUNCTION_ARGS)
/*
* Convert vector to float4[]
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_float4);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_to_float4);
Datum
vector_to_float4(PG_FUNCTION_ARGS)
{
@@ -549,131 +543,150 @@ vector_to_float4(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Convert half vector to vector
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_to_vector);
Datum
halfvec_to_vector(PG_FUNCTION_ARGS)
{
HalfVector *vec = PG_GETARG_HALFVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
CheckDim(vec->dim);
CheckExpectedDim(typmod, vec->dim);
result = InitVector(vec->dim);
for (int i = 0; i < vec->dim; i++)
result->x[i] = HalfToFloat4(vec->x[i]);
PG_RETURN_POINTER(result);
}
VECTOR_TARGET_CLONES static float
VectorL2SquaredDistance(int dim, float *ax, float *bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float diff = ax[i] - bx[i];
distance += diff * diff;
}
return distance;
}
/*
* Get the L2 distance between vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(l2_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l2_distance);
Datum
l2_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
float diff;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
diff = ax[i] - bx[i];
distance += diff * diff;
}
PG_RETURN_FLOAT8(sqrt((double) distance));
PG_RETURN_FLOAT8(sqrt((double) VectorL2SquaredDistance(a->dim, a->x, b->x)));
}
/*
* Get the L2 squared distance between vectors
* This saves a sqrt calculation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_l2_squared_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_l2_squared_distance);
Datum
vector_l2_squared_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
float diff;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
diff = ax[i] - bx[i];
distance += diff * diff;
}
PG_RETURN_FLOAT8((double) VectorL2SquaredDistance(a->dim, a->x, b->x));
}
PG_RETURN_FLOAT8((double) distance);
VECTOR_TARGET_CLONES static float
VectorInnerProduct(int dim, float *ax, float *bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += ax[i] * bx[i];
return distance;
}
/*
* Get the inner product of two vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(inner_product);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(inner_product);
Datum
inner_product(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += ax[i] * bx[i];
PG_RETURN_FLOAT8((double) distance);
PG_RETURN_FLOAT8((double) VectorInnerProduct(a->dim, a->x, b->x));
}
/*
* Get the negative inner product of two vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_negative_inner_product);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_negative_inner_product);
Datum
vector_negative_inner_product(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += ax[i] * bx[i];
PG_RETURN_FLOAT8((double) distance * -1);
PG_RETURN_FLOAT8((double) -VectorInnerProduct(a->dim, a->x, b->x));
}
/*
* Get the cosine distance between two vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(cosine_distance);
Datum
cosine_distance(PG_FUNCTION_ARGS)
VECTOR_TARGET_CLONES static double
VectorCosineSimilarity(int dim, float *ax, float *bx)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
float similarity = 0.0;
float norma = 0.0;
float normb = 0.0;
double similarity;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
for (int i = 0; i < dim; i++)
{
distance += ax[i] * bx[i];
similarity += ax[i] * bx[i];
norma += ax[i] * ax[i];
normb += bx[i] * bx[i];
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
similarity = (double) distance / sqrt((double) norma * (double) normb);
return (double) similarity / sqrt((double) norma * (double) normb);
}
/*
* Get the cosine distance between two vectors
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(cosine_distance);
Datum
cosine_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
double similarity;
CheckDims(a, b);
similarity = VectorCosineSimilarity(a->dim, a->x, b->x);
#ifdef _MSC_VER
/* /fp:fast may not propagate NaN */
@@ -695,24 +708,17 @@ cosine_distance(PG_FUNCTION_ARGS)
* Currently uses angular distance since needs to satisfy triangle inequality
* Assumes inputs are unit vectors (skips norm)
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_spherical_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_spherical_distance);
Datum
vector_spherical_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float dp = 0.0;
double distance;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
dp += ax[i] * bx[i];
distance = (double) dp;
distance = (double) VectorInnerProduct(a->dim, a->x, b->x);
/* Prevent NaN with acos with loss of precision */
if (distance > 1)
@@ -723,32 +729,38 @@ vector_spherical_distance(PG_FUNCTION_ARGS)
PG_RETURN_FLOAT8(acos(distance) / M_PI);
}
/* Does not require FMA, but keep logic simple */
VECTOR_TARGET_CLONES static float
VectorL1Distance(int dim, float *ax, float *bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += fabsf(ax[i] - bx[i]);
return distance;
}
/*
* Get the L1 distance between vectors
* Get the L1 distance between two vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(l1_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l1_distance);
Datum
l1_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += fabsf(ax[i] - bx[i]);
PG_RETURN_FLOAT8((double) distance);
PG_RETURN_FLOAT8((double) VectorL1Distance(a->dim, a->x, b->x));
}
/*
* Get the dimensions of a vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_dims);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_dims);
Datum
vector_dims(PG_FUNCTION_ARGS)
{
@@ -760,7 +772,7 @@ vector_dims(PG_FUNCTION_ARGS)
/*
* Get the L2 norm of a vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_norm);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_norm);
Datum
vector_norm(PG_FUNCTION_ARGS)
{
@@ -775,10 +787,49 @@ vector_norm(PG_FUNCTION_ARGS)
PG_RETURN_FLOAT8(sqrt(norm));
}
/*
* Normalize a vector with the L2 norm
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l2_normalize);
Datum
l2_normalize(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
float *ax = a->x;
double norm = 0;
Vector *result;
float *rx;
result = InitVector(a->dim);
rx = result->x;
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
norm += (double) ax[i] * (double) ax[i];
norm = sqrt(norm);
/* Return zero vector for zero norm */
if (norm > 0)
{
for (int i = 0; i < a->dim; i++)
rx[i] = ax[i] / norm;
/* Check for overflow */
for (int i = 0; i < a->dim; i++)
{
if (isinf(rx[i]))
float_overflow_error();
}
}
PG_RETURN_POINTER(result);
}
/*
* Add vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_add);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_add);
Datum
vector_add(PG_FUNCTION_ARGS)
{
@@ -811,7 +862,7 @@ vector_add(PG_FUNCTION_ARGS)
/*
* Subtract vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_sub);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_sub);
Datum
vector_sub(PG_FUNCTION_ARGS)
{
@@ -844,7 +895,7 @@ vector_sub(PG_FUNCTION_ARGS)
/*
* Multiply vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_mul);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_mul);
Datum
vector_mul(PG_FUNCTION_ARGS)
{
@@ -877,15 +928,105 @@ vector_mul(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Concatenate vectors
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_concat);
Datum
vector_concat(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
Vector *result;
int dim = a->dim + b->dim;
CheckDim(dim);
result = InitVector(dim);
for (int i = 0; i < a->dim; i++)
result->x[i] = a->x[i];
for (int i = 0; i < b->dim; i++)
result->x[i + a->dim] = b->x[i];
PG_RETURN_POINTER(result);
}
/*
* Quantize a vector
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(binary_quantize);
Datum
binary_quantize(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
float *ax = a->x;
VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result);
for (int i = 0; i < a->dim; i++)
rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result);
}
/*
* Get a subvector
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(subvector);
Datum
subvector(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
int32 start = PG_GETARG_INT32(1);
int32 count = PG_GETARG_INT32(2);
int32 end;
float *ax = a->x;
Vector *result;
int dim;
if (count < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
/*
* Check if (start + count > a->dim), avoiding integer overflow. a->dim
* and count are both positive, so a->dim - count won't overflow.
*/
if (start > a->dim - count)
end = a->dim + 1;
else
end = start + count;
/* Indexing starts at 1, like substring */
if (start < 1)
start = 1;
else if (start > a->dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
dim = end - start;
CheckDim(dim);
result = InitVector(dim);
for (int i = 0; i < dim; i++)
result->x[i] = ax[start - 1 + i];
PG_RETURN_POINTER(result);
}
/*
* Internal helper to compare vectors
*/
int
vector_cmp_internal(Vector * a, Vector * b)
{
CheckDims(a, b);
int dim = Min(a->dim, b->dim);
for (int i = 0; i < a->dim; i++)
/* Check values before dimensions to be consistent with Postgres arrays */
for (int i = 0; i < dim; i++)
{
if (a->x[i] < b->x[i])
return -1;
@@ -893,18 +1034,25 @@ vector_cmp_internal(Vector * a, Vector * b)
if (a->x[i] > b->x[i])
return 1;
}
if (a->dim < b->dim)
return -1;
if (a->dim > b->dim)
return 1;
return 0;
}
/*
* Less than
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_lt);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_lt);
Datum
vector_lt(PG_FUNCTION_ARGS)
{
Vector *a = (Vector *) PG_GETARG_VECTOR_P(0);
Vector *b = (Vector *) PG_GETARG_VECTOR_P(1);
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
PG_RETURN_BOOL(vector_cmp_internal(a, b) < 0);
}
@@ -912,12 +1060,12 @@ vector_lt(PG_FUNCTION_ARGS)
/*
* Less than or equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_le);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_le);
Datum
vector_le(PG_FUNCTION_ARGS)
{
Vector *a = (Vector *) PG_GETARG_VECTOR_P(0);
Vector *b = (Vector *) PG_GETARG_VECTOR_P(1);
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
PG_RETURN_BOOL(vector_cmp_internal(a, b) <= 0);
}
@@ -925,12 +1073,12 @@ vector_le(PG_FUNCTION_ARGS)
/*
* Equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_eq);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_eq);
Datum
vector_eq(PG_FUNCTION_ARGS)
{
Vector *a = (Vector *) PG_GETARG_VECTOR_P(0);
Vector *b = (Vector *) PG_GETARG_VECTOR_P(1);
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
PG_RETURN_BOOL(vector_cmp_internal(a, b) == 0);
}
@@ -938,12 +1086,12 @@ vector_eq(PG_FUNCTION_ARGS)
/*
* Not equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_ne);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_ne);
Datum
vector_ne(PG_FUNCTION_ARGS)
{
Vector *a = (Vector *) PG_GETARG_VECTOR_P(0);
Vector *b = (Vector *) PG_GETARG_VECTOR_P(1);
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
PG_RETURN_BOOL(vector_cmp_internal(a, b) != 0);
}
@@ -951,12 +1099,12 @@ vector_ne(PG_FUNCTION_ARGS)
/*
* Greater than or equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_ge);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_ge);
Datum
vector_ge(PG_FUNCTION_ARGS)
{
Vector *a = (Vector *) PG_GETARG_VECTOR_P(0);
Vector *b = (Vector *) PG_GETARG_VECTOR_P(1);
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
PG_RETURN_BOOL(vector_cmp_internal(a, b) >= 0);
}
@@ -964,12 +1112,12 @@ vector_ge(PG_FUNCTION_ARGS)
/*
* Greater than
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_gt);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_gt);
Datum
vector_gt(PG_FUNCTION_ARGS)
{
Vector *a = (Vector *) PG_GETARG_VECTOR_P(0);
Vector *b = (Vector *) PG_GETARG_VECTOR_P(1);
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
PG_RETURN_BOOL(vector_cmp_internal(a, b) > 0);
}
@@ -977,12 +1125,12 @@ vector_gt(PG_FUNCTION_ARGS)
/*
* Compare vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_cmp);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_cmp);
Datum
vector_cmp(PG_FUNCTION_ARGS)
{
Vector *a = (Vector *) PG_GETARG_VECTOR_P(0);
Vector *b = (Vector *) PG_GETARG_VECTOR_P(1);
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
PG_RETURN_INT32(vector_cmp_internal(a, b));
}
@@ -990,7 +1138,7 @@ vector_cmp(PG_FUNCTION_ARGS)
/*
* Accumulate vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_accum);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_accum);
Datum
vector_accum(PG_FUNCTION_ARGS)
{
@@ -1049,12 +1197,13 @@ vector_accum(PG_FUNCTION_ARGS)
}
/*
* Combine vectors
* Combine vectors or half vectors (also used for halfvec_combine)
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_combine);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_combine);
Datum
vector_combine(PG_FUNCTION_ARGS)
{
/* Must also update parameters of halfvec_combine if modifying */
ArrayType *statearray1 = PG_GETARG_ARRAYTYPE_P(0);
ArrayType *statearray2 = PG_GETARG_ARRAYTYPE_P(1);
float8 *statevalues1;
@@ -1121,7 +1270,7 @@ vector_combine(PG_FUNCTION_ARGS)
/*
* Average vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_avg);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_avg);
Datum
vector_avg(PG_FUNCTION_ARGS)
{
@@ -1151,3 +1300,26 @@ vector_avg(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Convert sparse vector to dense vector
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_to_vector);
Datum
sparsevec_to_vector(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
int dim = svec->dim;
float *values = SPARSEVEC_VALUES(svec);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitVector(dim);
for (int i = 0; i < svec->nnz; i++)
result->x[svec->indices[i]] = values[i];
PG_RETURN_POINTER(result);
}

