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231 Commits

Author SHA1 Message Date
Andrew Kane
665b3dfa1c Skip if FMA available [skip ci] 2024-04-14 14:17:10 -07:00
Andrew Kane
ce597f770d Updated changelog [skip ci] 2024-04-13 20:23:33 -07:00
Andrew Kane
1234fffcb0 Fixed CI 2024-04-13 20:17:33 -07:00
Andrew Kane
e70a47c154 Added CPU dispatching for vector distance functions 2024-04-13 20:12:47 -07:00
Andrew Kane
0c9ad67a1c Added section on subvector indexing [skip ci] 2024-04-13 18:18:12 -07:00
Andrew Kane
8a4845b52e Fixed CI 2024-04-13 16:09:42 -07:00
Andrew Kane
e14fdba8b3 Improved sparsevec input tests [skip ci] 2024-04-13 16:00:14 -07:00
Andrew Kane
5abf83c415 Improved sparsevec input tests [skip ci] 2024-04-13 15:58:00 -07:00
Andrew Kane
96b30fd25d Improved error message and tests for sparsevec_in 2024-04-13 15:50:40 -07:00
Andrew Kane
1c791480ff Fixed flaky test [skip ci] 2024-04-13 15:49:20 -07:00
Andrew Kane
545ae30057 Improved performance of sparsevec_in 2024-04-13 15:42:16 -07:00
Andrew Kane
20fb2e0797 Improved sparsevec_in [skip ci] 2024-04-13 15:13:08 -07:00
Andrew Kane
89629abc08 Removed unneeded check [skip ci] 2024-04-13 15:06:17 -07:00
Andrew Kane
db112862a5 Improved performance of halfvec_in 2024-04-13 15:04:52 -07:00
Andrew Kane
bb84d69e57 Removed todo [skip ci] 2024-04-13 15:02:14 -07:00
Andrew Kane
7ea1590ea3 Removed todo [skip ci] 2024-04-13 15:01:23 -07:00
Andrew Kane
d98eb0a28d Fixed flaky test [skip ci] 2024-04-13 15:00:58 -07:00
Andrew Kane
72eee91d00 Fixed test 2024-04-13 14:55:14 -07:00
Andrew Kane
f5e6e58359 Improved performance of vector_in 2024-04-13 14:49:00 -07:00
Andrew Kane
8f93d02c71 Updated comments [skip ci] 2024-04-13 14:06:10 -07:00
Andrew Kane
c5c82bafda Updated invalid input syntax messages to be consistent [skip ci] 2024-04-13 11:32:47 -07:00
Andrew Kane
f627e69c5f Fixed test [skip ci] 2024-04-13 11:21:25 -07:00
Andrew Kane
23944302fe Improved input functions [skip ci] 2024-04-13 11:09:59 -07:00
Andrew Kane
9957ba6817 Improved input tests [skip ci] 2024-04-13 10:56:34 -07:00
Andrew Kane
aed463dbad Fixed headers 2024-04-12 11:58:27 -07:00
Andrew Kane
f64abe3aae Fixed performance of halfvec 2024-04-12 11:50:34 -07:00
Andrew Kane
06d90fdc76 Updated comments [skip ci] 2024-04-11 22:35:11 -07:00
Andrew Kane
cc4b01bd49 Moved code [skip ci] 2024-04-11 22:25:53 -07:00
Andrew Kane
3621a84ef8 Moved code to separate function [skip ci] 2024-04-11 22:23:16 -07:00
Andrew Kane
b9d5269547 Improved IVFFlat build recall test 2024-04-11 21:47:49 -07:00
Andrew Kane
fbc96bb488 Added comments [skip ci] 2024-04-11 21:38:09 -07:00
Andrew Kane
5510ae5b8c Better account for equal distances [skip ci] 2024-04-11 21:34:46 -07:00
Andrew Kane
70eee06e83 Fixed CI 2024-04-11 21:17:23 -07:00
Andrew Kane
f2bffff460 Improved code for item size [skip ci] 2024-04-11 21:14:48 -07:00
Andrew Kane
af7d9b74a9 Fixed max dimensions for halfvec for IVFFlat [skip ci] 2024-04-11 21:07:45 -07:00
Andrew Kane
f1a71524f0 Added comment [skip ci] 2024-04-11 20:35:41 -07:00
Andrew Kane
7710cc8c28 Added comments [skip ci] 2024-04-11 20:34:15 -07:00
Andrew Kane
fea2eb262e Moved type check out of loop [skip ci] 2024-04-11 20:31:27 -07:00
Andrew Kane
1bc6f954f4 Fixed flaky test [skip ci] 2024-04-11 20:15:14 -07:00
Andrew Kane
6fd6b0bd5f Fixed CI 2024-04-11 20:09:10 -07:00
Andrew Kane
546006b7ca Added comment [skip ci] 2024-04-11 20:03:12 -07:00
Andrew Kane
cca0edf458 Improved k-means types [skip ci] 2024-04-11 20:00:07 -07:00
Andrew Kane
8d9400bae3 Added support for halfvec to IVFFlat 2024-04-11 19:56:39 -07:00
Andrew Kane
a4531ca51f Fixed halfvec_cmp_internal function [skip ci] 2024-04-11 19:43:25 -07:00
Andrew Kane
94ee6b13c3 Show memory from outer context [skip ci] 2024-04-11 18:38:35 -07:00
Andrew Kane
e6a591275a Added halfvec_cmp_internal function [skip ci] 2024-04-11 18:33:54 -07:00
Andrew Kane
7fddd296ee Improved k-means code [skip ci] 2024-04-11 17:16:54 -07:00
Andrew Kane
c581db9f98 Improved k-means code [skip ci] 2024-04-11 17:15:20 -07:00
Andrew Kane
626bc053e5 Improved k-means code [skip ci] 2024-04-11 16:54:43 -07:00
Andrew Kane
66a29dbdf3 Switched to Datum for ApplyNorm [skip ci] 2024-04-11 16:50:21 -07:00
Andrew Kane
1c26da6ef5 Mark type-specific code [skip ci] 2024-04-11 16:44:10 -07:00
Andrew Kane
000cc13c29 Switched to datumIsEqual for duplicate check in IVFFlat [skip ci] 2024-04-11 16:37:34 -07:00
Andrew Kane
bbfe1e8b61 Removed more vector-specific code from IVFFlat [skip ci] 2024-04-11 14:05:41 -07:00
Andrew Kane
7e8be16e37 Improved code [skip ci] 2024-04-11 14:01:21 -07:00
Andrew Kane
17c2f9c0b6 Removed more vector-specific code from IVFFlat 2024-04-11 13:59:20 -07:00
Andrew Kane
bd52ed29e0 Added halfvec_spherical_distance function [skip ci] 2024-04-11 13:52:59 -07:00
Andrew Kane
245bac5e8e Removed vector-specific code from IVFFlat [skip ci] 2024-04-11 13:50:23 -07:00
Andrew Kane
d84fc303ee Removed vector-specific code from IVFFlat [skip ci] 2024-04-11 13:49:28 -07:00
Andrew Kane
4ff36af67e Added itemsize to VectorArray [skip ci] 2024-04-11 13:47:36 -07:00
Andrew Kane
5834b58c5a Moved VECTOR_SIZE out of IVFFLAT_LIST_SIZE [skip ci] 2024-04-11 09:43:35 -07:00
Andrew Kane
381216a956 Improved variable scoping 2024-04-11 09:41:47 -07:00
Andrew Kane
c3c6af8a84 Improved variable scoping [skip ci] 2024-04-11 09:38:54 -07:00
Andrew Kane
d45f561d75 Use memory context for k-means [skip ci] 2024-04-11 09:34:05 -07:00
Andrew Kane
e1647473c9 Updated IvfflatGetType [skip ci] 2024-04-11 09:25:07 -07:00
Andrew Kane
e8bd7cd2f5 Updated test to be independent of order [skip ci] 2024-04-11 09:22:03 -07:00
Andrew Kane
bed40ec0b5 Moved code to get scan value to separate function for IVFFlat [skip ci] 2024-04-11 09:20:10 -07:00
Andrew Kane
d64295dfd7 Improved test SQL [skip ci] 2024-04-10 16:38:07 -07:00
Andrew Kane
8178a902ce Fixed flaky test [skip ci] 2024-04-10 16:34:56 -07:00
Andrew Kane
f9f53b64e8 Added tests for HNSW vacuum recall for bit, halfvec, and sparsevec 2024-04-10 16:29:48 -07:00
Andrew Kane
fc83cd8d12 Fixed flaky tests [skip ci] 2024-04-10 14:06:50 -07:00
Andrew Kane
1e41ed6f15 Added more cast tests [skip ci] 2024-04-10 14:05:51 -07:00
Andrew Kane
e6ca831f3d Store very small values as zero for halfvec 2024-04-10 13:59:51 -07:00
Andrew Kane
a824af42fb Improved error message for out of range values for halfvec [skip ci] 2024-04-10 13:47:45 -07:00
Andrew Kane
8a29bf4619 Added more cast tests [skip ci] 2024-04-10 13:42:30 -07:00
Andrew Kane
33369e0744 Added tests for HNSW duplicates for bit, halfvec, and sparsevec 2024-04-10 13:23:20 -07:00
Andrew Kane
34b09cc062 Added test for HNSW insert recall with sparsevec 2024-04-10 13:10:37 -07:00
Andrew Kane
d8f3e18db6 Added test for HNSW insert recall with halfvec [skip ci] 2024-04-10 13:06:56 -07:00
Andrew Kane
e6e7d7c1bc Added test for HNSW insert recall with bit [skip ci] 2024-04-10 13:03:48 -07:00
Andrew Kane
bf355792b2 Added tests for sparsevec_norm [skip ci] 2024-04-10 11:37:11 -07:00
Andrew Kane
12f4a34708 Added tests for halfvec_norm [skip ci] 2024-04-09 18:00:42 -07:00
Andrew Kane
f6becf01aa Improved input tests [skip ci] 2024-04-09 17:34:11 -07:00
Andrew Kane
dd5b856f68 Improved cast tests [skip ci] 2024-04-09 17:10:52 -07:00
Andrew Kane
9c96164f2c Improved cast tests [skip ci] 2024-04-09 17:05:42 -07:00
Andrew Kane
b583803b2c Improved cast tests [skip ci] 2024-04-09 17:02:21 -07:00
Andrew Kane
a04bf7fce2 Moved cast test [skip ci] 2024-04-09 16:48:45 -07:00
Andrew Kane
62b411f94c Improved sparsevec input test [skip ci] 2024-04-09 16:44:34 -07:00
Andrew Kane
82a17b81f5 Improved sparsevec input test [skip ci] 2024-04-09 16:41:48 -07:00
Andrew Kane
3b2ca7df7a Added sparsevec to copy test [skip ci] 2024-04-09 16:35:06 -07:00
Andrew Kane
21d125abed Improved tests [skip ci] 2024-04-09 16:31:52 -07:00
Andrew Kane
f42ccd451d Improved sparsevec input tests [skip ci] 2024-04-09 16:29:23 -07:00
Andrew Kane
85345e3f8c Removed todo [skip ci] 2024-04-09 14:41:49 -07:00
Andrew Kane
05ce20990c Added test for bit dimensions [skip ci] 2024-04-09 14:31:33 -07:00
Andrew Kane
f3477cf28d DRY vector_spherical_distance [skip ci] 2024-04-08 16:45:08 -07:00
Andrew Kane
434f3f5e88 DRY vector distance functions 2024-04-08 16:41:50 -07:00
Andrew Kane
bd6fdb73eb Improved naming [skip ci] 2024-04-08 16:35:57 -07:00
Andrew Kane
ab382a2053 Improved code [skip ci] 2024-04-08 15:32:16 -07:00
Andrew Kane
191c8e1cca Use consistent naming [skip ci] 2024-04-08 14:56:59 -07:00
Andrew Kane
3eba34e5e3 Improved code for feature detection 2024-04-08 14:40:12 -07:00
Andrew Kane
862f17c1de Removed unneeded initialization [skip ci] 2024-04-08 14:15:34 -07:00
Andrew Kane
21bcff6722 Added CPU dispatching for halfvec distance functions - #311
Co-authored-by: Arda Aytekin <arda.aytekin@microsoft.com>
2024-04-08 13:50:18 -07:00
Andrew Kane
60b4bb2ad1 Moved halfvec distance functions to separate file [skip ci] 2024-04-08 10:00:34 -07:00
Andrew Kane
c27363fbf7 Improved halfvec tests 2024-04-08 00:31:44 -07:00
Andrew Kane
06309f5d07 Updated comments [skip ci] 2024-04-07 21:55:44 -07:00
Andrew Kane
39b8bd1816 Switched to storeu [skip ci] 2024-04-07 21:04:59 -07:00
Andrew Kane
925aa4e048 Added SIMD version of L2 distance 2024-04-07 20:22:19 -07:00
Andrew Kane
9ed39cee67 Added SIMD version of inner product 2024-04-07 20:10:54 -07:00
Andrew Kane
494087222f Removed note [skip ci] 2024-04-07 20:02:17 -07:00
Andrew Kane
4c0b10451f Fixed flaky test [skip ci] 2024-04-07 19:11:16 -07:00
Andrew Kane
3bd67fef54 DRY halfvec distance functions 2024-04-07 19:03:20 -07:00
Andrew Kane
d861a0304e Removed extra space [skip ci] 2024-04-07 19:02:30 -07:00
Andrew Kane
d8719d59a3 Improved halfvec performance with F16C support 2024-04-07 18:53:50 -07:00
Andrew Kane
98d4b1a364 Updated docs on halfvec performance [skip ci] 2024-04-07 16:16:39 -07:00
Andrew Kane
33daf87fcb Improved performance of HalfToFloat4 2024-04-07 13:01:58 -07:00
Andrew Kane
faa33c32d9 Added link to halfvec performance section [skip ci] 2024-04-07 10:55:46 -07:00
Andrew Kane
0df30c12a7 Added section on halfvec performance [skip ci] 2024-04-07 10:54:28 -07:00
Andrew Kane
8d7e0e693c Fixed vector to sparsevec conversion 2024-04-07 10:30:54 -07:00
Andrew Kane
457adcbbdb Added TAP test for sparsevec 2024-04-07 10:20:19 -07:00
Andrew Kane
bada41484f Improved bit function tests [skip ci] 2024-04-06 18:21:37 -07:00
Andrew Kane
60104264d5 Improved error message [skip ci] 2024-04-06 15:52:26 -07:00
Andrew Kane
53c4faaf72 Updated readme [skip ci] 2024-04-06 14:52:26 -07:00
Andrew Kane
5fa3da5400 Fixed flaky test [skip ci] 2024-04-06 14:21:10 -07:00
Andrew Kane
4450029bdc Changed indices to start at 1 for sparse vectors to match SQL 2024-04-06 14:02:07 -07:00
Andrew Kane
aec853dc68 Added memory usage for HNSW index scans [skip ci] 2024-04-04 14:37:39 -07:00
Andrew Kane
2d24d65f1c Added sparse vectors section [skip ci] 2024-04-04 00:00:54 -07:00
Andrew Kane
abd9963e66 Added half vectors section [skip ci] 2024-04-03 23:55:08 -07:00
Andrew Kane
7e5df3c9fe Updated binary vectors section [skip ci] 2024-04-03 23:36:43 -07:00
Andrew Kane
61e803a4dc Updated readme [skip ci] 2024-04-03 23:26:25 -07:00
Andrew Kane
2e5cbf611a Simplified bit test 2024-04-03 23:26:03 -07:00
Andrew Kane
d28b2cfccf Added binary vectors section [skip ci] 2024-04-03 23:23:52 -07:00
Andrew Kane
6c4a115ebf Updated readme [skip ci] 2024-04-03 23:17:27 -07:00
Andrew Kane
c421dc6483 Added binary quantization section [skip ci] 2024-04-03 23:15:28 -07:00
Andrew Kane
8961de6179 Improved halfvec input check [skip ci] 2024-04-03 22:23:23 -07:00
Andrew Kane
9f61dcff5d Improved error messages for halfvec input [skip ci] 2024-04-03 22:20:13 -07:00
Andrew Kane
7667abe9a0 Improved test [skip ci] 2024-04-03 22:08:48 -07:00
Andrew Kane
3219a30290 Raise error for varbit 2024-04-03 21:30:43 -07:00
Andrew Kane
483e42b9c4 Added tests for varbit [skip ci] 2024-04-03 21:15:57 -07:00
Andrew Kane
41b4bf79ba Updated readme [skip ci] 2024-04-03 21:08:45 -07:00
Andrew Kane
fc1aeee62c Added SPARSEVEC_MAX_NNZ 2024-04-03 21:05:35 -07:00
Andrew Kane
35d0fe88b9 Added IvfflatType [skip ci] 2024-04-03 16:40:27 -07:00
Andrew Kane
aaa2d644ce Added quantize_binary and subvector functions for halfvec 2024-04-03 14:53:03 -07:00
Andrew Kane
253acbccf4 Updated readme [skip ci] 2024-04-03 11:05:55 -07:00
Andrew Kane
060d299e4b Improved error message for out of range elements 2024-04-03 10:12:17 -07:00
Andrew Kane
d7354a86a8 Updated readme [skip ci] 2024-04-02 14:45:25 -07:00
Andrew Kane
daba71694b Updated readme [skip ci] 2024-04-02 14:39:14 -07:00
Andrew Kane
506dd2b44a Updated changelog [skip ci] 2024-04-02 14:33:57 -07:00
Andrew Kane
bcf41f5f66 Fixed flaky test [skip ci] 2024-04-02 14:31:05 -07:00
Andrew Kane
abac7a3f77 Added sparsevec type 2024-04-02 14:25:09 -07:00
Andrew Kane
32a502c838 Added halfvec type 2024-04-02 13:55:45 -07:00
Andrew Kane
1134e52762 Renamed regression tests [skip ci] 2024-04-02 13:33:44 -07:00
Andrew Kane
3ef632e042 Added Mac arm64 to CI [skip ci] 2024-04-02 12:48:19 -07:00
Andrew Kane
e2a527ffda Fixed flaky test [skip ci] 2024-04-02 12:23:48 -07:00
Andrew Kane
835f010257 Fixed missing header for Postgres 12 2024-04-02 12:17:41 -07:00
Andrew Kane
d6044dd423 Added subvector function 2024-04-02 12:13:04 -07:00
Andrew Kane
c75634a03c Fixed type check [skip ci] 2024-04-01 22:31:02 -07:00
Andrew Kane
ab7b2ed39e Updated comparison operators to support vectors with different dimensions - #451 2024-04-01 22:12:06 -07:00
Andrew Kane
499b6bc2c9 Fixed regression test list for Windows [skip ci] 2024-04-01 21:32:28 -07:00
Andrew Kane
741c6a8a7b Renamed tests [skip ci] 2024-04-01 20:51:21 -07:00
Andrew Kane
1c82bdd932 Updated comments [skip ci] 2024-04-01 20:33:12 -07:00
Andrew Kane
94a444f029 Added support for bit vectors to HNSW 2024-04-01 20:30:55 -07:00
Andrew Kane
7ee9074a9c Updated comment [skip ci] 2024-03-31 18:33:26 -07:00
Andrew Kane
2f2f3631a8 Improved vector_out code 2024-03-31 09:55:07 -07:00
Andrew Kane
4b22851bbd Added more vector input tests [skip ci] 2024-03-30 10:17:55 -07:00
Andrew Kane
3acdbf99e8 Added casting to distance functions in tests [skip ci] 2024-03-30 09:05:15 -07:00
Andrew Kane
11ea3d8483 Updated SQL comments [skip ci] 2024-03-30 08:29:01 -07:00
Andrew Kane
2c48e3edc2 Mark type-specific code 2024-03-29 14:01:48 -07:00
Andrew Kane
7d63bb4b98 Fixed flaky test [skip ci] 2024-03-29 11:00:16 -07:00
Andrew Kane
de410a2915 Use variable for max dimemsions [skip ci] 2024-03-29 10:57:16 -07:00
Andrew Kane
64aa99aa31 Added todo [skip ci] 2024-03-29 10:56:24 -07:00
Andrew Kane
997fa167da Removed vector-specific code from HNSW 2024-03-29 10:50:06 -07:00
Andrew Kane
67eec4edbf Improved tuning section [skip ci] 2024-03-27 22:04:28 -07:00
Andrew Kane
396090d8e0 Improved code [skip ci] 2024-03-27 21:38:22 -07:00
Andrew Kane
ba18942fcf Removed normvec from IVFFlat for simplicity (no difference in performance) 2024-03-27 16:41:17 -07:00
Andrew Kane
8e59455c3c Removed normvec for simplicity (no difference in performance) 2024-03-27 16:33:11 -07:00
Andrew Kane
bd50e3067d Updated readme [skip ci] 2024-03-27 14:14:49 -07:00
Andrew Kane
af9d4ad659 Updated readme [skip ci] 2024-03-27 14:12:08 -07:00
Andrew Kane
08abb63cbe Added notes about NULL vectors [skip ci] 2024-03-27 11:50:37 -07:00
Andrew Kane
06b8556a49 Revert "Updated readme [skip ci]"
This reverts commit 3f674c9994.
2024-03-25 23:33:46 -07:00
Andrew Kane
3f674c9994 Updated readme [skip ci] 2024-03-25 23:33:17 -07:00
Andrew Kane
31e41b3ba9 Added FAQ about binary vectors [skip ci] 2024-03-24 11:07:34 -07:00
Andrew Kane
903a925662 Improved type modifier tests 2024-03-21 17:31:08 -07:00
Andrew Kane
96ff19be44 Version bump to 0.6.2 [skip ci] 2024-03-18 10:21:04 -07:00
Andrew Kane
6c969bebad Updated changelog [skip ci] 2024-03-18 10:11:45 -07:00
Andrew Kane
b64a1482d9 Moved example [skip ci] 2024-03-16 15:20:26 -07:00
Andrew Kane
a5f2d70bc2 Use temp directory for installation instructions on Windows [skip ci] 2024-03-16 12:02:45 -07:00
Andrew Kane
f3fcb5e005 Moved installation notes for Windows [skip ci] 2024-03-16 11:47:18 -07:00
Andrew Kane
3a6e0afb9c Added installation notes for Windows [skip ci] 2024-03-16 11:35:55 -07:00
Andrew Kane
183d50bdbd Added note about creating indexes concurrently [skip ci] 2024-03-16 10:45:09 -07:00
Andrew Kane
bd776fee68 Updated readme [skip ci] 2024-03-16 10:44:45 -07:00
Andrew Kane
d30b113e4b Updated readme [skip ci] 2024-03-15 21:54:58 -07:00
Andrew Kane
fd3200f718 Updated readme [skip ci] 2024-03-15 21:47:57 -07:00
Andrew Kane
02c815d876 Added docs on tuning, monitoring, and scaling [skip ci] 2024-03-15 19:00:49 -07:00
Andrew Kane
4b2a7cc49d Improved performance section [skip ci] 2024-03-15 17:54:14 -07:00
Andrew Kane
da0ff998e9 Updated readme [skip ci] 2024-03-15 14:23:56 -07:00
Andrew Kane
cb36e24289 Improved portability section [skip ci] 2024-03-15 14:23:04 -07:00
Andrew Kane
b1d0d4c7a3 Improved troubleshooting docs [skip ci] 2024-03-15 14:01:24 -07:00
Andrew Kane
1dc6514b66 Updated comment [skip ci] 2024-03-15 12:38:14 -07:00
Andrew Kane
6c53f7ca02 Updated comment [skip ci] 2024-03-15 12:37:47 -07:00
Heikki Linnakangas
0d35a14198 Fix compiler warnings in strict C99 mode (#487)
Redefining a typedef is a C11 feature:

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

I got these warnings when I built PostgreSQL with "CC=clang
CFLAGS=-std=gnu99"; other similar options would surely produce the
warnings too.
2024-03-12 02:02:33 -07:00
Andrew Kane
3ea2ce89be Reduced lock contention with parallel HNSW index builds 2024-03-11 20:16:55 -07:00
Andrew Kane
62350b1589 Added note about IVFFlat results [skip ci] 2024-03-06 00:29:55 -08:00
Andrew Kane
dd57309281 Added section about HNSW results - #480 [skip ci] 2024-03-06 00:27:50 -08:00
Andrew Kane
c6ddf62a29 Version bump to 0.6.1 [skip ci] 2024-03-04 10:27:59 -08:00
Andrew Kane
801be04d8b Updated CI [skip ci] 2024-03-02 17:06:11 -08:00
Andrew Kane
587e9ba97c Added link to bulk loading example [skip ci] 2024-02-29 21:25:11 -08:00
Andrew Kane
d57047a935 Moved COPY example and added FORMAT [skip ci] 2024-02-29 20:35:01 -08:00
oneturkmen
f1db1f17e3 Update README.md (#472) 2024-02-29 20:27:53 -08:00
Andrew Kane
2f48c0fac4 Updated changelog [skip ci] 2024-02-29 18:10:19 -08:00
Andrew Kane
84a8aa8176 Added note about HNSW build time [skip ci] 2024-02-29 16:25:58 -08:00
Andrew Kane
f64ebbef50 Added OPTFLAGS to readme [skip ci] 2024-02-29 16:15:22 -08:00
Andrew Kane
ac8156509b Updated vector operators for <= and >= 2024-02-29 15:43:29 -08:00
Andrew Kane
82bf69b479 Fixed vector subtraction being marked as commutative - fixes #475 2024-02-29 14:36:18 -08:00
Andrew Kane
4be2f57916 Updated license year [skip ci] 2024-02-29 13:44:58 -08:00
Andrew Kane
91e3d2905f Fixed sort function for Postgres 12 2024-02-28 16:26:41 -08:00
Andrew Kane
fe2406564f Replaced pairing heap with array in SelectNeighbors - closes #447
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2024-02-28 15:47:26 -08:00
Andrew Kane
fa52511eaa Fixed closer caching for Postgres 12 2024-02-28 15:44:38 -08:00
Andrew Kane
447ef4d27a Specify Postgres version for Valgrind [skip ci] 2024-02-28 14:16:48 -08:00
Andrew Kane
b36cd22ccc Enable assertions on CI 2024-02-28 14:15:34 -08:00
Andrew Kane
b447ae4989 Avoid base address for relptr for Postgres < 14.5 2024-02-28 14:10:14 -08:00
Andrew Kane
efed873a3e Revert "Replaced pairing heap with array in SelectNeighbors - closes #447"
This reverts commit 14b278dec9.
2024-02-28 11:33:14 -08:00
Andrew Kane
14b278dec9 Replaced pairing heap with array in SelectNeighbors - closes #447
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2024-02-28 11:25:12 -08:00
Andrew Kane
133a728e48 Updated changelog [skip ci] 2024-02-20 16:38:05 -08:00
Andrew Kane
ca10cbaa7d Revert "Remove offsethash"
This reverts commit 1cbd204f52.
2024-02-20 16:07:32 -08:00
Andrew Kane
eb29019a14 Revert "Eliminate a few HnswPtrAccess invocations"
This reverts commit 334c386a45.
2024-02-20 16:07:21 -08:00
Heikki Linnakangas
334c386a45 Eliminate a few HnswPtrAccess invocations
HnswPtrAccess() is pretty cheap, but it stills seems worthwhile to
avoid repeated calls in the hot paths when it can be easily avoided.
2024-02-19 14:13:18 +02:00
Heikki Linnakangas
1cbd204f52 Remove offsethash
The original motivation was to eliminate the superfluous HnswPtrAccess
call from AddToVisited. The caller has to call HnswPtrAccess() anyway,
so it makes sense to pass the HnswElement rather than HnswElementPtr
to AddToVisited(). But then I realized that we can use the
pointer-variant even with shared memory, because the visited-hash is
backend-private, and the addresses where the elements are mapped to in
shared memory are stable within the backend.
2024-02-19 14:12:26 +02:00
Andrew Kane
5ba62fca84 Fixed crash with shared_preload_libraries - fixes #460 2024-02-14 17:13:30 -08:00
Andrew Kane
22cb2a3fe7 Simplified Docker tasks [skip ci] 2024-02-07 12:03:33 -08:00
Andrew Kane
72b144906a Added Valgrind to CI 2024-02-07 09:43:01 -08:00
Andrew Kane
a618c1bc78 Updated port name [skip ci] 2024-02-06 12:43:20 -08:00
Andrew Kane
f43cd0ed98 Improved type [skip ci] 2024-02-05 19:38:52 -08:00
Andrew Kane
51df640961 Added instructions for pkg [skip ci] 2024-02-05 17:01:36 -08:00
103 changed files with 7362 additions and 658 deletions

