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113 Commits

Author SHA1 Message Date
Andrew Kane
c599017441 Improved naming [skip ci] 2026-07-10 17:37:27 -07:00
Andrew Kane
f341cea329 Reduced memory usage for few samples for IVFFlat index builds [skip ci] 2026-07-10 17:33:05 -07:00
Andrew Kane
73356ecfa7 Improved check for VectorArrayInit [skip ci] 2026-07-10 16:30:35 -07:00
Andrew Kane
0e557b1d18 Updated readme [skip ci] 2026-07-10 15:16:36 -07:00
Andrew Kane
769a60884c Updated readme [skip ci] 2026-07-10 14:20:26 -07:00
Andrew Kane
8711840058 Added section on multitenancy [skip ci] 2026-07-10 14:13:13 -07:00
Andrew Kane
159b79aaad Version bump to 0.8.5 [skip ci] 2026-07-08 16:03:40 -07:00
Andrew Kane
c5a277a975 Hardened VectorArrayInit 2026-07-08 10:15:21 -07:00
Andrew Kane
124f6c61a4 Added Postgres 20 to CI [skip ci] 2026-07-07 16:15:39 -07:00
Andrew Kane
5ca52d12b6 Updated checkout action [skip ci] 2026-07-07 15:46:41 -07:00
Andrew Kane
1f61d1111b Added ubuntu-26.04 to CI [skip ci] 2026-07-07 15:46:06 -07:00
Andrew Kane
fb1b8966eb Added comment to IVFFlat vacuuming test [skip ci] 2026-07-01 17:21:26 -07:00
Andrew Kane
71ce9d3311 Added test for concurrent INSERTs, DELETEs, SELECTs, and VACUUM with IVFFlat [skip ci] 2026-07-01 17:18:34 -07:00
Andrew Kane
d19cc0d371 Improved HNSW vacuuming test [skip ci] 2026-07-01 17:14:53 -07:00
Andrew Kane
89fda3e100 Removed slow tests [skip ci] 2026-07-01 16:05:53 -07:00
Andrew Kane
30d8654b47 Added tests for HNSW index dimensions for bit type [skip ci] 2026-07-01 15:49:07 -07:00
Andrew Kane
a846385cc7 Added tests for index dimensions for bit type [skip ci] 2026-07-01 15:47:05 -07:00
Andrew Kane
98d7c4124e Added IVFFlat memory tests for bit [skip ci] 2026-07-01 15:45:18 -07:00
Andrew Kane
2a2b4a0b58 Updated changelog [skip ci] 2026-07-01 12:35:46 -07:00
Andrew Kane
f15a50387f Moved logic for calculating number of samples [skip ci] 2026-07-01 12:27:03 -07:00
Andrew Kane
971b7d7fd6 Added IVFFlat memory tests for halfvec [skip ci] 2026-07-01 12:21:08 -07:00
Andrew Kane
f51d8ed989 Improved readability of options tests [skip ci] 2026-07-01 12:17:50 -07:00
Andrew Kane
a76a18d526 Added tests for index dimensions [skip ci] 2026-07-01 12:15:27 -07:00
Andrew Kane
b383e4d191 Reduced memory usage for small tables for IVFFlat index builds - resolves #995 and resolves #996
Co-authored-by: Itai Spiegel <itai@mave.com>
2026-07-01 11:54:21 -07:00
Andrew Kane
1d458ad5d7 Version bump to 0.8.4 [skip ci] 2026-06-30 15:24:14 -07:00
Andrew Kane
9fa17c10b8 Added comments to HNSW vacuuming tests [skip ci] 2026-06-30 13:40:32 -07:00
Andrew Kane
14149b19f5 Added SELECTs to HNSW vacuuming test for good measure [skip ci] 2026-06-30 13:34:11 -07:00
Andrew Kane
34d796fbab Added test for concurrent INSERTs, DELETEs, and VACUUM with HNSW - #993 2026-06-30 13:23:04 -07:00
Andrew Kane
53341bb6c7 Simplified test [skip ci] 2026-06-30 13:16:17 -07:00
Andrew Kane
0d9720f440 Added test for concurrent SELECTs and VACUUM [skip ci] 2026-06-30 13:12:47 -07:00
Andrew Kane
cb246cb72d Improved naming [skip ci] 2026-06-30 02:46:31 -07:00
Andrew Kane
d053de2d94 Removed deletion list check in MarkDeleted (does not help safety) [skip ci] 2026-06-30 02:31:54 -07:00
Andrew Kane
83bac90869 Added checks for deleted tuples rather than relying on ItemPointerIsValid [skip ci] 2026-06-30 01:40:30 -07:00
Andrew Kane
4eca5024df Updated comment [skip ci] 2026-06-30 01:35:07 -07:00
Andrew Kane
a31771bc45 Changed log message to assertion [skip ci] 2026-06-30 01:25:36 -07:00
Andrew Kane
ecddde963a Added check to confirm in deletion list before marking as deleted 2026-06-30 01:15:38 -07:00
Andrew Kane
ecd413d0fe Improved naming [skip ci] 2026-06-30 01:03:08 -07:00
Andrew Kane
497db7976c Fixed hnsw graph not repaired error with HNSW vacuuming - fixes #993 2026-06-30 00:34:01 -07:00
Andrew Kane
f1dd4e3b03 Updated urls [skip ci] 2026-06-29 01:08:14 -07:00
Andrew Kane
7d067d7b83 Updated changelog [skip ci] 2026-06-24 11:44:04 -07:00
Andrew Kane
d4dd73d970 Moved repair confirmation after lock wait to catch more potential issues 2026-06-23 11:39:16 -07:00
Bhagyesh Chaturvedi
ffe28bb954 Fix HNSW insert and vacuum race 2026-06-23 06:00:23 +00:00
Andrew Kane
0dbc1a27c0 Removed redundant check [skip ci] 2026-06-18 12:56:57 -07:00
Andrew Kane
08c4e7ff10 Hardened VectorArrayGet and VectorArraySet [skip ci] 2026-06-18 12:56:12 -07:00
Andrew Kane
6731c49811 Fixed overflow check (should never be hit) [skip ci] 2026-06-18 12:51:38 -07:00
Andrew Kane
f2617f02d1 Updated style to be consistent with latest Postgres [skip ci] 2026-06-18 12:44:11 -07:00
Andrew Kane
bdf19077db Ensure centers and samples fit into maintenance_work_mem before allocating for IVFFlat index builds - closes #986 2026-06-18 12:29:58 -07:00
Andrew Kane
90cd2b4ee5 Improved memory tracking for IVFFlat index builds [skip ci] 2026-06-18 11:57:03 -07:00
Andrew Kane
b44d1b4c5f Added todo [skip ci] 2026-06-18 11:51:37 -07:00
Andrew Kane
cc5b865c33 Added itemsize to IvfflatBuildState [skip ci] 2026-06-18 11:49:29 -07:00
Andrew Kane
4895021088 Hardened NeedsUpdated [skip ci] 2026-06-18 11:19:27 -07:00
Andrew Kane
eda77b3492 DRY normalize code for IVFFlat index builds 2026-06-18 11:16:51 -07:00
Andrew Kane
a2364b1793 Switched to VectorArraySet for NormCenters [skip ci] 2026-06-18 11:05:37 -07:00
Andrew Kane
a0eaf70d17 Hardened VectorArraySet [skip ci] 2026-06-18 11:03:09 -07:00
Andrew Kane
586e7515ba Version bump to 0.8.3 [skip ci] 2026-06-17 21:26:13 -07:00
Andrew Kane
a619d0b34d Simplified logic for HNSW vacuum progress [skip ci] 2026-06-17 12:18:17 -07:00
Andrew Kane