View File

@@ -12,7 +12,7 @@ typedef struct Vector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int16 dim; /* number of dimensions */
int16 unused;
int16 unused; /* reserved for future use, always zero */
float x[FLEXIBLE_ARRAY_MEMBER];
} Vector;
@@ -20,4 +20,11 @@ Vector *InitVector(int dim);
void PrintVector(char *msg, Vector * vector);
int vector_cmp_internal(Vector * a, Vector * b);
/* TODO Move to better place */
#if PG_VERSION_NUM >= 160000
#define FUNCTION_PREFIX
#else
#define FUNCTION_PREFIX PGDLLEXPORT
#endif
#endif

140
test/expected/bit.out Normal file
View File

@@ -0,0 +1,140 @@
SELECT hamming_distance('111', '111');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance('111', '110');
hamming_distance
------------------
1
(1 row)
SELECT hamming_distance('111', '100');
hamming_distance
------------------
2
(1 row)
SELECT hamming_distance('111', '000');
hamming_distance
------------------
3
(1 row)
SELECT hamming_distance('10101010101010101010', '01010101010101010101');
hamming_distance
------------------
20
(1 row)
SELECT hamming_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010');
hamming_distance
------------------
513
(1 row)
SELECT hamming_distance('110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011', '100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001');
hamming_distance
------------------
2
(1 row)
SELECT hamming_distance('', '');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance('111', '00');
ERROR: different bit lengths 3 and 2
SELECT hamming_distance('111', '000'::varbit(4));
hamming_distance
------------------
3
(1 row)
SELECT hamming_distance('111', '0000'::varbit(4));
ERROR: different bit lengths 3 and 4
SELECT jaccard_distance('1111', '1111');
jaccard_distance
------------------
0
(1 row)
SELECT jaccard_distance('1111', '1110');
jaccard_distance
------------------
0.25
(1 row)
SELECT jaccard_distance('1111', '1100');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance('1111', '1000');
jaccard_distance
------------------
0.75
(1 row)
SELECT jaccard_distance('1111', '0000');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('1100', '1000');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance('10101010101010101010', '01010101010101010101');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101');
jaccard_distance
------------------
0
(1 row)
SELECT jaccard_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011', '100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance('', '');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('1111', '000');
ERROR: different bit lengths 4 and 3
SELECT jaccard_distance('1111', '0000'::varbit(5));
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('1111', '00000'::varbit(5));
ERROR: different bit lengths 4 and 5

View File

@@ -1,4 +1,5 @@
SET enable_seqscan = off;
-- vector
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t (val);
@@ -8,10 +9,53 @@ SELECT * FROM t WHERE val = '[1,2,3]';
[1,2,3]
(1 row)
SELECT * FROM t ORDER BY val LIMIT 1;
SELECT * FROM t ORDER BY val;
val
---------
[0,0,0]
(1 row)
[1,1,1]
[1,2,3]
(4 rows)
DROP TABLE t;
-- halfvec
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t (val);
SELECT * FROM t WHERE val = '[1,2,3]';
val
---------
[1,2,3]
(1 row)
SELECT * FROM t ORDER BY val;
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
(4 rows)
DROP TABLE t;
-- sparsevec
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t (val);
SELECT * FROM t WHERE val = '{1:1,2:2,3:3}/3';
val
-----------------
{1:1,2:2,3:3}/3
(1 row)
SELECT * FROM t ORDER BY val;
val
-----------------
{}/3
{1:1,2:1,3:1}/3
{1:1,2:2,3:3}/3
(4 rows)
DROP TABLE t;

View File

@@ -28,6 +28,26 @@ SELECT ARRAY[1,2,3]::numeric[]::vector;
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::real[];
float4
---------
{1,2,3}
(1 row)
SELECT '{1,2,3}'::real[]::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{NULL}'::real[]::vector;
ERROR: array must not contain nulls
SELECT '{NaN}'::real[]::vector;
@@ -40,10 +60,152 @@ SELECT '{}'::real[]::vector;
ERROR: vector must have at least 1 dimension
SELECT '{{1}}'::real[]::vector;
ERROR: array must be 1-D
SELECT '[1,2,3]'::vector::real[];
float4
SELECT '{1,2,3}'::double precision[]::vector;
vector
---------
{1,2,3}
[1,2,3]
(1 row)
SELECT '{1,2,3}'::double precision[]::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::double precision[]::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{4e38,-4e38}'::double precision[]::vector;
ERROR: infinite value not allowed in vector
SELECT '{1e-46,-1e-46}'::double precision[]::vector;
vector
--------
[0,-0]
(1 row)
SELECT '[1,2,3]'::vector::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[65520]'::vector::halfvec;
ERROR: "65520" is out of range for type halfvec
SELECT '[1e-8]'::vector::halfvec;
halfvec
---------
[0]
(1 row)
SELECT '[1,2,3]'::halfvec::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{1,2,3}'::real[]::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '{65520,-65520}'::real[]::halfvec;
ERROR: "65520" is out of range for type halfvec
SELECT '{1e-8,-1e-8}'::real[]::halfvec;
halfvec
---------
[0,-0]
(1 row)
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(5);
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(4);
ERROR: expected 4 dimensions, not 5
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector;
vector
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(5);
vector
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(4);
ERROR: expected 4 dimensions, not 5
SELECT '{}/16001'::sparsevec::vector;
ERROR: vector cannot have more than 16000 dimensions
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec;
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec(5);
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec(4);
ERROR: expected 4 dimensions, not 5
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec;
halfvec
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec(5);
halfvec
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec(4);
ERROR: expected 4 dimensions, not 5
SELECT '{}/16001'::sparsevec::halfvec;
ERROR: halfvec cannot have more than 16000 dimensions
SELECT '{1:65520}/1'::sparsevec::halfvec;
ERROR: "65520" is out of range for type halfvec
SELECT '{1:1e-8}/1'::sparsevec::halfvec;
halfvec
---------
[0]
(1 row)
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;

View File

@@ -1,8 +1,9 @@
-- vector
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val vector(3));
\copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/data.bin' WITH (FORMAT binary)
\copy t TO 'results/vector.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/vector.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
val
---------
@@ -14,3 +15,37 @@ SELECT * FROM t2 ORDER BY val;
DROP TABLE t;
DROP TABLE t2;
-- halfvec
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val halfvec(3));
\copy t TO 'results/halfvec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/halfvec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
(4 rows)
DROP TABLE t;
DROP TABLE t2;
-- sparsevec
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE TABLE t2 (val sparsevec(3));
\copy t TO 'results/sparsevec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/sparsevec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
val
-----------------
{}/3
{1:1,2:1,3:1}/3
{1:1,2:2,3:3}/3
(4 rows)
DROP TABLE t;
DROP TABLE t2;

View File

@@ -1,210 +0,0 @@
SELECT '[1,2,3]'::vector + '[4,5,6]';
?column?
----------
[5,7,9]
(1 row)
SELECT '[3e38]'::vector + '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2,3]'::vector - '[4,5,6]';
?column?
------------
[-3,-3,-3]
(1 row)
SELECT '[-3e38]'::vector - '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2,3]'::vector * '[4,5,6]';
?column?
-----------
[4,10,18]
(1 row)
SELECT '[1e37]'::vector * '[1e37]';
ERROR: value out of range: overflow
SELECT '[1e-37]'::vector * '[1e-37]';
ERROR: value out of range: underflow
SELECT vector_dims('[1,2,3]');
vector_dims
-------------
3
(1 row)
SELECT round(vector_norm('[1,1]')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT vector_norm('[3,4]');
vector_norm
-------------
5
(1 row)
SELECT vector_norm('[0,1]');
vector_norm
-------------
1
(1 row)
SELECT vector_norm('[3e37,4e37]')::real;
vector_norm
-------------
5e+37
(1 row)
SELECT l2_distance('[0,0]', '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]', '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l2_distance('[3e38]', '[-3e38]');
l2_distance
-------------
Infinity
(1 row)
SELECT inner_product('[1,2]', '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT inner_product('[3e38]', '[3e38]');
inner_product
---------------
Infinity
(1 row)
SELECT cosine_distance('[1,2]', '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]', '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]', '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]', '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]', '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[3e38]', '[3e38]');
cosine_distance
-----------------
NaN
(1 row)
SELECT l1_distance('[0,0]', '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]', '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l1_distance('[3e38]', '[-3e38]');
l1_distance
-------------
Infinity
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
avg
-----
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: expected 2 dimensions, not 1
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
avg
---------
[3e+38]
(1 row)
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
ERROR: vector cannot have more than 16000 dimensions
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
sum
-----
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: different vector dimensions 2 and 1
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
ERROR: value out of range: overflow

