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488 Commits

Author SHA1 Message Date
Andrew Kane
9f944e5c54 Fixed logic [skip ci] 2024-09-23 13:52:50 -07:00
Andrew Kane
e70e582d2f Increase ef_search if needed to improve recall 2023-11-18 15:44:38 -08:00
Andrew Kane
bacd99b37a Test result count [skip ci] 2023-11-18 13:58:05 -08:00
Andrew Kane
08bd246529 Fixed vacuum test [skip ci] 2023-11-10 14:03:13 -08:00
Andrew Kane
f57f2b6821 Added support for inline filtering with HNSW 2023-11-10 13:28:48 -08:00
Andrew Kane
69a2ce0d43 Use datumIsEqual to compare 2023-11-10 10:46:48 -08:00
Andrew Kane
c5e8c46b80 Switched from VECTOR_SIZE to VARSIZE_ANY [skip ci] 2023-11-09 19:41:38 -08:00
Andrew Kane
94f7304ccd Keep vector for now to be overly cautious about packing [skip ci] 2023-11-09 18:43:55 -08:00
Andrew Kane
d078db3d25 Switched HnswElementTuple to generic data and zero full section 2023-11-09 18:28:25 -08:00
Andrew Kane
fbb904ae2f Use pointer for VARSIZE_ANY 2023-11-09 17:50:28 -08:00
Andrew Kane
3cf6f62900 Switched to datum for HnswElement 2023-11-09 17:35:39 -08:00
Andrew Kane
2a69e22ca4 Switched from VECTOR_SIZE to VARSIZE_ANY where possible (less vector-specific) 2023-11-09 17:16:43 -08:00
Andrew Kane
84e073888c Removed vector-specific code from HNSW_ELEMENT_TUPLE_SIZE [skip ci] 2023-11-09 16:57:01 -08:00
Andrew Kane
81a62d55d1 Switched from HNSW_ELEMENT_TUPLE_SIZE to ItemIdGetLength where possible (less vector-specific) 2023-11-09 16:32:00 -08:00
Andrew Kane
3f3463bde5 Improved memory calculation for HNSW and removed vector-specific code 2023-11-09 16:21:26 -08:00
Andrew Kane
a01a72d812 Updated comment [skip ci] 2023-11-05 08:42:06 -08:00
Andrew Kane
0c2fc18a80 Updated comment [skip ci] 2023-11-05 08:40:21 -08:00
Andrew Kane
e860042d3c Improved variable name [skip ci] 2023-11-05 08:35:54 -08:00
Andrew Kane
5986862bd2 Added note about check constraint [skip ci] 2023-11-04 15:01:37 -07:00
Andrew Kane
5d24f5d09a Improved header installation on Windows 2023-11-04 11:16:40 -07:00
Andrew Kane
7c43b0d8ee Updated example [skip ci] 2023-11-03 23:54:50 -07:00
Andrew Kane
7be40036f4 Updated readme [skip ci] 2023-11-03 23:46:23 -07:00
Andrew Kane
9b5a1a69db Updated readme [skip ci] 2023-11-03 23:43:47 -07:00
Andrew Kane
04b96506f5 Added info on storing vectors with more precision [skip ci] 2023-11-03 20:14:28 -07:00
Andrew Kane
35cd7b63cb Updated readme [skip ci] 2023-11-03 17:02:30 -07:00
Andrew Kane
b5416d6f10 Updated readme [skip ci] 2023-11-03 16:48:57 -07:00
Andrew Kane
f361bf2704 Improved docs on indexing vectors with different dimensions [skip ci] 2023-11-03 16:42:14 -07:00
Andrew Kane
3d8c1921aa Improved upgrading docs - #339 [skip ci] 2023-11-03 16:15:06 -07:00
Andrew Kane
154207bc17 Added info on columns with different dimensions [skip ci] 2023-11-03 16:02:00 -07:00
Andrew Kane
8e507f3bf5 Free remaining allocation from deconstruct_array - #332 2023-11-02 21:20:21 -07:00
Andrew Kane
e115773a55 Removed unneeded allocation 2023-11-02 21:16:06 -07:00
Andrew Kane
9333bef046 Added link to setup-pgvector [skip ci] 2023-11-02 13:22:19 -07:00
Andrew Kane
4851e47d9f Added Reciprocal Rank Fusion example to readme [skip ci] 2023-11-01 13:20:49 -07:00
Andrew Kane
12aecfb4f5 Added Nim and Zig to readme [skip ci] 2023-10-31 02:26:18 -07:00
Andrew Kane
800697fb14 Updated column alias [skip ci] 2023-10-29 16:47:55 -07:00
Andrew Kane
de1f2b09dd Improved indexing progress queries [skip ci] 2023-10-29 16:41:39 -07:00
Andrew Kane
bcccb7f5a5 Improved docs for indexing progress - closes #320 and closes #321 [skip ci] 2023-10-29 16:13:12 -07:00
Andrew Kane
bec3d30d68 Added TypeScript to readme [skip ci] 2023-10-29 12:49:01 -07:00
Andrew Kane
588de60445 Added Groovy to readme [skip ci] 2023-10-29 12:39:53 -07:00
Andrew Kane
c599f92b52 Updated readme [skip ci] 2023-10-27 13:22:37 -07:00
Andrew Kane
2a17b335da Added Kotlin to readme [skip ci] 2023-10-26 12:25:58 -07:00
Andrew Kane
6ede6ac301 Added link to pgvector-c [skip ci] 2023-10-26 00:30:06 -07:00
Andrew Kane
3f49b95f01 Added Postgres 17 to CI [skip ci] 2023-10-19 00:37:24 -07:00
Andrew Kane
ef1bea7163 Updated checkout action [skip ci] 2023-10-19 00:36:53 -07:00
Andrew Kane
e630efd195 Version bump to 0.5.1 [skip ci] 2023-10-10 17:40:57 -07:00
Andrew Kane
b5b912906b Added check for MVCC-compliant snapshot and removed marking tuples as dead for IVFFlat index scans - closes #260 2023-10-10 17:28:48 -07:00
Andrew Kane
4b5db94307 Disable closer caching for new elements for now 2023-10-06 14:27:09 -07:00
Andrew Kane
65e70326b8 Updated comment [skip ci] 2023-10-06 14:07:35 -07:00
Andrew Kane
71641ed84e Updated comment [skip ci] 2023-10-06 13:58:07 -07:00
Andrew Kane
f3dba25036 Added comment [skip ci] 2023-10-06 13:56:25 -07:00
Andrew Kane
5588ba6410 Improved variable name [skip ci] 2023-10-06 13:46:19 -07:00
Andrew Kane
ec9fac5456 Improved closerSet logic 2023-10-06 13:39:55 -07:00
Andrew Kane
8085d3e538 Moved sorting logic into SelectNeighbors 2023-10-06 12:56:15 -07:00
Andrew Kane
cae162ffc6 Ensure order is deterministic for SelectNeighbors closer caching 2023-10-06 12:26:53 -07:00
Andrew Kane
62482e3760 Use e for consistency 2023-10-05 16:15:13 -07:00
Heikki Linnakangas
c81302b835 Improve HNSW index build performance more (#295)
This takes the approach from commit a713e2acaa further. Once we have
remove a candidate from the "closer" set, we still don't need to
recalculate everything that follows. Any candidates that were in the
closer set before still only need to be compared with any new
candidates that we have added.
2023-10-05 16:04:50 -07:00
Andrew Kane
a713e2acaa Improved performance of HNSW index builds - closes #292
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2023-10-05 13:21:26 -07:00
Andrew Kane
6e1312ddbe DRY max size 2023-10-04 21:43:34 -07:00
Andrew Kane
4ef5bca275 Use BLCKSZ for consistency 2023-10-04 21:37:55 -07:00
Xiaoran Wang
1ecf6ada76 Include ItemIdData when computing the maxSize for the data in a page (#274)
As the data is aligned, for hnsw, the combined size won't be in the range
(8156 (maxSize exlucding `ItemIdData`), 8160]. So even if the
ItemIdData is not included in the maxSize, it works well now, but I
think it's better to make it correct.
2023-10-04 21:26:46 -07:00
Andrew Kane
564a3d45fc Added check for MVCC-compliant snapshot for HNSW index scans - closes #281 2023-10-04 20:14:50 -07:00
Andrew Kane
8d7abb6590 Revert "Fixed locking for index scans for HNSW - #256"
This reverts commit d032726976.
2023-09-26 23:00:14 -07:00
jeff-davis
b247b688a8 No need to MarkBufferDirty(); GenericXLogFinish() does that. (#265) 2023-09-15 13:14:10 -07:00
Andrew Kane
9672446a4c Updated order [skip ci] 2023-09-12 19:53:12 -07:00
Andrew Kane
334614b7f7 Added HnswFreeNeighbors function [skip ci] 2023-09-12 19:49:31 -07:00
Andrew Kane
643eacd9dc Improved variable name [skip ci] 2023-09-12 19:37:42 -07:00
Andrew Kane
bca50a03fa Use consistent variable name 2023-09-12 19:24:31 -07:00
Andrew Kane
d87833cacc Improved variable scoping [skip ci] 2023-09-12 19:16:55 -07:00
Andrew Kane
4c01073ac1 Improved variable scoping [skip ci] 2023-09-12 18:43:43 -07:00
Andrew Kane
6fed8f1e78 Improved types and scoping for k-means [skip ci] 2023-09-12 18:37:56 -07:00
Andrew Kane
611f5b1047 Improved variable scoping [skip ci] 2023-09-12 18:35:53 -07:00
Andrew Kane
e367155732 Improved types and scoping for k-means 2023-09-12 18:33:31 -07:00
Andrew Kane
466c556b1a Improved variable scoping [skip ci] 2023-09-12 18:24:46 -07:00
Andrew Kane
75e09265d6 Improved variable scoping [skip ci] 2023-09-12 18:14:20 -07:00
Andrew Kane
77c5070fb6 Improved variable scoping [skip ci] 2023-09-12 16:50:51 -07:00
Andrew Kane
1006fdf3f2 Improved variable scoping [skip ci] 2023-09-12 16:44:09 -07:00
Andrew Kane
4209c9b3af Improved variable scoping 2023-09-12 16:13:10 -07:00
Andrew Kane
ec0bb4e4ff Improved code 2023-09-12 15:43:28 -07:00
Andrew Kane
b164833933 Removed pinning for HNSW index scan 2023-09-11 12:12:28 -07:00
Andrew Kane
30fb4dd602 Updated comments [skip ci] 2023-09-07 15:29:54 -07:00
Andrew Kane
d032726976 Fixed locking for index scans for HNSW - #256 2023-09-07 15:27:26 -07:00
Andrew Kane
8fa9001474 Improved Makefiles 2023-09-05 16:43:23 -07:00
Andrew Kane
3431acef94 Improved variable names 2023-09-03 16:49:24 -07:00
Andrew Kane
41bdf24cb7 Fixed flaky test 2023-09-03 15:24:40 -07:00
Andrew Kane
3469a0e74c Simplified test [skip ci] 2023-09-03 15:18:23 -07:00
Andrew Kane
0fe43ca675 Added test for marking tuples as dead 2023-09-03 15:15:02 -07:00
Andrew Kane
bbbe1db72b Improved performance of index scans for IVFFlat after updates and deletes 2023-09-03 14:21:57 -07:00
Andrew Kane
bab5fea9e7 Improved variable name [skip ci] 2023-09-03 12:32:59 -07:00
Andrew Kane
b1f9519689 Get info from metapage to determine cost 2023-09-03 12:31:01 -07:00
Andrew Kane
4571fccc60 Fixed previous commit 2023-09-03 10:51:56 -07:00
Andrew Kane
db747e5aa0 Get lists from metapage 2023-09-03 10:34:44 -07:00
Andrew Kane
2179414c05 Updated extension comment [skip ci] 2023-09-03 03:08:35 -07:00
Andrew Kane
8426ee61d2 Improved upgrading instructions [skip ci] 2023-09-03 03:02:10 -07:00
Andrew Kane
c98c4e13aa Added query for checking version to readme [skip ci] 2023-09-03 02:57:56 -07:00
Andrew Kane
04312f6638 Simplified HNSW vacuum logic 2023-09-03 02:25:19 -07:00
Andrew Kane
72ea3c1210 Added GetScanValue function 2023-09-03 01:59:27 -07:00
Andrew Kane
b0801b8833 Fixed vacuum from previous commit 2023-09-03 01:58:45 -07:00
Andrew Kane
d05d6ee83d Get m from metapage 2023-09-03 01:35:21 -07:00
Andrew Kane
4022bb66a0 Improved variable scoping 2023-09-02 21:14:31 -07:00
Andrew Kane
034d4acaea Removed comment [skip ci] 2023-09-02 18:23:08 -07:00
Andrew Kane
01f58e470a Revert "Use int64 for wlen"
This reverts commit dbef8d1ad1.
2023-09-02 18:09:10 -07:00
Andrew Kane
dbef8d1ad1 Use int64 for wlen 2023-09-02 17:55:48 -07:00
Andrew Kane
5c005cf57c Revert "No need to increment wlen when removing"
This reverts commit 6b2e215447.
2023-09-02 17:41:31 -07:00
Andrew Kane
5665a11a05 Updated comment [skip ci] 2023-09-02 15:34:33 -07:00
Andrew Kane
6b2e215447 No need to increment wlen when removing 2023-09-02 15:33:40 -07:00
Andrew Kane
0d86191eaf Improved test for cosine distance [skip ci] 2023-09-01 19:59:21 -07:00
Andrew Kane
cf9f7aeea9 Added another test for cosine distance [skip ci] 2023-09-01 19:57:28 -07:00
Andrew Kane
0b0e542ce6 Fixed auto-vectorization for vector_spherical_distance with MSVC 2023-09-01 18:42:37 -07:00
Andrew Kane
a4590d2d9d Simplified WAL tests [skip ci] 2023-09-01 15:49:52 -07:00
Andrew Kane
9ebec1529b Updated comments [skip ci] 2023-09-01 00:35:06 -07:00
Andrew Kane
77ff4c18f0 Updated comments [skip ci] 2023-09-01 00:32:42 -07:00
Andrew Kane
88dabaa41c Added test for IVFFlat insert recall 2023-09-01 00:30:02 -07:00
Andrew Kane
1809ffa52b Renamed test [skip ci] 2023-09-01 00:15:07 -07:00
Andrew Kane
024f283ee8 Updated header order [skip ci] 2023-09-01 00:14:03 -07:00
Andrew Kane
da3b2fab46 Updated readme [skip ci] 2023-08-31 22:20:13 -07:00
Andrew Kane
884026a23c Updated changelog [skip ci] 2023-08-29 10:13:05 -07:00
Andrew Kane
4d352e6c30 Updated changelog [skip ci] 2023-08-29 10:11:53 -07:00
Andrew Kane
a8e257e1f1 Added comments [skip ci] 2023-08-28 22:02:48 -07:00
Andrew Kane
3913432303 Version bump to 0.5.0 [skip ci] 2023-08-28 17:01:16 -07:00
Andrew Kane
baeebec244 Updated readme [skip ci] 2023-08-28 15:34:07 -07:00
Andrew Kane
d578a4cccc Updated readme [skip ci] 2023-08-28 15:30:28 -07:00
Andrew Kane
1e18e19496 Updated readme [skip ci] 2023-08-28 15:25:11 -07:00
Andrew Kane
39f973dab2 Updated readme [skip ci] 2023-08-28 15:00:58 -07:00
Andrew Kane
453fa15f28 Updated readme [skip ci] 2023-08-28 09:57:46 -07:00
Jonathan S. Katz
e50a79108f Set default HNSW "ef_construction" to 64 (#230) 2023-08-26 16:05:08 -07:00
Andrew Kane
cfaa2ecd7f Improved HNSW graph repair - #239 2023-08-26 14:06:03 -07:00
Andrew Kane
bb1e5ed98f Improved code [skip ci] 2023-08-25 21:05:18 -07:00
Andrew Kane
8801832946 Fixed check in SelectNeighbors 2023-08-25 20:46:05 -07:00
Andrew Kane
552c64d492 Improved HNSW code 2023-08-25 20:39:07 -07:00
Andrew Kane
86c29b3bf0 Improved param code 2023-08-23 21:10:00 -07:00
Andrew Kane
e406b7f5ea Added comments [skip ci] 2023-08-23 21:03:07 -07:00
Andrew Kane
6d88a9e1d2 Updated HNSW_PAGE_ID [skip ci] 2023-08-21 22:59:53 -07:00
Andrew Kane
1e851c12c0 Updated comment [skip ci] 2023-08-21 22:55:24 -07:00
Andrew Kane
8ed3cc5f0b Improved macro [skip ci] 2023-08-21 22:52:58 -07:00
Andrew Kane
bace0891bd Updated comments [skip ci] 2023-08-21 22:51:24 -07:00
Andrew Kane
4600979504 Updated comments [skip ci] 2023-08-21 22:38:09 -07:00
Andrew Kane
69addf05d0 Updated comments [skip ci] 2023-08-21 22:21:53 -07:00
Andrew Kane
4a5ae8a8df Updated comment [skip ci] 2023-08-21 21:59:47 -07:00
Andrew Kane
ce7da66ca2 Updated comment [skip ci] 2023-08-21 20:57:54 -07:00
Andrew Kane
c6be1c5e13 Fixed test 2023-08-21 20:45:56 -07:00
Andrew Kane
9b3d1a32ff Updated comment [skip ci] 2023-08-21 16:27:03 -07:00
Andrew Kane
8420734350 Updated comments [skip ci] 2023-08-21 16:26:32 -07:00
Andrew Kane
8b03267267 Improved locking for HNSW vacuum [skip ci] 2023-08-21 16:24:55 -07:00
Andrew Kane
641ddf5413 Improved locking for HNSW vacuum 2023-08-21 16:12:29 -07:00
Andrew Kane
782a1051e3 Improved locking for HNSW vacuum 2023-08-21 16:06:32 -07:00
Andrew Kane
ca2be5be6e Updated comment [skip ci] 2023-08-21 16:00:44 -07:00
Andrew Kane
0e1de45463 Improved locking code [skip ci] 2023-08-21 15:42:59 -07:00
Andrew Kane
3f3b3ca8e3 Made function static [skip ci] 2023-08-21 03:27:42 -07:00
Andrew Kane
d4fe67e8ee Simplified locking for entry point 2023-08-21 03:22:23 -07:00
Andrew Kane
02f4e0ec8b Revert "Added version to reduce stale reads and writes and prepare for optimistic locking"
This reverts commit ef1209eaf4.
2023-08-21 02:47:27 -07:00
Andrew Kane
1301706d30 Increased concurrency in HNSW insert test 2023-08-21 02:46:16 -07:00
Andrew Kane
0d58683011 Improved HNSW insert test 2023-08-21 02:44:20 -07:00
Andrew Kane
90a042e5aa Wait for selects to complete 2023-08-21 02:24:53 -07:00
Andrew Kane
bbd57dfebf Moved wait [skip ci] 2023-08-21 01:02:05 -07:00
Andrew Kane
40a013a622 Wait for inserts to complete when vacuuming HNSW 2023-08-21 00:36:32 -07:00
Andrew Kane
ef1209eaf4 Added version to reduce stale reads and writes and prepare for optimistic locking 2023-08-20 17:08:20 -07:00
Andrew Kane
687263ccd4 DRY HNSW vacuum code 2023-08-20 14:52:31 -07:00
Andrew Kane
a62c045c93 Update metapage if needed for HNSW vacuum 2023-08-19 12:19:42 -07:00
Andrew Kane
651e4343c1 Made entryPoint argument for RepairGraphElement 2023-08-19 11:47:13 -07:00
Andrew Kane
2ca2ef94e6 Use rmdir [skip ci] 2023-08-19 10:15:50 -07:00
Andrew Kane
6ba95691d3 Added headers for Windows 2023-08-19 10:03:15 -07:00
Andrew Kane
e9de248e4f Skip i386 tests for windows branches [skip ci] 2023-08-19 10:01:55 -07:00
Andrew Kane
fe79d435c0 Use HEADERS for simplicity [skip ci] 2023-08-19 09:58:25 -07:00
Florents Tselai
b34525fbc2 Make pgvector headers available to others. (#233) 2023-08-19 09:56:02 -07:00
Andrew Kane
206c42e170 Cleaned up header 2023-08-19 01:22:28 -07:00
Andrew Kane
4f8d824280 Use variable for uninstall [skip ci] 2023-08-19 01:21:05 -07:00
Andrew Kane
ca847d02b0 Fixed highest point in HNSW vacuum [skip ci] 2023-08-18 22:23:19 -07:00
Andrew Kane
ca726052ae Fixed flaky test [skip ci] 2023-08-18 20:54:31 -07:00
Andrew Kane
2b25127f3d Fixed flaky test [skip ci] 2023-08-18 20:53:47 -07:00
Andrew Kane
fecb8c06c9 Simplified code 2023-08-18 20:49:00 -07:00
Andrew Kane
a03f6ae4bc Added prefix to function name [skip ci] 2023-08-18 00:54:09 -07:00
Andrew Kane
ed20d98777 Check if item pointer is valid [skip ci] 2023-08-16 17:29:59 -07:00
Andrew Kane
b72a22b3c0 Fixed duplicate connections when repairing graph 2023-08-16 17:07:19 -07:00
Andrew Kane
8c5c0f791e Improved HNSW insert code [skip ci] 2023-08-16 16:31:11 -07:00
Andrew Kane
f9f5ae61df Added test for select with no data for ivfflat 2023-08-15 23:44:18 -07:00
Andrew Kane
2b138d6cb5 Fixed select with no data 2023-08-15 23:25:28 -07:00
Andrew Kane
e8f36aee92 Improved HNSW vacuum code [skip ci] 2023-08-15 22:36:47 -07:00
Andrew Kane
508a8a9ac7 Updated comments [skip ci] 2023-08-15 20:32:15 -07:00
Andrew Kane
d0b0298cda Improved HNSW vacuum code [skip ci] 2023-08-15 20:02:21 -07:00
Andrew Kane
c3bafc76e8 Only update entry point on inserts if level is greater 2023-08-15 12:31:06 -07:00
Andrew Kane
86a062e504 Set entry level in CreateMetaPage [skip ci] 2023-08-15 11:47:05 -07:00
Andrew Kane
b421e76f29 Updated comment [skip ci] 2023-08-13 17:23:52 -07:00
Andrew Kane
ef480ff0b9 Added comment [skip ci] 2023-08-13 17:22:25 -07:00
Andrew Kane
e1d6654063 Revert "Improved HNSW vacuum performance"
This reverts commit c5b2f3ac8b.
2023-08-13 17:19:22 -07:00
Andrew Kane
c5b2f3ac8b Improved HNSW vacuum performance 2023-08-13 16:50:36 -07:00
Andrew Kane
0f238b1fa9 Update neighbors when vacuuming 2023-08-13 16:17:30 -07:00
Andrew Kane
6fc7d06313 Improved HNSW vacuuming 2023-08-13 15:53:07 -07:00
Andrew Kane
304e262a41 Fixed initialization 2023-08-13 15:50:05 -07:00
Andrew Kane
23cb79c1dc Fixed recall for HNSW after vacuuming 2023-08-13 15:37:47 -07:00
Andrew Kane
dc8d467ba5 Improved HNSW vacuum recall test 2023-08-13 13:46:06 -07:00
Andrew Kane
29a0a00731 Improved test [skip ci] 2023-08-13 13:42:51 -07:00
Andrew Kane
eda07ccf7c Improved test 2023-08-13 13:35:43 -07:00
Andrew Kane
c694dbb776 Added test for HNSW vacuum recall 2023-08-13 13:09:51 -07:00
Andrew Kane
3a857ef9f9 Updated readme [skip ci] 2023-08-13 12:16:36 -07:00
Andrew Kane
b60e2483a9 Improved HNSW vacuum stats [skip ci] 2023-08-12 14:09:13 -07:00
Andrew Kane
4295ee3b3a Updated todos [skip ci] 2023-08-12 13:47:20 -07:00
Andrew Kane
8b1ea42d42 Improved HNSW vacuum test 2023-08-12 12:41:27 -07:00
Andrew Kane
3c291fea41 Added todo [skip ci] 2023-08-12 12:41:02 -07:00
Andrew Kane
3d568ef6a1 Added comments [skip ci] 2023-08-11 21:12:18 -07:00
Andrew Kane
7db3b08ef4 Simplified tests [skip ci] 2023-08-11 19:41:55 -07:00
Andrew Kane
4196c88dbd Added opclass to tests [skip ci] 2023-08-11 19:40:04 -07:00
Andrew Kane
3e7ee6ea04 Simplified opclasses in TAP tests [skip ci] 2023-08-11 19:20:03 -07:00
Andrew Kane
5616c1d7a7 Simplified TAP tests [skip ci] 2023-08-11 19:16:08 -07:00
Andrew Kane
0778a507de Use consistent style in TAP tests, part 2 [skip ci] 2023-08-11 19:13:22 -07:00
Andrew Kane
aabbeac30c Use consistent style in TAP tests [skip ci] 2023-08-11 19:08:15 -07:00
Andrew Kane
746dce72ef Use concurrent inserts for insert recall test 2023-08-11 18:41:00 -07:00
Andrew Kane
098813c483 Improved concurrent inserts test for HNSW [skip ci] 2023-08-11 18:33:01 -07:00
Andrew Kane
9d689afd7e Updated test name [skip ci] 2023-08-11 17:17:28 -07:00
Andrew Kane
03930e15a4 Updated comment [skip ci] 2023-08-11 17:09:09 -07:00
Andrew Kane
8a807c01f6 Test fallback path for duplicates [skip ci] 2023-08-11 17:07:38 -07:00
Andrew Kane
85ebb7714e Updated test name [skip ci] 2023-08-11 17:07:17 -07:00
Andrew Kane
34e99593ab Added comment [skip ci] 2023-08-11 17:02:50 -07:00
Andrew Kane
fc45231ef0 Improving naming [skip ci] 2023-08-11 14:56:46 -07:00
Andrew Kane
0191a90f9f Updated comment [skip ci] 2023-08-11 14:37:56 -07:00
Andrew Kane
82e83bd3b1 Added comment [skip ci] 2023-08-11 14:29:24 -07:00
Andrew Kane
d8a14c658a Fixed flaky test [skip ci] 2023-08-11 13:38:42 -07:00
Andrew Kane
ae5de26893 Improved logic for updating HNSW insert page 2023-08-11 13:24:56 -07:00
Andrew Kane
daef83a112 Added comment [skip ci] 2023-08-11 13:03:38 -07:00
Andrew Kane
c9d82c6bdc Revert "Improved insert logic [skip ci]"
This reverts commit 573a336f53.
2023-08-11 12:52:58 -07:00
Andrew Kane
573a336f53 Improved insert logic [skip ci] 2023-08-11 12:39:22 -07:00
Andrew Kane
e7a913f361 Updated comment [skip ci] 2023-08-11 10:11:01 -07:00
Andrew Kane
33438c3cf9 Use neighbor page for insert page [skip ci] 2023-08-11 09:51:41 -07:00
Andrew Kane
8ec1821f1e Added comment [skip ci] 2023-08-11 09:45:08 -07:00
Andrew Kane
b288de719d Consider previously deleted tuples for insert page [skip ci] 2023-08-11 09:41:31 -07:00
Andrew Kane
c13f713f29 Improved test [skip ci] 2023-08-11 09:36:29 -07:00
Andrew Kane
6d15435003 Updated comment [skip ci] 2023-08-11 09:26:54 -07:00
Andrew Kane
12d15a9c41 Improved inserts for HNSW 2023-08-11 09:23:56 -07:00
Andrew Kane
c64288377b Updated min ef_construction to 4 [skip ci] 2023-08-10 21:11:10 -07:00
Andrew Kane
451e36cee7 Added check for ef_construction [skip ci] 2023-08-10 21:09:38 -07:00
Andrew Kane
3ff2e34d7f Updated min M to 2 [skip ci] 2023-08-10 20:57:50 -07:00
Andrew Kane
94a684c9e9 Added test for duplicates 2023-08-10 20:52:58 -07:00
Andrew Kane
1a0d7bccc7 Updated min ef_search to 1 [skip ci] 2023-08-10 20:47:15 -07:00
Andrew Kane
ded8bda72a Fixed flaky test [skip ci] 2023-08-10 18:59:11 -07:00
Andrew Kane
9b967d592f Improved concurrent inserts with empty entry point, part 2 2023-08-10 18:31:58 -07:00
Andrew Kane
ed513e62c1 Improved code for skipping element [skip ci] 2023-08-10 15:29:08 -07:00
Andrew Kane
27ccb5fa7a Improved code [skip ci] 2023-08-10 15:23:26 -07:00
Andrew Kane
92e25e7733 Fixed warning 2023-08-10 15:10:07 -07:00
Andrew Kane
a18bea24b8 Improved concurrent inserts with low number of elements 2023-08-10 15:07:28 -07:00
Andrew Kane
483173460b Improved concurrent inserts with empty entry point 2023-08-10 14:35:24 -07:00
Andrew Kane
da8a914106 Moved FindDuplicate [skip ci] 2023-08-10 13:44:21 -07:00
Andrew Kane
4d6da72b08 Simplified code 2023-08-10 09:56:17 -07:00
Andrew Kane
443c7a5dab Updated variable name [skip ci] 2023-08-10 09:02:01 -07:00
Andrew Kane
9287fe8bcc Updated comment [skip ci] 2023-08-10 08:59:38 -07:00
Andrew Kane
309fa94c05 Improved performance for duplicates 2023-08-10 08:52:45 -07:00
Andrew Kane
6f15dd266c Improved construction code 2023-08-10 08:38:31 -07:00
Andrew Kane
df68eb4570 Look for duplicates last, since may need to fallback 2023-08-10 00:00:27 -07:00
Andrew Kane
7c0d94c99c Improved concurrent inserts 2023-08-09 23:51:35 -07:00
Andrew Kane
d63d430af8 Fixed flaky test [skip ci] 2023-08-09 20:06:28 -07:00
Andrew Kane
5d62e4d080 Moved SelectNeighbors after duplicate check 2023-08-09 19:19:41 -07:00
Andrew Kane
dab8f25d1c Fixed overflow with vector_norm 2023-08-09 16:33:54 -07:00
Andrew Kane
4b887a98ae Moved define [skip ci] 2023-08-09 10:21:01 -07:00
Andrew Kane
d253bafee6 Added HNSW paper to thanks [skip ci] 2023-08-08 23:34:57 -07:00
Andrew Kane
600ca5a797 Improved logic for pruning elements 2023-08-08 18:22:55 -07:00
Andrew Kane
c17d51588a Removed distance from neighbor tuples 2023-08-08 18:11:11 -07:00
Andrew Kane
51d292c93d Added HNSW index type - #181 2023-08-08 16:42:47 -07:00
Andrew Kane
19a6c81367 Fixed link [skip ci] 2023-08-08 01:48:27 -07:00
Andrew Kane
6f212d7cc1 Improved Windows instructions, part 2 [skip ci] 2023-08-07 14:01:24 -07:00
Andrew Kane
25ecabf1ea Improved Windows instructions - closes #218 [skip ci] 2023-08-07 13:56:00 -07:00
Andrew Kane
03457f41ba Added link to pgvector-dart - closes #215 [skip ci] 2023-08-06 22:37:54 -07:00
Andrew Kane
e45c84fd46 Added space before comment [skip ci] 2023-08-05 10:20:30 -07:00
Andrew Kane
37b49b0a37 Fixed results for NULL and NaN distances - fixes #205
Co-authored-by: Xiaoran Wang <wxiaoran@vmware.com>
2023-08-05 09:36:58 -07:00
Andrew Kane
4df01af8b6 Fixed Docker build instructions - #197 [skip ci] 2023-07-27 09:34:11 -07:00
Andrew Kane
237a6df51f Fixed Docker build - fixes #197 2023-07-27 09:27:47 -07:00
Andrew Kane
bcc1366d86 Added tests for large distances 2023-07-25 16:49:21 -07:00
Andrew Kane
047877f495 Improved test 2023-07-25 16:04:32 -07:00
Andrew Kane
e36cf20bce Fixed CI 2023-07-25 15:44:04 -07:00
Andrew Kane
47e5a86b63 Fixed out of range results for cosine distance - fixes #196 2023-07-25 14:54:13 -07:00
Andrew Kane
f210791846 Updated readme [skip ci] 2023-07-19 22:21:12 -07:00
Andrew Kane
280ec74cbd Updated readme [skip ci] 2023-07-19 16:37:32 -07:00
Andrew Kane
67e6b9ee6d Updated readme [skip ci] 2023-07-19 15:58:20 -07:00
Andrew Kane
0160f8f2f1 Added troubleshooting section - closes #186 [skip ci] 2023-07-19 15:48:34 -07:00
Andrew Kane
b710dc68a0 Use fused multiply-add for cosine distance 2023-07-18 16:10:17 -07:00
Andrew Kane
8a05debda1 Ran pgindent [skip ci] 2023-07-18 16:08:50 -07:00
Andrew Kane
1a81b21029 Updated changelog [skip ci] 2023-07-18 16:03:42 -07:00
Andrew Kane
cf1f151cff Now available on DigitalOcean [skip ci] 2023-07-18 13:20:54 -07:00
Pavel Borisov
3950bc3dc6 Speed up ivfflat build: use float instead of double for dot product (#180)
calculation

On ARM this makes CPU using vector multiply-add instruction (fmadd)
instead of vector multiplication + conversion to double + addition
(fmul + fcvt + fadd) at each vector dimension.