ad222abf48 Improved HNSW vacuum progress for round block sizes [skip ci] 2026-06-16 14:21:23 -07:00
Andrew Kane
8a81a3fe3a Added HNSW_VACUUM_PROGRESS flag [skip ci] 2026-06-16 13:53:40 -07:00
Andrew Kane
fc804925a4 Added todo [skip ci] 2026-06-16 12:33:25 -07:00
Andrew Kane
98dc4aa6d0 Added pass to confirm graph was repaired for HNSW vacuuming 2026-06-16 10:51:54 -07:00
Andrew Kane
7b72aeeff3 Added check for deleted element [skip ci] 2026-06-16 10:13:40 -07:00
Andrew Kane
4682d51e5d Added memory usage for HNSW vacuuming [skip ci] 2026-06-16 10:10:13 -07:00
Andrew Kane
91fe2e62e7 Added benchmarking for HNSW vacuuming [skip ci] 2026-06-16 09:53:47 -07:00
Andrew Kane
eedba7ee14 Fixed possible index corruption with HNSW vacuuming - resolves #988
Co-authored-by: Bhagyesh Chaturvedi <bhagyeshc@google.com>
2026-06-16 09:44:34 -07:00
Andrew Kane
32284ba28a Updated CI for latest windows-2025 image [skip ci] 2026-06-15 19:24:02 -07:00
Andrew Kane
1f68c73c96 Updated changelog [skip ci] 2026-06-10 20:20:55 -07:00
Andrew Kane
f15bc0904f Updated changelog [skip ci] 2026-06-10 20:13:55 -07:00
Andrew Kane
2b7ad083dc Always use inline pg_popcount64 for Postgres 19+ - #985 2026-06-10 20:08:03 -07:00
Andrew Kane
421a35fcdc Fixed performance regression with Hamming distance and Jaccard distance with Postgres 18 - fixes #985 2026-06-10 19:55:21 -07:00
Andrew Kane
12368bd79c Updated readme [skip ci] 2026-05-30 11:58:10 -07:00
Andrew Kane
88a0085459 Improved casting [skip ci] 2026-05-26 14:09:19 -07:00
Andrew Kane
ea23884efd Ran latest pgindent [skip ci] 2026-05-26 13:39:55 -07:00
Andrew Kane
3351f3d43e Simplified comment [skip ci] 2026-05-26 13:39:20 -07:00
Andrew Kane
d238409bec Merge pull request #979 from xingtanzjr/fix_ivf_create_concurrently
Fix CREATE INDEX CONCURRENTLY crash on ivfflat with assertion-enabled PostgreSQL
2026-04-27 03:28:52 -07:00
Zhang Jinrui
529f37175b Fix CREATE INDEX CONCURRENTLY crash on ivfflat with assertion-enabled PostgreSQL by passing anyvisible=false in ivfflat SampleRows 2026-04-27 10:15:32 +00:00
Andrew Kane
bce3946392 Added link to PgHero [skip ci] 2026-04-27 02:11:17 -07:00
Andrew Kane
13cb253d30 Added link to PgDog [skip ci] 2026-04-27 00:09:20 -07:00
Andrew Kane
41b3cdc011 Updated readme [skip ci] 2026-04-26 14:47:17 -07:00
Andrew Kane
ec02a96239 Updated readme [skip ci] 2026-04-26 14:45:12 -07:00
Andrew Kane
610d95b8d2 Moved scaling section [skip ci] 2026-04-26 13:12:28 -07:00
Andrew Kane
609d01f4c6 Added more scaling advice to readme [skip ci] 2026-04-26 12:56:07 -07:00
Andrew Kane
a7551a61ca Updated style [skip ci] 2026-04-14 16:21:32 -07:00
lychen0613
5c9a97af3b optimize: defer sample normalization when building ivfflat 2026-04-14 16:14:17 -07:00
Andrew Kane
8af675cd25 Added comment [skip ci] 2026-04-14 16:10:45 -07:00
Andrew Kane
97e0ed4464 Fixed compilation errors with Postgres 19 2026-04-14 15:46:10 -07:00
Andrew Kane
533ad160e0 Fixed CI 2026-04-14 13:51:04 -07:00
Andrew Kane
dfbd724a1f Changed rowstoskip to double to match reservoir_get_next_S 2026-04-14 13:38:20 -07:00
lychen0613
5f270c9663 Add benchmark for ivfflat sample rows 2026-04-14 21:56:10 +08:00
lychen0613
352ec5be29 fix: correctly use reservoir_get_next_S when building ivfflat 2026-04-14 17:57:40 +08:00
Andrew Kane
17916cad00 Improved includes [skip ci] 2026-02-25 17:35:23 -08:00
Andrew Kane
284f2f0fec Improved casting for HNSW scan memory limit [skip ci] 2026-02-25 12:59:17 -08:00
Andrew Kane
edd49863ba Improved limit for HNSW scan memory 2026-02-25 12:52:29 -08:00
Andrew Kane
411291189d Updated changelog [skip ci] 2026-02-25 11:28:43 -08:00
Andrew Kane
cab9da72c0 Version bump to 0.8.2 [skip ci] 2026-02-25 10:46:57 -08:00
Andrew Kane
d702ee31f2 Added test case for low memory HNSW index builds 2026-02-25 10:41:17 -08:00
Andrew Kane
9ed39fb94b Hardened shared memory allocator
Co-authored-by: chungkn from OneMount Group <kimngocchung.k2a@gmail.com>
2026-02-25 10:39:01 -08:00
Andrew Kane
b7e680d41a Fixed integer wraparound leading to buffer overflow with parallel HNSW index build
Reported-by: chungkn from OneMount Group <kimngocchung.k2a@gmail.com>
2026-02-25 10:35:14 -08:00
Andrew Kane
f5841f07fd Updated CI 2026-02-23 14:06:35 -08:00
Andrew Kane
35ab919bf5 Switched to statically-allocated IndexAmRoutine for Postgres 19 [skip ci] 2026-01-21 16:40:35 -08:00
Andrew Kane
5c08be0291 Updated checkout action [skip ci] 2026-01-15 20:45:56 -08:00
Jack Huang
544686feb1 Add RISC-V64 architecture support in Makefile (#948) 2026-01-14 06:11:58 -08:00
Andrew Kane
1a8ebb1129 Updated license year [skip ci] 2026-01-05 13:01:58 -08:00
Andrew Kane
aca89aec73 Switched to scanner_isspace for Postgres 17+ - resolves #942 2026-01-05 12:54:04 -08:00
Andrew Kane
c9875f5150 Simplified test case - resolves #943 2026-01-05 12:42:14 -08:00
Andrew Kane
df2c3d301f Added link to pgvector-cobol [skip ci] 2025-12-13 11:33:35 -08:00
Andrew Kane
d557f1c9b1 Added link to pgvector-tcl [skip ci] 2025-12-11 23:22:56 -08:00
Andrew Kane
3d6dd20469 Removed unneeded check 2025-12-11 16:28:45 -08:00
Andrew Kane
c711da411c Improved includes for indexes 2025-12-11 15:35:37 -08:00
Andrew Kane
3975e212cc Improved includes for ivfkmeans [skip ci] 2025-12-11 13:26:36 -08:00
Andrew Kane
2b741ef068 Improved includes for types 2025-12-11 00:35:18 -08:00
Andrew Kane
f85a7d3fd0 Keep clang-tidy happy [skip ci] 2025-12-10 20:03:26 -08:00
Andrew Kane
5c25f81789 Fixed inconsistent parameter names [skip ci] 2025-12-10 18:49:00 -08:00
Andrew Kane
d72ee71f23 Fixed compilation errors with Postgres 19 2025-12-10 14:59:29 -08:00
54 changed files with 1245 additions and 768 deletions