636
test/expected/halfvec.out Normal file
View File

@@ -0,0 +1,636 @@
SELECT '[1,2,3]'::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[-1,-2,-3]'::halfvec;
halfvec
------------
[-1,-2,-3]
(1 row)
SELECT '[1.,2.,3.]'::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT ' [ 1, 2 , 3 ] '::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1.23456]'::halfvec;
halfvec
------------
[1.234375]
(1 row)
SELECT '[hello,1]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[hello,1]"
LINE 1: SELECT '[hello,1]'::halfvec;
^
SELECT '[NaN,1]'::halfvec;
ERROR: NaN not allowed in halfvec
LINE 1: SELECT '[NaN,1]'::halfvec;
^
SELECT '[Infinity,1]'::halfvec;
ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[Infinity,1]'::halfvec;
^
SELECT '[-Infinity,1]'::halfvec;
ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[-Infinity,1]'::halfvec;
^
SELECT '[65519,-65519]'::halfvec;
halfvec
----------------
[65504,-65504]
(1 row)
SELECT '[65520,-65520]'::halfvec;
ERROR: "65520" is out of range for type halfvec
LINE 1: SELECT '[65520,-65520]'::halfvec;
^
SELECT '[1e-8,-1e-8]'::halfvec;
halfvec
---------
[0,-0]
(1 row)
SELECT '[4e38,1]'::halfvec;
ERROR: "4e38" is out of range for type halfvec
LINE 1: SELECT '[4e38,1]'::halfvec;
^
SELECT '[1e-46,1]'::halfvec;
halfvec
---------
[0,1]
(1 row)
SELECT '[1,2,3'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,2,3"
LINE 1: SELECT '[1,2,3'::halfvec;
^
SELECT '[1,2,3]9'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::halfvec;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::halfvec;
ERROR: invalid input syntax for type halfvec: "1,2,3"
LINE 1: SELECT '1,2,3'::halfvec;
^
DETAIL: Vector contents must start with "[".
SELECT ''::halfvec;
ERROR: invalid input syntax for type halfvec: ""
LINE 1: SELECT ''::halfvec;
^
DETAIL: Vector contents must start with "[".
SELECT '['::halfvec;
ERROR: invalid input syntax for type halfvec: "["
LINE 1: SELECT '['::halfvec;
^
SELECT '[ '::halfvec;
ERROR: invalid input syntax for type halfvec: "[ "
LINE 1: SELECT '[ '::halfvec;
^
SELECT '[,'::halfvec;
ERROR: invalid input syntax for type halfvec: "[,"
LINE 1: SELECT '[,'::halfvec;
^
SELECT '[]'::halfvec;
ERROR: halfvec must have at least 1 dimension
LINE 1: SELECT '[]'::halfvec;
^
SELECT '[ ]'::halfvec;
ERROR: halfvec must have at least 1 dimension
LINE 1: SELECT '[ ]'::halfvec;
^
SELECT '[,]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[,]"
LINE 1: SELECT '[,]'::halfvec;
^
SELECT '[1,]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,]"
LINE 1: SELECT '[1,]'::halfvec;
^
SELECT '[1a]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1a]"
LINE 1: SELECT '[1a]'::halfvec;
^
SELECT '[1,,3]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,,3]"
LINE 1: SELECT '[1,,3]'::halfvec;
^
SELECT '[1, ,3]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::halfvec;
^
SELECT '[1,2,3]'::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::halfvec(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::halfvec(3, 2);
^
SELECT '[1,2,3]'::halfvec('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::halfvec('a');
^
SELECT '[1,2,3]'::halfvec(0);
ERROR: dimensions for type halfvec must be at least 1
LINE 1: SELECT '[1,2,3]'::halfvec(0);
^
SELECT '[1,2,3]'::halfvec(16001);
ERROR: dimensions for type halfvec cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::halfvec(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::halfvec[]);
unnest
---------
[1,2,3]
[4,5,6]
(2 rows)
SELECT '{"[1,2,3]"}'::halfvec(2)[];
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::halfvec + '[4,5,6]';
?column?
----------
[5,7,9]
(1 row)
SELECT '[65519]'::halfvec + '[65519]';
ERROR: value out of range: overflow
SELECT '[1,2]'::halfvec + '[3]';
ERROR: different halfvec dimensions 2 and 1
SELECT '[1,2,3]'::halfvec - '[4,5,6]';
?column?
------------
[-3,-3,-3]
(1 row)
SELECT '[-65519]'::halfvec - '[65519]';
ERROR: value out of range: overflow
SELECT '[1,2]'::halfvec - '[3]';
ERROR: different halfvec dimensions 2 and 1
SELECT '[1,2,3]'::halfvec * '[4,5,6]';
?column?
-----------
[4,10,18]
(1 row)
SELECT '[65519]'::halfvec * '[65519]';
ERROR: value out of range: overflow
SELECT '[1e-7]'::halfvec * '[1e-7]';
ERROR: value out of range: underflow
SELECT '[1,2]'::halfvec * '[3]';
ERROR: different halfvec dimensions 2 and 1
SELECT '[1,2,3]'::halfvec || '[4,5]';
?column?
-------------
[1,2,3,4,5]
(1 row)
SELECT array_fill(0, ARRAY[16000])::halfvec || '[1]';
ERROR: halfvec cannot have more than 16000 dimensions
SELECT '[1,2,3]'::halfvec < '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec < '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec <= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec <= '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec = '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec = '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec != '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec != '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec >= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec >= '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec > '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec > '[1,2]';
?column?
----------
t
(1 row)
SELECT halfvec_cmp('[1,2,3]', '[1,2,3]');
halfvec_cmp
-------------
0
(1 row)
SELECT halfvec_cmp('[1,2,3]', '[0,0,0]');
halfvec_cmp
-------------
1
(1 row)
SELECT halfvec_cmp('[0,0,0]', '[1,2,3]');
halfvec_cmp
-------------
-1
(1 row)
SELECT halfvec_cmp('[1,2]', '[1,2,3]');
halfvec_cmp
-------------
-1
(1 row)
SELECT halfvec_cmp('[1,2,3]', '[1,2]');
halfvec_cmp
-------------
1
(1 row)
SELECT halfvec_cmp('[1,2]', '[2,3,4]');
halfvec_cmp
-------------
-1
(1 row)
SELECT halfvec_cmp('[2,3]', '[1,2,3]');
halfvec_cmp
-------------
1
(1 row)
SELECT vector_dims('[1,2,3]'::halfvec);
vector_dims
-------------
3
(1 row)
SELECT round(l2_norm('[1,1]'::halfvec)::numeric, 5);
round
---------
1.41421
(1 row)
SELECT l2_norm('[3,4]'::halfvec);
l2_norm
---------
5
(1 row)
SELECT l2_norm('[0,1]'::halfvec);
l2_norm
---------
1
(1 row)
SELECT l2_norm('[0,0]'::halfvec);
l2_norm
---------
0
(1 row)
SELECT l2_norm('[2]'::halfvec);
l2_norm
---------
2
(1 row)
SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,1,1,1,1,1,1,4,5]');
l2_distance
-------------
5
(1 row)
SELECT '[0,0]'::halfvec <-> '[3,4]';
?column?
----------
5
(1 row)
SELECT inner_product('[1,2]'::halfvec, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT inner_product('[65504]'::halfvec, '[65504]');
inner_product
---------------
4290774016
(1 row)
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
inner_product
---------------
45
(1 row)
SELECT '[1,2]'::halfvec <#> '[3,4]';
?column?
----------
-11
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]'::halfvec, '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT cosine_distance('[1,1]'::halfvec, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[-1,-2,-3,-4,-5,-6,-7,-8,-9]');
cosine_distance
-----------------
2
(1 row)
SELECT '[1,2]'::halfvec <=> '[2,4]';
?column?
----------
0
(1 row)
SELECT l1_distance('[0,0]'::halfvec, '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
l1_distance
-------------
0
(1 row)
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[0,3,2,5,4,7,6,9,8]');
l1_distance
-------------
9
(1 row)
SELECT '[0,0]'::halfvec <+> '[3,4]';
?column?
----------
7
(1 row)
SELECT l2_normalize('[3,4]'::halfvec);
l2_normalize
------------------------
[0.60009766,0.7998047]
(1 row)
SELECT l2_normalize('[3,0]'::halfvec);
l2_normalize
--------------
[1,0]
(1 row)
SELECT l2_normalize('[0,0.1]'::halfvec);
l2_normalize
--------------
[0,1]
(1 row)
SELECT l2_normalize('[0,0]'::halfvec);
l2_normalize
--------------
[0,0]
(1 row)
SELECT l2_normalize('[65504]'::halfvec);
l2_normalize
--------------
[1]
(1 row)
SELECT binary_quantize('[1,0,-1]'::halfvec);
binary_quantize
-----------------
100
(1 row)
SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
binary_quantize
-----------------
01001110101
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
subvector
-----------
[1,2,3]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2);
subvector
-----------
[3,4]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 3);
subvector
-----------
[1]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 9);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 0);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, -1);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 2);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, 2147483647, 10);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2147483647);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, -2147483644, 2147483647);
subvector
-----------
[1,2]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]']) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]', NULL]) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY[]::halfvec[]) v;
avg
-----
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::halfvec, '[3]']) v;
ERROR: expected 2 dimensions, not 1
SELECT avg(v) FROM unnest(ARRAY['[65504]'::halfvec, '[65504]']) v;
avg
---------
[65504]
(1 row)
SELECT halfvec_avg(array_agg(n)) FROM generate_series(1, 16002) n;
ERROR: halfvec cannot have more than 16000 dimensions
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]']) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]', NULL]) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY[]::halfvec[]) v;
sum
-----
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::halfvec, '[3]']) v;
ERROR: different halfvec dimensions 2 and 1
SELECT sum(v) FROM unnest(ARRAY['[65504]'::halfvec, '[65504]']) v;
ERROR: value out of range: overflow

View File

@@ -0,0 +1,51 @@
SET enable_seqscan = off;
-- hamming
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
val
-----
111
110
100
000
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- jaccard
CREATE TABLE t (val bit(4));
INSERT INTO t (val) VALUES (B'0000'), (B'1100'), (B'1111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_jaccard_ops);
INSERT INTO t (val) VALUES (B'1110');
SELECT * FROM t ORDER BY val <%> B'1111';
val
------
1111
1110
1100
0000
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <%> (SELECT NULL::bit)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- varbit
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
ERROR: type not supported for hnsw index
CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
ERROR: column cannot have more than 64000 dimensions for hnsw index
DROP TABLE t;

View File

@@ -1,26 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_cosine_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
val
---------
[1,1,1]
[1,2,3]
[1,2,4]
(3 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
count
-------
3
(1 row)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
count
-------
3
(1 row)
DROP TABLE t;

View File

@@ -0,0 +1,102 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;
-- inner product
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_ip_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
val
---------
[1,2,4]
[1,2,3]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::halfvec)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- cosine
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_cosine_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
val
---------
[1,1,1]
[1,2,3]
[1,2,4]
(3 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
count
-------
3
(1 row)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t2;
count
-------
3
(1 row)
DROP TABLE t;
-- L1
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_l1_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <+> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::halfvec)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

@@ -1,21 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_ip_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
val
---------
[1,2,4]
[1,2,3]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

@@ -1,36 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;

View File

@@ -1,26 +0,0 @@
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 1);
ERROR: value 1 out of bounds for option "m"
DETAIL: Valid values are between "2" and "100".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
ERROR: value 101 out of bounds for option "m"
DETAIL: Valid values are between "2" and "100".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
ERROR: value 3 out of bounds for option "ef_construction"
DETAIL: Valid values are between "4" and "1000".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
ERROR: value 1001 out of bounds for option "ef_construction"
DETAIL: Valid values are between "4" and "1000".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
ERROR: ef_construction must be greater than or equal to 2 * m
SHOW hnsw.ef_search;
hnsw.ef_search
----------------
40
(1 row)
SET hnsw.ef_search = 0;
ERROR: 0 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
SET hnsw.ef_search = 1001;
ERROR: 1001 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
DROP TABLE t;

View File

@@ -0,0 +1,112 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
val
-----------------
{1:1,2:2,3:3}/3
{1:1,2:2,3:4}/3
{1:1,2:1,3:1}/3
{}/3
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
val
-----
(0 rows)
DROP TABLE t;
-- inner product
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_ip_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <#> '{1:3,2:3,3:3}/3';
val
-----------------
{1:1,2:2,3:4}/3
{1:1,2:2,3:3}/3
{1:1,2:1,3:1}/3
{}/3
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::sparsevec)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- cosine
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_cosine_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <=> '{1:3,2:3,3:3}/3';
val
-----------------
{1:1,2:1,3:1}/3
{1:1,2:2,3:3}/3
{1:1,2:2,3:4}/3
(3 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '{}/3') t2;
count
-------
3
(1 row)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::sparsevec)) t2;
count
-------
3
(1 row)
DROP TABLE t;
-- L1
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_l1_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <+> '{1:3,2:3,3:3}/3';
val
-----------------
{1:1,2:2,3:3}/3
{1:1,2:2,3:4}/3
{1:1,2:1,3:1}/3
{}/3
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::sparsevec)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- non-zero elements
CREATE TABLE t (val sparsevec(1001));
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
TRUNCATE t;
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
DROP TABLE t;

View File

@@ -1,13 +0,0 @@
SET enable_seqscan = off;
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
DROP TABLE t;

View File

@@ -0,0 +1,142 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;
-- inner product
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_ip_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
val
---------
[1,2,4]
[1,2,3]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- cosine
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_cosine_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
val
---------
[1,1,1]
[1,2,3]
[1,2,4]
(3 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
count
-------
3
(1 row)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
count
-------
3
(1 row)
DROP TABLE t;
-- L1
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l1_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <+> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
DROP TABLE t;
-- options
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 1);
ERROR: value 1 out of bounds for option "m"
DETAIL: Valid values are between "2" and "100".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
ERROR: value 101 out of bounds for option "m"
DETAIL: Valid values are between "2" and "100".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
ERROR: value 3 out of bounds for option "ef_construction"
DETAIL: Valid values are between "4" and "1000".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
ERROR: value 1001 out of bounds for option "ef_construction"
DETAIL: Valid values are between "4" and "1000".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
ERROR: ef_construction must be greater than or equal to 2 * m
SHOW hnsw.ef_search;
hnsw.ef_search
----------------
40
(1 row)
SET hnsw.ef_search = 0;
ERROR: 0 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
SET hnsw.ef_search = 1001;
ERROR: 1001 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
DROP TABLE t;

View File

@@ -1,129 +0,0 @@
SELECT '[1,2,3]'::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[-1,-2,-3]'::vector;
vector
------------
[-1,-2,-3]
(1 row)
SELECT '[1.,2.,3.]'::vector;
vector
---------
[1,2,3]
(1 row)
SELECT ' [ 1, 2 , 3 ] '::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[1.23456]'::vector;
vector
-----------
[1.23456]
(1 row)
SELECT '[hello,1]'::vector;
ERROR: invalid input syntax for type vector: "[hello,1]"
LINE 1: SELECT '[hello,1]'::vector;
^
SELECT '[NaN,1]'::vector;
ERROR: NaN not allowed in vector
LINE 1: SELECT '[NaN,1]'::vector;
^
SELECT '[Infinity,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[Infinity,1]'::vector;
^
SELECT '[-Infinity,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[-Infinity,1]'::vector;
^
SELECT '[1.5e38,-1.5e38]'::vector;
vector
--------------------
[1.5e+38,-1.5e+38]
(1 row)
SELECT '[1.5e+38,-1.5e+38]'::vector;
vector
--------------------
[1.5e+38,-1.5e+38]
(1 row)
SELECT '[1.5e-38,-1.5e-38]'::vector;
vector
--------------------
[1.5e-38,-1.5e-38]
(1 row)
SELECT '[4e38,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[4e38,1]'::vector;
^
SELECT '[1,2,3'::vector;
ERROR: malformed vector literal: "[1,2,3"
LINE 1: SELECT '[1,2,3'::vector;
^
DETAIL: Unexpected end of input.
SELECT '[1,2,3]9'::vector;
ERROR: malformed vector literal: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::vector;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::vector;
ERROR: malformed vector literal: "1,2,3"
LINE 1: SELECT '1,2,3'::vector;
^
DETAIL: Vector contents must start with "[".
SELECT ''::vector;
ERROR: malformed vector literal: ""
LINE 1: SELECT ''::vector;
^
DETAIL: Vector contents must start with "[".
SELECT '['::vector;
ERROR: malformed vector literal: "["
LINE 1: SELECT '['::vector;
^
DETAIL: Unexpected end of input.
SELECT '[,'::vector;
ERROR: malformed vector literal: "[,"
LINE 1: SELECT '[,'::vector;
^
DETAIL: Unexpected end of input.
SELECT '[]'::vector;
ERROR: vector must have at least 1 dimension
LINE 1: SELECT '[]'::vector;
^
SELECT '[1,]'::vector;
ERROR: invalid input syntax for type vector: "[1,]"
LINE 1: SELECT '[1,]'::vector;
^
SELECT '[1a]'::vector;
ERROR: invalid input syntax for type vector: "[1a]"
LINE 1: SELECT '[1a]'::vector;
^
SELECT '[1,,3]'::vector;
ERROR: malformed vector literal: "[1,,3]"
LINE 1: SELECT '[1,,3]'::vector;
^
SELECT '[1, ,3]'::vector;
ERROR: invalid input syntax for type vector: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::vector;
^
SELECT '[1,2,3]'::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
unnest
---------
[1,2,3]
[4,5,6]
(2 rows)
SELECT '{"[1,2,3]"}'::vector(2)[];
ERROR: expected 2 dimensions, not 3