View File

@@ -28,7 +28,7 @@ jobs:
dev-files: true
- run: make
env:
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
- run: |
export PG_CONFIG=`which pg_config`
sudo --preserve-env=PG_CONFIG make install
@@ -40,27 +40,43 @@ jobs:
sudo apt-get install libipc-run-perl
- run: make prove_installcheck
mac:
runs-on: macos-latest
runs-on: ${{ matrix.os }}
if: ${{ !startsWith(github.ref_name, 'windows') }}
strategy:
fail-fast: false
matrix:
include:
- postgres: 16
os: macos-14
- postgres: 14
os: macos-12
steps:
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14
postgres-version: ${{ matrix.postgres }}
- run: make
env:
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter
- run: make install
- run: make installcheck
- if: ${{ failure() }}
run: cat regression.diffs
# Homebrew Postgres does not enable TAP tests, so need to download
- run: |
brew install cpanm
cpanm --notest IPC::Run
wget -q https://github.com/postgres/postgres/archive/refs/tags/REL_14_10.tar.gz
tar xf REL_14_10.tar.gz
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres-REL_14_10/src/test/perl" PERL5LIB="/Users/runner/perl5/lib/perl5"
- run: make clean && /usr/local/opt/llvm@15/bin/scan-build --status-bugs make PG_CFLAGS="-DUSE_ASSERT_CHECKING"
wget -q https://github.com/postgres/postgres/archive/refs/tags/$TAG.tar.gz
tar xf $TAG.tar.gz
mv postgres-$TAG postgres
env:
TAG: ${{ matrix.postgres == 16 && 'REL_16_2' || 'REL_14_11' }}
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres/src/test/perl -I ./test/perl"
env:
PERL5LIB: /Users/runner/perl5/lib/perl5
- run: make clean && $(brew --prefix llvm@15)/bin/scan-build --status-bugs make
env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING
windows:
runs-on: windows-latest
if: ${{ !startsWith(github.ref_name, 'mac') }}
@@ -71,6 +87,7 @@ jobs:
postgres-version: 14
- run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
cd %TEMP% && ^
nmake /NOLOGO /F Makefile.win && ^
nmake /NOLOGO /F Makefile.win install && ^
nmake /NOLOGO /F Makefile.win installcheck && ^
@@ -97,4 +114,15 @@ jobs:
sudo -u postgres make installcheck
sudo -u postgres make prove_installcheck
env:
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
valgrind:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: ankane/setup-postgres-valgrind@v1
with:
postgres-version: 16
- run: make OPTFLAGS=""
- run: sudo --preserve-env=PG_CONFIG make install
- run: make installcheck

View File

@@ -1,6 +1,24 @@
## 0.6.1 (unreleased)
## 0.7.0 (unreleased)
- Added `halfvec` type
- Added `sparsevec` type
- Added support for `bit` vectors to HNSW
- Added `hamming_distance` function
- Added `jaccard_distance` function
- Added `quantize_binary` function
- Added `subvector` function
- Added CPU dispatching for distance functions on Linux x86-64
- Updated comparison operators to support vectors with different dimensions
## 0.6.2 (2024-03-18)
- Reduced lock contention with parallel HNSW index builds
## 0.6.1 (2024-03-04)
- Fixed error with `ANALYZE` and vectors with different dimensions
- Fixed segmentation fault with `shared_preload_libraries`
- Fixed vector subtraction being marked as commutative
## 0.6.0 (2024-01-29)

View File

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

View File

@@ -2,7 +2,7 @@
"name": "vector",
"abstract": "Open-source vector similarity search for Postgres",
"description": "Supports L2 distance, inner product, and cosine distance",
"version": "0.6.0",
"version": "0.6.2",
"maintainer": [
"Andrew Kane <andrew@ankane.org>"
],
@@ -20,7 +20,7 @@
"vector": {
"file": "sql/vector.sql",
"docfile": "README.md",
"version": "0.6.0",
"version": "0.6.2",
"abstract": "Open-source vector similarity search for Postgres"
}
},

View File

@@ -1,10 +1,10 @@
EXTENSION = vector
EXTVERSION = 0.6.0
EXTVERSION = 0.6.2
MODULE_big = vector
DATA = $(wildcard sql/*--*.sql)
OBJS = src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
HEADERS = src/vector.h
OBJS = src/bitvector.o src/halfutils.o src/halfvec.o src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/sparsevec.o src/vector.o
HEADERS = src/halfvec.h src/sparsevec.h src/vector.h
TESTS = $(wildcard test/sql/*.sql)
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))
@@ -12,7 +12,7 @@ REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
OPTFLAGS = -march=native
# Mac ARM doesn't support -march=native
# Mac ARM doesn't always support -march=native
ifeq ($(shell uname -s), Darwin)
ifeq ($(shell uname -p), arm)
# no difference with -march=armv8.5-a
@@ -71,11 +71,9 @@ PG_MAJOR ?= 16
.PHONY: docker
docker:
docker build --pull --no-cache --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) .
docker build --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .
docker build --pull --no-cache --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .
.PHONY: docker-release
docker-release:
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) .
docker buildx build --push --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .

View File

@@ -1,10 +1,10 @@
EXTENSION = vector
EXTVERSION = 0.6.0
EXTVERSION = 0.6.2
OBJS = src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
HEADERS = src\vector.h
OBJS = src\bitvector.obj src\halfutils.obj src\halfvec.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\sparsevec.obj src\vector.obj
HEADERS = src\halfvec.h src\sparsevec.h src\vector.h
REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
REGRESS = bit_functions btree cast copy halfvec_functions halfvec_input hnsw_bit_hamming hnsw_bit_jaccard hnsw_halfvec_cosine hnsw_halfvec_ip hnsw_halfvec_l2 hnsw_options hnsw_sparsevec_cosine hnsw_sparsevec_ip hnsw_sparsevec_l2 hnsw_unlogged hnsw_vector_cosine hnsw_vector_ip hnsw_vector_l2 ivfflat_options ivfflat_unlogged ivfflat_vector_cosine ivfflat_vector_ip ivfflat_vector_l2 sparsevec_functions sparsevec_input vector_functions vector_input
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
# For /arch flags

389
README.md
View File

@@ -20,15 +20,15 @@ Compile and install the extension (supports Postgres 12+)
```sh
cd /tmp
git clone --branch v0.6.0 https://github.com/pgvector/pgvector.git
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo
```
See the [installation notes](#installation-notes) if you run into issues
See the [installation notes](#installation-notes---linux-and-mac) if you run into issues
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [pkg](#pkg), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
### Windows
@@ -44,12 +44,15 @@ Then use `nmake` to build:
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16"
git clone --branch v0.6.0 https://github.com/pgvector/pgvector.git
cd %TEMP%
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
```
See the [installation notes](#installation-notes---windows) if you run into issues
You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
## Getting Started
@@ -102,6 +105,12 @@ Insert vectors
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
```
Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py))
```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
```
Upsert vectors
```sql
@@ -212,7 +221,24 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
```
Vectors with up to 2,000 dimensions can be indexed.
Hamming distance - unreleased
```sql
CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
```
Jaccard distance - unreleased
```sql
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
```
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (unreleased)
- `bit` - up to 64,000 dimensions (unreleased)
- `sparsevec` - up to 1,000 non-zero elements (unreleased)
### Index Options
@@ -264,6 +290,8 @@ HINT: Increase maintenance_work_mem to speed up builds.
Note: Do not set `maintenance_work_mem` so high that it exhausts the memory on the server
Like other index types, its faster to create an index after loading your initial data
Starting with 0.6.0, you can also speed up index creation by increasing the number of parallel workers (2 by default)
```sql
@@ -315,7 +343,10 @@ Cosine distance
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
```
Vectors with up to 2,000 dimensions can be indexed.
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (unreleased)
### Query Options
@@ -389,6 +420,103 @@ Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
```
## Half Vectors
*Unreleased*
Use the `halfvec` type to store half-precision vectors
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));
```
## Half Indexing
*Unreleased*
Index vectors at half precision for smaller indexes and faster build times
```sql
CREATE INDEX ON items USING hnsw ((embedding::halfvec(3)) halfvec_l2_ops);
```
Get the nearest neighbors
```sql
SELECT * FROM items ORDER BY embedding::halfvec(3) <-> '[1,2,3]' LIMIT 5;
```
## Binary Vectors
Use the `bit` type to store binary vectors ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py))
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES ('000'), ('111');
```
Get the nearest neighbors by Hamming distance
```sql
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Or (unreleased)
```sql
SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
```
Also supports Jaccard distance (`<%>`)
## Binary Quantization
*Unreleased*
Use expression indexing for binary quantization
```sql
CREATE INDEX ON items USING hnsw ((quantize_binary(embedding)::bit(3)) bit_hamming_ops);
```
Get the nearest neighbors by Hamming distance
```sql
SELECT * FROM items ORDER BY quantize_binary(embedding)::bit(3) <~> quantize_binary('[1,-2,3]') LIMIT 5;
```
Re-rank by the original vectors for better recall
```sql
SELECT * FROM (
SELECT * FROM items ORDER BY quantize_binary(embedding)::bit(3) <~> quantize_binary('[1,-2,3]') LIMIT 20
) ORDER BY embedding <=> '[1,-2,3]' LIMIT 5;
```
## Sparse Vectors
*Unreleased*
Use the `sparsevec` type to store sparse vectors
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding sparsevec(5));
```
Insert vectors
```sql
INSERT INTO items (embedding) VALUES ('{1:1,3:2,5:3}/5'), ('{1:4,3:5,5:6}/5');
```
Note: The format is `{index1:value1,index2:value2,...}/dimensions` and indices start at 1 like SQL arrays
Get the nearest neighbors by L2 distance
```sql
SELECT * FROM items ORDER BY embedding <-> '{1:3,3:1,5:2}/5' LIMIT 5;
```
## Hybrid Search
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search.
@@ -400,15 +528,77 @@ SELECT id, content FROM items, plainto_tsquery('hello search') query
You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search_rrf.py) or a [cross-encoder](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search.py) to combine results.
## Subvector Indexing
*Unreleased*
Use expression indexing to index subvectors
```sql
CREATE INDEX ON items USING hnsw ((subvector(embedding, 1, 3)::vector(3)) vector_cosine_ops);
```
Get the nearest neighbors by cosine distance
```sql
SELECT * FROM items ORDER BY subvector(embedding, 1, 3)::vector(3) <=> subvector('[1,2,3,4,5]'::vector, 1, 3) LIMIT 5;
```
Re-rank by the full vectors for better recall
```sql
SELECT * FROM (
SELECT * FROM items ORDER BY subvector(embedding, 1, 3)::vector(3) <=> subvector('[1,2,3,4,5]'::vector, 1, 3) LIMIT 20
) ORDER BY embedding <=> '[1,2,3,4,5]' LIMIT 5;
```
## Performance
### Tuning
Use a tool like [PgTune](https://pgtune.leopard.in.ua/) to set initial values for Postgres server parameters. For instance, `shared_buffers` should typically be 25% of the servers memory. You can find the config file with:
```sql
SHOW config_file;
```
And check individual settings with:
```sql
SHOW shared_buffers;
```
Be sure to restart Postgres for changes to take effect.
### Loading
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py)).
```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
```
Add any indexes *after* loading the initial data for best performance.
### Indexing
See index build time for [HNSW](#index-build-time) and [IVFFlat](#index-build-time-1).
In production environments, create indexes concurrently to avoid blocking writes.
```sql
CREATE INDEX CONCURRENTLY ...
```
### Querying
Use `EXPLAIN ANALYZE` to debug performance.
```sql
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
### Exact Search
#### Exact Search
To speed up queries without an index, increase `max_parallel_workers_per_gather`.
@@ -422,7 +612,7 @@ If vectors are normalized to length 1 (like [OpenAI embeddings](https://platform
SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5;
```
### Approximate Search
#### Approximate Search
To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
@@ -430,7 +620,7 @@ To speed up queries with an IVFFlat index, increase the number of inverted lists
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 1000);
```
## Vacuuming
### Vacuuming
Vacuuming can take a while for HNSW indexes. Speed it up by reindexing first.
@@ -439,6 +629,41 @@ REINDEX INDEX CONCURRENTLY index_name;
VACUUM table_name;
```
## Monitoring
Monitor performance with [pg_stat_statements](https://www.postgresql.org/docs/current/pgstatstatements.html) (be sure to add it to `shared_preload_libraries`).
```sql
CREATE EXTENSION pg_stat_statements;
```
Get the most time-consuming queries with:
```sql
SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_time_ms,
ROUND((total_plan_time + total_exec_time) / 60000) AS total_time_min
FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20;
```
Note: Replace `total_plan_time + total_exec_time` with `total_time` for Postgres < 13
Monitor recall by comparing results from approximate search with exact search.
```sql
BEGIN;
SET LOCAL enable_indexscan = off; -- use exact search
SELECT ...
COMMIT;
```
## Scaling
Scale pgvector the same way you scale Postgres.
Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus.py)).
## Languages
Use pgvector from any language with a Postgres client. You can even generate and store vectors in one language and query them in another.
@@ -544,7 +769,17 @@ SELECT pg_size_pretty(pg_relation_size('index_name'));
#### Why isnt a query using an index?
The cost estimation in pgvector < 0.4.3 does not always work well with the planner. You can encourage the planner to use an index for a query with:
The query needs to have an `ORDER BY` and `LIMIT`, and the `ORDER BY` must be the result of a distance operator, not an expression.
```sql
-- index
ORDER BY embedding <=> '[3,1,2]' LIMIT 5;
-- no index
ORDER BY 1 - (embedding <=> '[3,1,2]') DESC LIMIT 5;
```
You can encourage the planner to use an index for a query with:
```sql
BEGIN;
@@ -573,6 +808,12 @@ or choose to store vectors inline:
ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
```
#### Why are there less results for a query after adding an HNSW index?
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead.
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
#### Why are there less results for a query after adding an IVFFlat index?
The index was likely created with too little data for the number of lists. Drop the index until the table has more data.
@@ -581,11 +822,20 @@ The index was likely created with too little data for the number of lists. Drop
DROP INDEX index_name;
```
Results can also be limited by the number of probes (`ivfflat.probes`).
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
## Reference
- [Vector](#vector-type)
- [Halfvec](#halfvec-type)
- [Bit](#bit-type)
- [Sparsevec](#sparsevec-type)
### Vector Type
Each vector takes `4 * dimensions + 8` bytes of storage. Each element is a single precision floating-point number (like the `real` type in Postgres), and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Vectors can have up to 16,000 dimensions.
Each vector takes `4 * dimensions + 8` bytes of storage. Each element is a single-precision floating-point number (like the `real` type in Postgres), and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Vectors can have up to 16,000 dimensions.
### Vector Operators
@@ -606,17 +856,81 @@ 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
quantize_binary(vector) → bit | quantize | unreleased
subvector(vector, integer, integer) → vector | subvector | unreleased
vector_dims(vector) → integer | number of dimensions |
vector_norm(vector) → double precision | Euclidean norm |
### Aggregate Functions
### Vector Aggregate Functions
Function | Description | Added
--- | --- | ---
avg(vector) → vector | average |
sum(vector) → vector | sum | 0.5.0
## Installation Notes
### Halfvec Type
Each half vector takes `2 * dimensions + 8` bytes of storage. Each element is a half-precision floating-point number, and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Half vectors can have up to 16,000 dimensions.
### Halfvec Operators
Operator | Description | Added
--- | --- | ---
<-> | Euclidean distance | unreleased
<#> | negative inner product | unreleased
<=> | cosine distance | unreleased
### Halfvec Functions
Function | Description | Added
--- | --- | ---
cosine_distance(halfvec, halfvec) → double precision | cosine distance | unreleased
inner_product(halfvec, halfvec) → double precision | inner product | unreleased
l2_distance(halfvec, halfvec) → double precision | Euclidean distance | unreleased
l1_distance(halfvec, halfvec) → double precision | taxicab distance | unreleased
quantize_binary(halfvec) → bit | quantize | unreleased
subvector(halfvec, integer, integer) → halfvec | subvector | unreleased
### Bit Type
Each bit vector takes `dimensions / 8 + 8` bytes of storage. See the [Postgres docs](https://www.postgresql.org/docs/current/datatype-bit.html) for more info.
### Bit Operators
Operator | Description | Added
--- | --- | ---
<~> | Hamming distance | unreleased
<%> | Jaccard distance | unreleased
### Bit Functions
Function | Description | Added
--- | --- | ---
hamming_distance(bit, bit) → double precision | Hamming distance | unreleased
jaccard_distance(bit, bit) → double precision | Jaccard distance | unreleased
### Sparsevec Type
Each sparse vector takes `8 * non-zero elements + 16` bytes of storage. Each element is a single-precision floating-point number, and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Sparse vectors can have up to 16,000 non-zero elements.
### Sparsevec Operators
Operator | Description | Added
--- | --- | ---
<-> | Euclidean distance | unreleased
<#> | negative inner product | unreleased
<=> | cosine distance | unreleased
### Sparsevec Functions
Function | Description | Added
--- | --- | ---
cosine_distance(sparsevec, sparsevec) → double precision | cosine distance | unreleased
inner_product(sparsevec, sparsevec) → double precision | inner product | unreleased
l2_distance(sparsevec, sparsevec) → double precision | Euclidean distance | unreleased
l1_distance(sparsevec, sparsevec) → double precision | taxicab distance | unreleased
## Installation Notes - Linux and Mac
### Postgres Location
@@ -656,6 +970,26 @@ Note: Replace `16` with your Postgres server version
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, reinstall Xcode Command Line Tools.
### Portability
By default, pgvector compiles with `-march=native` on some platforms for best performance. However, this can lead to `Illegal instruction` errors if trying to run the compiled extension on a different machine.
To compile for portability, use:
```sh
make OPTFLAGS=""
```
## Installation Notes - Windows
### Missing Header
If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct.
### Permissions
If installation fails with `Access is denied`, re-run the installation instructions as an administrator.
## Additional Installation Methods
### Docker
@@ -671,7 +1005,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
You can also build the image manually:
```sh
git clone --branch v0.6.0 https://github.com/pgvector/pgvector.git
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector
docker build --build-arg PG_MAJOR=16 -t myuser/pgvector .
```
@@ -716,6 +1050,21 @@ sudo dnf install pgvector_16
Note: Replace `16` with your Postgres server version
### pkg
Install the FreeBSD package with:
```sh
pkg install postgresql15-pg_vector
```
or the port with:
```sh
cd /usr/ports/databases/pgvector
make install
```
### conda-forge
With Conda Postgres, install from [conda-forge](https://anaconda.org/conda-forge/pgvector) with:
@@ -825,6 +1174,12 @@ make installcheck REGRESS=functions # regression test
make prove_installcheck PROVE_TESTS=test/t/001_ivfflat_wal.pl # TAP test
```
To enable assertions:
```sh
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
```
To enable benchmarking:
```sh
@@ -837,12 +1192,6 @@ To show memory usage:
make clean && PG_CFLAGS="-DHNSW_MEMORY -DIVFFLAT_MEMORY" make && make install
```
To enable assertions:
```sh
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
```
To get k-means metrics:
```sh

View File

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

View File

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

View File

@@ -0,0 +1,283 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.0'" to load this file. \quit
CREATE FUNCTION quantize_binary(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(vector, int, int) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
);
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit);
CREATE TYPE halfvec;
CREATE FUNCTION halfvec_in(cstring, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_out(halfvec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_recv(internal, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_send(halfvec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE halfvec (
INPUT = halfvec_in,
OUTPUT = halfvec_out,
TYPMOD_IN = halfvec_typmod_in,
RECEIVE = halfvec_recv,
SEND = halfvec_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_norm(halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION quantize_binary(halfvec) RETURNS bit
AS 'MODULE_PATHNAME', 'halfvec_quantize_binary' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(halfvec, int, int) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_spherical_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(integer[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(real[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(double precision[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(numeric[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_float4(halfvec, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (halfvec AS halfvec)
WITH FUNCTION halfvec(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS real[])
WITH FUNCTION halfvec_to_float4(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (integer[] AS halfvec)
WITH FUNCTION array_to_halfvec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS halfvec)
WITH FUNCTION array_to_halfvec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS halfvec)
WITH FUNCTION array_to_halfvec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS halfvec)
WITH FUNCTION array_to_halfvec(numeric[], integer, boolean) AS ASSIGNMENT;
CREATE OPERATOR <-> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec),
FUNCTION 3 l2_distance(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 halfvec_norm(halfvec);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 halfvec_norm(halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 halfvec_norm(halfvec);
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 halfvec_norm(halfvec);
CREATE FUNCTION halfvec_to_vector(halfvec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_halfvec(vector, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (halfvec AS vector)
WITH FUNCTION halfvec_to_vector(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS halfvec)
WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT;
CREATE TYPE sparsevec;
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE sparsevec (
INPUT = sparsevec_in,
OUTPUT = sparsevec_out,
TYPMOD_IN = sparsevec_typmod_in,
RECEIVE = sparsevec_recv,
SEND = sparsevec_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_norm(sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (sparsevec AS sparsevec)
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS vector)
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS sparsevec)
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
CREATE OPERATOR <-> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR CLASS sparsevec_l2_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_ip_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_cosine_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 2 sparsevec_norm(sparsevec);

View File

@@ -1,7 +1,7 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "CREATE EXTENSION vector" to load this file. \quit
-- type
-- vector type
CREATE TYPE vector;
@@ -29,7 +29,7 @@ CREATE TYPE vector (
STORAGE = external
);
-- functions
-- vector functions
CREATE FUNCTION l2_distance(vector, vector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -58,7 +58,13 @@ CREATE FUNCTION vector_sub(vector, vector) RETURNS vector
CREATE FUNCTION vector_mul(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- private functions
CREATE FUNCTION quantize_binary(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(vector, int, int) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- vector private functions
CREATE FUNCTION vector_lt(vector, vector) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -99,7 +105,7 @@ CREATE FUNCTION vector_avg(double precision[]) RETURNS vector
CREATE FUNCTION vector_combine(double precision[], double precision[]) RETURNS double precision[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- aggregates
-- vector aggregates
CREATE AGGREGATE avg(vector) (
SFUNC = vector_accum,
@@ -117,7 +123,7 @@ CREATE AGGREGATE sum(vector) (
PARALLEL = SAFE
);
-- cast functions
-- vector cast functions
CREATE FUNCTION vector(vector, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -137,7 +143,7 @@ CREATE FUNCTION array_to_vector(numeric[], integer, boolean) RETURNS vector
CREATE FUNCTION vector_to_float4(vector, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- casts
-- vector casts
CREATE CAST (vector AS vector)
WITH FUNCTION vector(vector, integer, boolean) AS IMPLICIT;
@@ -157,7 +163,7 @@ CREATE CAST (double precision[] AS vector)
CREATE CAST (numeric[] AS vector)
WITH FUNCTION array_to_vector(numeric[], integer, boolean) AS ASSIGNMENT;
-- operators
-- vector operators
CREATE OPERATOR <-> (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l2_distance,
@@ -180,8 +186,7 @@ CREATE OPERATOR + (
);
CREATE OPERATOR - (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub,
COMMUTATOR = -
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub
);
CREATE OPERATOR * (
@@ -195,11 +200,10 @@ CREATE OPERATOR < (
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
);
-- should use scalarlesel and scalarlejoinsel, but not supported in Postgres < 11
CREATE OPERATOR <= (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_le,
COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
CREATE OPERATOR = (
@@ -214,11 +218,10 @@ CREATE OPERATOR <> (
RESTRICT = eqsel, JOIN = eqjoinsel
);
-- should use scalargesel and scalargejoinsel, but not supported in Postgres < 11
CREATE OPERATOR >= (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_ge,
COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
RESTRICT = scalargesel, JOIN = scalargejoinsel
);
CREATE OPERATOR > (
@@ -243,7 +246,7 @@ CREATE ACCESS METHOD hnsw TYPE INDEX HANDLER hnswhandler;
COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method';
-- opclasses
-- vector opclasses
CREATE OPERATOR CLASS vector_ops
DEFAULT FOR TYPE vector USING btree AS
@@ -290,3 +293,310 @@ CREATE OPERATOR CLASS vector_cosine_ops
OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_negative_inner_product(vector, vector),
FUNCTION 2 vector_norm(vector);
-- bit functions
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
);
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit);
-- halfvec type
CREATE TYPE halfvec;
CREATE FUNCTION halfvec_in(cstring, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_out(halfvec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_recv(internal, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_send(halfvec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE halfvec (
INPUT = halfvec_in,
OUTPUT = halfvec_out,
TYPMOD_IN = halfvec_typmod_in,
RECEIVE = halfvec_recv,
SEND = halfvec_send,
STORAGE = external
);
-- halfvec functions
CREATE FUNCTION l2_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_norm(halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION quantize_binary(halfvec) RETURNS bit
AS 'MODULE_PATHNAME', 'halfvec_quantize_binary' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(halfvec, int, int) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec private functions
CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_spherical_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec cast functions
CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(integer[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(real[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(double precision[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(numeric[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_float4(halfvec, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec casts
CREATE CAST (halfvec AS halfvec)
WITH FUNCTION halfvec(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS real[])
WITH FUNCTION halfvec_to_float4(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (integer[] AS halfvec)
WITH FUNCTION array_to_halfvec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS halfvec)
WITH FUNCTION array_to_halfvec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS halfvec)
WITH FUNCTION array_to_halfvec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS halfvec)
WITH FUNCTION array_to_halfvec(numeric[], integer, boolean) AS ASSIGNMENT;
-- halfvec operators
CREATE OPERATOR <-> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
-- halfvec opclasses
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec),
FUNCTION 3 l2_distance(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 halfvec_norm(halfvec);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 halfvec_norm(halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 halfvec_norm(halfvec);
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 halfvec_norm(halfvec);
-- extension casts
CREATE FUNCTION halfvec_to_vector(halfvec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_halfvec(vector, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (halfvec AS vector)
WITH FUNCTION halfvec_to_vector(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS halfvec)
WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT;
--- sparsevec type
CREATE TYPE sparsevec;
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE sparsevec (
INPUT = sparsevec_in,
OUTPUT = sparsevec_out,
TYPMOD_IN = sparsevec_typmod_in,
RECEIVE = sparsevec_recv,
SEND = sparsevec_send,
STORAGE = external
);
-- sparsevec functions
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_norm(sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec private functions
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec cast functions
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec casts
CREATE CAST (sparsevec AS sparsevec)
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS vector)
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS sparsevec)
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
-- sparsevec operators
CREATE OPERATOR <-> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
-- sparsevec opclasses
CREATE OPERATOR CLASS sparsevec_l2_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_ip_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_cosine_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 2 sparsevec_norm(sparsevec);