View File

@@ -8,10 +8,12 @@ jobs:
fail-fast: false
matrix:
include:
- postgres: 20
os: ubuntu-26.04
- postgres: 19
os: ubuntu-24.04
os: ubuntu-26.04
- postgres: 18
os: ubuntu-24.04
os: ubuntu-26.04-arm
- postgres: 17
os: ubuntu-24.04
- postgres: 16
@@ -23,7 +25,7 @@ jobs:
- postgres: 13
os: ubuntu-22.04
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
@@ -53,7 +55,7 @@ jobs:
- postgres: 14
os: macos-15-intel
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
@@ -72,7 +74,7 @@ jobs:
tar xf $TAG.tar.gz
mv postgres-$TAG postgres
env:
TAG: ${{ matrix.postgres == 18 && 'REL_18_0' || 'REL_14_19' }}
TAG: ${{ matrix.postgres == 18 && 'REL_18_2' || 'REL_14_21' }}
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres/src/test/perl -I ./test/perl"
env:
PERL5LIB: /Users/runner/perl5/lib/perl5
@@ -92,12 +94,12 @@ jobs:
- postgres: 14
os: windows-2022
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
- run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
call "C:\Program Files\Microsoft Visual Studio\${{ matrix.os == 'windows-2025' && 18 || 2022 }}\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
nmake /NOLOGO /F Makefile.win && ^
nmake /NOLOGO /F Makefile.win install && ^
nmake /NOLOGO /F Makefile.win installcheck ${{ matrix.postgres != 17 && 'PG_REGRESS=$(PGROOT)\bin\pg_regress' || '' }} && ^
@@ -133,7 +135,7 @@ jobs:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v5
- uses: actions/checkout@v7
- uses: ankane/setup-postgres-valgrind@v1
with:
postgres-version: 18

View File

@@ -1,9 +1,21 @@
## 0.9.0 (unreleased)
## 0.8.5 (2026-07-08)
- Added support for inline filtering with HNSW
- Reduced memory usage for small tables for IVFFlat index builds
## 0.8.2 (unreleased)
## 0.8.4 (2026-06-30)
- Fixed `hnsw graph not repaired` error with HNSW vacuuming
- Fixed possible error with inserts during HNSW vacuuming
- Fixed memory exceeding `maintenance_work_mem` with IVFFlat index builds
## 0.8.3 (2026-06-17)
- Fixed possible index corruption with HNSW vacuuming
- Fixed performance regression with Hamming distance and Jaccard distance with Postgres 18
## 0.8.2 (2026-02-25)
- Fixed buffer overflow with parallel HNSW index build - [more info](https://github.com/pgvector/pgvector/issues/959)
- Improved `install` target on Windows
- Fixed `Index Searches` in `EXPLAIN` output for Postgres 18

View File

@@ -5,7 +5,7 @@ ARG DEBIAN_CODENAME=bookworm
FROM postgres:$PG_MAJOR-$DEBIAN_CODENAME
ARG PG_MAJOR
ADD https://github.com/pgvector/pgvector.git#v0.8.1 /tmp/pgvector
ADD https://github.com/pgvector/pgvector.git#v0.8.5 /tmp/pgvector
RUN apt-get update && \
apt-mark hold locales && \

View File

@@ -1,4 +1,4 @@
Portions Copyright (c) 1996-2025, PostgreSQL Global Development Group
Portions Copyright (c) 1996-2026, PostgreSQL Global Development Group
Portions Copyright (c) 1994, The Regents of the University of California

View File

@@ -2,12 +2,12 @@
"name": "vector",
"abstract": "Open-source vector similarity search for Postgres",
"description": "Supports L2 distance, inner product, and cosine distance",
"version": "0.8.1",
"version": "0.8.5",
"maintainer": [
"Andrew Kane <andrew@ankane.org>"
],
"license": {
"PostgreSQL": "http://www.postgresql.org/about/licence"
"PostgreSQL": "https://www.postgresql.org/about/licence"
},
"prereqs": {
"runtime": {
@@ -20,7 +20,7 @@
"vector": {
"file": "sql/vector.sql",
"docfile": "README.md",
"version": "0.8.1",
"version": "0.8.5",
"abstract": "Open-source vector similarity search for Postgres"
}
},
@@ -38,7 +38,7 @@
"generated_by": "Andrew Kane",
"meta-spec": {
"version": "1.0.0",
"url": "http://pgxn.org/meta/spec.txt"
"url": "https://pgxn.org/meta/spec.txt"
},
"tags": [
"vectors",

View File

@@ -1,5 +1,5 @@
EXTENSION = vector
EXTVERSION = 0.8.1
EXTVERSION = 0.8.5
MODULE_big = vector
DATA = $(wildcard sql/*--*--*.sql)
@@ -27,6 +27,11 @@ ifneq ($(filter ppc64%, $(shell uname -m)), )
OPTFLAGS =
endif
# RISC-V64 doesn't support -march=native
ifeq ($(shell uname -m), riscv64)
OPTFLAGS =
endif
# For auto-vectorization:
# - GCC (needs -ftree-vectorize OR -O3) - https://gcc.gnu.org/projects/tree-ssa/vectorization.html
# - Clang (could use pragma instead) - https://llvm.org/docs/Vectorizers.html

View File

@@ -1,5 +1,5 @@
EXTENSION = vector
EXTVERSION = 0.8.1
EXTVERSION = 0.8.5
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