View File

@@ -0,0 +1,37 @@
SET enable_seqscan = off;
-- hamming
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
val
-----
111
110
100
000
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- varbit
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops) WITH (lists = 1);
ERROR: type not supported for ivfflat index
CREATE INDEX ON t USING ivfflat ((val::bit(3)) bit_hamming_ops) WITH (lists = 1);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
CREATE INDEX ON t USING ivfflat ((val::bit(64001)) bit_hamming_ops) WITH (lists = 1);
ERROR: column cannot have more than 64000 dimensions for ivfflat index
CREATE INDEX ON t USING ivfflat ((val::bit(2)) bit_hamming_ops) WITH (lists = 5);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;

View File

@@ -1,26 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_cosine_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
val
---------
[1,1,1]
[1,2,3]
[1,2,4]
(3 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
count
-------
3
(1 row)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
count
-------
3
(1 row)
DROP TABLE t;

View File

@@ -0,0 +1,84 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;
-- inner product
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_ip_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
val
---------
[1,2,4]
[1,2,3]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::halfvec)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- cosine
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_cosine_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
val
---------
[1,1,1]
[1,2,3]
[1,2,4]
(3 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
count
-------
3
(1 row)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t2;
count
-------
3
(1 row)
DROP TABLE t;

View File

@@ -1,21 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_ip_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
val
---------
[1,2,4]
[1,2,3]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

@@ -1,39 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;

View File

@@ -1,14 +0,0 @@
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 0);
ERROR: value 0 out of bounds for option "lists"
DETAIL: Valid values are between "1" and "32768".
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
ERROR: value 32769 out of bounds for option "lists"
DETAIL: Valid values are between "1" and "32768".
SHOW ivfflat.probes;
ivfflat.probes
----------------
1
(1 row)
DROP TABLE t;

View File

@@ -1,13 +0,0 @@
SET enable_seqscan = off;
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
DROP TABLE t;

View File

@@ -0,0 +1,112 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;
-- inner product
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_ip_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
val
---------
[1,2,4]
[1,2,3]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- cosine
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_cosine_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
val
---------
[1,1,1]
[1,2,3]
[1,2,4]
(3 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
count
-------
3
(1 row)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
count
-------
3
(1 row)
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
DROP TABLE t;
-- options
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 0);
ERROR: value 0 out of bounds for option "lists"
DETAIL: Valid values are between "1" and "32768".
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
ERROR: value 32769 out of bounds for option "lists"
DETAIL: Valid values are between "1" and "32768".
SHOW ivfflat.probes;
ivfflat.probes
----------------
1
(1 row)
DROP TABLE t;

653
test/expected/sparsevec.out Normal file
View File

@@ -0,0 +1,653 @@
SELECT '{1:1.5,3:3.5}/5'::sparsevec;
sparsevec
-----------------
{1:1.5,3:3.5}/5
(1 row)
SELECT '{1:-2,3:-4}/5'::sparsevec;
sparsevec
---------------
{1:-2,3:-4}/5
(1 row)
SELECT '{1:2.,3:4.}/5'::sparsevec;
sparsevec
-------------
{1:2,3:4}/5
(1 row)
SELECT ' { 1 : 1.5 , 3 : 3.5 } / 5 '::sparsevec;
sparsevec
-----------------
{1:1.5,3:3.5}/5
(1 row)
SELECT '{1:1.23456}/1'::sparsevec;
sparsevec
---------------
{1:1.23456}/1
(1 row)
SELECT '{1:hello,2:1}/2'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:hello,2:1}/2"
LINE 1: SELECT '{1:hello,2:1}/2'::sparsevec;
^
SELECT '{1:NaN,2:1}/2'::sparsevec;
ERROR: NaN not allowed in sparsevec
LINE 1: SELECT '{1:NaN,2:1}/2'::sparsevec;
^
SELECT '{1:Infinity,2:1}/2'::sparsevec;
ERROR: infinite value not allowed in sparsevec
LINE 1: SELECT '{1:Infinity,2:1}/2'::sparsevec;
^
SELECT '{1:-Infinity,2:1}/2'::sparsevec;
ERROR: infinite value not allowed in sparsevec
LINE 1: SELECT '{1:-Infinity,2:1}/2'::sparsevec;
^
SELECT '{1:1.5e38,2:-1.5e38}/2'::sparsevec;
sparsevec
--------------------------
{1:1.5e+38,2:-1.5e+38}/2
(1 row)
SELECT '{1:1.5e+38,2:-1.5e+38}/2'::sparsevec;
sparsevec
--------------------------
{1:1.5e+38,2:-1.5e+38}/2
(1 row)
SELECT '{1:1.5e-38,2:-1.5e-38}/2'::sparsevec;
sparsevec
--------------------------
{1:1.5e-38,2:-1.5e-38}/2
(1 row)
SELECT '{1:4e38,2:1}/2'::sparsevec;
ERROR: "4e38" is out of range for type sparsevec
LINE 1: SELECT '{1:4e38,2:1}/2'::sparsevec;
^
SELECT '{1:-4e38,2:1}/2'::sparsevec;
ERROR: "-4e38" is out of range for type sparsevec
LINE 1: SELECT '{1:-4e38,2:1}/2'::sparsevec;
^
SELECT '{1:1e-46,2:1}/2'::sparsevec;
ERROR: "1e-46" is out of range for type sparsevec
LINE 1: SELECT '{1:1e-46,2:1}/2'::sparsevec;
^
SELECT '{1:-1e-46,2:1}/2'::sparsevec;
ERROR: "-1e-46" is out of range for type sparsevec
LINE 1: SELECT '{1:-1e-46,2:1}/2'::sparsevec;
^
SELECT ''::sparsevec;
ERROR: invalid input syntax for type sparsevec: ""
LINE 1: SELECT ''::sparsevec;
^
DETAIL: Vector contents must start with "{".
SELECT '{'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{"
LINE 1: SELECT '{'::sparsevec;
^
SELECT '{ '::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{ "
LINE 1: SELECT '{ '::sparsevec;
^
SELECT '{:'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{:"
LINE 1: SELECT '{:'::sparsevec;
^
SELECT '{,'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{,"
LINE 1: SELECT '{,'::sparsevec;
^
SELECT '{}'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{}"
LINE 1: SELECT '{}'::sparsevec;
^
DETAIL: Unexpected end of input.
SELECT '{}/'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{}/"
LINE 1: SELECT '{}/'::sparsevec;
^
SELECT '{}/1'::sparsevec;
sparsevec
-----------
{}/1
(1 row)
SELECT '{}/1a'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{}/1a"
LINE 1: SELECT '{}/1a'::sparsevec;
^
DETAIL: Junk after closing.
SELECT '{ }/1'::sparsevec;
sparsevec
-----------
{}/1
(1 row)
SELECT '{:}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{:}/1"
LINE 1: SELECT '{:}/1'::sparsevec;
^
SELECT '{,}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{,}/1"
LINE 1: SELECT '{,}/1'::sparsevec;
^
SELECT '{1,}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1,}/1"
LINE 1: SELECT '{1,}/1'::sparsevec;
^
SELECT '{:1}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{:1}/1"
LINE 1: SELECT '{:1}/1'::sparsevec;
^
SELECT '{1:}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:}/1"
LINE 1: SELECT '{1:}/1'::sparsevec;
^
SELECT '{1a:1}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1a:1}/1"
LINE 1: SELECT '{1a:1}/1'::sparsevec;
^
SELECT '{1:1a}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:1a}/1"
LINE 1: SELECT '{1:1a}/1'::sparsevec;
^
SELECT '{1:1,}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:1,}/1"
LINE 1: SELECT '{1:1,}/1'::sparsevec;
^
SELECT '{1:0,2:1,3:0}/3'::sparsevec;
sparsevec
-----------
{2:1}/3
(1 row)
SELECT '{2:1,1:1}/2'::sparsevec;
sparsevec
-------------
{1:1,2:1}/2
(1 row)
SELECT '{1:1,1:1}/2'::sparsevec;
ERROR: sparsevec indices must not contain duplicates
LINE 1: SELECT '{1:1,1:1}/2'::sparsevec;
^
SELECT '{1:1,2:1,1:1}/2'::sparsevec;
ERROR: sparsevec indices must not contain duplicates
LINE 1: SELECT '{1:1,2:1,1:1}/2'::sparsevec;
^
SELECT '{}/5'::sparsevec;
sparsevec
-----------
{}/5
(1 row)
SELECT '{}/-1'::sparsevec;
ERROR: sparsevec must have at least 1 dimension
LINE 1: SELECT '{}/-1'::sparsevec;
^
SELECT '{}/1000000001'::sparsevec;
ERROR: sparsevec cannot have more than 1000000000 dimensions
LINE 1: SELECT '{}/1000000001'::sparsevec;
^
SELECT '{}/2147483648'::sparsevec;
ERROR: sparsevec cannot have more than 1000000000 dimensions
LINE 1: SELECT '{}/2147483648'::sparsevec;
^
SELECT '{}/-2147483649'::sparsevec;
ERROR: sparsevec must have at least 1 dimension
LINE 1: SELECT '{}/-2147483649'::sparsevec;
^
SELECT '{}/9223372036854775808'::sparsevec;
ERROR: sparsevec cannot have more than 1000000000 dimensions
LINE 1: SELECT '{}/9223372036854775808'::sparsevec;
^
SELECT '{}/-9223372036854775809'::sparsevec;
ERROR: sparsevec must have at least 1 dimension
LINE 1: SELECT '{}/-9223372036854775809'::sparsevec;
^
SELECT '{2147483647:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{2147483647:1}/1'::sparsevec;
^
SELECT '{2147483648:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{2147483648:1}/1'::sparsevec;
^
SELECT '{-2147483648:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{-2147483648:1}/1'::sparsevec;
^
SELECT '{-2147483649:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{-2147483649:1}/1'::sparsevec;
^
SELECT '{0:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{0:1}/1'::sparsevec;
^
SELECT '{2:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{2:1}/1'::sparsevec;
^
SELECT '{}/3'::sparsevec(3);
sparsevec
-----------
{}/3
(1 row)
SELECT '{}/3'::sparsevec(2);
ERROR: expected 2 dimensions, not 3
SELECT '{}/3'::sparsevec(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '{}/3'::sparsevec(3, 2);
^
SELECT '{}/3'::sparsevec('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '{}/3'::sparsevec('a');
^
SELECT '{}/3'::sparsevec(0);
ERROR: dimensions for type sparsevec must be at least 1
LINE 1: SELECT '{}/3'::sparsevec(0);
^
SELECT '{}/3'::sparsevec(1000000001);
ERROR: dimensions for type sparsevec cannot exceed 1000000000
LINE 1: SELECT '{}/3'::sparsevec(1000000001);
^
SELECT '{1:1,2:2,3:3}/3'::sparsevec < '{1:1,2:2,3:3}/3';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec < '{1:1,2:2}/2';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec <= '{1:1,2:2,3:3}/3';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec <= '{1:1,2:2}/2';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec = '{1:1,2:2,3:3}/3';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec = '{1:1,2:2}/2';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec != '{1:1,2:2,3:3}/3';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec != '{1:1,2:2}/2';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec >= '{1:1,2:2,3:3}/3';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec >= '{1:1,2:2}/2';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec > '{1:1,2:2,3:3}/3';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec > '{1:1,2:2}/2';
?column?
----------
t
(1 row)
SELECT sparsevec_cmp('{1:1,2:2,3:3}/3', '{1:1,2:2,3:3}/3');
sparsevec_cmp
---------------
0
(1 row)
SELECT sparsevec_cmp('{1:1,2:2,3:3}/3', '{}/3');
sparsevec_cmp
---------------
1
(1 row)
SELECT sparsevec_cmp('{}/3', '{1:1,2:2,3:3}/3');
sparsevec_cmp
---------------
-1
(1 row)
SELECT sparsevec_cmp('{1:1,2:2}/2', '{1:1,2:2,3:3}/3');
sparsevec_cmp
---------------
-1
(1 row)
SELECT sparsevec_cmp('{1:1,2:2,3:3}/3', '{1:1,2:2}/2');
sparsevec_cmp
---------------
1
(1 row)
SELECT sparsevec_cmp('{1:1,2:2}/2', '{1:2,2:3,3:4}/3');
sparsevec_cmp
---------------
-1
(1 row)
SELECT sparsevec_cmp('{1:2,2:3}/2', '{1:1,2:2,3:3}/3');
sparsevec_cmp
---------------
1
(1 row)
SELECT round(l2_norm('{1:1,2:1}/2'::sparsevec)::numeric, 5);
round
---------
1.41421
(1 row)
SELECT l2_norm('{1:3,2:4}/2'::sparsevec);
l2_norm
---------
5
(1 row)
SELECT l2_norm('{2:1}/2'::sparsevec);
l2_norm
---------
1
(1 row)
SELECT l2_norm('{1:3e37,2:4e37}/2'::sparsevec)::real;
l2_norm
---------
5e+37
(1 row)
SELECT l2_norm('{}/2'::sparsevec);
l2_norm
---------
0
(1 row)
SELECT l2_norm('{1:2}/1'::sparsevec);
l2_norm
---------
2
(1 row)
SELECT l2_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{1:3}/2'::sparsevec, '{2:4}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{2:4}/2'::sparsevec, '{1:3}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{1:3,2:4}/2'::sparsevec, '{}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{}/2'::sparsevec, '{2:1}/2');
l2_distance
-------------
1
(1 row)
SELECT '{}/2'::sparsevec <-> '{1:3,2:4}/2';
?column?
----------
5
(1 row)
SELECT inner_product('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
inner_product
---------------
10
(1 row)
SELECT inner_product('{1:1,2:2}/2'::sparsevec, '{1:3}/1');
ERROR: different sparsevec dimensions 2 and 1
SELECT inner_product('{1:1,3:3}/4'::sparsevec, '{2:2,4:4}/4');
inner_product
---------------
0
(1 row)
SELECT inner_product('{2:2,4:4}/4'::sparsevec, '{1:1,3:3}/4');
inner_product
---------------
0
(1 row)
SELECT inner_product('{1:1,3:3,5:5}/5'::sparsevec, '{2:4,3:6,4:8}/5');
inner_product
---------------
18
(1 row)
SELECT inner_product('{1:1}/2'::sparsevec, '{}/2');
inner_product
---------------
0
(1 row)
SELECT inner_product('{}/2'::sparsevec, '{1:1}/2');
inner_product
---------------
0
(1 row)
SELECT inner_product('{1:3e38}/1'::sparsevec, '{1:3e38}/1');
inner_product
---------------
Infinity
(1 row)
SELECT inner_product('{1:1,3:3,5:5}/5'::sparsevec, '{2:4,3:6,4:8}/5');
inner_product
---------------
18
(1 row)
SELECT '{1:1,2:2}/2'::sparsevec <#> '{1:3,2:4}/2';
?column?
----------
-11
(1 row)
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{}/2');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:1,2:1}/2');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{1:1}/2'::sparsevec, '{2:2}/2');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:-1,2:-1}/2');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('{1:2}/2'::sparsevec, '{2:2}/2');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('{2:2}/2'::sparsevec, '{1:2}/2');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{1:3}/1');
ERROR: different sparsevec dimensions 2 and 1
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:1.1,2:1.1}/2');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:-1.1,2:-1.1}/2');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('{1:3e38}/1'::sparsevec, '{1:3e38}/1');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
cosine_distance
-----------------
NaN
(1 row)
SELECT '{1:1,2:2}/2'::sparsevec <=> '{1:2,2:4}/2';
?column?
----------
0
(1 row)
SELECT l1_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('{}/2'::sparsevec, '{2:1}/2');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('{1:1,2:2}/2'::sparsevec, '{1:3}/1');
ERROR: different sparsevec dimensions 2 and 1
SELECT l1_distance('{1:3e38}/1'::sparsevec, '{1:-3e38}/1');
l1_distance
-------------
Infinity
(1 row)
SELECT l1_distance('{1:1,3:3,5:5,7:7}/8'::sparsevec, '{2:2,4:4,6:6,8:8}/8');
l1_distance
-------------
36
(1 row)
SELECT l1_distance('{1:1,3:3,5:5,7:7,9:9}/9'::sparsevec, '{2:2,4:4,6:6,8:8}/9');
l1_distance
-------------
45
(1 row)
SELECT '{}/2'::sparsevec <+> '{1:3,2:4}/2';
?column?
----------
7
(1 row)
SELECT l2_normalize('{1:3,2:4}/2'::sparsevec);
l2_normalize
-----------------
{1:0.6,2:0.8}/2
(1 row)
SELECT l2_normalize('{1:3}/2'::sparsevec);
l2_normalize
--------------
{1:1}/2
(1 row)
SELECT l2_normalize('{2:0.1}/2'::sparsevec);
l2_normalize
--------------
{2:1}/2
(1 row)
SELECT l2_normalize('{}/2'::sparsevec);
l2_normalize
--------------
{}/2
(1 row)
SELECT l2_normalize('{1:3e38}/1'::sparsevec);
l2_normalize
--------------
{1:1}/1
(1 row)
SELECT l2_normalize('{1:3e38,2:1e-37}/2'::sparsevec);
l2_normalize
--------------
{1:1}/2
(1 row)
SELECT l2_normalize('{2:3e37,4:3e-37,6:4e37,8:4e-37}/9'::sparsevec);
l2_normalize
-----------------
{2:0.6,6:0.8}/9
(1 row)