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#include "postgres.h"
#include "bitvector.h"
#include "port/pg_bitutils.h"
#include "utils/varbit.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/*
* Allocate and initialize a new bit vector
*/
VarBit *
InitBitVector(int dim)
{
VarBit *result;
int size;
size = VARBITTOTALLEN(dim);
result = (VarBit *) palloc0(size);
SET_VARSIZE(result, size);
VARBITLEN(result) = dim;
return result;
}
/*
* Ensure same dimensions
*/
static inline void
CheckDims(VarBit *a, VarBit *b)
{
if (VARBITLEN(a) != VARBITLEN(b))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different bit lengths %u and %u", VARBITLEN(a), VARBITLEN(b))));
}
/*
* Get the Hamming distance between two bit vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(hamming_distance);
Datum
hamming_distance(PG_FUNCTION_ARGS)
{
VarBit *a = PG_GETARG_VARBIT_P(0);
VarBit *b = PG_GETARG_VARBIT_P(1);
unsigned char *ax = VARBITS(a);
unsigned char *bx = VARBITS(b);
uint64 distance = 0;
CheckDims(a, b);
/* TODO Improve performance */
for (uint32 i = 0; i < VARBITBYTES(a); i++)
distance += pg_number_of_ones[ax[i] ^ bx[i]];
PG_RETURN_FLOAT8((double) distance);
}
/*
* Get the Jaccard distance between two bit vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(jaccard_distance);
Datum
jaccard_distance(PG_FUNCTION_ARGS)
{
VarBit *a = PG_GETARG_VARBIT_P(0);
VarBit *b = PG_GETARG_VARBIT_P(1);
unsigned char *ax = VARBITS(a);
unsigned char *bx = VARBITS(b);
uint64 ab = 0;
uint64 aa;
uint64 bb;
CheckDims(a, b);
/* TODO Improve performance */
for (uint32 i = 0; i < VARBITBYTES(a); i++)
ab += pg_number_of_ones[ax[i] & bx[i]];
if (ab == 0)
PG_RETURN_FLOAT8(1);
aa = pg_popcount((char *) ax, VARBITBYTES(a));
bb = pg_popcount((char *) bx, VARBITBYTES(b));
PG_RETURN_FLOAT8(1 - (ab / ((double) (aa + bb - ab))));
}

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

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#include "postgres.h"
#include "halfutils.h"
#include "halfvec.h"
#ifdef HALFVEC_DISPATCH
#include <immintrin.h>
#if defined(HAVE__GET_CPUID)
#include <cpuid.h>
#elif defined(HAVE__CPUID)
#include <intrin.h>
#endif
#ifdef _MSC_VER
#define TARGET_F16C_FMA
#else
#define TARGET_F16C_FMA __attribute__((target("f16c,fma")))
#endif
#endif
float (*HalfvecL2SquaredDistance) (int dim, half * ax, half * bx);
float (*HalfvecInnerProduct) (int dim, half * ax, half * bx);
static float
HalfvecL2SquaredDistanceDefault(int dim, half * ax, half * bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
return distance;
}
#ifdef HALFVEC_DISPATCH
TARGET_F16C_FMA static float
HalfvecL2SquaredDistanceF16cFma(int dim, half * ax, half * bx)
{
float distance;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 dist = _mm256_setzero_ps();
for (i = 0; i < count; i += 8)
{
__m128i axi = _mm_loadu_si128((__m128i *) (ax + i));
__m128i bxi = _mm_loadu_si128((__m128i *) (bx + i));
__m256 axs = _mm256_cvtph_ps(axi);
__m256 bxs = _mm256_cvtph_ps(bxi);
__m256 diff = _mm256_sub_ps(axs, bxs);
dist = _mm256_fmadd_ps(diff, diff, dist);
}
_mm256_storeu_ps(s, dist);
distance = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
for (; i < dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
return distance;
}
#endif
static float
HalfvecInnerProductDefault(int dim, half * ax, half * bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
return distance;
}
#ifdef HALFVEC_DISPATCH
TARGET_F16C_FMA static float
HalfvecInnerProductF16cFma(int dim, half * ax, half * bx)
{
float distance;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 dist = _mm256_setzero_ps();
for (i = 0; i < count; i += 8)
{
__m128i axi = _mm_loadu_si128((__m128i *) (ax + i));
__m128i bxi = _mm_loadu_si128((__m128i *) (bx + i));
__m256 axs = _mm256_cvtph_ps(axi);
__m256 bxs = _mm256_cvtph_ps(bxi);
dist = _mm256_fmadd_ps(axs, bxs, dist);
}
_mm256_storeu_ps(s, dist);
distance = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
for (; i < dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
return distance;
}
#endif
#ifdef HALFVEC_DISPATCH
#define CPU_FEATURE_FMA (1 << 12)
#define CPU_FEATURE_F16C (1 << 29)
static bool
SupportsCpuFeature(unsigned int feature)
{
unsigned int exx[4] = {0, 0, 0, 0};
#if defined(HAVE__GET_CPUID)
__get_cpuid(1, &exx[0], &exx[1], &exx[2], &exx[3]);
#elif defined(HAVE__CPUID)
__cpuid(exx, 1);
#endif
return (exx[2] & feature) == feature;
}
#endif
void
HalfvecInit(void)
{
/*
* Could skip pointer when single function, but no difference in
* performance
*/
HalfvecL2SquaredDistance = HalfvecL2SquaredDistanceDefault;
HalfvecInnerProduct = HalfvecInnerProductDefault;
#ifdef HALFVEC_DISPATCH
if (SupportsCpuFeature(CPU_FEATURE_FMA | CPU_FEATURE_F16C))
{
HalfvecL2SquaredDistance = HalfvecL2SquaredDistanceF16cFma;
HalfvecInnerProduct = HalfvecInnerProductF16cFma;
}
#endif
}

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

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#include "postgres.h"
#include <math.h>
#include "bitvector.h"
#include "catalog/pg_type.h"
#include "common/shortest_dec.h"
#include "fmgr.h"
#include "halfutils.h"
#include "halfvec.h"
#include "lib/stringinfo.h"
#include "libpq/pqformat.h"
#include "port.h" /* for strtof() */
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
#include "utils/lsyscache.h"
#include "utils/numeric.h"
#include "vector.h"
#if PG_VERSION_NUM < 130000
#define TYPALIGN_DOUBLE 'd'
#define TYPALIGN_INT 'i'
#endif
/*
* Get a half from a message buffer
*/
static half
pq_getmsghalf(StringInfo msg)
{
union
{
half h;
uint16 i;
} swap;
swap.i = pq_getmsgint(msg, 2);
return swap.h;
}
/*
* Append a half to a StringInfo buffer
*/
static void
pq_sendhalf(StringInfo buf, half h)
{
union
{
half h;
uint16 i;
} swap;
swap.h = h;
pq_sendint16(buf, swap.i);
}
/*
* Ensure same dimensions
*/
static inline void
CheckDims(HalfVector * a, HalfVector * b)
{
if (a->dim != b->dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different halfvec dimensions %d and %d", a->dim, b->dim)));
}
/*
* Ensure expected dimensions
*/
static inline void
CheckExpectedDim(int32 typmod, int dim)
{
if (typmod != -1 && typmod != dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected %d dimensions, not %d", typmod, dim)));
}
/*
* Ensure valid dimensions
*/
static inline void
CheckDim(int dim)
{
if (dim < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("halfvec must have at least 1 dimension")));
if (dim > HALFVEC_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("halfvec cannot have more than %d dimensions", HALFVEC_MAX_DIM)));
}
/*
* Ensure finite element
*/
static inline void
CheckElement(half value)
{
if (HalfIsNan(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("NaN not allowed in halfvec")));
if (HalfIsInf(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("infinite value not allowed in halfvec")));
}
/*
* Allocate and initialize a new half vector
*/
HalfVector *
InitHalfVector(int dim)
{
HalfVector *result;
int size;
size = HALFVEC_SIZE(dim);
result = (HalfVector *) palloc0(size);
SET_VARSIZE(result, size);
result->dim = dim;
return result;
}
/*
* Check for whitespace, since array_isspace() is static
*/
static inline bool
halfvec_isspace(char ch)
{
if (ch == ' ' ||
ch == '\t' ||
ch == '\n' ||
ch == '\r' ||
ch == '\v' ||
ch == '\f')
return true;
return false;
}
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_in);
Datum
halfvec_in(PG_FUNCTION_ARGS)
{
char *lit = PG_GETARG_CSTRING(0);
int32 typmod = PG_GETARG_INT32(2);
half x[HALFVEC_MAX_DIM];
int dim = 0;
char *pt = lit;
HalfVector *result;
while (halfvec_isspace(*pt))
pt++;
if (*pt != '[')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type halfvec: \"%s\"", lit),
errdetail("Vector contents must start with \"[\".")));
pt++;
while (halfvec_isspace(*pt))
pt++;
if (*pt == ']')
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("halfvec must have at least 1 dimension")));
for (;;)
{
float val;
char *stringEnd;
if (dim == HALFVEC_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("halfvec cannot have more than %d dimensions", HALFVEC_MAX_DIM)));
while (halfvec_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 halfvec: \"%s\"", lit)));
errno = 0;
/* Postgres sets LC_NUMERIC to C on startup */
val = strtof(pt, &stringEnd);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type halfvec: \"%s\"", lit)));
x[dim] = Float4ToHalfUnchecked(val);
/* Check for range error like float4in */
if ((errno == ERANGE && isinf(val)) || (HalfIsInf(x[dim]) && !isinf(val)))
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type halfvec", pnstrdup(pt, stringEnd - pt))));
CheckElement(x[dim]);
dim++;
pt = stringEnd;
while (halfvec_isspace(*pt))
pt++;
if (*pt == ',')
pt++;
else if (*pt == ']')
{
pt++;
break;
}
else
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type halfvec: \"%s\"", lit)));
}
/* Only whitespace is allowed after the closing brace */
while (halfvec_isspace(*pt))
pt++;
if (*pt != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type halfvec: \"%s\"", lit),
errdetail("Junk after closing right brace.")));
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitHalfVector(dim);
for (int i = 0; i < dim; i++)
result->x[i] = x[i];
PG_RETURN_POINTER(result);
}
#define AppendChar(ptr, c) (*(ptr)++ = (c))
#define AppendFloat(ptr, f) ((ptr) += float_to_shortest_decimal_bufn((f), (ptr)))
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_out);
Datum
halfvec_out(PG_FUNCTION_ARGS)
{
HalfVector *vector = PG_GETARG_HALFVEC_P(0);
int dim = vector->dim;
char *buf;
char *ptr;
/*
* Need:
*
* dim * (FLOAT_SHORTEST_DECIMAL_LEN - 1) bytes for
* float_to_shortest_decimal_bufn
*
* dim - 1 bytes for separator
*
* 3 bytes for [, ], and \0
*/
buf = (char *) palloc(FLOAT_SHORTEST_DECIMAL_LEN * dim + 2);
ptr = buf;
AppendChar(ptr, '[');
for (int i = 0; i < dim; i++)
{
if (i > 0)
AppendChar(ptr, ',');
AppendFloat(ptr, HalfToFloat4(vector->x[i]));
}
AppendChar(ptr, ']');
*ptr = '\0';
PG_FREE_IF_COPY(vector, 0);
PG_RETURN_CSTRING(buf);
}
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_typmod_in);
Datum
halfvec_typmod_in(PG_FUNCTION_ARGS)
{
ArrayType *ta = PG_GETARG_ARRAYTYPE_P(0);
int32 *tl;
int n;
tl = ArrayGetIntegerTypmods(ta, &n);
if (n != 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("invalid type modifier")));
if (*tl < 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type halfvec must be at least 1")));
if (*tl > HALFVEC_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type halfvec cannot exceed %d", HALFVEC_MAX_DIM)));
PG_RETURN_INT32(*tl);
}
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_recv);
Datum
halfvec_recv(PG_FUNCTION_ARGS)
{
StringInfo buf = (StringInfo) PG_GETARG_POINTER(0);
int32 typmod = PG_GETARG_INT32(2);
HalfVector *result;
int16 dim;
int16 unused;
dim = pq_getmsgint(buf, sizeof(int16));
unused = pq_getmsgint(buf, sizeof(int16));
CheckDim(dim);
CheckExpectedDim(typmod, dim);
if (unused != 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected unused to be 0, not %d", unused)));
result = InitHalfVector(dim);
for (int i = 0; i < dim; i++)
{
result->x[i] = pq_getmsghalf(buf);
CheckElement(result->x[i]);
}
PG_RETURN_POINTER(result);
}
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_send);
Datum
halfvec_send(PG_FUNCTION_ARGS)
{
HalfVector *vec = PG_GETARG_HALFVEC_P(0);
StringInfoData buf;
pq_begintypsend(&buf);
pq_sendint(&buf, vec->dim, sizeof(int16));
pq_sendint(&buf, vec->unused, sizeof(int16));
for (int i = 0; i < vec->dim; i++)
pq_sendhalf(&buf, vec->x[i]);
PG_RETURN_BYTEA_P(pq_endtypsend(&buf));
}
/*
* Convert half vector to half vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec);
Datum
halfvec(PG_FUNCTION_ARGS)
{
HalfVector *vec = PG_GETARG_HALFVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
CheckExpectedDim(typmod, vec->dim);
PG_RETURN_POINTER(vec);
}
/*
* Convert array to half vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(array_to_halfvec);
Datum
array_to_halfvec(PG_FUNCTION_ARGS)
{
ArrayType *array = PG_GETARG_ARRAYTYPE_P(0);
int32 typmod = PG_GETARG_INT32(1);
HalfVector *result;
int16 typlen;
bool typbyval;
char typalign;
Datum *elemsp;
int nelemsp;
if (ARR_NDIM(array) > 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("array must be 1-D")));
if (ARR_HASNULL(array) && array_contains_nulls(array))
ereport(ERROR,
(errcode(ERRCODE_NULL_VALUE_NOT_ALLOWED),
errmsg("array must not contain nulls")));
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 = InitHalfVector(nelemsp);
if (ARR_ELEMTYPE(array) == INT4OID)
{
for (int i = 0; i < nelemsp; i++)
result->x[i] = Float4ToHalf(DatumGetInt32(elemsp[i]));
}
else if (ARR_ELEMTYPE(array) == FLOAT8OID)
{
for (int i = 0; i < nelemsp; i++)
result->x[i] = Float4ToHalf(DatumGetFloat8(elemsp[i]));
}
else if (ARR_ELEMTYPE(array) == FLOAT4OID)
{
for (int i = 0; i < nelemsp; i++)
result->x[i] = Float4ToHalf(DatumGetFloat4(elemsp[i]));
}
else if (ARR_ELEMTYPE(array) == NUMERICOID)
{
for (int i = 0; i < nelemsp; i++)
result->x[i] = Float4ToHalf(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);
}
/*
* Convert half vector to float4[]
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_to_float4);
Datum
halfvec_to_float4(PG_FUNCTION_ARGS)
{
HalfVector *vec = PG_GETARG_HALFVEC_P(0);
Datum *datums;
ArrayType *result;
datums = (Datum *) palloc(sizeof(Datum) * vec->dim);
for (int i = 0; i < vec->dim; i++)
datums[i] = Float4GetDatum(HalfToFloat4(vec->x[i]));
/* Use TYPALIGN_INT for float4 */
result = construct_array(datums, vec->dim, FLOAT4OID, sizeof(float4), true, TYPALIGN_INT);
pfree(datums);
PG_RETURN_POINTER(result);
}
/*
* Convert vector to half vec
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_halfvec);
Datum
vector_to_halfvec(PG_FUNCTION_ARGS)
{
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
HalfVector *result;
CheckDim(vec->dim);
CheckExpectedDim(typmod, vec->dim);
result = InitHalfVector(vec->dim);
for (int i = 0; i < vec->dim; i++)
result->x[i] = Float4ToHalf(vec->x[i]);
PG_RETURN_POINTER(result);
}
/*
* Get the L2 distance between half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_distance);
Datum
halfvec_l2_distance(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(sqrt((double) HalfvecL2SquaredDistance(a->dim, a->x, b->x)));
}
/*
* Get the L2 squared distance between half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_squared_distance);
Datum
halfvec_l2_squared_distance(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8((double) HalfvecL2SquaredDistance(a->dim, a->x, b->x));
}
/*
* Get the inner product of two half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_inner_product);
Datum
halfvec_inner_product(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8((double) HalfvecInnerProduct(a->dim, a->x, b->x));
}
/*
* Get the negative inner product of two half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_negative_inner_product);
Datum
halfvec_negative_inner_product(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8((double) -HalfvecInnerProduct(a->dim, a->x, b->x));
}
/*
* Get the cosine distance between two half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_cosine_distance);
Datum
halfvec_cosine_distance(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1);
half *ax = a->x;
half *bx = b->x;
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++)
{
float axi = HalfToFloat4(ax[i]);
float bxi = HalfToFloat4(bx[i]);
distance += axi * bxi;
norma += axi * axi;
normb += bxi * bxi;
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
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;
else if (similarity < -1)
similarity = -1;
PG_RETURN_FLOAT8(1 - similarity);
}
/*
* Get the distance for spherical k-means
* Currently uses angular distance since needs to satisfy triangle inequality
* Assumes inputs are unit vectors (skips norm)
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_spherical_distance);
Datum
halfvec_spherical_distance(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1);
double distance;
CheckDims(a, b);
distance = (double) HalfvecInnerProduct(a->dim, a->x, b->x);
/* Prevent NaN with acos with loss of precision */
if (distance > 1)
distance = 1;
else if (distance < -1)
distance = -1;
PG_RETURN_FLOAT8(acos(distance) / M_PI);
}
/*
* Get the L1 distance between two half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l1_distance);
Datum
halfvec_l1_distance(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1);
half *ax = a->x;
half *bx = b->x;
float distance = 0.0;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += fabsf(HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]));
PG_RETURN_FLOAT8((double) distance);
}
/*
* Get the L2 norm of a half vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_norm);
Datum
halfvec_norm(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
half *ax = a->x;
double norm = 0.0;
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
double axi = (double) HalfToFloat4(ax[i]);
norm += axi * axi;
}
PG_RETURN_FLOAT8(sqrt(norm));
}
/*
* Quantize a half vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_quantize_binary);
Datum
halfvec_quantize_binary(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
half *ax = a->x;
VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result);
for (int i = 0; i < a->dim; i++)
rx[i / 8] |= (HalfToFloat4(ax[i]) > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result);
}
/*
* Get a subvector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_subvector);
Datum
halfvec_subvector(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
int32 start = PG_GETARG_INT32(1);
int32 count = PG_GETARG_INT32(2);
int32 end = start + count;
half *ax = a->x;
HalfVector *result;
int dim;
/* Indexing starts at 1, like substring */
if (start < 1)
start = 1;
if (end > a->dim)
end = a->dim + 1;
dim = end - start;
CheckDim(dim);
result = InitHalfVector(dim);
for (int i = 0; i < dim; i++)
result->x[i] = ax[start - 1 + i];
PG_RETURN_POINTER(result);
}
/*
* Internal helper to compare half vectors
*/
int
halfvec_cmp_internal(HalfVector * a, HalfVector * b)
{
int dim = Min(a->dim, b->dim);
/* Check values before dimensions to be consistent with Postgres arrays */
for (int i = 0; i < dim; i++)
{
if (HalfToFloat4(a->x[i]) < HalfToFloat4(b->x[i]))
return -1;
if (HalfToFloat4(a->x[i]) > HalfToFloat4(b->x[i]))
return 1;
}
if (a->dim < b->dim)
return -1;
if (a->dim > b->dim)
return 1;
return 0;
}

47
src/halfvec.h Normal file
View File

@@ -0,0 +1,47 @@
#ifndef HALFVEC_H
#define HALFVEC_H
#define __STDC_WANT_IEC_60559_TYPES_EXT__
#include <float.h>
#include "vector.h"
#if defined(__x86_64__) || defined(_M_AMD64)
#define HALFVEC_DISPATCH
#endif
/* F16C has better performance than _Float16 (on x86-64) */
#if defined(__F16C__)
#define F16C_SUPPORT
#elif defined(__FLT16_MAX__) && !defined(HALFVEC_DISPATCH)
#define FLT16_SUPPORT
#endif
#ifdef FLT16_SUPPORT
#define half _Float16
#define HALF_MAX FLT16_MAX
#else
#define half uint16
#define HALF_MAX 65504
#endif
#define HALFVEC_MAX_DIM VECTOR_MAX_DIM
#define HALFVEC_SIZE(_dim) (offsetof(HalfVector, x) + sizeof(half)*(_dim))
#define DatumGetHalfVector(x) ((HalfVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_HALFVEC_P(x) DatumGetHalfVector(PG_GETARG_DATUM(x))
#define PG_RETURN_HALFVEC_P(x) PG_RETURN_POINTER(x)
typedef struct HalfVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int16 dim; /* number of dimensions */
int16 unused;
half x[FLEXIBLE_ARRAY_MEMBER];
} HalfVector;
HalfVector *InitHalfVector(int dim);
int halfvec_cmp_internal(HalfVector * a, HalfVector * b);
#endif

View File

@@ -8,6 +8,7 @@
#include "commands/progress.h"
#include "commands/vacuum.h"
#include "hnsw.h"
#include "miscadmin.h"
#include "utils/guc.h"
#include "utils/selfuncs.h"
@@ -28,7 +29,7 @@ static relopt_kind hnsw_relopt_kind;
* this grows bigger, we should use a shmem_request_hook and
* RequestAddinShmemSpace() to pre-reserve space for this.
*/
static void
void
HnswInitLockTranche(void)
{
int *tranche_ids;
@@ -53,7 +54,8 @@ HnswInitLockTranche(void)
void
HnswInit(void)
{
HnswInitLockTranche();
if (!process_shared_preload_libraries_in_progress)
HnswInitLockTranche();
hnsw_relopt_kind = add_reloption_kind();
add_int_reloption(hnsw_relopt_kind, "m", "Max number of connections",

View File

@@ -17,6 +17,7 @@
#endif
#define HNSW_MAX_DIM 2000
#define HNSW_MAX_NNZ 1000
/* Support functions */
#define HNSW_DISTANCE_PROC 1
@@ -55,6 +56,14 @@
#define HNSW_UPDATE_ENTRY_GREATER 1
#define HNSW_UPDATE_ENTRY_ALWAYS 2
typedef enum HnswType
{
HNSW_TYPE_VECTOR,
HNSW_TYPE_HALFVEC,
HNSW_TYPE_BIT,
HNSW_TYPE_SPARSEVEC
} HnswType;
/* Build phases */
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
#define PROGRESS_HNSW_PHASE_LOAD 2
@@ -80,7 +89,7 @@
#if PG_VERSION_NUM < 130000
#define list_delete_last(list) list_truncate(list, list_length(list) - 1)
#define list_sort(list, cmp) list_qsort(list, cmp)
#define list_sort(list, cmp) ((list) = list_qsort(list, cmp))
#endif
#define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
@@ -129,7 +138,7 @@ HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr)
HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
HnswPtrDeclare(char, DatumRelptr, DatumPtr);
typedef struct HnswElementData
struct HnswElementData
{
HnswElementPtr next;
ItemPointerData heaptids[HNSW_HEAPTIDS];
@@ -144,7 +153,7 @@ typedef struct HnswElementData
BlockNumber neighborPage;
DatumPtr value;
LWLock lock;
} HnswElementData;
};
typedef HnswElementData * HnswElement;
@@ -155,12 +164,12 @@ typedef struct HnswCandidate
bool closer;
} HnswCandidate;
typedef struct HnswNeighborArray
struct HnswNeighborArray
{
int length;
bool closerSet;
HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
} HnswNeighborArray;
};
typedef struct HnswPairingHeapNode
{
@@ -185,6 +194,7 @@ typedef struct HnswGraph
/* Entry state */
LWLock entryLock;
LWLock entryWaitLock;
HnswElementPtr entryPoint;
/* Allocations state */
@@ -234,12 +244,6 @@ typedef struct HnswAllocator
void *state;
} HnswAllocator;
typedef struct HnswSupport
{
FmgrInfo *procinfo;
Oid collation;
} HnswSupport;
typedef struct HnswBuildState
{
/* Info */
@@ -247,6 +251,7 @@ typedef struct HnswBuildState
Relation index;
IndexInfo *indexInfo;
ForkNumber forkNum;
HnswType type;
/* Settings */
int dimensions;
@@ -258,7 +263,7 @@ typedef struct HnswBuildState
double reltuples;
/* Support functions */
HnswSupport support;
FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
Oid collation;
@@ -267,7 +272,6 @@ typedef struct HnswBuildState
HnswGraph *graph;
double ml;
int maxLevel;
Vector *normvec;
/* Memory */
MemoryContext graphCtx;
@@ -335,7 +339,7 @@ typedef struct HnswScanOpaqueData
MemoryContext tmpCtx;
/* Support functions */
HnswSupport support;
FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
Oid collation;
} HnswScanOpaqueData;
@@ -355,7 +359,8 @@ typedef struct HnswVacuumState
int efConstruction;
/* Support functions */
HnswSupport support;
FmgrInfo *procinfo;
Oid collation;
/* Variables */
struct tidhash_hash *deleted;
@@ -371,30 +376,32 @@ typedef struct HnswVacuumState
int HnswGetM(Relation index);
int HnswGetEfConstruction(Relation index);
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
void HnswInitSupport(HnswSupport * support, Relation index);
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
HnswType HnswGetType(Relation index);
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type);
void HnswCheckValue(Datum value, HnswType type);
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
void HnswInitPage(Buffer buf, Page page);
void HnswInit(void);
List *HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement);
List *HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement);
HnswElement HnswGetEntryPoint(Relation index);
void HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint);
void *HnswAlloc(HnswAllocator * allocator, Size size);
HnswElement HnswInitElement(char *base, ItemPointer tid, int m, double ml, int maxLevel, HnswAllocator * alloc);
HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno);
void HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, HnswSupport * support, int m, int efConstruction, bool existing);
HnswCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, HnswSupport * support, bool loadVec);
void HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing);
HnswCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum, bool building);
void HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m);
void HnswAddHeapTid(HnswElement element, ItemPointer heaptid);
void HnswInitNeighbors(char *base, HnswElement element, int m, HnswAllocator * alloc);
bool HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building);
void HnswUpdateNeighborsOnDisk(Relation index, HnswSupport * support, HnswElement e, int m, bool checkExisting, bool building);
void HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building);
void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec);
void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, HnswSupport * support, bool loadVec);
void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element);
void HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, HnswSupport * support);
void HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
void HnswLoadNeighbors(HnswElement element, Relation index, int m);
void HnswInitLockTranche(void);
PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);
/* Index access methods */