Output of distance functions and calculations that are are done once
per vector pair are left double as this don't make speed difference
and for compatibility.
2023-07-18 12:55:38 -07:00
Andrew Kane
f4c28b1c06 Improved includes 2023-07-17 13:17:48 -07:00
Andrew Kane
d13eb8563e Improved includes 2023-07-17 13:15:10 -07:00
Andrew Kane
f6fc033622 Removed unneeded comments [skip ci] 2023-07-17 13:08:27 -07:00
Andrew Kane
518a35784d Improved variable name [skip ci] 2023-07-17 00:18:14 -07:00
Andrew Kane
c3394ace03 Removed unused variable from IvfflatUpdateList 2023-07-17 00:15:20 -07:00
Andrew Kane
98ba795d83 Improved variable scoping 2023-07-17 00:11:21 -07:00
Andrew Kane
6e8746277e Moved _PG_init 2023-07-16 20:03:34 -07:00
Andrew Kane
ad8df27fbb Changed sorting tuples indexing phase to assigning tuples [skip ci] 2023-07-16 18:46:45 -07:00
Andrew Kane
b77451f19e Renamed tests 2023-07-16 16:07:33 -07:00
Andrew Kane
f1d3aa2ba8 Updated comment [skip ci] 2023-07-16 16:02:47 -07:00
Andrew Kane
a722df9cac Test sum aggregate 2023-07-16 15:49:24 -07:00
Andrew Kane
a0c7f618ff Simplified sum aggregate 2023-07-16 15:30:03 -07:00
Andrew Kane
f9d9d64a4e Updated header [skip ci] 2023-07-16 00:55:42 -07:00
Andrew Kane
1fd9794d19 Updated readme [skip ci] 2023-07-15 23:15:49 -07:00
Andrew Kane
13ecd271ba Removed unneeded lists check [skip ci] 2023-07-15 23:06:34 -07:00
Andrew Kane
fd3c3ce83d Added test for avg with large values 2023-07-15 23:03:15 -07:00
Andrew Kane
5796f38ad2 Added test for 2-d array 2023-07-15 22:58:15 -07:00
Andrew Kane
1d47d7218d Improved array_to_vector [skip ci] 2023-07-15 22:56:29 -07:00
Andrew Kane
42007b41ea Improved null check and fixed message [skip ci] 2023-07-15 22:51:40 -07:00
Andrew Kane
21f56374b5 Added test for empty string [skip ci] 2023-07-15 22:45:19 -07:00
Andrew Kane
890f189495 Removed todo [skip ci] 2023-07-15 22:37:52 -07:00
Andrew Kane
ed1bc3e856 Added sum aggregate 2023-07-15 20:25:30 -07:00
Andrew Kane
08e7209810 Added element-wise multiplication for vectors 2023-07-15 20:19:51 -07:00
Andrew Kane
cd4ac17f9f Added l1_distance function - #166 2023-07-15 20:13:45 -07:00
Andrew Kane
b6a822918f Added support for parallel index builds 2023-07-15 19:52:25 -07:00
Andrew Kane
21d5d7e934 Improved variable scoping 2023-07-15 19:01:40 -07:00
Andrew Kane
ea47342870 Improved variable scoping 2023-07-15 18:53:41 -07:00
Andrew Kane
22e9be6528 Use LockRelationForExtension 2023-07-15 18:25:26 -07:00
Andrew Kane
b56971febe Updated link [skip ci] 2023-07-11 21:47:08 -07:00
Jonathan S. Katz
de6502ab6e Simplify TAP test structure to align with upstream (#169)
postgres/postgres@549ec20 moved to using "done_testing()" from
the Perl testing framework, which removed the need to include test
counts.
2023-06-29 11:36:08 -04:00
Andrew Kane
7aaba14440 Added comment [skip ci] 2023-06-29 10:25:06 -04:00
Andrew Kane
ee0bf10d7d Fixed CI for equal distances 2023-06-29 10:24:02 -04:00
Andrew Kane
88094fc39f Fixed tests 2023-06-29 10:17:15 -04:00
Andrew Kane
209394faab Now available on Google Cloud SQL [skip ci] 2023-06-26 11:17:10 -04:00
Andrew Kane
673aca97fc Fixed CI for branches for i386 2023-06-16 17:38:51 -04:00
Andrew Kane
0e2dc0e6d4 Updated readme [skip ci] 2023-06-16 10:15:22 -04:00
Andrew Kane
3c681b94fd Updated example [skip ci] 2023-06-16 10:03:07 -04:00
Andrew Kane
1982121694 Version bump to 0.4.4 [skip ci] 2023-06-12 01:55:22 -07:00
Andrew Kane
9c8c4483db Updated changelog [skip ci] 2023-06-12 01:23:47 -07:00
Andrew Kane
426ae1f16e Added scan-build to CI 2023-06-12 01:13:21 -07:00
Andrew Kane
06c3e68bef Fixed segmentation fault with text representation 2023-06-12 01:09:40 -07:00
Andrew Kane
e5a620e02c Improved tests 2023-06-11 19:23:30 -07:00
Andrew Kane
092bb80f58 Added test for small floats [skip ci] 2023-06-11 19:19:07 -07:00
Andrew Kane
b690cd4d5d Added tests for large floats [skip ci] 2023-06-11 19:17:54 -07:00
Andrew Kane
4e0d11acfe Improved test [skip ci] 2023-06-11 19:15:42 -07:00
Andrew Kane
aa63f80b69 Improved test [skip ci] 2023-06-11 19:14:32 -07:00
Andrew Kane
b8a7355731 Improved test [skip ci] 2023-06-11 19:12:56 -07:00
Andrew Kane
3332669489 Improved tests [skip ci] 2023-06-11 19:11:17 -07:00
Andrew Kane
08c70bb57f Added more input tests [skip ci] 2023-06-11 19:08:24 -07:00
Andrew Kane
eff0de6a64 Updated comments [skip ci] 2023-06-11 18:36:41 -07:00
Andrew Kane
3cf7ce6543 Added comment for CheckDim [skip ci] 2023-06-11 13:06:51 -07:00
Andrew Kane
3cb6440744 Simplified PrintVector [skip ci] 2023-06-11 12:54:18 -07:00
Andrew Kane
b6a0d2b12b Check for empty string like float4in [skip ci] 2023-06-11 12:34:24 -07:00
Andrew Kane
78632e3301 Added input test case [skip ci] 2023-06-11 12:22:52 -07:00
Andrew Kane
f8c85905c3 Use vector_isspace to remove whitespace before strtof 2023-06-11 12:21:27 -07:00
Andrew Kane
0a98a953cd Fixed consecutive delimiters with text representation 2023-06-11 12:10:52 -07:00
Andrew Kane
a577c2df80 Updated format [skip ci] 2023-06-11 12:04:02 -07:00
Andrew Kane
7ee9e86b10 Improved error message for invalid input syntax 2023-06-11 12:00:04 -07:00
Andrew Kane
5fdf5573a0 No need to manually free memory on errors 2023-06-11 09:42:20 -07:00
Andrew Kane
2b939edfee Improved error message for malformed vector literal - #153 2023-06-11 09:24:11 -07:00
Andrew Kane
987026a559 Improved benchmarking for index build [skip ci] 2023-06-10 21:50:31 -07:00
Andrew Kane
d158eefa60 Updated guidance on probes [skip ci] 2023-06-10 17:47:41 -07:00
Andrew Kane
a7bbb0772d Version bump to 0.4.3 [skip ci] 2023-06-10 12:19:41 -07:00
Andrew Kane
6ad276aa54 Added Postgres 16 to CI 2023-06-10 11:35:28 -07:00
Andrew Kane
c03ce7d62a Ensure insert page is always set 2023-06-10 11:29:47 -07:00
Andrew Kane
629fa6f0cd Updated cost estimation code (same logic) 2023-06-10 10:52:29 -07:00
Andrew Kane
a33e72d58e Always change some cost to sequential, and always update total cost 2023-06-10 02:10:53 -07:00
Andrew Kane
49e6a72d36 Remove cost of extra pages when random_page_cost equals seq_page_cost 2023-06-10 01:18:21 -07:00
Andrew Kane
b158a5fa48 Moved get_tablespace_page_costs [skip ci] 2023-06-10 01:07:54 -07:00
Andrew Kane
81cc04df61 Only adjust cost if random_page_cost is higher than seq_page_cost 2023-06-10 01:06:05 -07:00
Andrew Kane
d6ab4892fe Updated example [skip ci] 2023-06-09 21:29:42 -07:00
Andrew Kane
cbaf470f2e Added build arg to docs [skip ci] 2023-06-09 21:24:23 -07:00
Andrew Kane
8cb32cac76 Added comment [skip ci] 2023-06-09 21:20:48 -07:00
Andrew Kane
4ce915cf16 Improved cost estimate - #133 2023-06-09 21:11:16 -07:00
Andrew Kane
41b766c24b Use index tuples 2023-06-09 19:55:49 -07:00
Andrew Kane
d11fe7bbfb Updated changelog [skip ci] 2023-06-09 19:05:53 -07:00
Andrew Kane
2c35074f3a Use ref to fix CI for PRs 2023-06-09 18:56:43 -07:00
Andrew Kane
b4c1c3ab63 Fixed CI 2023-06-09 18:52:51 -07:00
Andrew Kane
edcbafca79 Fixed CI 2023-06-09 18:49:57 -07:00
Andrew Kane
cbec1b3f48 Improved warnings check 2023-06-09 18:46:26 -07:00
Andrew Kane
f81d863dfd Catch warnings on CI 2023-06-09 18:39:44 -07:00
Jonathan S. Katz
b8c7a4f4b6 Fix compiler warnings on Ubuntu (#156)
The compiler was complaining about a missing include due to the
addition of NaN/inf checks in 482a5f8b. Adding the include
silences the warnings.
2023-06-09 18:27:36 -07:00
Jonathan S. Katz
7446cbde8f Update ivfflat cost estimation to choose index for more searches (#133)
Co-authored-by: Andrew Kane <andrew@ankane.org>
2023-06-09 17:53:14 -07:00
Andrew Kane
9f2359894f Added todo [skip ci] 2023-06-09 00:27:01 -07:00
Andrew Kane
3c78130868 Removed extra line [skip ci] 2023-06-08 23:14:34 -07:00
Andrew Kane
768cd5d5d5 Default closest center to 0 2023-06-08 23:07:25 -07:00
Andrew Kane
7335a122db Added comments [skip ci] 2023-06-08 23:02:03 -07:00
Andrew Kane
2115630fb0 Added comments [skip ci] 2023-06-08 23:01:09 -07:00
Andrew Kane
836be51298 Improved variable name [skip ci] 2023-06-08 22:51:20 -07:00
Andrew Kane
972d9d61cb Simplified code [skip ci] 2023-06-08 22:43:00 -07:00
Andrew Kane
8be2b6c244 Free memory on errors 2023-06-08 22:35:31 -07:00
Andrew Kane
0134debfb8 Free datums 2023-06-08 21:23:03 -07:00
Andrew Kane
2f93781c3b Updated changelog [skip ci] 2023-06-08 20:45:48 -07:00
Andrew Kane
4d910f30fd Updated license year [skip ci] 2023-06-08 20:31:01 -07:00
Andrew Kane
a20add331f Updated comments [skip ci] 2023-06-08 20:26:27 -07:00
Andrew Kane
f03381bc62 Updated changelog [skip ci] 2023-06-08 19:59:52 -07:00
Andrew Kane
198390333e Moved whitespace check 2023-06-08 19:52:49 -07:00
yihong
41c68bf692 fix: input function does not allow tailing spaces (#148) 2023-06-08 19:51:20 -07:00
Andrew Kane
13cf29088d Updated changelog [skip ci] 2023-06-08 18:43:47 -07:00
Andrew Kane
1aea0dfcd8 Added element check to binary format and fixed segmentation fault with index creation - fixes #151 2023-06-08 18:32:36 -07:00
Andrew Kane
b6430bae62 Moved overflow check 2023-06-04 13:37:31 -07:00
Andrew Kane
8294a0a562 Improved style [skip ci] 2023-06-04 13:30:28 -07:00
Andrew Kane
b31c8062c3 Avoid allocating more memory 2023-06-04 13:24:27 -07:00
Andrew Kane
73ff7c3c68 Updated changelog [skip ci] 2023-06-04 12:22:42 -07:00
Andrew Kane
482a5f8b66 Added check for NaN 2023-06-04 10:52:28 -07:00
Andrew Kane
e971fdd4fd Fixed infinite values with list centers 2023-06-04 10:42:55 -07:00
Andrew Kane
6330abb7df Added link to hybrid search example [skip ci] 2023-05-31 16:12:58 -07:00
Andrew Kane
7938b476ea Added test for out of range value 2023-05-31 14:07:05 -07:00
Andrew Kane
0ef0467a0f Fixed infinite values with vector addition and subtraction 2023-05-31 13:54:19 -07:00
Andrew Kane
dee2c4feb1 Updated example [skip ci] 2023-05-28 16:48:09 -07:00
Andrew Kane
29d9ec6f1e Updated example [skip ci] 2023-05-28 12:17:40 -07:00
Andrew Kane
0200134397 Added note about hybrid search [skip ci] 2023-05-28 12:14:10 -07:00
Andrew Kane
ceddbac6bf Improved example [skip ci] 2023-05-28 11:36:36 -07:00
Andrew Kane
0deb443458 Added link to multicolumn indexes [skip ci] 2023-05-28 11:07:26 -07:00
Andrew Kane
d1fb0d8e27 Improved filtering docs [skip ci] 2023-05-28 10:58:07 -07:00
Andrew Kane
9e5f7fd5ec Use tsql to fix syntax highlighting [skip ci] 2023-05-27 22:53:47 -07:00
Andrew Kane
7f744b02c8 Updated readme [skip ci] 2023-05-27 22:17:29 -07:00
Andrew Kane
a9c6af89e8 Fixed link [skip ci] 2023-05-27 22:08:52 -07:00
Andrew Kane
212af771bd Added Postgres.app to readme [skip ci] 2023-05-27 22:08:13 -07:00
Andrew Kane
b37d154b26 Updated readme [skip ci] 2023-05-27 21:14:35 -07:00
Andrew Kane
51bd223b4a Updated readme [skip ci] 2023-05-27 13:44:08 -07:00
Andrew Kane
491b6b18f9 Use apt in readme [skip ci] 2023-05-22 14:10:35 -07:00
Andrew Kane
4576a9f9a4 APT packages are now in the main distribution - #131 [skip ci] 2023-05-22 14:01:35 -07:00
Andrew Kane
451ac59a03 Improved code [skip ci] 2023-05-20 19:04:35 -07:00
Andrew Kane
6f94c5e897 Improved code [skip ci] 2023-05-20 19:02:38 -07:00
Andrew Kane
e9c88d6f25 Added instructions for APT [skip ci] 2023-05-19 13:23:09 -07:00
Andrew Kane
a912d1af9a Call FreeAccessStrategy 2023-05-19 13:09:30 -07:00
Andrew Kane
fa401b7883 Fixed compilation error on PowerPC - closes #117
Co-authored-by: Ilya <badt@appar.at>
2023-05-17 16:59:22 -07:00
Andrew Kane
e97ef5fbac Updated changelog [skip ci] 2023-05-17 16:55:52 -07:00
Andrew Kane
dfe487145f Fixed CI 2023-05-17 15:16:58 -07:00
Andrew Kane
c2f331908f Updated changelog [skip ci] 2023-05-17 15:14:30 -07:00
Andrew Kane
7911a3b395 Updated changelog [skip ci] 2023-05-17 15:12:10 -07:00
Andrew Kane
0d46281c02 Added i386 to CI 2023-05-17 15:07:59 -07:00
Andrew Kane
59071dc78d Fixed sort operator - fixes #131 2023-05-17 14:04:15 -07:00
Andrew Kane
5b3878b7fe Fixed avg functions when float8 is pass by reference - #131 2023-05-17 12:01:08 -07:00
mulander
18e7319a40 docs: pgvector now available on Azure (#129)
Available on:
- Azure Database for PostgreSQL Flexible Server
- Azure Cosmos DB for PostgreSQL
2023-05-17 10:58:33 -07:00
Andrew Kane
69672cd84d Version bump to 0.4.2 [skip ci] 2023-05-13 20:47:40 -07:00
Andrew Kane
300adba2f1 Updated messages 2023-05-13 20:44:46 -07:00
Andrew Kane
e362279199 Updated changelog [skip ci] 2023-05-12 18:01:25 -07:00
Andrew Kane
53301021f6 Added dimensions check to vector_avg 2023-05-12 17:19:16 -07:00
Andrew Kane
8f589f6d09 Added test for array_to_vector 2023-05-12 17:14:29 -07:00
Nathan Bossart
dcf206128a Check bounds unconditionally in array_to_vector(). (#127)
Presently, array_to_vector()'s call to CheckDim() is skipped when typmod != -1, which allows for bypassing VECTOR_MAX_DIM.  To fix, call Check[Expected]Dim() unconditionally.  CheckExpectedDim() takes no action when typmod == -1, so there's no need to guard it with an 'if' statement.
2023-05-12 17:08:51 -07:00
Andrew Kane
3244d40e8a Added note about --preserve-env [skip ci] 2023-05-10 12:13:15 -07:00
Andrew Kane
7d8dbcaa3c Added note about Homebrew Postgres [skip ci] 2023-05-10 12:06:30 -07:00
Andrew Kane
7f575f55fb Removed block size note - #120 [skip ci] 2023-05-09 14:43:24 -07:00
Andrew Kane
94e7487d5f Fixed link [skip ci] 2023-05-06 12:33:20 -07:00
Andrew Kane
74a3cd597f Improved Docker tasks [skip ci] 2023-05-06 12:11:10 -07:00
Andrew Kane
db8ed738b8 Split Docker tasks [skip ci] 2023-05-06 11:59:46 -07:00
Andrew Kane
54c550420b Added Docker image for linux/arm64 - closes #115 2023-05-06 11:50:59 -07:00
Fabian Fischer
cc539a0a27 docs: aws rds supports pgvector now (#110) 2023-05-03 13:08:06 -07:00
Andrew Kane
d885e2bcfa Added FAQ about results [skip ci] 2023-05-02 10:17:31 -07:00
Andrew Kane
a445355a48 Added Heroku Postgres link [skip ci] 2023-04-26 12:48:55 -07:00
Andrew Kane
d5b17a3624 Fixed installation error with Postgres 12.0-12.2 - fixes #101 2023-04-25 09:36:21 -07:00
Andrew Kane
6383078029 Updated readme [skip ci] 2023-04-22 17:07:10 -07:00
Andrew Kane
5146c7cc57 Added guidance for probes to readme [skip ci] 2023-04-20 12:32:49 -07:00
Andrew Kane
ac63f9858b Updated readme [skip ci] 2023-04-14 12:35:59 -07:00
Andrew Kane
76a4166857 Added link to pgvector-crystal [skip ci] 2023-04-13 21:10:18 -07:00
Andrew Kane
31fb6963a3 Now available on Render [skip ci] 2023-04-13 13:20:06 -07:00
Andrew Kane
18c06cb9b1 Added link to pgvector-swift [skip ci] 2023-04-11 21:11:46 -07:00
Andrew Kane
f858796c64 Added link to pgvector-haskell [skip ci] 2023-04-11 12:53:00 -07:00
Andrew Kane
f32f695844 Improved notice [skip ci] 2023-04-10 21:31:33 -07:00
Andrew Kane
1b013a94f7 Added notice when index created with little data [skip ci] 2023-04-10 21:28:24 -07:00
Andrew Kane
00148dfa1f Improved indexing docs [skip ci] 2023-04-10 21:12:25 -07:00
Andrew Kane
67fc791d95 Improved indexing docs [skip ci] 2023-04-10 21:04:46 -07:00
Andrew Kane
8bf360ed84 Updated header [skip ci] 2023-04-02 11:24:46 -07:00
Andrew Kane
f79d28347b Updated installation notes [skip ci] 2023-04-02 11:21:57 -07:00
Andrew Kane
20cf63de0a Updated readme [skip ci] 2023-04-02 10:56:37 -07:00
Andrew Kane
587cbcf15b Updated readme [skip ci] 2023-04-02 10:46:44 -07:00
Andrew Kane
c09edb5b8f Moved instructions [skip ci] 2023-04-02 10:39:41 -07:00
Will Laurance
c63501cca4 Update readme to show example usage of PG_CONFIG (#79) 2023-04-02 10:34:02 -07:00
Andrew Kane
58f0c922d2 Updated readme [skip ci] 2023-04-02 10:24:21 -07:00
Andrew Kane
36e73d2818 Updated readme [skip ci] 2023-04-01 20:06:18 -07:00
Andrew Kane
dd92d0ece3 Updated readme [skip ci] 2023-04-01 20:04:47 -07:00
Andrew Kane
6ede7681a5 Updated readme [skip ci] 2023-04-01 19:47:13 -07:00
Andrew Kane
8733729149 Updated readme [skip ci] 2023-04-01 19:45:13 -07:00
Andrew Kane
03a5789132 Updated readme [skip ci] 2023-04-01 19:44:23 -07:00
Andrew Kane
e5b612a856 Updated readme [skip ci] 2023-04-01 19:34:21 -07:00
Andrew Kane
9a7d3532f5 Updated readme [skip ci] 2023-04-01 19:32:26 -07:00
Andrew Kane
91315dfeff Added additional instructions for Ubuntu, Debian, and Windows [skip ci] 2023-04-01 17:42:44 -07:00
Andrew Kane
6e3101d527 Updated Dockerfile [skip ci] 2023-04-01 13:31:52 -07:00
Andrew Kane
96ae1a6a72 Added PG_MAJOR arg to Dockerfile [skip ci] 2023-04-01 13:15:00 -07:00
Andrew Kane
55aeba8bd6 Added lists to example [skip ci] 2023-03-31 22:12:35 -07:00
Andrew Kane
aebe1bae02 Updated readme [skip ci] 2023-03-31 21:55:24 -07:00
Andrew Kane
14355b9312 Updated readme [skip ci] 2023-03-31 21:46:38 -07:00
Andrew Kane
b5c66d0416 Updated readme [skip ci] 2023-03-31 21:36:25 -07:00
Andrew Kane
f534d9878a Updated readme [skip ci] 2023-03-31 21:31:38 -07:00
Andrew Kane
f3df137db6 Improved indexing instructions [skip ci] 2023-03-31 21:28:45 -07:00
Andrew Kane
489cdb5068 Added delete example [skip ci] 2023-03-31 20:02:22 -07:00
Andrew Kane
161f48793e Updated readme [skip ci] 2023-03-31 19:59:53 -07:00
Andrew Kane
f0f7ffca41 Updated readme [skip ci] 2023-03-31 19:34:39 -07:00
Andrew Kane
138d9be616 Added storage examples [skip ci] 2023-03-31 19:17:26 -07:00
Andrew Kane
fb98e73255 Updated readme [skip ci] 2023-03-31 18:55:51 -07:00
Andrew Kane
4754cac40c Updated readme [skip ci] 2023-03-31 18:47:15 -07:00
Andrew Kane
8432efb7d8 Added cosine similarity example [skip ci] 2023-03-31 18:34:36 -07:00
Andrew Kane
c38410259c Updated header [skip ci] 2023-03-31 16:59:21 -07:00
Andrew Kane
609d9fbf0a Updated header [skip ci] 2023-03-31 16:54:14 -07:00
Andrew Kane
7946424639 Updated header [skip ci] 2023-03-31 16:49:40 -07:00
Andrew Kane
d51310dfa0 Updated readme [skip ci] 2023-03-31 16:38:09 -07:00
Andrew Kane
30f2893aeb Updated readme [skip ci] 2023-03-31 16:30:42 -07:00
Andrew Kane
5d0f88529e Updated readme [skip ci] 2023-03-31 16:28:27 -07:00
Andrew Kane
1d020abdd1 Added auto-vectorized comments [skip ci] 2023-03-31 16:20:10 -07:00
Andrew Kane
d0fdd42652 Added comment [skip ci] 2023-03-31 13:37:33 -07:00
Andrew Kane
8473468925 Added instructions for Yum - #76 2023-03-30 15:39:27 -07:00
Andrew Kane
9c01524466 Updated readme [skip ci] 2023-03-26 23:39:09 -07:00
Andrew Kane
121baa411e Added debug message for index scan 2023-03-26 12:45:44 -07:00
Andrew Kane
50005d7326 Updated CI [skip ci] 2023-03-26 09:46:21 -07:00
Andrew Kane
ec12d79cbc Added link to pgvector-perl [skip ci] 2023-03-23 21:42:43 -07:00
Andrew Kane
d3eb56df07 Improved tests 2023-03-22 16:35:56 -07:00
Andrew Kane
13f7aa50c3 Added Render link [skip ci] 2023-03-22 16:29:06 -07:00
Andrew Kane
81e9e72fbc Updated guidance on lists [skip ci] 2023-03-22 14:00:47 -07:00
Andrew Kane
8d95510302 Updated readme [skip ci] 2023-03-22 13:32:25 -07:00
Andrew Kane
53bb2ed0cd Updated Homebrew instructions [skip ci] 2023-03-21 13:20:57 -07:00
79 changed files with 7247 additions and 675 deletions

View File

@@ -8,6 +8,10 @@ jobs:
fail-fast: false
matrix:
include:
- postgres: 17
os: ubuntu-22.04
- postgres: 16
os: ubuntu-22.04
- postgres: 15
os: ubuntu-22.04
- postgres: 14
@@ -17,14 +21,16 @@ jobs:
- postgres: 12
os: ubuntu-20.04
- postgres: 11
os: ubuntu-18.04
os: ubuntu-20.04
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
dev-files: true
- run: make
env:
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
- run: |
export PG_CONFIG=`which pg_config`
sudo --preserve-env=PG_CONFIG make install
@@ -39,11 +45,13 @@ jobs:
runs-on: macos-latest
if: ${{ !startsWith(github.ref_name, 'windows') }}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14
- run: make
env:
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter
- run: make install
- run: make installcheck
- if: ${{ failure() }}
@@ -54,11 +62,12 @@ jobs:
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
windows:
runs-on: windows-latest
if: ${{ !startsWith(github.ref_name, 'mac') }}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14
@@ -70,3 +79,24 @@ jobs:
nmake /NOLOGO /F Makefile.win clean && ^
nmake /NOLOGO /F Makefile.win uninstall
shell: cmd
i386:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest
container:
image: debian:11
options: --platform linux/386
steps:
- run: apt-get update && apt-get install -y build-essential git libipc-run-perl postgresql-13 postgresql-server-dev-13 sudo
- run: service postgresql start
- run: |
git clone https://github.com/${{ github.repository }}.git pgvector
cd pgvector
git fetch origin ${{ github.ref }}
git reset --hard FETCH_HEAD
make
make install
chown -R postgres .
sudo -u postgres make installcheck
sudo -u postgres make prove_installcheck
env:
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare

View File

@@ -1,3 +1,46 @@
## 0.6.0 (unreleased)
- Added support for inline filtering with HNSW
## 0.5.1 (2023-10-10)
- Improved performance of HNSW index builds
- Added check for MVCC-compliant snapshot for index scans
## 0.5.0 (2023-08-28)
- Added HNSW index type
- Added support for parallel index builds for IVFFlat
- Added `l1_distance` function
- Added element-wise multiplication for vectors
- Added `sum` aggregate
- Improved performance of distance functions
- Fixed out of range results for cosine distance
- Fixed results for NULL and NaN distances for IVFFlat
## 0.4.4 (2023-06-12)
- Improved error message for malformed vector literal
- Fixed segmentation fault with text input
- Fixed consecutive delimiters with text input
## 0.4.3 (2023-06-10)
- Improved cost estimation
- Improved support for spaces with text input
- Fixed infinite and NaN values with binary input
- Fixed infinite values with vector addition and subtraction
- Fixed infinite values with list centers
- Fixed compilation error when `float8` is pass by reference
- Fixed compilation error on PowerPC
- Fixed segmentation fault with index creation on i386
## 0.4.2 (2023-05-13)
- Added notice when index created with little data
- Fixed dimensions check for some direct function calls
- Fixed installation error with Postgres 12.0-12.2
## 0.4.1 (2023-03-21)
- Improved performance of cosine distance

View File

@@ -1,9 +1,12 @@
FROM postgres:15
ARG PG_MAJOR=15
FROM postgres:$PG_MAJOR
ARG PG_MAJOR
COPY . /tmp/pgvector
RUN apt-get update && \
apt-get install -y --no-install-recommends build-essential postgresql-server-dev-15 && \
apt-mark hold locales && \
apt-get install -y --no-install-recommends build-essential postgresql-server-dev-$PG_MAJOR && \
cd /tmp/pgvector && \
make clean && \
make OPTFLAGS="" && \
@@ -11,6 +14,7 @@ RUN apt-get update && \
mkdir /usr/share/doc/pgvector && \
cp LICENSE README.md /usr/share/doc/pgvector && \
rm -r /tmp/pgvector && \
apt-get remove -y build-essential postgresql-server-dev-15 && \
apt-get remove -y build-essential postgresql-server-dev-$PG_MAJOR && \
apt-get autoremove -y && \
apt-mark unhold locales && \
rm -rf /var/lib/apt/lists/*

View File

@@ -1,4 +1,4 @@
Portions Copyright (c) 1996-2022, PostgreSQL Global Development Group
Portions Copyright (c) 1996-2023, 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": "0.4.1",
"version": "0.5.1",
"maintainer": [
"Andrew Kane <andrew@ankane.org>"
],
@@ -20,7 +20,7 @@
"vector": {
"file": "sql/vector.sql",
"docfile": "README.md",
"version": "0.4.1",
"version": "0.5.1",
"abstract": "Open-source vector similarity search for Postgres"
}
},

View File

@@ -1,23 +1,30 @@
EXTENSION = vector
EXTVERSION = 0.4.1
EXTVERSION = 0.5.1
MODULE_big = vector
DATA = $(wildcard sql/*--*.sql)
OBJS = src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
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
TESTS = $(wildcard test/sql/*.sql)
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))
REGRESS_OPTS = --inputdir=test --load-extension=vector
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
OPTFLAGS = -march=native
# Mac ARM doesn't support -march=native
ifeq ($(shell uname -s), Darwin)
ifeq ($(shell uname -p), arm)
# no difference with -march=armv8.5-a
OPTFLAGS =
endif
endif
# PowerPC doesn't support -march=native
ifneq ($(filter ppc64%, $(shell uname -m)), )
OPTFLAGS =
endif
# For auto-vectorization:
# - GCC (needs -ftree-vectorize OR -O3) - https://gcc.gnu.org/projects/tree-ssa/vectorization.html
# - Clang (could use pragma instead) - https://llvm.org/docs/Vectorizers.html
@@ -62,3 +69,9 @@ dist:
docker:
docker build --pull --no-cache --platform linux/amd64 -t ankane/pgvector:latest .
.PHONY: docker-release
docker-release:
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 -t ankane/pgvector:latest .
docker buildx build --push --platform linux/amd64,linux/arm64 -t ankane/pgvector:v$(EXTVERSION) .