View File

@@ -0,0 +1,672 @@
SELECT '[1,2,3]'::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[-1,-2,-3]'::vector;
vector
------------
[-1,-2,-3]
(1 row)
SELECT '[1.,2.,3.]'::vector;
vector
---------
[1,2,3]
(1 row)
SELECT ' [ 1, 2 , 3 ] '::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[1.23456]'::vector;
vector
-----------
[1.23456]
(1 row)
SELECT '[hello,1]'::vector;
ERROR: invalid input syntax for type vector: "[hello,1]"
LINE 1: SELECT '[hello,1]'::vector;
^
SELECT '[NaN,1]'::vector;
ERROR: NaN not allowed in vector
LINE 1: SELECT '[NaN,1]'::vector;
^
SELECT '[Infinity,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[Infinity,1]'::vector;
^
SELECT '[-Infinity,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[-Infinity,1]'::vector;
^
SELECT '[1.5e38,-1.5e38]'::vector;
vector
--------------------
[1.5e+38,-1.5e+38]
(1 row)
SELECT '[1.5e+38,-1.5e+38]'::vector;
vector
--------------------
[1.5e+38,-1.5e+38]
(1 row)
SELECT '[1.5e-38,-1.5e-38]'::vector;
vector
--------------------
[1.5e-38,-1.5e-38]
(1 row)
SELECT '[4e38,1]'::vector;
ERROR: "4e38" is out of range for type vector
LINE 1: SELECT '[4e38,1]'::vector;
^
SELECT '[-4e38,1]'::vector;
ERROR: "-4e38" is out of range for type vector
LINE 1: SELECT '[-4e38,1]'::vector;
^
SELECT '[1e-46,1]'::vector;
vector
--------
[0,1]
(1 row)
SELECT '[-1e-46,1]'::vector;
vector
--------
[-0,1]
(1 row)
SELECT '[1,2,3'::vector;
ERROR: invalid input syntax for type vector: "[1,2,3"
LINE 1: SELECT '[1,2,3'::vector;
^
SELECT '[1,2,3]9'::vector;
ERROR: invalid input syntax for type vector: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::vector;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::vector;
ERROR: invalid input syntax for type vector: "1,2,3"
LINE 1: SELECT '1,2,3'::vector;
^
DETAIL: Vector contents must start with "[".
SELECT ''::vector;
ERROR: invalid input syntax for type vector: ""
LINE 1: SELECT ''::vector;
^
DETAIL: Vector contents must start with "[".
SELECT '['::vector;
ERROR: invalid input syntax for type vector: "["
LINE 1: SELECT '['::vector;
^
SELECT '[ '::vector;
ERROR: invalid input syntax for type vector: "[ "
LINE 1: SELECT '[ '::vector;
^
SELECT '[,'::vector;
ERROR: invalid input syntax for type vector: "[,"
LINE 1: SELECT '[,'::vector;
^
SELECT '[]'::vector;
ERROR: vector must have at least 1 dimension
LINE 1: SELECT '[]'::vector;
^
SELECT '[ ]'::vector;
ERROR: vector must have at least 1 dimension
LINE 1: SELECT '[ ]'::vector;
^
SELECT '[,]'::vector;
ERROR: invalid input syntax for type vector: "[,]"
LINE 1: SELECT '[,]'::vector;
^
SELECT '[1,]'::vector;
ERROR: invalid input syntax for type vector: "[1,]"
LINE 1: SELECT '[1,]'::vector;
^
SELECT '[1a]'::vector;
ERROR: invalid input syntax for type vector: "[1a]"
LINE 1: SELECT '[1a]'::vector;
^
SELECT '[1,,3]'::vector;
ERROR: invalid input syntax for type vector: "[1,,3]"
LINE 1: SELECT '[1,,3]'::vector;
^
SELECT '[1, ,3]'::vector;
ERROR: invalid input syntax for type vector: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::vector;
^
SELECT '[1,2,3]'::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::vector(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::vector(3, 2);
^
SELECT '[1,2,3]'::vector('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::vector('a');
^
SELECT '[1,2,3]'::vector(0);
ERROR: dimensions for type vector must be at least 1
LINE 1: SELECT '[1,2,3]'::vector(0);
^
SELECT '[1,2,3]'::vector(16001);
ERROR: dimensions for type vector cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::vector(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
unnest
---------
[1,2,3]
[4,5,6]
(2 rows)
SELECT '{"[1,2,3]"}'::vector(2)[];
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::vector + '[4,5,6]';
?column?
----------
[5,7,9]
(1 row)
SELECT '[3e38]'::vector + '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2]'::vector + '[3]';
ERROR: different vector dimensions 2 and 1
SELECT '[1,2,3]'::vector - '[4,5,6]';
?column?
------------
[-3,-3,-3]
(1 row)
SELECT '[-3e38]'::vector - '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2]'::vector - '[3]';
ERROR: different vector dimensions 2 and 1
SELECT '[1,2,3]'::vector * '[4,5,6]';
?column?
-----------
[4,10,18]
(1 row)
SELECT '[1e37]'::vector * '[1e37]';
ERROR: value out of range: overflow
SELECT '[1e-37]'::vector * '[1e-37]';
ERROR: value out of range: underflow
SELECT '[1,2]'::vector * '[3]';
ERROR: different vector dimensions 2 and 1
SELECT '[1,2,3]'::vector || '[4,5]';
?column?
-------------
[1,2,3,4,5]
(1 row)
SELECT array_fill(0, ARRAY[16000])::vector || '[1]';
ERROR: vector cannot have more than 16000 dimensions
SELECT '[1,2,3]'::vector < '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector < '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector <= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector <= '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector = '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector = '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector != '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector != '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector >= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector >= '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector > '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector > '[1,2]';
?column?
----------
t
(1 row)
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
vector_cmp
------------
0
(1 row)
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
vector_cmp
------------
1
(1 row)
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[1,2]', '[1,2,3]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[1,2,3]', '[1,2]');
vector_cmp
------------
1
(1 row)
SELECT vector_cmp('[1,2]', '[2,3,4]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[2,3]', '[1,2,3]');
vector_cmp
------------
1
(1 row)
SELECT vector_dims('[1,2,3]'::vector);
vector_dims
-------------
3
(1 row)
SELECT round(vector_norm('[1,1]')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT vector_norm('[3,4]');
vector_norm
-------------
5
(1 row)
SELECT vector_norm('[0,1]');
vector_norm
-------------
1
(1 row)
SELECT vector_norm('[3e37,4e37]')::real;
vector_norm
-------------
5e+37
(1 row)
SELECT vector_norm('[0,0]');
vector_norm
-------------
0
(1 row)
SELECT vector_norm('[2]');
vector_norm
-------------
2
(1 row)
SELECT l2_distance('[0,0]'::vector, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]'::vector, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
l2_distance
-------------
Infinity
(1 row)
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::vector, '[1,1,1,1,1,1,1,4,5]');
l2_distance
-------------
5
(1 row)
SELECT '[0,0]'::vector <-> '[3,4]';
?column?
----------
5
(1 row)
SELECT inner_product('[1,2]'::vector, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT inner_product('[3e38]'::vector, '[3e38]');
inner_product
---------------
Infinity
(1 row)
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::vector, '[1,2,3,4,5,6,7,8,9]');
inner_product
---------------
45
(1 row)
SELECT '[1,2]'::vector <#> '[3,4]';
?column?
----------
-11
(1 row)
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[1,2,3,4,5,6,7,8,9]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[-1,-2,-3,-4,-5,-6,-7,-8,-9]');
cosine_distance
-----------------
2
(1 row)
SELECT '[1,2]'::vector <=> '[2,4]';
?column?
----------
0
(1 row)
SELECT l1_distance('[0,0]'::vector, '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]'::vector, '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
l1_distance
-------------
Infinity
(1 row)
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[1,2,3,4,5,6,7,8,9]');
l1_distance
-------------
0
(1 row)
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[0,3,2,5,4,7,6,9,8]');
l1_distance
-------------
9
(1 row)
SELECT '[0,0]'::vector <+> '[3,4]';
?column?
----------
7
(1 row)
SELECT l2_normalize('[3,4]'::vector);
l2_normalize
--------------
[0.6,0.8]
(1 row)
SELECT l2_normalize('[3,0]'::vector);
l2_normalize
--------------
[1,0]
(1 row)
SELECT l2_normalize('[0,0.1]'::vector);
l2_normalize
--------------
[0,1]
(1 row)
SELECT l2_normalize('[0,0]'::vector);
l2_normalize
--------------
[0,0]
(1 row)
SELECT l2_normalize('[3e38]'::vector);
l2_normalize
--------------
[1]
(1 row)
SELECT binary_quantize('[1,0,-1]'::vector);
binary_quantize
-----------------
100
(1 row)
SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
binary_quantize
-----------------
01001110101
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
subvector
-----------
[1,2,3]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);
subvector
-----------
[3,4]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, -1, 3);
subvector
-----------
[1]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 3, 9);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 1, 0);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, 3, -1);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, -1, 2);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, 2147483647, 10);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2147483647);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, -2147483644, 2147483647);
subvector
-----------
[1,2]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
avg
-----
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: expected 2 dimensions, not 1
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
avg
---------
[3e+38]
(1 row)
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
ERROR: vector cannot have more than 16000 dimensions
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
sum
-----
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: different vector dimensions 2 and 1
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
ERROR: value out of range: overflow