View File

@@ -44,6 +44,7 @@
#include "access/xact.h"
#include "access/xloginsert.h"
#include "catalog/index.h"
#include "catalog/pg_type_d.h"
#include "commands/progress.h"
#include "hnsw.h"
#include "miscadmin.h"
@@ -176,7 +177,7 @@ CreateGraphPages(HnswBuildState * buildstate)
Size etupSize;
Size ntupSize;
Size combinedSize;
void *valuePtr = HnswPtrAccess(base, element->value);
Pointer valuePtr = HnswPtrAccess(base, element->value);
/* Update iterator */
iter = element->next;
@@ -373,7 +374,7 @@ AddElementInMemory(char *base, HnswGraph * graph, HnswElement element)
* Update neighbors
*/
static void
UpdateNeighborsInMemory(char *base, HnswSupport * support, HnswElement e, int m)
UpdateNeighborsInMemory(char *base, FmgrInfo *procinfo, Oid collation, HnswElement e, int m)
{
for (int lc = e->level; lc >= 0; lc--)
{
@@ -390,7 +391,7 @@ UpdateNeighborsInMemory(char *base, HnswSupport * support, HnswElement e, int m)
/* Use element for lock instead of hc since hc can be replaced */
LWLockAcquire(&neighborElement->lock, LW_EXCLUSIVE);
HnswUpdateConnection(base, e, hc, lm, lc, NULL, NULL, support);
HnswUpdateConnection(base, e, hc, lm, lc, NULL, NULL, procinfo, collation);
LWLockRelease(&neighborElement->lock);
}
}
@@ -400,7 +401,7 @@ UpdateNeighborsInMemory(char *base, HnswSupport * support, HnswElement e, int m)
* Update graph in memory
*/
static void
UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, int efConstruction, HnswElement entryPoint, HnswBuildState * buildstate)
UpdateGraphInMemory(FmgrInfo *procinfo, Oid collation, HnswElement element, int m, int efConstruction, HnswElement entryPoint, HnswBuildState * buildstate)
{
HnswGraph *graph = buildstate->graph;
char *base = buildstate->hnswarea;
@@ -413,7 +414,7 @@ UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, int efCon
AddElementInMemory(base, graph, element);
/* Update neighbors */
UpdateNeighborsInMemory(base, support, element, m);
UpdateNeighborsInMemory(base, procinfo, collation, element, m);
/* Update entry point if needed (already have lock) */
if (entryPoint == NULL || element->level > entryPoint->level)
@@ -426,13 +427,20 @@ UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, int efCon
static void
InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
{
FmgrInfo *procinfo = buildstate->procinfo;
Oid collation = buildstate->collation;
HnswGraph *graph = buildstate->graph;
HnswElement entryPoint;
LWLock *entryLock = &graph->entryLock;
LWLock *entryWaitLock = &graph->entryWaitLock;
int efConstruction = buildstate->efConstruction;
int m = buildstate->m;
char *base = buildstate->hnswarea;
/* Wait if another process needs exclusive lock on entry lock */
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
LWLockRelease(entryWaitLock);
/* Get entry point */
LWLockAcquire(entryLock, LW_SHARED);
entryPoint = HnswPtrAccess(base, graph->entryPoint);
@@ -443,18 +451,20 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
/* Release shared lock */
LWLockRelease(entryLock);
/* Get exclusive lock */
/* Tell other processes to wait and get exclusive lock */
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
LWLockAcquire(entryLock, LW_EXCLUSIVE);
LWLockRelease(entryWaitLock);
/* Get latest entry point after lock is acquired */
entryPoint = HnswPtrAccess(base, graph->entryPoint);
}
/* Find neighbors for element */
HnswFindElementNeighbors(base, element, entryPoint, NULL, &buildstate->support, m, efConstruction, false);
HnswFindElementNeighbors(base, element, entryPoint, NULL, procinfo, collation, m, efConstruction, false);
/* Update graph in memory */
UpdateGraphInMemory(&buildstate->support, element, m, efConstruction, entryPoint, buildstate);
UpdateGraphInMemory(procinfo, collation, element, m, efConstruction, entryPoint, buildstate);
/* Release entry lock */
LWLockRelease(entryLock);
@@ -477,10 +487,13 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
/* Detoast once for all calls */
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Check value */
HnswCheckValue(value, buildstate->type);
/* Normalize if needed */
if (buildstate->normprocinfo != NULL)
{
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->type))
return false;
}
@@ -599,6 +612,9 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
static void
InitGraph(HnswGraph * graph, char *base, long memoryTotal)
{
/* Initialize the lock tranche if needed */
HnswInitLockTranche();
HnswPtrStore(base, graph->head, (HnswElement) NULL);
HnswPtrStore(base, graph->entryPoint, (HnswElement) NULL);
graph->memoryUsed = 0;
@@ -607,6 +623,7 @@ InitGraph(HnswGraph * graph, char *base, long memoryTotal)
graph->indtuples = 0;
SpinLockInit(&graph->lock);
LWLockInitialize(&graph->entryLock, hnsw_lock_tranche_id);
LWLockInitialize(&graph->entryWaitLock, hnsw_lock_tranche_id);
LWLockInitialize(&graph->allocatorLock, hnsw_lock_tranche_id);
LWLockInitialize(&graph->flushLock, hnsw_lock_tranche_id);
}
@@ -652,27 +669,50 @@ HnswSharedMemoryAlloc(Size size, void *state)
return chunk;
}
/*
* Get max dimensions
*/
static int
GetMaxDimensions(HnswType type)
{
int maxDimensions = HNSW_MAX_DIM;
if (type == HNSW_TYPE_HALFVEC)
maxDimensions *= 2;
else if (type == HNSW_TYPE_BIT)
maxDimensions *= 32;
else if (type == HNSW_TYPE_SPARSEVEC)
maxDimensions = INT_MAX;
return maxDimensions;
}
/*
* Initialize the build state
*/
static void
InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum)
{
int maxDimensions;
buildstate->heap = heap;
buildstate->index = index;
buildstate->indexInfo = indexInfo;
buildstate->forkNum = forkNum;
buildstate->type = HnswGetType(index);
buildstate->m = HnswGetM(index);
buildstate->efConstruction = HnswGetEfConstruction(index);
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
maxDimensions = GetMaxDimensions(buildstate->type);
/* 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->dimensions > maxDimensions)
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", maxDimensions);
if (buildstate->efConstruction < 2 * buildstate->m)
elog(ERROR, "ef_construction must be greater than or equal to 2 * m");
@@ -681,7 +721,7 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->indtuples = 0;
/* Get support functions */
HnswInitSupport(&buildstate->support, index);
buildstate->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
buildstate->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
buildstate->collation = index->rd_indcollation[0];
@@ -690,9 +730,6 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->ml = HnswGetMl(buildstate->m);
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
/* Reuse for each tuple */
buildstate->normvec = InitVector(buildstate->dimensions);
buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext,
"Hnsw build graph context",
#if PG_VERSION_NUM >= 150000
@@ -716,7 +753,6 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
static void
FreeBuildState(HnswBuildState * buildstate)
{
pfree(buildstate->normvec);
MemoryContextDelete(buildstate->graphCtx);
MemoryContextDelete(buildstate->tmpCtx);
}
@@ -972,6 +1008,14 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
/* Report less than allocated so never fails */
InitGraph(&hnswshared->graphData, hnswarea, esthnswarea - 1024 * 1024);
/*
* Avoid base address for relptr for Postgres < 14.5
* https://github.com/postgres/postgres/commit/7201cd18627afc64850537806da7f22150d1a83b
*/
#if PG_VERSION_NUM < 140005
hnswshared->graphData.memoryUsed += MAXALIGN(1);
#endif
shm_toc_insert(pcxt->toc, PARALLEL_KEY_HNSW_SHARED, hnswshared);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_HNSW_AREA, hnswarea);

View File

@@ -340,7 +340,7 @@ ConnectionExists(HnswElement e, HnswNeighborTuple ntup, int startIdx, int lm)
* Update neighbors
*/
void
HnswUpdateNeighborsOnDisk(Relation index, HnswSupport * support, HnswElement e, int m, bool checkExisting, bool building)
HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building)
{
char *base = NULL;
@@ -373,7 +373,7 @@ HnswUpdateNeighborsOnDisk(Relation index, HnswSupport * support, HnswElement e,
*/
/* Select neighbors */
HnswUpdateConnection(NULL, e, hc, lm, lc, &idx, index, support);
HnswUpdateConnection(NULL, e, hc, lm, lc, &idx, index, procinfo, collation);
/* New element was not selected as a neighbor */
if (idx == -1)
@@ -527,7 +527,7 @@ FindDuplicateOnDisk(Relation index, HnswElement element, bool building)
* Update graph on disk
*/
static void
UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, int m, int efConstruction, HnswElement entryPoint, bool building)
UpdateGraphOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement element, int m, int efConstruction, HnswElement entryPoint, bool building)
{
BlockNumber newInsertPage = InvalidBlockNumber;
@@ -543,7 +543,7 @@ UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, in
HnswUpdateMetaPage(index, 0, NULL, newInsertPage, MAIN_FORKNUM, building);
/* Update neighbors */
HnswUpdateNeighborsOnDisk(index, support, element, m, false, building);
HnswUpdateNeighborsOnDisk(index, procinfo, collation, element, m, false, building);
/* Update entry point if needed */
if (entryPoint == NULL || element->level > entryPoint->level)
@@ -560,11 +560,10 @@ HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull,
HnswElement element;
int m;
int efConstruction = HnswGetEfConstruction(index);
FmgrInfo *procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
Oid collation = index->rd_indcollation[0];
LOCKMODE lockmode = ShareLock;
char *base = NULL;
HnswSupport support;
HnswInitSupport(&support, index);
/*
* Get a shared lock. This allows vacuum to ensure no in-flight inserts
@@ -595,10 +594,10 @@ HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull,
}
/* Find neighbors for element */
HnswFindElementNeighbors(base, element, entryPoint, index, &support, m, efConstruction, false);
HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, false);
/* Update graph on disk */
UpdateGraphOnDisk(index, &support, element, m, efConstruction, entryPoint, building);
UpdateGraphOnDisk(index, procinfo, collation, element, m, efConstruction, entryPoint, building);
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
@@ -615,15 +614,19 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
Datum value;
FmgrInfo *normprocinfo;
Oid collation = index->rd_indcollation[0];
HnswType type = HnswGetType(index);
/* Detoast once for all calls */
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Check value */
HnswCheckValue(value, type);
/* Normalize if needed */
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
if (normprocinfo != NULL)
{
if (!HnswNormValue(normprocinfo, collation, &value, NULL))
if (!HnswNormValue(normprocinfo, collation, &value, type))
return;
}

View File

@@ -15,6 +15,8 @@ GetScanItems(IndexScanDesc scan, Datum q)
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
Relation index = scan->indexRelation;
FmgrInfo *procinfo = so->procinfo;
Oid collation = so->collation;
List *ep;
List *w;
int m;
@@ -27,38 +29,15 @@ GetScanItems(IndexScanDesc scan, Datum q)
if (entryPoint == NULL)
return NIL;
ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, &so->support, false));
ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, procinfo, collation, false));
for (int lc = entryPoint->level; lc >= 1; lc--)
{
w = HnswSearchLayer(base, q, ep, 1, lc, index, &so->support, m, false, NULL);
w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, false, NULL);
ep = w;
}
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, &so->support, m, false, NULL);
}
/*
* Get dimensions from metapage
*/
static int
GetDimensions(Relation index)
{
Buffer buf;
Page page;
HnswMetaPage metap;
int dimensions;
buf = ReadBuffer(index, HNSW_METAPAGE_BLKNO);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
metap = HnswPageGetMeta(page);
dimensions = metap->dimensions;
UnlockReleaseBuffer(buf);
return dimensions;
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
}
/*
@@ -71,7 +50,7 @@ GetScanValue(IndexScanDesc scan)
Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
value = PointerGetDatum(NULL);
else
{
value = scan->orderByData->sk_argument;
@@ -82,7 +61,7 @@ GetScanValue(IndexScanDesc scan)
/* Fine if normalization fails */
if (so->normprocinfo != NULL)
HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
HnswNormValue(so->normprocinfo, so->collation, &value, HnswGetType(scan->indexRelation));
}
return value;
@@ -106,7 +85,7 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
ALLOCSET_DEFAULT_SIZES);
/* Set support functions */
HnswInitSupport(&so->support, index);
so->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
so->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
so->collation = index->rd_indcollation[0];
@@ -179,6 +158,10 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
so->first = false;
#if defined(HNSW_MEMORY) && PG_VERSION_NUM >= 130000
elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(so->tmpCtx, false) / (1024 * 1024));
#endif
}
while (list_length(so->w) > 0)

View File

@@ -3,12 +3,18 @@
#include <math.h>
#include "access/generic_xlog.h"
#include "catalog/pg_type.h"
#include "catalog/pg_type_d.h"
#include "halfutils.h"
#include "halfvec.h"
#include "hnsw.h"
#include "lib/pairingheap.h"
#include "sparsevec.h"
#include "storage/bufmgr.h"
#include "utils/datum.h"
#include "utils/memdebug.h"
#include "utils/rel.h"
#include "utils/syscache.h"
#include "vector.h"
#if PG_VERSION_NUM >= 130000
@@ -150,13 +156,39 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
}
/*
* Init support function
* Get type
*/
void
HnswInitSupport(HnswSupport * support, Relation index)
HnswType
HnswGetType(Relation index)
{
support->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
support->collation = index->rd_indcollation[0];
Oid typid = TupleDescAttr(index->rd_att, 0)->atttypid;
HeapTuple tuple;
Form_pg_type type;
HnswType result;
if (typid == BITOID)
return HNSW_TYPE_BIT;
tuple = SearchSysCache1(TYPEOID, ObjectIdGetDatum(typid));
if (!HeapTupleIsValid(tuple))
elog(ERROR, "cache lookup failed for type %u", typid);
type = (Form_pg_type) GETSTRUCT(tuple);
if (strcmp(NameStr(type->typname), "vector") == 0)
result = HNSW_TYPE_VECTOR;
else if (strcmp(NameStr(type->typname), "halfvec") == 0)
result = HNSW_TYPE_HALFVEC;
else if (strcmp(NameStr(type->typname), "sparsevec") == 0)
result = HNSW_TYPE_SPARSEVEC;
else
{
ReleaseSysCache(tuple);
elog(ERROR, "type not supported for hnsw index");
}
ReleaseSysCache(tuple);
return result;
}
/*
@@ -168,21 +200,50 @@ HnswInitSupport(HnswSupport * support, Relation index)
* if it's different than the original value
*/
bool
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type)
{
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0)
{
Vector *v = DatumGetVector(*value);
/* TODO Remove vector-specific code */
if (type == HNSW_TYPE_VECTOR)
{
Vector *v = DatumGetVector(*value);
Vector *result = InitVector(v->dim);
if (result == NULL)
result = InitVector(v->dim);
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
*value = PointerGetDatum(result);
}
else if (type == HNSW_TYPE_HALFVEC)
{
HalfVector *v = DatumGetHalfVector(*value);
HalfVector *result = InitHalfVector(v->dim);
*value = PointerGetDatum(result);
for (int i = 0; i < v->dim; i++)
result->x[i] = Float4ToHalfUnchecked(HalfToFloat4(v->x[i]) / norm);
*value = PointerGetDatum(result);
}
else if (type == HNSW_TYPE_SPARSEVEC)
{
SparseVector *v = DatumGetSparseVector(*value);
SparseVector *result = InitSparseVector(v->dim, v->nnz);
float *vx = SPARSEVEC_VALUES(v);
float *rx = SPARSEVEC_VALUES(result);
for (int i = 0; i < v->nnz; i++)
{
result->indices[i] = v->indices[i];
rx[i] = vx[i] / norm;
}
*value = PointerGetDatum(result);
}
else
elog(ERROR, "Unsupported type");
return true;
}
@@ -190,6 +251,21 @@ HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
return false;
}
/*
* Check if a value can be indexed
*/
void
HnswCheckValue(Datum value, HnswType type)
{
if (type == HNSW_TYPE_SPARSEVEC)
{
SparseVector *vec = DatumGetSparseVector(value);
if (vec->nnz > HNSW_MAX_NNZ)
elog(ERROR, "sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ);
}
}
/*
* New buffer
*/
@@ -565,7 +641,7 @@ HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHe
* Load an element and optionally get its distance from q
*/
void
HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, HnswSupport * support, bool loadVec)
HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec)
{
Buffer buf;
Page page;
@@ -585,7 +661,12 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
/* Calculate distance */
if (distance != NULL)
*distance = (float) DatumGetFloat8(FunctionCall2Coll(support->procinfo, support->collation, *q, PointerGetDatum(&etup->data)));
{
if (DatumGetPointer(*q) == NULL)
*distance = 0;
else
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
}
UnlockReleaseBuffer(buf);
}
@@ -594,27 +675,27 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
* Get the distance for a candidate
*/
static float
GetCandidateDistance(char *base, HnswCandidate * hc, Datum q, HnswSupport * support)
GetCandidateDistance(char *base, HnswCandidate * hc, Datum q, FmgrInfo *procinfo, Oid collation)
{
HnswElement hce = HnswPtrAccess(base, hc->element);
Datum value = HnswGetValue(base, hce);
return DatumGetFloat8(FunctionCall2Coll(support->procinfo, support->collation, q, value));
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, q, value));
}
/*
* Create a candidate for the entry point
*/
HnswCandidate *
HnswEntryCandidate(char *base, HnswElement entryPoint, Datum q, Relation index, HnswSupport * support, bool loadVec)
HnswEntryCandidate(char *base, HnswElement entryPoint, Datum q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec)
{
HnswCandidate *hc = palloc(sizeof(HnswCandidate));
HnswPtrStore(base, hc->element, entryPoint);
if (index == NULL)
hc->distance = GetCandidateDistance(base, hc, q, support);
hc->distance = GetCandidateDistance(base, hc, q, procinfo, collation);
else
HnswLoadElement(entryPoint, &hc->distance, &q, index, support, loadVec);
HnswLoadElement(entryPoint, &hc->distance, &q, index, procinfo, collation, loadVec);
return hc;
}
@@ -732,7 +813,7 @@ CountElement(char *base, HnswElement skipElement, HnswCandidate * hc)
* Algorithm 2 from paper
*/
List *
HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement)
HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement)
{
List *w = NIL;
pairingheap *C = pairingheap_allocate(CompareNearestCandidates, NULL);
@@ -814,9 +895,9 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, H
f = ((HnswPairingHeapNode *) pairingheap_first(W))->inner;
if (index == NULL)
eDistance = GetCandidateDistance(base, e, q, support);
eDistance = GetCandidateDistance(base, e, q, procinfo, collation);
else
HnswLoadElement(eElement, &eDistance, &q, index, support, inserting);
HnswLoadElement(eElement, &eDistance, &q, index, procinfo, collation, inserting);
Assert(!eElement->deleted);
@@ -870,12 +951,15 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, H
static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistances(const ListCell *a, const ListCell *b)
{
HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b);
#else
CompareCandidateDistances(const void *a, const void *b)
#endif
{
HnswCandidate *hca = lfirst((ListCell *) a);
HnswCandidate *hcb = lfirst((ListCell *) b);
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif
if (hca->distance < hcb->distance)
return 1;
@@ -898,12 +982,15 @@ CompareCandidateDistances(const void *a, const void *b)
static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b)
{
HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b);
#else
CompareCandidateDistancesOffset(const void *a, const void *b)
#endif
{
HnswCandidate *hca = lfirst((ListCell *) a);
HnswCandidate *hcb = lfirst((ListCell *) b);
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif
if (hca->distance < hcb->distance)
return 1;
@@ -924,19 +1011,19 @@ CompareCandidateDistancesOffset(const void *a, const void *b)
* Calculate the distance between elements
*/
static float
HnswGetDistance(char *base, HnswElement a, HnswElement b, HnswSupport * support)
HnswGetDistance(char *base, HnswElement a, HnswElement b, FmgrInfo *procinfo, Oid collation)
{
Datum aValue = HnswGetValue(base, a);
Datum bValue = HnswGetValue(base, b);
return DatumGetFloat8(FunctionCall2Coll(support->procinfo, support->collation, aValue, bValue));
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, aValue, bValue));
}
/*
* Check if an element is closer to q than any element from R
*/
static bool
CheckElementCloser(char *base, HnswCandidate * e, List *r, HnswSupport * support)
CheckElementCloser(char *base, HnswCandidate * e, List *r, FmgrInfo *procinfo, Oid collation)
{
HnswElement eElement = HnswPtrAccess(base, e->element);
ListCell *lc2;
@@ -945,7 +1032,7 @@ CheckElementCloser(char *base, HnswCandidate * e, List *r, HnswSupport * support
{
HnswCandidate *ri = lfirst(lc2);
HnswElement riElement = HnswPtrAccess(base, ri->element);
float distance = HnswGetDistance(base, eElement, riElement, support);
float distance = HnswGetDistance(base, eElement, riElement, procinfo, collation);
if (distance <= e->distance)
return false;
@@ -958,11 +1045,13 @@ CheckElementCloser(char *base, HnswCandidate * e, List *r, HnswSupport * support
* Algorithm 4 from paper
*/
static List *
SelectNeighbors(char *base, List *c, int lm, int lc, HnswSupport * support, HnswElement e2, HnswCandidate * newCandidate, HnswCandidate * *pruned, bool sortCandidates)
SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid collation, HnswElement e2, HnswCandidate * newCandidate, HnswCandidate * *pruned, bool sortCandidates)
{
List *r = NIL;
List *w = list_copy(c);
pairingheap *wd;
HnswCandidate **wd;
int wdlen = 0;
int wdoff = 0;
HnswNeighborArray *neighbors = HnswGetNeighbors(base, e2, lc);
bool mustCalculate = !neighbors->closerSet;
List *added = NIL;
@@ -971,7 +1060,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, HnswSupport * support, Hnsw
if (list_length(w) <= lm)
return w;
wd = pairingheap_allocate(CompareNearestCandidates, NULL);
wd = palloc(sizeof(HnswCandidate *) * list_length(w));
/* Ensure order of candidates is deterministic for closer caching */
if (sortCandidates)
@@ -991,7 +1080,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, HnswSupport * support, Hnsw
/* Use previous state of r and wd to skip work when possible */
if (mustCalculate)
e->closer = CheckElementCloser(base, e, r, support);
e->closer = CheckElementCloser(base, e, r, procinfo, collation);
else if (list_length(added) > 0)
{
/* Keep Valgrind happy for in-memory, parallel builds */
@@ -1004,7 +1093,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, HnswSupport * support, Hnsw
*/
if (e->closer)
{
e->closer = CheckElementCloser(base, e, added, support);
e->closer = CheckElementCloser(base, e, added, procinfo, collation);
if (!e->closer)
removedAny = true;
@@ -1017,7 +1106,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, HnswSupport * support, Hnsw
*/
if (removedAny)
{
e->closer = CheckElementCloser(base, e, r, support);
e->closer = CheckElementCloser(base, e, r, procinfo, collation);
if (e->closer)
added = lappend(added, e);
}
@@ -1025,7 +1114,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, HnswSupport * support, Hnsw
}
else if (e == newCandidate)
{
e->closer = CheckElementCloser(base, e, r, support);
e->closer = CheckElementCloser(base, e, r, procinfo, collation);
if (e->closer)
added = lappend(added, e);
}
@@ -1037,21 +1126,21 @@ SelectNeighbors(char *base, List *c, int lm, int lc, HnswSupport * support, Hnsw
if (e->closer)
r = lappend(r, e);
else
pairingheap_add(wd, &(CreatePairingHeapNode(e)->ph_node));
wd[wdlen++] = e;
}
/* Cached value can only be used in future if sorted deterministically */
neighbors->closerSet = sortCandidates;
/* Keep pruned connections */
while (!pairingheap_is_empty(wd) && list_length(r) < lm)
r = lappend(r, ((HnswPairingHeapNode *) pairingheap_remove_first(wd))->inner);
while (wdoff < wdlen && list_length(r) < lm)
r = lappend(r, wd[wdoff++]);
/* Return pruned for update connections */
if (pruned != NULL)
{
if (!pairingheap_is_empty(wd))
*pruned = ((HnswPairingHeapNode *) pairingheap_first(wd))->inner;
if (wdoff < wdlen)
*pruned = wd[wdoff];
else
*pruned = linitial(w);
}
@@ -1076,7 +1165,7 @@ AddConnections(char *base, HnswElement element, List *neighbors, int lc)
* Update connections
*/
void
HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, HnswSupport * support)
HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation)
{
HnswElement hce = HnswPtrAccess(base, hc->element);
HnswNeighborArray *currentNeighbors = HnswGetNeighbors(base, hce, lc);
@@ -1109,9 +1198,9 @@ HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm
HnswElement hc3Element = HnswPtrAccess(base, hc3->element);
if (HnswPtrIsNull(base, hc3Element->value))
HnswLoadElement(hc3Element, &hc3->distance, &q, index, support, true);
HnswLoadElement(hc3Element, &hc3->distance, &q, index, procinfo, collation, true);
else
hc3->distance = GetCandidateDistance(base, hc3, q, support);
hc3->distance = GetCandidateDistance(base, hc3, q, procinfo, collation);
/* Prune element if being deleted */
if (hc3Element->heaptidsLength == 0)
@@ -1131,7 +1220,7 @@ HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm
c = lappend(c, &currentNeighbors->items[i]);
c = lappend(c, &hc2);
SelectNeighbors(base, c, lm, lc, support, hce, &hc2, &pruned, true);
SelectNeighbors(base, c, lm, lc, procinfo, collation, hce, &hc2, &pruned, true);
/* Should not happen */
if (pruned == NULL)
@@ -1205,7 +1294,7 @@ PrecomputeHash(char *base, HnswElement element)
* Algorithm 1 from paper
*/
void
HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, HnswSupport * support, int m, int efConstruction, bool existing)
HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing)
{
List *ep;
List *w;
@@ -1225,13 +1314,13 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
return;
/* Get entry point and level */
ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, support, true));
ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, procinfo, collation, true));
entryLevel = entryPoint->level;
/* 1st phase: greedy search to insert level */
for (int lc = entryLevel; lc >= level + 1; lc--)
{
w = HnswSearchLayer(base, q, ep, 1, lc, index, support, m, true, skipElement);
w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, true, skipElement);
ep = w;
}
@@ -1249,7 +1338,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
List *neighbors;
List *lw;
w = HnswSearchLayer(base, q, ep, efConstruction, lc, index, support, m, true, skipElement);
w = HnswSearchLayer(base, q, ep, efConstruction, lc, index, procinfo, collation, m, true, skipElement);
/* Elements being deleted or skipped can help with search */
/* but should be removed before selecting neighbors */
@@ -1263,7 +1352,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
* sortCandidates to true for in-memory builds to enable closer
* caching, but there does not seem to be a difference in performance.
*/
neighbors = SelectNeighbors(base, lw, lm, lc, support, element, NULL, NULL, false);
neighbors = SelectNeighbors(base, lw, lm, lc, procinfo, collation, element, NULL, NULL, false);
AddConnections(base, element, neighbors, lc);

