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161 Commits

Author SHA1 Message Date
Andrew Kane
67c72ac8c3 Added support for async I/O [skip ci] 2025-11-18 22:44:20 -08:00
Andrew Kane
a126c02184 Added link to pgvector-ada [skip ci] 2025-10-30 22:29:36 -07:00
Andrew Kane
744362305b Updated changelog [skip ci] 2025-10-30 11:48:44 -07:00
Andrew Kane
69e78e36a3 Added link to pgvetor-pascal [skip ci] 2025-10-30 11:40:29 -07:00
Andrew Kane
8dd37d4fb2 Improved install target for Windows - #917 [skip ci] 2025-10-30 11:03:59 -07:00
Andrew Kane
a24125839a Updated readme [skip ci] 2025-10-28 10:25:34 -07:00
Andrew Kane
2ee3113417 Updated readme [skip ci] 2025-10-22 13:10:58 -07:00
Andrew Kane
3ebb9a506e Added varatt headers for Postgres 16+ 2025-10-22 11:56:05 -07:00
Andrew Kane
727d4836d2 Fixed Index Searches in EXPLAIN output for Postgres 18 2025-10-22 11:47:11 -07:00
Andrew Kane
d823c44591 Removed unused parameter [skip ci] 2025-09-27 15:58:18 -07:00
Andrew Kane
8f4aa0751c Removed unused parameters [skip ci] 2025-09-27 15:51:32 -07:00
Andrew Kane
1ff30720c7 Updated readme [skip ci] 2025-09-26 13:02:37 -07:00
Andrew Kane
4cef9213ec Added Docker images for Postgres 18 [skip ci] 2025-09-25 20:00:10 -07:00
Andrew Kane
90add68d6f Updated style to be consistent with Mac [skip ci] 2025-09-25 15:55:30 -07:00
Andrew Kane
bc05dbf312 Updated CI for Postgres 18 [skip ci] 2025-09-25 15:54:37 -07:00
Andrew Kane
02fefc0e3f Updated readme for Postgres 18 [skip ci] 2025-09-25 15:46:28 -07:00
Andrew Kane
e7899b1250 Updated checkout action [skip ci] 2025-09-22 11:55:01 -07:00
Andrew Kane
9e29dff78c Updated CI [skip ci] 2025-09-19 19:16:08 -07:00
Andrew Kane
13c0dbf530 Test with macos-15-intel on CI [skip ci] 2025-09-19 18:34:51 -07:00
Andrew Kane
c205a12107 Updated CI [skip ci] 2025-09-05 17:03:37 -07:00
Andrew Kane
db3755a58f Added windows-2025 to CI [skip ci] 2025-09-05 16:41:22 -07:00
Andrew Kane
778dacf20c Version bump to 0.8.1 [skip ci] 2025-09-04 17:51:09 -07:00
Andrew Kane
3f687687ee Fixed compilation error with Postgres 19 2025-09-04 15:58:23 -07:00
Andrew Kane
815f48e489 Updated changelog [skip ci] 2025-09-04 15:36:18 -07:00
Andrew Kane
67e648b13e Added another test for binary_quantize function [skip ci] 2025-08-29 01:09:18 -07:00
Andrew Kane
c3ff955231 Reordered supported Docker tags [skip ci] 2025-08-23 19:57:14 -07:00
Andrew Kane
6f46a1035d Added new Docker images to readme [skip ci] 2025-08-23 19:46:07 -07:00
Andrew Kane
bbe66e821b Added Docker images for Debian 13 / Trixie [skip ci] 2025-08-23 19:34:11 -07:00
Julien Rouhaud
dd3a1e9137 Use NIL for empty lists (#890)
Postgres standard way to check for list emptiness is to compare a pointer to
NIL rather than NULL.
2025-08-23 03:31:22 -07:00
Andrew Kane
ea4746f6c0 Updated comment [skip ci] 2025-08-19 14:26:36 -07:00
Andrew Kane
6aec80ccdb Improved performance of binary_quantize function for halfvec 2025-08-19 13:47:11 -07:00
Luca Giacchino
0c9070ba82 Add autovectorized implementation of binary quantize 2025-08-19 13:18:50 -07:00
Andrew Kane
30382418da Ran pgindent [skip ci] 2025-08-19 12:44:54 -07:00
Andrew Kane
26b50e536f Updated FreeBSD package name in readme [skip ci] 2025-08-09 12:09:29 -07:00
Andrew Kane
e29fc3aa1a Switched to PG_MODULE_MAGIC_EXT for Postgres 18+ [skip ci] 2025-07-31 19:59:27 -07:00
Andrew Kane
6ef7fccb5c Added Postgres 19 to CI [skip ci] 2025-07-27 19:50:46 -07:00
Andrew Kane
5b8b68ba1d Use consistent style [skip ci] 2025-07-27 18:19:28 -07:00
Andrew Kane
3be8693c13 Added supported Docker tags to readme [skip ci] 2025-07-27 13:44:59 -07:00
Andrew Kane
247c8dc8a5 Updated changelog [skip ci] 2025-07-27 13:25:51 -07:00
Andrew Kane
3600ab93e5 Added Docker images with -bookworm suffix [skip ci] 2025-07-27 13:14:29 -07:00
Andrew Kane
665db75a3c Updated Dockerfile to use release [skip ci] 2025-07-27 12:34:23 -07:00
Andrew Kane
44163d0a97 Revert "Added OS to Dockerfile [skip ci]"
This reverts commit 33ca8a61e2.
2025-07-09 22:01:34 -07:00
Andrew Kane
33ca8a61e2 Added OS to Dockerfile [skip ci] 2025-07-09 16:25:05 -07:00
Andrew Kane
742e2d1d28 Synced .dockerignore with .gitignore [skip ci] 2025-07-09 16:22:43 -07:00
Andrew Kane
a7c49d8283 Updated readme [skip ci] 2025-07-01 11:13:29 -07:00
Andrew Kane
ae9ee81e4d Fixed relaxed results example for Postgres 17 - #862 [skip ci] 2025-07-01 10:11:50 -07:00
Andrew Kane
fa1dee4e3b Updated link [skip ci] 2025-07-01 03:35:26 -07:00
Andrew Kane
e6bad96a03 Ran pgindent [skip ci] 2025-06-18 20:07:46 -07:00
Jon Daniel
3a49d141b3 Vectorizing vector_concat for improved performance (#861)
* Vectorizing vector_concat for improved performance

On an ARM chip this should generate SIMD instructions to copy the two
incoming vectors to the new vector as opposed to doing it all in
software.

* Moving declarations to above CheckDim

* Removing const from dims

* Formatting
2025-06-18 20:06:32 -07:00
Andrew Kane
ce09c9a27a Improved variable names [skip ci] 2025-06-18 17:32:37 -07:00
Andrew Kane
870ca6724d Fixed CI [skip ci] 2025-06-18 16:26:30 -07:00
Andrew Kane
8ad680f009 Ran pgindent [skip ci] 2025-06-18 16:11:15 -07:00
Jon Daniel
fe697e8788 vectorize: optimize VectorSumCenter and HalfvecSumCenter (#860)
* vectorize: optimize VectorSumCenter and HalfvecSumCenter

The functions VectorSumCenter and HalfvecSumCenter were not being
vectorized by the compiler. A few slight changes will allow these
optimizations to take place and get a performance boost by utilizing
SIMD instructions.

This optimization helps improve performance of vector operations in IVF
index building and updating.

* Removing const, commenting that it is only vectoirzed on ARM
2025-06-18 16:09:43 -07:00
Andrew Kane
bf28ed8176 Set random seed for IVFFLAT_BENCH [skip ci] 2025-06-18 10:57:18 -07:00
Andrew Kane
799cfebf70 Updated readme [skip ci] 2025-06-04 14:29:53 -07:00
Andrew Kane
3cd1f09f66 Updated Windows installation instructions - #593 [skip ci] 2025-06-04 14:18:53 -07:00
Andrew Kane
e2efe62fe5 Updated readme [skip ci] 2025-05-12 13:11:43 -07:00
Andrew Kane
7b58352336 Updated readme [skip ci] 2025-05-06 21:39:51 -07:00
Andrew Kane
83d410eae9 Updated readme [skip ci] 2025-04-13 13:07:31 -07:00
Andrew Kane
ebbfe8dba0 Fixed CI for Postgres 18 [skip ci] 2025-04-05 13:05:27 -07:00
Andrew Kane
e575866297 Revert "Fixed warnings with Postgres 18 [skip ci]"
This reverts commit 32e95a8598.
2025-04-05 12:56:00 -07:00
Andrew Kane
35f4f7fc80 Improved warning check [skip ci] 2025-04-05 12:38:30 -07:00
Andrew Kane
32e95a8598 Fixed warnings with Postgres 18 [skip ci] 2025-04-05 12:13:38 -07:00
Andrew Kane
a03dc5b7d0 Added fields to IndexAmRoutine for Postgres 18 [skip ci] 2025-04-05 11:31:57 -07:00
Andrew Kane
d365aac370 Added note about index options to index build time docs - #807 [skip ci] 2025-03-26 11:56:38 -07:00
Andrew Kane
05182479a2 Added ARM to CI [skip ci] 2025-03-24 19:26:52 -07:00
Andrew Kane
cc0958dec5 Removed deprecated runner image [skip ci] 2025-03-24 19:18:01 -07:00
Andrew Kane
4af2b06dc5 Improved installation note [skip ci] 2025-03-23 14:59:28 -07:00
Andrew Kane
880dc4d6b9 Added Windows installation note about mismatched architecture - #593 #797 #804 [skip ci] 2025-03-23 11:51:10 -07:00
Andrew Kane
fef635c9e5 Updated readme [skip ci] 2025-02-20 00:05:35 -08:00
Andrew Kane
78ed8f1157 Fixed compilation error with Postgres 18 - fixes #779 2025-02-17 16:38:14 -08:00
Andrew Kane
f11e4d7b20 Updated readme [skip ci] 2025-02-17 13:22:50 -08:00
Andrew Kane
aafdf4167d Improved missing SDK docs [skip ci] 2025-02-17 13:16:31 -08:00
Andrew Kane
656b059258 Added tests for iterative index scan with empty index - resolves #679 [skip ci] 2025-02-13 16:28:14 -08:00
Andrew Kane
7cf9980696 Updated Windows installation notes for Postgres 17.3 - closes #669 [skip ci] 2025-02-13 10:04:22 -08:00
Andrew Kane
2fe560dc58 Fixed extra-semi warnings [skip ci] 2025-01-18 13:08:11 -08:00
Andrew Kane
b46beada1a Restored assertion checking on CI for Postgres 18 [skip ci] 2025-01-15 19:24:24 -08:00
Andrew Kane
0a42bc7aa5 Fixed undefined symbol: verify_compact_attribute error with Postgres 18 on CI 2025-01-10 13:54:18 -08:00
Andrew Kane
f5df32c41d Updated license year [skip ci] 2025-01-10 08:51:07 -08:00
Andrew Kane
2c53c30415 Fixed compilation error with Postgres 18 2025-01-10 08:50:51 -08:00
Rui Chen
b4bc010459 chore(ci): update to use pg 17 (#755)
* chore(ci): update to use pg 17

Signed-off-by: Rui Chen <rui@chenrui.dev>

* chore(ci): update pg 14 to `REL_14_15`

Signed-off-by: Rui Chen <rui@chenrui.dev>

---------

Signed-off-by: Rui Chen <rui@chenrui.dev>
2025-01-10 08:39:32 -08:00
Andrew Kane
7b4ff9b59f Updated CI to support macos-15 [skip ci] 2025-01-10 08:37:52 -08:00
Andrew Kane
cfdcbd75d1 Updated FreeBSD docs [skip ci] 2024-12-09 08:11:11 -08:00
Andrew Kane
5136983f35 Added link to pgvector-fortran [skip ci] 2024-12-06 09:39:02 -08:00
Andrew Kane
4ab4b89980 Added link to pgvector-erlang [skip ci] 2024-12-06 06:16:34 -08:00
Andrew Kane
85f0e3ccf6 Added link to pgvector-gleam [skip ci] 2024-12-05 19:29:57 -08:00
Andrew Kane
28e797cb5a Added link to pgvector-d [skip ci] 2024-12-05 16:56:21 -08:00
Andrew Kane
1263d753be Added link to pgvector-raku [skip ci] 2024-12-05 07:13:39 -08:00
Andrew Kane
5bc7937715 Added iterative index scans to troubleshooting docs [skip ci] 2024-11-22 15:22:06 -08:00
Andrew Kane
e7e899e9af Updated readme [skip ci] 2024-11-22 11:55:46 -08:00
Andrew Kane
2627c5ff77 Version bump to 0.8.0 [skip ci] 2024-10-30 13:06:34 -07:00
Andrew Kane
34b3cfdc43 Updated min Postgres version in META.json [skip ci] 2024-10-30 13:06:12 -07:00
Andrew Kane
cd218aae5a Removed unneeded code 2024-10-30 13:05:10 -07:00
Andrew Kane
ba9367f86c Updated readme [skip ci] 2024-10-30 12:58:00 -07:00
Andrew Kane
9c20550a41 Updated readme 2024-10-30 12:54:42 -07:00
Andrew Kane
e3e74fe94e Updated readme [skip ci] 2024-10-29 00:04:35 -07:00
Andrew Kane
96a5a44632 Updated readme [skip ci] 2024-10-28 23:52:16 -07:00
Andrew Kane
67e1392a83 Updated readme [skip ci] 2024-10-28 22:58:56 -07:00
Andrew Kane
e530a1a026 Updated readme [skip ci] 2024-10-28 22:49:41 -07:00
Andrew Kane
6170e2645b Updated readme [skip ci] 2024-10-28 22:44:44 -07:00
Andrew Kane
e6bae175f1 Updated readme [skip ci] 2024-10-28 22:26:50 -07:00
Andrew Kane
52b777e04a Updated readme [skip ci] 2024-10-28 22:01:27 -07:00
Andrew Kane
307271214f Updated readme [skip ci] 2024-10-28 21:42:05 -07:00
Andrew Kane
6e9f74ddce Updated readme [skip ci] 2024-10-28 20:04:09 -07:00
Andrew Kane
258215ad97 Improved test [skip ci] 2024-10-28 15:54:39 -07:00
Andrew Kane
fb87b6da91 Fixed test 2024-10-28 13:55:26 -07:00
Andrew Kane
a2a0b377f0 Removed memory limit debug message from HNSW index scans (EXPLAIN ANALYZE can be used instead) 2024-10-28 13:46:49 -07:00
Andrew Kane
2f770307b8 Removed unused variable [skip ci] 2024-10-28 13:38:42 -07:00
Andrew Kane
c04e16ff5b Removed debug message from IVFFlat index scans [skip ci] 2024-10-28 13:36:57 -07:00
Andrew Kane
bd4d272f26 Updated changelog [skip ci] 2024-10-28 13:05:27 -07:00
Andrew Kane
8bb797cc2f Updated changelog [skip ci] 2024-10-28 13:00:55 -07:00
Andrew Kane
fe6ec03dac Improved filtering section [skip ci] 2024-10-28 12:08:27 -07:00
Andrew Kane
c1161f8889 Updated readme [skip ci] 2024-10-28 02:08:53 -07:00
Andrew Kane
c530a3c490 Updated comment [skip ci] 2024-10-28 00:56:10 -07:00
Andrew Kane
d8b9e8ef73 Updated readme [skip ci] 2024-10-28 00:55:25 -07:00
Andrew Kane
00894efed5 Updated readme [skip ci] 2024-10-28 00:45:26 -07:00
Andrew Kane
0aa0f6619b Updated readme [skip ci] 2024-10-28 00:43:39 -07:00
Andrew Kane
38d053001e Updated readme [skip ci] 2024-10-28 00:32:12 -07:00
Andrew Kane
ccb95407e7 Updated readme [skip ci] 2024-10-28 00:09:26 -07:00
Andrew Kane
04d5e934a1 Scan 2000 more tuples with default work_mem 2024-10-27 22:23:28 -07:00
Andrew Kane
b163b5b196 Moved code [skip ci] 2024-10-27 22:21:43 -07:00
Andrew Kane
6a30c1e824 Fixed test [skip ci] 2024-10-27 21:10:51 -07:00
Andrew Kane
2db1b19644 Use greater than [skip ci] 2024-10-27 21:07:22 -07:00
Andrew Kane
305d62146e Updated comment [skip ci] 2024-10-27 21:05:32 -07:00
Andrew Kane
f9d627c9a9 Updated default value of hnsw.scan_mem_multiplier [skip ci] 2024-10-27 21:05:04 -07:00
Andrew Kane
38f42820be Added test for hnsw.scan_mem_multiplier [skip ci] 2024-10-27 20:05:58 -07:00
Andrew Kane
15c8245b42 Updated readme [skip ci] 2024-10-27 19:30:40 -07:00
Andrew Kane
572a9ab404 Updated readme [skip ci] 2024-10-27 18:58:50 -07:00
Andrew Kane
00492d7e57 Ensure max memory fits into Size for HNSW index scans 2024-10-27 14:21:15 -07:00
Andrew Kane
857d716d9e Renamed iterative_search to iterative_scan 2024-10-27 14:02:22 -07:00
Andrew Kane
c5dd2af750 Added comments [skip ci] 2024-10-25 21:39:03 -07:00
Andrew Kane
78b877bdaf Revert "Renamed iterative_search to iterative_scan"
This reverts commit 7043cce893.
2024-10-24 20:32:07 -07:00
Andrew Kane
7043cce893 Renamed iterative_search to iterative_scan 2024-10-24 20:31:43 -07:00
Andrew Kane
62039d74f6 Added iterative search section to readme [skip ci] 2024-10-24 18:05:29 -07:00
Andrew Kane
ac6576e53a Added hnsw.search_mem_multiplier option 2024-10-24 18:02:20 -07:00
Andrew Kane
67eff41c44 Updated changelog [skip ci] 2024-10-23 15:12:40 -07:00
Andrew Kane
1291b12090 Added Postgres 18 to CI [skip ci] 2024-10-22 00:38:19 -07:00
Andrew Kane
24522700b8 Improved hnswrescan 2024-10-21 23:41:32 -07:00
Andrew Kane
bfb3a45b31 Use consistent order [skip ci] 2024-10-21 21:47:03 -07:00
Andrew Kane
e718eb8da4 Updated range and defaults for iterative search parameters 2024-10-21 20:38:50 -07:00
Andrew Kane
049972a4a3 Improved test output [skip ci] 2024-10-13 17:22:49 -07:00
Andrew Kane
61027645e9 Improved test output [skip ci] 2024-10-13 17:21:38 -07:00
Andrew Kane
a41b327b33 Speed up test [skip ci] 2024-10-13 17:12:12 -07:00
Andrew Kane
7f735ebd9b Added test for strict order [skip ci] 2024-10-13 17:04:03 -07:00
Andrew Kane
02b01e1ca9 Show tuples with memory usage [skip ci] 2024-10-12 22:05:13 -07:00
Andrew Kane
388e42f6e6 Fixed flaky test [skip ci] 2024-10-11 15:48:19 -07:00
Andrew Kane
bf379eed86 Use a memory context for IVFFlat index scans 2024-10-11 15:46:38 -07:00
Andrew Kane
e1bc929429 Simplify lists for IvfflatScanOpaque [skip ci] 2024-10-11 15:29:23 -07:00
Andrew Kane
38285aacc7 Revert "Updated IVFFlat to support multiple attributes (not enabled yet)"
This reverts commit 772ab69de6.
2024-10-11 15:01:54 -07:00
Andrew Kane
a2408e60fa Revert "Added IndexTuple to HNSW elements (first step to support multiple attributes)"
This reverts commit 53a8734bac.
2024-10-11 14:57:57 -07:00
Andrew Kane
53a8734bac Added IndexTuple to HNSW elements (first step to support multiple attributes) 2024-10-11 14:12:01 -07:00
Andrew Kane
7484625227 Added comments [skip ci] 2024-10-11 11:59:36 -07:00
Andrew Kane
d1ebb8db73 Use -1 for no limit for ivfflat.max_probes [skip ci] 2024-10-11 11:43:32 -07:00
Andrew Kane
42af8aa1d1 Updated GUC descriptions [skip ci] 2024-10-11 11:26:27 -07:00
Andrew Kane
9d15a76b60 Improved enum naming [skip ci] 2024-10-11 11:20:36 -07:00
Andrew Kane
a3a20f9816 Simplified GUC names [skip ci] 2024-10-11 11:18:01 -07:00
Andrew Kane
b26a21b848 Added regression tests for iterative search [skip ci] 2024-10-11 11:07:11 -07:00
Andrew Kane
2dc392ed6c Updated GUC names [skip ci] 2024-10-10 23:50:11 -07:00
Andrew Kane
960d2848cb Updated comment [skip ci] 2024-10-10 21:02:33 -07:00
Andrew Kane
8e88b481a6 Use a lower max allocation size than default to allow scanning more tuples for iterative search before exceeding work_mem [skip ci] 2024-10-10 20:57:57 -07:00
Andrew Kane
124018b8dd Added HnswInitSearchCandidate function 2024-10-10 19:30:47 -07:00
44 changed files with 1005 additions and 924 deletions