View File

@@ -1,10 +1,11 @@
EXTENSION = vector
EXTVERSION = 0.4.1
EXTVERSION = 0.5.1
OBJS = src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
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
REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
REGRESS_OPTS = --inputdir=test --load-extension=vector
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
# For /arch flags
# https://learn.microsoft.com/en-us/cpp/build/reference/arch-minimum-cpu-architecture
@@ -54,6 +55,8 @@ install:
copy $(SHLIB) "$(PKGLIBDIR)"
copy $(EXTENSION).control "$(SHAREDIR)\extension"
copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
mkdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
for %f in ($(HEADERS)) do copy %f "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
installcheck:
"$(BINDIR)\pg_regress" --bindir="$(BINDIR)" $(REGRESS_OPTS) $(REGRESS)
@@ -61,7 +64,9 @@ installcheck:
uninstall:
del /f "$(PKGLIBDIR)\$(SHLIB)"
del /f "$(SHAREDIR)\extension\$(EXTENSION).control"
del /f "$(SHAREDIR)\extension\vector--*.sql"
del /f "$(SHAREDIR)\extension\$(EXTENSION)--*.sql"
del /f "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)\*.h"
rmdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
clean:
del /f $(SHLIB) $(EXTENSION).lib $(EXTENSION).exp