View File

@@ -11,6 +11,8 @@ Store your vectors with the rest of your data. Supports:
Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recovery, JOINs, and all of the other [great features](https://www.postgresql.org/about/) of Postgres
Have a lot of vectors? Use [quantization](#scaling) to scale
[![Build Status](https://github.com/pgvector/pgvector/actions/workflows/build.yml/badge.svg)](https://github.com/pgvector/pgvector/actions)
## Installation
@@ -21,7 +23,7 @@ Compile and install the extension (supports Postgres 13+)
```sh
cd /tmp
git clone --branch v0.8.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.8.5 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo
@@ -38,7 +40,7 @@ Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/buil
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\18"
cd %TEMP%
git clone --branch v0.8.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.8.5 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
@@ -314,6 +316,8 @@ For a large number of workers, you may need to increase `max_parallel_workers` (
The [index options](#index-options) also have a significant impact on build time (use the defaults unless seeing low recall)
Use [binary quantization](#binary-quantization) for faster build times at scale
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
@@ -443,13 +447,7 @@ Exact indexes work well for conditions that match a low percentage of rows. Othe
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.
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, enable [iterative index scans](#iterative-index-scans), which will automatically scan more of the index when needed.
```sql
SET hnsw.iterative_scan = strict_order;
@@ -467,10 +465,14 @@ If filtering by many different values, consider [partitioning](https://www.postg
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
```
Or a composite HNSW index (added in 0.9.0)
## Multitenancy
For applications with multiple tenants, sharing an approximate index between tenants means vectors from one tenant can affect recall (and speed) for other tenants.
For tenant isolation, use [list partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html) or separate tables.
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops, category_id);
CREATE TABLE items (customer_id int, embedding vector(3)) PARTITION BY LIST(customer_id);
```
## Iterative Index Scans
@@ -679,6 +681,10 @@ SHOW shared_buffers;
Be sure to restart Postgres for changes to take effect.
### Storing
Use the `halfvec` type instead of `vector` for a smaller working set.
### Loading
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py)).
@@ -693,6 +699,8 @@ Add any indexes *after* loading the initial data for best performance.
See index build time for [HNSW](#index-build-time) and [IVFFlat](#index-build-time-1).
Use [binary quantization](#binary-quantization) for smaller indexes and faster build times at scale.
In production environments, create indexes concurrently to avoid blocking writes.
```sql
@@ -723,6 +731,8 @@ SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5;
#### Approximate Search
Use [binary quantization](#binary-quantization) with re-ranking to keep indexes in-memory at scale.
To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
```sql
@@ -738,21 +748,20 @@ REINDEX INDEX CONCURRENTLY index_name;
VACUUM table_name;
```
## Scaling
For a smaller working set:
1. Use the `halfvec` type instead of `vector` for tables
2. Use [binary quantization](#binary-quantization) for indexes (with re-ranking for search)
Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus), [PgDog](https://github.com/pgdogdev/pgdog), or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus/example.py)).
## Monitoring
Monitor performance with [pg_stat_statements](https://www.postgresql.org/docs/current/pgstatstatements.html) (be sure to add it to `shared_preload_libraries`).
```sql
CREATE EXTENSION pg_stat_statements;
```
Get the most time-consuming queries with:
```sql
SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_time_ms,
ROUND((total_plan_time + total_exec_time) / 60000) AS total_time_min
FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20;
```
Use existing tools like [pg_stat_statements](https://www.postgresql.org/docs/current/pgstatstatements.html) or [PgHero](https://github.com/ankane/pghero) to monitor performance.
Monitor recall by comparing results from approximate search with exact search.
@@ -763,14 +772,6 @@ SELECT ...
COMMIT;
```
## Scaling
Scale pgvector the same way you scale Postgres.
Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus/example.py)).
## Languages
Use pgvector from any language with a Postgres client. You can even generate and store vectors in one language and query them in another.
@@ -782,6 +783,7 @@ Algol | [pgvector-algol](https://github.com/pgvector/pgvector-algol)
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)
COBOL | [pgvector-cobol](https://github.com/pgvector/pgvector-cobol)
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)
@@ -809,6 +811,7 @@ 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)
Tcl | [pgvector-tcl](https://github.com/pgvector/pgvector-tcl)
Zig | [pgvector-zig](https://github.com/pgvector/pgvector-zig)
## Frequently Asked Questions
@@ -882,6 +885,8 @@ No, but like other index types, youll likely see better performance if they d
SELECT pg_size_pretty(pg_relation_size('index_name'));
```
Use [half-precision indexing](#half-precision-indexing) or [binary quantization](#binary-quantization) for smaller indexes.
## Troubleshooting
#### Why isnt a query using an index?
@@ -1156,23 +1161,23 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
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`
- `pg18-trixie`, `0.8.5-pg18-trixie`
- `pg18-bookworm`, `0.8.5-pg18-bookworm`, `pg18`, `0.8.5-pg18`
- `pg17-trixie`, `0.8.5-pg17-trixie`
- `pg17-bookworm`, `0.8.5-pg17-bookworm`, `pg17`, `0.8.5-pg17`
- `pg16-trixie`, `0.8.5-pg16-trixie`
- `pg16-bookworm`, `0.8.5-pg16-bookworm`, `pg16`, `0.8.5-pg16`
- `pg15-trixie`, `0.8.5-pg15-trixie`
- `pg15-bookworm`, `0.8.5-pg15-bookworm`, `pg15`, `0.8.5-pg15`
- `pg14-trixie`, `0.8.5-pg14-trixie`
- `pg14-bookworm`, `0.8.5-pg14-bookworm`, `pg14`, `0.8.5-pg14`
- `pg13-trixie`, `0.8.5-pg13-trixie`
- `pg13-bookworm`, `0.8.5-pg13-bookworm`, `pg13`, `0.8.5-pg13`
You can also build the image manually:
```sh
git clone --branch v0.8.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.8.5 https://github.com/pgvector/pgvector.git
cd pgvector
docker build --pull --build-arg PG_MAJOR=18 -t myuser/pgvector .
```
@@ -1288,7 +1293,6 @@ 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
@@ -1335,7 +1339,7 @@ make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
To enable benchmarking:
```sh
make clean && PG_CFLAGS="-DIVFFLAT_BENCH" make && make install
make clean && PG_CFLAGS="-DHNSW_BENCH -DIVFFLAT_BENCH" make && make install
```
To show memory usage:

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 '0.8.2'" to load this file. \quit

View File

@@ -1,10 +0,0 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.9.0'" to load this file. \quit
CREATE FUNCTION hnsw_attribute_distance(integer, integer) RETURNS float8
AS 'MODULE_PATHNAME', 'hnsw_int4_attribute_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR CLASS vector_integer_ops
DEFAULT FOR TYPE integer USING hnsw AS
OPERATOR 2 = (integer, integer),
FUNCTION 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 '0.8.3'" to load this file. \quit

View File

@@ -0,0 +1,2 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.8.4'" to load this file. \quit

View File

@@ -0,0 +1,2 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.8.5'" 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