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@@ -1,8 +0,0 @@
/.git/
/dist/
/results/
/tmp_check/
/sql/vector--?.?.?.sql
regression.*
*.o
*.so

View File

@@ -8,27 +8,29 @@ jobs:
fail-fast: false
matrix:
include:
# - postgres: 18
# os: ubuntu-24.04
- postgres: 19
os: ubuntu-24.04
- postgres: 18
os: ubuntu-24.04
- postgres: 17
os: ubuntu-24.04
- postgres: 16
os: ubuntu-22.04
os: ubuntu-24.04-arm
- postgres: 15
os: ubuntu-22.04
- postgres: 14
os: ubuntu-20.04
os: ubuntu-22.04-arm
- postgres: 13
os: ubuntu-20.04
os: ubuntu-22.04
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
dev-files: true
- run: make
env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare ${{ matrix.postgres >= 18 && '-Wno-missing-field-initializers' || '' }}
- run: |
export PG_CONFIG=`which pg_config`
sudo --preserve-env=PG_CONFIG make install
@@ -46,18 +48,18 @@ jobs:
fail-fast: false
matrix:
include:
- postgres: 16
os: macos-14
- postgres: 18
os: macos-26
- postgres: 14
os: macos-13
os: macos-15-intel
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
- run: make
env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-unknown-warning-option ${{ matrix.postgres >= 18 && '-Wno-missing-field-initializers' || '' }}
- run: make install
- run: make installcheck
- if: ${{ failure() }}
@@ -70,26 +72,35 @@ jobs:
tar xf $TAG.tar.gz
mv postgres-$TAG postgres
env:
TAG: ${{ matrix.postgres == 16 && 'REL_16_2' || 'REL_14_11' }}
TAG: ${{ matrix.postgres == 18 && 'REL_18_0' || 'REL_14_19' }}
- 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
- run: make clean && $(brew --prefix llvm@$LLVM_VERSION)/bin/scan-build --status-bugs make
env:
LLVM_VERSION: ${{ matrix.os == 'macos-26' && 20 || 18 }}
PG_CFLAGS: -DUSE_ASSERT_CHECKING
windows:
runs-on: windows-latest
runs-on: ${{ matrix.os }}
if: ${{ !startsWith(github.ref_name, 'mac') }}
strategy:
fail-fast: false
matrix:
include:
- postgres: 17
os: windows-2025
- postgres: 14
os: windows-2022
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14
postgres-version: ${{ matrix.postgres }}
- run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
nmake /NOLOGO /F Makefile.win && ^
nmake /NOLOGO /F Makefile.win install && ^
nmake /NOLOGO /F Makefile.win installcheck && ^
nmake /NOLOGO /F Makefile.win installcheck ${{ matrix.postgres != 17 && 'PG_REGRESS=$(PGROOT)\bin\pg_regress' || '' }} && ^
nmake /NOLOGO /F Makefile.win clean && ^
nmake /NOLOGO /F Makefile.win uninstall
shell: cmd
@@ -122,10 +133,10 @@ jobs:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: actions/checkout@v5
- uses: ankane/setup-postgres-valgrind@v1
with:
postgres-version: 16
postgres-version: 18
check-ub: yes
- run: make OPTFLAGS=""
- run: sudo --preserve-env=PG_CONFIG make install

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@@ -1,11 +1,20 @@
## 0.8.0 (unreleased)
## 0.8.2 (unreleased)
- Improved `install` target on Windows
- Fixed `Index Searches` in `EXPLAIN` output for Postgres 18
## 0.8.1 (2025-09-04)
- Added support for Postgres 18 rc1
- Improved performance of `binary_quantize` function
## 0.8.0 (2024-10-30)
- Added support for inline filtering with HNSW
- Added support for iterative index scans
- Added casts for arrays to `sparsevec`
- Improved cost estimation
- Improved cost estimation for better index selection when filtering
- Improved performance of HNSW index scans
- Improved performance of HNSW inserts and on-disk index builds
- Reduced memory usage for HNSW index scans
- Dropped support for Postgres 12
## 0.7.4 (2024-08-05)

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@@ -1,8 +1,11 @@
# syntax=docker/dockerfile:1
ARG PG_MAJOR=17
FROM postgres:$PG_MAJOR
ARG DEBIAN_CODENAME=bookworm
FROM postgres:$PG_MAJOR-$DEBIAN_CODENAME
ARG PG_MAJOR
COPY . /tmp/pgvector
ADD https://github.com/pgvector/pgvector.git#v0.8.1 /tmp/pgvector
RUN apt-get update && \
apt-mark hold locales && \

View File

@@ -1,4 +1,4 @@
Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
Portions Copyright (c) 1996-2025, 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": "0.7.4",
"version": "0.8.1",
"maintainer": [
"Andrew Kane <andrew@ankane.org>"
],
@@ -12,7 +12,7 @@
"prereqs": {
"runtime": {
"requires": {
"PostgreSQL": "12.0.0"
"PostgreSQL": "13.0.0"
}
}
},
@@ -20,7 +20,7 @@
"vector": {
"file": "sql/vector.sql",
"docfile": "README.md",
"version": "0.7.4",
"version": "0.8.1",
"abstract": "Open-source vector similarity search for Postgres"
}
},

View File

@@ -1,5 +1,5 @@
EXTENSION = vector
EXTVERSION = 0.7.4
EXTVERSION = 0.8.1
MODULE_big = vector
DATA = $(wildcard sql/*--*--*.sql)
@@ -76,4 +76,9 @@ docker:
.PHONY: docker-release
docker-release:
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) --build-arg DEBIAN_CODENAME=bookworm -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR)-bookworm -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR)-bookworm .
.PHONY: docker-release-trixie
docker-release-trixie:
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) --build-arg DEBIAN_CODENAME=trixie -t pgvector/pgvector:pg$(PG_MAJOR)-trixie -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR)-trixie .

View File

@@ -1,5 +1,5 @@
EXTENSION = vector
EXTVERSION = 0.7.4
EXTVERSION = 0.8.1
DATA_built = sql\$(EXTENSION)--$(EXTVERSION).sql
OBJS = src\bitutils.obj src\bitvec.obj src\halfutils.obj src\halfvec.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\sparsevec.obj src\vector.obj
@@ -31,6 +31,9 @@ LIBDIR = $(PGROOT)\lib
PKGLIBDIR = $(PGROOT)\lib
SHAREDIR = $(PGROOT)\share
# Use $(PGROOT)\bin\pg_regress for Postgres < 17
PG_REGRESS = $(LIBDIR)\pgxs\src\test\regress\pg_regress
CFLAGS = /nologo /I"$(INCLUDEDIR_SERVER)\port\win32_msvc" /I"$(INCLUDEDIR_SERVER)\port\win32" /I"$(INCLUDEDIR_SERVER)" /I"$(INCLUDEDIR)"
CFLAGS = $(CFLAGS) $(PG_CFLAGS)
@@ -54,11 +57,11 @@ install: all
copy $(SHLIB) "$(PKGLIBDIR)"
copy $(EXTENSION).control "$(SHAREDIR)\extension"
copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
mkdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
if not exist "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)" mkdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
for %f in ($(HEADERS)) do copy %f "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
installcheck:
"$(BINDIR)\pg_regress" --bindir="$(BINDIR)" $(REGRESS_OPTS) $(REGRESS)
"$(PG_REGRESS)" --bindir="$(BINDIR)" $(REGRESS_OPTS) $(REGRESS)
uninstall:
del /f "$(PKGLIBDIR)\$(SHLIB)"