View File

@@ -189,6 +189,8 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
GenericXLogState *state;
int m = vacuumstate->m;
int efConstruction = vacuumstate->efConstruction;
FmgrInfo *procinfo = vacuumstate->procinfo;
Oid collation = vacuumstate->collation;
BufferAccessStrategy bas = vacuumstate->bas;
HnswNeighborTuple ntup = vacuumstate->ntup;
Size ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, m);
@@ -203,7 +205,7 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
element->heaptidsLength = 0;
/* Find neighbors for element, skipping itself */
HnswFindElementNeighbors(base, element, entryPoint, index, &vacuumstate->support, m, efConstruction, true);
HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, true);
/* Zero memory for each element */
MemSet(ntup, 0, HNSW_TUPLE_ALLOC_SIZE);
@@ -227,7 +229,7 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
UnlockReleaseBuffer(buf);
/* Update neighbors */
HnswUpdateNeighborsOnDisk(index, &vacuumstate->support, element, m, true, false);
HnswUpdateNeighborsOnDisk(index, procinfo, collation, element, m, true, false);
}
/*
@@ -254,7 +256,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
LockPage(index, HNSW_UPDATE_LOCK, ShareLock);
/* Load element */
HnswLoadElement(highestPoint, NULL, NULL, index, &vacuumstate->support, true);
HnswLoadElement(highestPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true);
/* Repair if needed */
if (NeedsUpdated(vacuumstate, highestPoint))
@@ -292,7 +294,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
* is outdated, this can remove connections at higher levels in
* the graph until they are repaired, but this should be fine.
*/
HnswLoadElement(entryPoint, NULL, NULL, index, &vacuumstate->support, true);
HnswLoadElement(entryPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true);
if (NeedsUpdated(vacuumstate, entryPoint))
{
@@ -571,8 +573,8 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
vacuumstate->callback_state = callback_state;
vacuumstate->efConstruction = HnswGetEfConstruction(index);
vacuumstate->bas = GetAccessStrategy(BAS_BULKREAD);
vacuumstate->support.procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
vacuumstate->support.collation = index->rd_indcollation[0];
vacuumstate->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
vacuumstate->collation = index->rd_indcollation[0];
vacuumstate->ntup = palloc0(HNSW_TUPLE_ALLOC_SIZE);
vacuumstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw vacuum temporary context",

View File

@@ -10,12 +10,14 @@
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
#include "commands/progress.h"
#include "halfvec.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "optimizer/optimizer.h"
#include "storage/bufmgr.h"
#include "tcop/tcopprot.h"
#include "utils/memutils.h"
#include "vector.h"
#if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h"
@@ -57,13 +59,13 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
*/
if (buildstate->kmeansnormprocinfo != NULL)
{
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->normvec))
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->type))
return;
}
if (samples->length < targsamples)
{
VectorArraySet(samples, samples->length, DatumGetVector(value));
VectorArraySet(samples, samples->length, DatumGetPointer(value));
samples->length++;
}
else
@@ -80,7 +82,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
#endif
Assert(k >= 0 && k < targsamples);
VectorArraySet(samples, k, DatumGetVector(value));
VectorArraySet(samples, k, DatumGetPointer(value));
}
buildstate->rowstoskip -= 1;
@@ -105,7 +107,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
/* Add sample */
AddSample(values, state);
AddSample(values, buildstate);
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
@@ -153,7 +155,7 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
/* Normalize if needed */
if (buildstate->normprocinfo != NULL)
{
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->type))
return;
}
@@ -312,25 +314,58 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
}
}
/*
* Get max dimensions
*/
static int
GetMaxDimensions(IvfflatType type)
{
int maxDimensions = IVFFLAT_MAX_DIM;
if (type == IVFFLAT_TYPE_HALFVEC)
maxDimensions *= 2;
return maxDimensions;
}
/*
* Get item size
*/
static Size
GetItemSize(IvfflatType type, int dimensions)
{
if (type == IVFFLAT_TYPE_VECTOR)
return VECTOR_SIZE(dimensions);
else if (type == IVFFLAT_TYPE_HALFVEC)
return HALFVEC_SIZE(dimensions);
else
elog(ERROR, "Unsupported type");
}
/*
* Initialize the build state
*/
static void
InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo)
{
int maxDimensions;
buildstate->heap = heap;
buildstate->index = index;
buildstate->indexInfo = indexInfo;
buildstate->type = IvfflatGetType(index);
buildstate->lists = IvfflatGetLists(index);
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
maxDimensions = GetMaxDimensions(buildstate->type);
/* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0)
elog(ERROR, "column does not have dimensions");
if (buildstate->dimensions > IVFFLAT_MAX_DIM)
elog(ERROR, "column cannot have more than %d dimensions for ivfflat index", IVFFLAT_MAX_DIM);
if (buildstate->dimensions > maxDimensions)
elog(ERROR, "column cannot have more than %d dimensions for ivfflat index", maxDimensions);
buildstate->reltuples = 0;
buildstate->indtuples = 0;
@@ -353,12 +388,9 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->slot = MakeSingleTupleTableSlot(buildstate->tupdesc, &TTSOpsVirtual);
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions);
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, GetItemSize(buildstate->type, buildstate->dimensions));
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
/* Reuse for each tuple */
buildstate->normvec = InitVector(buildstate->dimensions);
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat build temporary context",
ALLOCSET_DEFAULT_SIZES);
@@ -380,7 +412,6 @@ FreeBuildState(IvfflatBuildState * buildstate)
{
VectorArrayFree(buildstate->centers);
pfree(buildstate->listInfo);
pfree(buildstate->normvec);
#ifdef IVFFLAT_KMEANS_DEBUG
pfree(buildstate->listSums);
@@ -412,7 +443,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
/* Sample rows */
/* TODO Ensure within maintenance_work_mem */
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions);
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions, buildstate->centers->itemsize);
if (buildstate->heap != NULL)
{
SampleRows(buildstate);
@@ -427,7 +458,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
}
/* Calculate centers */
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers));
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers, buildstate->type));
/* Free samples before we allocate more memory */
VectorArrayFree(buildstate->samples);
@@ -472,7 +503,7 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
Size listSize;
IvfflatList list;
listSize = MAXALIGN(IVFFLAT_LIST_SIZE(dimensions));
listSize = MAXALIGN(IVFFLAT_LIST_SIZE(centers->itemsize));
list = palloc0(listSize);
buf = IvfflatNewBuffer(index, forkNum);
@@ -485,7 +516,7 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
/* Load list */
list->startPage = InvalidBlockNumber;
list->insertPage = InvalidBlockNumber;
memcpy(&list->center, VectorArrayGet(centers, i), VECTOR_SIZE(dimensions));
memcpy(&list->center, VectorArrayGet(centers, i), centers->itemsize);
/* Ensure free space */
if (PageGetFreeSpace(page) < listSize)
@@ -590,7 +621,7 @@ ParallelHeapScan(IvfflatBuildState * buildstate)
* Perform a worker's portion of a parallel sort
*/
static void
IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, Sharedsort *sharedsort, Vector * ivfcenters, int sortmem, bool progress)
IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, Sharedsort *sharedsort, char *ivfcenters, int sortmem, bool progress)
{
SortCoordinate coordinate;
IvfflatBuildState buildstate;
@@ -614,7 +645,7 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
indexInfo = BuildIndexInfo(ivfspool->index);
indexInfo->ii_Concurrent = ivfshared->isconcurrent;
InitBuildState(&buildstate, ivfspool->heap, ivfspool->index, indexInfo);
memcpy(buildstate.centers->items, ivfcenters, VECTOR_SIZE(buildstate.centers->dim) * buildstate.centers->maxlen);
memcpy(buildstate.centers->items, ivfcenters, buildstate.centers->itemsize * buildstate.centers->maxlen);
buildstate.centers->length = buildstate.centers->maxlen;
ivfspool->sortstate = tuplesort_begin_heap(buildstate.tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, sortmem, coordinate, false);
buildstate.sortstate = ivfspool->sortstate;
@@ -662,7 +693,7 @@ IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc)
IvfflatSpool *ivfspool;
IvfflatShared *ivfshared;
Sharedsort *sharedsort;
Vector *ivfcenters;
char *ivfcenters;
Relation heapRel;
Relation indexRel;
LOCKMODE heapLockmode;
@@ -776,7 +807,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
Size estcenters;
IvfflatShared *ivfshared;
Sharedsort *sharedsort;
Vector *ivfcenters;
char *ivfcenters;
IvfflatLeader *ivfleader = (IvfflatLeader *) palloc0(sizeof(IvfflatLeader));
bool leaderparticipates = true;
int querylen;
@@ -803,7 +834,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
shm_toc_estimate_chunk(&pcxt->estimator, estivfshared);
estsort = tuplesort_estimate_shared(scantuplesortstates);
shm_toc_estimate_chunk(&pcxt->estimator, estsort);
estcenters = VECTOR_SIZE(buildstate->dimensions) * buildstate->lists;
estcenters = buildstate->centers->itemsize * buildstate->centers->maxlen;
shm_toc_estimate_chunk(&pcxt->estimator, estcenters);
shm_toc_estimate_keys(&pcxt->estimator, 3);
@@ -855,7 +886,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
tuplesort_initialize_shared(sharedsort, scantuplesortstates,
pcxt->seg);
ivfcenters = (Vector *) shm_toc_allocate(pcxt->toc, estcenters);
ivfcenters = shm_toc_allocate(pcxt->toc, estcenters);
memcpy(ivfcenters, buildstate->centers->items, estcenters);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_IVFFLAT_SHARED, ivfshared);

View File

@@ -43,13 +43,19 @@
#define IVFFLAT_MAX_LISTS 32768
#define IVFFLAT_DEFAULT_PROBES 1
typedef enum IvfflatType
{
IVFFLAT_TYPE_VECTOR,
IVFFLAT_TYPE_HALFVEC
} IvfflatType;
/* Build phases */
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
#define PROGRESS_IVFFLAT_PHASE_KMEANS 2
#define PROGRESS_IVFFLAT_PHASE_ASSIGN 3
#define PROGRESS_IVFFLAT_PHASE_LOAD 4
#define IVFFLAT_LIST_SIZE(_dim) (offsetof(IvfflatListData, center) + VECTOR_SIZE(_dim))
#define IVFFLAT_LIST_SIZE(size) (offsetof(IvfflatListData, center) + size)
#define IvfflatPageGetOpaque(page) ((IvfflatPageOpaque) PageGetSpecialPointer(page))
#define IvfflatPageGetMeta(page) ((IvfflatMetaPageData *) PageGetContents(page))
@@ -85,7 +91,8 @@ typedef struct VectorArrayData
int length;
int maxlen;
int dim;
Vector *items;
Size itemsize;
char *items;
} VectorArrayData;
typedef VectorArrayData * VectorArray;
@@ -144,7 +151,7 @@ typedef struct IvfflatLeader
IvfflatShared *ivfshared;
Sharedsort *sharedsort;
Snapshot snapshot;
Vector *ivfcenters;
char *ivfcenters;
} IvfflatLeader;
typedef struct IvfflatBuildState
@@ -153,6 +160,7 @@ typedef struct IvfflatBuildState
Relation heap;
Relation index;
IndexInfo *indexInfo;
IvfflatType type;
/* Settings */
int dimensions;
@@ -172,7 +180,6 @@ typedef struct IvfflatBuildState
VectorArray samples;
VectorArray centers;
ListInfo *listInfo;
Vector *normvec;
#ifdef IVFFLAT_KMEANS_DEBUG
double inertia;
@@ -256,18 +263,18 @@ typedef struct IvfflatScanOpaqueData
typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
#define VECTOR_ARRAY_SIZE(_length, _dim) (sizeof(VectorArrayData) + (_length) * VECTOR_SIZE(_dim))
#define VECTOR_ARRAY_OFFSET(_arr, _offset) ((char*) (_arr)->items + (_offset) * VECTOR_SIZE((_arr)->dim))
#define VectorArrayGet(_arr, _offset) ((Vector *) VECTOR_ARRAY_OFFSET(_arr, _offset))
#define VectorArraySet(_arr, _offset, _val) memcpy(VECTOR_ARRAY_OFFSET(_arr, _offset), _val, VECTOR_SIZE((_arr)->dim))
#define VECTOR_ARRAY_SIZE(_length, _size) (sizeof(VectorArrayData) + (_length) * _size)
#define VECTOR_ARRAY_OFFSET(_arr, _offset) ((char*) (_arr)->items + (_offset) * (_arr)->itemsize)
#define VectorArrayGet(_arr, _offset) VECTOR_ARRAY_OFFSET(_arr, _offset)
#define VectorArraySet(_arr, _offset, _val) memcpy(VECTOR_ARRAY_OFFSET(_arr, _offset), _val, (_arr)->itemsize)
/* Methods */
VectorArray VectorArrayInit(int maxlen, int dimensions);
VectorArray VectorArrayInit(int maxlen, int dimensions, Size itemsize);
void VectorArrayFree(VectorArray arr);
void PrintVectorArray(char *msg, VectorArray arr);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatType type);
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
IvfflatType IvfflatGetType(Relation index);
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, IvfflatType type);
int IvfflatGetLists(Relation index);
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);

View File

@@ -85,7 +85,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL)
{
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, IvfflatGetType(index)))
return;
}

View File

@@ -3,12 +3,13 @@
#include <float.h>
#include <math.h>
#include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h"
#include "miscadmin.h"
#ifdef IVFFLAT_MEMORY
#include "utils/datum.h"
#include "utils/memutils.h"
#endif
#include "vector.h"
/*
* Initialize with kmeans++
@@ -46,12 +47,12 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
for (j = 0; j < numSamples; j++)
{
Vector *vec = VectorArrayGet(samples, j);
Datum vec = PointerGetDatum(VectorArrayGet(samples, j));
double distance;
/* Only need to compute distance for new center */
/* TODO Use triangle inequality to reduce distance calculations */
distance = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, i))));
distance = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, i))));
/* Set lower bound */
lowerBound[j * numCenters + i] = distance;
@@ -89,15 +90,29 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
* Apply norm to vector
*/
static inline void
ApplyNorm(FmgrInfo *normprocinfo, Oid collation, Vector * vec)
ApplyNorm(FmgrInfo *normprocinfo, Oid collation, Datum value, IvfflatType type)
{
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(vec)));
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, value));
/* TODO Handle zero norm */
if (norm > 0)
{
for (int i = 0; i < vec->dim; i++)
vec->x[i] /= norm;
if (type == IVFFLAT_TYPE_VECTOR)
{
Vector *vec = DatumGetVector(value);
for (int i = 0; i < vec->dim; i++)
vec->x[i] /= norm;
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
HalfVector *vec = DatumGetHalfVector(value);
for (int i = 0; i < vec->dim; i++)
vec->x[i] = Float4ToHalfUnchecked(HalfToFloat4(vec->x[i]) / norm);
}
else
elog(ERROR, "Unsupported type");
}
}
@@ -110,11 +125,20 @@ CompareVectors(const void *a, const void *b)
return vector_cmp_internal((Vector *) a, (Vector *) b);
}
/*
* Compare half vectors
*/
static int
CompareHalfVectors(const void *a, const void *b)
{
return halfvec_cmp_internal((HalfVector *) a, (HalfVector *) b);
}
/*
* Quick approach if we have little data
*/
static void
QuickCenters(Relation index, VectorArray samples, VectorArray centers)
QuickCenters(Relation index, VectorArray samples, VectorArray centers, IvfflatType type)
{
int dimensions = centers->dim;
Oid collation = index->rd_indcollation[0];
@@ -123,14 +147,20 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
/* Copy existing vectors while avoiding duplicates */
if (samples->length > 0)
{
qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
if (type == IVFFLAT_TYPE_VECTOR)
qsort(samples->items, samples->length, samples->itemsize, CompareVectors);
else if (type == IVFFLAT_TYPE_HALFVEC)
qsort(samples->items, samples->length, samples->itemsize, CompareHalfVectors);
else
elog(ERROR, "Unsupported type");
for (int i = 0; i < samples->length; i++)
{
Vector *vec = VectorArrayGet(samples, i);
Datum vec = PointerGetDatum(VectorArrayGet(samples, i));
if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
if (i == 0 || !datumIsEqual(vec, PointerGetDatum(VectorArrayGet(samples, i - 1)), false, -1))
{
VectorArraySet(centers, centers->length, vec);
VectorArraySet(centers, centers->length, DatumGetPointer(vec));
centers->length++;
}
}
@@ -139,17 +169,34 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
/* Fill remaining with random data */
while (centers->length < centers->maxlen)
{
Vector *vec = VectorArrayGet(centers, centers->length);
Datum center = PointerGetDatum(VectorArrayGet(centers, centers->length));
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
if (type == IVFFLAT_TYPE_VECTOR)
{
Vector *vec = DatumGetVector(center);
for (int j = 0; j < dimensions; j++)
vec->x[j] = RandomDouble();
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
for (int j = 0; j < dimensions; j++)
vec->x[j] = RandomDouble();
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
HalfVector *vec = DatumGetHalfVector(center);
SET_VARSIZE(vec, HALFVEC_SIZE(dimensions));
vec->dim = dimensions;
for (int j = 0; j < dimensions; j++)
vec->x[j] = Float4ToHalfUnchecked((float) RandomDouble());
}
else
elog(ERROR, "Unsupported type");
/* Normalize if needed (only needed for random centers) */
if (normprocinfo != NULL)
ApplyNorm(normprocinfo, collation, vec);
ApplyNorm(normprocinfo, collation, center, type);
centers->length++;
}
@@ -160,18 +207,120 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
* Show memory usage
*/
static void
ShowMemoryUsage(Size estimatedSize)
ShowMemoryUsage(MemoryContext context, Size estimatedSize)
{
#if PG_VERSION_NUM >= 130000
elog(INFO, "total memory: %zu MB",
MemoryContextMemAllocated(CurrentMemoryContext, true) / (1024 * 1024));
MemoryContextMemAllocated(context, true) / (1024 * 1024));
#else
MemoryContextStats(CurrentMemoryContext);
MemoryContextStats(context);
#endif
elog(INFO, "estimated memory: %zu MB", estimatedSize / (1024 * 1024));
}
#endif
/*
* Compute new centers
*/
static void
ComputeNewCenters(VectorArray samples, VectorArray aggCenters, VectorArray newCenters, int *centerCounts, int *closestCenters, FmgrInfo *normprocinfo, Oid collation, IvfflatType type)
{
int dimensions = aggCenters->dim;
int numCenters = aggCenters->maxlen;
int numSamples = samples->length;
/* Reset sum and count */
for (int j = 0; j < numCenters; j++)
{
Vector *vec = (Vector *) VectorArrayGet(aggCenters, j);
for (int k = 0; k < dimensions; k++)
vec->x[k] = 0.0;
centerCounts[j] = 0;
}
/* Increment sum of closest center */
if (type == IVFFLAT_TYPE_VECTOR)
{
for (int j = 0; j < numSamples; j++)
{
Vector *aggCenter = (Vector *) VectorArrayGet(aggCenters, closestCenters[j]);
Vector *vec = (Vector *) VectorArrayGet(samples, j);
for (int k = 0; k < dimensions; k++)
aggCenter->x[k] += vec->x[k];
}
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
for (int j = 0; j < numSamples; j++)
{
Vector *aggCenter = (Vector *) VectorArrayGet(aggCenters, closestCenters[j]);
HalfVector *vec = (HalfVector *) VectorArrayGet(samples, j);
for (int k = 0; k < dimensions; k++)
aggCenter->x[k] += HalfToFloat4(vec->x[k]);
}
}
else
elog(ERROR, "Unsupported type");
/* Increment count of closest center */
for (int j = 0; j < numSamples; j++)
centerCounts[closestCenters[j]] += 1;
/* Divide sum by count */
for (int j = 0; j < numCenters; j++)
{
Vector *vec = (Vector *) VectorArrayGet(aggCenters, j);
if (centerCounts[j] > 0)
{
/* Double avoids overflow, but requires more memory */
/* TODO Update bounds */
for (int k = 0; k < dimensions; k++)
{
if (isinf(vec->x[k]))
vec->x[k] = vec->x[k] > 0 ? FLT_MAX : -FLT_MAX;
}
for (int k = 0; k < dimensions; k++)
vec->x[k] /= centerCounts[j];
}
else
{
/* TODO Handle empty centers properly */
for (int k = 0; k < dimensions; k++)
vec->x[k] = RandomDouble();
}
}
/* Set new centers if different from agg centers */
if (type == IVFFLAT_TYPE_HALFVEC)
{
for (int j = 0; j < numCenters; j++)
{
Vector *aggCenter = (Vector *) VectorArrayGet(aggCenters, j);
HalfVector *newCenter = (HalfVector *) VectorArrayGet(newCenters, j);
for (int k = 0; k < dimensions; k++)
newCenter->x[k] = Float4ToHalfUnchecked(aggCenter->x[k]);
}
}
/* Normalize if needed */
if (normprocinfo != NULL)
{
for (int j = 0; j < numCenters; j++)
{
Datum newCenter = PointerGetDatum(VectorArrayGet(newCenters, j));
ApplyNorm(normprocinfo, collation, newCenter, type);
}
}
}
/*
* Use Elkan for performance. This requires distance function to satisfy triangle inequality.
*
@@ -181,19 +330,16 @@ ShowMemoryUsage(Size estimatedSize)
* https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
*/
static void
ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatType type)
{
FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
Oid collation;
Vector *vec;
Vector *newCenter;
int64 j;
int64 k;
int dimensions = centers->dim;
int numCenters = centers->maxlen;
int numSamples = samples->length;
VectorArray newCenters;
VectorArray aggCenters;
int *centerCounts;
int *closestCenters;
float *lowerBound;
@@ -201,11 +347,14 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
float *s;
float *halfcdist;
float *newcdist;
MemoryContext kmeansCtx;
MemoryContext oldCtx;
/* Calculate allocation sizes */
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->dim);
Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->dim);
Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, dimensions);
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->itemsize);
Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->itemsize);
Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, centers->itemsize);
Size aggCentersSize = type == IVFFLAT_TYPE_VECTOR ? 0 : VECTOR_ARRAY_SIZE(numCenters, VECTOR_SIZE(dimensions));
Size centerCountsSize = sizeof(int) * numCenters;
Size closestCentersSize = sizeof(int) * numSamples;
Size lowerBoundSize = sizeof(float) * numSamples * numCenters;
@@ -215,7 +364,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
Size newcdistSize = sizeof(float) * numCenters;
/* Calculate total size */
Size totalSize = samplesSize + centersSize + newCentersSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
Size totalSize = samplesSize + centersSize + newCentersSize + aggCentersSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
/* Check memory requirements */
/* Add one to error message to ceil */
@@ -234,6 +383,12 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
collation = index->rd_indcollation[0];
/* Use memory context */
kmeansCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat kmeans temporary context",
ALLOCSET_DEFAULT_SIZES);
oldCtx = MemoryContextSwitchTo(kmeansCtx);
/* Allocate space */
/* Use float instead of double to save memory */
centerCounts = palloc(centerCountsSize);
@@ -244,29 +399,50 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
halfcdist = palloc_extended(halfcdistSize, MCXT_ALLOC_HUGE);
newcdist = palloc(newcdistSize);
newCenters = VectorArrayInit(numCenters, dimensions);
for (j = 0; j < numCenters; j++)
aggCenters = VectorArrayInit(numCenters, dimensions, VECTOR_SIZE(dimensions));
for (int j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(newCenters, j);
Vector *vec = (Vector *) VectorArrayGet(aggCenters, j);
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
}
if (type == IVFFLAT_TYPE_VECTOR)
{
/* Use same centers to save memory */
newCenters = aggCenters;
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
newCenters = VectorArrayInit(numCenters, dimensions, centers->itemsize);
for (int j = 0; j < numCenters; j++)
{
HalfVector *vec = (HalfVector *) VectorArrayGet(newCenters, j);
SET_VARSIZE(vec, HALFVEC_SIZE(dimensions));
vec->dim = dimensions;
}
}
else
elog(ERROR, "Unsupported type");
#ifdef IVFFLAT_MEMORY
ShowMemoryUsage(totalSize);
ShowMemoryUsage(oldCtx, totalSize);
#endif
/* Pick initial centers */
InitCenters(index, samples, centers, lowerBound);
/* Assign each x to its closest initial center c(x) = argmin d(x,c) */
for (j = 0; j < numSamples; j++)
for (int64 j = 0; j < numSamples; j++)
{
float minDistance = FLT_MAX;
int closestCenter = 0;
/* Find closest center */
for (k = 0; k < numCenters; k++)
for (int64 k = 0; k < numCenters; k++)
{
/* TODO Use Lemma 1 in k-means++ initialization */
float distance = lowerBound[j * numCenters + k];
@@ -292,13 +468,13 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
CHECK_FOR_INTERRUPTS();
/* Step 1: For all centers, compute distance */
for (j = 0; j < numCenters; j++)
for (int64 j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(centers, j);
Datum vec = PointerGetDatum(VectorArrayGet(centers, j));
for (k = j + 1; k < numCenters; k++)
for (int64 k = j + 1; k < numCenters; k++)
{
float distance = 0.5 * DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
float distance = 0.5 * DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, k))));
halfcdist[j * numCenters + k] = distance;
halfcdist[k * numCenters + j] = distance;
@@ -306,11 +482,11 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
}
/* For all centers c, compute s(c) */
for (j = 0; j < numCenters; j++)
for (int64 j = 0; j < numCenters; j++)
{
float minDistance = FLT_MAX;
for (k = 0; k < numCenters; k++)
for (int64 k = 0; k < numCenters; k++)
{
float distance;
@@ -327,7 +503,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
rjreset = iteration != 0;
for (j = 0; j < numSamples; j++)
for (int64 j = 0; j < numSamples; j++)
{
bool rj;
@@ -337,8 +513,9 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
rj = rjreset;
for (k = 0; k < numCenters; k++)
for (int64 k = 0; k < numCenters; k++)
{
Datum vec;
float dxcx;
/* Step 3: For all remaining points x and centers c */
@@ -351,12 +528,12 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
if (upperBound[j] <= halfcdist[closestCenters[j] * numCenters + k])
continue;
vec = VectorArrayGet(samples, j);
vec = PointerGetDatum(VectorArrayGet(samples, j));
/* Step 3a */
if (rj)
{
dxcx = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, closestCenters[j]))));
dxcx = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, closestCenters[j]))));
/* d(x,c(x)) computed, which is a form of d(x,c) */
lowerBound[j * numCenters + closestCenters[j]] = dxcx;
@@ -370,7 +547,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Step 3b */
if (dxcx > lowerBound[j * numCenters + k] || dxcx > halfcdist[closestCenters[j] * numCenters + k])
{
float dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
float dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, k))));
/* d(x,c) calculated */
lowerBound[j * numCenters + k] = dxc;
@@ -389,66 +566,15 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
}
/* Step 4: For each center c, let m(c) be mean of all points assigned */
for (j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(newCenters, j);
for (k = 0; k < dimensions; k++)
vec->x[k] = 0.0;
centerCounts[j] = 0;
}
for (j = 0; j < numSamples; j++)
{
int closestCenter;
vec = VectorArrayGet(samples, j);
closestCenter = closestCenters[j];
/* Increment sum and count of closest center */
newCenter = VectorArrayGet(newCenters, closestCenter);
for (k = 0; k < dimensions; k++)
newCenter->x[k] += vec->x[k];
centerCounts[closestCenter] += 1;
}
for (j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(newCenters, j);
if (centerCounts[j] > 0)
{
/* Double avoids overflow, but requires more memory */
/* TODO Update bounds */
for (k = 0; k < dimensions; k++)
{
if (isinf(vec->x[k]))
vec->x[k] = vec->x[k] > 0 ? FLT_MAX : -FLT_MAX;
}
for (k = 0; k < dimensions; k++)
vec->x[k] /= centerCounts[j];
}
else
{
/* TODO Handle empty centers properly */
for (k = 0; k < dimensions; k++)
vec->x[k] = RandomDouble();
}
/* Normalize if needed */
if (normprocinfo != NULL)
ApplyNorm(normprocinfo, collation, vec);
}
ComputeNewCenters(samples, aggCenters, newCenters, centerCounts, closestCenters, normprocinfo, collation, type);
/* Step 5 */
for (j = 0; j < numCenters; j++)
for (int j = 0; j < numCenters; j++)
newcdist[j] = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(VectorArrayGet(centers, j)), PointerGetDatum(VectorArrayGet(newCenters, j))));
for (j = 0; j < numSamples; j++)
for (int64 j = 0; j < numSamples; j++)
{
for (k = 0; k < numCenters; k++)
for (int64 k = 0; k < numCenters; k++)
{
float distance = lowerBound[j * numCenters + k] - newcdist[k];
@@ -461,32 +587,26 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Step 6 */
/* We reset r(x) before Step 3 in the next iteration */
for (j = 0; j < numSamples; j++)
for (int j = 0; j < numSamples; j++)
upperBound[j] += newcdist[closestCenters[j]];
/* Step 7 */
for (j = 0; j < numCenters; j++)
for (int j = 0; j < numCenters; j++)
VectorArraySet(centers, j, VectorArrayGet(newCenters, j));
if (changes == 0 && iteration != 0)
break;
}
VectorArrayFree(newCenters);
pfree(centerCounts);
pfree(closestCenters);
pfree(lowerBound);
pfree(upperBound);
pfree(s);
pfree(halfcdist);
pfree(newcdist);
MemoryContextSwitchTo(oldCtx);
MemoryContextDelete(kmeansCtx);
}
/*
* Detect issues with centers
*/
static void
CheckCenters(Relation index, VectorArray centers)
CheckCenters(Relation index, VectorArray centers, IvfflatType type)
{
FmgrInfo *normprocinfo;
@@ -496,24 +616,48 @@ CheckCenters(Relation index, VectorArray centers)
/* 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 (type == IVFFLAT_TYPE_VECTOR)
{
if (isnan(vec->x[j]))
elog(ERROR, "NaN detected. Please report a bug.");
Vector *vec = (Vector *) VectorArrayGet(centers, i);
if (isinf(vec->x[j]))
elog(ERROR, "Infinite value detected. Please report a bug.");
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.");
}
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
HalfVector *vec = (HalfVector *) VectorArrayGet(centers, i);
for (int j = 0; j < vec->dim; j++)
{
if (HalfIsNan(vec->x[j]))
elog(ERROR, "NaN detected. Please report a bug.");
if (HalfIsInf(vec->x[j]))
elog(ERROR, "Infinite value detected. Please report a bug.");
}
}
else
elog(ERROR, "Unsupported type");
}
/* Ensure no duplicate centers */
/* Fine to sort in-place */
qsort(centers->items, centers->length, VECTOR_SIZE(centers->dim), CompareVectors);
if (type == IVFFLAT_TYPE_VECTOR)
qsort(centers->items, centers->length, centers->itemsize, CompareVectors);
else if (type == IVFFLAT_TYPE_HALFVEC)
qsort(centers->items, centers->length, centers->itemsize, CompareHalfVectors);
else
elog(ERROR, "Unsupported type");
for (int i = 1; i < centers->length; i++)
{
if (CompareVectors(VectorArrayGet(centers, i), VectorArrayGet(centers, i - 1)) == 0)
if (datumIsEqual(PointerGetDatum(VectorArrayGet(centers, i)), PointerGetDatum(VectorArrayGet(centers, i - 1)), false, -1))
elog(ERROR, "Duplicate centers detected. Please report a bug.");
}
@@ -539,12 +683,12 @@ CheckCenters(Relation index, VectorArray centers)
* We use spherical k-means for inner product and cosine
*/
void
IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers)
IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatType type)
{
if (samples->length <= centers->maxlen)
QuickCenters(index, samples, centers);
QuickCenters(index, samples, centers, type);
else
ElkanKmeans(index, samples, centers);
ElkanKmeans(index, samples, centers, type);
CheckCenters(index, centers);
CheckCenters(index, centers, type);
}