565
README.md
View File

@@ -2,13 +2,13 @@
Open-source vector similarity search for Postgres
```sql
CREATE TABLE items (embedding vector(3));
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops);
SELECT * FROM items ORDER BY embedding <-> '[1,2,3]' LIMIT 5;
```
Store your vectors with the rest of your data. Supports:
Supports L2 distance, inner product, and cosine distance
- exact and approximate nearest neighbor search
- L2 distance, inner product, and cosine 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
[![Build Status](https://github.com/pgvector/pgvector/workflows/build/badge.svg?branch=master)](https://github.com/pgvector/pgvector/actions)
@@ -17,53 +17,101 @@ Supports L2 distance, inner product, and cosine distance
Compile and install the extension (supports Postgres 11+)
```sh
git clone --branch v0.4.1 https://github.com/pgvector/pgvector.git
cd /tmp
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo
```
Then load it in databases where you want to use it
See the [installation notes](#installation-notes) if you run into issues
```sql
CREATE EXTENSION vector;
```
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), or [conda-forge](#conda-forge)
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).
## Getting Started
Enable the extension (do this once in each database where you want to use it)
```tsql
CREATE EXTENSION vector;
```
Create a vector column with 3 dimensions
```sql
CREATE TABLE items (embedding vector(3));
CREATE TABLE items (id bigserial PRIMARY KEY, embedding vector(3));
```
Insert values
Insert vectors
```sql
INSERT INTO items VALUES ('[1,2,3]'), ('[4,5,6]');
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
```
Get the nearest neighbor by L2 distance
Get the nearest neighbors by L2 distance
```sql
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 1;
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
Also supports inner product (`<#>`) and cosine distance (`<=>`)
Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators
## Querying
## Storing
Use a `SELECT` clause to get the distance
Create a new table with a vector column
```sql
SELECT embedding <-> '[3,1,2]' AS distance FROM items;
CREATE TABLE items (id bigserial PRIMARY KEY, embedding vector(3));
```
Use a `WHERE` clause to get rows within a certain distance
Or add a vector column to an existing table
```sql
ALTER TABLE items ADD COLUMN embedding vector(3);
```
Insert vectors
```sql
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
```
Upsert vectors
```sql
INSERT INTO items (id, embedding) VALUES (1, '[1,2,3]'), (2, '[4,5,6]')
ON CONFLICT (id) DO UPDATE SET embedding = EXCLUDED.embedding;
```
Update vectors
```sql
UPDATE items SET embedding = '[1,2,3]' WHERE id = 1;
```
Delete vectors
```sql
DELETE FROM items WHERE id = 1;
```
## Querying
Get the nearest neighbors to a vector
```sql
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
Get the nearest neighbors to a row
```sql
SELECT * FROM items WHERE id != 1 ORDER BY embedding <-> (SELECT embedding FROM items WHERE id = 1) LIMIT 5;
```
Get rows within a certain distance
```sql
SELECT * FROM items WHERE embedding <-> '[3,1,2]' < 5;
@@ -71,61 +119,98 @@ SELECT * FROM items WHERE embedding <-> '[3,1,2]' < 5;
Note: Combine with `ORDER BY` and `LIMIT` to use an index
Get the average of vectors
#### Distances
Get the distance
```sql
SELECT embedding <-> '[3,1,2]' AS distance FROM items;
```
For inner product, multiply by -1 (since `<#>` returns the negative inner product)
```tsql
SELECT (embedding <#> '[3,1,2]') * -1 AS inner_product FROM items;
```
For cosine similarity, use 1 - cosine distance
```sql
SELECT 1 - (embedding <=> '[3,1,2]') AS cosine_similarity FROM items;
```
#### Aggregates
Average vectors
```sql
SELECT AVG(embedding) FROM items;
```
Average groups of vectors
```sql
SELECT category_id, AVG(embedding) FROM items GROUP BY category_id;
```
## Indexing
Speed up queries with an approximate index. Add an index for each distance function you want to use.
By default, pgvector performs exact nearest neighbor search, which provides perfect recall.
You can add an index to use approximate nearest neighbor search, which trades some recall for speed. Unlike typical indexes, you will see different results for queries after adding an approximate index.
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);
```
Inner product
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_ip_ops);
```
Cosine distance
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops);
```
Indexes should be created after the table has some data for optimal clustering. Also, unlike typical indexes which only affect performance, you may see different results for queries after adding an approximate index. Vectors with up to 2,000 dimensions can be indexed.
### Index Options
Specify the number of inverted lists (100 by default)
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100);
```
A [good place to start](https://github.com/facebookresearch/faiss/issues/112) is `4 * sqrt(rows)`
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 = 1;
SET ivfflat.probes = 10;
```
A higher value improves 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)
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 = 1;
SET LOCAL ivfflat.probes = 10;
SELECT ...
COMMIT;
```
@@ -135,77 +220,188 @@ COMMIT;
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, tuples_done, tuples_total FROM pg_stat_progress_create_index;
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases are:
The phases for IVFFlat are:
1. `initializing`
2. `performing k-means`
3. `sorting tuples`
3. `assigning tuples`
4. `loading tuples`
Note: `tuples_done` and `tuples_total` are only populated during the `loading tuples` phase
Note: `%` is only populated during the `loading tuples` phase
### Partial Indexes
## HNSW
Consider [partial indexes](https://www.postgresql.org/docs/current/indexes-partial.html) for queries with a `WHERE` clause
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.
Add an index for each distance function you want to use.
L2 distance
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops);
```
Inner product
```sql
CREATE INDEX ON items USING hnsw (embedding vector_ip_ops);
```
Cosine distance
```sql
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
```
Vectors with up to 2,000 dimensions can be indexed.
### Index Options
Specify HNSW parameters
- `m` - the max number of connections per layer (16 by default)
- `ef_construction` - the size of the dynamic candidate list for constructing the graph (64 by default)
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops) WITH (m = 16, ef_construction = 64);
```
### Query Options
Specify the size of the dynamic candidate list for search (40 by default)
```sql
SET hnsw.ef_search = 100;
```
A higher value provides better recall at the cost of speed.
Use `SET LOCAL` inside a transaction to set it for a single query
```sql
BEGIN;
SET LOCAL hnsw.ef_search = 100;
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 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases for HNSW are:
1. `initializing`
2. `loading tuples`
## Filtering
There are a few ways to index nearest neighbor queries with a `WHERE` clause
```sql
SELECT * FROM items WHERE category_id = 123 ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
can be indexed with:
Create an index on one [or more](https://www.postgresql.org/docs/current/indexes-multicolumn.html) of the `WHERE` columns for exact search
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WHERE (category_id = 123);
CREATE INDEX ON items (category_id);
```
To index many different values of `category_id`, consider [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html) on `category_id`.
Or a composite HNSW index for approximate search (added in 0.6.0)
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops, 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);
```
Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html) for approximate search on many different values of the `WHERE` columns
```sql
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
```
## Hybrid Search
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search.
```sql
SELECT id, content FROM items, plainto_tsquery('hello search') query
WHERE textsearch @@ query ORDER BY ts_rank_cd(textsearch, query) DESC LIMIT 5;
```
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.
## Performance
Use `EXPLAIN ANALYZE` to debug performance.
```sql
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
### Exact Search
To speed up queries without an index, increase `max_parallel_workers_per_gather`.
```sql
SET max_parallel_workers_per_gather = 4;
```
To speed up queries with an index, increase the number of inverted lists (at the expense of recall).
If vectors are normalized to length 1 (like [OpenAI embeddings](https://platform.openai.com/docs/guides/embeddings/which-distance-function-should-i-use)), use inner product for best performance.
```tsql
SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5;
```
### Approximate Search
To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
```sql
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 1000);
```
Use `EXPLAIN ANALYZE` to debug performance.
```sql
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 1;
```
## 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.
Language | Libraries / Examples
--- | ---
C | [pgvector-c](https://github.com/pgvector/pgvector-c)
C++ | [pgvector-cpp](https://github.com/pgvector/pgvector-cpp)
C# | [pgvector-dotnet](https://github.com/pgvector/pgvector-dotnet)
Crystal | [pgvector-crystal](https://github.com/pgvector/pgvector-crystal)
Dart | [pgvector-dart](https://github.com/pgvector/pgvector-dart)
Elixir | [pgvector-elixir](https://github.com/pgvector/pgvector-elixir)
Go | [pgvector-go](https://github.com/pgvector/pgvector-go)
Java, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
Haskell | [pgvector-haskell](https://github.com/pgvector/pgvector-haskell)
Java, Kotlin, Groovy, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
JavaScript, TypeScript | [pgvector-node](https://github.com/pgvector/pgvector-node)
Julia | [pgvector-julia](https://github.com/pgvector/pgvector-julia)
Lua | [pgvector-lua](https://github.com/pgvector/pgvector-lua)
Node.js | [pgvector-node](https://github.com/pgvector/pgvector-node)
Nim | [pgvector-nim](https://github.com/pgvector/pgvector-nim)
Perl | [pgvector-perl](https://github.com/pgvector/pgvector-perl)
PHP | [pgvector-php](https://github.com/pgvector/pgvector-php)
Python | [pgvector-python](https://github.com/pgvector/pgvector-python)
R | [pgvector-r](https://github.com/pgvector/pgvector-r)
Ruby | [pgvector-ruby](https://github.com/pgvector/pgvector-ruby), [Neighbor](https://github.com/ankane/neighbor)
Rust | [pgvector-rust](https://github.com/pgvector/pgvector-rust)
Swift | [pgvector-swift](https://github.com/pgvector/pgvector-swift)
Zig | [pgvector-zig](https://github.com/pgvector/pgvector-zig)
## Frequently Asked Questions
@@ -219,10 +415,97 @@ 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?
Two things you can try are:
Youll need to use [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction) at the moment.
1. use dimensionality reduction
2. compile Postgres with a larger block size (`./configure --with-blocksize=32`) and edit the limit in `src/ivfflat.h`
#### Can I store vectors with different dimensions in the same column?
You can use `vector` as the type (instead of `vector(3)`).
```sql
CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id));
```
However, you can only create indexes on rows with the same number of dimensions (using [expression](https://www.postgresql.org/docs/current/indexes-expressional.html) and [partial](https://www.postgresql.org/docs/current/indexes-partial.html) indexing):
```sql
CREATE INDEX ON embeddings USING hnsw ((embedding::vector(3)) vector_l2_ops) WHERE (model_id = 123);
```
and query with:
```sql
SELECT * FROM embeddings WHERE model_id = 123 ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
```
#### Can I store vectors with more precision?
You can use the `double precision[]` or `numeric[]` type to store vectors with more precision.
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding double precision[]);
-- use {} instead of [] for Postgres arrays
INSERT INTO items (embedding) VALUES ('{1,2,3}'), ('{4,5,6}');
```
Optionally, add a [check constraint](https://www.postgresql.org/docs/current/ddl-constraints.html) to ensure data can be converted to the `vector` type and has the expected dimensions.
```sql
ALTER TABLE items ADD CHECK (vector_dims(embedding::vector) = 3);
```
Use [expression indexing](https://www.postgresql.org/docs/current/indexes-expressional.html) to index (at a lower precision):
```sql
CREATE INDEX ON items USING hnsw ((embedding::vector(3)) vector_l2_ops);
```
and query with:
```sql
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
```
## Troubleshooting
#### 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:
```sql
BEGIN;
SET LOCAL enable_seqscan = off;
SELECT ...
COMMIT;
```
Also, if the table is small, a table scan may be faster.
#### Why isnt a query using a parallel table scan?
The planner doesnt consider [out-of-line storage](https://www.postgresql.org/docs/current/storage-toast.html) in cost estimates, which can make a serial scan look cheaper. You can reduce the cost of a parallel scan for a query with:
```sql
BEGIN;
SET LOCAL min_parallel_table_scan_size = 1;
SET LOCAL parallel_setup_cost = 1;
SELECT ...
COMMIT;
```
or choose to store vectors inline:
```sql
ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
```
#### 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.
```sql
DROP INDEX index_name;
```
## Reference
@@ -232,29 +515,80 @@ Each vector takes `4 * dimensions + 8` bytes of storage. Each element is a singl
### Vector Operators
Operator | Description
--- | ---
\+ | element-wise addition
\- | element-wise subtraction
<-> | Euclidean distance
<#> | negative inner product
<=> | cosine distance
Operator | Description | Added
--- | --- | ---
\+ | element-wise addition |
\- | element-wise subtraction |
\* | element-wise multiplication | 0.5.0
<-> | Euclidean distance |
<#> | negative inner product |
<=> | cosine distance |
### Vector Functions
Function | Description
--- | ---
cosine_distance(vector, vector) → double precision | cosine distance
inner_product(vector, vector) → double precision | inner product
l2_distance(vector, vector) → double precision | Euclidean distance
vector_dims(vector) → integer | number of dimensions
vector_norm(vector) → double precision | Euclidean norm
Function | Description | Added
--- | --- | ---
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
vector_dims(vector) → integer | number of dimensions |
vector_norm(vector) → double precision | Euclidean norm |
### Aggregate Functions
Function | Description
--- | ---
avg(vector) → vector | arithmetic mean
Function | Description | Added
--- | --- | ---
avg(vector) → vector | average |
sum(vector) → vector | sum | 0.5.0
## Installation Notes
### 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
```
Then re-run the installation instructions (run `make clean` before `make` if needed). If `sudo` is needed for `make install`, use:
```sh
sudo --preserve-env=PG_CONFIG make install
```
### 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.
For Ubuntu and Debian, use:
```sh
sudo apt install postgresql-server-dev-15
```
Note: Replace `15` with your Postgres server version
### Windows
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:
```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\15"
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
```
## Additional Installation Methods
@@ -271,9 +605,9 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
You can also build the image manually:
```sh
git clone --branch v0.4.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
cd pgvector
docker build -t pgvector .
docker build --build-arg PG_MAJOR=15 -t myuser/pgvector .
```
### Homebrew
@@ -281,9 +615,11 @@ docker build -t pgvector .
With Homebrew Postgres, you can use:
```sh
brew install pgvector/brew/pgvector
brew install pgvector
```
Note: This only adds it to the `postgresql@14` formula
### PGXN
Install from the [PostgreSQL Extension Network](https://pgxn.org/dist/vector) with:
@@ -292,6 +628,28 @@ Install from the [PostgreSQL Extension Network](https://pgxn.org/dist/vector) wi
pgxn install vector
```
### APT
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
```
Note: Replace `15` 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
# or
sudo dnf install pgvector_15
```
Note: Replace `15` with your Postgres server version
### conda-forge
With Conda Postgres, install from [conda-forge](https://anaconda.org/conda-forge/pgvector) with:
@@ -302,25 +660,28 @@ conda install -c conda-forge pgvector
This method is [community-maintained](https://github.com/conda-forge/pgvector-feedstock) by [@mmcauliffe](https://github.com/mmcauliffe)
### Postgres.app
Download the [latest release](https://postgresapp.com/downloads.html) with Postgres 15+.
## Hosted Postgres
pgvector is available on [these providers](https://github.com/pgvector/pgvector/issues/54).
To request a new extension on other providers:
- Amazon RDS - follow the instructions on [this page](https://aws.amazon.com/rds/postgresql/faqs/)
- Google Cloud SQL - vote or comment on [this page](https://issuetracker.google.com/issues/265172065)
- DigitalOcean Managed Databases - vote or comment on [this page](https://ideas.digitalocean.com/app-framework-services/p/pgvector-extension-for-postgresql)
- Azure Database - vote or comment on [this page](https://feedback.azure.com/d365community/idea/7b423322-6189-ed11-a81b-000d3ae49307)
## Upgrading
Install the latest version and run:
[Install](#installation) the latest version (use the same method as the original installation). Then in each database you want to upgrade, run:
```sql
ALTER EXTENSION vector UPDATE;
```
You can check the version in the current database with:
```sql
SELECT extversion FROM pg_extension WHERE extname = 'vector';
```
## Upgrade Notes
### 0.4.0
@@ -353,9 +714,11 @@ Thanks to:
- [PASE: PostgreSQL Ultra-High-Dimensional Approximate Nearest Neighbor Search Extension](https://dl.acm.org/doi/pdf/10.1145/3318464.3386131)
- [Faiss: A Library for Efficient Similarity Search and Clustering of Dense Vectors](https://github.com/facebookresearch/faiss)
- [Using the Triangle Inequality to Accelerate k-means](https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf)
- [Using the Triangle Inequality to Accelerate k-means](https://cdn.aaai.org/ICML/2003/ICML03-022.pdf)
- [k-means++: The Advantage of Careful Seeding](https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf)
- [Concept Decompositions for Large Sparse Text Data using Clustering](https://www.cs.utexas.edu/users/inderjit/public_papers/concept_mlj.pdf)
- [Efficient and Robust Approximate Nearest Neighbor Search using Hierarchical Navigable Small World Graphs](https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf)
- [HQANN: Efficient and Robust Similarity Search for Hybrid Queries with Structured and Unstructured Constraints](https://arxiv.org/pdf/2207.07940.pdf)
## History
@@ -403,4 +766,4 @@ Resources for contributors
- [Extension Building Infrastructure](https://www.postgresql.org/docs/current/extend-pgxs.html)
- [Index Access Method Interface Definition](https://www.postgresql.org/docs/current/indexam.html)
- [Generic WAL Records](https://www.postgresql.org/docs/13/generic-wal.html)
- [Generic WAL Records](https://www.postgresql.org/docs/current/generic-wal.html)

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 '0.4.2'" 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 '0.4.3'" 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 '0.4.4'" to load this file. \quit

View File

@@ -0,0 +1,43 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.5.0'" to load this file. \quit
CREATE FUNCTION l1_distance(vector, vector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_mul(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR * (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_mul,
COMMUTATOR = *
);
CREATE AGGREGATE sum(vector) (
SFUNC = vector_add,
STYPE = vector,
COMBINEFUNC = vector_add,
PARALLEL = SAFE
);
CREATE FUNCTION hnswhandler(internal) RETURNS index_am_handler
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE ACCESS METHOD hnsw TYPE INDEX HANDLER hnswhandler;
COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method';
CREATE OPERATOR CLASS vector_l2_ops
FOR TYPE vector USING hnsw AS
OPERATOR 1 <-> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_l2_squared_distance(vector, vector);
CREATE OPERATOR CLASS vector_ip_ops
FOR TYPE vector USING hnsw AS
OPERATOR 1 <#> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_negative_inner_product(vector, vector);
CREATE OPERATOR CLASS vector_cosine_ops
FOR TYPE vector USING hnsw AS
OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_negative_inner_product(vector, vector),
FUNCTION 2 vector_norm(vector);

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 '0.5.1'" to load this file. \quit

View File

@@ -0,0 +1,10 @@
-- 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
CREATE FUNCTION hnsw_attribute_distance(integer, integer) RETURNS float8
AS 'MODULE_PATHNAME', 'hnsw_int4_attribute_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR CLASS vector_integer_ops
DEFAULT FOR TYPE integer USING hnsw AS
OPERATOR 2 = (integer, integer),
FUNCTION 3 hnsw_attribute_distance(integer, integer);

View File

@@ -40,6 +40,9 @@ CREATE FUNCTION inner_product(vector, vector) RETURNS float8
CREATE FUNCTION cosine_distance(vector, vector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(vector, vector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_dims(vector) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -52,6 +55,9 @@ CREATE FUNCTION vector_add(vector, vector) RETURNS vector
CREATE FUNCTION vector_sub(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_mul(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- private functions
CREATE FUNCTION vector_lt(vector, vector) RETURNS bool
@@ -104,6 +110,13 @@ CREATE AGGREGATE avg(vector) (
PARALLEL = SAFE
);
CREATE AGGREGATE sum(vector) (
SFUNC = vector_add,
STYPE = vector,
COMBINEFUNC = vector_add,
PARALLEL = SAFE
);
-- cast functions
CREATE FUNCTION vector(vector, integer, boolean) RETURNS vector
@@ -171,6 +184,11 @@ CREATE OPERATOR - (
COMMUTATOR = -
);
CREATE OPERATOR * (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_mul,
COMMUTATOR = *
);
CREATE OPERATOR < (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_lt,
COMMUTATOR = > , NEGATOR = >= ,
@@ -209,7 +227,7 @@ CREATE OPERATOR > (
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
);
-- access method
-- access methods
CREATE FUNCTION ivfflathandler(internal) RETURNS index_am_handler
AS 'MODULE_PATHNAME' LANGUAGE C;
@@ -218,6 +236,13 @@ CREATE ACCESS METHOD ivfflat TYPE INDEX HANDLER ivfflathandler;
COMMENT ON ACCESS METHOD ivfflat IS 'ivfflat index access method';
CREATE FUNCTION hnswhandler(internal) RETURNS index_am_handler
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE ACCESS METHOD hnsw TYPE INDEX HANDLER hnswhandler;
COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method';
-- opclasses
CREATE OPERATOR CLASS vector_ops
@@ -249,3 +274,29 @@ CREATE OPERATOR CLASS vector_cosine_ops
FUNCTION 2 vector_norm(vector),
FUNCTION 3 vector_spherical_distance(vector, vector),
FUNCTION 4 vector_norm(vector);
CREATE OPERATOR CLASS vector_l2_ops
FOR TYPE vector USING hnsw AS
OPERATOR 1 <-> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_l2_squared_distance(vector, vector);
CREATE OPERATOR CLASS vector_ip_ops
FOR TYPE vector USING hnsw AS
OPERATOR 1 <#> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_negative_inner_product(vector, vector);
CREATE OPERATOR CLASS vector_cosine_ops
FOR TYPE vector USING hnsw AS
OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_negative_inner_product(vector, vector),
FUNCTION 2 vector_norm(vector);
-- hnsw attributes
CREATE FUNCTION hnsw_attribute_distance(integer, integer) RETURNS float8
AS 'MODULE_PATHNAME', 'hnsw_int4_attribute_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR CLASS vector_integer_ops
DEFAULT FOR TYPE integer USING hnsw AS
OPERATOR 2 = (integer, integer),
FUNCTION 3 hnsw_attribute_distance(integer, integer);

238
src/hnsw.c Normal file
View File

@@ -0,0 +1,238 @@
#include "postgres.h"
#include <float.h>
#include <math.h>
#include "access/amapi.h"
#include "commands/vacuum.h"
#include "hnsw.h"
#include "utils/guc.h"
#include "utils/selfuncs.h"
#if PG_VERSION_NUM >= 120000
#include "commands/progress.h"
#endif
int hnsw_ef_search;
static relopt_kind hnsw_relopt_kind;
/*
* Initialize index options and variables
*/
void
HnswInit(void)
{
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
#if PG_VERSION_NUM >= 130000
,AccessExclusiveLock
#endif
);
add_int_reloption(hnsw_relopt_kind, "ef_construction", "Size of the dynamic candidate list for construction",
HNSW_DEFAULT_EF_CONSTRUCTION, HNSW_MIN_EF_CONSTRUCTION, HNSW_MAX_EF_CONSTRUCTION
#if PG_VERSION_NUM >= 130000
,AccessExclusiveLock
#endif
);
DefineCustomIntVariable("hnsw.ef_search", "Sets the size of the dynamic candidate list for search",
"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);
}
/*
* Get the name of index build phase
*/
#if PG_VERSION_NUM >= 120000
static char *
hnswbuildphasename(int64 phasenum)
{
switch (phasenum)
{
case PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE:
return "initializing";
case PROGRESS_HNSW_PHASE_LOAD:
return "loading tuples";
default:
return NULL;
}
}
#endif
/*
* Estimate the cost of an index scan
*/
static void
hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
Cost *indexStartupCost, Cost *indexTotalCost,
Selectivity *indexSelectivity, double *indexCorrelation,
double *indexPages)
{
GenericCosts costs;
int m;
int entryLevel;
Relation index;
#if PG_VERSION_NUM < 120000
List *qinfos;
#endif
/* Never use index without order */
if (path->indexorderbys == NULL)
{
*indexStartupCost = DBL_MAX;
*indexTotalCost = DBL_MAX;
*indexSelectivity = 0;
*indexCorrelation = 0;
*indexPages = 0;
return;
}
MemSet(&costs, 0, sizeof(costs));
index = index_open(path->indexinfo->indexoid, NoLock);
HnswGetMetaPageInfo(index, &m, NULL);
index_close(index, NoLock);
/* Approximate entry level */
entryLevel = (int) -log(1.0 / path->indexinfo->tuples) * HnswGetMl(m);
/* TODO Improve estimate of visited tuples (currently underestimates) */
/* 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;
*indexTotalCost = costs.indexTotalCost;
*indexSelectivity = costs.indexSelectivity;
*indexCorrelation = costs.indexCorrelation;
*indexPages = costs.numIndexPages;
}
/*
* Parse and validate the reloptions
*/
static bytea *
hnswoptions(Datum reloptions, bool validate)
{
static const relopt_parse_elt tab[] = {
{"m", RELOPT_TYPE_INT, offsetof(HnswOptions, m)},
{"ef_construction", RELOPT_TYPE_INT, offsetof(HnswOptions, efConstruction)},
};
#if PG_VERSION_NUM >= 130000
return (bytea *) build_reloptions(reloptions, validate,
hnsw_relopt_kind,
sizeof(HnswOptions),
tab, lengthof(tab));
#else
relopt_value *options;
int numoptions;
HnswOptions *rdopts;
options = parseRelOptions(reloptions, validate, hnsw_relopt_kind, &numoptions);
rdopts = allocateReloptStruct(sizeof(HnswOptions), options, numoptions);
fillRelOptions((void *) rdopts, sizeof(HnswOptions), options, numoptions,
validate, tab, lengthof(tab));
return (bytea *) rdopts;
#endif
}
/*
* Validate catalog entries for the specified operator class
*/
static bool
hnswvalidate(Oid opclassoid)
{
return true;
}
/*
* Define index handler
*
* See https://www.postgresql.org/docs/current/index-api.html
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(hnswhandler);
Datum
hnswhandler(PG_FUNCTION_ARGS)
{
IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0;
amroutine->amsupport = 3;
#if PG_VERSION_NUM >= 130000
amroutine->amoptsprocnum = 0;
#endif
amroutine->amcanorder = false;
amroutine->amcanorderbyop = true;
amroutine->amcanbackward = false; /* can change direction mid-scan */
amroutine->amcanunique = false;
amroutine->amcanmulticol = true;
amroutine->amoptionalkey = true;
amroutine->amsearcharray = false;
amroutine->amsearchnulls = false;
amroutine->amstorage = false;
amroutine->amclusterable = false;
amroutine->ampredlocks = false;
amroutine->amcanparallel = false;
amroutine->amcaninclude = false;
#if PG_VERSION_NUM >= 130000
amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */
amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL;
#endif
amroutine->amkeytype = InvalidOid;
/* Interface functions */
amroutine->ambuild = hnswbuild;
amroutine->ambuildempty = hnswbuildempty;
amroutine->aminsert = hnswinsert;
amroutine->ambulkdelete = hnswbulkdelete;
amroutine->amvacuumcleanup = hnswvacuumcleanup;
amroutine->amcanreturn = NULL;
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;
#endif
amroutine->ambeginscan = hnswbeginscan;
amroutine->amrescan = hnswrescan;
amroutine->amgettuple = hnswgettuple;
amroutine->amgetbitmap = NULL;
amroutine->amendscan = hnswendscan;
amroutine->ammarkpos = NULL;
amroutine->amrestrpos = NULL;
/* Interface functions to support parallel index scans */
amroutine->amestimateparallelscan = NULL;
amroutine->aminitparallelscan = NULL;
amroutine->amparallelrescan = NULL;
PG_RETURN_POINTER(amroutine);
}
/*
* Get the distance between two int4 attributes
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(hnsw_int4_attribute_distance);
Datum
hnsw_int4_attribute_distance(PG_FUNCTION_ARGS)
{
int32 a = PG_GETARG_INT32(0);
int32 b = PG_GETARG_INT32(1);
double distance = ((double) a) - ((double) b);
PG_RETURN_FLOAT8(distance);
}

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#ifndef HNSW_H
#define HNSW_H
#include "postgres.h"
#include "access/generic_xlog.h"
#include "access/reloptions.h"
#include "nodes/execnodes.h"
#include "port.h" /* for random() */
#include "utils/sampling.h"
#include "vector.h"
#if PG_VERSION_NUM < 110000
#error "Requires PostgreSQL 11+"
#endif
#define HNSW_MAX_DIM 2000
/* Support functions */
#define HNSW_DISTANCE_PROC 1
#define HNSW_NORM_PROC 2
#define HNSW_ATTRIBUTE_DISTANCE_PROC 3
#define HNSW_VERSION 1
#define HNSW_MAGIC_NUMBER 0xA953A953
#define HNSW_PAGE_ID 0xFF90
/* Preserved page numbers */
#define HNSW_METAPAGE_BLKNO 0
#define HNSW_HEAD_BLKNO 1 /* first element page */
/* Must correspond to page numbers since page lock is used */
#define HNSW_UPDATE_LOCK 0
#define HNSW_SCAN_LOCK 1
/* HNSW parameters */
#define HNSW_DEFAULT_M 16
#define HNSW_MIN_M 2
#define HNSW_MAX_M 100
#define HNSW_DEFAULT_EF_CONSTRUCTION 64
#define HNSW_MIN_EF_CONSTRUCTION 4
#define HNSW_MAX_EF_CONSTRUCTION 1000
#define HNSW_DEFAULT_EF_SEARCH 40
#define HNSW_MIN_EF_SEARCH 1
#define HNSW_MAX_EF_SEARCH 1000
/* Tuple types */
#define HNSW_ELEMENT_TUPLE_TYPE 1
#define HNSW_NEIGHBOR_TUPLE_TYPE 2
/* Make graph robust against non-HOT updates */
#define HNSW_HEAPTIDS 10
#define HNSW_UPDATE_ENTRY_GREATER 1
#define HNSW_UPDATE_ENTRY_ALWAYS 2
/* Build phases */
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
#define PROGRESS_HNSW_PHASE_LOAD 2
#define HNSW_MAX_SIZE (BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - sizeof(ItemIdData))
#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 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)
#else
#define RandomDouble() (((double) random()) / MAX_RANDOM_VALUE)
#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)
#endif
#define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
#define HnswIsNeighborTuple(tup) ((tup)->type == HNSW_NEIGHBOR_TUPLE_TYPE)
/* 2 * M connections for ground layer */
#define HnswGetLayerM(m, layer) (layer == 0 ? (m) * 2 : (m))
/* Optimal ML from paper */
#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)
/* Variables */
extern int hnsw_ef_search;
typedef struct HnswNeighborArray HnswNeighborArray;
typedef struct HnswElementData
{
List *heaptids;
uint8 level;
uint8 deleted;
HnswNeighborArray *neighbors;
BlockNumber blkno;
OffsetNumber offno;
OffsetNumber neighborOffno;
BlockNumber neighborPage;
Datum value;
IndexTuple itup;
} HnswElementData;
typedef HnswElementData * HnswElement;
typedef struct HnswCandidate
{
HnswElement element;
float distance;
bool matches;
bool closer;
} HnswCandidate;
typedef struct HnswNeighborArray
{
int length;
bool closerSet;
HnswCandidate *items;
} HnswNeighborArray;
typedef struct HnswPairingHeapNode
{
pairingheap_node ph_node;
HnswCandidate *inner;
} HnswPairingHeapNode;
/* HNSW index options */
typedef struct HnswOptions
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int m; /* number of connections */
int efConstruction; /* size of dynamic candidate list */
} HnswOptions;
typedef struct HnswBuildState
{
/* Info */
Relation heap;
Relation index;
IndexInfo *indexInfo;
ForkNumber forkNum;
/* Settings */
int dimensions;
int m;
int efConstruction;
/* Statistics */
double indtuples;
double reltuples;
/* Support functions */
FmgrInfo **procinfos;
FmgrInfo *normprocinfo;
Oid *collations;
/* Variables */
List *elements;
HnswElement entryPoint;
double ml;
int maxLevel;
long memoryLeft;
bool flushed;
bool useIndexTuple;
Vector *normvec;
/* Memory */
MemoryContext tmpCtx;
} HnswBuildState;
typedef struct HnswMetaPageData
{
uint32 magicNumber;
uint32 version;
uint32 dimensions;
uint16 m;
uint16 efConstruction;
BlockNumber entryBlkno;
OffsetNumber entryOffno;
int16 entryLevel;
BlockNumber insertPage;
} HnswMetaPageData;
typedef HnswMetaPageData * HnswMetaPage;
typedef struct HnswPageOpaqueData
{
BlockNumber nextblkno;
uint16 unused;
uint16 page_id; /* for identification of HNSW indexes */
} HnswPageOpaqueData;
typedef HnswPageOpaqueData * HnswPageOpaque;
typedef struct HnswElementTupleData
{
uint8 type;
uint8 level;
uint8 deleted;
uint8 unused;
ItemPointerData heaptids[HNSW_HEAPTIDS];
ItemPointerData neighbortid;
uint16 unused2;
Vector data;
} HnswElementTupleData;
typedef HnswElementTupleData * HnswElementTuple;
typedef struct HnswNeighborTupleData
{
uint8 type;
uint8 unused;
uint16 count;
ItemPointerData indextids[FLEXIBLE_ARRAY_MEMBER];
} HnswNeighborTupleData;
typedef HnswNeighborTupleData * HnswNeighborTuple;
typedef struct HnswScanOpaqueData
{
bool first;
List *w;
MemoryContext tmpCtx;
/* Support functions */
FmgrInfo **procinfos;
FmgrInfo *normprocinfo;
Oid *collations;
} HnswScanOpaqueData;
typedef HnswScanOpaqueData * HnswScanOpaque;
typedef struct HnswVacuumState
{
/* Info */
Relation index;
IndexBulkDeleteResult *stats;
IndexBulkDeleteCallback callback;
void *callback_state;
/* Settings */
int m;
int efConstruction;
/* Support functions */
FmgrInfo **procinfos;
Oid *collations;
/* Variables */
HTAB *deleted;
BufferAccessStrategy bas;
HnswNeighborTuple ntup;
HnswElementData highestPoint;
/* Memory */
MemoryContext tmpCtx;
} HnswVacuumState;
/* Methods */
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);
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, IndexTuple qtup, ScanKeyData *keyData, List *ep, int ef, int lc, Relation index, FmgrInfo **procinfos, Oid *collations, int m, bool loadVec, HnswElement skipElement, bool inMemory);
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);
HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno);
void HnswInsertElement(HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo **procinfos, Oid *collations, int m, int efConstruction, bool existing, bool inMemory);
HnswElement HnswFindDuplicate(HnswElement e, Relation index);
HnswCandidate *HnswEntryCandidate(HnswElement em, Datum q, IndexTuple qtup, ScanKeyData *keyData, Relation rel, FmgrInfo **procinfos, Oid *collations, bool loadVec, bool inMemory);
void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum);
void HnswSetNeighborTuple(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 **procinfos, Oid *collations, HnswElement e, int m, bool checkExisting);
void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec, Relation index);
void HnswLoadElement(HnswElement element, float *distance, bool *matches, Datum *q, IndexTuple qtup, ScanKeyData *keyData, Relation index, FmgrInfo **procinfos, Oid *collations, bool loadVec);
void HnswSetElementTuple(HnswElementTuple etup, HnswElement element, bool useIndexTuple);
void HnswUpdateConnection(HnswElement element, HnswCandidate * hc, int m, int lc, int *updateIdx, Relation index, FmgrInfo **procinfos, Oid *collations, bool inMemory);