303
README.md
View File

@@ -17,11 +17,11 @@ Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recove
### Linux and Mac
Compile and install the extension (supports Postgres 12+)
Compile and install the extension (supports Postgres 13+)
```sh
cd /tmp
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
git clone --branch v0.8.1 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo
@@ -33,27 +33,17 @@ You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#p
### Windows
Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/build/building-on-the-command-line?view=msvc-170#download-and-install-the-tools) is installed, and run:
Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/build/building-on-the-command-line?view=msvc-170#download-and-install-the-tools) is installed and run `x64 Native Tools Command Prompt for VS [version]` as administrator. Then use `nmake` to build:
```cmd
call "C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvars64.bat"
```
Note: The exact path will vary depending on your Visual Studio version and edition
Then use `nmake` to build:
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16"
set "PGROOT=C:\Program Files\PostgreSQL\18"
cd %TEMP%
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
git clone --branch v0.8.1 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
```
Note: Postgres 17 is not supported yet due to an upstream issue
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).
@@ -84,7 +74,7 @@ Get the nearest neighbors by L2 distance
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`, added in 0.7.0)
Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`)
Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators
@@ -148,9 +138,9 @@ Supported distance functions are:
- `<->` - L2 distance
- `<#>` - (negative) inner product
- `<=>` - cosine distance
- `<+>` - L1 distance (added in 0.7.0)
- `<~>` - Hamming distance (binary vectors, added in 0.7.0)
- `<%>` - Jaccard distance (binary vectors, added in 0.7.0)
- `<+>` - L1 distance
- `<~>` - Hamming distance (binary vectors)
- `<%>` - Jaccard distance (binary vectors)
Get the nearest neighbors to a row
@@ -237,19 +227,19 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
```
L1 distance - added in 0.7.0
L1 distance
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l1_ops);
```
Hamming distance - added in 0.7.0
Hamming distance
```sql
CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
```
Jaccard distance - added in 0.7.0
Jaccard distance
```sql
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
@@ -258,9 +248,9 @@ CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
- `sparsevec` - up to 1,000 non-zero elements (added in 0.7.0)
- `halfvec` - up to 4,000 dimensions
- `bit` - up to 64,000 dimensions
- `sparsevec` - up to 1,000 non-zero elements
### Index Options
@@ -314,17 +304,19 @@ Note: Do not set `maintenance_work_mem` so high that it exhausts the memory on t
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)
You can also speed up index creation by increasing the number of parallel workers (2 by default)
```sql
SET max_parallel_maintenance_workers = 7; -- plus leader
```
For a large number of workers, you may also need to increase `max_parallel_workers` (8 by default)
For a large number of workers, you may need to increase `max_parallel_workers` (8 by default)
The [index options](#index-options) also have a significant impact on build time (use the defaults unless seeing low recall)
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
```sql
SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
@@ -367,7 +359,7 @@ Cosine distance
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
```
Hamming distance - added in 0.7.0
Hamming distance
```sql
CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100);
@@ -376,8 +368,8 @@ CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 10
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
- `halfvec` - up to 4,000 dimensions
- `bit` - up to 64,000 dimensions
### Query Options
@@ -410,7 +402,7 @@ For a large number of workers, you may also need to increase `max_parallel_worke
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
```sql
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
@@ -427,39 +419,127 @@ Note: `%` is only populated during the `loading tuples` phase
## Filtering
There are a few ways to index nearest neighbor queries with a `WHERE` clause
There are a few ways to index nearest neighbor queries with a `WHERE` clause.
```sql
SELECT * FROM items WHERE category_id = 123 ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
Create an index on one [or more](https://www.postgresql.org/docs/current/indexes-multicolumn.html) of the `WHERE` columns for exact search
A good place to start is creating an index on the filter column. This can provide fast, exact nearest neighbor search in many cases. Postgres has a number of [index types](https://www.postgresql.org/docs/current/indexes-types.html) for this: B-tree (default), hash, GiST, SP-GiST, GIN, and BRIN.
```sql
CREATE INDEX ON items (category_id);
```
Or a composite HNSW index for approximate search (added in 0.8.0)
For multiple columns, consider a [multicolumn index](https://www.postgresql.org/docs/current/indexes-multicolumn.html).
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops, category_id);
CREATE INDEX ON items (location_id, category_id);
```
Or a [partial index](https://www.postgresql.org/docs/current/indexes-partial.html) on the vector column for approximate search
Exact indexes work well for conditions that match a low percentage of rows. Otherwise, [approximate indexes](#indexing) can work better.
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops);
```
With approximate indexes, filtering is applied *after* the index is scanned. If a condition matches 10% of rows, with HNSW and the default `hnsw.ef_search` of 40, only 4 rows will match on average. For more rows, increase `hnsw.ef_search`.
```sql
SET hnsw.ef_search = 200;
```
Starting with 0.8.0, you can enable [iterative index scans](#iterative-index-scans), which will automatically scan more of the index when needed.
```sql
SET hnsw.iterative_scan = strict_order;
```
If filtering by only a few distinct values, consider [partial indexing](https://www.postgresql.org/docs/current/indexes-partial.html).
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops) WHERE (category_id = 123);
```
Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html) for approximate search on many different values of the `WHERE` columns
If filtering by many different values, consider [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html).
```sql
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
```
## Half-Precision Vectors
## Iterative Index Scans
*Added in 0.7.0*
With approximate indexes, queries with filtering can return less results since filtering is applied *after* the index is scanned. Starting with 0.8.0, you can enable iterative index scans, which will automatically scan more of the index until enough results are found (or it reaches `hnsw.max_scan_tuples` or `ivfflat.max_probes`).
Iterative scans can use strict or relaxed ordering.
Strict ensures results are in the exact order by distance
```sql
SET hnsw.iterative_scan = strict_order;
```
Relaxed allows results to be slightly out of order by distance, but provides better recall
```sql
SET hnsw.iterative_scan = relaxed_order;
# or
SET ivfflat.iterative_scan = relaxed_order;
```
With relaxed ordering, you can use a [materialized CTE](https://www.postgresql.org/docs/current/queries-with.html#QUERIES-WITH-CTE-MATERIALIZATION) to get strict ordering
```sql
WITH relaxed_results AS MATERIALIZED (
SELECT id, embedding <-> '[1,2,3]' AS distance FROM items WHERE category_id = 123 ORDER BY distance LIMIT 5
) SELECT * FROM relaxed_results ORDER BY distance + 0;
```
Note: `+ 0` is needed for Postgres 17+
For queries that filter by distance, use a materialized CTE and place the distance filter outside of it for best performance (due to the [current behavior](https://www.postgresql.org/message-id/flat/CAOdR5yGUoMQ6j7M5hNUXrySzaqZVGf_Ne%2B8fwZMRKTFxU1nbJg%40mail.gmail.com) of the Postgres executor)
```sql
WITH nearest_results AS MATERIALIZED (
SELECT id, embedding <-> '[1,2,3]' AS distance FROM items ORDER BY distance LIMIT 5
) SELECT * FROM nearest_results WHERE distance < 5 ORDER BY distance;
```
Note: Place any other filters inside the CTE
### Iterative Scan Options
Since scanning a large portion of an approximate index is expensive, there are options to control when a scan ends.
#### HNSW
Specify the max number of tuples to visit (20,000 by default)
```sql
SET hnsw.max_scan_tuples = 20000;
```
Note: This is approximate and does not affect the initial scan
Specify the max amount of memory to use, as a multiple of `work_mem` (1 by default)
```sql
SET hnsw.scan_mem_multiplier = 2;
```
Note: Try increasing this if increasing `hnsw.max_scan_tuples` does not improve recall
#### IVFFlat
Specify the max number of probes
```sql
SET ivfflat.max_probes = 100;
```
Note: If this is lower than `ivfflat.probes`, `ivfflat.probes` will be used
## Half-Precision Vectors
Use the `halfvec` type to store half-precision vectors
@@ -469,8 +549,6 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));
## Half-Precision Indexing
*Added in 0.7.0*
Index vectors at half precision for smaller indexes
```sql
@@ -492,24 +570,16 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES ('000'), ('111');
```
Get the nearest neighbors by Hamming distance (added in 0.7.0)
Get the nearest neighbors by Hamming distance
```sql
SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
```
Or (before 0.7.0)
```sql
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Also supports Jaccard distance (`<%>`)
## Binary Quantization
*Added in 0.7.0*
Use expression indexing for binary quantization
```sql
@@ -532,8 +602,6 @@ SELECT * FROM (
## Sparse Vectors
*Added in 0.7.0*
Use the `sparsevec` type to store sparse vectors
```sql
@@ -567,8 +635,6 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python
## Indexing Subvectors
*Added in 0.7.0*
Use expression indexing to index subvectors
```sql
@@ -629,10 +695,10 @@ CREATE INDEX CONCURRENTLY ...
### Querying
Use `EXPLAIN ANALYZE` to debug performance.
Use `EXPLAIN (ANALYZE, BUFFERS)` to debug performance.
```sql
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
EXPLAIN (ANALYZE, BUFFERS) SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
#### Exact Search
@@ -682,8 +748,6 @@ SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_t
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
@@ -707,25 +771,32 @@ Use pgvector from any language with a Postgres client. You can even generate and
Language | Libraries / Examples
--- | ---
Ada | [pgvector-ada](https://github.com/pgvector/pgvector-ada)
C | [pgvector-c](https://github.com/pgvector/pgvector-c)
C++ | [pgvector-cpp](https://github.com/pgvector/pgvector-cpp)
C#, F#, Visual Basic | [pgvector-dotnet](https://github.com/pgvector/pgvector-dotnet)
Crystal | [pgvector-crystal](https://github.com/pgvector/pgvector-crystal)
D | [pgvector-d](https://github.com/pgvector/pgvector-d)
Dart | [pgvector-dart](https://github.com/pgvector/pgvector-dart)
Elixir | [pgvector-elixir](https://github.com/pgvector/pgvector-elixir)
Erlang | [pgvector-erlang](https://github.com/pgvector/pgvector-erlang)
Fortran | [pgvector-fortran](https://github.com/pgvector/pgvector-fortran)
Gleam | [pgvector-gleam](https://github.com/pgvector/pgvector-gleam)
Go | [pgvector-go](https://github.com/pgvector/pgvector-go)
Haskell | [pgvector-haskell](https://github.com/pgvector/pgvector-haskell)
Java, Kotlin, Groovy, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
JavaScript, TypeScript | [pgvector-node](https://github.com/pgvector/pgvector-node)
Julia | [pgvector-julia](https://github.com/pgvector/pgvector-julia)
Julia | [Pgvector.jl](https://github.com/pgvector/Pgvector.jl)
Lisp | [pgvector-lisp](https://github.com/pgvector/pgvector-lisp)
Lua | [pgvector-lua](https://github.com/pgvector/pgvector-lua)
Nim | [pgvector-nim](https://github.com/pgvector/pgvector-nim)
OCaml | [pgvector-ocaml](https://github.com/pgvector/pgvector-ocaml)
Pascal | [pgvector-pascal](https://github.com/pgvector/pgvector-pascal)
Perl | [pgvector-perl](https://github.com/pgvector/pgvector-perl)
PHP | [pgvector-php](https://github.com/pgvector/pgvector-php)
Python | [pgvector-python](https://github.com/pgvector/pgvector-python)
R | [pgvector-r](https://github.com/pgvector/pgvector-r)
Raku | [pgvector-raku](https://github.com/pgvector/pgvector-raku)
Ruby | [pgvector-ruby](https://github.com/pgvector/pgvector-ruby), [Neighbor](https://github.com/ankane/neighbor)
Rust | [pgvector-rust](https://github.com/pgvector/pgvector-rust)
Swift | [pgvector-swift](https://github.com/pgvector/pgvector-swift)
@@ -743,11 +814,11 @@ Yes, pgvector uses the write-ahead log (WAL), which allows for replication and p
#### What if I want to index vectors with more than 2,000 dimensions?
You can use [half-precision indexing](#half-precision-indexing) to index up to 4,000 dimensions or [binary quantization](#binary-quantization) to index up to 64,000 dimensions. Another option is [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction).
You can use [half-precision vectors](#half-precision-vectors) or [half-precision indexing](#half-precision-indexing) to index up to 4,000 dimensions or [binary quantization](#binary-quantization) to index up to 64,000 dimensions. Other options are [indexing subvectors](#indexing-subvectors) (for models that support it) or [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction).
#### Can I store vectors with different dimensions in the same column?
You can use `vector` as the type (instead of `vector(3)`).
You can use `vector` as the type (instead of `vector(n)`).
```sql
CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id));
@@ -847,7 +918,7 @@ 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.
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`), which is 40 by default. There may be even less results due to dead tuples or filtering conditions in the query. Enabling [iterative index scans](#iterative-index-scans) can help address this.
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
@@ -859,7 +930,7 @@ 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`).
Results can also be limited by the number of probes (`ivfflat.probes`). Enabling [iterative index scans](#iterative-index-scans) can address this.
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
@@ -995,7 +1066,7 @@ l2_normalize(sparsevec) → sparsevec | Normalize with Euclidean norm | 0.7.0
If your machine has multiple Postgres installations, specify the path to [pg_config](https://www.postgresql.org/docs/current/app-pgconfig.html) with:
```sh
export PG_CONFIG=/Library/PostgreSQL/17/bin/pg_config
export PG_CONFIG=/Library/PostgreSQL/18/bin/pg_config
```
Then re-run the installation instructions (run `make clean` before `make` if needed). If `sudo` is needed for `make install`, use:
@@ -1006,11 +1077,11 @@ sudo --preserve-env=PG_CONFIG make install
A few common paths on Mac are:
- EDB installer - `/Library/PostgreSQL/17/bin/pg_config`
- Homebrew (arm64) - `/opt/homebrew/opt/postgresql@17/bin/pg_config`
- Homebrew (x86-64) - `/usr/local/opt/postgresql@17/bin/pg_config`
- EDB installer - `/Library/PostgreSQL/18/bin/pg_config`
- Homebrew (arm64) - `/opt/homebrew/opt/postgresql@18/bin/pg_config`
- Homebrew (x86-64) - `/usr/local/opt/postgresql@18/bin/pg_config`
Note: Replace `17` with your Postgres server version
Note: Replace `18` with your Postgres server version
### Missing Header
@@ -1019,14 +1090,20 @@ If compilation fails with `fatal error: postgres.h: No such file or directory`,
For Ubuntu and Debian, use:
```sh
sudo apt install postgresql-server-dev-17
sudo apt install postgresql-server-dev-18
```
Note: Replace `17` with your Postgres server version
Note: Replace `18` with your Postgres server version
### Missing SDK
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, reinstall Xcode Command Line Tools.
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, your Postgres installation points to a path that no longer exists.
```sh
pg_config --cppflags
```
Reinstall Postgres to fix this.
### Portability
@@ -1044,6 +1121,14 @@ make OPTFLAGS=""
If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct.
### Mismatched Architecture
If compilation fails with `error C2196: case value '4' already used`, make sure youre using the `x64 Native Tools Command Prompt`. Then run `nmake /F Makefile.win clean` and re-run the installation instructions.
### Missing Symbol
If linking fails with `unresolved external symbol float_to_shortest_decimal_bufn` with Postgres 17.0-17.2, upgrade to Postgres 17.3+.
### Permissions
If installation fails with `Access is denied`, re-run the installation instructions as an administrator.
@@ -1055,17 +1140,38 @@ If installation fails with `Access is denied`, re-run the installation instructi
Get the [Docker image](https://hub.docker.com/r/pgvector/pgvector) with:
```sh
docker pull pgvector/pgvector:pg17
docker pull pgvector/pgvector:pg18-trixie
```
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `17` with your Postgres server version, and run it the same way).
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `18` with your Postgres server version, and run it the same way).
Supported tags are:
- `pg18-trixie`, `0.8.1-pg18-trixie`
- `pg18-bookworm`, `0.8.1-pg18-bookworm`, `pg18`, `0.8.1-pg18`
- `pg17-trixie`, `0.8.1-pg17-trixie`
- `pg17-bookworm`, `0.8.1-pg17-bookworm`, `pg17`, `0.8.1-pg17`
- `pg16-trixie`, `0.8.1-pg16-trixie`
- `pg16-bookworm`, `0.8.1-pg16-bookworm`, `pg16`, `0.8.1-pg16`
- `pg15-trixie`, `0.8.1-pg15-trixie`
- `pg15-bookworm`, `0.8.1-pg15-bookworm`, `pg15`, `0.8.1-pg15`
- `pg14-trixie`, `0.8.1-pg14-trixie`
- `pg14-bookworm`, `0.8.1-pg14-bookworm`, `pg14`, `0.8.1-pg14`
- `pg13-trixie`, `0.8.1-pg13-trixie`
- `pg13-bookworm`, `0.8.1-pg13-bookworm`, `pg13`, `0.8.1-pg13`
You can also build the image manually:
```sh
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
git clone --branch v0.8.1 https://github.com/pgvector/pgvector.git
cd pgvector
docker build --pull --build-arg PG_MAJOR=17 -t myuser/pgvector .
docker build --pull --build-arg PG_MAJOR=18 -t myuser/pgvector .
```
If you increase `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
```sh
docker run --shm-size=1g ...
```