@@ -31,10 +31,12 @@
#define BIT_TARGET_CLONES
#endif
/* Use built-ins when possible for inlining */
#if defined(HAVE__BUILTIN_POPCOUNT) && defined(HAVE_LONG_INT_64)
/* Use built-ins when possible for Postgres < 19 for inlining */
#if PG_VERSION_NUM >= 190000
#define popcount64(x) pg_popcount64(x)
#elif defined(HAVE__BUILTIN_POPCOUNT) && (defined(HAVE_LONG_INT_64) || SIZEOF_LONG == 8)
#define popcount64(x) __builtin_popcountl(x)
#elif defined(HAVE__BUILTIN_POPCOUNT) && defined(HAVE_LONG_LONG_INT_64)
#elif defined(HAVE__BUILTIN_POPCOUNT) && (defined(HAVE_LONG_LONG_INT_64) || SIZEOF_LONG_LONG == 8)
#define popcount64(x) __builtin_popcountll(x)
#elif !defined(_MSC_VER)
/* Fails to resolve with MSVC */
@@ -169,7 +171,7 @@ BitJaccardDistanceAvx512Popcount(uint32 bytes, unsigned char *ax, unsigned char
#endif
TARGET_XSAVE static bool
SupportsAvx512Popcount()
SupportsAvx512Popcount(void)
{
unsigned int exx[4] = {0, 0, 0, 0};

View File

@@ -2,6 +2,7 @@
#include "bitutils.h"
#include "bitvec.h"
#include "fmgr.h"
#include "utils/varbit.h"
#include "vector.h"

View File

@@ -1,5 +1,7 @@
#include "postgres.h"
#include <math.h>
#include "halfutils.h"
#include "halfvec.h"

View File

@@ -13,12 +13,20 @@
#include "port.h" /* for strtof() */
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
#include "utils/fmgrprotos.h"
#include "utils/lsyscache.h"
#include "utils/numeric.h"
#include "utils/varbit.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 170000
#include "parser/scansup.h"
#endif
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
@@ -129,9 +137,9 @@ InitHalfVector(int dim)
return result;
}
/*
* Check for whitespace, since array_isspace() is static
*/
#if PG_VERSION_NUM >= 170000
#define halfvec_isspace(ch) scanner_isspace(ch)
#else
static inline bool
halfvec_isspace(char ch)
{
@@ -144,6 +152,7 @@ halfvec_isspace(char ch)
return true;
return false;
}
#endif
/*
* Check state array

View File

@@ -1,18 +1,25 @@
#include "postgres.h"
#include <float.h>
#include <limits.h>
#include <math.h>
#include "access/amapi.h"
#include "access/genam.h"
#include "access/reloptions.h"
#include "commands/progress.h"
#include "commands/vacuum.h"
#include "fmgr.h"
#include "hnsw.h"
#include "miscadmin.h"
#include "nodes/pg_list.h"
#include "storage/lwlock.h"
#include "utils/float.h"
#include "utils/guc.h"
#include "utils/relcache.h"
#include "utils/selfuncs.h"
#include "utils/spccache.h"
#include "vector.h"
#if PG_VERSION_NUM < 150000
#define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
@@ -260,10 +267,68 @@ FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnswhandler);
Datum
hnswhandler(PG_FUNCTION_ARGS)
{
#if PG_VERSION_NUM >= 190000
static const IndexAmRoutine amroutine = {
.type = T_IndexAmRoutine,
.amstrategies = 0,
.amsupport = 3,
.amoptsprocnum = 0,
.amcanorder = false,
.amcanorderbyop = true,
.amcanhash = false,
.amconsistentequality = false,
.amconsistentordering = false,
.amcanbackward = false,
.amcanunique = false,
.amcanmulticol = false,
.amoptionalkey = true,
.amsearcharray = false,
.amsearchnulls = false,
.amstorage = false,
.amclusterable = false,
.ampredlocks = false,
.amcanparallel = false,
.amcanbuildparallel = true,
.amcaninclude = false,
.amusemaintenanceworkmem = false,
.amsummarizing = false,
.amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL,
.amkeytype = InvalidOid,
.ambuild = hnswbuild,
.ambuildempty = hnswbuildempty,
.aminsert = hnswinsert,
.aminsertcleanup = NULL,
.ambulkdelete = hnswbulkdelete,
.amvacuumcleanup = hnswvacuumcleanup,
.amcanreturn = NULL,
.amcostestimate = hnswcostestimate,
.amgettreeheight = NULL,
.amoptions = hnswoptions,
.amproperty = NULL,
.ambuildphasename = hnswbuildphasename,
.amvalidate = hnswvalidate,
.amadjustmembers = NULL,
.ambeginscan = hnswbeginscan,
.amrescan = hnswrescan,
.amgettuple = hnswgettuple,
.amgetbitmap = NULL,
.amendscan = hnswendscan,
.ammarkpos = NULL,
.amrestrpos = NULL,
.amestimateparallelscan = NULL,
.aminitparallelscan = NULL,
.amparallelrescan = NULL,
.amtranslatestrategy = NULL,
.amtranslatecmptype = NULL,
};
PG_RETURN_POINTER(&amroutine);
#else
IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0;
amroutine->amsupport = 4;
amroutine->amsupport = 3;
amroutine->amoptsprocnum = 0;
amroutine->amcanorder = false;
amroutine->amcanorderbyop = true;
@@ -274,7 +339,7 @@ hnswhandler(PG_FUNCTION_ARGS)
#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;
@@ -333,18 +398,5 @@ hnswhandler(PG_FUNCTION_ARGS)
#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);
#endif
}

View File

@@ -3,15 +3,29 @@
#include "postgres.h"
#include <math.h>
#include "access/genam.h"
#include "access/parallel.h"
#include "lib/pairingheap.h"
#include "nodes/execnodes.h"
#include "port.h" /* for random() */
#include "storage/bufpage.h"
#include "storage/condition_variable.h"
#include "storage/lwlock.h"
#include "storage/s_lock.h"
#include "utils/relptr.h"
#include "utils/sampling.h"
#include "vector.h"
#ifdef HNSW_BENCH
#include "portability/instr_time.h"
#endif
#if PG_VERSION_NUM >= 190000
typedef Pointer Item;
#endif
#define HNSW_MAX_DIM 2000
#define HNSW_MAX_NNZ 1000
@@ -19,7 +33,6 @@
#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
@@ -69,6 +82,21 @@
#define HnswPageGetOpaque(page) ((HnswPageOpaque) PageGetSpecialPointer(page))
#define HnswPageGetMeta(page) ((HnswMetaPageData *) PageGetContents(page))
#ifdef HNSW_BENCH
#define HnswBench(name, code) \
do { \
instr_time start; \
instr_time duration; \
INSTR_TIME_SET_CURRENT(start); \
(code); \
INSTR_TIME_SET_CURRENT(duration); \
INSTR_TIME_SUBTRACT(duration, start); \
elog(INFO, "%s: %.3f ms", name, INSTR_TIME_GET_MILLISEC(duration)); \
} while (0)
#else
#define HnswBench(name, code) (code)
#endif
#if PG_VERSION_NUM >= 150000
#define RandomDouble() pg_prng_double(&pg_global_prng_state)
#define SeedRandom(seed) pg_prng_seed(&pg_global_prng_state, seed)
@@ -108,8 +136,6 @@
#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_scan;
@@ -137,7 +163,6 @@ HnswPtrDeclare(HnswElementData, HnswElementRelptr, HnswElementPtr);
HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr);
HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
HnswPtrDeclare(char, DatumRelptr, DatumPtr);
HnswPtrDeclare(IndexTupleData, IndexTupleRelptr, IndexTuplePtr);
struct HnswElementData
{
@@ -154,7 +179,6 @@ struct HnswElementData
OffsetNumber neighborOffno;
BlockNumber neighborPage;
DatumPtr value;
IndexTuplePtr itup;
LWLock lock;
};
@@ -180,7 +204,6 @@ typedef struct HnswSearchCandidate
pairingheap_node w_node;
HnswElementPtr element;
double distance;
bool matches;
} HnswSearchCandidate;
/* HNSW index options */
@@ -259,16 +282,14 @@ 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
@@ -297,8 +318,6 @@ typedef struct HnswBuildState
HnswGraph *graph;
double ml;
int maxLevel;
bool useIndexTuple;
TupleDesc tupdesc;
/* Memory */
MemoryContext graphCtx;
@@ -408,10 +427,11 @@ typedef struct HnswVacuumState
HnswSupport support;
/* Variables */
struct tidhash_hash *deleted;
struct tidhash_hash *deleting;
BufferAccessStrategy bas;
HnswNeighborTuple ntup;
HnswElementData highestPoint;
HnswElementData fallbackPoint;
/* Memory */
MemoryContext tmpCtx;
@@ -427,32 +447,30 @@ 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);
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);
HnswSearchCandidate *HnswEntryCandidate(char *base, HnswElement entryPoint, HnswQuery * q, Relation index, 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

@@ -36,11 +36,14 @@
*/
#include "postgres.h"
#include <math.h>
#include <limits.h>
#include "access/genam.h"
#include "access/parallel.h"
#include "access/relscan.h"
#include "access/table.h"