void HnswLoadNeighbors(HnswElement element, Relation index, int m);
void HnswElementSetData(HnswElement element, Relation index, Datum value, Datum *values, bool *isnull);
/* Index access methods */
IndexBuildResult *hnswbuild(Relation heap, Relation index, IndexInfo *indexInfo);
void hnswbuildempty(Relation index);
bool hnswinsert(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heap, IndexUniqueCheck checkUnique
#if PG_VERSION_NUM >= 140000
,bool indexUnchanged
#endif
,IndexInfo *indexInfo
);
IndexBulkDeleteResult *hnswbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats, IndexBulkDeleteCallback callback, void *callback_state);
IndexBulkDeleteResult *hnswvacuumcleanup(IndexVacuumInfo *info, IndexBulkDeleteResult *stats);
IndexScanDesc hnswbeginscan(Relation index, int nkeys, int norderbys);
void hnswrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int norderbys);
bool hnswgettuple(IndexScanDesc scan, ScanDirection dir);
void hnswendscan(IndexScanDesc scan);
FmgrInfo **HnswInitProcinfos(Relation index);
#endif

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#include "postgres.h"
#include <math.h>
#include "catalog/index.h"
#include "hnsw.h"
#include "miscadmin.h"
#include "lib/pairingheap.h"
#include "nodes/pg_list.h"
#include "storage/bufmgr.h"
#include "utils/datum.h"
#include "utils/memutils.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_TUPLES_DONE 0
#endif
#if PG_VERSION_NUM >= 130000
#define CALLBACK_ITEM_POINTER ItemPointer tid
#else
#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
/*
* Create the metapage
*/
static void
CreateMetaPage(HnswBuildState * buildstate)
{
Relation index = buildstate->index;
ForkNumber forkNum = buildstate->forkNum;
Buffer buf;
Page page;
GenericXLogState *state;
HnswMetaPage metap;
buf = HnswNewBuffer(index, forkNum);
HnswInitRegisterPage(index, &buf, &page, &state);
/* Set metapage data */
metap = HnswPageGetMeta(page);
metap->magicNumber = HNSW_MAGIC_NUMBER;
metap->version = HNSW_VERSION;
metap->dimensions = buildstate->dimensions;
metap->m = buildstate->m;
metap->efConstruction = buildstate->efConstruction;
metap->entryBlkno = InvalidBlockNumber;
metap->entryOffno = InvalidOffsetNumber;
metap->entryLevel = -1;
metap->insertPage = InvalidBlockNumber;
((PageHeader) page)->pd_lower =
((char *) metap + sizeof(HnswMetaPageData)) - (char *) page;
HnswCommitBuffer(buf, state);
}
/*
* Add a new page
*/
static void
HnswBuildAppendPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state, ForkNumber forkNum)
{
/* Add a new page */
Buffer newbuf = HnswNewBuffer(index, forkNum);
/* Update previous page */
HnswPageGetOpaque(*page)->nextblkno = BufferGetBlockNumber(newbuf);
/* Commit */
GenericXLogFinish(*state);
UnlockReleaseBuffer(*buf);
/* Can take a while, so ensure we can interrupt */
/* Needs to be called when no buffer locks are held */
LockBuffer(newbuf, BUFFER_LOCK_UNLOCK);
CHECK_FOR_INTERRUPTS();
LockBuffer(newbuf, BUFFER_LOCK_EXCLUSIVE);
/* Prepare new page */
*buf = newbuf;
*state = GenericXLogStart(index);
*page = GenericXLogRegisterBuffer(*state, *buf, GENERIC_XLOG_FULL_IMAGE);
HnswInitPage(*buf, *page);
}
/*
* Create element pages
*/
static void
CreateElementPages(HnswBuildState * buildstate)
{
Relation index = buildstate->index;
ForkNumber forkNum = buildstate->forkNum;
bool useIndexTuple = buildstate->useIndexTuple;
Size etupAllocSize;
Size maxSize;
HnswElementTuple etup;
HnswNeighborTuple ntup;
BlockNumber insertPage;
Buffer buf;
Page page;
GenericXLogState *state;
ListCell *lc;
/* Calculate sizes */
etupAllocSize = BLCKSZ;
maxSize = HNSW_MAX_SIZE;
/* Allocate once */
etup = palloc0(etupAllocSize);
ntup = palloc0(BLCKSZ);
/* Prepare first page */
buf = HnswNewBuffer(index, forkNum);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, GENERIC_XLOG_FULL_IMAGE);
HnswInitPage(buf, page);
foreach(lc, buildstate->elements)
{
HnswElement element = lfirst(lc);
Size etupSize;
Size ntupSize;
Size combinedSize;
/* Zero memory for each element */
MemSet(etup, 0, etupAllocSize);
/* Calculate sizes */
etupSize = HNSW_ELEMENT_TUPLE_SIZE(useIndexTuple ? IndexTupleSize(element->itup) : VARSIZE_ANY(DatumGetPointer(element->value)));
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, buildstate->m);
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
/* Initial size check */
if (etupSize > etupAllocSize)
elog(ERROR, "index tuple too large");
HnswSetElementTuple(etup, element, useIndexTuple);
/* Keep element and neighbors on the same page if possible */
if (PageGetFreeSpace(page) < etupSize || (combinedSize <= maxSize && PageGetFreeSpace(page) < combinedSize))
HnswBuildAppendPage(index, &buf, &page, &state, forkNum);
/* Calculate offsets */
element->blkno = BufferGetBlockNumber(buf);
element->offno = OffsetNumberNext(PageGetMaxOffsetNumber(page));
if (combinedSize <= maxSize)
{
element->neighborPage = element->blkno;
element->neighborOffno = OffsetNumberNext(element->offno);
}
else
{
element->neighborPage = element->blkno + 1;
element->neighborOffno = FirstOffsetNumber;
}
ItemPointerSet(&etup->neighbortid, element->neighborPage, element->neighborOffno);
/* Add element */
if (PageAddItem(page, (Item) etup, etupSize, InvalidOffsetNumber, false, false) != element->offno)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Add new page if needed */
if (PageGetFreeSpace(page) < ntupSize)
HnswBuildAppendPage(index, &buf, &page, &state, forkNum);
/* Add placeholder for neighbors */
if (PageAddItem(page, (Item) ntup, ntupSize, InvalidOffsetNumber, false, false) != element->neighborOffno)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
}
insertPage = BufferGetBlockNumber(buf);
/* Commit */
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
HnswUpdateMetaPage(index, HNSW_UPDATE_ENTRY_ALWAYS, buildstate->entryPoint, insertPage, forkNum);
pfree(etup);
pfree(ntup);
}
/*
* Create neighbor pages
*/
static void
CreateNeighborPages(HnswBuildState * buildstate)
{
Relation index = buildstate->index;
ForkNumber forkNum = buildstate->forkNum;
int m = buildstate->m;
ListCell *lc;
HnswNeighborTuple ntup;
/* Allocate once */
ntup = palloc0(BLCKSZ);
foreach(lc, buildstate->elements)
{
HnswElement e = lfirst(lc);
Buffer buf;
Page page;
GenericXLogState *state;
Size ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
/* Can take a while, so ensure we can interrupt */
/* Needs to be called when no buffer locks are held */
CHECK_FOR_INTERRUPTS();
buf = ReadBufferExtended(index, forkNum, e->neighborPage, RBM_NORMAL, NULL);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
HnswSetNeighborTuple(ntup, e, m);
if (!PageIndexTupleOverwrite(page, e->neighborOffno, (Item) ntup, ntupSize))
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Commit */
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
}
pfree(ntup);
}
/*
* Free elements
*/
static void
FreeElements(HnswBuildState * buildstate)
{
ListCell *lc;
foreach(lc, buildstate->elements)
HnswFreeElement(lfirst(lc));
list_free(buildstate->elements);
}
/*
* Flush pages
*/
static void
FlushPages(HnswBuildState * buildstate)
{
CreateMetaPage(buildstate);
CreateElementPages(buildstate);
CreateNeighborPages(buildstate);
buildstate->flushed = true;
FreeElements(buildstate);
}
/*
* Insert tuple
*/
static bool
InsertTuple(Relation index, Datum *values, bool *isnull, HnswElement element, HnswBuildState * buildstate, HnswElement * dup, MemoryContext outerCtx)
{
FmgrInfo **procinfos = buildstate->procinfos;
Oid *collations = buildstate->collations;
HnswElement entryPoint = buildstate->entryPoint;
int efConstruction = buildstate->efConstruction;
int m = buildstate->m;
bool inMemory = true;
MemoryContext oldCtx;
/* Detoast once for all calls */
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Normalize if needed */
if (buildstate->normprocinfo != NULL)
{
if (!HnswNormValue(buildstate->normprocinfo, collations[0], &value, buildstate->normvec))
return false;
}
/* Copy value to element so accessible outside of memory context */
oldCtx = MemoryContextSwitchTo(outerCtx);
HnswElementSetData(element, index, value, values, isnull);
MemoryContextSwitchTo(oldCtx);
/* Insert element in graph */
HnswInsertElement(element, entryPoint, index, procinfos, collations, m, efConstruction, false, inMemory);
/* Look for duplicate */
*dup = HnswFindDuplicate(element, index);
/* Update neighbors if needed */
if (*dup == NULL)
{
for (int lc = element->level; lc >= 0; lc--)
{
int lm = HnswGetLayerM(m, lc);
HnswNeighborArray *neighbors = &element->neighbors[lc];
for (int i = 0; i < neighbors->length; i++)
HnswUpdateConnection(element, &neighbors->items[i], lm, lc, NULL, index, procinfos, collations, inMemory);
}
}
/* Update entry point if needed */
if (*dup == NULL && (entryPoint == NULL || element->level > entryPoint->level))
buildstate->entryPoint = element;
UpdateProgress(PROGRESS_CREATEIDX_TUPLES_DONE, ++buildstate->indtuples);
return *dup == NULL;
}
/*
* Get the memory used by an element
*/
static long
HnswElementMemory(HnswElement e, int m)
{
long elementSize = sizeof(HnswElementData);
elementSize += sizeof(HnswNeighborArray) * (e->level + 1);
elementSize += sizeof(HnswCandidate) * (m * (e->level + 2));
elementSize += sizeof(ItemPointerData);
elementSize += IndexTupleSize(e->itup);
return elementSize;
}
/*
* Callback for table_index_build_scan
*/
static void
BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
bool *isnull, bool tupleIsAlive, void *state)
{
HnswBuildState *buildstate = (HnswBuildState *) state;
MemoryContext oldCtx;
HnswElement element;
HnswElement dup = NULL;
bool inserted;
#if PG_VERSION_NUM < 130000
ItemPointer tid = &hup->t_self;
#endif
/* Skip nulls */
if (isnull[0])
return;
if (buildstate->memoryLeft <= 0)
{
if (!buildstate->flushed)
{
ereport(NOTICE,
(errmsg("hnsw graph no longer fits into maintenance_work_mem after " INT64_FORMAT " tuples", (int64) buildstate->indtuples),
errdetail("Building will take significantly more time."),
errhint("Increase maintenance_work_mem to speed up builds.")));
FlushPages(buildstate);
}
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
if (HnswInsertTuple(buildstate->index, values, isnull, tid, buildstate->heap))
UpdateProgress(PROGRESS_CREATEIDX_TUPLES_DONE, ++buildstate->indtuples);
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
MemoryContextReset(buildstate->tmpCtx);
return;
}
/* Allocate necessary memory outside of memory context */
element = HnswInitElement(tid, buildstate->m, buildstate->ml, buildstate->maxLevel);
/* Use memory context since detoast can allocate */
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
/* Insert tuple */
inserted = InsertTuple(index, values, isnull, element, buildstate, &dup, oldCtx);
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
MemoryContextReset(buildstate->tmpCtx);
/* Add outside memory context */
if (dup != NULL)
{
HnswAddHeapTid(dup, tid);
buildstate->memoryLeft -= sizeof(ItemPointerData);
}
/* Add to buildstate or free */
if (inserted)
{
buildstate->elements = lappend(buildstate->elements, element);
buildstate->memoryLeft -= HnswElementMemory(element, buildstate->m);
}
else
HnswFreeElement(element);
}
/*
* Initialize the build state
*/
static void
InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum)
{
buildstate->heap = heap;
buildstate->index = index;
buildstate->indexInfo = indexInfo;
buildstate->forkNum = forkNum;
buildstate->m = HnswGetM(index);
buildstate->efConstruction = HnswGetEfConstruction(index);
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
/* TODO See if needed */
if (IndexRelationGetNumberOfKeyAttributes(index) > 2)
elog(ERROR, "index cannot have more than two columns");
if (!OidIsValid(index_getprocid(index, 1, HNSW_DISTANCE_PROC)))
elog(ERROR, "first column must be a vector");
for (int i = 1; i < IndexRelationGetNumberOfKeyAttributes(index); i++)
{
if (!OidIsValid(index_getprocid(index, i + 1, HNSW_ATTRIBUTE_DISTANCE_PROC)))
elog(ERROR, "column %d cannot be a vector", i + 1);
}
/* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0)
elog(ERROR, "column does not have dimensions");
if (buildstate->dimensions > HNSW_MAX_DIM)
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", HNSW_MAX_DIM);
if (buildstate->efConstruction < 2 * buildstate->m)
elog(ERROR, "ef_construction must be greater than or equal to 2 * m");
buildstate->reltuples = 0;
buildstate->indtuples = 0;
/* Get support functions */
buildstate->procinfos = HnswInitProcinfos(index);
buildstate->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
buildstate->collations = index->rd_indcollation;
buildstate->elements = NIL;
buildstate->entryPoint = NULL;
buildstate->ml = HnswGetMl(buildstate->m);
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
buildstate->memoryLeft = maintenance_work_mem * 1024L;
buildstate->flushed = false;
buildstate->useIndexTuple = IndexRelationGetNumberOfAttributes(index) > 1;
/* Reuse for each tuple */
buildstate->normvec = InitVector(buildstate->dimensions);
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw build temporary context",
ALLOCSET_DEFAULT_SIZES);
}
/*
* Free resources
*/
static void
FreeBuildState(HnswBuildState * buildstate)
{
pfree(buildstate->procinfos);
pfree(buildstate->normvec);
MemoryContextDelete(buildstate->tmpCtx);
}
/*
* Build graph
*/
static void
BuildGraph(HnswBuildState * buildstate, ForkNumber forkNum)
{
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_HNSW_PHASE_LOAD);
#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
}
/*
* Build the index
*/
static void
BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
HnswBuildState * buildstate, ForkNumber forkNum)
{
InitBuildState(buildstate, heap, index, indexInfo, forkNum);
if (buildstate->heap != NULL)
BuildGraph(buildstate, forkNum);
if (!buildstate->flushed)
FlushPages(buildstate);
FreeBuildState(buildstate);
}
/*
* Build the index for a logged table
*/
IndexBuildResult *
hnswbuild(Relation heap, Relation index, IndexInfo *indexInfo)
{
IndexBuildResult *result;
HnswBuildState buildstate;
BuildIndex(heap, index, indexInfo, &buildstate, MAIN_FORKNUM);
result = (IndexBuildResult *) palloc(sizeof(IndexBuildResult));
result->heap_tuples = buildstate.reltuples;
result->index_tuples = buildstate.indtuples;
return result;
}
/*
* Build the index for an unlogged table
*/
void
hnswbuildempty(Relation index)
{
IndexInfo *indexInfo = BuildIndexInfo(index);
HnswBuildState buildstate;
BuildIndex(NULL, index, indexInfo, &buildstate, INIT_FORKNUM);
}

585
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#include "postgres.h"
#include <math.h>
#include "hnsw.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
#include "utils/memutils.h"
/*
* Get the insert page
*/
static BlockNumber
GetInsertPage(Relation index)
{
Buffer buf;
Page page;
HnswMetaPage metap;
BlockNumber insertPage;
buf = ReadBuffer(index, HNSW_METAPAGE_BLKNO);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
metap = HnswPageGetMeta(page);
insertPage = metap->insertPage;
UnlockReleaseBuffer(buf);
return insertPage;
}
/*
* 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)
{
OffsetNumber offno;
OffsetNumber maxoffno = PageGetMaxOffsetNumber(page);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
/* Skip neighbor tuples */
if (!HnswIsElementTuple(etup))
continue;
if (etup->deleted)
{
BlockNumber elementPage = BufferGetBlockNumber(buf);
BlockNumber neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
OffsetNumber neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
ItemId itemid;
if (!BlockNumberIsValid(*newInsertPage))
*newInsertPage = elementPage;
if (neighborPage == elementPage)
{
*nbuf = buf;
*npage = page;
}
else
{
*nbuf = ReadBuffer(index, neighborPage);
LockBuffer(*nbuf, BUFFER_LOCK_EXCLUSIVE);
/* Skip WAL for now */
*npage = BufferGetPage(*nbuf);
}
itemid = PageGetItemId(*npage, neighborOffno);
/* Check for space on neighbor tuple page */
if (PageGetFreeSpace(*npage) + ItemIdGetLength(itemid) - sizeof(ItemIdData) >= ntupSize)
{
*freeOffno = offno;
*freeNeighborOffno = neighborOffno;
return true;
}
else if (*nbuf != buf)
UnlockReleaseBuffer(*nbuf);
}
}
return false;
}
/*
* Add a new page
*/
static void
HnswInsertAppendPage(Relation index, Buffer *nbuf, Page *npage, GenericXLogState *state, Page page)
{
/* Add a new page */
LockRelationForExtension(index, ExclusiveLock);
*nbuf = HnswNewBuffer(index, MAIN_FORKNUM);
UnlockRelationForExtension(index, ExclusiveLock);
/* Init new page */
*npage = GenericXLogRegisterBuffer(state, *nbuf, GENERIC_XLOG_FULL_IMAGE);
HnswInitPage(*nbuf, *npage);
/* Update previous buffer */
HnswPageGetOpaque(page)->nextblkno = BufferGetBlockNumber(*nbuf);
}
/*
* Add to element and neighbor pages
*/
static void
WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPage, BlockNumber *updatedInsertPage)
{
Buffer buf;
Page page;
GenericXLogState *state;
Size etupSize;
Size ntupSize;
Size combinedSize;
Size maxSize;
Size minCombinedSize;
HnswElementTuple etup;
BlockNumber currentPage = insertPage;
HnswNeighborTuple ntup;
Buffer nbuf;
Page npage;
OffsetNumber freeOffno = InvalidOffsetNumber;
OffsetNumber freeNeighborOffno = InvalidOffsetNumber;
BlockNumber newInsertPage = InvalidBlockNumber;
bool useIndexTuple = IndexRelationGetNumberOfAttributes(index) > 1;
/* Calculate sizes */
etupSize = HNSW_ELEMENT_TUPLE_SIZE(useIndexTuple ? IndexTupleSize(e->itup) : VARSIZE_ANY(DatumGetPointer(e->value)));
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
maxSize = HNSW_MAX_SIZE;
minCombinedSize = etupSize + HNSW_NEIGHBOR_TUPLE_SIZE(0, m) + sizeof(ItemIdData);
/* Prepare element tuple */
etup = palloc0(etupSize);
HnswSetElementTuple(etup, e, useIndexTuple);
/* Prepare neighbor tuple */
ntup = palloc0(ntupSize);
HnswSetNeighborTuple(ntup, e, m);
/* Find a page (or two if needed) to insert the tuples */
for (;;)
{
buf = ReadBuffer(index, currentPage);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
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)
newInsertPage = currentPage;
/* First, try the fastest path */
/* Space for both tuples on the current page */
/* This can split existing tuples in rare cases */
if (PageGetFreeSpace(page) >= combinedSize)
{
nbuf = buf;
npage = page;
break;
}
/* Next, try space from a deleted element */
if (HnswFreeOffset(index, buf, page, e, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage))
{
if (nbuf != buf)
npage = GenericXLogRegisterBuffer(state, nbuf, 0);
break;
}
/* Finally, try space for element only if last page */
/* 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);
break;
}
currentPage = HnswPageGetOpaque(page)->nextblkno;
if (BlockNumberIsValid(currentPage))
{
/* Move to next page */
GenericXLogAbort(state);
UnlockReleaseBuffer(buf);
}
else
{
Buffer newbuf;
Page newpage;
HnswInsertAppendPage(index, &newbuf, &newpage, state, page);
/* Commit */
GenericXLogFinish(state);
/* Unlock previous buffer */
UnlockReleaseBuffer(buf);
/* Prepare new buffer */
state = GenericXLogStart(index);
buf = newbuf;
page = GenericXLogRegisterBuffer(state, buf, 0);
/* Create new page for neighbors if needed */
if (PageGetFreeSpace(page) < combinedSize)
HnswInsertAppendPage(index, &nbuf, &npage, state, page);
else
{
nbuf = buf;
npage = page;
}
break;
}
}
e->blkno = BufferGetBlockNumber(buf);
e->neighborPage = BufferGetBlockNumber(nbuf);
/* Added tuple to new page if newInsertPage is not set */
/* So can set to neighbor page instead of element page */
if (!BlockNumberIsValid(newInsertPage))
newInsertPage = e->neighborPage;
if (OffsetNumberIsValid(freeOffno))
{
e->offno = freeOffno;
e->neighborOffno = freeNeighborOffno;
}
else
{
e->offno = OffsetNumberNext(PageGetMaxOffsetNumber(page));
if (nbuf == buf)
e->neighborOffno = OffsetNumberNext(e->offno);
else
e->neighborOffno = FirstOffsetNumber;
}
ItemPointerSet(&etup->neighbortid, e->neighborPage, e->neighborOffno);
/* Add element and neighbors */
if (OffsetNumberIsValid(freeOffno))
{
if (!PageIndexTupleOverwrite(page, e->offno, (Item) etup, etupSize))
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
if (!PageIndexTupleOverwrite(npage, e->neighborOffno, (Item) ntup, ntupSize))
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
}
else
{
if (PageAddItem(page, (Item) etup, etupSize, InvalidOffsetNumber, false, false) != e->offno)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
if (PageAddItem(npage, (Item) ntup, ntupSize, InvalidOffsetNumber, false, false) != e->neighborOffno)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
}
/* Commit */
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
if (nbuf != buf)
UnlockReleaseBuffer(nbuf);
/* Update the insert page */
if (BlockNumberIsValid(newInsertPage) && newInsertPage != insertPage)
*updatedInsertPage = newInsertPage;
}
/*
* Check if connection already exists
*/
static bool
ConnectionExists(HnswElement e, HnswNeighborTuple ntup, int startIdx, int lm)
{
for (int i = 0; i < lm; i++)
{
ItemPointer indextid = &ntup->indextids[startIdx + i];
if (!ItemPointerIsValid(indextid))
break;
if (ItemPointerGetBlockNumber(indextid) == e->blkno && ItemPointerGetOffsetNumber(indextid) == e->offno)
return true;
}
return false;
}
/*
* Update neighbors
*/
void
HnswUpdateNeighborPages(Relation index, FmgrInfo **procinfos, Oid *collations, HnswElement e, int m, bool checkExisting)
{
for (int lc = e->level; lc >= 0; lc--)
{
int lm = HnswGetLayerM(m, lc);
HnswNeighborArray *neighbors = &e->neighbors[lc];
for (int i = 0; i < neighbors->length; i++)
{
HnswCandidate *hc = &neighbors->items[i];
Buffer buf;
Page page;
GenericXLogState *state;
ItemId itemid;
HnswNeighborTuple ntup;
Size ntupSize;
int idx = -1;
int startIdx;
OffsetNumber offno = hc->element->neighborOffno;
/* Get latest neighbors since they may have changed */
/* Do not lock yet since selecting neighbors can take time */
HnswLoadNeighbors(hc->element, index, m);
/*
* Could improve performance for vacuuming by checking neighbors
* against list of elements being deleted to find index. It's
* important to exclude already deleted elements for this since
* they can be replaced at any time.
*/
/* Select neighbors */
HnswUpdateConnection(e, hc, lm, lc, &idx, index, procinfos, collations, false);
/* New element was not selected as a neighbor */
if (idx == -1)
continue;
/* Register page */
buf = ReadBuffer(index, hc->element->neighborPage);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
/* Get tuple */
itemid = PageGetItemId(page, offno);
ntup = (HnswNeighborTuple) PageGetItem(page, itemid);
ntupSize = ItemIdGetLength(itemid);
/* Calculate index for update */
startIdx = (hc->element->level - lc) * m;
/* Check for existing connection */
if (checkExisting && ConnectionExists(e, ntup, startIdx, lm))
idx = -1;
else if (idx == -2)
{
/* Find free offset if still exists */
/* TODO Retry updating connections if not */
for (int j = 0; j < lm; j++)
{
if (!ItemPointerIsValid(&ntup->indextids[startIdx + j]))
{
idx = startIdx + j;
break;
}
}
}
else
idx += startIdx;
/* Make robust to issues */
if (idx >= 0 && idx < ntup->count)
{
ItemPointer indextid = &ntup->indextids[idx];
/* Update neighbor */
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);
}
else
GenericXLogAbort(state);
UnlockReleaseBuffer(buf);
}
}
}
/*
* Add a heap TID to an existing element
*/
static bool
HnswAddDuplicate(Relation index, HnswElement element, HnswElement dup)
{
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);
/* Find space */
itemid = PageGetItemId(page, dup->offno);
etup = (HnswElementTuple) PageGetItem(page, itemid);
etupSize = ItemIdGetLength(itemid);
for (i = 0; i < HNSW_HEAPTIDS; i++)
{
if (!ItemPointerIsValid(&etup->heaptids[i]))
break;
}
/* Either being deleted or we lost our chance to another backend */
if (i == 0 || i == HNSW_HEAPTIDS)
{
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));
/* Commit */
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
return true;
}
/*
* Write changes to disk
*/
static void
WriteElement(Relation index, FmgrInfo **procinfos, Oid *collations, HnswElement element, int m, int efConstruction, HnswElement dup, HnswElement entryPoint)
{
BlockNumber newInsertPage = InvalidBlockNumber;
/* Try to add to existing page */
if (dup != NULL)
{
if (HnswAddDuplicate(index, element, dup))
return;
}
/* Write element and neighbor tuples */
WriteNewElementPages(index, element, m, GetInsertPage(index), &newInsertPage);
/* Update insert page if needed */
if (BlockNumberIsValid(newInsertPage))
HnswUpdateMetaPage(index, 0, NULL, newInsertPage, MAIN_FORKNUM);
/* Update neighbors */
HnswUpdateNeighborPages(index, procinfos, collations, element, m, false);
/* Update metapage if needed */
if (entryPoint == NULL || element->level > entryPoint->level)
HnswUpdateMetaPage(index, HNSW_UPDATE_ENTRY_GREATER, element, InvalidBlockNumber, MAIN_FORKNUM);
}
/*
* Insert a tuple into the index
*/
bool
HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
{
Datum value;
FmgrInfo *normprocinfo;
HnswElement entryPoint;
HnswElement element;
int m;
int efConstruction = HnswGetEfConstruction(index);
FmgrInfo **procinfos = HnswInitProcinfos(index);
Oid *collations = index->rd_indcollation;
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, collations[0], &value, NULL))
return false;
}
/*
* Get a shared lock. This allows vacuum to ensure no in-flight inserts
* before repairing graph. Use a page lock so it does not interfere with
* buffer lock (or reads when vacuuming).
*/
LockPage(index, HNSW_UPDATE_LOCK, lockmode);
/* Get m and entry point */
HnswGetMetaPageInfo(index, &m, &entryPoint);
/* Create an element */
element = HnswInitElement(heap_tid, m, HnswGetMl(m), HnswGetMaxLevel(m));
HnswElementSetData(element, index, value, values, isnull);
/* Prevent concurrent inserts when likely updating entry point */
if (entryPoint == NULL || element->level > entryPoint->level)
{
/* Release shared lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
/* Get exclusive lock */
lockmode = ExclusiveLock;
LockPage(index, HNSW_UPDATE_LOCK, lockmode);
/* Get latest entry point after lock is acquired */
entryPoint = HnswGetEntryPoint(index);
}
/* Insert element in graph */
HnswInsertElement(element, entryPoint, index, procinfos, collations, m, efConstruction, false, false);
/* Look for duplicate */
dup = HnswFindDuplicate(element, index);
/* Write to disk */
WriteElement(index, procinfos, collations, element, m, efConstruction, dup, entryPoint);
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
return true;
}
/*
* Insert a tuple into the index
*/
bool
hnswinsert(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid,
Relation heap, IndexUniqueCheck checkUnique
#if PG_VERSION_NUM >= 140000
,bool indexUnchanged
#endif
,IndexInfo *indexInfo
)
{
MemoryContext oldCtx;
MemoryContext insertCtx;
/* Skip nulls */
if (isnull[0])
return false;
/* Create memory context */
insertCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw insert temporary context",
ALLOCSET_DEFAULT_SIZES);
oldCtx = MemoryContextSwitchTo(insertCtx);
/* Insert tuple */
HnswInsertTuple(index, values, isnull, heap_tid, heap);
/* Delete memory context */
MemoryContextSwitchTo(oldCtx);
MemoryContextDelete(insertCtx);
return false;
}

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#include "postgres.h"
#include "access/relscan.h"
#include "hnsw.h"
#include "pgstat.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
#include "utils/memutils.h"
/*
* Algorithm 5 from paper
*/
static List *
GetScanItems(IndexScanDesc scan, Datum q)
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
Relation index = scan->indexRelation;
FmgrInfo **procinfos = so->procinfos;
Oid *collations = so->collations;
List *ep;
List *w;
int m;
HnswElement entryPoint;
ScanKeyData *keyData = scan->keyData;
/* Get m and entry point */
HnswGetMetaPageInfo(index, &m, &entryPoint);
if (entryPoint == NULL)
return NIL;
ep = list_make1(HnswEntryCandidate(entryPoint, q, NULL, keyData, index, procinfos, collations, false, false));
for (int lc = entryPoint->level; lc >= 1; lc--)
{
w = HnswSearchLayer(q, NULL, keyData, ep, 1, lc, index, procinfos, collations, m, false, NULL, false);
ep = w;
}
return HnswSearchLayer(q, NULL, keyData, ep, hnsw_ef_search, 0, index, procinfos, collations, m, false, NULL, false);
}
/*
* 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;
}
/*
* Get scan value
*/
static Datum
GetScanValue(IndexScanDesc scan)
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
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)
HnswNormValue(so->normprocinfo, so->collations[0], &value, NULL);
}
return value;
}
/*
* Prepare for an index scan
*/
IndexScanDesc
hnswbeginscan(Relation index, int nkeys, int norderbys)
{
IndexScanDesc scan;
HnswScanOpaque so;
scan = RelationGetIndexScan(index, nkeys, norderbys);
so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData));
so->first = true;
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw scan temporary context",
ALLOCSET_DEFAULT_SIZES);
/* Set support functions */
so->procinfos = HnswInitProcinfos(index);
so->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
so->collations = index->rd_indcollation;
scan->opaque = so;
return scan;
}
/*
* Start or restart an index scan
*/
void
hnswrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int norderbys)
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
so->first = true;
MemoryContextReset(so->tmpCtx);
if (keys && scan->numberOfKeys > 0)
memmove(scan->keyData, keys, scan->numberOfKeys * sizeof(ScanKeyData));
if (orderbys && scan->numberOfOrderBys > 0)
memmove(scan->orderByData, orderbys, scan->numberOfOrderBys * sizeof(ScanKeyData));
}
/*
* Fetch the next tuple in the given scan
*/
bool
hnswgettuple(IndexScanDesc scan, ScanDirection dir)
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
MemoryContext oldCtx = MemoryContextSwitchTo(so->tmpCtx);
/*
* Index can be used to scan backward, but Postgres doesn't support
* backward scan on operators
*/
Assert(ScanDirectionIsForward(dir));
if (so->first)
{
Datum value;
/* Count index scan for stats */
pgstat_count_index_scan(scan->indexRelation);
/* Safety check */
if (scan->orderByData == NULL)
elog(ERROR, "cannot scan hnsw index without order");
/* Requires MVCC-compliant snapshot as not able to maintain a pin */
/* https://www.postgresql.org/docs/current/index-locking.html */
if (!IsMVCCSnapshot(scan->xs_snapshot))
elog(ERROR, "non-MVCC snapshots are not supported with hnsw");
/* Get scan value */
value = GetScanValue(scan);
/*
* Get a shared lock. This allows vacuum to ensure no in-flight scans
* before marking tuples as deleted.
*/
LockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
so->w = GetScanItems(scan, value);
/* Release shared lock */
UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
so->first = false;
}
while (list_length(so->w) > 0)
{
HnswCandidate *hc = llast(so->w);
ItemPointer heaptid;
/* Move to next element if no valid heap TIDs */
if (list_length(hc->element->heaptids) == 0)
{
so->w = list_delete_last(so->w);
continue;
}
heaptid = llast(hc->element->heaptids);
hc->element->heaptids = list_delete_last(hc->element->heaptids);
MemoryContextSwitchTo(oldCtx);
#if PG_VERSION_NUM >= 120000
scan->xs_heaptid = *heaptid;
#else
scan->xs_ctup.t_self = *heaptid;
#endif
/* TODO Check during scan */
scan->xs_recheck = scan->numberOfKeys > 0;
scan->xs_recheckorderby = false;
return true;
}
MemoryContextSwitchTo(oldCtx);
return false;
}
/*
* End a scan and release resources
*/
void
hnswendscan(IndexScanDesc scan)
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
pfree(so->procinfos);
MemoryContextDelete(so->tmpCtx);
pfree(so);
scan->opaque = NULL;
}

1286
src/hnswutils.c Normal file

File diff suppressed because it is too large Load Diff

675
src/hnswvacuum.c Normal file
View File

@@ -0,0 +1,675 @@
#include "postgres.h"
#include <math.h>
#include "commands/vacuum.h"
#include "hnsw.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
#include "utils/memutils.h"
/*
* Check if deleted list contains an index TID
*/
static bool
DeletedContains(HTAB *deleted, ItemPointer indextid)
{
bool found;
hash_search(deleted, indextid, HASH_FIND, &found);
return found;
}
/*
* Remove deleted heap TIDs
*
* OK to remove for entry point, since always considered for searches and inserts
*/
static void
RemoveHeapTids(HnswVacuumState * vacuumstate)
{
BlockNumber blkno = HNSW_HEAD_BLKNO;
HnswElement highestPoint = &vacuumstate->highestPoint;
Relation index = vacuumstate->index;
BufferAccessStrategy bas = vacuumstate->bas;
HnswElement entryPoint = HnswGetEntryPoint(vacuumstate->index);
IndexBulkDeleteResult *stats = vacuumstate->stats;
/* Store separately since highestPoint.level is uint8 */
int highestLevel = -1;
/* Initialize highest point */
highestPoint->blkno = InvalidBlockNumber;
highestPoint->offno = InvalidOffsetNumber;
while (BlockNumberIsValid(blkno))
{
Buffer buf;
Page page;
GenericXLogState *state;
OffsetNumber offno;
OffsetNumber maxoffno;
bool updated = false;
vacuum_delay_point();
buf = ReadBufferExtended(index, MAIN_FORKNUM, blkno, RBM_NORMAL, bas);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
maxoffno = PageGetMaxOffsetNumber(page);
/* Iterate over nodes */
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
ItemId itemid = PageGetItemId(page, offno);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, itemid);
int idx = 0;
bool itemUpdated = false;
/* Skip neighbor tuples */
if (!HnswIsElementTuple(etup))
continue;
if (ItemPointerIsValid(&etup->heaptids[0]))
{
for (int i = 0; i < HNSW_HEAPTIDS; i++)
{
/* Stop at first unused */
if (!ItemPointerIsValid(&etup->heaptids[i]))
break;
if (vacuumstate->callback(&etup->heaptids[i], vacuumstate->callback_state))
{
itemUpdated = true;
stats->tuples_removed++;
}
else
{
/* Move to front of list */
etup->heaptids[idx++] = etup->heaptids[i];
stats->num_index_tuples++;
}
}
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;
}
}
if (!ItemPointerIsValid(&etup->heaptids[0]))
{
ItemPointerData ip;
/* Add to deleted list */
ItemPointerSet(&ip, blkno, offno);
(void) hash_search(vacuumstate->deleted, &ip, HASH_ENTER, NULL);
}
else if (etup->level > highestLevel && !(entryPoint != NULL && blkno == entryPoint->blkno && offno == entryPoint->offno))
{
/* Keep track of highest non-entry point */
highestPoint->blkno = blkno;
highestPoint->offno = offno;
highestPoint->level = etup->level;
highestLevel = etup->level;
}
}
blkno = HnswPageGetOpaque(page)->nextblkno;
if (updated)
GenericXLogFinish(state);
else
GenericXLogAbort(state);
UnlockReleaseBuffer(buf);
}
}
/*
* Check for deleted neighbors
*/
static bool
NeedsUpdated(HnswVacuumState * vacuumstate, HnswElement element)
{
Relation index = vacuumstate->index;
BufferAccessStrategy bas = vacuumstate->bas;
Buffer buf;
Page page;
HnswNeighborTuple ntup;
bool needsUpdated = false;
buf = ReadBufferExtended(index, MAIN_FORKNUM, element->neighborPage, RBM_NORMAL, bas);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, element->neighborOffno));
Assert(HnswIsNeighborTuple(ntup));
/* Check neighbors */
for (int i = 0; i < ntup->count; i++)
{
ItemPointer indextid = &ntup->indextids[i];
if (!ItemPointerIsValid(indextid))
continue;
/* Check if in deleted list */
if (DeletedContains(vacuumstate->deleted, indextid))
{
needsUpdated = true;
break;
}
}
/* Also update if layer 0 is not full */
/* This could indicate too many candidates being deleted during insert */
if (!needsUpdated)
needsUpdated = !ItemPointerIsValid(&ntup->indextids[ntup->count - 1]);
UnlockReleaseBuffer(buf);
return needsUpdated;
}
/*
* Repair graph for a single element
*/
static void
RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswElement entryPoint)
{
Relation index = vacuumstate->index;
Buffer buf;
Page page;
GenericXLogState *state;
int m = vacuumstate->m;
int efConstruction = vacuumstate->efConstruction;
FmgrInfo **procinfos = vacuumstate->procinfos;
Oid *collations = vacuumstate->collations;
BufferAccessStrategy bas = vacuumstate->bas;
HnswNeighborTuple ntup = vacuumstate->ntup;
Size ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, m);
/* 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;
/* Add element to graph, skipping itself */
HnswInsertElement(element, entryPoint, index, procinfos, collations, m, efConstruction, true, false);
/* Update neighbor tuple */
/* Do this before getting page to minimize locking */
HnswSetNeighborTuple(ntup, element, m);
/* Get neighbor page */
buf = ReadBufferExtended(index, MAIN_FORKNUM, element->neighborPage, RBM_NORMAL, bas);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
/* Overwrite tuple */
if (!PageIndexTupleOverwrite(page, element->neighborOffno, (Item) ntup, ntupSize))