View File

@@ -5,6 +5,7 @@
#include "access/relscan.h"
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
#include "halfvec.h"
#include "lib/pairingheap.h"
#include "ivfflat.h"
#include "miscadmin.h"
@@ -177,6 +178,42 @@ GetScanItems(IndexScanDesc scan, Datum value)
tuplesort_performsort(so->sortstate);
}
/*
* Get scan value
*/
static Datum
GetScanValue(IndexScanDesc scan)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL)
{
IvfflatType type = IvfflatGetType(scan->indexRelation);
if (type == IVFFLAT_TYPE_VECTOR)
value = PointerGetDatum(InitVector(so->dimensions));
else if (type == IVFFLAT_TYPE_HALFVEC)
value = PointerGetDatum(InitHalfVector(so->dimensions));
else
elog(ERROR, "Unsupported type");
}
else
{
value = scan->orderByData->sk_argument;
/* Value should not be compressed or toasted */
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Fine if normalization fails */
if (so->normprocinfo != NULL)
IvfflatNormValue(so->normprocinfo, so->collation, &value, IvfflatGetType(scan->indexRelation));
}
return value;
}
/*
* Prepare for an index scan
*/
@@ -281,21 +318,7 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
if (!IsMVCCSnapshot(scan->xs_snapshot))
elog(ERROR, "non-MVCC snapshots are not supported with ivfflat");
if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(so->dimensions));
else
{
value = scan->orderByData->sk_argument;
/* Value should not be compressed or toasted */
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Fine if normalization fails */
if (so->normprocinfo != NULL)
IvfflatNormValue(so->normprocinfo, so->collation, &value, NULL);
}
value = GetScanValue(scan);
IvfflatBench("GetScanLists", GetScanLists(scan, value));
IvfflatBench("GetScanItems", GetScanItems(scan, value));
so->first = false;

View File

@@ -1,22 +1,27 @@
#include "postgres.h"
#include "access/generic_xlog.h"
#include "catalog/pg_type.h"
#include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h"
#include "storage/bufmgr.h"
#include "vector.h"
#include "utils/syscache.h"
/*
* Allocate a vector array
*/
VectorArray
VectorArrayInit(int maxlen, int dimensions)
VectorArrayInit(int maxlen, int dimensions, Size itemsize)
{
VectorArray res = palloc(sizeof(VectorArrayData));
res->length = 0;
res->maxlen = maxlen;
res->dim = dimensions;
res->items = palloc_extended(maxlen * VECTOR_SIZE(dimensions), MCXT_ALLOC_ZERO | MCXT_ALLOC_HUGE);
res->itemsize = itemsize;
res->items = palloc_extended(maxlen * itemsize, MCXT_ALLOC_ZERO | MCXT_ALLOC_HUGE);
return res;
}
@@ -30,16 +35,6 @@ VectorArrayFree(VectorArray arr)
pfree(arr);
}
/*
* Print vector array - useful for debugging
*/
void
PrintVectorArray(char *msg, VectorArray arr)
{
for (int i = 0; i < arr->length; i++)
PrintVector(msg, VectorArrayGet(arr, i));
}
/*
* Get the number of lists in the index
*/
@@ -66,6 +61,37 @@ IvfflatOptionalProcInfo(Relation index, uint16 procnum)
return index_getprocinfo(index, 1, procnum);
}
/*
* Get type
*/
IvfflatType
IvfflatGetType(Relation index)
{
Oid typid = TupleDescAttr(index->rd_att, 0)->atttypid;
HeapTuple tuple;
Form_pg_type type;
IvfflatType result;
tuple = SearchSysCache1(TYPEOID, ObjectIdGetDatum(typid));
if (!HeapTupleIsValid(tuple))
elog(ERROR, "cache lookup failed for type %u", typid);
type = (Form_pg_type) GETSTRUCT(tuple);
if (strcmp(NameStr(type->typname), "vector") == 0)
result = IVFFLAT_TYPE_VECTOR;
else if (strcmp(NameStr(type->typname), "halfvec") == 0)
result = IVFFLAT_TYPE_HALFVEC;
else
{
ReleaseSysCache(tuple);
elog(ERROR, "type not supported for ivfflat index");
}
ReleaseSysCache(tuple);
return result;
}
/*
* Divide by the norm
*
@@ -75,21 +101,34 @@ IvfflatOptionalProcInfo(Relation index, uint16 procnum)
* if it's different than the original value
*/
bool
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, IvfflatType type)
{
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0)
{
Vector *v = DatumGetVector(*value);
if (type == IVFFLAT_TYPE_VECTOR)
{
Vector *v = DatumGetVector(*value);
Vector *result = InitVector(v->dim);
if (result == NULL)
result = InitVector(v->dim);
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
*value = PointerGetDatum(result);
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
HalfVector *v = DatumGetHalfVector(*value);
HalfVector *result = InitHalfVector(v->dim);
*value = PointerGetDatum(result);
for (int i = 0; i < v->dim; i++)
result->x[i] = Float4ToHalfUnchecked(HalfToFloat4(v->x[i]) / norm);
*value = PointerGetDatum(result);
}
else
elog(ERROR, "Unsupported type");
return true;
}

800
src/sparsevec.c Normal file
View File

@@ -0,0 +1,800 @@
#include "postgres.h"
#include <limits.h>
#include <math.h>
#include "fmgr.h"
#include "libpq/pqformat.h"
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "vector.h"
#if PG_VERSION_NUM >= 120000
#include "common/shortest_dec.h"
#include "utils/float.h"
#else
#include <float.h>
#include "utils/builtins.h"
#endif
/*
* Ensure same dimensions
*/
static inline void
CheckDims(SparseVector * a, SparseVector * b)
{
if (a->dim != b->dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different sparsevec dimensions %d and %d", a->dim, b->dim)));
}
/*
* Ensure expected dimensions
*/
static inline void
CheckExpectedDim(int32 typmod, int dim)
{
if (typmod != -1 && typmod != dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected %d dimensions, not %d", typmod, dim)));
}
/*
* Ensure valid dimensions
*/
static inline void
CheckDim(int dim)
{
if (dim < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("sparsevec must have at least 1 dimension")));
if (dim > SPARSEVEC_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d dimensions", SPARSEVEC_MAX_DIM)));
}
/*
* Ensure valid nnz
*/
static inline void
CheckNnz(int nnz, int dim)
{
if (nnz < 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("sparsevec cannot have negative number of elements")));
if (nnz > SPARSEVEC_MAX_NNZ)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d non-zero elements", SPARSEVEC_MAX_NNZ)));
if (nnz > dim)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more elements than dimensions")));
}
/*
* Ensure valid index
*/
static inline void
CheckIndex(int32 *indices, int i, int dim)
{
int32 index = indices[i];
if (index < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("index must be greater than zero")));
if (index > dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("index must be less than or equal to dimensions")));
if (i > 0)
{
if (index < indices[i - 1])
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("indexes must be in ascending order")));
if (index == indices[i - 1])
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("indexes must not contain duplicates")));
}
}
/*
* Ensure finite element
*/
static inline void
CheckElement(float value)
{
if (isnan(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("NaN not allowed in sparsevec")));
if (isinf(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("infinite value not allowed in sparsevec")));
}
/*
* Allocate and initialize a new sparse vector
*/
SparseVector *
InitSparseVector(int dim, int nnz)
{
SparseVector *result;
int size;
size = SPARSEVEC_SIZE(nnz);
result = (SparseVector *) palloc0(size);
SET_VARSIZE(result, size);
result->dim = dim;
result->nnz = nnz;
return result;
}
/*
* Check for whitespace, since array_isspace() is static
*/
static inline bool
sparsevec_isspace(char ch)
{
if (ch == ' ' ||
ch == '\t' ||
ch == '\n' ||
ch == '\r' ||
ch == '\v' ||
ch == '\f')
return true;
return false;
}
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_in);
Datum
sparsevec_in(PG_FUNCTION_ARGS)
{
char *lit = PG_GETARG_CSTRING(0);
int32 typmod = PG_GETARG_INT32(2);
int dim;
char *pt = lit;
char *stringEnd;
SparseVector *result;
float *rvalues;
int32 *indices;
float *values;
int maxNnz;
int nnz = 0;
maxNnz = 1;
while (*pt != '\0')
{
if (*pt == ',')
maxNnz++;
pt++;
}
if (maxNnz > SPARSEVEC_MAX_NNZ)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d non-zero elements", SPARSEVEC_MAX_NNZ)));
indices = palloc(maxNnz * sizeof(int32));
values = palloc(maxNnz * sizeof(float));
pt = lit;
while (sparsevec_isspace(*pt))
pt++;
if (*pt != '{')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit),
errdetail("Vector contents must start with \"{\".")));
pt++;
while (sparsevec_isspace(*pt))
pt++;
if (*pt == '}')
pt++;
else
{
for (;;)
{
long index;
float value;
/* TODO Better error */
if (nnz == maxNnz)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("ran out of buffer: \"%s\"", lit)));
while (sparsevec_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 sparsevec: \"%s\"", lit)));
/* Use similar logic as int2vectorin */
errno = 0;
index = strtol(pt, &stringEnd, 10);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
if (errno == ERANGE || index < 1 || index > INT_MAX)
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("index \"%ld\" is out of range for type sparsevec", index)));
pt = stringEnd;
while (sparsevec_isspace(*pt))
pt++;
if (*pt != ':')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
pt++;
while (sparsevec_isspace(*pt))
pt++;
errno = 0;
/* Use strtof like float4in to avoid a double-rounding problem */
/* Postgres sets LC_NUMERIC to C on startup */
value = strtof(pt, &stringEnd);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
/* Check for range error like float4in */
if (errno == ERANGE && (value == 0 || isinf(value)))
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type sparsevec", pnstrdup(pt, stringEnd - pt))));
CheckElement(value);
/* Do not store zero values */
if (value != 0)
{
indices[nnz] = index;
values[nnz] = value;
nnz++;
}
pt = stringEnd;
while (sparsevec_isspace(*pt))
pt++;
if (*pt == ',')
pt++;
else if (*pt == '}')
{
pt++;
break;
}
else
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
}
}
while (sparsevec_isspace(*pt))
pt++;
if (*pt != '/')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit),
errdetail("Unexpected end of input.")));
pt++;
while (sparsevec_isspace(*pt))
pt++;
/* Use similar logic as int2vectorin */
errno = 0;
dim = strtol(pt, &stringEnd, 10);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
pt = stringEnd;
/* Only whitespace is allowed after the closing brace */
while (sparsevec_isspace(*pt))
pt++;
if (*pt != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit),
errdetail("Junk after closing.")));
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitSparseVector(dim, nnz);
rvalues = SPARSEVEC_VALUES(result);
for (int i = 0; i < nnz; i++)
{
result->indices[i] = indices[i];
rvalues[i] = values[i];
CheckIndex(result->indices, i, dim);
}
PG_RETURN_POINTER(result);
}
#define AppendChar(ptr, c) (*(ptr)++ = (c))
#define AppendFloat(ptr, f) ((ptr) += float_to_shortest_decimal_bufn((f), (ptr)))
#if PG_VERSION_NUM >= 140000
#define AppendInt(ptr, i) ((ptr) += pg_ltoa((i), (ptr)))
#else
#define AppendInt(ptr, i) \
do { \
pg_ltoa(i, ptr); \
while (*ptr != '\0') \
ptr++; \
} while (0)
#endif
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_out);
Datum
sparsevec_out(PG_FUNCTION_ARGS)
{
SparseVector *sparsevec = PG_GETARG_SPARSEVEC_P(0);
float *values = SPARSEVEC_VALUES(sparsevec);
char *buf;
char *ptr;
/*
* Need:
*
* nnz * 10 bytes for index (positive integer)
*
* nnz bytes for :
*
* nnz * (FLOAT_SHORTEST_DECIMAL_LEN - 1) bytes for
* float_to_shortest_decimal_bufn
*
* nnz - 1 bytes for ,
*
* 10 bytes for dimensions
*
* 4 bytes for {, }, /, and \0
*/
buf = (char *) palloc((11 + FLOAT_SHORTEST_DECIMAL_LEN) * sparsevec->nnz + 13);
ptr = buf;
AppendChar(ptr, '{');
for (int i = 0; i < sparsevec->nnz; i++)
{
if (i > 0)
AppendChar(ptr, ',');
AppendInt(ptr, sparsevec->indices[i]);
AppendChar(ptr, ':');
AppendFloat(ptr, values[i]);
}
AppendChar(ptr, '}');
AppendChar(ptr, '/');
AppendInt(ptr, sparsevec->dim);
*ptr = '\0';
PG_FREE_IF_COPY(sparsevec, 0);
PG_RETURN_CSTRING(buf);
}
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_typmod_in);
Datum
sparsevec_typmod_in(PG_FUNCTION_ARGS)
{
ArrayType *ta = PG_GETARG_ARRAYTYPE_P(0);
int32 *tl;
int n;
tl = ArrayGetIntegerTypmods(ta, &n);
if (n != 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("invalid type modifier")));
if (*tl < 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type sparsevec must be at least 1")));
if (*tl > SPARSEVEC_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type sparsevec cannot exceed %d", SPARSEVEC_MAX_DIM)));
PG_RETURN_INT32(*tl);
}
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_recv);
Datum
sparsevec_recv(PG_FUNCTION_ARGS)
{
StringInfo buf = (StringInfo) PG_GETARG_POINTER(0);
int32 typmod = PG_GETARG_INT32(2);
SparseVector *result;
int32 dim;
int32 nnz;
int32 unused;
float *values;
dim = pq_getmsgint(buf, sizeof(int32));
nnz = pq_getmsgint(buf, sizeof(int32));
unused = pq_getmsgint(buf, sizeof(int32));
CheckDim(dim);
CheckNnz(nnz, dim);
CheckExpectedDim(typmod, dim);
if (unused != 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected unused to be 0, not %d", unused)));
result = InitSparseVector(dim, nnz);
values = SPARSEVEC_VALUES(result);
for (int i = 0; i < nnz; i++)
{
result->indices[i] = pq_getmsgint(buf, sizeof(int32));
CheckIndex(result->indices, i, dim);
}
for (int i = 0; i < nnz; i++)
{
values[i] = pq_getmsgfloat4(buf);
CheckElement(values[i]);
}
PG_RETURN_POINTER(result);
}
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_send);
Datum
sparsevec_send(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
float *values = SPARSEVEC_VALUES(svec);
StringInfoData buf;
pq_begintypsend(&buf);
pq_sendint(&buf, svec->dim, sizeof(int32));
pq_sendint(&buf, svec->nnz, sizeof(int32));
pq_sendint(&buf, svec->unused, sizeof(int32));
for (int i = 0; i < svec->nnz; i++)
pq_sendint(&buf, svec->indices[i], sizeof(int32));
for (int i = 0; i < svec->nnz; i++)
pq_sendfloat4(&buf, values[i]);
PG_RETURN_BYTEA_P(pq_endtypsend(&buf));
}
/*
* Convert sparse vector to sparse vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec);
Datum
sparsevec(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
CheckExpectedDim(typmod, svec->dim);
PG_RETURN_POINTER(svec);
}
/*
* Convert dense vector to sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_sparsevec);
Datum
vector_to_sparsevec(PG_FUNCTION_ARGS)
{
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
SparseVector *result;
int dim = vec->dim;
int nnz = 0;
float *values;
int j = 0;
CheckDim(dim);
CheckExpectedDim(typmod, dim);
for (int i = 0; i < dim; i++)
{
if (vec->x[i] != 0)
nnz++;
}
result = InitSparseVector(dim, nnz);
values = SPARSEVEC_VALUES(result);
for (int i = 0; i < dim; i++)
{
if (vec->x[i] != 0)
{
/* Safety check */
if (j == nnz)
elog(ERROR, "safety check failed");
result->indices[j] = i + 1;
values[j] = vec->x[i];
j++;
}
}
PG_RETURN_POINTER(result);
}
/*
* Get the L2 squared distance between sparse vectors
*/
static double
SparsevecL2SquaredDistance(SparseVector * a, SparseVector * b)
{
float *ax = SPARSEVEC_VALUES(a);
float *bx = SPARSEVEC_VALUES(b);
double distance = 0.0;
int bpos = 0;
for (int i = 0; i < a->nnz; i++)
{
int ai = a->indices[i];
int bi = -1;
for (int j = bpos; j < b->nnz; j++)
{
bi = b->indices[j];
if (ai == bi)
{
double diff = ax[i] - bx[j];
distance += diff * diff;
}
else if (ai > bi)
distance += bx[j] * bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
if (ai != bi)
distance += ax[i] * ax[i];
}
for (int j = bpos; j < b->nnz; j++)
distance += bx[j] * bx[j];
return distance;
}
/*
* Get the L2 distance between sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_distance);
Datum
sparsevec_l2_distance(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(sqrt(SparsevecL2SquaredDistance(a, b)));
}
/*
* Get the L2 squared distance between sparse vectors
* This saves a sqrt calculation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_squared_distance);
Datum
sparsevec_l2_squared_distance(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(SparsevecL2SquaredDistance(a, b));
}
/*
* Get the inner product of two sparse vectors
*/
static double
SparsevecInnerProduct(SparseVector * a, SparseVector * b)
{
float *ax = SPARSEVEC_VALUES(a);
float *bx = SPARSEVEC_VALUES(b);
double distance = 0.0;
int bpos = 0;
for (int i = 0; i < a->nnz; i++)
{
int ai = a->indices[i];
for (int j = bpos; j < b->nnz; j++)
{
int bi = b->indices[j];
/* Only update when the same index */
if (ai == bi)
distance += ax[i] * bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
}
return distance;
}
/*
* Get the inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_inner_product);
Datum
sparsevec_inner_product(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(SparsevecInnerProduct(a, b));
}
/*
* Get the negative inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_negative_inner_product);
Datum
sparsevec_negative_inner_product(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(-SparsevecInnerProduct(a, b));
}
/*
* Get the cosine distance between two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_cosine_distance);
Datum
sparsevec_cosine_distance(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
float *ax = SPARSEVEC_VALUES(a);
float *bx = SPARSEVEC_VALUES(b);
float norma = 0.0;
float normb = 0.0;
double similarity;
CheckDims(a, b);
similarity = SparsevecInnerProduct(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->nnz; i++)
norma += ax[i] * ax[i];
/* Auto-vectorized */
for (int i = 0; i < b->nnz; i++)
normb += bx[i] * bx[i];
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
similarity /= 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);
}
/*
* Get the L2 norm of a sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_norm);
Datum
sparsevec_norm(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
float *ax = SPARSEVEC_VALUES(a);
double norm = 0.0;
/* Auto-vectorized */
for (int i = 0; i < a->nnz; i++)
norm += (double) ax[i] * (double) ax[i];
PG_RETURN_FLOAT8(sqrt(norm));
}

25
src/sparsevec.h Normal file
View File

@@ -0,0 +1,25 @@
#ifndef SPARSEVEC_H
#define SPARSEVEC_H
#define SPARSEVEC_MAX_DIM 100000
#define SPARSEVEC_MAX_NNZ 16000
/* Ensure values are aligned */
#define SPARSEVEC_SIZE(_nnz) (offsetof(SparseVector, indices) + MAXALIGN((_nnz) * sizeof(int32)) + (_nnz * sizeof(float)))
#define SPARSEVEC_VALUES(x) ((float *) (((char *) (x)) + offsetof(SparseVector, indices) + MAXALIGN((x)->nnz * sizeof(int32))))
#define DatumGetSparseVector(x) ((SparseVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_SPARSEVEC_P(x) DatumGetSparseVector(PG_GETARG_DATUM(x))
#define PG_RETURN_SPARSEVEC_P(x) PG_RETURN_POINTER(x)
typedef struct SparseVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int32 dim; /* number of dimensions */
int32 nnz;
int32 unused;
int32 indices[FLEXIBLE_ARRAY_MEMBER];
} SparseVector;
SparseVector *InitSparseVector(int dim, int nnz);
#endif