27
test/sql/bit.sql Normal file
View File

@@ -0,0 +1,27 @@
SELECT hamming_distance('111', '111');
SELECT hamming_distance('111', '110');
SELECT hamming_distance('111', '100');
SELECT hamming_distance('111', '000');
SELECT hamming_distance('10101010101010101010', '01010101010101010101');
SELECT hamming_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101');
SELECT hamming_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010');
SELECT hamming_distance('110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011', '100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001');
SELECT hamming_distance('', '');
SELECT hamming_distance('111', '00');
SELECT hamming_distance('111', '000'::varbit(4));
SELECT hamming_distance('111', '0000'::varbit(4));
SELECT jaccard_distance('1111', '1111');
SELECT jaccard_distance('1111', '1110');
SELECT jaccard_distance('1111', '1100');
SELECT jaccard_distance('1111', '1000');
SELECT jaccard_distance('1111', '0000');
SELECT jaccard_distance('1100', '1000');
SELECT jaccard_distance('10101010101010101010', '01010101010101010101');
SELECT jaccard_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101');
SELECT jaccard_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010');
SELECT jaccard_distance('110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011', '100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001');
SELECT jaccard_distance('', '');
SELECT jaccard_distance('1111', '000');
SELECT jaccard_distance('1111', '0000'::varbit(5));
SELECT jaccard_distance('1111', '00000'::varbit(5));

View File

@@ -1,10 +1,34 @@
SET enable_seqscan = off;
-- vector
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t (val);
SELECT * FROM t WHERE val = '[1,2,3]';
SELECT * FROM t ORDER BY val LIMIT 1;
SELECT * FROM t ORDER BY val;
DROP TABLE t;
-- halfvec
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t (val);
SELECT * FROM t WHERE val = '[1,2,3]';
SELECT * FROM t ORDER BY val;
DROP TABLE t;
-- sparsevec
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t (val);
SELECT * FROM t WHERE val = '{1:1,2:2,3:3}/3';
SELECT * FROM t ORDER BY val;
DROP TABLE t;

View File

@@ -3,13 +3,61 @@ SELECT ARRAY[1.0,2.0,3.0]::vector;
SELECT ARRAY[1,2,3]::float4[]::vector;
SELECT ARRAY[1,2,3]::float8[]::vector;
SELECT ARRAY[1,2,3]::numeric[]::vector;
SELECT '[1,2,3]'::vector::real[];
SELECT '{1,2,3}'::real[]::vector;
SELECT '{1,2,3}'::real[]::vector(3);
SELECT '{1,2,3}'::real[]::vector(2);
SELECT '{NULL}'::real[]::vector;
SELECT '{NaN}'::real[]::vector;
SELECT '{Infinity}'::real[]::vector;
SELECT '{-Infinity}'::real[]::vector;
SELECT '{}'::real[]::vector;
SELECT '{{1}}'::real[]::vector;
SELECT '[1,2,3]'::vector::real[];
SELECT '{1,2,3}'::double precision[]::vector;
SELECT '{1,2,3}'::double precision[]::vector(3);
SELECT '{1,2,3}'::double precision[]::vector(2);
SELECT '{4e38,-4e38}'::double precision[]::vector;
SELECT '{1e-46,-1e-46}'::double precision[]::vector;
SELECT '[1,2,3]'::vector::halfvec;
SELECT '[1,2,3]'::vector::halfvec(3);
SELECT '[1,2,3]'::vector::halfvec(2);
SELECT '[65520]'::vector::halfvec;
SELECT '[1e-8]'::vector::halfvec;
SELECT '[1,2,3]'::halfvec::vector;
SELECT '[1,2,3]'::halfvec::vector(3);
SELECT '[1,2,3]'::halfvec::vector(2);
SELECT '{1,2,3}'::real[]::halfvec;
SELECT '{1,2,3}'::real[]::halfvec(3);
SELECT '{1,2,3}'::real[]::halfvec(2);
SELECT '{65520,-65520}'::real[]::halfvec;
SELECT '{1e-8,-1e-8}'::real[]::halfvec;
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(5);
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(4);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector;
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(5);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(4);
SELECT '{}/16001'::sparsevec::vector;
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec;
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec(5);
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec(4);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec;
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec(5);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec(4);
SELECT '{}/16001'::sparsevec::halfvec;
SELECT '{1:65520}/1'::sparsevec::halfvec;
SELECT '{1:1e-8}/1'::sparsevec::halfvec;
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;

View File

@@ -1,10 +1,42 @@
-- vector
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val vector(3));
\copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/data.bin' WITH (FORMAT binary)
\copy t TO 'results/vector.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/vector.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
DROP TABLE t;
DROP TABLE t2;
-- halfvec
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val halfvec(3));
\copy t TO 'results/halfvec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/halfvec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
DROP TABLE t;
DROP TABLE t2;
-- sparsevec
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE TABLE t2 (val sparsevec(3));
\copy t TO 'results/sparsevec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/sparsevec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;

View File

@@ -1,51 +0,0 @@
SELECT '[1,2,3]'::vector + '[4,5,6]';
SELECT '[3e38]'::vector + '[3e38]';
SELECT '[1,2,3]'::vector - '[4,5,6]';
SELECT '[-3e38]'::vector - '[3e38]';
SELECT '[1,2,3]'::vector * '[4,5,6]';
SELECT '[1e37]'::vector * '[1e37]';
SELECT '[1e-37]'::vector * '[1e-37]';
SELECT vector_dims('[1,2,3]');
SELECT round(vector_norm('[1,1]')::numeric, 5);
SELECT vector_norm('[3,4]');
SELECT vector_norm('[0,1]');
SELECT vector_norm('[3e37,4e37]')::real;
SELECT l2_distance('[0,0]', '[3,4]');
SELECT l2_distance('[0,0]', '[0,1]');
SELECT l2_distance('[1,2]', '[3]');
SELECT l2_distance('[3e38]', '[-3e38]');
SELECT inner_product('[1,2]', '[3,4]');
SELECT inner_product('[1,2]', '[3]');
SELECT inner_product('[3e38]', '[3e38]');
SELECT cosine_distance('[1,2]', '[2,4]');
SELECT cosine_distance('[1,2]', '[0,0]');
SELECT cosine_distance('[1,1]', '[1,1]');
SELECT cosine_distance('[1,0]', '[0,2]');
SELECT cosine_distance('[1,1]', '[-1,-1]');
SELECT cosine_distance('[1,2]', '[3]');
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
SELECT cosine_distance('[3e38]', '[3e38]');
SELECT l1_distance('[0,0]', '[3,4]');
SELECT l1_distance('[0,0]', '[0,1]');
SELECT l1_distance('[1,2]', '[3]');
SELECT l1_distance('[3e38]', '[-3e38]');
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;

147
test/sql/halfvec.sql Normal file
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@@ -0,0 +1,147 @@
SELECT '[1,2,3]'::halfvec;
SELECT '[-1,-2,-3]'::halfvec;
SELECT '[1.,2.,3.]'::halfvec;
SELECT ' [ 1, 2 , 3 ] '::halfvec;
SELECT '[1.23456]'::halfvec;
SELECT '[hello,1]'::halfvec;
SELECT '[NaN,1]'::halfvec;
SELECT '[Infinity,1]'::halfvec;
SELECT '[-Infinity,1]'::halfvec;
SELECT '[65519,-65519]'::halfvec;
SELECT '[65520,-65520]'::halfvec;
SELECT '[1e-8,-1e-8]'::halfvec;
SELECT '[4e38,1]'::halfvec;
SELECT '[1e-46,1]'::halfvec;
SELECT '[1,2,3'::halfvec;
SELECT '[1,2,3]9'::halfvec;
SELECT '1,2,3'::halfvec;
SELECT ''::halfvec;
SELECT '['::halfvec;
SELECT '[ '::halfvec;
SELECT '[,'::halfvec;
SELECT '[]'::halfvec;
SELECT '[ ]'::halfvec;
SELECT '[,]'::halfvec;
SELECT '[1,]'::halfvec;
SELECT '[1a]'::halfvec;
SELECT '[1,,3]'::halfvec;
SELECT '[1, ,3]'::halfvec;
SELECT '[1,2,3]'::halfvec(3);
SELECT '[1,2,3]'::halfvec(2);
SELECT '[1,2,3]'::halfvec(3, 2);
SELECT '[1,2,3]'::halfvec('a');
SELECT '[1,2,3]'::halfvec(0);
SELECT '[1,2,3]'::halfvec(16001);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::halfvec[]);
SELECT '{"[1,2,3]"}'::halfvec(2)[];
SELECT '[1,2,3]'::halfvec + '[4,5,6]';
SELECT '[65519]'::halfvec + '[65519]';
SELECT '[1,2]'::halfvec + '[3]';
SELECT '[1,2,3]'::halfvec - '[4,5,6]';
SELECT '[-65519]'::halfvec - '[65519]';
SELECT '[1,2]'::halfvec - '[3]';
SELECT '[1,2,3]'::halfvec * '[4,5,6]';
SELECT '[65519]'::halfvec * '[65519]';
SELECT '[1e-7]'::halfvec * '[1e-7]';
SELECT '[1,2]'::halfvec * '[3]';
SELECT '[1,2,3]'::halfvec || '[4,5]';
SELECT array_fill(0, ARRAY[16000])::halfvec || '[1]';
SELECT '[1,2,3]'::halfvec < '[1,2,3]';
SELECT '[1,2,3]'::halfvec < '[1,2]';
SELECT '[1,2,3]'::halfvec <= '[1,2,3]';
SELECT '[1,2,3]'::halfvec <= '[1,2]';
SELECT '[1,2,3]'::halfvec = '[1,2,3]';
SELECT '[1,2,3]'::halfvec = '[1,2]';
SELECT '[1,2,3]'::halfvec != '[1,2,3]';
SELECT '[1,2,3]'::halfvec != '[1,2]';
SELECT '[1,2,3]'::halfvec >= '[1,2,3]';
SELECT '[1,2,3]'::halfvec >= '[1,2]';
SELECT '[1,2,3]'::halfvec > '[1,2,3]';
SELECT '[1,2,3]'::halfvec > '[1,2]';
SELECT halfvec_cmp('[1,2,3]', '[1,2,3]');
SELECT halfvec_cmp('[1,2,3]', '[0,0,0]');
SELECT halfvec_cmp('[0,0,0]', '[1,2,3]');
SELECT halfvec_cmp('[1,2]', '[1,2,3]');
SELECT halfvec_cmp('[1,2,3]', '[1,2]');
SELECT halfvec_cmp('[1,2]', '[2,3,4]');
SELECT halfvec_cmp('[2,3]', '[1,2,3]');
SELECT vector_dims('[1,2,3]'::halfvec);
SELECT round(l2_norm('[1,1]'::halfvec)::numeric, 5);
SELECT l2_norm('[3,4]'::halfvec);
SELECT l2_norm('[0,1]'::halfvec);
SELECT l2_norm('[0,0]'::halfvec);
SELECT l2_norm('[2]'::halfvec);
SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
SELECT l2_distance('[1,2]'::halfvec, '[3]');
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,1,1,1,1,1,1,4,5]');
SELECT '[0,0]'::halfvec <-> '[3,4]';
SELECT inner_product('[1,2]'::halfvec, '[3,4]');
SELECT inner_product('[1,2]'::halfvec, '[3]');
SELECT inner_product('[65504]'::halfvec, '[65504]');
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
SELECT '[1,2]'::halfvec <#> '[3,4]';
SELECT cosine_distance('[1,2]'::halfvec, '[2,4]');
SELECT cosine_distance('[1,2]'::halfvec, '[0,0]');
SELECT cosine_distance('[1,1]'::halfvec, '[1,1]');
SELECT cosine_distance('[1,0]'::halfvec, '[0,2]');
SELECT cosine_distance('[1,1]'::halfvec, '[-1,-1]');
SELECT cosine_distance('[1,2]'::halfvec, '[3]');
SELECT cosine_distance('[1,1]'::halfvec, '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::halfvec, '[-1.1,-1.1]');
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[-1,-2,-3,-4,-5,-6,-7,-8,-9]');
SELECT '[1,2]'::halfvec <=> '[2,4]';
SELECT l1_distance('[0,0]'::halfvec, '[3,4]');
SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
SELECT l1_distance('[1,2]'::halfvec, '[3]');
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[0,3,2,5,4,7,6,9,8]');
SELECT '[0,0]'::halfvec <+> '[3,4]';
SELECT l2_normalize('[3,4]'::halfvec);
SELECT l2_normalize('[3,0]'::halfvec);
SELECT l2_normalize('[0,0.1]'::halfvec);
SELECT l2_normalize('[0,0]'::halfvec);
SELECT l2_normalize('[65504]'::halfvec);
SELECT binary_quantize('[1,0,-1]'::halfvec);
SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2);
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 3);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 9);
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 0);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, -1);
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 2);
SELECT subvector('[1,2,3,4,5]'::halfvec, 2147483647, 10);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2147483647);
SELECT subvector('[1,2,3,4,5]'::halfvec, -2147483644, 2147483647);
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::halfvec[]) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::halfvec, '[3]']) v;
SELECT avg(v) FROM unnest(ARRAY['[65504]'::halfvec, '[65504]']) v;
SELECT halfvec_avg(array_agg(n)) FROM generate_series(1, 16002) n;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]']) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]', NULL]) v;
SELECT sum(v) FROM unnest(ARRAY[]::halfvec[]) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::halfvec, '[3]']) v;
SELECT sum(v) FROM unnest(ARRAY['[65504]'::halfvec, '[65504]']) v;