### Homebrew
@@ -1076,7 +1182,7 @@ With Homebrew Postgres, you can use:
brew install pgvector
```
Note: This only adds it to the `postgresql@17` and `postgresql@14` formulas
Note: This only adds it to the `postgresql@18` and `postgresql@17` formulas
### PGXN
@@ -1091,29 +1197,29 @@ pgxn install vector
Debian and Ubuntu packages are available from the [PostgreSQL APT Repository](https://wiki.postgresql.org/wiki/Apt). Follow the [setup instructions](https://wiki.postgresql.org/wiki/Apt#Quickstart) and run:
```sh
sudo apt install postgresql-17-pgvector
sudo apt install postgresql-18-pgvector
```
Note: Replace `17` with your Postgres server version
Note: Replace `18` with your Postgres server version
### Yum
RPM packages are available from the [PostgreSQL Yum Repository](https://yum.postgresql.org/). Follow the [setup instructions](https://www.postgresql.org/download/linux/redhat/) for your distribution and run:
```sh
sudo yum install pgvector_17
sudo yum install pgvector_18
# or
sudo dnf install pgvector_17
sudo dnf install pgvector_18
```
Note: Replace `17` with your Postgres server version
Note: Replace `18` with your Postgres server version
### pkg
Install the FreeBSD package with:
```sh
pkg install postgresql15-pgvector
pkg install postgresql17-pgvector
```
or the port with:
@@ -1155,36 +1261,6 @@ You can check the version in the current database with:
SELECT extversion FROM pg_extension WHERE extname = 'vector';
```
## Upgrade Notes
### 0.6.0
#### Postgres 12
If upgrading with Postgres 12, remove this line from `sql/vector--0.5.1--0.6.0.sql`:
```sql
ALTER TYPE vector SET (STORAGE = external);
```
Then run `make install` and `ALTER EXTENSION vector UPDATE;`.
#### Docker
The Docker image is now published in the `pgvector` org, and there are tags for each supported version of Postgres (rather than a `latest` tag).
```sh
docker pull pgvector/pgvector:pg16
# or
docker pull pgvector/pgvector:0.6.0-pg16
```
Also, if youve increased `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
```sh
docker run --shm-size=1g ...
```
## Thanks
Thanks to:
@@ -1195,7 +1271,6 @@ Thanks to:
- [k-means++: The Advantage of Careful Seeding](https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf)
- [Concept Decompositions for Large Sparse Text Data using Clustering](https://www.cs.utexas.edu/users/inderjit/public_papers/concept_mlj.pdf)
- [Efficient and Robust Approximate Nearest Neighbor Search using Hierarchical Navigable Small World Graphs](https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf)
- [HQANN: Efficient and Robust Similarity Search for Hybrid Queries with Structured and Unstructured Constraints](https://arxiv.org/pdf/2207.07940.pdf)
## History

View File

@@ -24,11 +24,3 @@ CREATE CAST (double precision[] AS sparsevec)
CREATE CAST (numeric[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(numeric[], integer, boolean) AS ASSIGNMENT;
CREATE FUNCTION hnsw_attribute_distance(integer, integer) RETURNS float8
AS 'MODULE_PATHNAME', 'hnsw_int4_attribute_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR CLASS vector_integer_ops
DEFAULT FOR TYPE integer USING hnsw AS
OPERATOR 2 = (integer, integer),
FUNCTION 4 hnsw_attribute_distance(integer, integer);

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 '0.8.1'" to load this file. \quit

View File

@@ -916,13 +916,3 @@ CREATE OPERATOR CLASS sparsevec_l1_ops
OPERATOR 1 <+> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(sparsevec, sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);
-- hnsw attributes
CREATE FUNCTION hnsw_attribute_distance(integer, integer) RETURNS float8
AS 'MODULE_PATHNAME', 'hnsw_int4_attribute_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR CLASS vector_integer_ops
DEFAULT FOR TYPE integer USING hnsw AS
OPERATOR 2 = (integer, integer),
FUNCTION 4 hnsw_attribute_distance(integer, integer);

View File

@@ -898,8 +898,21 @@ halfvec_binary_quantize(PG_FUNCTION_ARGS)
half *ax = a->x;
VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result);
int i = 0;
int count = (a->dim / 8) * 8;
for (int i = 0; i < a->dim; i++)
/* Auto-vectorized on aarch64 */
for (; i < count; i += 8)
{
unsigned char result_byte = 0;
for (int j = 0; j < 8; j++)
result_byte |= (HalfToFloat4(ax[i + j]) > 0) << (7 - j);
rx[i / 8] = result_byte;
}
for (; i < a->dim; i++)
rx[i / 8] |= (HalfToFloat4(ax[i]) > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result);

View File

@@ -18,16 +18,17 @@
#define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
#endif
static const struct config_enum_entry hnsw_iterative_search_options[] = {
{"off", HNSW_ITERATIVE_SEARCH_OFF, false},
{"on", HNSW_ITERATIVE_SEARCH_RELAXED, false},
{"strict", HNSW_ITERATIVE_SEARCH_STRICT, false},
static const struct config_enum_entry hnsw_iterative_scan_options[] = {
{"off", HNSW_ITERATIVE_SCAN_OFF, false},
{"relaxed_order", HNSW_ITERATIVE_SCAN_RELAXED, false},
{"strict_order", HNSW_ITERATIVE_SCAN_STRICT, false},
{NULL, 0, false}
};
int hnsw_ef_search;
int hnsw_iterative_search_max_tuples;
int hnsw_iterative_search;
int hnsw_iterative_scan;
int hnsw_max_scan_tuples;
double hnsw_scan_mem_multiplier;
int hnsw_lock_tranche_id;
static relopt_kind hnsw_relopt_kind;
@@ -51,12 +52,20 @@ HnswInitLockTranche(void)
sizeof(int) * 1,
&found);
if (!found)
{
#if PG_VERSION_NUM >= 190000
tranche_ids[0] = LWLockNewTrancheId("HnswBuild");
#else
tranche_ids[0] = LWLockNewTrancheId();
#endif
}
hnsw_lock_tranche_id = tranche_ids[0];
LWLockRelease(AddinShmemInitLock);
#if PG_VERSION_NUM < 190000
/* Per-backend registration of the tranche ID */
LWLockRegisterTranche(hnsw_lock_tranche_id, "HnswBuild");
#endif
}
/*
@@ -78,14 +87,19 @@ HnswInit(void)
"Valid range is 1..1000.", &hnsw_ef_search,
HNSW_DEFAULT_EF_SEARCH, HNSW_MIN_EF_SEARCH, HNSW_MAX_EF_SEARCH, PGC_USERSET, 0, NULL, NULL, NULL);
DefineCustomEnumVariable("hnsw.iterative_search", "Sets iterative search",
NULL, &hnsw_iterative_search,
HNSW_ITERATIVE_SEARCH_OFF, hnsw_iterative_search_options, PGC_USERSET, 0, NULL, NULL, NULL);
DefineCustomEnumVariable("hnsw.iterative_scan", "Sets the mode for iterative scans",
NULL, &hnsw_iterative_scan,
HNSW_ITERATIVE_SCAN_OFF, hnsw_iterative_scan_options, PGC_USERSET, 0, NULL, NULL, NULL);
/* TODO Ensure ivfflat.max_probes uses same value for "all" */
DefineCustomIntVariable("hnsw.iterative_search_max_tuples", "Sets the max number of candidates to visit for iterative search",
"-1 means all", &hnsw_iterative_search_max_tuples,
-1, -1, INT_MAX, PGC_USERSET, 0, NULL, NULL, NULL);
/* This is approximate and does not affect the initial scan */
DefineCustomIntVariable("hnsw.max_scan_tuples", "Sets the max number of tuples to visit for iterative scans",
NULL, &hnsw_max_scan_tuples,
20000, 1, INT_MAX, PGC_USERSET, 0, NULL, NULL, NULL);
/* Same range as hash_mem_multiplier */
DefineCustomRealVariable("hnsw.scan_mem_multiplier", "Sets the multiple of work_mem to use for iterative scans",
NULL, &hnsw_scan_mem_multiplier,
1, 1, 1000, PGC_USERSET, 0, NULL, NULL, NULL);
MarkGUCPrefixReserved("hnsw");
}
@@ -124,13 +138,17 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
Relation index;
/* Never use index without order */
if (path->indexorderbys == NULL)
if (path->indexorderbys == NIL)
{
*indexStartupCost = get_float8_infinity();
*indexTotalCost = get_float8_infinity();
*indexSelectivity = 0;
*indexCorrelation = 0;
*indexPages = 0;
#if PG_VERSION_NUM >= 180000
/* See "On disable_cost" thread on pgsql-hackers */
path->path.disabled_nodes = 2;
#endif
return;
}
@@ -245,13 +263,18 @@ hnswhandler(PG_FUNCTION_ARGS)
IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0;
amroutine->amsupport = 4;
amroutine->amsupport = 3;
amroutine->amoptsprocnum = 0;
amroutine->amcanorder = false;
amroutine->amcanorderbyop = true;
#if PG_VERSION_NUM >= 180000
amroutine->amcanhash = false;
amroutine->amconsistentequality = false;
amroutine->amconsistentordering = false;
#endif
amroutine->amcanbackward = false; /* can change direction mid-scan */
amroutine->amcanunique = false;
amroutine->amcanmulticol = true;
amroutine->amcanmulticol = false;
amroutine->amoptionalkey = true;
amroutine->amsearcharray = false;
amroutine->amsearchnulls = false;
@@ -281,6 +304,9 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amvacuumcleanup = hnswvacuumcleanup;
amroutine->amcanreturn = NULL;
amroutine->amcostestimate = hnswcostestimate;
#if PG_VERSION_NUM >= 180000
amroutine->amgettreeheight = NULL;
#endif
amroutine->amoptions = hnswoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
amroutine->ambuildphasename = hnswbuildphasename;
@@ -301,19 +327,10 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->aminitparallelscan = NULL;
amroutine->amparallelrescan = NULL;
#if PG_VERSION_NUM >= 180000
amroutine->amtranslatestrategy = NULL;
amroutine->amtranslatecmptype = NULL;
#endif
PG_RETURN_POINTER(amroutine);
}
/*
* Get the distance between two int4 attributes
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(hnsw_int4_attribute_distance);
Datum
hnsw_int4_attribute_distance(PG_FUNCTION_ARGS)
{
int32 a = PG_GETARG_INT32(0);
int32 b = PG_GETARG_INT32(1);
double distance = ((double) a) - ((double) b);
PG_RETURN_FLOAT8(distance);
}

View File

@@ -19,7 +19,6 @@
#define HNSW_DISTANCE_PROC 1
#define HNSW_NORM_PROC 2
#define HNSW_TYPE_INFO_PROC 3
#define HNSW_ATTRIBUTE_DISTANCE_PROC 4
#define HNSW_VERSION 1
#define HNSW_MAGIC_NUMBER 0xA953A953
@@ -108,27 +107,26 @@
#define HnswPtrPointer(hp) (hp).ptr
#define HnswPtrOffset(hp) relptr_offset((hp).relptr)
#define HnswUseIndexTuple(index) (IndexRelationGetNumberOfAttributes(index) > 1)
/* Variables */
extern int hnsw_ef_search;
extern int hnsw_iterative_search;
extern int hnsw_iterative_search_max_tuples;
extern int hnsw_iterative_scan;
extern int hnsw_max_scan_tuples;
extern double hnsw_scan_mem_multiplier;
extern int hnsw_lock_tranche_id;
typedef enum HnswIterativeSearchType
typedef enum HnswIterativeScanMode
{
HNSW_ITERATIVE_SEARCH_OFF,
HNSW_ITERATIVE_SEARCH_RELAXED,
HNSW_ITERATIVE_SEARCH_STRICT
} HnswIterativeSearchType;
HNSW_ITERATIVE_SCAN_OFF,
HNSW_ITERATIVE_SCAN_RELAXED,
HNSW_ITERATIVE_SCAN_STRICT
} HnswIterativeScanMode;
typedef struct HnswElementData HnswElementData;
typedef struct HnswNeighborArray HnswNeighborArray;
#define HnswPtrDeclare(type, relptrtype, ptrtype) \
relptr_declare(type, relptrtype); \
typedef union { type *ptr; relptrtype relptr; } ptrtype;
typedef union { type *ptr; relptrtype relptr; } ptrtype
/* Pointers that can be absolute or relative */
/* Use char for DatumPtr so works with Pointer */
@@ -136,7 +134,6 @@ HnswPtrDeclare(HnswElementData, HnswElementRelptr, HnswElementPtr);
HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr);
HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
HnswPtrDeclare(char, DatumRelptr, DatumPtr);
HnswPtrDeclare(IndexTupleData, IndexTupleRelptr, IndexTuplePtr);
struct HnswElementData
{
@@ -153,7 +150,6 @@ struct HnswElementData
OffsetNumber neighborOffno;
BlockNumber neighborPage;
DatumPtr value;
IndexTuplePtr itup;
LWLock lock;
};
@@ -179,7 +175,6 @@ typedef struct HnswSearchCandidate
pairingheap_node w_node;
HnswElementPtr element;
double distance;
bool matches;
} HnswSearchCandidate;
/* HNSW index options */
@@ -258,16 +253,14 @@ typedef struct HnswTypeInfo
typedef struct HnswSupport
{
FmgrInfo *procinfo[2];
FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
Oid *collation;
Oid collation;
} HnswSupport;
typedef struct HnswQuery
{
Datum value;
IndexTuple itup;
ScanKeyData *keyData;
} HnswQuery;
typedef struct HnswBuildState
@@ -296,8 +289,6 @@ typedef struct HnswBuildState
HnswGraph *graph;
double ml;
int maxLevel;
bool useIndexTuple;
TupleDesc tupdesc;
/* Memory */
MemoryContext graphCtx;
@@ -371,6 +362,13 @@ typedef union
ItemPointerData indextid;
} HnswUnvisited;
typedef struct HnswReadStreamData
{
HnswUnvisited *unvisited;
int unvisitedLength;
int visited;
} HnswReadStreamData;
typedef struct HnswScanOpaqueData
{
const HnswTypeInfo *typeInfo;
@@ -382,6 +380,7 @@ typedef struct HnswScanOpaqueData
int m;
int64 tuples;
double previousDistance;
Size maxMemory;
MemoryContext tmpCtx;
/* Support functions */
@@ -425,32 +424,30 @@ bool HnswCheckNorm(HnswSupport * support, Datum value);
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
void HnswInitPage(Buffer buf, Page page);
void HnswInit(void);
List *HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement, bool inMemory, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples);
List *HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples, bool maintenance);
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, bool inMemory);
HnswSearchCandidate *HnswEntryCandidate(char *base, HnswElement em, HnswQuery * q, Relation rel, HnswSupport * support, bool loadVec, bool inMemory);
void HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, HnswSupport * support, int m, int efConstruction, bool existing, bool maintenance);
HnswSearchCandidate *HnswEntryCandidate(char *base, HnswElement em, HnswQuery * q, Relation rel, HnswSupport * support, 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);
HnswNeighborArray *HnswInitNeighborArray(int lm, HnswAllocator * allocator);
void HnswInitNeighbors(char *base, HnswElement element, int m, HnswAllocator * alloc);
bool HnswInsertTupleOnDisk(Relation index, HnswSupport * support, IndexTuple itup, ItemPointer heaptid, bool building, TupleDesc tupdesc);
bool HnswInsertTupleOnDisk(Relation index, HnswSupport * support, Datum value, ItemPointer heaptid, bool building);
void HnswUpdateNeighborsOnDisk(Relation index, HnswSupport * support, HnswElement e, int m, bool checkExisting, bool building);
void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec, Relation index);
void HnswLoadElement(HnswElement element, double *distance, bool *matches, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, double *maxDistance);
void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element, bool useIndexTuple);
void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec);
void HnswLoadElement(HnswElement element, double *distance, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, double *maxDistance);
bool HnswFormIndexValue(Datum *out, Datum *values, bool *isnull, const HnswTypeInfo * typeInfo, HnswSupport * support);
void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element);
void HnswUpdateConnection(char *base, HnswNeighborArray * neighbors, HnswElement newElement, float distance, int lm, int *updateIdx, Relation index, HnswSupport * support);
bool HnswFormIndexTuple(IndexTuple *out, Datum *values, bool *isnull, const HnswTypeInfo * typeInfo, HnswSupport * support, TupleDesc tupdesc);
bool HnswLoadNeighborTids(HnswElement element, ItemPointerData *indextids, Relation index, int m, int lm, int lc);
void HnswInitLockTranche(void);
const HnswTypeInfo *HnswGetTypeInfo(Relation index);
PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);
Size HnswGetElementTupleSize(char *base, HnswElement element, bool useIndexTuple);
bool HnswIndexTupleIsEqual(IndexTuple a, IndexTuple b, TupleDesc tupdesc);
/* Index access methods */
IndexBuildResult *hnswbuild(Relation heap, Relation index, IndexInfo *indexInfo);

View File

@@ -54,6 +54,10 @@
#include "utils/datum.h"
#include "utils/memutils.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h"
#else
@@ -148,7 +152,6 @@ CreateGraphPages(HnswBuildState * buildstate)
Page page;
HnswElementPtr iter = buildstate->graph->head;
char *base = buildstate->hnswarea;
bool useIndexTuple = buildstate->useIndexTuple;
/* Calculate sizes */
maxSize = HNSW_MAX_SIZE;
@@ -168,6 +171,7 @@ CreateGraphPages(HnswBuildState * buildstate)
Size etupSize;
Size ntupSize;
Size combinedSize;
Pointer valuePtr = HnswPtrAccess(base, element->value);
/* Update iterator */
iter = element->next;
@@ -176,7 +180,7 @@ CreateGraphPages(HnswBuildState * buildstate)
MemSet(etup, 0, HNSW_TUPLE_ALLOC_SIZE);
/* Calculate sizes */
etupSize = HnswGetElementTupleSize(base, element, useIndexTuple);
etupSize = HNSW_ELEMENT_TUPLE_SIZE(VARSIZE_ANY(valuePtr));
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, buildstate->m);
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
@@ -186,7 +190,7 @@ CreateGraphPages(HnswBuildState * buildstate)
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("index tuple too large")));
HnswSetElementTuple(base, etup, element, useIndexTuple);
HnswSetElementTuple(base, etup, element);
/* Keep element and neighbors on the same page if possible */
if (PageGetFreeSpace(page) < etupSize || (combinedSize <= maxSize && PageGetFreeSpace(page) < combinedSize))
@@ -327,18 +331,19 @@ AddDuplicateInMemory(HnswElement element, HnswElement dup)
* Find duplicate element
*/
static bool
FindDuplicateInMemory(char *base, HnswElement element, bool useIndexTuple, TupleDesc tupdesc)
FindDuplicateInMemory(char *base, HnswElement element)
{
HnswNeighborArray *neighbors = HnswGetNeighbors(base, element, 0);
IndexTuple itup = HnswPtrAccess(base, element->itup);
Datum value = HnswGetValue(base, element);
for (int i = 0; i < neighbors->length; i++)
{
HnswCandidate *neighbor = &neighbors->items[i];
HnswElement neighborElement = HnswPtrAccess(base, neighbor->element);
Datum neighborValue = HnswGetValue(base, neighborElement);
/* Exit early since ordered by distance */
if (!HnswIndexTupleIsEqual(itup, HnswPtrAccess(base, neighborElement->itup), tupdesc))
if (!datumIsEqual(value, neighborValue, false, -1))
return false;
/* Check for space */
@@ -365,7 +370,7 @@ AddElementInMemory(char *base, HnswGraph * graph, HnswElement element)
* Update neighbors
*/
static void
UpdateNeighborsInMemory(char *base, Relation index, HnswSupport * support, HnswElement e, int m)
UpdateNeighborsInMemory(char *base, HnswSupport * support, HnswElement e, int m)
{
for (int lc = e->level; lc >= 0; lc--)
{
@@ -387,7 +392,7 @@ UpdateNeighborsInMemory(char *base, Relation index, HnswSupport * support, HnswE
Assert(neighborElement);
LWLockAcquire(&neighborElement->lock, LW_EXCLUSIVE);
HnswUpdateConnection(base, HnswGetNeighbors(base, neighborElement, lc), e, hc->distance, lm, NULL, index, support);
HnswUpdateConnection(base, HnswGetNeighbors(base, neighborElement, lc), e, hc->distance, lm, NULL, NULL, support);
LWLockRelease(&neighborElement->lock);
}
}
@@ -397,20 +402,20 @@ UpdateNeighborsInMemory(char *base, Relation index, HnswSupport * support, HnswE
* Update graph in memory
*/
static void
UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, int efConstruction, HnswElement entryPoint, HnswBuildState * buildstate)
UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, HnswElement entryPoint, HnswBuildState * buildstate)
{
HnswGraph *graph = buildstate->graph;
char *base = buildstate->hnswarea;
/* Look for duplicate */
if (FindDuplicateInMemory(base, element, buildstate->useIndexTuple, buildstate->tupdesc))
if (FindDuplicateInMemory(base, element))
return;
/* Add element */
AddElementInMemory(base, graph, element);
/* Update neighbors */
UpdateNeighborsInMemory(base, buildstate->index, support, element, m);
UpdateNeighborsInMemory(base, support, element, m);
/* Update entry point if needed (already have lock) */
if (entryPoint == NULL || element->level > entryPoint->level)
@@ -423,7 +428,6 @@ UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, int efCon
static void
InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
{
Relation index = buildstate->index;
HnswGraph *graph = buildstate->graph;
HnswSupport *support = &buildstate->support;
HnswElement entryPoint;
@@ -457,10 +461,10 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
}
/* Find neighbors for element */
HnswFindElementNeighbors(base, element, entryPoint, index, support, m, efConstruction, false, true);
HnswFindElementNeighbors(base, element, entryPoint, NULL, support, m, efConstruction, false, true);
/* Update graph in memory */
UpdateGraphInMemory(support, element, m, efConstruction, entryPoint, buildstate);
UpdateGraphInMemory(support, element, m, entryPoint, buildstate);
/* Release entry lock */
LWLockRelease(entryLock);
@@ -476,20 +480,18 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
HnswElement element;
HnswAllocator *allocator = &buildstate->allocator;
HnswSupport *support = &buildstate->support;
Size valueSize;
Pointer valuePtr;
LWLock *flushLock = &graph->flushLock;
char *base = buildstate->hnswarea;
TupleDesc tupdesc = buildstate->tupdesc;
IndexTuple itup;
Size itupSize;
IndexTuple itupShared;
bool unused;
Datum value;
/* Form index tuple */
if (!HnswFormIndexTuple(&itup, values, isnull, buildstate->typeInfo, support, tupdesc))
/* Form index value */
if (!HnswFormIndexValue(&value, values, isnull, buildstate->typeInfo, support))
return false;
/* Get tuple size */
itupSize = IndexTupleSize(itup);
/* Get datum size */
valueSize = VARSIZE_ANY(DatumGetPointer(value));
/* Ensure graph not flushed when inserting */
LWLockAcquire(flushLock, LW_SHARED);
@@ -499,7 +501,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
{
LWLockRelease(flushLock);
return HnswInsertTupleOnDisk(index, support, itup, heaptid, true, tupdesc);
return HnswInsertTupleOnDisk(index, support, value, heaptid, true);
}
/*
@@ -531,12 +533,12 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
LWLockRelease(flushLock);
return HnswInsertTupleOnDisk(index, support, itup, heaptid, true, tupdesc);
return HnswInsertTupleOnDisk(index, support, value, heaptid, true);
}
/* Ok, we can proceed to allocate the element */
element = HnswInitElement(base, heaptid, buildstate->m, buildstate->ml, buildstate->maxLevel, allocator);
itupShared = HnswAlloc(allocator, itupSize);
valuePtr = HnswAlloc(allocator, valueSize);
/*
* We have now allocated the space needed for the element, so we don't
@@ -545,10 +547,9 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
*/
LWLockRelease(&graph->allocatorLock);
/* Copy the tuple */
memcpy(itupShared, itup, itupSize);
HnswPtrStore(base, element->itup, itupShared);
HnswPtrStore(base, element->value, DatumGetPointer(index_getattr(itupShared, 1, tupdesc, &unused)));
/* Copy the datum */
memcpy(valuePtr, DatumGetPointer(value), valueSize);
HnswPtrStore(base, element->value, valuePtr);
/* Create a lock for the element */
LWLockInitialize(&element->lock, hnsw_lock_tranche_id);
@@ -675,19 +676,6 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
errmsg("type not supported for hnsw index")));
/* TODO See if needed */
if (IndexRelationGetNumberOfKeyAttributes(index) > 2)
elog(ERROR, "index cannot have more than two columns");
if (!OidIsValid(index_getprocid(index, 1, HNSW_DISTANCE_PROC)))
elog(ERROR, "first column must be a vector");
for (int i = 1; i < IndexRelationGetNumberOfKeyAttributes(index); i++)
{
if (!OidIsValid(index_getprocid(index, i + 1, HNSW_ATTRIBUTE_DISTANCE_PROC)))
elog(ERROR, "column %d cannot be a vector", i + 1);
}
/* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0)
ereport(ERROR,
@@ -714,8 +702,6 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->graph = &buildstate->graphData;
buildstate->ml = HnswGetMl(buildstate->m);
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
buildstate->useIndexTuple = HnswUseIndexTuple(index);
buildstate->tupdesc = RelationGetDescr(index);
buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext,
"Hnsw build graph context",
@@ -1072,7 +1058,7 @@ ComputeParallelWorkers(Relation heap, Relation index)
* Build graph
*/
static void
BuildGraph(HnswBuildState * buildstate, ForkNumber forkNum)
BuildGraph(HnswBuildState * buildstate)
{
int parallel_workers = 0;
@@ -1120,7 +1106,7 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
InitBuildState(buildstate, heap, index, indexInfo, forkNum);
BuildGraph(buildstate, forkNum);
BuildGraph(buildstate);
if (RelationNeedsWAL(index) || forkNum == INIT_FORKNUM)
log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true);

View File

@@ -9,6 +9,10 @@
#include "utils/datum.h"
#include "utils/memutils.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/*
* Get the insert page
*/
@@ -156,10 +160,9 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
BlockNumber newInsertPage = InvalidBlockNumber;
uint8 tupleVersion;
char *base = NULL;
bool useIndexTuple = HnswUseIndexTuple(index);
/* Calculate sizes */
etupSize = HnswGetElementTupleSize(base, e, useIndexTuple);
etupSize = HNSW_ELEMENT_TUPLE_SIZE(VARSIZE_ANY(HnswPtrAccess(base, e->value)));
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
maxSize = HNSW_MAX_SIZE;
@@ -167,7 +170,7 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
/* Prepare element tuple */
etup = palloc0(etupSize);
HnswSetElementTuple(base, etup, e, useIndexTuple);
HnswSetElementTuple(base, etup, e);
/* Prepare neighbor tuple */
ntup = palloc0(ntupSize);
@@ -384,9 +387,8 @@ LoadElementsForInsert(HnswNeighborArray * neighbors, HnswQuery * q, int *idx, Re
HnswCandidate *hc = &neighbors->items[i];
HnswElement element = HnswPtrAccess(base, hc->element);
double distance;
bool matches;
HnswLoadElement(element, &distance, &matches, q, index, support, true, NULL);
HnswLoadElement(element, &distance, q, index, support, true, NULL);
hc->distance = distance;
/* Prune element if being deleted */
@@ -430,8 +432,6 @@ GetUpdateIndex(HnswElement element, HnswElement newElement, float distance, int
HnswQuery q;
q.value = HnswGetValue(base, element);
q.itup = HnswPtrAccess(base, element->itup);
q.keyData = NULL;
LoadElementsForInsert(neighbors, &q, &idx, index, support);
@@ -637,30 +637,21 @@ AddDuplicateOnDisk(Relation index, HnswElement element, HnswElement dup, bool bu
* Find duplicate element
*/
static bool
FindDuplicateOnDisk(Relation index, HnswElement element, bool building, TupleDesc tupdesc)
FindDuplicateOnDisk(Relation index, HnswElement element, bool building)
{
char *base = NULL;
HnswNeighborArray *neighbors = HnswGetNeighbors(base, element, 0);
Datum value = HnswGetValue(base, element);
IndexTuple itup = HnswPtrAccess(base, element->itup);
for (int i = 0; i < neighbors->length; i++)
{
HnswCandidate *neighbor = &neighbors->items[i];
HnswElement neighborElement = HnswPtrAccess(base, neighbor->element);
Datum neighborValue = HnswGetValue(base, neighborElement);
if (HnswUseIndexTuple(index))
{
/* Exit early since ordered by distance */
if (!HnswIndexTupleIsEqual(itup, HnswPtrAccess(base, neighborElement->itup), tupdesc))
return false;
}
else
{
/* Exit early since ordered by distance */
if (!datumIsEqual(value, HnswGetValue(base, neighborElement), false, -1))
return false;
}
/* Exit early since ordered by distance */
if (!datumIsEqual(value, neighborValue, false, -1))
return false;
if (AddDuplicateOnDisk(index, element, neighborElement, building))
return true;
@@ -673,12 +664,12 @@ FindDuplicateOnDisk(Relation index, HnswElement element, bool building, TupleDes
* Update graph on disk
*/
static void
UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, int m, int efConstruction, HnswElement entryPoint, bool building, TupleDesc tupdesc)
UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, int m, HnswElement entryPoint, bool building)
{
BlockNumber newInsertPage = InvalidBlockNumber;
/* Look for duplicate */
if (FindDuplicateOnDisk(index, element, building, tupdesc))
if (FindDuplicateOnDisk(index, element, building))
return;
/* Add element */
@@ -700,7 +691,7 @@ UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, in
* Insert a tuple into the index
*/
bool
HnswInsertTupleOnDisk(Relation index, HnswSupport * support, IndexTuple itup, ItemPointer heaptid, bool building, TupleDesc tupdesc)
HnswInsertTupleOnDisk(Relation index, HnswSupport * support, Datum value, ItemPointer heaptid, bool building)
{
HnswElement entryPoint;
HnswElement element;
@@ -708,7 +699,6 @@ HnswInsertTupleOnDisk(Relation index, HnswSupport * support, IndexTuple itup, It
int efConstruction = HnswGetEfConstruction(index);
LOCKMODE lockmode = ShareLock;
char *base = NULL;
bool unused;
/*
* Get a shared lock. This allows vacuum to ensure no in-flight inserts
@@ -722,8 +712,7 @@ HnswInsertTupleOnDisk(Relation index, HnswSupport * support, IndexTuple itup, It
/* Create an element */
element = HnswInitElement(base, heaptid, m, HnswGetMl(m), HnswGetMaxLevel(m), NULL);
HnswPtrStore(base, element->itup, itup);
HnswPtrStore(base, element->value, DatumGetPointer(index_getattr(itup, 1, tupdesc, &unused)));
HnswPtrStore(base, element->value, DatumGetPointer(value));
/* Prevent concurrent inserts when likely updating entry point */
if (entryPoint == NULL || element->level > entryPoint->level)
@@ -740,10 +729,10 @@ HnswInsertTupleOnDisk(Relation index, HnswSupport * support, IndexTuple itup, It
}
/* Find neighbors for element */
HnswFindElementNeighbors(base, element, entryPoint, index, support, m, efConstruction, false, false);
HnswFindElementNeighbors(base, element, entryPoint, index, support, m, efConstruction, false, building);
/* Update graph on disk */
UpdateGraphOnDisk(index, support, element, m, efConstruction, entryPoint, building, tupdesc);
UpdateGraphOnDisk(index, support, element, m, entryPoint, building);
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
@@ -757,18 +746,17 @@ HnswInsertTupleOnDisk(Relation index, HnswSupport * support, IndexTuple itup, It
static void
HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid)
{
IndexTuple itup;
Datum value;
const HnswTypeInfo *typeInfo = HnswGetTypeInfo(index);
TupleDesc tupdesc = RelationGetDescr(index);
HnswSupport support;
HnswInitSupport(&support, index);
/* Form index tuple */
if (!HnswFormIndexTuple(&itup, values, isnull, typeInfo, &support, tupdesc))
/* Form index value */
if (!HnswFormIndexValue(&value, values, isnull, typeInfo, &support))
return;
HnswInsertTupleOnDisk(index, &support, itup, heaptid, false, tupdesc);
HnswInsertTupleOnDisk(index, &support, value, heaptid, false);
}
/*

View File

@@ -22,30 +22,26 @@ GetScanItems(IndexScanDesc scan, Datum value)
int m;
HnswElement entryPoint;
char *base = NULL;
bool inMemory = false;
HnswQuery *q = &so->q;
q->value = value;
q->itup = NULL;
q->keyData = scan->keyData;
/* Get m and entry point */
HnswGetMetaPageInfo(index, &m, &entryPoint);
q->value = value;
so->m = m;
if (entryPoint == NULL)
return NIL;
ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, support, false, inMemory));
ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, support, false));
for (int lc = entryPoint->level; lc >= 1; lc--)
{
w = HnswSearchLayer(base, q, ep, 1, lc, index, support, m, false, NULL, inMemory, NULL, NULL, true, NULL);
w = HnswSearchLayer(base, q, ep, 1, lc, index, support, m, false, NULL, NULL, NULL, true, NULL, false);
ep = w;
}
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, support, m, false, NULL, inMemory, &so->v, hnsw_iterative_search != HNSW_ITERATIVE_SEARCH_OFF ? &so->discarded : NULL, true, &so->tuples);
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, support, m, false, NULL, &so->v, hnsw_iterative_scan != HNSW_ITERATIVE_SCAN_OFF ? &so->discarded : NULL, true, &so->tuples, false);
}
/*
@@ -76,7 +72,7 @@ ResumeScanItems(IndexScanDesc scan)
ep = lappend(ep, sc);
}
return HnswSearchLayer(base, &so->q, ep, batch_size, 0, index, &so->support, so->m, false, NULL, false, &so->v, &so->discarded, false, &so->tuples);
return HnswSearchLayer(base, &so->q, ep, batch_size, 0, index, &so->support, so->m, false, NULL, &so->v, &so->discarded, false, &so->tuples, false);
}
/*
@@ -100,12 +96,23 @@ GetScanValue(IndexScanDesc scan)
/* Normalize if needed */
if (so->support.normprocinfo != NULL)
value = HnswNormValue(so->typeInfo, so->support.collation[0], value);
value = HnswNormValue(so->typeInfo, so->support.collation, value);
}
return value;
}
#if defined(HNSW_MEMORY)
/*
* Show memory usage
*/
static void
ShowMemoryUsage(HnswScanOpaque so)
{
elog(INFO, "memory: %zu KB, tuples: " INT64_FORMAT, MemoryContextMemAllocated(so->tmpCtx, false) / 1024, so->tuples);
}
#endif
/*
* Prepare for an index scan
*/
@@ -114,21 +121,29 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
{
IndexScanDesc scan;
HnswScanOpaque so;
double maxMemory;
scan = RelationGetIndexScan(index, nkeys, norderbys);
so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData));
so->typeInfo = HnswGetTypeInfo(index);
so->first = true;
so->v.tids = NULL;
so->discarded = NULL;
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw scan temporary context",
ALLOCSET_DEFAULT_SIZES);
/* Set support functions */
HnswInitSupport(&so->support, index);
/*
* Use a lower max allocation size than default to allow scanning more
* tuples for iterative search before exceeding work_mem
*/
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw scan temporary context",
0, 8 * 1024, 256 * 1024);
/* Calculate max memory */
/* Add 256 extra bytes to fill last block when close */
maxMemory = (double) work_mem * hnsw_scan_mem_multiplier * 1024.0 + 256;
so->maxMemory = Min(maxMemory, (double) SIZE_MAX);
scan->opaque = so;
return scan;
@@ -142,13 +157,10 @@ hnswrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int no
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
if (so->v.tids != NULL)
tidhash_reset(so->v.tids);
if (so->discarded != NULL)
pairingheap_reset(so->discarded);
so->first = true;
/* v and discarded are allocated in tmpCtx */
so->v.tids = NULL;
so->discarded = NULL;
so->tuples = 0;
so->previousDistance = -get_float8_infinity();
MemoryContextReset(so->tmpCtx);
@@ -181,6 +193,10 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
/* Count index scan for stats */
pgstat_count_index_scan(scan->indexRelation);
#if PG_VERSION_NUM >= 180000
if (scan->instrument)
scan->instrument->nsearches++;
#endif
/* Safety check */
if (scan->orderByData == NULL)
@@ -208,7 +224,7 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
so->first = false;
#if defined(HNSW_MEMORY)
elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(so->tmpCtx, false) / 1024);
ShowMemoryUsage(so);
#endif
}
@@ -221,15 +237,15 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
if (list_length(so->w) == 0)
{
if (hnsw_iterative_search == HNSW_ITERATIVE_SEARCH_OFF)
if (hnsw_iterative_scan == HNSW_ITERATIVE_SCAN_OFF)
break;
/* Empty index */
if (so->discarded == NULL)
break;
/* Reached max number of additional tuples */
if (hnsw_iterative_search_max_tuples != -1 && so->tuples >= hnsw_iterative_search_max_tuples)
/* Reached max number of tuples or memory limit */
if (so->tuples >= hnsw_max_scan_tuples || MemoryContextMemAllocated(so->tmpCtx, false) > so->maxMemory)
{
if (pairingheap_is_empty(so->discarded))
break;
@@ -237,21 +253,6 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
/* Return remaining tuples */
so->w = lappend(so->w, HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded)));
}
/* Prevent scans from consuming too much memory */
else if (MemoryContextMemAllocated(so->tmpCtx, false) > (Size) work_mem * 1024L)
{
if (pairingheap_is_empty(so->discarded))
{
ereport(DEBUG1,
(errmsg("hnsw index scan exceeded work_mem after " INT64_FORMAT " tuples", so->tuples),
errhint("Increase work_mem to scan more tuples.")));
break;
}
/* Return remaining tuples */
so->w = lappend(so->w, HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded)));
}
else
{
/*
@@ -270,7 +271,7 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
#if defined(HNSW_MEMORY)
elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(so->tmpCtx, false) / 1024);
ShowMemoryUsage(so);
#endif
}
@@ -282,12 +283,12 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
element = HnswPtrAccess(base, sc->element);
/* Move to next element if no valid heap TIDs */
if (!sc->matches || element->heaptidsLength == 0)
if (element->heaptidsLength == 0)
{
so->w = list_delete_last(so->w);
/* Mark memory as free for next iteration */
if (hnsw_iterative_search != HNSW_ITERATIVE_SEARCH_OFF)
if (hnsw_iterative_scan != HNSW_ITERATIVE_SCAN_OFF)
{
pfree(element);
pfree(sc);
@@ -298,7 +299,7 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
heaptid = &element->heaptids[--element->heaptidsLength];
if (hnsw_iterative_search == HNSW_ITERATIVE_SEARCH_STRICT)
if (hnsw_iterative_scan == HNSW_ITERATIVE_SCAN_STRICT)
{
if (sc->distance < so->previousDistance)
continue;

View File

@@ -15,6 +15,14 @@
#include "utils/memdebug.h"
#include "utils/rel.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 170000
#include "storage/read_stream.h"
#endif
#if PG_VERSION_NUM < 170000
static inline uint64
murmurhash64(uint64 data)
@@ -146,39 +154,11 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
void
HnswInitSupport(HnswSupport * support, Relation index)
{
support->procinfo[0] = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
if (IndexRelationGetNumberOfKeyAttributes(index) > 1)
support->procinfo[1] = index_getprocinfo(index, 2, HNSW_ATTRIBUTE_DISTANCE_PROC);
support->collation = index->rd_indcollation;
support->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
support->collation = index->rd_indcollation[0];
support->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
}
/*
* Get element tuple size
*/
Size
HnswGetElementTupleSize(char *base, HnswElement element, bool useIndexTuple)
{
Size size;
if (useIndexTuple)
{
IndexTuple itup = HnswPtrAccess(base, element->itup);