#include "access/tableam.h"
#include "access/tupdesc.h"
#include "access/xact.h"
#include "access/xloginsert.h"
#include "catalog/index.h"
@@ -48,11 +51,15 @@
#include "commands/progress.h"
#include "hnsw.h"
#include "miscadmin.h"
#include "nodes/execnodes.h"
#include "optimizer/optimizer.h"
#include "storage/bufmgr.h"
#include "storage/condition_variable.h"
#include "tcop/tcopprot.h"
#include "utils/datum.h"
#include "utils/memutils.h"
#include "utils/rel.h"
#include "utils/snapmgr.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
@@ -73,6 +80,8 @@
#define PARALLEL_KEY_HNSW_AREA UINT64CONST(0xA000000000000002)
#define PARALLEL_KEY_QUERY_TEXT UINT64CONST(0xA000000000000003)
#define HNSW_MAX_GRAPH_MEMORY (SIZE_MAX / 2)
/*
* Create the metapage
*/
@@ -152,7 +161,6 @@ CreateGraphPages(HnswBuildState * buildstate)
Page page;
HnswElementPtr iter = buildstate->graph->head;
char *base = buildstate->hnswarea;
bool useIndexTuple = buildstate->useIndexTuple;
/* Calculate sizes */
maxSize = HNSW_MAX_SIZE;
@@ -172,6 +180,7 @@ CreateGraphPages(HnswBuildState * buildstate)
Size etupSize;
Size ntupSize;
Size combinedSize;
Pointer valuePtr = HnswPtrAccess(base, element->value);
/* Update iterator */
iter = element->next;
@@ -180,7 +189,7 @@ 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);
@@ -190,7 +199,7 @@ 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))
@@ -331,18 +340,19 @@ 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 */
@@ -369,7 +379,7 @@ 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--)
{
@@ -391,7 +401,7 @@ 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);
}
}
@@ -407,14 +417,14 @@ UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, HnswEleme
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)
@@ -427,7 +437,6 @@ UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, HnswEleme
static void
InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
{
Relation index = buildstate->index;
HnswGraph *graph = buildstate->graph;
HnswSupport *support = &buildstate->support;
HnswElement entryPoint;
@@ -461,7 +470,7 @@ 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);
/* Update graph in memory */
UpdateGraphInMemory(support, element, m, entryPoint, buildstate);
@@ -480,20 +489,22 @@ 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;
Size memoryMargin;
/* 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));
/* In a parallel build, add a margin so allocations never fail */
memoryMargin = base == NULL ? 0 : 1024 * 1024;
/* Ensure graph not flushed when inserting */
LWLockAcquire(flushLock, LW_SHARED);
@@ -503,7 +514,7 @@ 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);
}
/*
@@ -516,7 +527,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
* Check that we have enough memory available for the new element now that
* we have the allocator lock, and flush pages if needed.
*/
if (graph->memoryUsed >= graph->memoryTotal)
if (graph->memoryUsed + memoryMargin >= graph->memoryTotal)
{
LWLockRelease(&graph->allocatorLock);
@@ -535,12 +546,12 @@ 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
@@ -549,10 +560,9 @@ 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, (char *) valuePtr);
/* Create a lock for the element */
LWLockInitialize(&element->lock, hnsw_lock_tranche_id);
@@ -610,7 +620,7 @@ InitGraph(HnswGraph * graph, char *base, Size memoryTotal)
HnswPtrStore(base, graph->head, (HnswElement) NULL);
HnswPtrStore(base, graph->entryPoint, (HnswElement) NULL);
graph->memoryUsed = 0;
graph->memoryTotal = memoryTotal;
graph->memoryTotal = Min(memoryTotal, HNSW_MAX_GRAPH_MEMORY);
graph->flushed = false;
graph->indtuples = 0;
SpinLockInit(&graph->lock);
@@ -651,9 +661,17 @@ static void *
HnswSharedMemoryAlloc(Size size, void *state)
{
HnswBuildState *buildstate = (HnswBuildState *) state;
void *chunk = buildstate->hnswarea + buildstate->graph->memoryUsed;
Size alignedSize = MAXALIGN(size);
void *chunk;
buildstate->graph->memoryUsed += MAXALIGN(size);
if (alignedSize > 1024 * 1024)
elog(ERROR, "hnsw allocation too large");
if (buildstate->graph->memoryUsed + alignedSize > buildstate->graph->memoryTotal)
elog(ERROR, "hnsw allocator out of memory");
chunk = buildstate->hnswarea + buildstate->graph->memoryUsed;
buildstate->graph->memoryUsed += alignedSize;
return chunk;
}
@@ -679,19 +697,6 @@ 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,
@@ -714,12 +719,10 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
/* Get support functions */
HnswInitSupport(&buildstate->support, index);
InitGraph(&buildstate->graphData, NULL, (Size) maintenance_work_mem * 1024L);
InitGraph(&buildstate->graphData, NULL, maintenance_work_mem * (Size) 1024);
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",
@@ -800,7 +803,11 @@ HnswParallelScanAndInsert(Relation heapRel, Relation indexRel, HnswShared * hnsw
buildstate.hnswarea = hnswarea;
InitAllocator(&buildstate.allocator, &HnswSharedMemoryAlloc, &buildstate);
scan = table_beginscan_parallel(heapRel,
ParallelTableScanFromHnswShared(hnswshared));
ParallelTableScanFromHnswShared(hnswshared)
#if PG_VERSION_NUM >= 190000
,SO_NONE
#endif
);
reltuples = table_index_build_scan(heapRel, indexRel, indexInfo,
true, progress, BuildCallback,
(void *) &buildstate, scan);
@@ -949,11 +956,13 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
/* Leave space for other objects in shared memory */
/* Docker has a default limit of 64 MB for shm_size */
/* which happens to be the default value of maintenance_work_mem */
esthnswarea = maintenance_work_mem * 1024L;
esthnswarea = maintenance_work_mem * (Size) 1024;
estother = 3 * 1024 * 1024;
if (esthnswarea > estother)
esthnswarea -= estother;
esthnswarea = Min(esthnswarea, HNSW_MAX_GRAPH_MEMORY);
shm_toc_estimate_chunk(&pcxt->estimator, esthnswarea);
shm_toc_estimate_keys(&pcxt->estimator, 2);
@@ -996,8 +1005,7 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
snapshot);
hnswarea = (char *) shm_toc_allocate(pcxt->toc, esthnswarea);
/* Report less than allocated so never fails */
InitGraph(&hnswshared->graphData, hnswarea, esthnswarea - 1024 * 1024);
InitGraph(&hnswshared->graphData, hnswarea, esthnswarea);
/*
* Avoid base address for relptr for Postgres < 14.5

View File

@@ -1,13 +1,15 @@
#include "postgres.h"
#include <math.h>
#include "access/genam.h"
#include "access/generic_xlog.h"
#include "hnsw.h"
#include "nodes/execnodes.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
#include "storage/lwlock.h"
#include "utils/datum.h"
#include "utils/memutils.h"
#include "utils/rel.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
@@ -160,10 +162,9 @@ 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;
@@ -171,7 +172,7 @@ 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);
@@ -388,9 +389,8 @@ 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 */
@@ -434,8 +434,6 @@ 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);
@@ -641,30 +639,21 @@ 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;
@@ -677,12 +666,12 @@ FindDuplicateOnDisk(Relation index, HnswElement element, bool building, TupleDes
* Update graph on disk
*/
static void
UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, int m, 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 */
@@ -704,7 +693,7 @@ 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;
@@ -712,7 +701,6 @@ 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
@@ -726,8 +714,7 @@ 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, (char *) DatumGetPointer(value));
/* Prevent concurrent inserts when likely updating entry point */
if (entryPoint == NULL || element->level > entryPoint->level)
@@ -744,10 +731,10 @@ 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);
/* Update graph on disk */