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Commit */
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
/* Update neighbors */
HnswUpdateNeighborPages(index, procinfos, collations, element, m, true);
}
/*
* Repair graph entry point
*/
static void
RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
{
Relation index = vacuumstate->index;
HnswElement highestPoint = &vacuumstate->highestPoint;
HnswElement entryPoint;
MemoryContext oldCtx = MemoryContextSwitchTo(vacuumstate->tmpCtx);
if (!BlockNumberIsValid(highestPoint->blkno))
highestPoint = NULL;
/*
* Repair graph for highest non-entry point. Highest point may be outdated
* due to inserts that happen during and after RemoveHeapTids.
*/
if (highestPoint != NULL)
{
/* Get a shared lock */
LockPage(index, HNSW_UPDATE_LOCK, ShareLock);
/* Load element */
HnswLoadElement(highestPoint, NULL, NULL, NULL, NULL, NULL, index, vacuumstate->procinfos, vacuumstate->collations, true);
/* Repair if needed */
if (NeedsUpdated(vacuumstate, highestPoint))
RepairGraphElement(vacuumstate, highestPoint, HnswGetEntryPoint(index));
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, ShareLock);
}
/* Prevent concurrent inserts when possibly updating entry point */
LockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
/* Get latest entry point */
entryPoint = HnswGetEntryPoint(index);
if (entryPoint != NULL)
{
ItemPointerData epData;
ItemPointerSet(&epData, entryPoint->blkno, entryPoint->offno);
if (DeletedContains(vacuumstate->deleted, &epData))
{
/*
* Replace the entry point with the highest point. If highest
* 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);
}
else
{
/*
* Repair the entry point with the highest point. If highest point
* 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, NULL, NULL, NULL, index, vacuumstate->procinfos, vacuumstate->collations, true);
if (NeedsUpdated(vacuumstate, entryPoint))
{
/* Reset neighbors from previous update */
if (highestPoint != NULL)
highestPoint->neighbors = NULL;
RepairGraphElement(vacuumstate, entryPoint, highestPoint);
}
}
}
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
MemoryContextReset(vacuumstate->tmpCtx);
}
/*
* Repair graph for all elements
*/
static void
RepairGraph(HnswVacuumState * vacuumstate)
{
Relation index = vacuumstate->index;
BufferAccessStrategy bas = vacuumstate->bas;
BlockNumber blkno = HNSW_HEAD_BLKNO;
/*
* Wait for inserts to complete. Inserts before this point may have
* neighbors about to be deleted. Inserts after this point will not.
*/
LockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
UnlockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
/* Repair entry point first */
RepairGraphEntryPoint(vacuumstate);
while (BlockNumberIsValid(blkno))
{
Buffer buf;
Page page;
OffsetNumber offno;
OffsetNumber maxoffno;
List *elements = NIL;
ListCell *lc2;
MemoryContext oldCtx;
vacuum_delay_point();
oldCtx = MemoryContextSwitchTo(vacuumstate->tmpCtx);
buf = ReadBufferExtended(index, MAIN_FORKNUM, blkno, RBM_NORMAL, bas);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
maxoffno = PageGetMaxOffsetNumber(page);
/* Load items into memory to minimize locking */
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
HnswElement element;
/* Skip neighbor tuples */
if (!HnswIsElementTuple(etup))
continue;
/* Skip updating neighbors if being deleted */
if (!ItemPointerIsValid(&etup->heaptids[0]))
continue;
/* Create an element */
element = HnswInitElementFromBlock(blkno, offno);
HnswLoadElementFromTuple(element, etup, false, true, index);
elements = lappend(elements, element);
}
blkno = HnswPageGetOpaque(page)->nextblkno;
UnlockReleaseBuffer(buf);
/* Update neighbor pages */
foreach(lc2, elements)
{
HnswElement element = (HnswElement) lfirst(lc2);
HnswElement entryPoint;
LOCKMODE lockmode = ShareLock;
/* Check if any neighbors point to deleted values */
if (!NeedsUpdated(vacuumstate, element))
continue;
/* Get a shared lock */
LockPage(index, HNSW_UPDATE_LOCK, lockmode);
/* Refresh entry point for each element */
entryPoint = HnswGetEntryPoint(index);
/* Prevent concurrent inserts when likely updating entry point */
if (entryPoint == NULL || element->level > entryPoint->level)
{
/* Release shared lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
/* Get exclusive lock */
lockmode = ExclusiveLock;
LockPage(index, HNSW_UPDATE_LOCK, lockmode);
/* Get latest entry point after lock is acquired */
entryPoint = HnswGetEntryPoint(index);
}
/* Repair connections */
RepairGraphElement(vacuumstate, element, entryPoint);
/*
* Update metapage if needed. Should only happen if entry point
* was replaced and highest point was outdated.
*/
if (entryPoint == NULL || element->level > entryPoint->level)
HnswUpdateMetaPage(index, HNSW_UPDATE_ENTRY_GREATER, element, InvalidBlockNumber, MAIN_FORKNUM);
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
}
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
MemoryContextReset(vacuumstate->tmpCtx);
}
}
/*
* Mark items as deleted
*/
static void
MarkDeleted(HnswVacuumState * vacuumstate)
{
BlockNumber blkno = HNSW_HEAD_BLKNO;
BlockNumber insertPage = InvalidBlockNumber;
Relation index = vacuumstate->index;
BufferAccessStrategy bas = vacuumstate->bas;
bool useIndexTuple = IndexRelationGetNumberOfAttributes(index) > 1;
/*
* Wait for index scans to complete. Scans before this point may contain
* tuples about to be deleted. Scans after this point will not, since the
* graph has been repaired.
*/
LockPage(index, HNSW_SCAN_LOCK, ExclusiveLock);
UnlockPage(index, HNSW_SCAN_LOCK, ExclusiveLock);
while (BlockNumberIsValid(blkno))
{
Buffer buf;
Page page;
GenericXLogState *state;
OffsetNumber offno;
OffsetNumber maxoffno;
vacuum_delay_point();
buf = ReadBufferExtended(index, MAIN_FORKNUM, blkno, RBM_NORMAL, bas);
/*
* ambulkdelete cannot delete entries from pages that are pinned by
* other backends
*
* https://www.postgresql.org/docs/current/index-locking.html
*/
LockBufferForCleanup(buf);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
maxoffno = PageGetMaxOffsetNumber(page);
/* Update element and neighbors together */
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
ItemId itemid = PageGetItemId(page, offno);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, itemid);
HnswNeighborTuple ntup;
Size etupSize;
Size ntupSize;
Buffer nbuf;
Page npage;
BlockNumber neighborPage;
OffsetNumber neighborOffno;
/* Skip neighbor tuples */
if (!HnswIsElementTuple(etup))
continue;
/* Skip deleted tuples */
if (etup->deleted)
{
/* Set to first free page */
if (!BlockNumberIsValid(insertPage))
insertPage = blkno;
continue;
}
/* Skip live tuples */
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);
if (neighborPage == blkno)
{
nbuf = buf;
npage = page;
}
else
{
nbuf = ReadBufferExtended(index, MAIN_FORKNUM, neighborPage, RBM_NORMAL, bas);
LockBuffer(nbuf, BUFFER_LOCK_EXCLUSIVE);
npage = GenericXLogRegisterBuffer(state, nbuf, 0);
}
ntup = (HnswNeighborTuple) PageGetItem(npage, PageGetItemId(npage, neighborOffno));
/* Overwrite element */
etup->deleted = 1;
if (useIndexTuple)
{
IndexTuple itup = (IndexTuple) &etup->data;
MemSet(itup, 0, IndexTupleSize(itup));
}
else
{
Vector *vec = (Vector *) (&etup->data);
MemSet(vec, 0, VARSIZE_ANY(vec));
}
/* Overwrite neighbors */
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));
/* Commit */
GenericXLogFinish(state);
if (nbuf != buf)
UnlockReleaseBuffer(nbuf);
/* Set to first free page */
if (!BlockNumberIsValid(insertPage))
insertPage = blkno;
/* Prepare new xlog */
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
}
blkno = HnswPageGetOpaque(page)->nextblkno;
GenericXLogAbort(state);
UnlockReleaseBuffer(buf);
}
/* Update insert page last, after everything has been marked as deleted */
HnswUpdateMetaPage(index, 0, NULL, insertPage, MAIN_FORKNUM);
}
/*
* Initialize the vacuum state
*/
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));
vacuumstate->index = index;
vacuumstate->stats = stats;
vacuumstate->callback = callback;
vacuumstate->callback_state = callback_state;
vacuumstate->efConstruction = HnswGetEfConstruction(index);
vacuumstate->bas = GetAccessStrategy(BAS_BULKREAD);
vacuumstate->procinfos = HnswInitProcinfos(index);
vacuumstate->collations = index->rd_indcollation;
vacuumstate->ntup = palloc0(BLCKSZ);
vacuumstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw vacuum temporary context",
ALLOCSET_DEFAULT_SIZES);
/* Get m from metapage */
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);
}
/*
* Free resources
*/
static void
FreeVacuumState(HnswVacuumState * vacuumstate)
{
hash_destroy(vacuumstate->deleted);
FreeAccessStrategy(vacuumstate->bas);
pfree(vacuumstate->procinfos);
pfree(vacuumstate->ntup);
MemoryContextDelete(vacuumstate->tmpCtx);
}
/*
* Bulk delete tuples from the index
*/
IndexBulkDeleteResult *
hnswbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
IndexBulkDeleteCallback callback, void *callback_state)
{
HnswVacuumState vacuumstate;
InitVacuumState(&vacuumstate, info, stats, callback, callback_state);
/* Pass 1: Remove heap TIDs */
RemoveHeapTids(&vacuumstate);
/* Pass 2: Repair graph */
RepairGraph(&vacuumstate);
/* Pass 3: Mark as deleted */
MarkDeleted(&vacuumstate);
FreeVacuumState(&vacuumstate);
return vacuumstate.stats;
}
/*
* Clean up after a VACUUM operation
*/
IndexBulkDeleteResult *
hnswvacuumcleanup(IndexVacuumInfo *info, IndexBulkDeleteResult *stats)
{
Relation rel = info->index;
if (info->analyze_only)
return stats;
/* stats is NULL if ambulkdelete not called */
/* OK to return NULL if index not changed */
if (stats == NULL)
return NULL;
stats->num_pages = RelationGetNumberOfBlocks(rel);
return stats;
}

View File

@@ -2,10 +2,15 @@
#include <float.h>
#include "access/parallel.h"
#include "access/xact.h"
#include "catalog/index.h"
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "storage/bufmgr.h"
#include "tcop/tcopprot.h"
#include "utils/memutils.h"
#if PG_VERSION_NUM >= 140000
@@ -23,9 +28,6 @@
#define PROGRESS_CREATEIDX_TUPLES_DONE 0
#endif
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
#if PG_VERSION_NUM >= 130000
#define CALLBACK_ITEM_POINTER ItemPointer tid
#else
@@ -38,6 +40,25 @@
#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)
#define PARALLEL_KEY_QUERY_TEXT UINT64CONST(0xA000000000000004)
/*
* Add sample
*/
@@ -147,10 +168,9 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
{
double distance;
double minDistance = DBL_MAX;
int closestCenter = -1;
int closestCenter = 0;
VectorArray centers = buildstate->centers;
TupleTableSlot *slot = buildstate->slot;
int i;
/* Detoast once for all calls */
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
@@ -163,7 +183,7 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
}
/* Find the list that minimizes the distance */
for (i = 0; i < centers->length; i++)
for (int i = 0; i < centers->length; i++)
{
distance = DatumGetFloat8(FunctionCall2Coll(buildstate->procinfo, buildstate->collation, value, PointerGetDatum(VectorArrayGet(centers, i))));
@@ -258,15 +278,8 @@ GetNextTuple(Tuplesortstate *sortstate, TupleDesc tupdesc, TupleTableSlot *slot,
static void
InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
{
Buffer buf;
Page page;
GenericXLogState *state;
int list;
IndexTuple itup = NULL; /* silence compiler warning */
BlockNumber startPage;
BlockNumber insertPage;
Size itemsz;
int i;
int64 inserted = 0;
#if PG_VERSION_NUM >= 120000
@@ -282,8 +295,14 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
GetNextTuple(buildstate->sortstate, tupdesc, slot, &itup, &list);
for (i = 0; i < buildstate->centers->length; i++)
for (int i = 0; i < buildstate->centers->length; i++)
{
Buffer buf;
Page page;
GenericXLogState *state;
BlockNumber startPage;
BlockNumber insertPage;
/* Can take a while, so ensure we can interrupt */
/* Needs to be called when no buffer locks are held */
CHECK_FOR_INTERRUPTS();
@@ -297,7 +316,8 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
while (list == i)
{
/* Check for free space */
itemsz = MAXALIGN(IndexTupleSize(itup));
Size itemsz = MAXALIGN(IndexTupleSize(itup));
if (PageGetFreeSpace(page) < itemsz)
IvfflatAppendPage(index, &buf, &page, &state, forkNum);
@@ -317,7 +337,7 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
IvfflatCommitBuffer(buf, state);
/* Set the start and insert pages */
IvfflatUpdateList(index, state, buildstate->listInfo[i], insertPage, InvalidBlockNumber, startPage, forkNum);
IvfflatUpdateList(index, buildstate->listInfo[i], insertPage, InvalidBlockNumber, startPage, forkNum);
}
}
@@ -351,9 +371,7 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->collation = index->rd_indcollation[0];
/* Require more than one dimension for spherical k-means */
/* Lists check for backwards compatibility */
/* TODO Remove lists check in 0.3.0 */
if (buildstate->kmeansnormprocinfo != NULL && buildstate->dimensions == 1 && buildstate->lists > 1)
if (buildstate->kmeansnormprocinfo != NULL && buildstate->dimensions == 1)
elog(ERROR, "dimensions must be greater than one for this opclass");
/* Create tuple description for sorting */
@@ -387,6 +405,8 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->listSums = palloc0(sizeof(double) * buildstate->lists);
buildstate->listCounts = palloc0(sizeof(int) * buildstate->lists);
#endif
buildstate->ivfleader = NULL;
}
/*
@@ -431,8 +451,18 @@ ComputeCenters(IvfflatBuildState * buildstate)
/* TODO Ensure within maintenance_work_mem */
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions);
if (buildstate->heap != NULL)
{
SampleRows(buildstate);
if (buildstate->samples->length < buildstate->lists)
{
ereport(NOTICE,
(errmsg("ivfflat index created with little data"),
errdetail("This will cause low recall."),
errhint("Drop the index until the table has more data.")));
}
}
/* Calculate centers */
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers));
@@ -473,33 +503,33 @@ static void
CreateListPages(Relation index, VectorArray centers, int dimensions,
int lists, ForkNumber forkNum, ListInfo * *listInfo)
{
int i;
Buffer buf;
Page page;
GenericXLogState *state;
OffsetNumber offno;
Size itemsz;
Size listSize;
IvfflatList list;
itemsz = MAXALIGN(IVFFLAT_LIST_SIZE(dimensions));
list = palloc(itemsz);
listSize = MAXALIGN(IVFFLAT_LIST_SIZE(dimensions));
list = palloc(listSize);
buf = IvfflatNewBuffer(index, forkNum);
IvfflatInitRegisterPage(index, &buf, &page, &state);
for (i = 0; i < lists; i++)
for (int i = 0; i < lists; i++)
{
OffsetNumber offno;
/* Load list */
list->startPage = InvalidBlockNumber;
list->insertPage = InvalidBlockNumber;
memcpy(&list->center, VectorArrayGet(centers, i), VECTOR_SIZE(dimensions));
/* Ensure free space */
if (PageGetFreeSpace(page) < itemsz)
if (PageGetFreeSpace(page) < listSize)
IvfflatAppendPage(index, &buf, &page, &state, forkNum);
/* Add the item */
offno = PageAddItem(page, (Item) list, itemsz, InvalidOffsetNumber, false, false);
offno = PageAddItem(page, (Item) list, listSize, InvalidOffsetNumber, false, false);
if (offno == InvalidOffsetNumber)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
@@ -523,7 +553,7 @@ PrintKmeansMetrics(IvfflatBuildState * buildstate)
elog(INFO, "inertia: %.3e", buildstate->inertia);
/* Calculate Davies-Bouldin index */
if (buildstate->lists > 1)
if (buildstate->lists > 1 && !buildstate->ivfleader)
{
double db = 0.0;
@@ -558,43 +588,478 @@ PrintKmeansMetrics(IvfflatBuildState * buildstate)
}
#endif
/*
* Within leader, wait for end of heap scan
*/
static double
ParallelHeapScan(IvfflatBuildState * buildstate)
{
IvfflatShared *ivfshared = buildstate->ivfleader->ivfshared;
int nparticipanttuplesorts;
double reltuples;
nparticipanttuplesorts = buildstate->ivfleader->nparticipanttuplesorts;
for (;;)
{
SpinLockAcquire(&ivfshared->mutex);
if (ivfshared->nparticipantsdone == nparticipanttuplesorts)
{
buildstate->indtuples = ivfshared->indtuples;
reltuples = ivfshared->reltuples;
#ifdef IVFFLAT_KMEANS_DEBUG
buildstate->inertia = ivfshared->inertia;
#endif
SpinLockRelease(&ivfshared->mutex);
break;
}
SpinLockRelease(&ivfshared->mutex);
ConditionVariableSleep(&ivfshared->workersdonecv,
WAIT_EVENT_PARALLEL_CREATE_INDEX_SCAN);
}
ConditionVariableCancelSleep();
return reltuples;
}
/*
* Perform a worker's portion of a parallel sort
*/
static void
IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, Sharedsort *sharedsort, Vector * ivfcenters, int sortmem, bool progress)
{
SortCoordinate coordinate;
IvfflatBuildState buildstate;
#if PG_VERSION_NUM >= 120000
TableScanDesc scan;
#else
HeapScanDesc scan;
#endif
double reltuples;
IndexInfo *indexInfo;
/* Sort options, which must match AssignTuples */
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Int4LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
/* Initialize local tuplesort coordination state */
coordinate = palloc0(sizeof(SortCoordinateData));
coordinate->isWorker = true;
coordinate->nParticipants = -1;
coordinate->sharedsort = sharedsort;
/* Join parallel scan */
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);
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);
/* Record statistics */
SpinLockAcquire(&ivfshared->mutex);
ivfshared->nparticipantsdone++;
ivfshared->reltuples += reltuples;
ivfshared->indtuples += buildstate.indtuples;
#ifdef IVFFLAT_KMEANS_DEBUG
ivfshared->inertia += buildstate.inertia;
#endif
SpinLockRelease(&ivfshared->mutex);
/* Log statistics */
if (progress)
ereport(DEBUG1, (errmsg("leader processed " INT64_FORMAT " tuples", (int64) reltuples)));
else
ereport(DEBUG1, (errmsg("worker processed " INT64_FORMAT " tuples", (int64) reltuples)));
/* Notify leader */
ConditionVariableSignal(&ivfshared->workersdonecv);
/* We can end tuplesorts immediately */
tuplesort_end(ivfspool->sortstate);
FreeBuildState(&buildstate);
}
/*
* Perform work within a launched parallel process
*/
void
IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc)
{
char *sharedquery;
IvfflatSpool *ivfspool;
IvfflatShared *ivfshared;
Sharedsort *sharedsort;
Vector *ivfcenters;
Relation heapRel;
Relation indexRel;
LOCKMODE heapLockmode;
LOCKMODE indexLockmode;
int sortmem;
/* Set debug_query_string for individual workers first */
sharedquery = shm_toc_lookup(toc, PARALLEL_KEY_QUERY_TEXT, true);
debug_query_string = sharedquery;
/* Report the query string from leader */
pgstat_report_activity(STATE_RUNNING, debug_query_string);
/* Look up shared state */
ivfshared = shm_toc_lookup(toc, PARALLEL_KEY_IVFFLAT_SHARED, false);
/* Open relations using lock modes known to be obtained by index.c */
if (!ivfshared->isconcurrent)
{
heapLockmode = ShareLock;
indexLockmode = AccessExclusiveLock;
}
else
{
heapLockmode = ShareUpdateExclusiveLock;
indexLockmode = RowExclusiveLock;
}
/* 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 */
ivfspool = (IvfflatSpool *) palloc0(sizeof(IvfflatSpool));
ivfspool->heap = heapRel;
ivfspool->index = indexRel;
/* Look up shared state private to tuplesort.c */
sharedsort = shm_toc_lookup(toc, PARALLEL_KEY_TUPLESORT, false);
tuplesort_attach_shared(sharedsort, seg);
ivfcenters = shm_toc_lookup(toc, PARALLEL_KEY_IVFFLAT_CENTERS, false);
/* Perform sorting */
sortmem = maintenance_work_mem / ivfshared->scantuplesortstates;
IvfflatParallelScanAndSort(ivfspool, ivfshared, sharedsort, ivfcenters, sortmem, false);
/* Close relations within worker */
index_close(indexRel, indexLockmode);
#if PG_VERSION_NUM >= 120000
table_close(heapRel, heapLockmode);
#else
heap_close(heapRel, heapLockmode);
#endif
}
/*
* End parallel build
*/
static void
IvfflatEndParallel(IvfflatLeader * ivfleader)
{
/* Shutdown worker processes */
WaitForParallelWorkersToFinish(ivfleader->pcxt);
/* Free last reference to MVCC snapshot, if one was used */
if (IsMVCCSnapshot(ivfleader->snapshot))
UnregisterSnapshot(ivfleader->snapshot);
DestroyParallelContext(ivfleader->pcxt);
ExitParallelMode();
}
/*
* Return size of shared memory required for parallel index build
*/
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
}
/*
* Within leader, participate as a parallel worker
*/
static void
IvfflatLeaderParticipateAsWorker(IvfflatBuildState * buildstate)
{
IvfflatLeader *ivfleader = buildstate->ivfleader;
IvfflatSpool *leaderworker;
int sortmem;
/* Allocate memory and initialize private spool */
leaderworker = (IvfflatSpool *) palloc0(sizeof(IvfflatSpool));
leaderworker->heap = buildstate->heap;
leaderworker->index = buildstate->index;
/* Perform work common to all participants */
sortmem = maintenance_work_mem / ivfleader->nparticipanttuplesorts;
IvfflatParallelScanAndSort(leaderworker, ivfleader->ivfshared,
ivfleader->sharedsort, ivfleader->ivfcenters,
sortmem, true);
}
/*
* Begin parallel build
*/
static void
IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int request)
{
ParallelContext *pcxt;
int scantuplesortstates;
Snapshot snapshot;
Size estivfshared;
Size estsort;
Size estcenters;
IvfflatShared *ivfshared;
Sharedsort *sharedsort;
Vector *ivfcenters;
IvfflatLeader *ivfleader = (IvfflatLeader *) palloc0(sizeof(IvfflatLeader));
bool leaderparticipates = true;
int querylen;
#ifdef DISABLE_LEADER_PARTICIPATION
leaderparticipates = false;
#endif
/* 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;
/* Get snapshot for table scan */
if (!isconcurrent)
snapshot = SnapshotAny;
else
snapshot = RegisterSnapshot(GetTransactionSnapshot());
/* Estimate size of workspaces */
estivfshared = ParallelEstimateShared(buildstate->heap, snapshot);
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;
shm_toc_estimate_chunk(&pcxt->estimator, estcenters);
shm_toc_estimate_keys(&pcxt->estimator, 3);
/* Finally, estimate PARALLEL_KEY_QUERY_TEXT space */
if (debug_query_string)
{
querylen = strlen(debug_query_string);
shm_toc_estimate_chunk(&pcxt->estimator, querylen + 1);
shm_toc_estimate_keys(&pcxt->estimator, 1);
}
else
querylen = 0; /* keep compiler quiet */
/* Everyone's had a chance to ask for space, so now create the DSM */
InitializeParallelDSM(pcxt);
/* If no DSM segment was available, back out (do serial build) */
if (pcxt->seg == NULL)
{
if (IsMVCCSnapshot(snapshot))
UnregisterSnapshot(snapshot);
DestroyParallelContext(pcxt);
ExitParallelMode();
return;
}
/* Store shared build state, for which we reserved space */
ivfshared = (IvfflatShared *) shm_toc_allocate(pcxt->toc, estivfshared);
/* Initialize immutable state */
ivfshared->heaprelid = RelationGetRelid(buildstate->heap);
ivfshared->indexrelid = RelationGetRelid(buildstate->index);
ivfshared->isconcurrent = isconcurrent;
ivfshared->scantuplesortstates = scantuplesortstates;
ConditionVariableInit(&ivfshared->workersdonecv);
SpinLockInit(&ivfshared->mutex);
/* Initialize mutable state */
ivfshared->nparticipantsdone = 0;
ivfshared->reltuples = 0;
ivfshared->indtuples = 0;
#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);
memcpy(ivfcenters, buildstate->centers->items, estcenters);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_IVFFLAT_SHARED, ivfshared);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_TUPLESORT, sharedsort);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_IVFFLAT_CENTERS, ivfcenters);
/* Store query string for workers */
if (debug_query_string)
{
char *sharedquery;
sharedquery = (char *) shm_toc_allocate(pcxt->toc, querylen + 1);
memcpy(sharedquery, debug_query_string, querylen + 1);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_QUERY_TEXT, sharedquery);
}
/* Launch workers, saving status for leader/caller */
LaunchParallelWorkers(pcxt);
ivfleader->pcxt = pcxt;
ivfleader->nparticipanttuplesorts = pcxt->nworkers_launched;
if (leaderparticipates)
ivfleader->nparticipanttuplesorts++;
ivfleader->ivfshared = ivfshared;
ivfleader->sharedsort = sharedsort;
ivfleader->snapshot = snapshot;
ivfleader->ivfcenters = ivfcenters;
/* If no workers were successfully launched, back out (do serial build) */
if (pcxt->nworkers_launched == 0)
{
IvfflatEndParallel(ivfleader);
return;
}
/* Log participants */
ereport(DEBUG1, (errmsg("using %d parallel workers", pcxt->nworkers_launched)));
/* Save leader state now that it's clear build will be parallel */
buildstate->ivfleader = ivfleader;
/* Join heap scan ourselves */
if (leaderparticipates)
IvfflatLeaderParticipateAsWorker(buildstate);
/* Wait for all launched workers */
WaitForParallelWorkersToAttach(pcxt);
}
/*
* Scan table for tuples to index
*/
static void
AssignTuples(IvfflatBuildState * buildstate)
{
int parallel_workers = 0;
SortCoordinate coordinate = NULL;
/* Sort options, which must match IvfflatParallelScanAndSort */
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Int4LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_ASSIGN);
/* Calculate parallel workers */
if (buildstate->heap != NULL)
parallel_workers = plan_create_index_workers(RelationGetRelid(buildstate->heap), RelationGetRelid(buildstate->index));
/* Attempt to launch parallel worker scan when required */
if (parallel_workers > 0)
IvfflatBeginParallel(buildstate, buildstate->indexInfo->ii_Concurrent, parallel_workers);
/* Set up coordination state if at least one worker launched */
if (buildstate->ivfleader)
{
coordinate = (SortCoordinate) palloc0(sizeof(SortCoordinateData));
coordinate->isWorker = false;
coordinate->nParticipants = buildstate->ivfleader->nparticipanttuplesorts;
coordinate->sharedsort = buildstate->ivfleader->sharedsort;
}
/* Begin serial/leader tuplesort */
buildstate->sortstate = tuplesort_begin_heap(buildstate->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, maintenance_work_mem, coordinate, false);
/* Add tuples to sort */
if (buildstate->heap != NULL)
{
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);
#endif
}
}
/*
* Create entry pages
*/
static void
CreateEntryPages(IvfflatBuildState * buildstate, ForkNumber forkNum)
{
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Float8LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_SORT);
buildstate->sortstate = tuplesort_begin_heap(buildstate->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, maintenance_work_mem, NULL, false);
/* Add tuples to sort */
if (buildstate->heap != NULL)
{
#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
}
/* Assign */
IvfflatBench("assign tuples", AssignTuples(buildstate));
/* Sort */
tuplesort_performsort(buildstate->sortstate);
IvfflatBench("sort tuples", tuplesort_performsort(buildstate->sortstate));
#ifdef IVFFLAT_KMEANS_DEBUG
PrintKmeansMetrics(buildstate);
#endif
/* Load */
IvfflatBench("load tuples", InsertTuples(buildstate->index, buildstate, forkNum));
/* Insert */
InsertTuples(buildstate->index, buildstate, forkNum);
/* End sort */
tuplesort_end(buildstate->sortstate);
/* End parallel build */
if (buildstate->ivfleader)
IvfflatEndParallel(buildstate->ivfleader);
}
/*
@@ -611,7 +1076,7 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
/* Create pages */
CreateMetaPage(index, buildstate->dimensions, buildstate->lists, forkNum);
CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo);
IvfflatBench("CreateEntryPages", CreateEntryPages(buildstate, forkNum));
CreateEntryPages(buildstate, forkNum);
FreeBuildState(buildstate);
}

View File

@@ -7,6 +7,7 @@
#include "ivfflat.h"
#include "utils/guc.h"
#include "utils/selfuncs.h"
#include "utils/spccache.h"
#if PG_VERSION_NUM >= 120000
#include "commands/progress.h"
@@ -19,11 +20,11 @@ static relopt_kind ivfflat_relopt_kind;
* Initialize index options and variables
*/
void
_PG_init(void)
IvfflatInit(void)
{
ivfflat_relopt_kind = add_reloption_kind();
add_int_reloption(ivfflat_relopt_kind, "lists", "Number of inverted lists",
IVFFLAT_DEFAULT_LISTS, 1, IVFFLAT_MAX_LISTS
IVFFLAT_DEFAULT_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS
#if PG_VERSION_NUM >= 130000
,AccessExclusiveLock
#endif
@@ -31,7 +32,7 @@ _PG_init(void)
DefineCustomIntVariable("ivfflat.probes", "Sets the number of probes",
"Valid range is 1..lists.", &ivfflat_probes,
1, 1, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
IVFFLAT_DEFAULT_PROBES, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
}
/*
@@ -47,8 +48,8 @@ ivfflatbuildphasename(int64 phasenum)
return "initializing";
case PROGRESS_IVFFLAT_PHASE_KMEANS:
return "performing k-means";
case PROGRESS_IVFFLAT_PHASE_SORT:
return "sorting tuples";
case PROGRESS_IVFFLAT_PHASE_ASSIGN:
return "assigning tuples";
case PROGRESS_IVFFLAT_PHASE_LOAD:
return "loading tuples";
default:
@@ -63,14 +64,14 @@ ivfflatbuildphasename(int64 phasenum)
static void
ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
Cost *indexStartupCost, Cost *indexTotalCost,
Selectivity *indexSelectivity, double *indexCorrelation
,double *indexPages
)
Selectivity *indexSelectivity, double *indexCorrelation,
double *indexPages)
{
GenericCosts costs;
int lists;
double ratio;
Relation indexRel;
double spc_seq_page_cost;
Relation index;
#if PG_VERSION_NUM < 120000
List *qinfos;
#endif
@@ -88,6 +89,22 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
MemSet(&costs, 0, sizeof(costs));
index = index_open(path->indexinfo->indexoid, NoLock);
IvfflatGetMetaPageInfo(index, &lists, NULL);
index_close(index, NoLock);
/* Get the ratio of lists that we need to visit */
ratio = ((double) ivfflat_probes) / lists;
if (ratio > 1.0)
ratio = 1.0;
/*
* This gives us the subset of tuples to visit. This value is passed into
* the generic cost estimator to determine the number of pages to visit
* during the index scan.
*/
costs.numIndexTuples = path->indexinfo->tuples * ratio;
#if PG_VERSION_NUM >= 120000
genericcostestimate(root, path, loop_count, &costs);
#else
@@ -95,17 +112,31 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
genericcostestimate(root, path, loop_count, qinfos, &costs);
#endif
indexRel = index_open(path->indexinfo->indexoid, NoLock);
lists = IvfflatGetLists(indexRel);
index_close(indexRel, NoLock);
get_tablespace_page_costs(path->indexinfo->reltablespace, NULL, &spc_seq_page_cost);
ratio = ((double) ivfflat_probes) / lists;
if (ratio > 1)
ratio = 1;
/* Adjust cost if needed since TOAST not included in seq scan cost */
if (costs.numIndexPages > path->indexinfo->rel->pages && ratio < 0.5)
{
/* Change all page cost from random to sequential */
costs.indexTotalCost -= costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
costs.indexTotalCost *= ratio;
/* Remove cost of extra pages */
costs.indexTotalCost -= (costs.numIndexPages - path->indexinfo->rel->pages) * spc_seq_page_cost;
}
else
{
/* Change some page cost from random to sequential */
costs.indexTotalCost -= 0.5 * costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
}
/* Startup cost and total cost are same */
/*
* If the list selectivity is lower than what is returned from the generic
* cost estimator, use that.
*/
if (ratio < costs.indexSelectivity)
costs.indexSelectivity = ratio;
/* Use total cost since most work happens before first tuple is returned */
*indexStartupCost = costs.indexTotalCost;
*indexTotalCost = costs.indexTotalCost;
*indexSelectivity = costs.indexSelectivity;

View File

@@ -3,14 +3,11 @@
#include "postgres.h"
#if PG_VERSION_NUM < 110000
#error "Requires PostgreSQL 11+"
#endif
#include "access/generic_xlog.h"
#include "access/parallel.h"
#include "access/reloptions.h"
#include "nodes/execnodes.h"
#include "port.h" /* for strtof() and random() */
#include "port.h" /* for random() */
#include "utils/sampling.h"
#include "utils/tuplesort.h"
#include "vector.h"
@@ -19,6 +16,10 @@
#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
@@ -39,13 +40,16 @@
#define IVFFLAT_METAPAGE_BLKNO 0
#define IVFFLAT_HEAD_BLKNO 1 /* first list page */
/* IVFFlat parameters */
#define IVFFLAT_DEFAULT_LISTS 100
#define IVFFLAT_MIN_LISTS 1
#define IVFFLAT_MAX_LISTS 32768
#define IVFFLAT_DEFAULT_PROBES 1
/* Build phases */
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
#define PROGRESS_IVFFLAT_PHASE_KMEANS 2
#define PROGRESS_IVFFLAT_PHASE_SORT 3
#define PROGRESS_IVFFLAT_PHASE_ASSIGN 3
#define PROGRESS_IVFFLAT_PHASE_LOAD 4
#define IVFFLAT_LIST_SIZE(_dim) (offsetof(IvfflatListData, center) + VECTOR_SIZE(_dim))
@@ -79,9 +83,6 @@
/* Variables */
extern int ivfflat_probes;
/* Exported functions */
PGDLLEXPORT void _PG_init(void);
typedef struct VectorArrayData
{
int length;
@@ -105,6 +106,56 @@ typedef struct IvfflatOptions
int lists; /* number of lists */
} IvfflatOptions;
typedef struct IvfflatSpool
{
Tuplesortstate *sortstate;
Relation heap;
Relation index;
} IvfflatSpool;
typedef struct IvfflatShared
{
/* Immutable state */
Oid heaprelid;
Oid indexrelid;
bool isconcurrent;
int scantuplesortstates;
/* Worker progress */
ConditionVariable workersdonecv;
/* Mutex for mutable state */
slock_t mutex;
/* Mutable state */
int nparticipantsdone;
double reltuples;
double indtuples;
#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
{
ParallelContext *pcxt;
int nparticipanttuplesorts;
IvfflatShared *ivfshared;
Sharedsort *sharedsort;
Snapshot snapshot;
Vector *ivfcenters;
} IvfflatLeader;
typedef struct IvfflatBuildState
{
/* Info */
@@ -150,6 +201,9 @@ typedef struct IvfflatBuildState
/* Memory */
MemoryContext tmpCtx;
/* Parallel builds */
IvfflatLeader *ivfleader;
} IvfflatBuildState;
typedef struct IvfflatMetaPageData
@@ -190,8 +244,8 @@ typedef struct IvfflatScanList
typedef struct IvfflatScanOpaqueData
{
int probes;
int dimensions;
bool first;
Buffer buf;
/* Sorting */
Tuplesortstate *sortstate;
@@ -221,15 +275,18 @@ VectorArray VectorArrayInit(int maxlen, int dimensions);
void VectorArrayFree(VectorArray arr);
void PrintVectorArray(char *msg, VectorArray arr);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
FmgrInfo *IvfflatOptionalProcInfo(Relation rel, uint16 procnum);
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
int IvfflatGetLists(Relation index);
void IvfflatUpdateList(Relation index, GenericXLogState *state, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);
void IvfflatCommitBuffer(Buffer buf, GenericXLogState *state);
void IvfflatAppendPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state, ForkNumber forkNum);
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);
PGDLLEXPORT void IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc);
/* Index access methods */
IndexBuildResult *ivfflatbuild(Relation heap, Relation index, IndexInfo *indexInfo);

View File

@@ -4,42 +4,48 @@
#include "ivfflat.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
#include "utils/memutils.h"
/*
* Find the list that minimizes the distance function
*/
static void
FindInsertPage(Relation rel, Datum *values, BlockNumber *insertPage, ListInfo * listInfo)
FindInsertPage(Relation index, Datum *values, BlockNumber *insertPage, ListInfo * listInfo)
{
Buffer cbuf;
Page cpage;
IvfflatList list;
double distance;
double minDistance = DBL_MAX;
BlockNumber nextblkno = IVFFLAT_HEAD_BLKNO;
FmgrInfo *procinfo;
Oid collation;
OffsetNumber offno;
OffsetNumber maxoffno;
procinfo = index_getprocinfo(rel, 1, IVFFLAT_DISTANCE_PROC);
collation = rel->rd_indcollation[0];
/* Avoid compiler warning */
listInfo->blkno = nextblkno;
listInfo->offno = FirstOffsetNumber;
procinfo = index_getprocinfo(index, 1, IVFFLAT_DISTANCE_PROC);
collation = index->rd_indcollation[0];
/* Search all list pages */
while (BlockNumberIsValid(nextblkno))
{
cbuf = ReadBuffer(rel, nextblkno);
Buffer cbuf;
Page cpage;
OffsetNumber maxoffno;
cbuf = ReadBuffer(index, nextblkno);
LockBuffer(cbuf, BUFFER_LOCK_SHARE);
cpage = BufferGetPage(cbuf);
maxoffno = PageGetMaxOffsetNumber(cpage);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
for (OffsetNumber offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
IvfflatList list;
double distance;
list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, offno));
distance = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, values[0], PointerGetDatum(&list->center)));
if (distance < minDistance)
if (distance < minDistance || !BlockNumberIsValid(*insertPage))
{
*insertPage = list->insertPage;
listInfo->blkno = nextblkno;
@@ -58,7 +64,7 @@ FindInsertPage(Relation rel, Datum *values, BlockNumber *insertPage, ListInfo *
* Insert a tuple into the index
*/
static void
InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
{
IndexTuple itup;
Datum value;
@@ -75,33 +81,33 @@ InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Rel
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Normalize if needed */
normprocinfo = IvfflatOptionalProcInfo(rel, IVFFLAT_NORM_PROC);
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL)
{
if (!IvfflatNormValue(normprocinfo, rel->rd_indcollation[0], &value, NULL))
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
return;
}
/* Find the insert page - sets the page and list info */
FindInsertPage(rel, values, &insertPage, &listInfo);