size = IndexTupleSize(itup);
}
else
{
Pointer valuePtr = HnswPtrAccess(base, element->value);
size = VARSIZE_ANY(valuePtr);
}
return HNSW_ELEMENT_TUPLE_SIZE(size);
}
/*
* Normalize value
*/
@@ -194,38 +174,7 @@ HnswNormValue(const HnswTypeInfo * typeInfo, Oid collation, Datum value)
bool
HnswCheckNorm(HnswSupport * support, Datum value)
{
return DatumGetFloat8(FunctionCall1Coll(support->normprocinfo, support->collation[0], value)) > 0;
}
/*
* Check if index tuples are equal
*/
bool
HnswIndexTupleIsEqual(IndexTuple a, IndexTuple b, TupleDesc tupdesc)
{
for (int i = 0; i < tupdesc->natts; i++)
{
bool nullA;
bool nullB;
Datum datumA = index_getattr(a, i + 1, tupdesc, &nullA);
Datum datumB = index_getattr(b, i + 1, tupdesc, &nullB);
if (nullA || nullB)
{
if (nullA != nullB)
return false;
}
else
{
Form_pg_attribute att = TupleDescAttr(tupdesc, i);
if (!datumIsEqual(datumA, datumB, att->attbyval, att->attlen))
return false;
}
}
return true;
return DatumGetFloat8(FunctionCall1Coll(support->normprocinfo, support->collation, value)) > 0;
}
/*
@@ -316,7 +265,6 @@ HnswInitElement(char *base, ItemPointer heaptid, int m, double ml, int maxLevel,
HnswInitNeighbors(base, element, m, allocator);
HnswPtrStore(base, element->value, (Pointer) NULL);
HnswPtrStore(base, element->itup, (IndexTuple) NULL);
return element;
}
@@ -343,7 +291,6 @@ HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno)
element->offno = offno;
HnswPtrStore(base, element->neighbors, (HnswNeighborArrayPtr *) NULL);
HnswPtrStore(base, element->value, (Pointer) NULL);
HnswPtrStore(base, element->itup, (IndexTuple) NULL);
return element;
}
@@ -456,13 +403,11 @@ HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, Bloc
}
/*
* Form index tuple
* Form index value
*/
bool
HnswFormIndexTuple(IndexTuple *out, Datum *values, bool *isnull, const HnswTypeInfo * typeInfo, HnswSupport * support, TupleDesc tupdesc)
HnswFormIndexValue(Datum *out, Datum *values, bool *isnull, const HnswTypeInfo * typeInfo, HnswSupport * support)
{
Datum newValues[2];
/* Detoast once for all calls */
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
@@ -476,14 +421,10 @@ HnswFormIndexTuple(IndexTuple *out, Datum *values, bool *isnull, const HnswTypeI
if (!HnswCheckNorm(support, value))
return false;
value = HnswNormValue(typeInfo, support->collation[0], value);
value = HnswNormValue(typeInfo, support->collation, value);
}
newValues[0] = value;
for (int i = 1; i < tupdesc->natts; i++)
newValues[i] = values[i];
*out = index_form_tuple(tupdesc, newValues, isnull);
*out = value;
return true;
}
@@ -492,8 +433,10 @@ HnswFormIndexTuple(IndexTuple *out, Datum *values, bool *isnull, const HnswTypeI
* Set element tuple, except for neighbor info
*/
void
HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element, bool useIndexTuple)
HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element)
{
Pointer valuePtr = HnswPtrAccess(base, element->value);
etup->type = HNSW_ELEMENT_TUPLE_TYPE;
etup->level = element->level;
etup->deleted = 0;
@@ -505,19 +448,7 @@ HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element, bool
else
ItemPointerSetInvalid(&etup->heaptids[i]);
}
if (useIndexTuple)
{
IndexTuple itup = HnswPtrAccess(base, element->itup);
memcpy(&etup->data, itup, IndexTupleSize(itup));
}
else
{
Pointer valuePtr = HnswPtrAccess(base, element->value);
memcpy(&etup->data, valuePtr, VARSIZE_ANY(valuePtr));
}
memcpy(&etup->data, valuePtr, VARSIZE_ANY(valuePtr));
}
/*
@@ -559,7 +490,7 @@ HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m)
* Load an element from a tuple
*/
void
HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec, Relation index)
HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec)
{
element->level = etup->level;
element->deleted = etup->deleted;
@@ -583,135 +514,31 @@ HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHe
if (loadVec)
{
char *base = NULL;
Datum value = datumCopy(PointerGetDatum(&etup->data), false, -1);
if (HnswUseIndexTuple(index))
{
IndexTuple itup = CopyIndexTuple((IndexTuple) &etup->data);
TupleDesc tupdesc = RelationGetDescr(index);
bool unused;
HnswPtrStore(base, element->itup, itup);
HnswPtrStore(base, element->value, DatumGetPointer(index_getattr(itup, 1, tupdesc, &unused)));
}
else
{
Datum value = datumCopy(PointerGetDatum(&etup->data), false, -1);
HnswPtrStore(base, element->value, DatumGetPointer(value));
}
HnswPtrStore(base, element->value, DatumGetPointer(value));
}
}
/*
* Get the attribute distance
*/
static inline double
AttributeDistance(double e)
{
/* TODO Better bias */
/* must be >> max(w * g) + 1 / log10(2) */
double bias = 4.32;
return e > 0 ? bias - 1.0 / log10(e + 1) : 0;
}
/*
* Calculate the distance between values
*/
static double
HnswGetDistance(IndexTuple itup, Datum vec, HnswQuery * q, Relation index, HnswSupport * support, bool *matches)
static inline double
HnswGetDistance(Datum a, Datum b, HnswSupport * support)
{
double g;
if (DatumGetPointer(q->value) == NULL)
g = 0;
else
g = DatumGetFloat8(FunctionCall2Coll(support->procinfo[0], support->collation[0], q->value, vec));
Assert(PointerIsValid(matches));
*matches = true;
if (IndexRelationGetNumberOfKeyAttributes(index) > 1)
{
double w = 0.25;
double e = 0.0;
TupleDesc tupdesc = RelationGetDescr(index);
if (q->keyData)
{
/* TODO need to pass length of key data */
int keyCount = 1;
for (int i = 0; i < keyCount; i++)
{
ScanKey key = &q->keyData[i];
bool isnull;
Datum value = index_getattr(itup, key->sk_attno, tupdesc, &isnull);
bool attnull = key->sk_flags & SK_ISNULL;
if (isnull || attnull)
{
if (isnull != attnull)
{
e += 1000;
*matches = false;
}
}
else if (!DatumGetBool(FunctionCall2Coll(&key->sk_func, key->sk_collation, value, key->sk_argument)))
{
double ei = fabs(DatumGetFloat8(FunctionCall2Coll(support->procinfo[key->sk_attno - 1], support->collation[key->sk_attno - 1], value, key->sk_argument)));
if (ei > 0)
e += ei;
else
/* Distance is zero for inequality */
e += 1000;
*matches = false;
}
}
return w * g + AttributeDistance(e);
}
else if (q->itup)
{
int keyCount = IndexRelationGetNumberOfKeyAttributes(index) - 1;
for (int i = 0; i < keyCount; i++)
{
bool isnull;
bool attnull;
Datum value = index_getattr(itup, i + 2, tupdesc, &isnull);
Datum value2 = index_getattr(q->itup, i + 2, tupdesc, &attnull);
if (isnull || attnull)
{
if (isnull != attnull)
e += 1000;
}
else
e += fabs(DatumGetFloat8(FunctionCall2Coll(support->procinfo[i + 1], support->collation[i + 1], value, value2)));
}
return w * g + AttributeDistance(e);
}
}
return g;
return DatumGetFloat8(FunctionCall2Coll(support->procinfo, support->collation, a, b));
}
/*
* Load an element and optionally get its distance from q
*/
static void
HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, double *distance, bool *matches, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, double *maxDistance, HnswElement * element)
HnswLoadElementImpl(Buffer buf, OffsetNumber offno, double *distance, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, double *maxDistance, HnswElement * element)
{
Buffer buf;
Page page;
HnswElementTuple etup;
/* Read vector */
buf = ReadBuffer(index, blkno);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
@@ -722,32 +549,19 @@ HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, double *distance, boo
/* Calculate distance */
if (distance != NULL)
{
IndexTuple itup = NULL;
Datum value;
if (HnswUseIndexTuple(index))
{
TupleDesc tupdesc = RelationGetDescr(index);
bool unused;
itup = (IndexTuple) &etup->data;
value = index_getattr(itup, 1, tupdesc, &unused);
}
if (DatumGetPointer(q->value) == NULL)
*distance = 0;
else
{
value = PointerGetDatum(&etup->data);
}
*distance = HnswGetDistance(itup, value, q, index, support, matches);
*distance = HnswGetDistance(q->value, PointerGetDatum(&etup->data), support);
}
/* Load element */
if (distance == NULL || maxDistance == NULL || *distance < *maxDistance)
{
if (*element == NULL)
*element = HnswInitElementFromBlock(blkno, offno);
*element = HnswInitElementFromBlock(BufferGetBlockNumber(buf), offno);
HnswLoadElementFromTuple(*element, etup, true, loadVec, index);
HnswLoadElementFromTuple(*element, etup, true, loadVec);
}
UnlockReleaseBuffer(buf);
@@ -757,37 +571,52 @@ HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, double *distance, boo
* Load an element and optionally get its distance from q
*/
void
HnswLoadElement(HnswElement element, double *distance, bool *matches, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, double *maxDistance)
HnswLoadElement(HnswElement element, double *distance, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, double *maxDistance)
{
HnswLoadElementImpl(element->blkno, element->offno, distance, matches, q, index, support, loadVec, maxDistance, &element);
Buffer buf = ReadBuffer(index, element->blkno);
HnswLoadElementImpl(buf, element->offno, distance, q, index, support, loadVec, maxDistance, &element);
}
/*
* Get the distance for an element
*/
static double
GetElementDistance(char *base, HnswElement element, bool *matches, HnswQuery * q, Relation index, HnswSupport * support)
GetElementDistance(char *base, HnswElement element, HnswQuery * q, HnswSupport * support)
{
Datum value = HnswGetValue(base, element);
IndexTuple itup = HnswPtrAccess(base, element->itup);
return HnswGetDistance(itup, value, q, index, support, matches);
return HnswGetDistance(q->value, value, support);
}
/*
* Allocate a search candidate
*/
static HnswSearchCandidate *
HnswInitSearchCandidate(char *base, HnswElement element, double distance)
{
HnswSearchCandidate *sc = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, sc->element, element);
sc->distance = distance;
return sc;
}
/*
* Create a candidate for the entry point
*/
HnswSearchCandidate *
HnswEntryCandidate(char *base, HnswElement entryPoint, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, bool inMemory)
HnswEntryCandidate(char *base, HnswElement entryPoint, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec)
{
HnswSearchCandidate *sc = palloc(sizeof(HnswSearchCandidate));
bool inMemory = index == NULL;
double distance;
HnswPtrStore(base, sc->element, entryPoint);
if (inMemory)
sc->distance = GetElementDistance(base, entryPoint, &sc->matches, q, index, support);
distance = GetElementDistance(base, entryPoint, q, support);
else
HnswLoadElement(entryPoint, &sc->distance, &sc->matches, q, index, support, loadVec, NULL);
return sc;
HnswLoadElement(entryPoint, &distance, q, index, support, loadVec, NULL);
return HnswInitSearchCandidate(base, entryPoint, distance);
}
/*
@@ -986,11 +815,31 @@ HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *u
}
}
#if PG_VERSION_NUM >= 170000
/*
* Get next block number for read stream
*/
static BlockNumber
HnswReadStreamNextBlock(ReadStream *stream, void *callback_private_data, void *per_buffer_data)
{
HnswReadStreamData *streamData = callback_private_data;
OffsetNumber *offno = per_buffer_data;
HnswUnvisited *uv;
if (streamData->visited == streamData->unvisitedLength)
return InvalidBlockNumber;
uv = &streamData->unvisited[streamData->visited++];
*offno = ItemPointerGetOffsetNumber(&uv->indextid);
return ItemPointerGetBlockNumber(&uv->indextid);
}
#endif
/*
* Algorithm 2 from paper
*/
List *
HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement, bool inMemory, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples)
HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples, bool maintenance)
{
List *w = NIL;
pairingheap *C = pairingheap_allocate(CompareNearestCandidates, NULL);
@@ -1003,8 +852,28 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
int lm = HnswGetLayerM(m, lc);
HnswUnvisited *unvisited = palloc(lm * sizeof(HnswUnvisited));
int unvisitedLength;
uint64 additional = 0;
uint64 maxAdditional = q->keyData && lc == 0 ? 10000 : 0;
bool inMemory = index == NULL;
#if PG_VERSION_NUM >= 170000
HnswReadStreamData streamData;
ReadStream *stream = NULL;
if (!inMemory)
{
int flags = READ_STREAM_DEFAULT;
if (maintenance)
{
flags |= READ_STREAM_MAINTENANCE;
}
#if PG_VERSION_NUM >= 180000
flags |= READ_STREAM_USE_BATCHING;
#endif
stream = read_stream_begin_relation(flags, NULL, index, MAIN_FORKNUM, HnswReadStreamNextBlock, &streamData, sizeof(OffsetNumber));
}
#endif
if (v == NULL)
{
@@ -1037,6 +906,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
{
AddToVisited(base, v, sc->element, inMemory, &found);
/* OK to count elements instead of tuples */
if (tuples != NULL)
(*tuples)++;
}
@@ -1044,10 +914,6 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
pairingheap_add(C, &sc->c_node);
pairingheap_add(W, &sc->w_node);
/* Do not count elements that do not match filter towards ef */
if (!sc->matches && ++additional <= maxAdditional)
continue;
/*
* Do not count elements being deleted towards ef when vacuuming. It
* would be ideal to do this for inserts as well, but this could
@@ -1071,35 +937,67 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
if (inMemory)
HnswLoadUnvisitedFromMemory(base, cElement, unvisited, &unvisitedLength, v, lc, localNeighborhood, neighborhoodSize);
else
{
HnswLoadUnvisitedFromDisk(cElement, unvisited, &unvisitedLength, v, index, m, lm, lc);
#if PG_VERSION_NUM >= 170000
read_stream_resume(stream);
streamData.unvisited = unvisited;
streamData.unvisitedLength = unvisitedLength;
streamData.visited = 0;
#endif
}
/* OK to count elements instead of tuples */
if (tuples != NULL)
(*tuples) += unvisitedLength;
for (int i = 0; i < unvisitedLength; i++)
for (int i = 0;; i++)
{
HnswElement eElement;
HnswSearchCandidate *e;
double eDistance;
bool eMatches;
bool alwaysAdd = wlen < ef;
f = HnswGetSearchCandidate(w_node, pairingheap_first(W));
if (inMemory)
{
if (i == unvisitedLength)
break;
eElement = unvisited[i].element;
eDistance = GetElementDistance(base, eElement, &eMatches, q, index, support);
eDistance = GetElementDistance(base, eElement, q, support);
}
else
{
ItemPointer indextid = &unvisited[i].indextid;
BlockNumber blkno = ItemPointerGetBlockNumber(indextid);
OffsetNumber offno = ItemPointerGetOffsetNumber(indextid);
Buffer buf;
OffsetNumber offno;
#if PG_VERSION_NUM >= 170000
void *offnoPtr;
buf = read_stream_next_buffer(stream, &offnoPtr);
if (!BufferIsValid(buf))
break;
offno = *((OffsetNumber *) offnoPtr);
#else
ItemPointer indextid;
if (i == unvisitedLength)
break;
indextid = &unvisited[i].indextid;
buf = ReadBuffer(index, ItemPointerGetBlockNumber(indextid));
offno = ItemPointerGetOffsetNumber(indextid);
#endif
/* Avoid any allocations if not adding */
eElement = NULL;
HnswLoadElementImpl(blkno, offno, &eDistance, &eMatches, q, index, support, inserting, alwaysAdd || discarded != NULL ? NULL : &f->distance, &eElement);
HnswLoadElementImpl(buf, offno, &eDistance, q, index, support, inserting, alwaysAdd || discarded != NULL ? NULL : &f->distance, &eElement);
if (eElement == NULL)
continue;
@@ -1110,9 +1008,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
if (discarded != NULL)
{
/* Create a new candidate */
e = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, e->element, eElement);
e->distance = eDistance;
e = HnswInitSearchCandidate(base, eElement, eDistance);
pairingheap_add(*discarded, &e->w_node);
}
@@ -1124,10 +1020,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
continue;
/* Create a new candidate */
e = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, e->element, eElement);
e->distance = eDistance;
e->matches = eMatches;
e = HnswInitSearchCandidate(base, eElement, eDistance);
pairingheap_add(C, &e->c_node);
pairingheap_add(W, &e->w_node);
@@ -1138,10 +1031,6 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
*/
if (CountElement(skipElement, eElement))
{
/* Do not count elements that do not match filter towards ef */
if (!e->matches && ++additional <= maxAdditional)
continue;
wlen++;
/* No need to decrement wlen */
@@ -1164,6 +1053,11 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
w = lappend(w, sc);
}
#if PG_VERSION_NUM >= 170000
if (!inMemory)
read_stream_end(stream);
#endif
return w;
}
@@ -1219,24 +1113,18 @@ CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b)
* Check if an element is closer to q than any element from R
*/
static bool
CheckElementCloser(char *base, HnswCandidate * e, List *r, Relation index, HnswSupport * support)
CheckElementCloser(char *base, HnswCandidate * e, List *r, HnswSupport * support)
{
HnswElement eElement = HnswPtrAccess(base, e->element);
HnswQuery q;
Datum eValue = HnswGetValue(base, eElement);
ListCell *lc2;
q.value = HnswGetValue(base, eElement);
q.itup = HnswPtrAccess(base, eElement->itup);
q.keyData = NULL;
foreach(lc2, r)
{
HnswCandidate *ri = lfirst(lc2);
HnswElement riElement = HnswPtrAccess(base, ri->element);
Datum riValue = HnswGetValue(base, riElement);
IndexTuple ritup = HnswPtrAccess(base, riElement->itup);
bool matches;
float distance = HnswGetDistance(ritup, riValue, &q, index, support, &matches);
float distance = HnswGetDistance(eValue, riValue, support);
if (distance <= e->distance)
return false;
@@ -1249,7 +1137,7 @@ CheckElementCloser(char *base, HnswCandidate * e, List *r, Relation index, HnswS
* Algorithm 4 from paper
*/
static List *
SelectNeighbors(char *base, List *c, int lm, Relation index, HnswSupport * support, bool *closerSet, HnswCandidate * newCandidate, HnswCandidate * *pruned, bool sortCandidates)
SelectNeighbors(char *base, List *c, int lm, HnswSupport * support, bool *closerSet, HnswCandidate * newCandidate, HnswCandidate * *pruned, bool sortCandidates)
{
List *r = NIL;
List *w = list_copy(c);
@@ -1283,7 +1171,7 @@ SelectNeighbors(char *base, List *c, int lm, Relation index, HnswSupport * suppo
/* Use previous state of r and wd to skip work when possible */
if (mustCalculate)
e->closer = CheckElementCloser(base, e, r, index, support);
e->closer = CheckElementCloser(base, e, r, support);
else if (list_length(added) > 0)
{
/* Keep Valgrind happy for in-memory, parallel builds */
@@ -1296,7 +1184,8 @@ SelectNeighbors(char *base, List *c, int lm, Relation index, HnswSupport * suppo
*/
if (e->closer)
{
e->closer = CheckElementCloser(base, e, added, index, support);
e->closer = CheckElementCloser(base, e, added, support);
if (!e->closer)
removedAny = true;
}
@@ -1308,7 +1197,7 @@ SelectNeighbors(char *base, List *c, int lm, Relation index, HnswSupport * suppo
*/
if (removedAny)
{
e->closer = CheckElementCloser(base, e, r, index, support);
e->closer = CheckElementCloser(base, e, r, support);
if (e->closer)
added = lappend(added, e);
}
@@ -1316,7 +1205,7 @@ SelectNeighbors(char *base, List *c, int lm, Relation index, HnswSupport * suppo