UpdateGraphOnDisk(index, support, element, m, entryPoint, building, tupdesc);
UpdateGraphOnDisk(index, support, element, m, entryPoint, building);
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
@@ -761,18 +748,17 @@ 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

@@ -1,12 +1,23 @@
#include "postgres.h"
#include <limits.h>
#include "access/genam.h"
#include "access/relscan.h"
#include "hnsw.h"
#include "lib/pairingheap.h"
#include "miscadmin.h"
#include "nodes/pg_list.h"
#include "pgstat.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
#include "utils/float.h"
#include "utils/memutils.h"
#include "utils/relcache.h"
#include "utils/snapmgr.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/*
* Algorithm 5 from paper
@@ -22,30 +33,26 @@ 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);
ep = w;
}
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, support, m, false, NULL, inMemory, &so->v, hnsw_iterative_scan != HNSW_ITERATIVE_SCAN_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);
}
/*
@@ -76,7 +83,7 @@ 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);
}
/*
@@ -100,7 +107,7 @@ 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;
@@ -146,7 +153,7 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
/* 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);
so->maxMemory = Min(maxMemory, (double) (SIZE_MAX / 2));
scan->opaque = so;
@@ -287,7 +294,7 @@ 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);

View File

@@ -2,18 +2,20 @@
#include <math.h>
#include "access/genam.h"
#include "access/generic_xlog.h"
#include "catalog/pg_type.h"
#include "catalog/pg_type_d.h"
#include "common/hashfn.h"
#include "fmgr.h"
#include "hnsw.h"
#include "lib/pairingheap.h"
#include "nodes/pg_list.h"
#include "port/atomics.h"
#include "sparsevec.h"
#include "storage/bufmgr.h"
#include "utils/datum.h"
#include "utils/memdebug.h"
#include "utils/rel.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
@@ -150,39 +152,11 @@ 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
*/
@@ -198,38 +172,7 @@ 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;
}
/*
@@ -319,8 +262,7 @@ 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);
HnswPtrStore(base, element->value, (char *) NULL);
return element;
}
@@ -346,8 +288,7 @@ HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno)
element->blkno = blkno;
element->offno = offno;
HnswPtrStore(base, element->neighbors, (HnswNeighborArrayPtr *) NULL);
HnswPtrStore(base, element->value, (Pointer) NULL);
HnswPtrStore(base, element->itup, (IndexTuple) NULL);
HnswPtrStore(base, element->value, (char *) NULL);
return element;
}
@@ -460,13 +401,11 @@ 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]));
@@ -480,14 +419,10 @@ 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;
}
@@ -496,8 +431,10 @@ 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;
@@ -509,19 +446,7 @@ 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));
}
/*
@@ -563,7 +488,7 @@ 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;
@@ -587,128 +512,26 @@ 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, (char *) 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(BlockNumber blkno, OffsetNumber offno, double *distance, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, double *maxDistance, HnswElement * element)
{
Buffer buf;
Page page;
@@ -723,26 +546,16 @@ HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, double *distance, boo
Assert(HnswIsElementTuple(etup));
if (unlikely(etup->deleted))
elog(ERROR, "cannot load deleted element");
/* 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 */
@@ -751,7 +564,7 @@ HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, double *distance, boo
if (*element == NULL)
*element = HnswInitElementFromBlock(blkno, offno);
HnswLoadElementFromTuple(*element, etup, true, loadVec, index);
HnswLoadElementFromTuple(*element, etup, true, loadVec);
}
UnlockReleaseBuffer(buf);
@@ -761,34 +574,32 @@ 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);
HnswLoadElementImpl(element->blkno, 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, bool matches)
HnswInitSearchCandidate(char *base, HnswElement element, double distance)
{
HnswSearchCandidate *sc = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, sc->element, element);
sc->distance = distance;
sc->matches = matches;
return sc;
}
@@ -796,17 +607,17 @@ HnswInitSearchCandidate(char *base, HnswElement element, double distance, bool m
* 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)
{
bool inMemory = index == NULL;
double distance;
bool matches;
if (inMemory)
distance = GetElementDistance(base, entryPoint, &matches, q, index, support);
distance = GetElementDistance(base, entryPoint, q, support);
else
HnswLoadElement(entryPoint, &distance, &matches, q, index, support, loadVec, NULL);
HnswLoadElement(entryPoint, &distance, q, index, support, loadVec, NULL);
return HnswInitSearchCandidate(base, entryPoint, distance, matches);
return HnswInitSearchCandidate(base, entryPoint, distance);
}
/*
@@ -1009,7 +820,7 @@ HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *u
* 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)
{
List *w = NIL;
pairingheap *C = pairingheap_allocate(CompareNearestCandidates, NULL);
@@ -1022,8 +833,7 @@ 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 (v == NULL)
{
@@ -1064,10 +874,6 @@ 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
@@ -1102,7 +908,6 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
HnswElement eElement;
HnswSearchCandidate *e;
double eDistance;
bool eMatches;
bool alwaysAdd = wlen < ef;
f = HnswGetSearchCandidate(w_node, pairingheap_first(W));
@@ -1110,7 +915,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
if (inMemory)
{
eElement = unvisited[i].element;
eDistance = GetElementDistance(base, eElement, &eMatches, q, index, support);
eDistance = GetElementDistance(base, eElement, q, support);
}
else
{
@@ -1120,18 +925,18 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
/* 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(blkno, offno, &eDistance, q, index, support, inserting, alwaysAdd || discarded != NULL ? NULL : &f->distance, &eElement);
if (eElement == NULL)
continue;
}
if (eElement == NULL || !(eDistance < f->distance || alwaysAdd))
if (!(eDistance < f->distance || alwaysAdd))
{
if (discarded != NULL)
{
/* Create a new candidate */
e = HnswInitSearchCandidate(base, eElement, eDistance, eMatches);
e = HnswInitSearchCandidate(base, eElement, eDistance);
pairingheap_add(*discarded, &e->w_node);
}
@@ -1143,7 +948,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
continue;
/* Create a new candidate */
e = HnswInitSearchCandidate(base, eElement, eDistance, eMatches);
e = HnswInitSearchCandidate(base, eElement, eDistance);
pairingheap_add(C, &e->c_node);
pairingheap_add(W, &e->w_node);
@@ -1154,10 +959,6 @@ 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 */
@@ -1235,24 +1036,18 @@ 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;
@@ -1265,7 +1060,7 @@ 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);
@@ -1299,7 +1094,7 @@ 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 */
@@ -1312,7 +1107,8 @@ 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;
}
@@ -1324,7 +1120,7 @@ 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);
}
@@ -1332,7 +1128,7 @@ 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);
}
@@ -1409,7 +1205,7 @@ 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)
@@ -1480,19 +1276,17 @@ 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)
{
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)
@@ -1503,13 +1297,13 @@ 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);
ep = w;