FindInsertPage(index, values, &insertPage, &listInfo);
Assert(BlockNumberIsValid(insertPage));
originalInsertPage = insertPage;
/* Form tuple */
itup = index_form_tuple(RelationGetDescr(rel), &value, isnull);
itup = index_form_tuple(RelationGetDescr(index), &value, isnull);
itup->t_tid = *heap_tid;
/* Get tuple size */
itemsz = MAXALIGN(IndexTupleSize(itup));
Assert(itemsz <= BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(IvfflatPageOpaqueData)));
Assert(itemsz <= BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(IvfflatPageOpaqueData)) - sizeof(ItemIdData));
/* Find a page to insert the item */
for (;;)
{
buf = ReadBuffer(rel, insertPage);
buf = ReadBuffer(index, insertPage);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
state = GenericXLogStart(rel);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
if (PageGetFreeSpace(page) >= itemsz)
@@ -117,23 +123,16 @@ InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Rel
}
else
{
Buffer metabuf;
Buffer newbuf;
Page newpage;
/*
* From ReadBufferExtended: Caller is responsible for ensuring
* that only one backend tries to extend a relation at the same
* time!
*/
metabuf = ReadBuffer(rel, IVFFLAT_METAPAGE_BLKNO);
LockBuffer(metabuf, BUFFER_LOCK_EXCLUSIVE);
/* Add a new page */
newbuf = IvfflatNewBuffer(rel, MAIN_FORKNUM);
newpage = GenericXLogRegisterBuffer(state, newbuf, GENERIC_XLOG_FULL_IMAGE);
LockRelationForExtension(index, ExclusiveLock);
newbuf = IvfflatNewBuffer(index, MAIN_FORKNUM);
UnlockRelationForExtension(index, ExclusiveLock);
/* Init new page */
newpage = GenericXLogRegisterBuffer(state, newbuf, GENERIC_XLOG_FULL_IMAGE);
IvfflatInitPage(newbuf, newpage);
/* Update insert page */
@@ -143,18 +142,13 @@ InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Rel
IvfflatPageGetOpaque(page)->nextblkno = insertPage;
/* Commit */
MarkBufferDirty(newbuf);
MarkBufferDirty(buf);
GenericXLogFinish(state);
/* Unlock extend relation lock as early as possible */
UnlockReleaseBuffer(metabuf);
/* Unlock previous buffer */
UnlockReleaseBuffer(buf);
/* Prepare new buffer */
state = GenericXLogStart(rel);
state = GenericXLogStart(index);
buf = newbuf;
page = GenericXLogRegisterBuffer(state, buf, 0);
break;
@@ -163,13 +157,13 @@ InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Rel
/* Add to next offset */
if (PageAddItem(page, (Item) itup, itemsz, InvalidOffsetNumber, false, false) == InvalidOffsetNumber)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(rel));
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
IvfflatCommitBuffer(buf, state);
/* Update the insert page */
if (insertPage != originalInsertPage)
IvfflatUpdateList(rel, state, listInfo, insertPage, originalInsertPage, InvalidBlockNumber, MAIN_FORKNUM);
IvfflatUpdateList(index, listInfo, insertPage, originalInsertPage, InvalidBlockNumber, MAIN_FORKNUM);
}
/*

View File

@@ -1,6 +1,7 @@
#include "postgres.h"
#include <float.h>
#include <math.h>
#include "ivfflat.h"
#include "miscadmin.h"
@@ -15,12 +16,7 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
{
FmgrInfo *procinfo;
Oid collation;
int i;
int64 j;
double distance;
double sum;
double choice;
Vector *vec;
float *weight = palloc(samples->length * sizeof(float));
int numCenters = centers->maxlen;
int numSamples = samples->length;
@@ -33,17 +29,21 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
centers->length++;
for (j = 0; j < numSamples; j++)
weight[j] = DBL_MAX;
weight[j] = FLT_MAX;
for (i = 0; i < numCenters; i++)
for (int i = 0; i < numCenters; i++)
{
double sum;
double choice;
CHECK_FOR_INTERRUPTS();
sum = 0.0;
for (j = 0; j < numSamples; j++)
{
vec = VectorArrayGet(samples, j);
Vector *vec = VectorArrayGet(samples, j);
double distance;
/* Only need to compute distance for new center */
/* TODO Use triangle inequality to reduce distance calculations */
@@ -87,13 +87,12 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
static inline void
ApplyNorm(FmgrInfo *normprocinfo, Oid collation, Vector * vec)
{
int i;
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(vec)));
/* TODO Handle zero norm */
if (norm > 0)
{
for (i = 0; i < vec->dim; i++)
for (int i = 0; i < vec->dim; i++)
vec->x[i] /= norm;
}
}
@@ -113,9 +112,6 @@ CompareVectors(const void *a, const void *b)
static void
QuickCenters(Relation index, VectorArray samples, VectorArray centers)
{
int i;
int j;
Vector *vec;
int dimensions = centers->dim;
Oid collation = index->rd_indcollation[0];
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
@@ -124,9 +120,9 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
if (samples->length > 0)
{
qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
for (i = 0; i < samples->length; i++)
for (int i = 0; i < samples->length; i++)
{
vec = VectorArrayGet(samples, i);
Vector *vec = VectorArrayGet(samples, i);
if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
{
@@ -139,12 +135,12 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
/* Fill remaining with random data */
while (centers->length < centers->maxlen)
{
vec = VectorArrayGet(centers, centers->length);
Vector *vec = VectorArrayGet(centers, centers->length);
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
for (j = 0; j < dimensions; j++)
for (int j = 0; j < dimensions; j++)
vec->x[j] = RandomDouble();
/* Normalize if needed (only needed for random centers) */
@@ -171,7 +167,6 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
Oid collation;
Vector *vec;
Vector *newCenter;
int iteration;
int64 j;
int64 k;
int dimensions = centers->dim;
@@ -185,14 +180,6 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
float *s;
float *halfcdist;
float *newcdist;
int changes;
double minDistance;
int closestCenter;
double distance;
bool rj;
bool rjreset;
double dxcx;
double dxc;
/* Calculate allocation sizes */
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->dim);
@@ -211,7 +198,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Check memory requirements */
/* Add one to error message to ceil */
if (totalSize / 1024 > maintenance_work_mem)
if (totalSize > (Size) maintenance_work_mem * 1024L)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("memory required is %zu MB, maintenance_work_mem is %d MB",
@@ -250,14 +237,14 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Assign each x to its closest initial center c(x) = argmin d(x,c) */
for (j = 0; j < numSamples; j++)
{
minDistance = DBL_MAX;
closestCenter = -1;
float minDistance = FLT_MAX;
int closestCenter = 0;
/* Find closest center */
for (k = 0; k < numCenters; k++)
{
/* TODO Use Lemma 1 in k-means++ initialization */
distance = lowerBound[j * numCenters + k];
float distance = lowerBound[j * numCenters + k];
if (distance < minDistance)
{
@@ -271,13 +258,14 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
}
/* Give 500 iterations to converge */
for (iteration = 0; iteration < 500; iteration++)
for (int iteration = 0; iteration < 500; iteration++)
{
int changes = 0;
bool rjreset;
/* Can take a while, so ensure we can interrupt */
CHECK_FOR_INTERRUPTS();
changes = 0;
/* Step 1: For all centers, compute distance */
for (j = 0; j < numCenters; j++)
{
@@ -285,7 +273,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
for (k = j + 1; k < numCenters; k++)
{
distance = 0.5 * DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
float distance = 0.5 * DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
halfcdist[j * numCenters + k] = distance;
halfcdist[k * numCenters + j] = distance;
}
@@ -294,10 +283,12 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* For all centers c, compute s(c) */
for (j = 0; j < numCenters; j++)
{
minDistance = DBL_MAX;
float minDistance = FLT_MAX;
for (k = 0; k < numCenters; k++)
{
float distance;
if (j == k)
continue;
@@ -313,6 +304,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
for (j = 0; j < numSamples; j++)
{
bool rj;
/* Step 2: Identify all points x such that u(x) <= s(c(x)) */
if (upperBound[j] <= s[closestCenters[j]])
continue;
@@ -321,6 +314,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
for (k = 0; k < numCenters; k++)
{
float dxcx;
/* Step 3: For all remaining points x and centers c */
if (k == closestCenters[j])
continue;
@@ -350,7 +345,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Step 3b */
if (dxcx > lowerBound[j * numCenters + k] || dxcx > halfcdist[closestCenters[j] * numCenters + k])
{
dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
float dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
/* d(x,c) calculated */
lowerBound[j * numCenters + k] = dxc;
@@ -364,7 +359,6 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
changes++;
}
}
}
}
@@ -381,6 +375,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
for (j = 0; j < numSamples; j++)
{
int closestCenter;
vec = VectorArrayGet(samples, j);
closestCenter = closestCenters[j];
@@ -398,6 +394,14 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
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];
}
@@ -421,7 +425,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
{
for (k = 0; k < numCenters; k++)
{
distance = lowerBound[j * numCenters + k] - newcdist[k];
float distance = lowerBound[j * numCenters + k] - newcdist[k];
if (distance < 0)
distance = 0;
@@ -437,7 +441,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Step 7 */
for (j = 0; j < numCenters; j++)
memcpy(VectorArrayGet(centers, j), VectorArrayGet(newCenters, j), VECTOR_SIZE(dimensions));
VectorArraySet(centers, j, VectorArrayGet(newCenters, j));
if (changes == 0 && iteration != 0)
break;
@@ -460,17 +464,29 @@ static void
CheckCenters(Relation index, VectorArray centers)
{
FmgrInfo *normprocinfo;
Oid collation;
int i;
double norm;
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 (i = 1; i < centers->length; i++)
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.");
@@ -481,11 +497,12 @@ CheckCenters(Relation index, VectorArray centers)
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL)
{
collation = index->rd_indcollation[0];
Oid collation = index->rd_indcollation[0];
for (i = 0; i < centers->length; i++)
for (int i = 0; i < centers->length; i++)
{
norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(VectorArrayGet(centers, i))));
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(VectorArrayGet(centers, i))));
if (norm == 0)
elog(ERROR, "Zero norm detected. Please report a bug.");
}

View File

@@ -3,14 +3,13 @@
#include <float.h>
#include "access/relscan.h"
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "pgstat.h"
#include "storage/bufmgr.h"
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
/*
* Compare list distances
*/
@@ -32,36 +31,36 @@ CompareLists(const pairingheap_node *a, const pairingheap_node *b, void *arg)
static void
GetScanLists(IndexScanDesc scan, Datum value)
{
Buffer cbuf;
Page cpage;
IvfflatList list;
OffsetNumber offno;
OffsetNumber maxoffno;
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
BlockNumber nextblkno = IVFFLAT_HEAD_BLKNO;
int listCount = 0;
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
double distance;
IvfflatScanList *scanlist;
double maxDistance = DBL_MAX;
/* Search all list pages */
while (BlockNumberIsValid(nextblkno))
{
Buffer cbuf;
Page cpage;
OffsetNumber maxoffno;
cbuf = ReadBuffer(scan->indexRelation, nextblkno);
LockBuffer(cbuf, BUFFER_LOCK_SHARE);
cpage = BufferGetPage(cbuf);
maxoffno = PageGetMaxOffsetNumber(cpage);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
for (OffsetNumber offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, offno));
IvfflatList list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, offno));
double distance;
/* Use procinfo from the index instead of scan key for performance */
distance = DatumGetFloat8(FunctionCall2Coll(so->procinfo, so->collation, PointerGetDatum(&list->center), value));
if (listCount < so->probes)
{
IvfflatScanList *scanlist;
scanlist = &so->lists[listCount];
scanlist->startPage = list->startPage;
scanlist->distance = distance;
@@ -76,6 +75,8 @@ GetScanLists(IndexScanDesc scan, Datum value)
}
else if (distance < maxDistance)
{
IvfflatScanList *scanlist;
/* Remove */
scanlist = (IvfflatScanList *) pairingheap_remove_first(so->listQueue);
@@ -102,15 +103,8 @@ static void
GetScanItems(IndexScanDesc scan, Datum value)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
Buffer buf;
Page page;
IndexTuple itup;
BlockNumber searchPage;
OffsetNumber offno;
OffsetNumber maxoffno;
Datum datum;
bool isnull;
TupleDesc tupdesc = RelationGetDescr(scan->indexRelation);
double tuples = 0;
#if PG_VERSION_NUM >= 120000
TupleTableSlot *slot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsVirtual);
@@ -128,19 +122,28 @@ GetScanItems(IndexScanDesc scan, Datum value)
/* Search closest probes lists */
while (!pairingheap_is_empty(so->listQueue))
{
searchPage = ((IvfflatScanList *) pairingheap_remove_first(so->listQueue))->startPage;
BlockNumber searchPage = ((IvfflatScanList *) pairingheap_remove_first(so->listQueue))->startPage;
/* Search all entry pages for list */
while (BlockNumberIsValid(searchPage))
{
Buffer buf;
Page page;
OffsetNumber maxoffno;
buf = ReadBufferExtended(scan->indexRelation, MAIN_FORKNUM, searchPage, RBM_NORMAL, bas);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
maxoffno = PageGetMaxOffsetNumber(page);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
for (OffsetNumber offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
itup = (IndexTuple) PageGetItem(page, PageGetItemId(page, offno));
IndexTuple itup;
Datum datum;
bool isnull;
ItemId itemid = PageGetItemId(page, offno);
itup = (IndexTuple) PageGetItem(page, itemid);
datum = index_getattr(itup, 1, tupdesc, &isnull);
/*
@@ -154,11 +157,11 @@ GetScanItems(IndexScanDesc scan, Datum value)
slot->tts_isnull[0] = false;
slot->tts_values[1] = PointerGetDatum(&itup->t_tid);
slot->tts_isnull[1] = false;
slot->tts_values[2] = Int32GetDatum((int) searchPage);
slot->tts_isnull[2] = false;
ExecStoreVirtualTuple(slot);
tuplesort_puttupleslot(so->sortstate, slot);
tuples++;
}
searchPage = IvfflatPageGetOpaque(page)->nextblkno;
@@ -167,6 +170,14 @@ GetScanItems(IndexScanDesc scan, Datum value)
}
}
FreeAccessStrategy(bas);
if (tuples < 100)
ereport(DEBUG1,
(errmsg("index scan found few tuples"),
errdetail("Index may have been created with little data."),
errhint("Recreate the index and possibly decrease lists.")));
tuplesort_performsort(so->sortstate);
}
@@ -179,6 +190,7 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
IndexScanDesc scan;
IvfflatScanOpaque so;
int lists;
int dimensions;
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Float8LessOperator};
Oid sortCollations[] = {InvalidOid};
@@ -186,15 +198,17 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
int probes = ivfflat_probes;
scan = RelationGetIndexScan(index, nkeys, norderbys);
lists = IvfflatGetLists(scan->indexRelation);
/* Get lists and dimensions from metapage */
IvfflatGetMetaPageInfo(index, &lists, &dimensions);
if (probes > lists)
probes = lists;
so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
so->buf = InvalidBuffer;
so->first = true;
so->probes = probes;
so->dimensions = dimensions;
/* Set support functions */
so->procinfo = index_getprocinfo(index, 1, IVFFLAT_DISTANCE_PROC);
@@ -203,13 +217,12 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
/* Create tuple description for sorting */
#if PG_VERSION_NUM >= 120000
so->tupdesc = CreateTemplateTupleDesc(3);
so->tupdesc = CreateTemplateTupleDesc(2);
#else
so->tupdesc = CreateTemplateTupleDesc(3, false);
so->tupdesc = CreateTemplateTupleDesc(2, false);
#endif
TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 3, "indexblkno", INT4OID, -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);
@@ -275,21 +288,24 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
if (scan->orderByData == NULL)
elog(ERROR, "cannot scan ivfflat index without order");
/* No items will match if null */
/* Requires MVCC-compliant snapshot as not able to pin during sorting */
/* https://www.postgresql.org/docs/current/index-locking.html */
if (!IsMVCCSnapshot(scan->xs_snapshot))
elog(ERROR, "non-MVCC snapshots are not supported with ivfflat");
if (scan->orderByData->sk_flags & SK_ISNULL)
return false;
value = scan->orderByData->sk_argument;
/* Value should not be compressed or toasted */
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
if (so->normprocinfo != NULL)
value = PointerGetDatum(InitVector(so->dimensions));
else
{
/* No items will match if normalization fails */
if (!IvfflatNormValue(so->normprocinfo, so->collation, &value, NULL))
return false;
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);
}
IvfflatBench("GetScanLists", GetScanLists(scan, value));
@@ -303,26 +319,14 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
if (tuplesort_gettupleslot(so->sortstate, true, false, so->slot, NULL))
{
ItemPointer tid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
BlockNumber indexblkno = DatumGetInt32(slot_getattr(so->slot, 3, &so->isnull));
ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
#if PG_VERSION_NUM >= 120000
scan->xs_heaptid = *tid;
scan->xs_heaptid = *heaptid;
#else
scan->xs_ctup.t_self = *tid;
scan->xs_ctup.t_self = *heaptid;
#endif
if (BufferIsValid(so->buf))
ReleaseBuffer(so->buf);
/*
* An index scan must maintain a pin on the index page holding the
* item last returned by amgettuple
*
* https://www.postgresql.org/docs/current/index-locking.html
*/
so->buf = ReadBuffer(scan->indexRelation, indexblkno);
scan->xs_recheckorderby = false;
return true;
}
@@ -338,10 +342,6 @@ ivfflatendscan(IndexScanDesc scan)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
/* Release pin */
if (BufferIsValid(so->buf))
ReleaseBuffer(so->buf);
pairingheap_free(so->listQueue);
tuplesort_end(so->sortstate);

View File

@@ -35,9 +35,7 @@ VectorArrayFree(VectorArray arr)
void
PrintVectorArray(char *msg, VectorArray arr)
{
int i;
for (i = 0; i < arr->length; i++)
for (int i = 0; i < arr->length; i++)
PrintVector(msg, VectorArrayGet(arr, i));
}
@@ -59,12 +57,12 @@ IvfflatGetLists(Relation index)
* Get proc
*/
FmgrInfo *
IvfflatOptionalProcInfo(Relation rel, uint16 procnum)
IvfflatOptionalProcInfo(Relation index, uint16 procnum)
{
if (!OidIsValid(index_getprocid(rel, 1, procnum)))
if (!OidIsValid(index_getprocid(index, 1, procnum)))
return NULL;
return index_getprocinfo(rel, 1, procnum);
return index_getprocinfo(index, 1, procnum);
}
/*
@@ -78,20 +76,16 @@ IvfflatOptionalProcInfo(Relation rel, uint16 procnum)
bool
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
{
Vector *v;
int i;
double norm;
norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0)
{
v = DatumGetVector(*value);
Vector *v = DatumGetVector(*value);
if (result == NULL)
result = InitVector(v->dim);
for (i = 0; i < v->dim; i++)
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
*value = PointerGetDatum(result);
@@ -142,7 +136,6 @@ IvfflatInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogStat
void
IvfflatCommitBuffer(Buffer buf, GenericXLogState *state)
{
MarkBufferDirty(buf);
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
}
@@ -166,8 +159,6 @@ IvfflatAppendPage(Relation index, Buffer *buf, Page *page, GenericXLogState **st
IvfflatInitPage(newbuf, newpage);
/* Commit */
MarkBufferDirty(*buf);
MarkBufferDirty(newbuf);
GenericXLogFinish(*state);
/* Unlock */
@@ -178,16 +169,40 @@ IvfflatAppendPage(Relation index, Buffer *buf, Page *page, GenericXLogState **st
*buf = newbuf;
}
/*
* Get the metapage info
*/
void
IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions)
{
Buffer buf;
Page page;
IvfflatMetaPage metap;
buf = ReadBuffer(index, IVFFLAT_METAPAGE_BLKNO);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
metap = IvfflatPageGetMeta(page);
*lists = metap->lists;
if (dimensions != NULL)
*dimensions = metap->dimensions;
UnlockReleaseBuffer(buf);
}
/*
* Update the start or insert page of a list
*/
void
IvfflatUpdateList(Relation index, GenericXLogState *state, ListInfo listInfo,
IvfflatUpdateList(Relation index, ListInfo listInfo,
BlockNumber insertPage, BlockNumber originalInsertPage,
BlockNumber startPage, ForkNumber forkNum)
{
Buffer buf;
Page page;
GenericXLogState *state;
IvfflatList list;
bool changed = false;

View File

@@ -12,34 +12,23 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
IndexBulkDeleteCallback callback, void *callback_state)
{
Relation index = info->index;
Buffer cbuf;
Page cpage;
Buffer buf;
Page page;
IvfflatList list;
IndexTuple itup;
ItemPointer htup;
OffsetNumber deletable[MaxOffsetNumber];
int ndeletable;
BlockNumber startPages[MaxOffsetNumber];
BlockNumber nextblkno = IVFFLAT_HEAD_BLKNO;
BlockNumber searchPage;
BlockNumber insertPage;
GenericXLogState *state;
OffsetNumber coffno;
OffsetNumber cmaxoffno;
OffsetNumber offno;
OffsetNumber maxoffno;
ListInfo listInfo;
BlockNumber blkno = IVFFLAT_HEAD_BLKNO;
BufferAccessStrategy bas = GetAccessStrategy(BAS_BULKREAD);
if (stats == NULL)
stats = (IndexBulkDeleteResult *) palloc0(sizeof(IndexBulkDeleteResult));
/* Iterate over list pages */
while (BlockNumberIsValid(nextblkno))
while (BlockNumberIsValid(blkno))
{
cbuf = ReadBuffer(index, nextblkno);
Buffer cbuf;
Page cpage;
OffsetNumber coffno;
OffsetNumber cmaxoffno;
BlockNumber startPages[MaxOffsetNumber];
ListInfo listInfo;
cbuf = ReadBuffer(index, blkno);
LockBuffer(cbuf, BUFFER_LOCK_SHARE);
cpage = BufferGetPage(cbuf);
@@ -48,23 +37,32 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
/* Iterate over lists */
for (coffno = FirstOffsetNumber; coffno <= cmaxoffno; coffno = OffsetNumberNext(coffno))
{
list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, coffno));
IvfflatList list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, coffno));
startPages[coffno - FirstOffsetNumber] = list->startPage;
}
listInfo.blkno = nextblkno;
nextblkno = IvfflatPageGetOpaque(cpage)->nextblkno;
listInfo.blkno = blkno;
blkno = IvfflatPageGetOpaque(cpage)->nextblkno;
UnlockReleaseBuffer(cbuf);
for (coffno = FirstOffsetNumber; coffno <= cmaxoffno; coffno = OffsetNumberNext(coffno))
{
searchPage = startPages[coffno - FirstOffsetNumber];
insertPage = InvalidBlockNumber;
BlockNumber searchPage = startPages[coffno - FirstOffsetNumber];
BlockNumber insertPage = InvalidBlockNumber;
/* Iterate over entry pages */
while (BlockNumberIsValid(searchPage))
{
Buffer buf;
Page page;
GenericXLogState *state;
OffsetNumber offno;
OffsetNumber maxoffno;
OffsetNumber deletable[MaxOffsetNumber];
int ndeletable;
vacuum_delay_point();
buf = ReadBufferExtended(index, MAIN_FORKNUM, searchPage, RBM_NORMAL, bas);
@@ -86,8 +84,8 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
/* Find deleted tuples */
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
itup = (IndexTuple) PageGetItem(page, PageGetItemId(page, offno));
htup = &(itup->t_tid);
IndexTuple itup = (IndexTuple) PageGetItem(page, PageGetItemId(page, offno));
ItemPointer htup = &(itup->t_tid);
if (callback(htup, callback_state))
{
@@ -109,7 +107,6 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
{
/* Delete tuples */
PageIndexMultiDelete(page, deletable, ndeletable);
MarkBufferDirty(buf);
GenericXLogFinish(state);
}
else
@@ -127,11 +124,13 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
if (BlockNumberIsValid(insertPage))
{
listInfo.offno = coffno;
IvfflatUpdateList(index, state, listInfo, insertPage, InvalidBlockNumber, InvalidBlockNumber, MAIN_FORKNUM);
IvfflatUpdateList(index, listInfo, insertPage, InvalidBlockNumber, InvalidBlockNumber, MAIN_FORKNUM);
}
}
}
FreeAccessStrategy(bas);
return stats;
}

View File

@@ -2,15 +2,22 @@
#include <math.h>
#include "vector.h"
#include "fmgr.h"
#include "catalog/pg_type.h"
#include "fmgr.h"
#include "hnsw.h"
#include "ivfflat.h"
#include "lib/stringinfo.h"
#include "libpq/pqformat.h"
#include "port.h" /* for strtof() */
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/lsyscache.h"
#include "utils/numeric.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 120000
#include "common/shortest_dec.h"
@@ -29,6 +36,17 @@
PG_MODULE_MAGIC;
/*
* Initialize index options and variables
*/
PGDLLEXPORT void _PG_init(void);
void
_PG_init(void)
{
HnswInit();
IvfflatInit();
}
/*
* Ensure same dimensions
*/
@@ -42,7 +60,7 @@ CheckDims(Vector * a, Vector * b)
}
/*
* Ensure expected dimension
* Ensure expected dimensions
*/
static inline void
CheckExpectedDim(int32 typmod, int dim)
@@ -53,7 +71,9 @@ CheckExpectedDim(int32 typmod, int dim)
errmsg("expected %d dimensions, not %d", typmod, dim)));
}
/*
* Ensure valid dimensions
*/
static inline void
CheckDim(int dim)
{
@@ -69,7 +89,7 @@ CheckDim(int dim)
}
/*
* Ensure finite elements
* Ensure finite element
*/
static inline void
CheckElement(float value)
@@ -79,13 +99,45 @@ CheckElement(float value)
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("NaN not allowed in vector")));
if (isinf(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("infinite value not allowed in vector")));
}
/*
* Allocate and initialize a new vector
*/
Vector *
InitVector(int dim)
{
Vector *result;
int size;
size = VECTOR_SIZE(dim);
result = (Vector *) palloc0(size);
SET_VARSIZE(result, size);
result->dim = dim;
return result;
}
/*
* Check for whitespace, since array_isspace() is static
*/
static inline bool
vector_isspace(char ch)
{
if (ch == ' ' ||
ch == '\t' ||
ch == '\n' ||
ch == '\r' ||
ch == '\v' ||
ch == '\f')
return true;
return false;
}
/*
* Check state array
*/
@@ -100,7 +152,7 @@ CheckStateArray(ArrayType *statearray, const char *caller)
return (float8 *) ARR_DATA_PTR(statearray);
}
#if PG_VERSION_NUM < 120000
#if PG_VERSION_NUM < 120003
static pg_noinline void
float_overflow_error(void)
{
@@ -108,31 +160,15 @@ float_overflow_error(void)
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("value out of range: overflow")));
}
#endif
/*
* Print vector - useful for debugging
*/
void
PrintVector(char *msg, Vector * vector)
static pg_noinline void
float_underflow_error(void)
{
StringInfoData buf;
int dim = vector->dim;
int i;
initStringInfo(&buf);
appendStringInfoChar(&buf, '[');
for (i = 0; i < dim; i++)
{
if (i > 0)
appendStringInfoString(&buf, ",");
appendStringInfoString(&buf, float8out_internal(vector->x[i]));
}
appendStringInfoChar(&buf, ']');
elog(INFO, "%s = %s", msg, buf.data);
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("value out of range: underflow")));
}
#endif
/*
* Convert textual representation to internal representation
@@ -143,17 +179,20 @@ vector_in(PG_FUNCTION_ARGS)
{
char *str = PG_GETARG_CSTRING(0);
int32 typmod = PG_GETARG_INT32(2);
int i;
float x[VECTOR_MAX_DIM];
int dim = 0;
char *pt;
char *stringEnd;
Vector *result;
char *lit = pstrdup(str);
while (vector_isspace(*str))
str++;
if (*str != '[')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", str),
errmsg("malformed vector literal: \"%s\"", lit),
errdetail("Vector contents must start with \"[\".")));
str++;
@@ -167,6 +206,15 @@ vector_in(PG_FUNCTION_ARGS)
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("vector cannot have more than %d dimensions", VECTOR_MAX_DIM)));
while (vector_isspace(*pt))
pt++;
/* Check for empty string like float4in */
if (*pt == '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
/* Use strtof like float4in to avoid a double-rounding problem */
x[dim] = strtof(pt, &stringEnd);
CheckElement(x[dim]);
@@ -175,37 +223,57 @@ vector_in(PG_FUNCTION_ARGS)
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", pt)));
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
while (vector_isspace(*stringEnd))
stringEnd++;
if (*stringEnd != '\0' && *stringEnd != ']')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", pt)));
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
pt = strtok(NULL, ",");
}
if (*stringEnd != ']')
if (stringEnd == NULL || *stringEnd != ']')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal"),
errmsg("malformed vector literal: \"%s\"", lit),
errdetail("Unexpected end of input.")));
if (stringEnd[1] != '\0')
stringEnd++;
/* Only whitespace is allowed after the closing brace */
while (vector_isspace(*stringEnd))
stringEnd++;
if (*stringEnd != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal"),
errmsg("malformed vector literal: \"%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);
CheckExpectedDim(typmod, dim);
result = InitVector(dim);
for (i = 0; i < dim; i++)
for (int i = 0; i < dim; i++)
result->x[i] = x[i];
PG_RETURN_POINTER(result);
@@ -222,7 +290,6 @@ vector_out(PG_FUNCTION_ARGS)
int dim = vector->dim;
char *buf;
char *ptr;
int i;
int n;
#if PG_VERSION_NUM < 120000
@@ -249,7 +316,7 @@ vector_out(PG_FUNCTION_ARGS)
*ptr = '[';
ptr++;
for (i = 0; i < dim; i++)
for (int i = 0; i < dim; i++)
{
if (i > 0)
{
@@ -272,6 +339,18 @@ vector_out(PG_FUNCTION_ARGS)
PG_RETURN_CSTRING(buf);
}
/*
* Print vector - useful for debugging
*/
void
PrintVector(char *msg, Vector * vector)
{
char *out = DatumGetPointer(DirectFunctionCall1(vector_out, PointerGetDatum(vector)));
elog(INFO, "%s = %s", msg, out);
pfree(out);
}
/*
* Convert type modifier
*/
@@ -315,7 +394,6 @@ vector_recv(PG_FUNCTION_ARGS)
Vector *result;
int16 dim;
int16 unused;
int i;
dim = pq_getmsgint(buf, sizeof(int16));
unused = pq_getmsgint(buf, sizeof(int16));
@@ -329,8 +407,11 @@ vector_recv(PG_FUNCTION_ARGS)
errmsg("expected unused to be 0, not %d", unused)));
result = InitVector(dim);
for (i = 0; i < dim; i++)
for (int i = 0; i < dim; i++)
{
result->x[i] = pq_getmsgfloat4(buf);
CheckElement(result->x[i]);
}
PG_RETURN_POINTER(result);
}
@@ -344,12 +425,11 @@ vector_send(PG_FUNCTION_ARGS)
{
Vector *vec = PG_GETARG_VECTOR_P(0);
StringInfoData buf;
int i;
pq_begintypsend(&buf);
pq_sendint(&buf, vec->dim, sizeof(int16));
pq_sendint(&buf, vec->unused, sizeof(int16));
for (i = 0; i < vec->dim; i++)
for (int i = 0; i < vec->dim; i++)
pq_sendfloat4(&buf, vec->x[i]);
PG_RETURN_BYTEA_P(pq_endtypsend(&buf));
@@ -357,17 +437,18 @@ vector_send(PG_FUNCTION_ARGS)
/*
* Convert vector to vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector);
Datum
vector(PG_FUNCTION_ARGS)
{
Vector *arg = PG_GETARG_VECTOR_P(0);
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
CheckExpectedDim(typmod, arg->dim);
CheckExpectedDim(typmod, vec->dim);
PG_RETURN_POINTER(arg);
PG_RETURN_POINTER(vec);
}
/*
@@ -379,13 +460,11 @@ array_to_vector(PG_FUNCTION_ARGS)
{
ArrayType *array = PG_GETARG_ARRAYTYPE_P(0);
int32 typmod = PG_GETARG_INT32(1);
int i;
Vector *result;
int16 typlen;
bool typbyval;
char typalign;
Datum *elemsp;
bool *nullsp;
int nelemsp;
if (ARR_NDIM(array) > 1)
@@ -393,37 +472,55 @@ array_to_vector(PG_FUNCTION_ARGS)
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("array must be 1-D")));
get_typlenbyvalalign(ARR_ELEMTYPE(array), &typlen, &typbyval, &typalign);
deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, &nullsp, &nelemsp);
if (ARR_HASNULL(array) && array_contains_nulls(array))
ereport(ERROR,
(errcode(ERRCODE_NULL_VALUE_NOT_ALLOWED),
errmsg("array must not contain nulls")));
if (typmod == -1)
CheckDim(nelemsp);
else
CheckExpectedDim(typmod, nelemsp);
get_typlenbyvalalign(ARR_ELEMTYPE(array), &typlen, &typbyval, &typalign);
deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, NULL, &nelemsp);
CheckDim(nelemsp);
CheckExpectedDim(typmod, nelemsp);
result = InitVector(nelemsp);
for (i = 0; i < nelemsp; i++)
if (ARR_ELEMTYPE(array) == INT4OID)
{
if (nullsp[i])
ereport(ERROR,
(errcode(ERRCODE_NULL_VALUE_NOT_ALLOWED),
errmsg("array must not containing NULLs")));
if (ARR_ELEMTYPE(array) == INT4OID)
for (int i = 0; i < nelemsp; i++)
result->x[i] = DatumGetInt32(elemsp[i]);
else if (ARR_ELEMTYPE(array) == FLOAT8OID)
result->x[i] = DatumGetFloat8(elemsp[i]);
else if (ARR_ELEMTYPE(array) == FLOAT4OID)
result->x[i] = DatumGetFloat4(elemsp[i]);
else if (ARR_ELEMTYPE(array) == NUMERICOID)
result->x[i] = DatumGetFloat4(DirectFunctionCall1(numeric_float4, elemsp[i]));
else
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("unsupported array type")));
CheckElement(result->x[i]);
}
else if (ARR_ELEMTYPE(array) == FLOAT8OID)
{
for (int i = 0; i < nelemsp; i++)
result->x[i] = DatumGetFloat8(elemsp[i]);
}
else if (ARR_ELEMTYPE(array) == FLOAT4OID)
{
for (int i = 0; i < nelemsp; i++)
result->x[i] = DatumGetFloat4(elemsp[i]);
}
else if (ARR_ELEMTYPE(array) == NUMERICOID)
{
for (int i = 0; i < nelemsp; i++)
result->x[i] = DatumGetFloat4(DirectFunctionCall1(numeric_float4, elemsp[i]));
}
else
{
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("unsupported array type")));
}
/*
* Free allocation from deconstruct_array. Do not free individual elements
* when pass-by-reference since they point to original array.
*/
pfree(elemsp);
/* Check elements */
for (int i = 0; i < result->dim; i++)
CheckElement(result->x[i]);
PG_RETURN_POINTER(result);
}
@@ -436,17 +533,18 @@ Datum
vector_to_float4(PG_FUNCTION_ARGS)
{
Vector *vec = PG_GETARG_VECTOR_P(0);
Datum *d;
Datum *datums;
ArrayType *result;
int i;
d = (Datum *) palloc(sizeof(Datum) * vec->dim);
datums = (Datum *) palloc(sizeof(Datum) * vec->dim);
for (i = 0; i < vec->dim; i++)
d[i] = Float4GetDatum(vec->x[i]);
for (int i = 0; i < vec->dim; i++)
datums[i] = Float4GetDatum(vec->x[i]);
/* Use TYPALIGN_INT for float4 */
result = construct_array(d, vec->dim, FLOAT4OID, sizeof(float4), true, TYPALIGN_INT);
result = construct_array(datums, vec->dim, FLOAT4OID, sizeof(float4), true, TYPALIGN_INT);
pfree(datums);
PG_RETURN_POINTER(result);
}
@@ -462,18 +560,19 @@ l2_distance(PG_FUNCTION_ARGS)
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
double distance = 0.0;
double diff;
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(distance));
PG_RETURN_FLOAT8(sqrt((double) distance));
}
/*
@@ -488,18 +587,19 @@ vector_l2_squared_distance(PG_FUNCTION_ARGS)
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
double distance = 0.0;
double diff;
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(distance);
PG_RETURN_FLOAT8((double) distance);
}
/*
@@ -513,14 +613,15 @@ inner_product(PG_FUNCTION_ARGS)
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
double distance = 0.0;
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(distance);
PG_RETURN_FLOAT8((double) distance);
}
/*
@@ -534,14 +635,15 @@ vector_negative_inner_product(PG_FUNCTION_ARGS)
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
double distance = 0.0;
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(distance * -1);
PG_RETURN_FLOAT8((double) distance * -1);
}
/*
@@ -555,12 +657,14 @@ cosine_distance(PG_FUNCTION_ARGS)
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
double distance = 0.0;
double norma = 0.0;
double normb = 0.0;
float distance = 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++)
{
distance += ax[i] * bx[i];
@@ -569,7 +673,21 @@ cosine_distance(PG_FUNCTION_ARGS)
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
PG_RETURN_FLOAT8(1 - (distance / sqrt(norma * normb)));
similarity = (double) distance / sqrt((double) norma * (double) normb);
#ifdef _MSC_VER
/* /fp:fast may not propagate NaN */
if (isnan(similarity))
PG_RETURN_FLOAT8(NAN);
#endif
/* Keep in range */
if (similarity > 1)
similarity = 1.0;
else if (similarity < -1)
similarity = -1.0;
PG_RETURN_FLOAT8(1.0 - similarity);
}
/*
@@ -583,12 +701,18 @@ vector_spherical_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
double distance = 0.0;
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++)
distance += a->x[i] * b->x[i];
dp += ax[i] * bx[i];
distance = (double) dp;
/* Prevent NaN with acos with loss of precision */
if (distance > 1)
@@ -599,6 +723,28 @@ vector_spherical_distance(PG_FUNCTION_ARGS)
PG_RETURN_FLOAT8(acos(distance) / M_PI);
}
/*
* Get the L1 distance between vectors
*/
PGDLLEXPORT 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);
}
/*
* Get the dimensions of a vector
*/
@@ -622,8 +768,9 @@ vector_norm(PG_FUNCTION_ARGS)
float *ax = a->x;
double norm = 0.0;
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
norm += ax[i] * ax[i];
norm += (double) ax[i] * (double) ax[i];
PG_RETURN_FLOAT8(sqrt(norm));
}
@@ -646,9 +793,18 @@ vector_add(PG_FUNCTION_ARGS)
result = InitVector(a->dim);
rx = result->x;
/* Auto-vectorized */
for (int i = 0, imax = a->dim; i < imax; i++)
rx[i] = ax[i] + bx[i];
/* Check for overflow */
for (int i = 0, imax = a->dim; i < imax; i++)
{
if (isinf(rx[i]))
float_overflow_error();
}
PG_RETURN_POINTER(result);
}
@@ -670,9 +826,54 @@ vector_sub(PG_FUNCTION_ARGS)
result = InitVector(a->dim);
rx = result->x;
/* Auto-vectorized */
for (int i = 0, imax = a->dim; i < imax; i++)
rx[i] = ax[i] - bx[i];
/* Check for overflow */
for (int i = 0, imax = a->dim; i < imax; i++)
{
if (isinf(rx[i]))
float_overflow_error();
}
PG_RETURN_POINTER(result);