}
else if (e == newCandidate)
{
e->closer = CheckElementCloser(base, e, r, index, support);
e->closer = CheckElementCloser(base, e, r, support);
if (e->closer)
added = lappend(added, e);
}
@@ -1393,7 +1282,7 @@ HnswUpdateConnection(char *base, HnswNeighborArray * neighbors, HnswElement newE
c = lappend(c, &neighbors->items[i]);
c = lappend(c, &newHc);
SelectNeighbors(base, c, lm, index, support, &neighbors->closerSet, &newHc, &pruned, true);
SelectNeighbors(base, c, lm, support, &neighbors->closerSet, &newHc, &pruned, true);
/* Should not happen */
if (pruned == NULL)
@@ -1464,19 +1353,17 @@ 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, bool inMemory)
HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, HnswSupport * support, int m, int efConstruction, bool existing, bool maintenance)
{
List *ep;
List *w;
int level = element->level;
int entryLevel;
HnswQuery q;
HnswElement skipElement = existing ? element : NULL;
bool inMemory = index == NULL;
q.value = HnswGetValue(base, element);
q.itup = HnswPtrAccess(base, element->itup);
q.keyData = NULL;
/* Precompute hash */
if (inMemory)
@@ -1487,13 +1374,13 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
return;
/* Get entry point and level */
ep = list_make1(HnswEntryCandidate(base, entryPoint, &q, index, support, true, inMemory));
ep = list_make1(HnswEntryCandidate(base, entryPoint, &q, index, support, 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, inMemory, NULL, NULL, true, NULL);
w = HnswSearchLayer(base, &q, ep, 1, lc, index, support, m, true, skipElement, NULL, NULL, true, NULL, maintenance);
ep = w;
}
@@ -1512,7 +1399,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
List *lw = NIL;
ListCell *lc2;
w = HnswSearchLayer(base, &q, ep, efConstruction, lc, index, support, m, true, skipElement, inMemory, NULL, NULL, true, NULL);
w = HnswSearchLayer(base, &q, ep, efConstruction, lc, index, support, m, true, skipElement, NULL, NULL, true, NULL, maintenance);
/* Convert search candidates to candidates */
foreach(lc2, w)
@@ -1536,7 +1423,7 @@ 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, index, support, &HnswGetNeighbors(base, element, lc)->closerSet, NULL, NULL, false);
neighbors = SelectNeighbors(base, lw, lm, support, &HnswGetNeighbors(base, element, lc)->closerSet, NULL, NULL, false);
AddConnections(base, element, neighbors, lc);
@@ -1592,7 +1479,7 @@ hnsw_halfvec_support(PG_FUNCTION_ARGS)
};
PG_RETURN_POINTER(&typeInfo);
};
}
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_bit_support);
Datum
@@ -1605,7 +1492,7 @@ hnsw_bit_support(PG_FUNCTION_ARGS)
};
PG_RETURN_POINTER(&typeInfo);
};
}
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_sparsevec_support);
Datum
@@ -1618,4 +1505,4 @@ hnsw_sparsevec_support(PG_FUNCTION_ARGS)
};
PG_RETURN_POINTER(&typeInfo);
};
}

View File

@@ -9,6 +9,14 @@
#include "storage/lmgr.h"
#include "utils/memutils.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 180000
#define vacuum_delay_point() vacuum_delay_point(false)
#endif
/*
* Check if deleted list contains an index TID
*/
@@ -204,7 +212,7 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
element->heaptidsLength = 0;
/* Find neighbors for element, skipping itself */
HnswFindElementNeighbors(base, element, entryPoint, index, support, m, efConstruction, true, false);
HnswFindElementNeighbors(base, element, entryPoint, index, support, m, efConstruction, true, true);
/* Zero memory for each element */
MemSet(ntup, 0, HNSW_TUPLE_ALLOC_SIZE);
@@ -256,7 +264,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
LockPage(index, HNSW_UPDATE_LOCK, ShareLock);
/* Load element */
HnswLoadElement(highestPoint, NULL, NULL, NULL, index, support, true, NULL);
HnswLoadElement(highestPoint, NULL, NULL, index, support, true, NULL);
/* Repair if needed */
if (NeedsUpdated(vacuumstate, highestPoint))
@@ -294,7 +302,7 @@ 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, NULL, index, support, true, NULL);
HnswLoadElement(entryPoint, NULL, NULL, index, support, true, NULL);
if (NeedsUpdated(vacuumstate, entryPoint))
{
@@ -370,7 +378,7 @@ RepairGraph(HnswVacuumState * vacuumstate)
/* Create an element */
element = HnswInitElementFromBlock(blkno, offno);
HnswLoadElementFromTuple(element, etup, false, true, index);
HnswLoadElementFromTuple(element, etup, false, true);
elements = lappend(elements, element);
}
@@ -440,7 +448,6 @@ MarkDeleted(HnswVacuumState * vacuumstate)
BlockNumber insertPage = InvalidBlockNumber;
Relation index = vacuumstate->index;
BufferAccessStrategy bas = vacuumstate->bas;
bool useIndexTuple = HnswUseIndexTuple(index);
/*
* Wait for index scans to complete. Scans before this point may contain
@@ -522,14 +529,7 @@ MarkDeleted(HnswVacuumState * vacuumstate)
/* Overwrite element */
etup->deleted = 1;
if (useIndexTuple)
{
IndexTuple itup = (IndexTuple) &etup->data;
MemSet(itup, 0, IndexTupleSize(itup));
}
else
MemSet(&etup->data, 0, VARSIZE_ANY(&etup->data));
MemSet(&etup->data, 0, VARSIZE_ANY(&etup->data));
/* Overwrite neighbors */
for (int i = 0; i < ntup->count; i++)

View File

@@ -20,6 +20,10 @@
#include "utils/memutils.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h"
#else
@@ -138,7 +142,7 @@ SampleRows(IvfflatBuildState * buildstate)
* Add tuple to sort
*/
static void
AddTupleToSort(Relation index, ItemPointer tid, Datum *values, bool *isnull, IvfflatBuildState * buildstate)
AddTupleToSort(ItemPointer tid, Datum *values, IvfflatBuildState * buildstate)
{
double distance;
double minDistance = DBL_MAX;
@@ -184,11 +188,6 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, bool *isnull, Ivf
slot->tts_isnull[1] = false;
slot->tts_values[2] = value;
slot->tts_isnull[2] = false;
for (int i = 1; i < buildstate->tupdesc->natts; i++)
{
slot->tts_values[2 + i] = values[i];
slot->tts_isnull[2 + i] = isnull[i];
}
ExecStoreVirtualTuple(slot);
/*
@@ -220,7 +219,7 @@ BuildCallback(Relation index, ItemPointer tid, Datum *values,
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
/* Add tuple to sort */
AddTupleToSort(index, tid, values, isnull, buildstate);
AddTupleToSort(tid, values, buildstate);
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
@@ -231,20 +230,19 @@ BuildCallback(Relation index, ItemPointer tid, Datum *values,
* Get index tuple from sort state
*/
static inline void
GetNextTuple(Tuplesortstate *sortstate, TupleDesc tupdesc, TupleTableSlot *slot, Datum *values, bool *isnull, IndexTuple *itup, int *list)
GetNextTuple(Tuplesortstate *sortstate, TupleDesc tupdesc, TupleTableSlot *slot, IndexTuple *itup, int *list)
{
if (tuplesort_gettupleslot(sortstate, true, false, slot, NULL))
{
bool unused;
Datum value;
bool isnull;
*list = DatumGetInt32(slot_getattr(slot, 1, &unused));
for (int i = 0; i < tupdesc->natts; i++)
values[i] = slot_getattr(slot, 3 + i, &isnull[i]);
*list = DatumGetInt32(slot_getattr(slot, 1, &isnull));
value = slot_getattr(slot, 3, &isnull);
/* Form the index tuple */
*itup = index_form_tuple(tupdesc, values, isnull);
(*itup)->t_tid = *((ItemPointer) DatumGetPointer(slot_getattr(slot, 2, &unused)));
*itup = index_form_tuple(tupdesc, &value, &isnull);
(*itup)->t_tid = *((ItemPointer) DatumGetPointer(slot_getattr(slot, 2, &isnull)));
}
else
*list = -1;
@@ -262,14 +260,12 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
TupleTableSlot *slot = MakeSingleTupleTableSlot(buildstate->sortdesc, &TTSOpsMinimalTuple);
TupleDesc tupdesc = buildstate->tupdesc;
Datum *values = palloc(tupdesc->natts * sizeof(Datum));
bool *isnull = palloc(tupdesc->natts * sizeof(bool));
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_LOAD);
pgstat_progress_update_param(PROGRESS_CREATEIDX_TUPLES_TOTAL, buildstate->indtuples);
GetNextTuple(buildstate->sortstate, tupdesc, slot, values, isnull, &itup, &list);
GetNextTuple(buildstate->sortstate, tupdesc, slot, &itup, &list);
for (int i = 0; i < buildstate->centers->length; i++)
{
@@ -305,7 +301,7 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
pgstat_progress_update_param(PROGRESS_CREATEIDX_TUPLES_DONE, ++inserted);
GetNextTuple(buildstate->sortstate, tupdesc, slot, values, isnull, &itup, &list);
GetNextTuple(buildstate->sortstate, tupdesc, slot, &itup, &list);
}
insertPage = BufferGetBlockNumber(buf);
@@ -315,9 +311,6 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
/* Set the start and insert pages */
IvfflatUpdateList(index, buildstate->listInfo[i], insertPage, InvalidBlockNumber, startPage, forkNum);
}
pfree(values);
pfree(isnull);
}
/*
@@ -368,11 +361,10 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
errmsg("dimensions must be greater than one for this opclass")));
/* Create tuple description for sorting */
buildstate->sortdesc = CreateTemplateTupleDesc(2 + buildstate->tupdesc->natts);
buildstate->sortdesc = CreateTemplateTupleDesc(3);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 1, "list", INT4OID, -1, 0);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
for (int i = 0; i < buildstate->tupdesc->natts; i++)
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) (3 + i), NULL, buildstate->tupdesc->attrs[i].atttypid, -1, 0);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 3, "vector", TupleDescAttr(buildstate->tupdesc, 0)->atttypid, -1, 0);
buildstate->slot = MakeSingleTupleTableSlot(buildstate->sortdesc, &TTSOpsVirtual);
@@ -482,8 +474,8 @@ CreateMetaPage(Relation index, int dimensions, int lists, ForkNumber forkNum)
* Create list pages
*/
static void
CreateListPages(Relation index, VectorArray centers, int dimensions,
int lists, ForkNumber forkNum, ListInfo * *listInfo)
CreateListPages(Relation index, VectorArray centers, int lists,
ForkNumber forkNum, ListInfo * *listInfo)
{
Buffer buf;
Page page;
@@ -1016,7 +1008,7 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
/* Create pages */
CreateMetaPage(index, buildstate->dimensions, buildstate->lists, forkNum);
CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo);
CreateListPages(index, buildstate->centers, buildstate->lists, forkNum, &buildstate->listInfo);
CreateEntryPages(buildstate, forkNum);
/* Write WAL for initialization fork since GenericXLog functions do not */
@@ -1035,6 +1027,10 @@ ivfflatbuild(Relation heap, Relation index, IndexInfo *indexInfo)
IndexBuildResult *result;
IvfflatBuildState buildstate;
#ifdef IVFFLAT_BENCH
SeedRandom(42);
#endif
BuildIndex(heap, index, indexInfo, &buildstate, MAIN_FORKNUM);
result = (IndexBuildResult *) palloc(sizeof(IndexBuildResult));

View File

@@ -17,13 +17,13 @@
#endif
int ivfflat_probes;
int ivfflat_iterative_search;
int ivfflat_iterative_search_max_probes;
int ivfflat_iterative_scan;
int ivfflat_max_probes;
static relopt_kind ivfflat_relopt_kind;
static const struct config_enum_entry ivfflat_iterative_search_options[] = {
{"off", IVFFLAT_ITERATIVE_SEARCH_OFF, false},
{"on", IVFFLAT_ITERATIVE_SEARCH_RELAXED, false},
static const struct config_enum_entry ivfflat_iterative_scan_options[] = {
{"off", IVFFLAT_ITERATIVE_SCAN_OFF, false},
{"relaxed_order", IVFFLAT_ITERATIVE_SCAN_RELAXED, false},
{NULL, 0, false}
};
@@ -41,13 +41,14 @@ IvfflatInit(void)
"Valid range is 1..lists.", &ivfflat_probes,
IVFFLAT_DEFAULT_PROBES, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
DefineCustomEnumVariable("ivfflat.iterative_search", "Sets whether to use iterative search",
NULL, &ivfflat_iterative_search,
IVFFLAT_ITERATIVE_SEARCH_OFF, ivfflat_iterative_search_options, PGC_USERSET, 0, NULL, NULL, NULL);
DefineCustomEnumVariable("ivfflat.iterative_scan", "Sets the mode for iterative scans",
NULL, &ivfflat_iterative_scan,
IVFFLAT_ITERATIVE_SCAN_OFF, ivfflat_iterative_scan_options, PGC_USERSET, 0, NULL, NULL, NULL);
DefineCustomIntVariable("ivfflat.iterative_search_max_probes", "Sets the max number of probes for iterative search",
"Zero sets to the number of lists", &ivfflat_iterative_search_max_probes,
0, 0, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
/* If this is less than probes, probes is used */
DefineCustomIntVariable("ivfflat.max_probes", "Sets the max number of probes for iterative scans",
NULL, &ivfflat_max_probes,
IVFFLAT_MAX_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
MarkGUCPrefixReserved("ivfflat");
}
@@ -91,13 +92,17 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
Relation index;
/* Never use index without order */
if (path->indexorderbys == NULL)
if (path->indexorderbys == NIL)
{
*indexStartupCost = get_float8_infinity();
*indexTotalCost = get_float8_infinity();
*indexSelectivity = 0;
*indexCorrelation = 0;
*indexPages = 0;
#if PG_VERSION_NUM >= 180000
/* See "On disable_cost" thread on pgsql-hackers */
path->path.disabled_nodes = 2;
#endif
return;
}
@@ -181,6 +186,11 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amoptsprocnum = 0;
amroutine->amcanorder = false;
amroutine->amcanorderbyop = true;
#if PG_VERSION_NUM >= 180000
amroutine->amcanhash = false;
amroutine->amconsistentequality = false;
amroutine->amconsistentordering = false;
#endif
amroutine->amcanbackward = false; /* can change direction mid-scan */
amroutine->amcanunique = false;
amroutine->amcanmulticol = false;
@@ -213,6 +223,9 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amvacuumcleanup = ivfflatvacuumcleanup;
amroutine->amcanreturn = NULL; /* tuple not included in heapsort */
amroutine->amcostestimate = ivfflatcostestimate;
#if PG_VERSION_NUM >= 180000
amroutine->amgettreeheight = NULL;
#endif
amroutine->amoptions = ivfflatoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
amroutine->ambuildphasename = ivfflatbuildphasename;
@@ -233,5 +246,10 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->aminitparallelscan = NULL;
amroutine->amparallelrescan = NULL;
#if PG_VERSION_NUM >= 180000
amroutine->amtranslatestrategy = NULL;
amroutine->amtranslatecmptype = NULL;
#endif
PG_RETURN_POINTER(amroutine);
}

View File

@@ -13,6 +13,10 @@
#include "utils/tuplesort.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 150000
#include "common/pg_prng.h"
#endif
@@ -73,21 +77,23 @@
#if PG_VERSION_NUM >= 150000
#define RandomDouble() pg_prng_double(&pg_global_prng_state)
#define RandomInt() pg_prng_uint32(&pg_global_prng_state)
#define SeedRandom(seed) pg_prng_seed(&pg_global_prng_state, seed)
#else
#define RandomDouble() (((double) random()) / MAX_RANDOM_VALUE)
#define RandomInt() random()
#define SeedRandom(seed) srandom(seed)
#endif
/* Variables */
extern int ivfflat_probes;
extern int ivfflat_iterative_search;
extern int ivfflat_iterative_search_max_probes;
extern int ivfflat_iterative_scan;
extern int ivfflat_max_probes;
typedef enum IvfflatIterativeSearchType
typedef enum IvfflatIterativeScanMode
{
IVFFLAT_ITERATIVE_SEARCH_OFF,
IVFFLAT_ITERATIVE_SEARCH_RELAXED
} IvfflatIterativeSearchType;
IVFFLAT_ITERATIVE_SCAN_OFF,
IVFFLAT_ITERATIVE_SCAN_RELAXED
} IvfflatIterativeScanMode;
typedef struct VectorArrayData
{
@@ -260,6 +266,7 @@ typedef struct IvfflatScanOpaqueData
int dimensions;
bool first;
Datum value;
MemoryContext tmpCtx;
/* Sorting */
Tuplesortstate *sortstate;
@@ -278,7 +285,7 @@ typedef struct IvfflatScanOpaqueData
pairingheap *listQueue;
BlockNumber *listPages;
int listIndex;
IvfflatScanList lists[FLEXIBLE_ARRAY_MEMBER]; /* must come last */
IvfflatScanList *lists;
} IvfflatScanOpaqueData;
typedef IvfflatScanOpaqueData * IvfflatScanOpaque;

View File

@@ -65,7 +65,7 @@ FindInsertPage(Relation index, Datum *values, BlockNumber *insertPage, ListInfo
* Insert a tuple into the index
*/
static void
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid)
{
const IvfflatTypeInfo *typeInfo = IvfflatGetTypeInfo(index);
IndexTuple itup;
@@ -78,8 +78,6 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
BlockNumber insertPage = InvalidBlockNumber;
ListInfo listInfo;
BlockNumber originalInsertPage;
TupleDesc tupdesc = RelationGetDescr(index);
Datum *newValues = palloc(tupdesc->natts * sizeof(Datum));
/* Detoast once for all calls */
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
@@ -104,12 +102,8 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
Assert(BlockNumberIsValid(insertPage));
originalInsertPage = insertPage;
newValues[0] = value;
for (int i = 1; i < tupdesc->natts; i++)
newValues[i] = values[i];
/* Form tuple */
itup = index_form_tuple(tupdesc, newValues, isnull);
itup = index_form_tuple(RelationGetDescr(index), &value, isnull);
itup->t_tid = *heap_tid;
/* Get tuple size */
@@ -210,7 +204,7 @@ ivfflatinsert(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid,
oldCtx = MemoryContextSwitchTo(insertCtx);
/* Insert tuple */
InsertTuple(index, values, isnull, heap_tid, heap);
InsertTuple(index, values, isnull, heap_tid);
/* Delete memory context */
MemoryContextSwitchTo(oldCtx);

View File

@@ -13,6 +13,10 @@
#include "utils/memutils.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/*
* Initialize with kmeans++
*

View File

@@ -10,10 +10,7 @@
#include "miscadmin.h"
#include "pgstat.h"
#include "storage/bufmgr.h"
#ifdef IVFFLAT_MEMORY
#include "utils/memutils.h"
#endif
#define GetScanList(ptr) pairingheap_container(IvfflatScanList, ph_node, ptr)
#define GetScanListConst(ptr) pairingheap_const_container(IvfflatScanList, ph_node, ptr)
@@ -117,7 +114,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
TupleDesc tupdesc = RelationGetDescr(scan->indexRelation);
double tuples = 0;
TupleTableSlot *slot = so->vslot;
int batchProbes = 0;
@@ -164,8 +160,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
ExecStoreVirtualTuple(slot);
tuplesort_puttupleslot(so->sortstate, slot);
tuples++;
}
searchPage = IvfflatPageGetOpaque(page)->nextblkno;
@@ -174,12 +168,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
}
}
if (tuples < 100 && ivfflat_iterative_search == IVFFLAT_ITERATIVE_SEARCH_OFF)
ereport(DEBUG1,
(errmsg("index scan found few tuples"),
errdetail("Index may have been created with little data."),
errhint("Recreate the index and possibly decrease lists.")));
tuplesort_performsort(so->sortstate);
#if defined(IVFFLAT_MEMORY)
@@ -221,7 +209,13 @@ GetScanValue(IndexScanDesc scan)
/* Normalize if needed */
if (so->normprocinfo != NULL)
{
MemoryContext oldCtx = MemoryContextSwitchTo(so->tmpCtx);
value = IvfflatNormValue(so->typeInfo, so->collation, value);
MemoryContextSwitchTo(oldCtx);
}
}
return value;
@@ -253,26 +247,25 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
int dimensions;
int probes = ivfflat_probes;
int maxProbes;
MemoryContext oldCtx;
scan = RelationGetIndexScan(index, nkeys, norderbys);
/* Get lists and dimensions from metapage */
IvfflatGetMetaPageInfo(index, &lists, &dimensions);
if (probes > lists)