35
test/sql/hnsw_bit.sql Normal file
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@@ -0,0 +1,35 @@
SET enable_seqscan = off;
-- hamming
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
DROP TABLE t;
-- jaccard
CREATE TABLE t (val bit(4));
INSERT INTO t (val) VALUES (B'0000'), (B'1100'), (B'1111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_jaccard_ops);
INSERT INTO t (val) VALUES (B'1110');
SELECT * FROM t ORDER BY val <%> B'1111';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <%> (SELECT NULL::bit)) t2;
DROP TABLE t;
-- varbit
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
DROP TABLE t;

View File

@@ -1,13 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_cosine_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
DROP TABLE t;

58
test/sql/hnsw_halfvec.sql Normal file
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@@ -0,0 +1,58 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;
-- inner product
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_ip_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::halfvec)) t2;
DROP TABLE t;
-- cosine
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_cosine_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t2;
DROP TABLE t;
-- L1
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_l1_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <+> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::halfvec)) t2;
DROP TABLE t;

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@@ -1,12 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_ip_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
DROP TABLE t;

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@@ -1,16 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;

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@@ -1,13 +0,0 @@
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 1);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
SHOW hnsw.ef_search;
SET hnsw.ef_search = 0;
SET hnsw.ef_search = 1001;
DROP TABLE t;

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@@ -0,0 +1,68 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
DROP TABLE t;
-- inner product
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_ip_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <#> '{1:3,2:3,3:3}/3';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::sparsevec)) t2;
DROP TABLE t;
-- cosine
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_cosine_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <=> '{1:3,2:3,3:3}/3';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '{}/3') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::sparsevec)) t2;
DROP TABLE t;
-- L1
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_l1_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <+> '{1:3,2:3,3:3}/3';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::sparsevec)) t2;
DROP TABLE t;
-- non-zero elements
CREATE TABLE t (val sparsevec(1001));
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
TRUNCATE t;
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
DROP TABLE t;

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@@ -1,9 +0,0 @@
SET enable_seqscan = off;
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;

84
test/sql/hnsw_vector.sql Normal file
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@@ -0,0 +1,84 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;
-- inner product
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_ip_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
DROP TABLE t;
-- cosine
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_cosine_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
DROP TABLE t;
-- L1
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l1_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <+> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::vector)) t2;
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;
-- options
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 1);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
SHOW hnsw.ef_search;
SET hnsw.ef_search = 0;
SET hnsw.ef_search = 1001;
DROP TABLE t;

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@@ -1,28 +0,0 @@
SELECT '[1,2,3]'::vector;
SELECT '[-1,-2,-3]'::vector;
SELECT '[1.,2.,3.]'::vector;
SELECT ' [ 1, 2 , 3 ] '::vector;
SELECT '[1.23456]'::vector;
SELECT '[hello,1]'::vector;
SELECT '[NaN,1]'::vector;
SELECT '[Infinity,1]'::vector;
SELECT '[-Infinity,1]'::vector;
SELECT '[1.5e38,-1.5e38]'::vector;
SELECT '[1.5e+38,-1.5e+38]'::vector;
SELECT '[1.5e-38,-1.5e-38]'::vector;
SELECT '[4e38,1]'::vector;
SELECT '[1,2,3'::vector;
SELECT '[1,2,3]9'::vector;
SELECT '1,2,3'::vector;
SELECT ''::vector;
SELECT '['::vector;
SELECT '[,'::vector;
SELECT '[]'::vector;
SELECT '[1,]'::vector;
SELECT '[1a]'::vector;
SELECT '[1,,3]'::vector;
SELECT '[1, ,3]'::vector;
SELECT '[1,2,3]'::vector(2);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
SELECT '{"[1,2,3]"}'::vector(2)[];

23
test/sql/ivfflat_bit.sql Normal file
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@@ -0,0 +1,23 @@
SET enable_seqscan = off;
-- hamming
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
DROP TABLE t;
-- varbit
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat ((val::bit(3)) bit_hamming_ops) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat ((val::bit(64001)) bit_hamming_ops) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat ((val::bit(2)) bit_hamming_ops) WITH (lists = 5);
DROP TABLE t;

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@@ -1,13 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_cosine_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
DROP TABLE t;

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@@ -0,0 +1,45 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;
-- inner product
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_ip_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::halfvec)) t2;
DROP TABLE t;
-- cosine
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_cosine_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t2;
DROP TABLE t;

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@@ -1,12 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_ip_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
DROP TABLE t;

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@@ -1,16 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;

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@@ -1,7 +0,0 @@
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 0);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
SHOW ivfflat.probes;
DROP TABLE t;

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@@ -1,9 +0,0 @@
SET enable_seqscan = off;
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;

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@@ -0,0 +1,65 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;
-- inner product
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_ip_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
DROP TABLE t;
-- cosine
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_cosine_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;
-- options
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 0);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
SHOW ivfflat.probes;
DROP TABLE t;

134
test/sql/sparsevec.sql Normal file
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@@ -0,0 +1,134 @@
SELECT '{1:1.5,3:3.5}/5'::sparsevec;
SELECT '{1:-2,3:-4}/5'::sparsevec;
SELECT '{1:2.,3:4.}/5'::sparsevec;
SELECT ' { 1 : 1.5 , 3 : 3.5 } / 5 '::sparsevec;
SELECT '{1:1.23456}/1'::sparsevec;
SELECT '{1:hello,2:1}/2'::sparsevec;
SELECT '{1:NaN,2:1}/2'::sparsevec;
SELECT '{1:Infinity,2:1}/2'::sparsevec;
SELECT '{1:-Infinity,2:1}/2'::sparsevec;
SELECT '{1:1.5e38,2:-1.5e38}/2'::sparsevec;
SELECT '{1:1.5e+38,2:-1.5e+38}/2'::sparsevec;
SELECT '{1:1.5e-38,2:-1.5e-38}/2'::sparsevec;
SELECT '{1:4e38,2:1}/2'::sparsevec;
SELECT '{1:-4e38,2:1}/2'::sparsevec;
SELECT '{1:1e-46,2:1}/2'::sparsevec;
SELECT '{1:-1e-46,2:1}/2'::sparsevec;
SELECT ''::sparsevec;
SELECT '{'::sparsevec;
SELECT '{ '::sparsevec;
SELECT '{:'::sparsevec;
SELECT '{,'::sparsevec;
SELECT '{}'::sparsevec;
SELECT '{}/'::sparsevec;
SELECT '{}/1'::sparsevec;
SELECT '{}/1a'::sparsevec;
SELECT '{ }/1'::sparsevec;
SELECT '{:}/1'::sparsevec;
SELECT '{,}/1'::sparsevec;
SELECT '{1,}/1'::sparsevec;
SELECT '{:1}/1'::sparsevec;
SELECT '{1:}/1'::sparsevec;
SELECT '{1a:1}/1'::sparsevec;
SELECT '{1:1a}/1'::sparsevec;
SELECT '{1:1,}/1'::sparsevec;
SELECT '{1:0,2:1,3:0}/3'::sparsevec;
SELECT '{2:1,1:1}/2'::sparsevec;
SELECT '{1:1,1:1}/2'::sparsevec;
SELECT '{1:1,2:1,1:1}/2'::sparsevec;
SELECT '{}/5'::sparsevec;
SELECT '{}/-1'::sparsevec;
SELECT '{}/1000000001'::sparsevec;
SELECT '{}/2147483648'::sparsevec;
SELECT '{}/-2147483649'::sparsevec;
SELECT '{}/9223372036854775808'::sparsevec;
SELECT '{}/-9223372036854775809'::sparsevec;
SELECT '{2147483647:1}/1'::sparsevec;
SELECT '{2147483648:1}/1'::sparsevec;
SELECT '{-2147483648:1}/1'::sparsevec;
SELECT '{-2147483649:1}/1'::sparsevec;
SELECT '{0:1}/1'::sparsevec;
SELECT '{2:1}/1'::sparsevec;
SELECT '{}/3'::sparsevec(3);
SELECT '{}/3'::sparsevec(2);
SELECT '{}/3'::sparsevec(3, 2);
SELECT '{}/3'::sparsevec('a');
SELECT '{}/3'::sparsevec(0);
SELECT '{}/3'::sparsevec(1000000001);
SELECT '{1:1,2:2,3:3}/3'::sparsevec < '{1:1,2:2,3:3}/3';
SELECT '{1:1,2:2,3:3}/3'::sparsevec < '{1:1,2:2}/2';
SELECT '{1:1,2:2,3:3}/3'::sparsevec <= '{1:1,2:2,3:3}/3';
SELECT '{1:1,2:2,3:3}/3'::sparsevec <= '{1:1,2:2}/2';
SELECT '{1:1,2:2,3:3}/3'::sparsevec = '{1:1,2:2,3:3}/3';
SELECT '{1:1,2:2,3:3}/3'::sparsevec = '{1:1,2:2}/2';
SELECT '{1:1,2:2,3:3}/3'::sparsevec != '{1:1,2:2,3:3}/3';
SELECT '{1:1,2:2,3:3}/3'::sparsevec != '{1:1,2:2}/2';
SELECT '{1:1,2:2,3:3}/3'::sparsevec >= '{1:1,2:2,3:3}/3';
SELECT '{1:1,2:2,3:3}/3'::sparsevec >= '{1:1,2:2}/2';
SELECT '{1:1,2:2,3:3}/3'::sparsevec > '{1:1,2:2,3:3}/3';
SELECT '{1:1,2:2,3:3}/3'::sparsevec > '{1:1,2:2}/2';
SELECT sparsevec_cmp('{1:1,2:2,3:3}/3', '{1:1,2:2,3:3}/3');
SELECT sparsevec_cmp('{1:1,2:2,3:3}/3', '{}/3');
SELECT sparsevec_cmp('{}/3', '{1:1,2:2,3:3}/3');
SELECT sparsevec_cmp('{1:1,2:2}/2', '{1:1,2:2,3:3}/3');
SELECT sparsevec_cmp('{1:1,2:2,3:3}/3', '{1:1,2:2}/2');
SELECT sparsevec_cmp('{1:1,2:2}/2', '{1:2,2:3,3:4}/3');
SELECT sparsevec_cmp('{1:2,2:3}/2', '{1:1,2:2,3:3}/3');
SELECT round(l2_norm('{1:1,2:1}/2'::sparsevec)::numeric, 5);
SELECT l2_norm('{1:3,2:4}/2'::sparsevec);
SELECT l2_norm('{2:1}/2'::sparsevec);
SELECT l2_norm('{1:3e37,2:4e37}/2'::sparsevec)::real;
SELECT l2_norm('{}/2'::sparsevec);
SELECT l2_norm('{1:2}/1'::sparsevec);
SELECT l2_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
SELECT l2_distance('{1:3}/2'::sparsevec, '{2:4}/2');
SELECT l2_distance('{2:4}/2'::sparsevec, '{1:3}/2');
SELECT l2_distance('{1:3,2:4}/2'::sparsevec, '{}/2');
SELECT l2_distance('{}/2'::sparsevec, '{2:1}/2');
SELECT '{}/2'::sparsevec <-> '{1:3,2:4}/2';
SELECT inner_product('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
SELECT inner_product('{1:1,2:2}/2'::sparsevec, '{1:3}/1');
SELECT inner_product('{1:1,3:3}/4'::sparsevec, '{2:2,4:4}/4');
SELECT inner_product('{2:2,4:4}/4'::sparsevec, '{1:1,3:3}/4');
SELECT inner_product('{1:1,3:3,5:5}/5'::sparsevec, '{2:4,3:6,4:8}/5');
SELECT inner_product('{1:1}/2'::sparsevec, '{}/2');
SELECT inner_product('{}/2'::sparsevec, '{1:1}/2');
SELECT inner_product('{1:3e38}/1'::sparsevec, '{1:3e38}/1');
SELECT inner_product('{1:1,3:3,5:5}/5'::sparsevec, '{2:4,3:6,4:8}/5');
SELECT '{1:1,2:2}/2'::sparsevec <#> '{1:3,2:4}/2';
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{}/2');
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:1,2:1}/2');
SELECT cosine_distance('{1:1}/2'::sparsevec, '{2:2}/2');
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:-1,2:-1}/2');
SELECT cosine_distance('{1:2}/2'::sparsevec, '{2:2}/2');
SELECT cosine_distance('{2:2}/2'::sparsevec, '{1:2}/2');
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{1:3}/1');
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:1.1,2:1.1}/2');
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:-1.1,2:-1.1}/2');
SELECT cosine_distance('{1:3e38}/1'::sparsevec, '{1:3e38}/1');
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
SELECT '{1:1,2:2}/2'::sparsevec <=> '{1:2,2:4}/2';
SELECT l1_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
SELECT l1_distance('{}/2'::sparsevec, '{2:1}/2');
SELECT l1_distance('{1:1,2:2}/2'::sparsevec, '{1:3}/1');
SELECT l1_distance('{1:3e38}/1'::sparsevec, '{1:-3e38}/1');
SELECT l1_distance('{1:1,3:3,5:5,7:7}/8'::sparsevec, '{2:2,4:4,6:6,8:8}/8');
SELECT l1_distance('{1:1,3:3,5:5,7:7,9:9}/9'::sparsevec, '{2:2,4:4,6:6,8:8}/9');
SELECT '{}/2'::sparsevec <+> '{1:3,2:4}/2';
SELECT l2_normalize('{1:3,2:4}/2'::sparsevec);
SELECT l2_normalize('{1:3}/2'::sparsevec);
SELECT l2_normalize('{2:0.1}/2'::sparsevec);
SELECT l2_normalize('{}/2'::sparsevec);
SELECT l2_normalize('{1:3e38}/1'::sparsevec);
SELECT l2_normalize('{1:3e38,2:1e-37}/2'::sparsevec);
SELECT l2_normalize('{2:3e37,4:3e-37,6:4e37,8:4e-37}/9'::sparsevec);