View File

@@ -2,14 +2,18 @@
#include <math.h>
#include "bitvector.h"
#include "catalog/pg_type.h"
#include "common/shortest_dec.h"
#include "fmgr.h"
#include "halfutils.h"
#include "halfvec.h"
#include "hnsw.h"
#include "ivfflat.h"
#include "lib/stringinfo.h"
#include "libpq/pqformat.h"
#include "port.h" /* for strtof() */
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
@@ -29,6 +33,13 @@
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
/* target_clones requires glibc */
#if defined(__x86_64__) && defined(__gnu_linux__) && defined(__has_attribute) && __has_attribute(target_clones) && !defined(__FMA__)
#define VECTOR_DISPATCH __attribute__((target_clones("default", "fma")))
#else
#define VECTOR_DISPATCH
#endif
PG_MODULE_MAGIC;
/*
@@ -38,6 +49,7 @@ PGDLLEXPORT void _PG_init(void);
void
_PG_init(void)
{
HalfvecInit();
HnswInit();
IvfflatInit();
}
@@ -176,27 +188,33 @@ vector_in(PG_FUNCTION_ARGS)
int32 typmod = PG_GETARG_INT32(2);
float x[VECTOR_MAX_DIM];
int dim = 0;
char *pt;
char *stringEnd;
char *pt = lit;
Vector *result;
char *litcopy = pstrdup(lit);
char *str = litcopy;
while (vector_isspace(*str))
str++;
while (vector_isspace(*pt))
pt++;
if (*str != '[')
if (*pt != '[')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit),
errmsg("invalid input syntax for type vector: \"%s\"", lit),
errdetail("Vector contents must start with \"[\".")));
str++;
pt = strtok(str, ",");
stringEnd = pt;
pt++;
while (pt != NULL && *stringEnd != ']')
while (vector_isspace(*pt))
pt++;
if (*pt == ']')
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
for (;;)
{
float val;
char *stringEnd;
if (dim == VECTOR_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
@@ -211,61 +229,55 @@ vector_in(PG_FUNCTION_ARGS)
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
errno = 0;
/* Use strtof like float4in to avoid a double-rounding problem */
x[dim] = strtof(pt, &stringEnd);
CheckElement(x[dim]);
dim++;
/* Postgres sets LC_NUMERIC to C on startup */
val = strtof(pt, &stringEnd);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
while (vector_isspace(*stringEnd))
stringEnd++;
/* Check for range error like float4in */
if (errno == ERANGE && isinf(val))
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type vector", pnstrdup(pt, stringEnd - pt))));
if (*stringEnd != '\0' && *stringEnd != ']')
CheckElement(val);
x[dim++] = val;
pt = stringEnd;
while (vector_isspace(*pt))
pt++;
if (*pt == ',')
pt++;
else if (*pt == ']')
{
pt++;
break;
}
else
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
pt = strtok(NULL, ",");
}
if (stringEnd == NULL || *stringEnd != ']')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit),
errdetail("Unexpected end of input.")));
stringEnd++;
/* Only whitespace is allowed after the closing brace */
while (vector_isspace(*stringEnd))
stringEnd++;
while (vector_isspace(*pt))
pt++;
if (*stringEnd != '\0')
if (*pt != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit),
errmsg("invalid input syntax for type vector: \"%s\"", lit),
errdetail("Junk after closing right brace.")));
/* Ensure no consecutive delimiters since strtok skips */
for (pt = lit + 1; *pt != '\0'; pt++)
{
if (pt[-1] == ',' && *pt == ',')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit)));
}
if (dim < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
pfree(litcopy);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitVector(dim);
@@ -275,6 +287,9 @@ vector_in(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
#define AppendChar(ptr, c) (*(ptr)++ = (c))
#define AppendFloat(ptr, f) ((ptr) += float_to_shortest_decimal_bufn((f), (ptr)))
/*
* Convert internal representation to textual representation
*/
@@ -286,7 +301,6 @@ vector_out(PG_FUNCTION_ARGS)
int dim = vector->dim;
char *buf;
char *ptr;
int n;
/*
* Need:
@@ -301,21 +315,17 @@ vector_out(PG_FUNCTION_ARGS)
buf = (char *) palloc(FLOAT_SHORTEST_DECIMAL_LEN * dim + 2);
ptr = buf;
*ptr = '[';
ptr++;
AppendChar(ptr, '[');
for (int i = 0; i < dim; i++)
{
if (i > 0)
{
*ptr = ',';
ptr++;
}
AppendChar(ptr, ',');
n = float_to_shortest_decimal_bufn(vector->x[i], ptr);
ptr += n;
AppendFloat(ptr, vector->x[i]);
}
*ptr = ']';
ptr++;
AppendChar(ptr, ']');
*ptr = '\0';
PG_FREE_IF_COPY(vector, 0);
@@ -532,6 +542,44 @@ vector_to_float4(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Convert half vector to vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_to_vector);
Datum
halfvec_to_vector(PG_FUNCTION_ARGS)
{
HalfVector *vec = PG_GETARG_HALFVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
CheckDim(vec->dim);
CheckExpectedDim(typmod, vec->dim);
result = InitVector(vec->dim);
for (int i = 0; i < vec->dim; i++)
result->x[i] = HalfToFloat4(vec->x[i]);
PG_RETURN_POINTER(result);
}
VECTOR_DISPATCH static float
VectorL2SquaredDistance(int dim, float *ax, float *bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float diff = ax[i] - bx[i];
distance += diff * diff;
}
return distance;
}
/*
* Get the L2 distance between vectors
*/
@@ -541,21 +589,10 @@ l2_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
float diff;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
diff = ax[i] - bx[i];
distance += diff * diff;
}
PG_RETURN_FLOAT8(sqrt((double) distance));
PG_RETURN_FLOAT8(sqrt((double) VectorL2SquaredDistance(a->dim, a->x, b->x)));
}
/*
@@ -568,21 +605,22 @@ vector_l2_squared_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
float diff;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
diff = ax[i] - bx[i];
distance += diff * diff;
}
PG_RETURN_FLOAT8((double) VectorL2SquaredDistance(a->dim, a->x, b->x));
}
PG_RETURN_FLOAT8((double) distance);
VECTOR_DISPATCH static float
VectorInnerProduct(int dim, float *ax, float *bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += ax[i] * bx[i];
return distance;
}
/*
@@ -594,17 +632,10 @@ inner_product(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += ax[i] * bx[i];
PG_RETURN_FLOAT8((double) distance);
PG_RETURN_FLOAT8((double) VectorInnerProduct(a->dim, a->x, b->x));
}
/*
@@ -616,17 +647,10 @@ vector_negative_inner_product(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += ax[i] * bx[i];
PG_RETURN_FLOAT8((double) distance * -1);
PG_RETURN_FLOAT8((double) -VectorInnerProduct(a->dim, a->x, b->x));
}
/*
@@ -684,18 +708,11 @@ vector_spherical_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float dp = 0.0;
double distance;
CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
dp += ax[i] * bx[i];
distance = (double) dp;
distance = (double) VectorInnerProduct(a->dim, a->x, b->x);
/* Prevent NaN with acos with loss of precision */
if (distance > 1)
@@ -860,6 +877,56 @@ vector_mul(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Quantize a vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(quantize_binary);
Datum
quantize_binary(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
float *ax = a->x;
VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result);
for (int i = 0; i < a->dim; i++)
rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result);
}
/*
* Get a subvector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(subvector);
Datum
subvector(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
int32 start = PG_GETARG_INT32(1);
int32 count = PG_GETARG_INT32(2);
int32 end = start + count;
float *ax = a->x;
Vector *result;
int dim;
/* Indexing starts at 1, like substring */
if (start < 1)
start = 1;
if (end > a->dim)
end = a->dim + 1;
dim = end - start;
CheckDim(dim);
result = InitVector(dim);
for (int i = 0; i < dim; i++)
result->x[i] = ax[start - 1 + i];
PG_RETURN_POINTER(result);
}
/*
* Internal helper to compare vectors
*/
@@ -897,9 +964,6 @@ vector_lt(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) < 0);
}
@@ -913,9 +977,6 @@ vector_le(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) <= 0);
}
@@ -929,9 +990,6 @@ vector_eq(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) == 0);
}
@@ -945,9 +1003,6 @@ vector_ne(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) != 0);
}
@@ -961,9 +1016,6 @@ vector_ge(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) >= 0);
}
@@ -977,9 +1029,6 @@ vector_gt(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) > 0);
}
@@ -1160,3 +1209,26 @@ vector_avg(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Convert sparse vector to dense vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_to_vector);
Datum
sparsevec_to_vector(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
int dim = svec->dim;
float *values = SPARSEVEC_VALUES(svec);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitVector(dim);
for (int i = 0; i < svec->nnz; i++)
result->x[svec->indices[i] - 1] = values[i];
PG_RETURN_POINTER(result);
}

View File

@@ -0,0 +1,104 @@
SELECT hamming_distance('111', '111');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance('111', '110');
hamming_distance
------------------
1
(1 row)
SELECT hamming_distance('111', '100');
hamming_distance
------------------
2
(1 row)
SELECT hamming_distance('111', '000');
hamming_distance
------------------
3
(1 row)
SELECT hamming_distance('10101010101010101010', '01010101010101010101');
hamming_distance
------------------
20
(1 row)
SELECT hamming_distance('', '');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance('111', '00');
ERROR: different bit lengths 3 and 2
SELECT hamming_distance('111', '000'::varbit(4));
hamming_distance
------------------
3
(1 row)
SELECT hamming_distance('111', '0000'::varbit(4));
ERROR: different bit lengths 3 and 4
SELECT jaccard_distance('1111', '1111');
jaccard_distance
------------------
0
(1 row)
SELECT jaccard_distance('1111', '1110');
jaccard_distance
------------------
0.25
(1 row)
SELECT jaccard_distance('1111', '1100');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance('1111', '1000');
jaccard_distance
------------------
0.75
(1 row)
SELECT jaccard_distance('1111', '0000');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('1100', '1000');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance('10101010101010101010', '01010101010101010101');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('', '');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('1111', '000');
ERROR: different bit lengths 4 and 3
SELECT jaccard_distance('1111', '0000'::varbit(5));
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('1111', '00000'::varbit(5));
ERROR: different bit lengths 4 and 5

View File

@@ -28,6 +28,26 @@ SELECT ARRAY[1,2,3]::numeric[]::vector;
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::real[];
float4
---------
{1,2,3}
(1 row)
SELECT '{1,2,3}'::real[]::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{NULL}'::real[]::vector;
ERROR: array must not contain nulls
SELECT '{NaN}'::real[]::vector;
@@ -40,12 +60,116 @@ SELECT '{}'::real[]::vector;
ERROR: vector must have at least 1 dimension
SELECT '{{1}}'::real[]::vector;
ERROR: array must be 1-D
SELECT '[1,2,3]'::vector::real[];
float4
SELECT '{1,2,3}'::double precision[]::vector;
vector
---------
{1,2,3}
[1,2,3]
(1 row)
SELECT '{1,2,3}'::double precision[]::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::double precision[]::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{4e38,-4e38}'::double precision[]::vector;
ERROR: infinite value not allowed in vector
SELECT '{1e-46,-1e-46}'::double precision[]::vector;
vector
--------
[0,-0]
(1 row)
SELECT '[1,2,3]'::vector::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[65520]'::vector::halfvec;
ERROR: "65520" is out of range for type halfvec
SELECT '[1e-8]'::vector::halfvec;
halfvec
---------
[0]
(1 row)
SELECT '[1,2,3]'::halfvec::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{1,2,3}'::real[]::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '{65520,-65520}'::real[]::halfvec;
ERROR: "65520" is out of range for type halfvec
SELECT '{1e-8,-1e-8}'::real[]::halfvec;
halfvec
---------
[0,-0]
(1 row)
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(5);
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(4);
ERROR: expected 4 dimensions, not 5
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector;
vector
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(5);
vector
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(4);
ERROR: expected 4 dimensions, not 5
SELECT '{}/16001'::sparsevec::vector;
ERROR: vector cannot have more than 16000 dimensions
SELECT 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;

View File

@@ -1,15 +1,15 @@
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val vector(3));
CREATE TABLE t (val vector(3), val2 halfvec(3), val3 sparsevec(3));
INSERT INTO t (val, val2, val3) VALUES ('[0,0,0]', '[0,0,0]', '{}/3'), ('[1,2,3]', '[1,2,3]', '{1:1,2:2,3:3}/3'), ('[1,1,1]', '[1,1,1]', '{1:1,2:1,3:1}/3'), (NULL, NULL, NULL);
CREATE TABLE t2 (val vector(3), val2 halfvec(3), val3 sparsevec(3));
\copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/data.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
val | val2 | val3
---------+---------+-----------------
[0,0,0] | [0,0,0] | {}/3
[1,1,1] | [1,1,1] | {1:1,2:1,3:1}/3
[1,2,3] | [1,2,3] | {1:1,2:2,3:3}/3
| |
(4 rows)
DROP TABLE t;

View File

@@ -0,0 +1,176 @@
SELECT round(halfvec_norm('[1,1]')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT halfvec_norm('[3,4]');
halfvec_norm
--------------
5
(1 row)
SELECT halfvec_norm('[0,1]');
halfvec_norm
--------------
1
(1 row)
SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,1,1,1,1,1,1,4,5]');
l2_distance
-------------
5
(1 row)
SELECT '[0,0]'::halfvec <-> '[3,4]';
?column?
----------
5
(1 row)
SELECT inner_product('[1,2]'::halfvec, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT inner_product('[65504]'::halfvec, '[65504]');
inner_product
---------------
4290774016
(1 row)
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
inner_product
---------------
45
(1 row)
SELECT '[1,2]'::halfvec <#> '[3,4]';
?column?
----------
-11
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]'::halfvec, '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT cosine_distance('[1,1]'::halfvec, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT '[1,2]'::halfvec <=> '[2,4]';
?column?
----------
0
(1 row)
SELECT l1_distance('[0,0]'::halfvec, '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT quantize_binary('[1,0,-1]'::halfvec);
quantize_binary
-----------------
100
(1 row)
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
quantize_binary
-----------------
01001110101
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
subvector
-----------
[1,2,3]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2);
subvector
-----------
[3,4]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 3);
subvector
-----------
[1]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 9);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 0);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, -1);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 2);
ERROR: halfvec must have at least 1 dimension

View File

@@ -0,0 +1,164 @@
SELECT '[1,2,3]'::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[-1,-2,-3]'::halfvec;
halfvec
------------
[-1,-2,-3]
(1 row)
SELECT '[1.,2.,3.]'::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT ' [ 1, 2 , 3 ] '::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1.23456]'::halfvec;
halfvec
------------
[1.234375]
(1 row)
SELECT '[hello,1]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[hello,1]"
LINE 1: SELECT '[hello,1]'::halfvec;
^
SELECT '[NaN,1]'::halfvec;
ERROR: NaN not allowed in halfvec
LINE 1: SELECT '[NaN,1]'::halfvec;
^
SELECT '[Infinity,1]'::halfvec;
ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[Infinity,1]'::halfvec;
^
SELECT '[-Infinity,1]'::halfvec;
ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[-Infinity,1]'::halfvec;
^
SELECT '[65519,-65519]'::halfvec;
halfvec
----------------
[65504,-65504]
(1 row)
SELECT '[65520,-65520]'::halfvec;
ERROR: "65520" is out of range for type halfvec
LINE 1: SELECT '[65520,-65520]'::halfvec;
^
SELECT '[1e-8,-1e-8]'::halfvec;
halfvec
---------
[0,-0]
(1 row)
SELECT '[4e38,1]'::halfvec;
ERROR: "4e38" is out of range for type halfvec
LINE 1: SELECT '[4e38,1]'::halfvec;
^
SELECT '[1e-46,1]'::halfvec;
halfvec
---------
[0,1]
(1 row)
SELECT '[1,2,3'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,2,3"
LINE 1: SELECT '[1,2,3'::halfvec;
^
SELECT '[1,2,3]9'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::halfvec;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::halfvec;
ERROR: invalid input syntax for type halfvec: "1,2,3"
LINE 1: SELECT '1,2,3'::halfvec;
^
DETAIL: Vector contents must start with "[".
SELECT ''::halfvec;
ERROR: invalid input syntax for type halfvec: ""
LINE 1: SELECT ''::halfvec;
^
DETAIL: Vector contents must start with "[".
SELECT '['::halfvec;
ERROR: invalid input syntax for type halfvec: "["
LINE 1: SELECT '['::halfvec;
^
SELECT '[ '::halfvec;
ERROR: invalid input syntax for type halfvec: "[ "
LINE 1: SELECT '[ '::halfvec;
^
SELECT '[,'::halfvec;
ERROR: invalid input syntax for type halfvec: "[,"
LINE 1: SELECT '[,'::halfvec;
^
SELECT '[]'::halfvec;
ERROR: halfvec must have at least 1 dimension
LINE 1: SELECT '[]'::halfvec;
^
SELECT '[ ]'::halfvec;
ERROR: halfvec must have at least 1 dimension
LINE 1: SELECT '[ ]'::halfvec;
^
SELECT '[,]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[,]"
LINE 1: SELECT '[,]'::halfvec;
^
SELECT '[1,]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,]"
LINE 1: SELECT '[1,]'::halfvec;
^
SELECT '[1a]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1a]"
LINE 1: SELECT '[1a]'::halfvec;
^
SELECT '[1,,3]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,,3]"
LINE 1: SELECT '[1,,3]'::halfvec;
^
SELECT '[1, ,3]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::halfvec;
^
SELECT '[1,2,3]'::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::halfvec(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::halfvec(3, 2);
^
SELECT '[1,2,3]'::halfvec('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::halfvec('a');
^
SELECT '[1,2,3]'::halfvec(0);
ERROR: dimensions for type halfvec must be at least 1
LINE 1: SELECT '[1,2,3]'::halfvec(0);
^
SELECT '[1,2,3]'::halfvec(16001);
ERROR: dimensions for type halfvec cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::halfvec(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::halfvec[]);
unnest
---------
[1,2,3]
[4,5,6]
(2 rows)
SELECT '{"[1,2,3]"}'::halfvec(2)[];
ERROR: expected 2 dimensions, not 3

View File

@@ -0,0 +1,29 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
val
-----
111
110
100
000
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- TODO move
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
ERROR: type not supported for hnsw index
CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
ERROR: column cannot have more than 64000 dimensions for hnsw index
DROP TABLE t;

View File

@@ -0,0 +1,21 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(4));
INSERT INTO t (val) VALUES (B'0000'), (B'1100'), (B'1111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_jaccard_ops);
INSERT INTO t (val) VALUES (B'1110');
SELECT * FROM t ORDER BY val <%> B'1111';
val
------
1111
1110
1100
0000
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <%> (SELECT NULL::bit)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

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

View File

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

View File

@@ -0,0 +1,33 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;

View File

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

View File

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

View File

@@ -0,0 +1,43 @@
SET enable_seqscan = off;
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
val
-----------------
{1:1,2:2,3:3}/3
{1:1,2:2,3:4}/3
{1:1,2:1,3:1}/3
{}/3
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
val
-----
(0 rows)
DROP TABLE t;
-- TODO move
CREATE TABLE t (val sparsevec(1001));
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
TRUNCATE t;
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
DROP TABLE t;

View File

@@ -12,14 +12,11 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
[0,0,0]
(4 rows)
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count

View File

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

View File

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

View File

@@ -0,0 +1,36 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;

View File

@@ -12,14 +12,11 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
[0,0,0]
(4 rows)
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count

View File

@@ -0,0 +1,86 @@
SELECT round(sparsevec_norm('{1:1,2:1}/2')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT sparsevec_norm('{1:3,2:4}/2');
sparsevec_norm
----------------
5
(1 row)
SELECT sparsevec_norm('{2:1}/2');
sparsevec_norm
----------------
1
(1 row)
SELECT sparsevec_norm('{1:3e37,2:4e37}/2')::real;
sparsevec_norm
----------------
5e+37
(1 row)
SELECT l2_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{}/2'::sparsevec, '{2:1}/2');
l2_distance
-------------
1
(1 row)
SELECT '{}/2'::sparsevec <-> '{1:3,2:4}/2';
?column?
----------
5
(1 row)
SELECT inner_product('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
inner_product
---------------
10
(1 row)
SELECT sparsevec_negative_inner_product('{1:1,2:2}/2', '{1:2,2:4}/2');
sparsevec_negative_inner_product
----------------------------------
-10
(1 row)
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{}/2');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:-1,2:-1}/2');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('{1:2}/2'::sparsevec, '{2:2}/2');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{1:2}/2'::sparsevec, '{1:1}/3');
ERROR: different sparsevec dimensions 2 and 3

View File

@@ -0,0 +1,215 @@
SELECT '{1:1.5,3:3.5}/5'::sparsevec;
sparsevec
-----------------
{1:1.5,3:3.5}/5
(1 row)
SELECT '{1:-2,3:-4}/5'::sparsevec;
sparsevec
---------------
{1:-2,3:-4}/5
(1 row)
SELECT '{1:2.,3:4.}/5'::sparsevec;
sparsevec
-------------
{1:2,3:4}/5
(1 row)
SELECT ' { 1 : 1.5 , 3 : 3.5 } / 5 '::sparsevec;
sparsevec
-----------------
{1:1.5,3:3.5}/5
(1 row)
SELECT '{1:1.23456}/1'::sparsevec;
sparsevec
---------------
{1:1.23456}/1
(1 row)
SELECT '{1:hello,2:1}/2'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:hello,2:1}/2"
LINE 1: SELECT '{1:hello,2:1}/2'::sparsevec;
^
SELECT '{1:NaN,2:1}/2'::sparsevec;
ERROR: NaN not allowed in sparsevec
LINE 1: SELECT '{1:NaN,2:1}/2'::sparsevec;
^
SELECT '{1:Infinity,2:1}/2'::sparsevec;
ERROR: infinite value not allowed in sparsevec
LINE 1: SELECT '{1:Infinity,2:1}/2'::sparsevec;
^
SELECT '{1:-Infinity,2:1}/2'::sparsevec;
ERROR: infinite value not allowed in sparsevec
LINE 1: SELECT '{1:-Infinity,2:1}/2'::sparsevec;
^
SELECT '{1:1.5e38,2:-1.5e38}/2'::sparsevec;
sparsevec
--------------------------
{1:1.5e+38,2:-1.5e+38}/2
(1 row)
SELECT '{1:1.5e+38,2:-1.5e+38}/2'::sparsevec;
sparsevec
--------------------------
{1:1.5e+38,2:-1.5e+38}/2
(1 row)
SELECT '{1:1.5e-38,2:-1.5e-38}/2'::sparsevec;
sparsevec
--------------------------
{1:1.5e-38,2:-1.5e-38}/2
(1 row)
SELECT '{1:4e38,2:1}/2'::sparsevec;
ERROR: "4e38" is out of range for type sparsevec
LINE 1: SELECT '{1:4e38,2:1}/2'::sparsevec;
^
SELECT '{1:-4e38,2:1}/2'::sparsevec;
ERROR: "-4e38" is out of range for type sparsevec
LINE 1: SELECT '{1:-4e38,2:1}/2'::sparsevec;
^
SELECT '{1:1e-46,2:1}/2'::sparsevec;
ERROR: "1e-46" is out of range for type sparsevec
LINE 1: SELECT '{1:1e-46,2:1}/2'::sparsevec;
^
SELECT '{1:-1e-46,2:1}/2'::sparsevec;
ERROR: "-1e-46" is out of range for type sparsevec
LINE 1: SELECT '{1:-1e-46,2:1}/2'::sparsevec;
^
SELECT ''::sparsevec;
ERROR: invalid input syntax for type sparsevec: ""
LINE 1: SELECT ''::sparsevec;
^
DETAIL: Vector contents must start with "{".
SELECT '{'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{"
LINE 1: SELECT '{'::sparsevec;
^
SELECT '{ '::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{ "
LINE 1: SELECT '{ '::sparsevec;
^
SELECT '{:'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{:"
LINE 1: SELECT '{:'::sparsevec;
^
SELECT '{,'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{,"
LINE 1: SELECT '{,'::sparsevec;
^
SELECT '{}'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{}"
LINE 1: SELECT '{}'::sparsevec;
^
DETAIL: Unexpected end of input.
SELECT '{}/'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{}/"
LINE 1: SELECT '{}/'::sparsevec;
^
SELECT '{}/1'::sparsevec;
sparsevec
-----------
{}/1
(1 row)
SELECT '{}/1a'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{}/1a"
LINE 1: SELECT '{}/1a'::sparsevec;
^
DETAIL: Junk after closing.
SELECT '{ }/1'::sparsevec;
sparsevec
-----------
{}/1
(1 row)
SELECT '{:}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{:}/1"
LINE 1: SELECT '{:}/1'::sparsevec;
^
SELECT '{,}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{,}/1"
LINE 1: SELECT '{,}/1'::sparsevec;
^
SELECT '{1,}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1,}/1"
LINE 1: SELECT '{1,}/1'::sparsevec;
^
SELECT '{:1}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{:1}/1"
LINE 1: SELECT '{:1}/1'::sparsevec;
^
SELECT '{1:}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:}/1"
LINE 1: SELECT '{1:}/1'::sparsevec;
^
SELECT '{1a:1}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1a:1}/1"
LINE 1: SELECT '{1a:1}/1'::sparsevec;
^
SELECT '{1:1a}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:1a}/1"
LINE 1: SELECT '{1:1a}/1'::sparsevec;
^
SELECT '{1:1,}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:1,}/1"
LINE 1: SELECT '{1:1,}/1'::sparsevec;
^
SELECT '{1:0,2:1,3:0}/3'::sparsevec;
sparsevec
-----------
{2:1}/3
(1 row)
SELECT '{2:1,1:1}/2'::sparsevec;
ERROR: indexes must be in ascending order
LINE 1: SELECT '{2:1,1:1}/2'::sparsevec;
^
SELECT '{}/5'::sparsevec;
sparsevec
-----------
{}/5
(1 row)
SELECT '{}/-1'::sparsevec;
ERROR: sparsevec must have at least 1 dimension
LINE 1: SELECT '{}/-1'::sparsevec;
^
SELECT '{}/100001'::sparsevec;
ERROR: sparsevec cannot have more than 100000 dimensions
LINE 1: SELECT '{}/100001'::sparsevec;
^
SELECT '{0:1}/1'::sparsevec;
ERROR: index "0" is out of range for type sparsevec
LINE 1: SELECT '{0:1}/1'::sparsevec;
^
SELECT '{2:1}/1'::sparsevec;
ERROR: index must be less than or equal to dimensions
LINE 1: SELECT '{2:1}/1'::sparsevec;
^
SELECT '{}/3'::sparsevec(3);
sparsevec
-----------
{}/3
(1 row)
SELECT '{}/3'::sparsevec(2);
ERROR: expected 2 dimensions, not 3
SELECT '{}/3'::sparsevec(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '{}/3'::sparsevec(3, 2);
^
SELECT '{}/3'::sparsevec('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '{}/3'::sparsevec('a');
^
SELECT '{}/3'::sparsevec(0);
ERROR: dimensions for type sparsevec must be at least 1
LINE 1: SELECT '{}/3'::sparsevec(0);
^
SELECT '{}/3'::sparsevec(100001);
ERROR: dimensions for type sparsevec cannot exceed 100000
LINE 1: SELECT '{}/3'::sparsevec(100001);
^

View File

@@ -24,6 +24,30 @@ SELECT '[1e37]'::vector * '[1e37]';
ERROR: value out of range: overflow
SELECT '[1e-37]'::vector * '[1e-37]';
ERROR: value out of range: underflow
SELECT '[1,2,3]'::vector < '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector < '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector <= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector <= '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector = '[1,2,3]';
?column?
----------
@@ -31,7 +55,47 @@ SELECT '[1,2,3]'::vector = '[1,2,3]';
(1 row)
SELECT '[1,2,3]'::vector = '[1,2]';
ERROR: different vector dimensions 3 and 2
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector != '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector != '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector >= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector >= '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector > '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector > '[1,2]';
?column?
----------
t
(1 row)
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
vector_cmp
------------
@@ -104,110 +168,152 @@ SELECT vector_norm('[3e37,4e37]')::real;
5e+37
(1 row)
SELECT l2_distance('[0,0]', '[3,4]');
SELECT l2_distance('[0,0]'::vector, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]', '[0,1]');
SELECT l2_distance('[0,0]'::vector, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]', '[3]');
SELECT l2_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l2_distance('[3e38]', '[-3e38]');
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
l2_distance
-------------
Infinity
(1 row)
SELECT inner_product('[1,2]', '[3,4]');
SELECT inner_product('[1,2]'::vector, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]', '[3]');
SELECT inner_product('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT inner_product('[3e38]', '[3e38]');
SELECT inner_product('[3e38]'::vector, '[3e38]');
inner_product
---------------
Infinity
(1 row)
SELECT cosine_distance('[1,2]', '[2,4]');
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]', '[0,0]');
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]', '[1,1]');
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]', '[0,2]');
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]', '[-1,-1]');
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]', '[3]');
SELECT cosine_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[3e38]', '[3e38]');
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
cosine_distance
-----------------
NaN
(1 row)
SELECT l1_distance('[0,0]', '[3,4]');
SELECT l1_distance('[0,0]'::vector, '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]', '[0,1]');
SELECT l1_distance('[0,0]'::vector, '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]', '[3]');
SELECT l1_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l1_distance('[3e38]', '[-3e38]');
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
l1_distance
-------------
Infinity
(1 row)
SELECT quantize_binary('[1,0,-1]'::vector);
quantize_binary
-----------------
100
(1 row)
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
quantize_binary
-----------------
01001110101
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
subvector
-----------
[1,2,3]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);
subvector
-----------
[3,4]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, -1, 3);
subvector
-----------
[1]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 3, 9);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 1, 0);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, 3, -1);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, -1, 2);
ERROR: vector must have at least 1 dimension
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
avg
-----------