probes = lists;
if (ivfflat_iterative_search != IVFFLAT_ITERATIVE_SEARCH_OFF)
{
if (ivfflat_iterative_search_max_probes == 0)
maxProbes = lists;
else
maxProbes = Min(ivfflat_iterative_search_max_probes, lists);
}
if (ivfflat_iterative_scan != IVFFLAT_ITERATIVE_SCAN_OFF)
maxProbes = Max(ivfflat_max_probes, probes);
else
maxProbes = probes;
so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + maxProbes * sizeof(IvfflatScanList));
if (probes > lists)
probes = lists;
if (maxProbes > lists)
maxProbes = lists;
so = (IvfflatScanOpaque) palloc(sizeof(IvfflatScanOpaqueData));
so->typeInfo = IvfflatGetTypeInfo(index);
so->first = true;
so->probes = probes;
@@ -284,6 +277,12 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
so->normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
so->collation = index->rd_indcollation[0];
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat scan temporary context",
ALLOCSET_DEFAULT_SIZES);
oldCtx = MemoryContextSwitchTo(so->tmpCtx);
/* Create tuple description for sorting */
so->tupdesc = CreateTemplateTupleDesc(2);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
@@ -306,6 +305,9 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
so->listQueue = pairingheap_allocate(CompareLists, scan);
so->listPages = palloc(maxProbes * sizeof(BlockNumber));
so->listIndex = 0;
so->lists = palloc(maxProbes * sizeof(IvfflatScanList));
MemoryContextSwitchTo(oldCtx);
scan->opaque = so;
@@ -353,6 +355,10 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
/* Count index scan for stats */
pgstat_count_index_scan(scan->indexRelation);
#if PG_VERSION_NUM >= 180000
if (scan->instrument)
scan->instrument->nsearches++;
#endif
/* Safety check */
if (scan->orderByData == NULL)
@@ -368,8 +374,6 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
IvfflatBench("GetScanItems", GetScanItems(scan, value));
so->first = false;
so->value = value;
/* TODO clean up if we allocated a new value */
}
while (!tuplesort_gettupleslot(so->sortstate, true, false, so->mslot, NULL))
@@ -396,13 +400,10 @@ ivfflatendscan(IndexScanDesc scan)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
pairingheap_free(so->listQueue);
pfree(so->listPages);
/* Free any temporary files */
tuplesort_end(so->sortstate);
FreeAccessStrategy(so->bas);
FreeTupleDesc(so->tupdesc);
/* TODO Free vslot and mslot without freeing TupleDesc */
MemoryContextDelete(so->tmpCtx);
pfree(so);
scan->opaque = NULL;

View File

@@ -259,8 +259,8 @@ VectorUpdateCenter(Pointer v, int dimensions, float *x)
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
for (int k = 0; k < dimensions; k++)
vec->x[k] = x[k];
for (int i = 0; i < dimensions; i++)
vec->x[i] = x[i];
}
static void
@@ -271,8 +271,8 @@ HalfvecUpdateCenter(Pointer v, int dimensions, float *x)
SET_VARSIZE(vec, HALFVEC_SIZE(dimensions));
vec->dim = dimensions;
for (int k = 0; k < dimensions; k++)
vec->x[k] = Float4ToHalfUnchecked(x[k]);
for (int i = 0; i < dimensions; i++)
vec->x[i] = Float4ToHalfUnchecked(x[i]);
}
static void
@@ -284,29 +284,33 @@ BitUpdateCenter(Pointer v, int dimensions, float *x)
SET_VARSIZE(vec, VARBITTOTALLEN(dimensions));
VARBITLEN(vec) = dimensions;
for (uint32 k = 0; k < VARBITBYTES(vec); k++)
nx[k] = 0;
for (uint32 i = 0; i < VARBITBYTES(vec); i++)
nx[i] = 0;
for (int k = 0; k < dimensions; k++)
nx[k / 8] |= (x[k] > 0.5 ? 1 : 0) << (7 - (k % 8));
for (int i = 0; i < dimensions; i++)
nx[i / 8] |= (x[i] > 0.5 ? 1 : 0) << (7 - (i % 8));
}
static void
VectorSumCenter(Pointer v, float *x)
{
Vector *vec = (Vector *) v;
int dim = vec->dim;
for (int k = 0; k < vec->dim; k++)
x[k] += vec->x[k];
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
x[i] += vec->x[i];
}
static void
HalfvecSumCenter(Pointer v, float *x)
{
HalfVector *vec = (HalfVector *) v;
int dim = vec->dim;
for (int k = 0; k < vec->dim; k++)
x[k] += HalfToFloat4(vec->x[k]);
/* Auto-vectorized on aarch64 */
for (int i = 0; i < dim; i++)
x[i] += HalfToFloat4(vec->x[i]);
}
static void
@@ -314,8 +318,8 @@ BitSumCenter(Pointer v, float *x)
{
VarBit *vec = (VarBit *) v;
for (int k = 0; k < VARBITLEN(vec); k++)
x[k] += (float) (((VARBITS(vec)[k / 8]) >> (7 - (k % 8))) & 0x01);
for (int i = 0; i < VARBITLEN(vec); i++)
x[i] += (float) (((VARBITS(vec)[i / 8]) >> (7 - (i % 8))) & 0x01);
}
/*
@@ -355,7 +359,7 @@ ivfflat_halfvec_support(PG_FUNCTION_ARGS)
};
PG_RETURN_POINTER(&typeInfo);
};
}
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_bit_support);
Datum
@@ -370,4 +374,4 @@ ivfflat_bit_support(PG_FUNCTION_ARGS)
};
PG_RETURN_POINTER(&typeInfo);
};
}

View File

@@ -5,6 +5,10 @@
#include "ivfflat.h"
#include "storage/bufmgr.h"
#if PG_VERSION_NUM >= 180000
#define vacuum_delay_point() vacuum_delay_point(false)
#endif
/*
* Bulk delete tuples from the index
*/

View File

@@ -4,6 +4,7 @@
#include <math.h>
#include "catalog/pg_type.h"
#include "common/shortest_dec.h"
#include "common/string.h"
#include "fmgr.h"
#include "halfutils.h"
@@ -12,17 +13,10 @@
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
#include "utils/lsyscache.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
typedef struct SparseInputElement
{
int32 index;

View File

@@ -35,7 +35,11 @@
#define VECTOR_TARGET_CLONES
#endif
#if PG_VERSION_NUM >= 180000
PG_MODULE_MAGIC_EXT(.name = "vector",.version = "0.8.1");
#else
PG_MODULE_MAGIC;
#endif
/*
* Initialize index options and variables
@@ -920,11 +924,13 @@ vector_concat(PG_FUNCTION_ARGS)
CheckDim(dim);
result = InitVector(dim);
for (int i = 0; i < a->dim; i++)
/* Auto-vectorized */
for (int i = 0, imax = a->dim; i < imax; i++)
result->x[i] = a->x[i];
for (int i = 0; i < b->dim; i++)
result->x[i + a->dim] = b->x[i];
/* Auto-vectorized */
for (int i = 0, imax = b->dim, start = a->dim; i < imax; i++)
result->x[i + start] = b->x[i];
PG_RETURN_POINTER(result);
}
@@ -940,8 +946,21 @@ binary_quantize(PG_FUNCTION_ARGS)
float *ax = a->x;
VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result);
int i = 0;
int count = (a->dim / 8) * 8;
for (int i = 0; i < a->dim; i++)
/* Auto-vectorized */
for (; i < count; i += 8)
{
unsigned char result_byte = 0;
for (int j = 0; j < 8; j++)
result_byte |= (ax[i + j] > 0) << (7 - j);
rx[i / 8] = result_byte;
}
for (; i < a->dim; i++)
rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result);

View File

@@ -540,6 +540,12 @@ SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec)
01001110101
(1 row)
SELECT binary_quantize('[1,2,3,-4,5,6,-7,8,1,-2,-3,4,5,-6,7,8,-1,2,3]'::halfvec);
binary_quantize
---------------------
1110110110011011011
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
subvector
-----------

View File

@@ -99,6 +99,38 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::vector)) t2
4
(1 row)
DROP TABLE t;
-- iterative
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SET hnsw.iterative_scan = strict_order;
SET hnsw.ef_search = 1;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
SET hnsw.iterative_scan = relaxed_order;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
RESET hnsw.iterative_scan;
RESET hnsw.ef_search;
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
@@ -139,4 +171,31 @@ SET hnsw.ef_search = 0;
ERROR: 0 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
SET hnsw.ef_search = 1001;
ERROR: 1001 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
SHOW hnsw.iterative_scan;
hnsw.iterative_scan
---------------------
off
(1 row)
SET hnsw.iterative_scan = on;
ERROR: invalid value for parameter "hnsw.iterative_scan": "on"
HINT: Available values: off, relaxed_order, strict_order.
SHOW hnsw.max_scan_tuples;
hnsw.max_scan_tuples
----------------------
20000
(1 row)
SET hnsw.max_scan_tuples = 0;
ERROR: 0 is outside the valid range for parameter "hnsw.max_scan_tuples" (1 .. 2147483647)
SHOW hnsw.scan_mem_multiplier;
hnsw.scan_mem_multiplier
--------------------------
1
(1 row)
SET hnsw.scan_mem_multiplier = 0;
ERROR: 0 is outside the valid range for parameter "hnsw.scan_mem_multiplier" (1 .. 1000)
SET hnsw.scan_mem_multiplier = 1001;
ERROR: 1001 is outside the valid range for parameter "hnsw.scan_mem_multiplier" (1 .. 1000)
DROP TABLE t;

View File

@@ -81,6 +81,46 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2
3
(1 row)
DROP TABLE t;
-- iterative
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 3);
SET ivfflat.iterative_scan = relaxed_order;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
SET ivfflat.max_probes = 1;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
(1 row)
SET ivfflat.max_probes = 2;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
(2 rows)
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)
RESET ivfflat.iterative_scan;
RESET ivfflat.max_probes;
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
@@ -109,4 +149,27 @@ SHOW ivfflat.probes;
1
(1 row)
SET ivfflat.probes = 0;
ERROR: 0 is outside the valid range for parameter "ivfflat.probes" (1 .. 32768)
SET ivfflat.probes = 32769;
ERROR: 32769 is outside the valid range for parameter "ivfflat.probes" (1 .. 32768)
SHOW ivfflat.iterative_scan;
ivfflat.iterative_scan
------------------------
off
(1 row)
SET ivfflat.iterative_scan = on;
ERROR: invalid value for parameter "ivfflat.iterative_scan": "on"
HINT: Available values: off, relaxed_order.
SHOW ivfflat.max_probes;
ivfflat.max_probes
--------------------
32768
(1 row)
SET ivfflat.max_probes = 0;
ERROR: 0 is outside the valid range for parameter "ivfflat.max_probes" (1 .. 32768)
SET ivfflat.max_probes = 32769;
ERROR: 32769 is outside the valid range for parameter "ivfflat.max_probes" (1 .. 32768)
DROP TABLE t;

View File

@@ -576,6 +576,12 @@ SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
01001110101
(1 row)
SELECT binary_quantize('[1,2,3,-4,5,6,-7,8,1,-2,-3,4,5,-6,7,8,-1,2,3]'::vector);
binary_quantize
---------------------
1110110110011011011
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
subvector
-----------

View File

@@ -121,6 +121,7 @@ SELECT l2_normalize('[65504]'::halfvec);
SELECT binary_quantize('[1,0,-1]'::halfvec);
SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
SELECT binary_quantize('[1,2,3,-4,5,6,-7,8,1,-2,-3,4,5,-6,7,8,-1,2,3]'::halfvec);
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2);

View File

@@ -57,6 +57,26 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::vector)) t2
DROP TABLE t;
-- iterative
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SET hnsw.iterative_scan = strict_order;
SET hnsw.ef_search = 1;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SET hnsw.iterative_scan = relaxed_order;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
RESET hnsw.iterative_scan;
RESET hnsw.ef_search;
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
@@ -81,4 +101,17 @@ SHOW hnsw.ef_search;
SET hnsw.ef_search = 0;
SET hnsw.ef_search = 1001;
SHOW hnsw.iterative_scan;
SET hnsw.iterative_scan = on;
SHOW hnsw.max_scan_tuples;
SET hnsw.max_scan_tuples = 0;
SHOW hnsw.scan_mem_multiplier;
SET hnsw.scan_mem_multiplier = 0;
SET hnsw.scan_mem_multiplier = 1001;
DROP TABLE t;

View File

@@ -44,6 +44,28 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2
DROP TABLE t;
-- iterative
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 3);
SET ivfflat.iterative_scan = relaxed_order;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SET ivfflat.max_probes = 1;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SET ivfflat.max_probes = 2;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
RESET ivfflat.iterative_scan;
RESET ivfflat.max_probes;
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
@@ -62,4 +84,16 @@ CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
SHOW ivfflat.probes;
SET ivfflat.probes = 0;
SET ivfflat.probes = 32769;
SHOW ivfflat.iterative_scan;
SET ivfflat.iterative_scan = on;
SHOW ivfflat.max_probes;
SET ivfflat.max_probes = 0;
SET ivfflat.max_probes = 32769;
DROP TABLE t;

View File

@@ -128,6 +128,7 @@ SELECT l2_normalize('[3e38]'::vector);
SELECT binary_quantize('[1,0,-1]'::vector);
SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
SELECT binary_quantize('[1,2,3,-4,5,6,-7,8,1,-2,-3,4,5,-6,7,8,-1,2,3]'::vector);
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);

View File

@@ -23,7 +23,7 @@ $node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops
my $count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = 10;
SET ivfflat.iterative_search = on;
SET ivfflat.iterative_scan = relaxed_order;
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
));
is($count, 10);
@@ -39,8 +39,8 @@ foreach ((30, 50, 70))
$count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = 10;
SET ivfflat.iterative_search = on;
SET ivfflat.iterative_search_max_probes = $max_probes;
SET ivfflat.iterative_scan = relaxed_order;
SET ivfflat.max_probes = $max_probes;
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst WHERE i = $i) LIMIT 11) t;
));
$sum += $count;

View File

@@ -19,7 +19,7 @@ sub test_recall
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
SET ivfflat.iterative_search = on;
SET ivfflat.iterative_scan = relaxed_order;
EXPLAIN ANALYZE SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan using idx on tst/);
@@ -29,7 +29,7 @@ sub test_recall
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
SET ivfflat.iterative_search = on;
SET ivfflat.iterative_scan = relaxed_order;
SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
@@ -48,7 +48,7 @@ sub test_recall
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
cmp_ok($correct / $total, ">=", $min, "$operator $c");
}
# Initialize node
@@ -103,7 +103,7 @@ for my $i (0 .. $#operators)
if ($c == 100)
{
test_recall($c, 1, 0.58, $operator);
test_recall($c, 1, 0.57, $operator);
test_recall($c, 10, 0.98, $operator);
}
else

View File

@@ -26,8 +26,9 @@ $node->safe_psql("postgres", qq(
my $count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.iterative_search = on;
SET work_mem = '8MB';
SET hnsw.iterative_scan = relaxed_order;
SET hnsw.max_scan_tuples = 100000;
SET hnsw.scan_mem_multiplier = 2;
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
));
is($count, 10);
@@ -42,9 +43,9 @@ foreach ((30000, 50000, 70000))
{
$count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.iterative_search = on;
SET hnsw.iterative_search_max_tuples = $max_tuples;
SET work_mem = '8MB';
SET hnsw.iterative_scan = relaxed_order;
SET hnsw.max_scan_tuples = $max_tuples;
SET hnsw.scan_mem_multiplier = 2;
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst WHERE i = $i) LIMIT 11) t;
));
$sum += $count;
@@ -55,13 +56,4 @@ foreach ((30000, 50000, 70000))
cmp_ok($avg, '<', $expected + 2);
}
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.iterative_search = on;
SET client_min_messages = debug1;
SET work_mem = '2MB';
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
));
like($stderr, qr/hnsw index scan exceeded work_mem after \d+ tuples/);
done_testing();

View File

@@ -10,18 +10,18 @@ my @expected;
my $limit = 20;
my $dim = 3;
my $array_sql = join(",", ('random()') x $dim);
my @cs = (100, 1000);
my @cs = (50, 500);
sub test_recall
{
my ($c, $ef_search, $min, $operator) = @_;
my ($c, $ef_search, $min, $operator, $mode) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
SET hnsw.iterative_search = on;
SET hnsw.iterative_scan = $mode;
EXPLAIN ANALYZE SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan using idx on tst/);
@@ -31,7 +31,7 @@ sub test_recall
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
SET hnsw.iterative_search = on;
SET hnsw.iterative_scan = $mode;
SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
@@ -50,7 +50,7 @@ sub test_recall
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
cmp_ok($correct / $total, ">=", $min, "$operator $mode $c");
}
# Initialize node
@@ -62,7 +62,7 @@ $node->start;
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 50000) i;"
);
# Generate queries
@@ -108,21 +108,8 @@ for my $i (0 .. $#operators)
push(@expected, $res);
}
if ($c == 100)
{
test_recall($c, 40, 0.99, $operator);
}
else
{
if ($operator eq "<->")
{
test_recall($c, 40, 0.99, $operator);
}
else
{
test_recall($c, 40, 0.99, $operator);
}
}
test_recall($c, 40, 0.99, $operator, "strict_order");
test_recall($c, 40, 0.99, $operator, "relaxed_order");
}
$node->safe_psql("postgres", "DROP INDEX idx;");

View File

@@ -1,113 +0,0 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
my @queries = ();
my @cs = ();
my @expected;
my $limit = 20;
my $dim = 3;
my $array_sql = join(",", ('random()') x $dim);
my $nc = 1000;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $cs[0] ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Cond/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SELECT i FROM tst WHERE c = $cs[$i] ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my %actual_set = map { $_ => 1 } @actual_ids;
is(scalar(@actual_ids), $limit);
my @expected_ids = split("\n", $expected[$i]);
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
}
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim), c int4);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql], i % $nc FROM generate_series(1, 20000) i;"
);
# Generate queries
for (1 .. 20)
{
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
push(@queries, "[" . join(",", @r) . "]");
push(@cs, int(rand() * $nc));
}
# Get exact results
@expected = ();
for my $i (0 .. $#queries)
{
my $res = $node->safe_psql("postgres", "SELECT i FROM tst WHERE c = $cs[$i] ORDER BY v <=> '$queries[$i]' LIMIT $limit;");
push(@expected, $res);
}
# Add index
$node->safe_psql("postgres", qq(
SET maintenance_work_mem = '256MB';
SET max_parallel_maintenance_workers = 2;
CREATE INDEX ON tst USING hnsw (v vector_cosine_ops, c);
));
# Test recall
test_recall(0.99, '<=>');
# Test vacuum
$node->safe_psql("postgres", "DELETE FROM tst WHERE c > 5;");
$node->safe_psql("postgres", "VACUUM tst;");
# Test columns
my ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (c);");
like($stderr, qr/first column must be a vector/);
($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (c, v vector_cosine_ops);");
like($stderr, qr/first column must be a vector/);
($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_cosine_ops, c, c);");
like($stderr, qr/index cannot have more than two columns/);
($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_cosine_ops, v vector_cosine_ops);");
like($stderr, qr/column 2 cannot be a vector/);
done_testing();

View File

@@ -1,4 +1,4 @@
comment = 'vector data type and ivfflat and hnsw access methods'
default_version = '0.7.4'
default_version = '0.8.1'
module_pathname = '$libdir/vector'
relocatable = true