154
test/sql/vector_type.sql Normal file
View File

@@ -0,0 +1,154 @@
SELECT '[1,2,3]'::vector;
SELECT '[-1,-2,-3]'::vector;
SELECT '[1.,2.,3.]'::vector;
SELECT ' [ 1, 2 , 3 ] '::vector;
SELECT '[1.23456]'::vector;
SELECT '[hello,1]'::vector;
SELECT '[NaN,1]'::vector;
SELECT '[Infinity,1]'::vector;
SELECT '[-Infinity,1]'::vector;
SELECT '[1.5e38,-1.5e38]'::vector;
SELECT '[1.5e+38,-1.5e+38]'::vector;
SELECT '[1.5e-38,-1.5e-38]'::vector;
SELECT '[4e38,1]'::vector;
SELECT '[-4e38,1]'::vector;
SELECT '[1e-46,1]'::vector;
SELECT '[-1e-46,1]'::vector;
SELECT '[1,2,3'::vector;
SELECT '[1,2,3]9'::vector;
SELECT '1,2,3'::vector;
SELECT ''::vector;
SELECT '['::vector;
SELECT '[ '::vector;
SELECT '[,'::vector;
SELECT '[]'::vector;
SELECT '[ ]'::vector;
SELECT '[,]'::vector;
SELECT '[1,]'::vector;
SELECT '[1a]'::vector;
SELECT '[1,,3]'::vector;
SELECT '[1, ,3]'::vector;
SELECT '[1,2,3]'::vector(3);
SELECT '[1,2,3]'::vector(2);
SELECT '[1,2,3]'::vector(3, 2);
SELECT '[1,2,3]'::vector('a');
SELECT '[1,2,3]'::vector(0);
SELECT '[1,2,3]'::vector(16001);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
SELECT '{"[1,2,3]"}'::vector(2)[];
SELECT '[1,2,3]'::vector + '[4,5,6]';
SELECT '[3e38]'::vector + '[3e38]';
SELECT '[1,2]'::vector + '[3]';
SELECT '[1,2,3]'::vector - '[4,5,6]';
SELECT '[-3e38]'::vector - '[3e38]';
SELECT '[1,2]'::vector - '[3]';
SELECT '[1,2,3]'::vector * '[4,5,6]';
SELECT '[1e37]'::vector * '[1e37]';
SELECT '[1e-37]'::vector * '[1e-37]';
SELECT '[1,2]'::vector * '[3]';
SELECT '[1,2,3]'::vector || '[4,5]';
SELECT array_fill(0, ARRAY[16000])::vector || '[1]';
SELECT '[1,2,3]'::vector < '[1,2,3]';
SELECT '[1,2,3]'::vector < '[1,2]';
SELECT '[1,2,3]'::vector <= '[1,2,3]';
SELECT '[1,2,3]'::vector <= '[1,2]';
SELECT '[1,2,3]'::vector = '[1,2,3]';
SELECT '[1,2,3]'::vector = '[1,2]';
SELECT '[1,2,3]'::vector != '[1,2,3]';
SELECT '[1,2,3]'::vector != '[1,2]';
SELECT '[1,2,3]'::vector >= '[1,2,3]';
SELECT '[1,2,3]'::vector >= '[1,2]';
SELECT '[1,2,3]'::vector > '[1,2,3]';
SELECT '[1,2,3]'::vector > '[1,2]';
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
SELECT vector_cmp('[1,2]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[1,2]');
SELECT vector_cmp('[1,2]', '[2,3,4]');
SELECT vector_cmp('[2,3]', '[1,2,3]');
SELECT vector_dims('[1,2,3]'::vector);
SELECT round(vector_norm('[1,1]')::numeric, 5);
SELECT vector_norm('[3,4]');
SELECT vector_norm('[0,1]');
SELECT vector_norm('[3e37,4e37]')::real;
SELECT vector_norm('[0,0]');
SELECT vector_norm('[2]');
SELECT l2_distance('[0,0]'::vector, '[3,4]');
SELECT l2_distance('[0,0]'::vector, '[0,1]');
SELECT l2_distance('[1,2]'::vector, '[3]');
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::vector, '[1,1,1,1,1,1,1,4,5]');
SELECT '[0,0]'::vector <-> '[3,4]';
SELECT inner_product('[1,2]'::vector, '[3,4]');
SELECT inner_product('[1,2]'::vector, '[3]');
SELECT inner_product('[3e38]'::vector, '[3e38]');
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::vector, '[1,2,3,4,5,6,7,8,9]');
SELECT '[1,2]'::vector <#> '[3,4]';
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
SELECT cosine_distance('[1,2]'::vector, '[3]');
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[1,2,3,4,5,6,7,8,9]');
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[-1,-2,-3,-4,-5,-6,-7,-8,-9]');
SELECT '[1,2]'::vector <=> '[2,4]';
SELECT l1_distance('[0,0]'::vector, '[3,4]');
SELECT l1_distance('[0,0]'::vector, '[0,1]');
SELECT l1_distance('[1,2]'::vector, '[3]');
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[1,2,3,4,5,6,7,8,9]');
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[0,3,2,5,4,7,6,9,8]');
SELECT '[0,0]'::vector <+> '[3,4]';
SELECT l2_normalize('[3,4]'::vector);
SELECT l2_normalize('[3,0]'::vector);
SELECT l2_normalize('[0,0.1]'::vector);
SELECT l2_normalize('[0,0]'::vector);
SELECT l2_normalize('[3e38]'::vector);
SELECT binary_quantize('[1,0,-1]'::vector);
SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);
SELECT subvector('[1,2,3,4,5]'::vector, -1, 3);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 9);
SELECT subvector('[1,2,3,4,5]'::vector, 1, 0);
SELECT subvector('[1,2,3,4,5]'::vector, 3, -1);
SELECT subvector('[1,2,3,4,5]'::vector, -1, 2);
SELECT subvector('[1,2,3,4,5]'::vector, 2147483647, 10);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2147483647);
SELECT subvector('[1,2,3,4,5]'::vector, -2147483644, 2147483647);
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;

View File

@@ -30,18 +30,19 @@ sub test_recall
SELECT i FROM tst ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my %actual_set = map { $_ => 1 } @actual_ids;
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@expected_ids)
foreach (@actual_ids)
{
if (exists($actual_set{$_}))
if (exists($expected_set{$_}))
{
$correct++;
}
$total++;
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
@@ -81,7 +82,12 @@ for my $i (0 .. $#operators)
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", "SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;");
my $res = $node->safe_psql("postgres", qq(
WITH top AS (
SELECT v $operator '$_' AS distance FROM tst ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator '$_') <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
@@ -98,8 +104,16 @@ for my $i (0 .. $#operators)
test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator);
}
# Account for equal distances
test_recall(100, 0.9925, $operator);
# Test probes equals lists
if ($operator eq "<=>")
{
test_recall(100, 0.9925, $operator);
}
else
{
test_recall(100, 1.00, $operator);
}
$node->safe_psql("postgres", "DROP INDEX idx;");
@@ -119,8 +133,16 @@ for my $i (0 .. $#operators)
test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator);
}
# Account for equal distances
test_recall(100, 0.9925, $operator);
# Test probes equals lists
if ($operator eq "<=>")
{
test_recall(100, 0.9925, $operator);
}
else
{
test_recall(100, 1.00, $operator);
}
$node->safe_psql("postgres", "DROP INDEX idx;");
}

View File

@@ -0,0 +1,116 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $dim = 3;
my $nc = 50;
my $limit = 20;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = get_new_node('node');
$node->init;
$node->start;
# Create table and index
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim), c int4, t text);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql], i % $nc, 'test ' || i FROM generate_series(1, 10000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING ivfflat (v vector_l2_ops) WITH (lists = 100);");
$node->safe_psql("postgres", "ANALYZE tst;");
# Generate query
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
my $query = "[" . join(",", @r) . "]";
my $c = int(rand() * $nc);
# Test attribute filtering
my $explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit;
));
# TODO Do not use index
like($explain, qr/Index Scan using idx/);
# Test attribute filtering with few rows removed
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c != $c ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
# Test attribute filtering with few rows removed comparison
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c >= 1 ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
# Test attribute filtering with many rows removed comparison
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c < 1 ORDER BY v <-> '$query' LIMIT $limit;
));
# TODO Do not use index
like($explain, qr/Index Scan using idx/);
# Test attribute filtering with few rows removed like
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE t LIKE '%%test%%' ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
# Test attribute filtering with many rows removed like
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE t LIKE '%%other%%' ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Seq Scan/);
# Test distance filtering
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' < 1 ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
# Test distance filtering greater than distance
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' > 1 ORDER BY v <-> '$query' LIMIT $limit;
));
# TODO Do not use index
like($explain, qr/Index Scan using idx/);
# Test distance filtering without order
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' < 1;
));
like($explain, qr/Seq Scan/);
# Test distance filtering without limit
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' < 1 ORDER BY v <-> '$query';
));
# TODO Do not use index
like($explain, qr/Index Scan using idx/);
# Test attribute index
$node->safe_psql("postgres", "CREATE INDEX attribute_idx ON tst (c);");
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit;
));
# TODO Use attribute index
like($explain, qr/Index Scan using idx/);
# Test partial index
$node->safe_psql("postgres", "CREATE INDEX partial_idx ON tst USING ivfflat (v vector_l2_ops) WITH (lists = 5) WHERE (c = $c);");
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit;
));
# TODO Use partial index
like($explain, qr/Index Scan using idx/);
done_testing();

View File

@@ -8,6 +8,7 @@ my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $array_sql = join(",", ('random() * random()') x 3);
sub test_recall
{
@@ -54,7 +55,7 @@ $node->start;
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector(3));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 10000) i;"
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 10000) i;"
);
# Generate queries
@@ -67,8 +68,8 @@ for (1 .. 20)
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("vector_l2_ops", "vector_ip_ops", "vector_cosine_ops");
my @operators = ("<->", "<#>", "<=>", "<+>");
my @opclasses = ("vector_l2_ops", "vector_ip_ops", "vector_cosine_ops", "vector_l1_ops");
for my $i (0 .. $#operators)
{
@@ -90,16 +91,15 @@ for my $i (0 .. $#operators)
));
# Test approximate results
my $min = $operator eq "<#>" ? 0.80 : 0.99;
my $min = $operator eq "<#>" ? 0.97 : 0.99;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel
# Build index in parallel in memory
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
SET hnsw.enable_parallel_build = on;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
@@ -109,6 +109,21 @@ for my $i (0 .. $#operators)
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel on disk
# Set parallel_workers on table to use workers with low maintenance_work_mem
($ret, $stdout, $stderr) = $node->psql("postgres", qq(
ALTER TABLE tst SET (parallel_workers = 2);
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '4MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
ALTER TABLE tst RESET (parallel_workers);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem/);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

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