View File

@@ -63,43 +63,68 @@ SELECT '[1.5e-38,-1.5e-38]'::vector;
(1 row)
SELECT '[4e38,1]'::vector;
ERROR: infinite value not allowed in vector
ERROR: "4e38" is out of range for type vector
LINE 1: SELECT '[4e38,1]'::vector;
^
SELECT '[-4e38,1]'::vector;
ERROR: "-4e38" is out of range for type vector
LINE 1: SELECT '[-4e38,1]'::vector;
^
SELECT '[1e-46,1]'::vector;
vector
--------
[0,1]
(1 row)
SELECT '[-1e-46,1]'::vector;
vector
--------
[-0,1]
(1 row)
SELECT '[1,2,3'::vector;
ERROR: malformed vector literal: "[1,2,3"
ERROR: invalid input syntax for type vector: "[1,2,3"
LINE 1: SELECT '[1,2,3'::vector;
^
DETAIL: Unexpected end of input.
SELECT '[1,2,3]9'::vector;
ERROR: malformed vector literal: "[1,2,3]9"
ERROR: invalid input syntax for type vector: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::vector;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::vector;
ERROR: malformed vector literal: "1,2,3"
ERROR: invalid input syntax for type vector: "1,2,3"
LINE 1: SELECT '1,2,3'::vector;
^
DETAIL: Vector contents must start with "[".
SELECT ''::vector;
ERROR: malformed vector literal: ""
ERROR: invalid input syntax for type vector: ""
LINE 1: SELECT ''::vector;
^
DETAIL: Vector contents must start with "[".
SELECT '['::vector;
ERROR: malformed vector literal: "["
ERROR: invalid input syntax for type vector: "["
LINE 1: SELECT '['::vector;
^
DETAIL: Unexpected end of input.
SELECT '[ '::vector;
ERROR: invalid input syntax for type vector: "[ "
LINE 1: SELECT '[ '::vector;
^
SELECT '[,'::vector;
ERROR: malformed vector literal: "[,"
ERROR: invalid input syntax for type vector: "[,"
LINE 1: SELECT '[,'::vector;
^
DETAIL: Unexpected end of input.
SELECT '[]'::vector;
ERROR: vector must have at least 1 dimension
LINE 1: SELECT '[]'::vector;
^
SELECT '[ ]'::vector;
ERROR: vector must have at least 1 dimension
LINE 1: SELECT '[ ]'::vector;
^
SELECT '[,]'::vector;
ERROR: invalid input syntax for type vector: "[,]"
LINE 1: SELECT '[,]'::vector;
^
SELECT '[1,]'::vector;
ERROR: invalid input syntax for type vector: "[1,]"
LINE 1: SELECT '[1,]'::vector;
@@ -109,15 +134,37 @@ ERROR: invalid input syntax for type vector: "[1a]"
LINE 1: SELECT '[1a]'::vector;
^
SELECT '[1,,3]'::vector;
ERROR: malformed vector literal: "[1,,3]"
ERROR: invalid input syntax for type vector: "[1,,3]"
LINE 1: SELECT '[1,,3]'::vector;
^
SELECT '[1, ,3]'::vector;
ERROR: invalid input syntax for type vector: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::vector;
^
SELECT '[1,2,3]'::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::vector(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::vector(3, 2);
^
SELECT '[1,2,3]'::vector('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::vector('a');
^
SELECT '[1,2,3]'::vector(0);
ERROR: dimensions for type vector must be at least 1
LINE 1: SELECT '[1,2,3]'::vector(0);
^
SELECT '[1,2,3]'::vector(16001);
ERROR: dimensions for type vector cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::vector(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
unnest
---------

View File

@@ -0,0 +1,21 @@
SELECT hamming_distance('111', '111');
SELECT hamming_distance('111', '110');
SELECT hamming_distance('111', '100');
SELECT hamming_distance('111', '000');
SELECT hamming_distance('10101010101010101010', '01010101010101010101');
SELECT hamming_distance('', '');
SELECT hamming_distance('111', '00');
SELECT hamming_distance('111', '000'::varbit(4));
SELECT hamming_distance('111', '0000'::varbit(4));
SELECT jaccard_distance('1111', '1111');
SELECT jaccard_distance('1111', '1110');
SELECT jaccard_distance('1111', '1100');
SELECT jaccard_distance('1111', '1000');
SELECT jaccard_distance('1111', '0000');
SELECT jaccard_distance('1100', '1000');
SELECT jaccard_distance('10101010101010101010', '01010101010101010101');
SELECT jaccard_distance('', '');
SELECT jaccard_distance('1111', '000');
SELECT jaccard_distance('1111', '0000'::varbit(5));
SELECT jaccard_distance('1111', '00000'::varbit(5));

View File

@@ -3,13 +3,50 @@ SELECT ARRAY[1.0,2.0,3.0]::vector;
SELECT ARRAY[1,2,3]::float4[]::vector;
SELECT ARRAY[1,2,3]::float8[]::vector;
SELECT ARRAY[1,2,3]::numeric[]::vector;
SELECT '[1,2,3]'::vector::real[];
SELECT '{1,2,3}'::real[]::vector;
SELECT '{1,2,3}'::real[]::vector(3);
SELECT '{1,2,3}'::real[]::vector(2);
SELECT '{NULL}'::real[]::vector;
SELECT '{NaN}'::real[]::vector;
SELECT '{Infinity}'::real[]::vector;
SELECT '{-Infinity}'::real[]::vector;
SELECT '{}'::real[]::vector;
SELECT '{{1}}'::real[]::vector;
SELECT '[1,2,3]'::vector::real[];
SELECT '{1,2,3}'::double precision[]::vector;
SELECT '{1,2,3}'::double precision[]::vector(3);
SELECT '{1,2,3}'::double precision[]::vector(2);
SELECT '{4e38,-4e38}'::double precision[]::vector;
SELECT '{1e-46,-1e-46}'::double precision[]::vector;
SELECT '[1,2,3]'::vector::halfvec;
SELECT '[1,2,3]'::vector::halfvec(3);
SELECT '[1,2,3]'::vector::halfvec(2);
SELECT '[65520]'::vector::halfvec;
SELECT '[1e-8]'::vector::halfvec;
SELECT '[1,2,3]'::halfvec::vector;
SELECT '[1,2,3]'::halfvec::vector(3);
SELECT '[1,2,3]'::halfvec::vector(2);
SELECT '{1,2,3}'::real[]::halfvec;
SELECT '{1,2,3}'::real[]::halfvec(3);
SELECT '{1,2,3}'::real[]::halfvec(2);
SELECT '{65520,-65520}'::real[]::halfvec;
SELECT '{1e-8,-1e-8}'::real[]::halfvec;
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(5);
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(4);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector;
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(5);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(4);
SELECT '{}/16001'::sparsevec::vector;
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;

View File

@@ -1,7 +1,7 @@
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t (val vector(3), val2 halfvec(3), val3 sparsevec(3));
INSERT INTO t (val, val2, val3) VALUES ('[0,0,0]', '[0,0,0]', '{}/3'), ('[1,2,3]', '[1,2,3]', '{1:1,2:2,3:3}/3'), ('[1,1,1]', '[1,1,1]', '{1:1,2:1,3:1}/3'), (NULL, NULL, NULL);
CREATE TABLE t2 (val vector(3));
CREATE TABLE t2 (val vector(3), val2 halfvec(3), val3 sparsevec(3));
\copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/data.bin' WITH (FORMAT binary)

View File

@@ -1,62 +0,0 @@
SELECT '[1,2,3]'::vector + '[4,5,6]';
SELECT '[3e38]'::vector + '[3e38]';
SELECT '[1,2,3]'::vector - '[4,5,6]';
SELECT '[-3e38]'::vector - '[3e38]';
SELECT '[1,2,3]'::vector * '[4,5,6]';
SELECT '[1e37]'::vector * '[1e37]';
SELECT '[1e-37]'::vector * '[1e-37]';
SELECT '[1,2,3]'::vector = '[1,2,3]';
SELECT '[1,2,3]'::vector = '[1,2]';
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
SELECT vector_cmp('[1,2]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[1,2]');
SELECT vector_cmp('[1,2]', '[2,3,4]');
SELECT vector_cmp('[2,3]', '[1,2,3]');
SELECT vector_dims('[1,2,3]');
SELECT round(vector_norm('[1,1]')::numeric, 5);
SELECT vector_norm('[3,4]');
SELECT vector_norm('[0,1]');
SELECT vector_norm('[3e37,4e37]')::real;
SELECT l2_distance('[0,0]', '[3,4]');
SELECT l2_distance('[0,0]', '[0,1]');
SELECT l2_distance('[1,2]', '[3]');
SELECT l2_distance('[3e38]', '[-3e38]');
SELECT inner_product('[1,2]', '[3,4]');
SELECT inner_product('[1,2]', '[3]');
SELECT inner_product('[3e38]', '[3e38]');
SELECT cosine_distance('[1,2]', '[2,4]');
SELECT cosine_distance('[1,2]', '[0,0]');
SELECT cosine_distance('[1,1]', '[1,1]');
SELECT cosine_distance('[1,0]', '[0,2]');
SELECT cosine_distance('[1,1]', '[-1,-1]');
SELECT cosine_distance('[1,2]', '[3]');
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
SELECT cosine_distance('[3e38]', '[3e38]');
SELECT l1_distance('[0,0]', '[3,4]');
SELECT l1_distance('[0,0]', '[0,1]');
SELECT l1_distance('[1,2]', '[3]');
SELECT l1_distance('[3e38]', '[-3e38]');
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;

View File

@@ -0,0 +1,40 @@
SELECT round(halfvec_norm('[1,1]')::numeric, 5);
SELECT halfvec_norm('[3,4]');
SELECT halfvec_norm('[0,1]');
SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
SELECT l2_distance('[1,2]'::halfvec, '[3]');
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,1,1,1,1,1,1,4,5]');
SELECT '[0,0]'::halfvec <-> '[3,4]';
SELECT inner_product('[1,2]'::halfvec, '[3,4]');
SELECT inner_product('[1,2]'::halfvec, '[3]');
SELECT inner_product('[65504]'::halfvec, '[65504]');
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
SELECT '[1,2]'::halfvec <#> '[3,4]';
SELECT cosine_distance('[1,2]'::halfvec, '[2,4]');
SELECT cosine_distance('[1,2]'::halfvec, '[0,0]');
SELECT cosine_distance('[1,1]'::halfvec, '[1,1]');
SELECT cosine_distance('[1,0]'::halfvec, '[0,2]');
SELECT cosine_distance('[1,1]'::halfvec, '[-1,-1]');
SELECT cosine_distance('[1,2]'::halfvec, '[3]');
SELECT cosine_distance('[1,1]'::halfvec, '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::halfvec, '[-1.1,-1.1]');
SELECT '[1,2]'::halfvec <=> '[2,4]';
SELECT l1_distance('[0,0]'::halfvec, '[3,4]');
SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
SELECT l1_distance('[1,2]'::halfvec, '[3]');
SELECT quantize_binary('[1,0,-1]'::halfvec);
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2);
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 3);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 9);
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 0);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, -1);
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 2);

View File

@@ -0,0 +1,38 @@
SELECT '[1,2,3]'::halfvec;
SELECT '[-1,-2,-3]'::halfvec;
SELECT '[1.,2.,3.]'::halfvec;
SELECT ' [ 1, 2 , 3 ] '::halfvec;
SELECT '[1.23456]'::halfvec;
SELECT '[hello,1]'::halfvec;
SELECT '[NaN,1]'::halfvec;
SELECT '[Infinity,1]'::halfvec;
SELECT '[-Infinity,1]'::halfvec;
SELECT '[65519,-65519]'::halfvec;
SELECT '[65520,-65520]'::halfvec;
SELECT '[1e-8,-1e-8]'::halfvec;
SELECT '[4e38,1]'::halfvec;
SELECT '[1e-46,1]'::halfvec;
SELECT '[1,2,3'::halfvec;
SELECT '[1,2,3]9'::halfvec;
SELECT '1,2,3'::halfvec;
SELECT ''::halfvec;
SELECT '['::halfvec;
SELECT '[ '::halfvec;
SELECT '[,'::halfvec;
SELECT '[]'::halfvec;
SELECT '[ ]'::halfvec;
SELECT '[,]'::halfvec;
SELECT '[1,]'::halfvec;
SELECT '[1a]'::halfvec;
SELECT '[1,,3]'::halfvec;
SELECT '[1, ,3]'::halfvec;
SELECT '[1,2,3]'::halfvec(3);
SELECT '[1,2,3]'::halfvec(2);
SELECT '[1,2,3]'::halfvec(3, 2);
SELECT '[1,2,3]'::halfvec('a');
SELECT '[1,2,3]'::halfvec(0);
SELECT '[1,2,3]'::halfvec(16001);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::halfvec[]);
SELECT '{"[1,2,3]"}'::halfvec(2)[];

View File

@@ -0,0 +1,19 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
DROP TABLE t;
-- TODO move
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
DROP TABLE t;

View File

@@ -0,0 +1,12 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(4));
INSERT INTO t (val) VALUES (B'0000'), (B'1100'), (B'1111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_jaccard_ops);
INSERT INTO t (val) VALUES (B'1110');
SELECT * FROM t ORDER BY val <%> B'1111';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <%> (SELECT NULL::bit)) t2;
DROP TABLE t;

View File

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

View File

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

View File

@@ -0,0 +1,16 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;

View File

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

View File

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

View File

@@ -0,0 +1,25 @@
SET enable_seqscan = off;
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
DROP TABLE t;
-- TODO move
CREATE TABLE t (val sparsevec(1001));
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
TRUNCATE t;
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
DROP TABLE t;

View File

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

View File

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

View File

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

View File

@@ -0,0 +1,16 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;

View File

@@ -7,7 +7,7 @@ CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;

View File

@@ -0,0 +1,18 @@
SELECT round(sparsevec_norm('{1:1,2:1}/2')::numeric, 5);
SELECT sparsevec_norm('{1:3,2:4}/2');
SELECT sparsevec_norm('{2:1}/2');
SELECT sparsevec_norm('{1:3e37,2:4e37}/2')::real;
SELECT l2_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
SELECT l2_distance('{}/2'::sparsevec, '{2:1}/2');
SELECT '{}/2'::sparsevec <-> '{1:3,2:4}/2';
SELECT inner_product('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
SELECT sparsevec_negative_inner_product('{1:1,2:2}/2', '{1:2,2:4}/2');
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{}/2');
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:-1,2:-1}/2');
SELECT cosine_distance('{1:2}/2'::sparsevec, '{2:2}/2');
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
SELECT cosine_distance('{1:2}/2'::sparsevec, '{1:1}/3');

View File

@@ -0,0 +1,48 @@
SELECT '{1:1.5,3:3.5}/5'::sparsevec;
SELECT '{1:-2,3:-4}/5'::sparsevec;
SELECT '{1:2.,3:4.}/5'::sparsevec;
SELECT ' { 1 : 1.5 , 3 : 3.5 } / 5 '::sparsevec;
SELECT '{1:1.23456}/1'::sparsevec;
SELECT '{1:hello,2:1}/2'::sparsevec;
SELECT '{1:NaN,2:1}/2'::sparsevec;
SELECT '{1:Infinity,2:1}/2'::sparsevec;
SELECT '{1:-Infinity,2:1}/2'::sparsevec;
SELECT '{1:1.5e38,2:-1.5e38}/2'::sparsevec;
SELECT '{1:1.5e+38,2:-1.5e+38}/2'::sparsevec;
SELECT '{1:1.5e-38,2:-1.5e-38}/2'::sparsevec;
SELECT '{1:4e38,2:1}/2'::sparsevec;
SELECT '{1:-4e38,2:1}/2'::sparsevec;
SELECT '{1:1e-46,2:1}/2'::sparsevec;
SELECT '{1:-1e-46,2:1}/2'::sparsevec;
SELECT ''::sparsevec;
SELECT '{'::sparsevec;
SELECT '{ '::sparsevec;
SELECT '{:'::sparsevec;
SELECT '{,'::sparsevec;
SELECT '{}'::sparsevec;
SELECT '{}/'::sparsevec;
SELECT '{}/1'::sparsevec;
SELECT '{}/1a'::sparsevec;
SELECT '{ }/1'::sparsevec;
SELECT '{:}/1'::sparsevec;
SELECT '{,}/1'::sparsevec;
SELECT '{1,}/1'::sparsevec;
SELECT '{:1}/1'::sparsevec;
SELECT '{1:}/1'::sparsevec;
SELECT '{1a:1}/1'::sparsevec;
SELECT '{1:1a}/1'::sparsevec;
SELECT '{1:1,}/1'::sparsevec;
SELECT '{1:0,2:1,3:0}/3'::sparsevec;
SELECT '{2:1,1:1}/2'::sparsevec;
SELECT '{}/5'::sparsevec;
SELECT '{}/-1'::sparsevec;
SELECT '{}/100001'::sparsevec;
SELECT '{0:1}/1'::sparsevec;
SELECT '{2:1}/1'::sparsevec;
SELECT '{}/3'::sparsevec(3);
SELECT '{}/3'::sparsevec(2);
SELECT '{}/3'::sparsevec(3, 2);
SELECT '{}/3'::sparsevec('a');
SELECT '{}/3'::sparsevec(0);
SELECT '{}/3'::sparsevec(100001);

View File

@@ -0,0 +1,83 @@
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 '[1,2,3]'::vector < '[1,2,3]';
SELECT '[1,2,3]'::vector < '[1,2]';
SELECT '[1,2,3]'::vector <= '[1,2,3]';
SELECT '[1,2,3]'::vector <= '[1,2]';
SELECT '[1,2,3]'::vector = '[1,2,3]';
SELECT '[1,2,3]'::vector = '[1,2]';
SELECT '[1,2,3]'::vector != '[1,2,3]';
SELECT '[1,2,3]'::vector != '[1,2]';
SELECT '[1,2,3]'::vector >= '[1,2,3]';
SELECT '[1,2,3]'::vector >= '[1,2]';
SELECT '[1,2,3]'::vector > '[1,2,3]';
SELECT '[1,2,3]'::vector > '[1,2]';
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
SELECT vector_cmp('[1,2]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[1,2]');
SELECT vector_cmp('[1,2]', '[2,3,4]');
SELECT vector_cmp('[2,3]', '[1,2,3]');
SELECT vector_dims('[1,2,3]');
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]'::vector, '[3,4]');
SELECT l2_distance('[0,0]'::vector, '[0,1]');
SELECT l2_distance('[1,2]'::vector, '[3]');
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
SELECT inner_product('[1,2]'::vector, '[3,4]');
SELECT inner_product('[1,2]'::vector, '[3]');
SELECT inner_product('[3e38]'::vector, '[3e38]');
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
SELECT cosine_distance('[1,2]'::vector, '[3]');
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
SELECT l1_distance('[0,0]'::vector, '[3,4]');
SELECT l1_distance('[0,0]'::vector, '[0,1]');
SELECT l1_distance('[1,2]'::vector, '[3]');
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
SELECT quantize_binary('[1,0,-1]'::vector);
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);
SELECT subvector('[1,2,3,4,5]'::vector, -1, 3);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 9);
SELECT subvector('[1,2,3,4,5]'::vector, 1, 0);
SELECT subvector('[1,2,3,4,5]'::vector, 3, -1);
SELECT subvector('[1,2,3,4,5]'::vector, -1, 2);
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;

View File

@@ -11,18 +11,30 @@ SELECT '[1.5e38,-1.5e38]'::vector;
SELECT '[1.5e+38,-1.5e+38]'::vector;
SELECT '[1.5e-38,-1.5e-38]'::vector;
SELECT '[4e38,1]'::vector;
SELECT '[-4e38,1]'::vector;
SELECT '[1e-46,1]'::vector;
SELECT '[-1e-46,1]'::vector;
SELECT '[1,2,3'::vector;
SELECT '[1,2,3]9'::vector;
SELECT '1,2,3'::vector;
SELECT ''::vector;
SELECT '['::vector;
SELECT '[ '::vector;
SELECT '[,'::vector;
SELECT '[]'::vector;
SELECT '[ ]'::vector;
SELECT '[,]'::vector;
SELECT '[1,]'::vector;
SELECT '[1a]'::vector;
SELECT '[1,,3]'::vector;
SELECT '[1, ,3]'::vector;
SELECT '[1,2,3]'::vector(3);
SELECT '[1,2,3]'::vector(2);
SELECT '[1,2,3]'::vector(3, 2);
SELECT '[1,2,3]'::vector('a');
SELECT '[1,2,3]'::vector(0);
SELECT '[1,2,3]'::vector(16001);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
SELECT '{"[1,2,3]"}'::vector(2)[];

View File

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

View File

@@ -98,6 +98,7 @@ for my $i (0 .. $#operators)
push(@expected, $res);
}
# Test approximate results
my $min = $operator eq "<#>" ? 0.80 : 0.99;
test_recall($min, $operator);

View File

@@ -86,7 +86,7 @@ foreach (@queries)
push(@expected, $res);
}
test_recall(0.20, $limit, "before vacuum");
test_recall(0.18, $limit, "before vacuum");
test_recall(0.95, 100, "before vacuum");
# TODO Test concurrent inserts with vacuum

View File

@@ -0,0 +1,137 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 52;
my $max = 2**$dim;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
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 hnsw.ef_search = 100;
SELECT i FROM tst ORDER BY v $operator $queries[$i] LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v bit($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, (random() * $max)::bigint::bit($dim) FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1 .. 20)
{
my $r = int(rand() * $max);
push(@queries, "${r}::bigint::bit($dim)");
}
# Check each index type
my @operators = ("<~>", "<\%>");
my @opclasses = ("bit_hamming_ops", "bit_jaccard_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Get exact results
@expected = ();
foreach (@queries)
{
# Handle ties
my $res = $node->safe_psql("postgres", qq(
WITH top AS (
SELECT v $operator $_ AS distance FROM tst ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator $_) <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
# Build index serially
$node->safe_psql("postgres", qq(
SET max_parallel_maintenance_workers = 0;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
# Test approximate results
my $min = $operator eq "<\%>" ? 0.95 : 0.98;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel in memory
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel on disk
# Set parallel_workers on table to use workers with low maintenance_work_mem
($ret, $stdout, $stderr) = $node->psql("postgres", qq(
ALTER TABLE tst SET (parallel_workers = 2);
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '4MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
ALTER TABLE tst RESET (parallel_workers);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem/);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

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@@ -0,0 +1,132 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 10;
my $array_sql = join(",", ('random()') x $dim);
sub test_recall
{
my ($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;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v halfvec($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1 .. 20)
{
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
push(@queries, "[" . join(",", @r) . "]");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("halfvec_l2_ops", "halfvec_ip_ops", "halfvec_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 hnsw (v $opclass);
));
# Test approximate results
my $min = $operator eq "<#>" ? 0.93 : 0.98;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel in memory
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel on disk
# Set parallel_workers on table to use workers with low maintenance_work_mem
($ret, $stdout, $stderr) = $node->psql("postgres", qq(
ALTER TABLE tst SET (parallel_workers = 2);
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '4MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
ALTER TABLE tst RESET (parallel_workers);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem/);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

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@@ -0,0 +1,128 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
sub test_recall
{
my ($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 int4, v sparsevec(3));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()]::vector::sparsevec FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "{1:$r1,2:$r2,3:$r3}/3");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("sparsevec_l2_ops", "sparsevec_ip_ops", "sparsevec_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 hnsw (v $opclass);
));
# Test approximate results
my $min = $operator eq "<#>" ? 0.80 : 0.99;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel in memory
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel on disk
# Set parallel_workers on table to use workers with low maintenance_work_mem
($ret, $stdout, $stderr) = $node->psql("postgres", qq(
ALTER TABLE tst SET (parallel_workers = 2);
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '4MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
ALTER TABLE tst RESET (parallel_workers);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem/);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

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@@ -0,0 +1,116 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 52;
my $max = 2**$dim;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
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 hnsw.ef_search = 100;
SELECT i FROM tst ORDER BY v $operator $queries[$i] LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v bit($dim));");
# Generate queries
for (1 .. 20)
{
my $r = int(rand() * $max);
push(@queries, "${r}::bigint::bit($dim)");
}
# Check each index type
my @operators = ("<~>", "<\%>");
my @opclasses = ("bit_hamming_ops", "bit_jaccard_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",
{
"023_hnsw_bit_insert_recall_$opclass" => "INSERT INTO tst (v) VALUES ((random() * $max)::bigint::bit($dim));"
}
);
# Get exact results
@expected = ();
foreach (@queries)
{
# Handle ties
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
WITH top AS (
SELECT v $operator $_ AS distance FROM tst ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator $_) <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
# Test approximate results
my $min = $operator eq "<\%>" ? 0.95 : 0.98;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
$node->safe_psql("postgres", "TRUNCATE tst;");
}
done_testing();

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@@ -0,0 +1,113 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 10;
my $array_sql = join(",", ('random()') x $dim);
sub test_recall
{
my ($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;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v halfvec($dim));");
# Generate queries
for (1 .. 20)
{
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
push(@queries, "[" . join(",", @r) . "]");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("halfvec_l2_ops", "halfvec_ip_ops", "halfvec_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",
{
"024_hnsw_halfvec_insert_recall_$opclass" => "INSERT INTO tst (v) VALUES (ARRAY[$array_sql]);"
}
);
# 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
my $min = $operator eq "<#>" ? 0.94 : 0.98;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
$node->safe_psql("postgres", "TRUNCATE tst;");
}
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 @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 sparsevec(3));");
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "{1:$r1,2:$r2,3:$r3}/3");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("sparsevec_l2_ops", "sparsevec_ip_ops", "sparsevec_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",
{
"025_hnsw_sparsevec_insert_recall_$opclass" => "INSERT INTO tst (v) VALUES (ARRAY[random(), random(), random()]::vector::sparsevec);"
}
);
# 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
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();

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@@ -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 bit(3));");
sub insert_vectors
{
for my $i (1 .. 20)
{
$node->safe_psql("postgres", "INSERT INTO tst VALUES ('111');");
}
}
sub test_duplicates
{
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 1;
SELECT COUNT(*) FROM (SELECT * FROM tst ORDER BY v <~> '111') t;
));
is($res, 10);
}
# Test duplicates with build
insert_vectors();
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v bit_hamming_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",
{
"026_hnsw_bit_duplicates" => "INSERT INTO tst VALUES ('111');"
}
);
done_testing();

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@@ -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 halfvec(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 halfvec_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",
{
"027_hnsw_halfvec_duplicates" => "INSERT INTO tst VALUES ('[1,1,1]');"
}
);
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 sparsevec(3));");
sub insert_vectors
{
for my $i (1 .. 20)
{
$node->safe_psql("postgres", "INSERT INTO tst VALUES ('{1:1,2:1,3:1}/3');");
}
}
sub test_duplicates
{
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 1;
SELECT COUNT(*) FROM (SELECT * FROM tst ORDER BY v <-> '{1:1,2:1,3:1}/3') t;
));
is($res, 10);
}
# Test duplicates with build
insert_vectors();
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v sparsevec_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",
{
"028_hnsw_sparsevec_duplicates" => "INSERT INTO tst VALUES ('{1:1,2:1,3:1}/3');"
}
);
done_testing();

View File

@@ -0,0 +1,100 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 52;
my $max = 2**$dim;
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 @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($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;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v bit($dim));");
$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, (random() * $max)::bigint::bit($dim) FROM generate_series(1, 10000) i;"
);
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v bit_hamming_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 $r = int(rand() * $max);
push(@queries, "${r}::bigint::bit($dim)");
}
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
WITH top AS (
SELECT v <~> $_ AS distance FROM tst ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v <~> $_) <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
test_recall(0.35, 100, "before vacuum");
# TODO Test concurrent inserts with vacuum
$node->safe_psql("postgres", "VACUUM tst;");
test_recall(0.80, 100, "after vacuum");
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 halfvec(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 halfvec_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(0.18, $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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