}
/*
* Multiply vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_mul);
Datum
vector_mul(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;
Vector *result;
float *rx;
CheckDims(a, b);
result = InitVector(a->dim);
rx = result->x;
/* Auto-vectorized */
for (int i = 0, imax = a->dim; i < imax; i++)
rx[i] = ax[i] * bx[i];
/* Check for overflow and underflow */
for (int i = 0, imax = a->dim; i < imax; i++)
{
if (isinf(rx[i]))
float_overflow_error();
if (rx[i] == 0 && !(ax[i] == 0 || bx[i] == 0))
float_underflow_error();
}
PG_RETURN_POINTER(result);
}
@@ -682,11 +883,9 @@ vector_sub(PG_FUNCTION_ARGS)
int
vector_cmp_internal(Vector * a, Vector * b)
{
int i;
CheckDims(a, b);
for (i = 0; i < a->dim; i++)
for (int i = 0; i < a->dim; i++)
{
if (a->x[i] < b->x[i])
return -1;
@@ -818,12 +1017,12 @@ vector_accum(PG_FUNCTION_ARGS)
n = statevalues[0] + 1.0;
statedatums = CreateStateDatums(dim);
statedatums[0] = Float8GetDatumFast(n);
statedatums[0] = Float8GetDatum(n);
if (newarr)
{
for (int i = 0; i < dim; i++)
statedatums[i + 1] = Float8GetDatumFast((double) x[i]);
statedatums[i + 1] = Float8GetDatum((double) x[i]);
}
else
{
@@ -831,10 +1030,11 @@ vector_accum(PG_FUNCTION_ARGS)
{
double v = statevalues[i + 1] + x[i];
/* Check for overflow */
if (isinf(v))
float_overflow_error();
statedatums[i + 1] = Float8GetDatumFast(v);
statedatums[i + 1] = Float8GetDatum(v);
}
}
@@ -879,7 +1079,7 @@ vector_combine(PG_FUNCTION_ARGS)
dim = STATE_DIMS(statearray2);
statedatums = CreateStateDatums(dim);
for (int i = 1; i <= dim; i++)
statedatums[i] = Float8GetDatumFast(statevalues2[i]);
statedatums[i] = Float8GetDatum(statevalues2[i]);
}
else if (n2 == 0.0)
{
@@ -887,7 +1087,7 @@ vector_combine(PG_FUNCTION_ARGS)
dim = STATE_DIMS(statearray1);
statedatums = CreateStateDatums(dim);
for (int i = 1; i <= dim; i++)
statedatums[i] = Float8GetDatumFast(statevalues1[i]);
statedatums[i] = Float8GetDatum(statevalues1[i]);
}
else
{
@@ -899,14 +1099,15 @@ vector_combine(PG_FUNCTION_ARGS)
{
double v = statevalues1[i] + statevalues2[i];
/* Check for overflow */
if (isinf(v))
float_overflow_error();
statedatums[i] = Float8GetDatumFast(v);
statedatums[i] = Float8GetDatum(v);
}
}
statedatums[0] = Float8GetDatumFast(n);
statedatums[0] = Float8GetDatum(n);
result = construct_array(statedatums, dim + 1,
FLOAT8OID,
@@ -929,7 +1130,6 @@ vector_avg(PG_FUNCTION_ARGS)
float8 n;
uint16 dim;
Vector *result;
float v;
/* Check array before using */
statevalues = CheckStateArray(statearray, "vector_avg");
@@ -941,12 +1141,12 @@ vector_avg(PG_FUNCTION_ARGS)
/* Create vector */
dim = STATE_DIMS(statearray);
CheckDim(dim);
result = InitVector(dim);
for (int i = 0; i < dim; i++)
{
v = statevalues[i + 1] / n;
CheckElement(v);
result->x[i] = v;
result->x[i] = statevalues[i + 1] / n;
CheckElement(result->x[i]);
}
PG_RETURN_POINTER(result);

View File

@@ -1,12 +1,6 @@
#ifndef VECTOR_H
#define VECTOR_H
#include "postgres.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#define VECTOR_MAX_DIM 16000
#define VECTOR_SIZE(_dim) (offsetof(Vector, x) + sizeof(float)*(_dim))
@@ -22,24 +16,8 @@ typedef struct Vector
float x[FLEXIBLE_ARRAY_MEMBER];
} Vector;
Vector *InitVector(int dim);
void PrintVector(char *msg, Vector * vector);
int vector_cmp_internal(Vector * a, Vector * b);
/*
* Allocate and initialize a new vector
*/
static inline Vector *
InitVector(int dim)
{
Vector *result;
int size;
size = VECTOR_SIZE(dim);
result = (Vector *) palloc0(size);
SET_VARSIZE(result, size);
result->dim = dim;
return result;
}
#endif

View File

@@ -29,7 +29,7 @@ SELECT ARRAY[1,2,3]::numeric[]::vector;
(1 row)
SELECT '{NULL}'::real[]::vector;
ERROR: array must not containing NULLs
ERROR: array must not contain nulls
SELECT '{NaN}'::real[]::vector;
ERROR: NaN not allowed in vector
SELECT '{Infinity}'::real[]::vector;
@@ -38,6 +38,8 @@ SELECT '{-Infinity}'::real[]::vector;
ERROR: infinite value not allowed in vector
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
---------
@@ -46,6 +48,8 @@ SELECT '[1,2,3]'::vector::real[];
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
ERROR: vector cannot have more than 16000 dimensions
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;
ERROR: vector cannot have more than 16000 dimensions
-- ensure no error
SELECT ARRAY[1,2,3] = ARRAY[1,2,3];
?column?

View File

@@ -4,12 +4,26 @@ SELECT '[1,2,3]'::vector + '[4,5,6]';
[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
-------------
@@ -22,14 +36,44 @@ SELECT round(vector_norm('[1,1]')::numeric, 5);
1.41421
(1 row)
SELECT round(l2_distance('[1,2]', '[0,0]')::numeric, 5);
round
---------
2.23607
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
---------------
@@ -38,10 +82,16 @@ SELECT inner_product('[1,2]', '[3,4]');
SELECT inner_product('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT round(cosine_distance('[1,2]', '[2,4]')::numeric, 5);
round
---------
0.00000
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]');
@@ -56,6 +106,12 @@ SELECT cosine_distance('[1,1]', '[1,1]');
0
(1 row)
SELECT cosine_distance('[1,0]', '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]', '[-1,-1]');
cosine_distance
-----------------
@@ -64,6 +120,44 @@ SELECT cosine_distance('[1,1]', '[-1,-1]');
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
-----------
@@ -84,3 +178,33 @@ SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
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

View File

@@ -0,0 +1,26 @@
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;

21
test/expected/hnsw_ip.out Normal file
View File

@@ -0,0 +1,21 @@
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;

36
test/expected/hnsw_l2.out Normal file
View File

@@ -0,0 +1,36 @@
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

@@ -0,0 +1,26 @@
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 +1,13 @@
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

@@ -4,10 +4,22 @@ SELECT '[1,2,3]'::vector;
[1,2,3]
(1 row)
SELECT '[-1,2,3]'::vector;
vector
----------
[-1,2,3]
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;
@@ -17,7 +29,7 @@ SELECT '[1.23456]'::vector;
(1 row)
SELECT '[hello,1]'::vector;
ERROR: invalid input syntax for type vector: "hello"
ERROR: invalid input syntax for type vector: "[hello,1]"
LINE 1: SELECT '[hello,1]'::vector;
^
SELECT '[NaN,1]'::vector;
@@ -32,13 +44,35 @@ 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
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
ERROR: malformed vector literal: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::vector;
^
DETAIL: Junk after closing right brace.
@@ -47,14 +81,41 @@ 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: "]"
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[]);

View File

@@ -11,9 +11,16 @@ SELECT * FROM t ORDER BY val <=> '[3,3,3]';
[1,2,4]
(3 rows)
SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector);
val
-----
(0 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

@@ -12,9 +12,10 @@ SELECT * FROM t ORDER BY val <#> '[3,3,3]';
[0,0,0]
(4 rows)
SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector);
val
-----
(0 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

@@ -1,7 +1,7 @@
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) WITH (lists = 1);
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
@@ -13,9 +13,13 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
(4 rows)
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
val
-----
(0 rows)
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM t;
count
@@ -23,4 +27,13 @@ SELECT COUNT(*) FROM t;
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

@@ -1,9 +1,8 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING ivfflat (val) WITH (lists = 0);
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) WITH (lists = 32769);
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;

View File

@@ -1,7 +1,7 @@
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) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------

View File

@@ -8,8 +8,10 @@ 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 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;
-- ensure no error
SELECT ARRAY[1,2,3] = ARRAY[1,2,3];

View File

@@ -1,22 +1,51 @@
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 round(l2_distance('[1,2]', '[0,0]')::numeric, 5);
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 round(cosine_distance('[1,2]', '[2,4]')::numeric, 5);
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;

13
test/sql/hnsw_cosine.sql Normal file
View File

@@ -0,0 +1,13 @@
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;

12
test/sql/hnsw_ip.sql Normal file
View File

@@ -0,0 +1,12 @@
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;

16
test/sql/hnsw_l2.sql Normal file
View File

@@ -0,0 +1,16 @@
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;

13
test/sql/hnsw_options.sql Normal file
View File

@@ -0,0 +1,13 @@
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;

View File

@@ -0,0 +1,9 @@
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;

View File

@@ -1,15 +1,27 @@
SELECT '[1,2,3]'::vector;
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[]);

View File

@@ -7,6 +7,7 @@ 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 * FROM t ORDER BY val <=> (SELECT NULL::vector);
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;

View File

@@ -7,6 +7,6 @@ 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 * FROM t ORDER BY val <#> (SELECT NULL::vector);
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
DROP TABLE t;

View File

@@ -2,7 +2,7 @@ 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) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
@@ -10,4 +10,7 @@ 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;

View File

@@ -1,8 +1,6 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING ivfflat (val) WITH (lists = 0);
CREATE INDEX ON t USING ivfflat (val) WITH (lists = 32769);
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;

View File

@@ -2,7 +2,7 @@ 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) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';

View File

@@ -5,7 +5,7 @@ use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More tests => 31;
use Test::More;
my $dim = 32;
@@ -19,14 +19,13 @@ sub test_index_replay
# Wait for replica to catch up
my $applname = $node_replica->name;
my $server_version_num = $node_primary->safe_psql("postgres", "SHOW server_version_num");
my $caughtup_query = "SELECT pg_current_wal_lsn() <= replay_lsn FROM pg_stat_replication WHERE application_name = '$applname';";
$node_primary->poll_query_until('postgres', $caughtup_query)
or die "Timed out while waiting for replica 1 to catch up";
my @r = ();
for (1 .. $dim) {
for (1 .. $dim)
{
push(@r, rand());
}
my $sql = join(",", @r);
@@ -52,11 +51,13 @@ my $array_sql = join(",", ('random()') x $dim);
# Initialize primary node
$node_primary = get_new_node('primary');
$node_primary->init(allows_streaming => 1);
if ($dim > 32) {
if ($dim > 32)
{
# TODO use wal_keep_segments for Postgres < 13
$node_primary->append_conf('postgresql.conf', qq(wal_keep_size = 1GB));
}
if ($dim > 1500) {
if ($dim > 1500)
{
$node_primary->append_conf('postgresql.conf', qq(maintenance_work_mem = 128MB));
}
$node_primary->start;
@@ -67,8 +68,7 @@ $node_primary->backup($backup_name);
# Create streaming replica linking to primary
$node_replica = get_new_node('replica');
$node_replica->init_from_backup($node_primary, $backup_name,
has_streaming => 1);
$node_replica->init_from_backup($node_primary, $backup_name, has_streaming => 1);
$node_replica->start;
# Create ivfflat index on primary
@@ -77,7 +77,7 @@ $node_primary->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));
$node_primary->safe_psql("postgres",
"INSERT INTO tst SELECT i % 10, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
);
$node_primary->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v);");
$node_primary->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);");
# Test that queries give same result
test_index_replay('initial');
@@ -95,3 +95,5 @@ for my $i (1 .. 10)
);
test_index_replay("insert $i");
}
done_testing();

View File

@@ -2,12 +2,13 @@ use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More tests => 1;
use Test::More;
my $dim = 3;
my @r = ();
for (1 .. $dim) {
for (1 .. $dim)
{
my $v = int(rand(1000)) + 1;
push(@r, "i % $v");
}
@@ -24,7 +25,7 @@ $node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i % 10, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v);");
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);");
# Get size
my $size = $node->safe_psql("postgres", "SELECT pg_total_relation_size('tst_v_idx');");
@@ -39,3 +40,5 @@ $node->safe_psql("postgres",
# Check size
my $new_size = $node->safe_psql("postgres", "SELECT pg_total_relation_size('tst_v_idx');");
is($size, $new_size, "size does not change");
done_testing();

View File

@@ -0,0 +1,128 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
sub test_recall
{
my ($probes, $min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan using idx on tst/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
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]);
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
}
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$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, 100000) i;"
);
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "[$r1,$r2,$r3]");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("vector_l2_ops", "vector_ip_ops", "vector_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", "SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;");
push(@expected, $res);
}
# Build index serially
$node->safe_psql("postgres", qq(
SET max_parallel_maintenance_workers = 0;
CREATE INDEX idx ON tst USING ivfflat (v $opclass);
));
# Test approximate results
if ($operator ne "<#>")
{
# TODO Fix test (uniform random vectors all have similar inner product)
test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator);
}
# Account for equal distances
test_recall(100, 0.9925, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
CREATE INDEX idx ON tst USING ivfflat (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
if ($operator ne "<#>")
{
# TODO Fix test (uniform random vectors all have similar inner product)
test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator);
}
# Account for equal distances
test_recall(100, 0.9925, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

View File

@@ -2,7 +2,7 @@ use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More tests => 3;
use Test::More;
# Initialize node
my $node = get_new_node('node');
@@ -20,7 +20,7 @@ sub test_centers
{
my ($lists, $min) = @_;
my ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING ivfflat (v) WITH (lists = $lists);");
my ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops) WITH (lists = $lists);");
is($ret, 0, $stderr);
}
@@ -34,3 +34,5 @@ $node->safe_psql("postgres",
# Test no error for duplicate centers
test_centers(10);
done_testing();

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@@ -2,7 +2,7 @@ use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More tests => 60;
use Test::More;
# Initialize node
my $node = get_new_node('node');
@@ -18,24 +18,21 @@ $node->safe_psql("postgres",
# Check each index type
my @operators = ("<->", "<#>", "<=>");
foreach (@operators) {
my $operator = $_;
my @opclasses = ("vector_l2_ops", "vector_ip_ops", "vector_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Add index
my $opclass;
if ($operator == "<->") {
$opclass = "vector_l2_ops";
} elsif ($operator == "<#>") {
$opclass = "vector_ip_ops";
} else {
$opclass = "vector_cosine_ops";
}
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v $opclass);");
# Test 100% recall
for (1..20) {
my $i = int(rand() * 100000);
my $query = $node->safe_psql("postgres", "SELECT v FROM tst WHERE i = $i;");
for (1 .. 20)
{
my $id = int(rand() * 100000);
my $query = $node->safe_psql("postgres", "SELECT v FROM tst WHERE i = $id;");
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SELECT v FROM tst ORDER BY v <-> '$query' LIMIT 1;
@@ -43,3 +40,5 @@ foreach (@operators) {
is($res, $query);
}
}
done_testing();

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@@ -2,7 +2,7 @@ use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More tests => 3;
use Test::More;
# Initialize node
my $node = get_new_node('node');
@@ -16,8 +16,8 @@ $node->safe_psql("postgres",
"INSERT INTO tst SELECT ARRAY[random(), random(), random()] FROM generate_series(1, 100000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX lists50 ON tst USING ivfflat (v) WITH (lists = 50);");
$node->safe_psql("postgres", "CREATE INDEX lists100 ON tst USING ivfflat (v) WITH (lists = 100);");
$node->safe_psql("postgres", "CREATE INDEX lists50 ON tst USING ivfflat (v vector_l2_ops) WITH (lists = 50);");
$node->safe_psql("postgres", "CREATE INDEX lists100 ON tst USING ivfflat (v vector_l2_ops) WITH (lists = 100);");
# Test prefers more lists
my $res = $node->safe_psql("postgres", "EXPLAIN SELECT v FROM tst ORDER BY v <-> '[0.5,0.5,0.5]' LIMIT 10;");
@@ -26,6 +26,8 @@ unlike($res, qr/lists50/);
# Test errors with too much memory
my ($ret, $stdout, $stderr) = $node->psql("postgres",
"CREATE INDEX lists10000 ON tst USING ivfflat (v) WITH (lists = 10000);"
"CREATE INDEX lists10000 ON tst USING ivfflat (v vector_l2_ops) WITH (lists = 10000);"
);
like($stderr, qr/memory required is/);
done_testing();

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@@ -2,7 +2,7 @@ use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More tests => 7;
use Test::More;
my $dim = 768;
@@ -19,7 +19,7 @@ $node->safe_psql("postgres", "CREATE TABLE tst (v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT ARRAY[$array_sql] FROM generate_series(1, 10000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v);");
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);");
$node->pgbench(
"--no-vacuum --client=5 --transactions=100",
@@ -28,7 +28,7 @@ $node->pgbench(
[qr{^$}],
"concurrent INSERTs",
{
"007_inserts" => "INSERT INTO tst SELECT ARRAY[$array_sql] FROM generate_series(1, 10) i;"
"007_ivfflat_inserts" => "INSERT INTO tst SELECT ARRAY[$array_sql] FROM generate_series(1, 10) i;"
}
);
@@ -53,3 +53,5 @@ $count = $node->safe_psql("postgres", qq(
));
is($count, $expected);
is(idx_scan(), 1);
done_testing();

49
test/t/008_aggregates.pl Normal file
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@@ -0,0 +1,49 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
# Initialize node
my $node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (r1 real, r2 real, r3 real, v vector(3));");
$node->safe_psql("postgres", qq(
INSERT INTO tst SELECT r1, r2, r3, ARRAY[r1, r2, r3] FROM (
SELECT random() + 1.01 AS r1, random() + 2.01 AS r2, random() + 3.01 AS r3 FROM generate_series(1, 1000000) t
) i;
));
sub test_aggregate
{
my ($agg) = @_;
# Test value
my $res = $node->safe_psql("postgres", "SELECT $agg(v) FROM tst;");
like($res, qr/\[1\.5/);
like($res, qr/,2\.5/);
like($res, qr/,3\.5/);
# Test matches real for avg
# Cannot test sum since sum(real) varies between calls
if ($agg eq 'avg')
{
my $r1 = $node->safe_psql("postgres", "SELECT $agg(r1)::float4 FROM tst;");
my $r2 = $node->safe_psql("postgres", "SELECT $agg(r2)::float4 FROM tst;");
my $r3 = $node->safe_psql("postgres", "SELECT $agg(r3)::float4 FROM tst;");
is($res, "[$r1,$r2,$r3]");
}
# Test explain
my $explain = $node->safe_psql("postgres", "EXPLAIN SELECT $agg(v) FROM tst;");
like($explain, qr/Partial Aggregate/);
}
test_aggregate('avg');
test_aggregate('sum');
done_testing();

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@@ -1,35 +0,0 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More tests => 5;
# Initialize node
my $node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (r1 real, r2 real, r3 real, v vector(3));");
$node->safe_psql("postgres", qq(
INSERT INTO tst SELECT r1, r2, r3, ARRAY[r1, r2, r3] FROM (
SELECT random() + 1.01 AS r1, random() + 2.01 AS r2, random() + 3.01 AS r3 FROM generate_series(1, 1000000) t
) i;
));
# Test avg
my $avg = $node->safe_psql("postgres", "SELECT AVG(v) FROM tst;");
like($avg, qr/\[1\.5/);
like($avg, qr/,2\.5/);
like($avg, qr/,3\.5/);
# Test matches real
my $r1 = $node->safe_psql("postgres", "SELECT AVG(r1)::float4 FROM tst;");
my $r2 = $node->safe_psql("postgres", "SELECT AVG(r2)::float4 FROM tst;");
my $r3 = $node->safe_psql("postgres", "SELECT AVG(r3)::float4 FROM tst;");
is($avg, "[$r1,$r2,$r3]");
# Test explain
my $explain = $node->safe_psql("postgres", "EXPLAIN SELECT AVG(v) FROM tst;");
like($explain, qr/Partial Aggregate/);

View File

@@ -2,7 +2,7 @@ use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More tests => 1;
use Test::More;
my $dim = 1024;
@@ -30,3 +30,5 @@ my ($ret, $stdout, $stderr) = $node->psql("postgres",
"INSERT INTO tst SELECT array_agg(n), array_agg(n), array_agg(n) FROM generate_series(1, $dim) n"
);
like($stderr, qr/row is too big/);
done_testing();

99
test/t/010_hnsw_wal.pl Normal file
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@@ -0,0 +1,99 @@
# Based on postgres/contrib/bloom/t/001_wal.pl
# Test generic xlog record work for hnsw index replication.
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $dim = 32;
my $node_primary;
my $node_replica;
# Run few queries on both primary and replica and check their results match.
sub test_index_replay
{
my ($test_name) = @_;
# Wait for replica to catch up
my $applname = $node_replica->name;
my $caughtup_query = "SELECT pg_current_wal_lsn() <= replay_lsn FROM pg_stat_replication WHERE application_name = '$applname';";
$node_primary->poll_query_until('postgres', $caughtup_query)
or die "Timed out while waiting for replica 1 to catch up";
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
my $sql = join(",", @r);
my $queries = qq(
SET enable_seqscan = off;
SELECT * FROM tst ORDER BY v <-> '[$sql]' LIMIT 10;
);
# Run test queries and compare their result
my $primary_result = $node_primary->safe_psql("postgres", $queries);
my $replica_result = $node_replica->safe_psql("postgres", $queries);
is($primary_result, $replica_result, "$test_name: query result matches");
return;
}
# Use ARRAY[random(), random(), random(), ...] over
# SELECT array_agg(random()) FROM generate_series(1, $dim)
# to generate different values for each row
my $array_sql = join(",", ('random()') x $dim);
# Initialize primary node
$node_primary = get_new_node('primary');
$node_primary->init(allows_streaming => 1);
if ($dim > 32)
{
# TODO use wal_keep_segments for Postgres < 13
$node_primary->append_conf('postgresql.conf', qq(wal_keep_size = 1GB));
}
if ($dim > 1500)
{
$node_primary->append_conf('postgresql.conf', qq(maintenance_work_mem = 128MB));
}
$node_primary->start;
my $backup_name = 'my_backup';
# Take backup
$node_primary->backup($backup_name);
# Create streaming replica linking to primary
$node_replica = get_new_node('replica');
$node_replica->init_from_backup($node_primary, $backup_name, has_streaming => 1);
$node_replica->start;
# Create hnsw index on primary
$node_primary->safe_psql("postgres", "CREATE EXTENSION vector;");
$node_primary->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
$node_primary->safe_psql("postgres",
"INSERT INTO tst SELECT i % 10, ARRAY[$array_sql] FROM generate_series(1, 1000) i;"
);
$node_primary->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops);");
# Test that queries give same result
test_index_replay('initial');
# Run 10 cycles of table modification. Run test queries after each modification.
for my $i (1 .. 10)
{
$node_primary->safe_psql("postgres", "DELETE FROM tst WHERE i = $i;");
test_index_replay("delete $i");
$node_primary->safe_psql("postgres", "VACUUM tst;");
test_index_replay("vacuum $i");
my ($start, $end) = (1001 + ($i - 1) * 100, 1000 + $i * 100);
$node_primary->safe_psql("postgres",
"INSERT INTO tst SELECT i % 10, ARRAY[$array_sql] FROM generate_series($start, $end) i;"
);
test_index_replay("insert $i");
}
done_testing();

54
test/t/011_hnsw_vacuum.pl Normal file
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@@ -0,0 +1,54 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $dim = 3;
my @r = ();
for (1 .. $dim)
{
my $v = int(rand(1000)) + 1;
push(@r, "i % $v");
}
my $array_sql = join(", ", @r);
# 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));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 10000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops);");
# Get size
my $size = $node->safe_psql("postgres", "SELECT pg_total_relation_size('tst_v_idx');");
# Delete all, vacuum, and insert same data
$node->safe_psql("postgres", "DELETE FROM tst;");
$node->safe_psql("postgres", "VACUUM tst;");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 10000) i;"
);
# Check size
# May increase some due to different levels
my $new_size = $node->safe_psql("postgres", "SELECT pg_total_relation_size('tst_v_idx');");
cmp_ok($new_size, "<=", $size * 1.02, "size does not increase too much");
# Delete all but one
$node->safe_psql("postgres", "DELETE FROM tst WHERE i != 123;");
$node->safe_psql("postgres", "VACUUM tst;");
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SELECT i FROM tst ORDER BY v <-> '[0,0,0]' LIMIT 10;
));
is($res, 123);
done_testing();

View File

@@ -2,7 +2,7 @@ use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More tests => 9;
use Test::More;
my $node;
my @queries = ();
@@ -11,14 +11,20 @@ my $limit = 20;
sub test_recall
{
my ($probes, $min, $operator) = @_;
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
for my $i (0 .. $#queries) {
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
SELECT i FROM tst ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
@@ -26,8 +32,10 @@ sub test_recall
my @expected_ids = split("\n", $expected[$i]);
foreach (@expected_ids) {
if (exists($actual_set{$_})) {
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
@@ -46,11 +54,12 @@ $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, 100000) i;"
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1..20) {
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
@@ -59,30 +68,26 @@ for (1..20) {
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("vector_l2_ops", "vector_ip_ops", "vector_cosine_ops");
foreach (@operators) {
my $operator = $_;
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Get exact results
@expected = ();
foreach (@queries) {
foreach (@queries)
{
my $res = $node->safe_psql("postgres", "SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;");
push(@expected, $res);
}
# Add index
my $opclass;
if ($operator == "<->") {
$opclass = "vector_l2_ops";
} elsif ($operator == "<#>") {
$opclass = "vector_ip_ops";
} else {
$opclass = "vector_cosine_ops";
}
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v $opclass);");
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v $opclass);");
# Test approximate results
test_recall(1, 0.75, $operator);
test_recall(10, 0.95, $operator);
test_recall(100, 1.0, $operator);
my $min = $operator eq "<#>" ? 0.80 : 0.99;
test_recall($min, $operator);
}
done_testing();

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@@ -0,0 +1,108 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
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]);
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
}
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector(3));");
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "[$r1,$r2,$r3]");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("vector_l2_ops", "vector_ip_ops", "vector_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Add index
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v $opclass);");
# Use concurrent inserts
$node->pgbench(
"--no-vacuum --client=10 --transactions=1000",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"013_hnsw_insert_recall_$opclass" => "INSERT INTO tst (v) VALUES (ARRAY[random(), random(), random()]);"
}
);
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;
));
push(@expected, $res);
}
my $min = $operator eq "<#>" ? 0.80 : 0.99;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
$node->safe_psql("postgres", "TRUNCATE tst;");
}
done_testing();

View File

@@ -0,0 +1,74 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
# Ensures elements and neighbors on both same and different pages
my $dim = 1900;
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;");
$node->safe_psql("postgres", "CREATE TABLE tst (v vector($dim));");
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops);");
sub idx_scan
{
# Stats do not update instantaneously
# https://www.postgresql.org/docs/current/monitoring-stats.html#MONITORING-STATS-VIEWS
sleep(1);
$node->safe_psql("postgres", "SELECT idx_scan FROM pg_stat_user_indexes WHERE indexrelid = 'tst_v_idx'::regclass;");
}
for my $i (1 .. 20)
{
$node->pgbench(
"--no-vacuum --client=10 --transactions=1",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"014_hnsw_inserts_$i" => "INSERT INTO tst VALUES (ARRAY[$array_sql]);"
}
);
my $count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SELECT COUNT(*) FROM (SELECT v FROM tst ORDER BY v <-> (SELECT v FROM tst LIMIT 1)) t;
));
is($count, 10);
$node->safe_psql("postgres", "TRUNCATE tst;");
}
$node->pgbench(
"--no-vacuum --client=20 --transactions=5",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"014_hnsw_inserts" => "INSERT INTO tst SELECT ARRAY[$array_sql] FROM generate_series(1, 10) i;"
}
);
my $count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 1000;
SELECT COUNT(*) FROM (SELECT v FROM tst ORDER BY v <-> (SELECT v FROM tst LIMIT 1)) t;
));
# Elements may lose all incoming connections with the HNSW algorithm
# Vacuuming can fix this if one of the elements neighbors is deleted
cmp_ok($count, ">=", 997);
is(idx_scan(), 21);
done_testing();

View File

@@ -0,0 +1,58 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
# Initialize node
my $node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (v vector(3));");
sub insert_vectors
{
for my $i (1 .. 20)
{
$node->safe_psql("postgres", "INSERT INTO tst VALUES ('[1,1,1]');");
}
}
sub test_duplicates
{
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 1;
SELECT COUNT(*) FROM (SELECT * FROM tst ORDER BY v <-> '[1,1,1]') t;
));
is($res, 10);
}
# Test duplicates with build
insert_vectors();
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v vector_l2_ops);");
test_duplicates();
# Reset
$node->safe_psql("postgres", "TRUNCATE tst;");
# Test duplicates with inserts
insert_vectors();
test_duplicates();
# Test fallback path for inserts
$node->pgbench(
"--no-vacuum --client=5 --transactions=100",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"015_hnsw_duplicates" => "INSERT INTO tst VALUES ('[1,1,1]');"
}
);
done_testing();

View File

@@ -0,0 +1,97 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
sub test_recall
{
my ($min, $ef_search, $test_name) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v <-> '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
SELECT i FROM tst ORDER BY v <-> '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my %actual_set = map { $_ => 1 } @actual_ids;
my @expected_ids = split("\n", $expected[$i]);
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
}
}
cmp_ok($correct / $total, ">=", $min, $test_name);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector(3));");
$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 10000) i;"
);
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops) WITH (m = 4, ef_construction = 8);");
# Delete data
$node->safe_psql("postgres", "DELETE FROM tst WHERE i > 2500;");
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "[$r1,$r2,$r3]");
}
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v <-> '$_' LIMIT $limit;
));
push(@expected, $res);
}
test_recall(0.20, $limit, "before vacuum");
test_recall(0.95, 100, "before vacuum");
# TODO Test concurrent inserts with vacuum
$node->safe_psql("postgres", "VACUUM tst;");
test_recall(0.95, $limit, "after vacuum");
done_testing();

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@@ -0,0 +1,117 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
sub test_recall
{
my ($probes, $min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan using idx on tst/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
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]);
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
}
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector(3));");
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "[$r1,$r2,$r3]");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("vector_l2_ops", "vector_ip_ops", "vector_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Add index
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING ivfflat (v $opclass);");
# Use concurrent inserts
$node->pgbench(
"--no-vacuum --client=10 --transactions=1000",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"017_ivfflat_insert_recall_$opclass" => "INSERT INTO tst (v) SELECT ARRAY[random(), random(), random()] FROM generate_series(1, 10) i;"
}
);
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;
));
push(@expected, $res);
}
# Test approximate results
if ($operator ne "<#>")
{
# TODO Fix test (uniform random vectors all have similar inner product)
test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator);
}
# Account for equal distances
test_recall(100, 0.9925, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
$node->safe_psql("postgres", "TRUNCATE tst;");
}
done_testing();

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@@ -0,0 +1,43 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $dim = 3;
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;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst (v) SELECT ARRAY[$array_sql] FROM generate_series(1, 10000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);");
# Delete data
$node->safe_psql("postgres", "DELETE FROM tst WHERE i % 100 != 0;");
my $exp = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v <-> '[0,0,0]';
));
# Run twice to make sure correct tuples marked as dead
for (1 .. 2)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = 100;
SELECT i FROM tst ORDER BY v <-> '[0,0,0]';
));
is($res, $exp);
}
done_testing();

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@@ -0,0 +1,109 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @cs = ();
my @expected;
my $limit = 20;
my $dim = 3;
my $array_sql = join(",", ('random()') x $dim);
my $nc = 50;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $cs[0] ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Cond/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SELECT i FROM tst WHERE c = $cs[$i] ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my %actual_set = map { $_ => 1 } @actual_ids;
is(scalar(@actual_ids), $limit);
my @expected_ids = split("\n", $expected[$i]);
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
}
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim), c int4);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql], i % $nc FROM generate_series(1, 20000) i;"
);
# Generate queries
for (1 .. 20)
{
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
push(@queries, "[" . join(",", @r) . "]");
push(@cs, int(rand() * $nc));
}
# Get exact results
@expected = ();
for my $i (0 .. $#queries)
{
my $res = $node->safe_psql("postgres", "SELECT i FROM tst WHERE c = $cs[$i] ORDER BY v <-> '$queries[$i]' LIMIT $limit;");
push(@expected, $res);
}
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops, c);");
# Test recall
test_recall(0.99, '<->');
# Test vacuum
$node->safe_psql("postgres", "DELETE FROM tst WHERE c > 5;");
$node->safe_psql("postgres", "VACUUM tst;");
# Test columns
my ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (c);");
like($stderr, qr/first column must be a vector/);
($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (c, v vector_l2_ops);");
like($stderr, qr/first column must be a vector/);
($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops, c, c);");
like($stderr, qr/index cannot have more than two columns/);
($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops, v vector_l2_ops);");
like($stderr, qr/column 2 cannot be a vector/);
done_testing();

View File

@@ -1,4 +1,4 @@
comment = 'vector data type and ivfflat access method'
default_version = '0.4.1'
comment = 'vector data type and ivfflat and hnsw access methods'
default_version = '0.5.1'
module_pathname = '$libdir/vector'
relocatable = true