}
@@ -1528,7 +1322,7 @@ 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);
/* Convert search candidates to candidates */
foreach(lc2, w)
@@ -1552,7 +1346,7 @@ 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);

View File

@@ -1,13 +1,14 @@
#include "postgres.h"
#include <math.h>
#include "access/genam.h"
#include "access/generic_xlog.h"
#include "commands/vacuum.h"
#include "hnsw.h"
#include "nodes/pg_list.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
#include "utils/memutils.h"
#include "utils/rel.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
@@ -18,12 +19,12 @@
#endif
/*
* Check if deleted list contains an index TID
* Check if deletion list contains an element
*/
static bool
DeletedContains(tidhash_hash * deleted, ItemPointer indextid)
DeletingElement(tidhash_hash * deleting, ItemPointer indextid)
{
return tidhash_lookup(deleted, *indextid) != NULL;
return tidhash_lookup(deleting, *indextid) != NULL;
}
/*
@@ -36,17 +37,20 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
{
BlockNumber blkno = HNSW_HEAD_BLKNO;
HnswElement highestPoint = &vacuumstate->highestPoint;
HnswElement fallbackPoint = &vacuumstate->fallbackPoint;
Relation index = vacuumstate->index;
BufferAccessStrategy bas = vacuumstate->bas;
HnswElement entryPoint = HnswGetEntryPoint(vacuumstate->index);
IndexBulkDeleteResult *stats = vacuumstate->stats;
/* Store separately since highestPoint.level is uint8 */
/* Store separately since HnswElement level is uint8 */
int highestLevel = -1;
int fallbackLevel = -1;
/* Initialize highest point */
/* Initialize highest point and fallback point */
highestPoint->blkno = InvalidBlockNumber;
highestPoint->offno = InvalidOffsetNumber;
fallbackPoint->blkno = InvalidBlockNumber;
fallbackPoint->offno = InvalidOffsetNumber;
while (BlockNumberIsValid(blkno))
{
@@ -76,6 +80,14 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
if (!HnswIsElementTuple(etup))
continue;
/*
* Skip deleted tuples. It is important they are not added to the
* deletion list to avoid false positives in NeedsUpdated and
* ConfirmRepaired.
*/
if (etup->deleted)
continue;
if (ItemPointerIsValid(&etup->heaptids[0]))
{
for (int i = 0; i < HNSW_HEAPTIDS; i++)
@@ -109,23 +121,40 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
if (!ItemPointerIsValid(&etup->heaptids[0]))
{
ItemPointerData ip;
ItemPointerData indextid;
bool found;
/* Add to deleted list */
ItemPointerSet(&ip, blkno, offno);
/* Add to deletion list */
ItemPointerSet(&indextid, blkno, offno);
tidhash_insert(vacuumstate->deleted, ip, &found);
tidhash_insert(vacuumstate->deleting, indextid, &found);
Assert(!found);
}
else if (etup->level > highestLevel && !(entryPoint != NULL && blkno == entryPoint->blkno && offno == entryPoint->offno))
else if (etup->level > highestLevel)
{
/* Keep track of highest non-entry point */
if (BlockNumberIsValid(highestPoint->blkno))
{
/* Current highest point becomes fallback */
fallbackPoint->blkno = highestPoint->blkno;
fallbackPoint->offno = highestPoint->offno;
fallbackPoint->level = highestPoint->level;
fallbackLevel = highestLevel;
}
/* Keep track of highest point */
highestPoint->blkno = blkno;
highestPoint->offno = offno;
highestPoint->level = etup->level;
highestLevel = etup->level;
}
else if (etup->level > fallbackLevel)
{
/* Keep track of second highest point */
fallbackPoint->blkno = blkno;
fallbackPoint->offno = offno;
fallbackPoint->level = etup->level;
fallbackLevel = etup->level;
}
}
blkno = HnswPageGetOpaque(page)->nextblkno;
@@ -137,6 +166,10 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
UnlockReleaseBuffer(buf);
}
#ifdef HNSW_MEMORY
elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(CurrentMemoryContext, true) / 1024);
#endif
}
/*
@@ -167,8 +200,8 @@ NeedsUpdated(HnswVacuumState * vacuumstate, HnswElement element)
if (!ItemPointerIsValid(indextid))
continue;
/* Check if in deleted list */
if (DeletedContains(vacuumstate->deleted, indextid))
/* Check if in deletion list */
if (DeletingElement(vacuumstate->deleting, indextid))
{
needsUpdated = true;
break;
@@ -177,7 +210,8 @@ NeedsUpdated(HnswVacuumState * vacuumstate, HnswElement element)
/* Also update if layer 0 is not full */
/* This could indicate too many candidates being deleted during insert */
if (!needsUpdated)
/* There should always be more than zero indextids, but check for safety */
if (!needsUpdated && ntup->count > 0)
needsUpdated = !ItemPointerIsValid(&ntup->indextids[ntup->count - 1]);
UnlockReleaseBuffer(buf);
@@ -212,7 +246,7 @@ 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);
/* Zero memory for each element */
MemSet(ntup, 0, HNSW_TUPLE_ALLOC_SIZE);
@@ -263,12 +297,27 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
/* Get a shared lock */
LockPage(index, HNSW_UPDATE_LOCK, ShareLock);
/* Load element */
HnswLoadElement(highestPoint, NULL, NULL, NULL, index, support, true, NULL);
/* Get latest entry point */
entryPoint = HnswGetEntryPoint(index);
/* Repair if needed */
if (NeedsUpdated(vacuumstate, highestPoint))
RepairGraphElement(vacuumstate, highestPoint, HnswGetEntryPoint(index));
/* Use fallback point if highest point is entry point */
if (entryPoint != NULL && entryPoint->blkno == highestPoint->blkno && entryPoint->offno == highestPoint->offno)
{
highestPoint = &vacuumstate->fallbackPoint;
if (!BlockNumberIsValid(highestPoint->blkno))
highestPoint = NULL;
}
if (highestPoint != NULL)
{
/* Load element */
HnswLoadElement(highestPoint, NULL, NULL, index, support, true, NULL);
/* Repair if needed */
if (NeedsUpdated(vacuumstate, highestPoint))
RepairGraphElement(vacuumstate, highestPoint, entryPoint);
}
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, ShareLock);
@@ -286,7 +335,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
ItemPointerSet(&epData, entryPoint->blkno, entryPoint->offno);
if (DeletedContains(vacuumstate->deleted, &epData))
if (DeletingElement(vacuumstate->deleting, &epData))
{
/*
* Replace the entry point with the highest point. If highest
@@ -302,7 +351,7 @@ 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))
{
@@ -372,13 +421,17 @@ RepairGraph(HnswVacuumState * vacuumstate)
if (!HnswIsElementTuple(etup))
continue;
/* Skip deleted tuples */
if (etup->deleted)
continue;
/* Skip updating neighbors if being deleted */
if (!ItemPointerIsValid(&etup->heaptids[0]))
continue;
/* Create an element */
element = HnswInitElementFromBlock(blkno, offno);
HnswLoadElementFromTuple(element, etup, false, true, index);
HnswLoadElementFromTuple(element, etup, false, true);
elements = lappend(elements, element);
}
@@ -435,6 +488,103 @@ RepairGraph(HnswVacuumState * vacuumstate)
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
MemoryContextReset(vacuumstate->tmpCtx);
#ifdef HNSW_VACUUM_PROGRESS
if (!BlockNumberIsValid(blkno) || (blkno - HNSW_HEAD_BLKNO) % 1000 == 0)
{
BlockNumber totalBlocks = RelationGetNumberOfBlocks(index);
BlockNumber currentBlocks = BlockNumberIsValid(blkno) ? blkno : totalBlocks;
elog(INFO, "hnsw vacuum progress: %.1f%%", 100.0 * currentBlocks / totalBlocks);
}
#endif
}
}
/*
* Confirm graph was repaired
*/
static void
ConfirmRepaired(HnswVacuumState * vacuumstate)
{
BlockNumber blkno = HNSW_HEAD_BLKNO;
Relation index = vacuumstate->index;
BufferAccessStrategy bas = vacuumstate->bas;
while (BlockNumberIsValid(blkno))
{
Buffer buf;
Page page;
OffsetNumber offno;
OffsetNumber maxoffno;
vacuum_delay_point();
buf = ReadBufferExtended(index, MAIN_FORKNUM, blkno, RBM_NORMAL, bas);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
maxoffno = PageGetMaxOffsetNumber(page);
/* Iterate over nodes */
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
HnswNeighborTuple ntup;
Buffer nbuf;
Page npage;
BlockNumber neighborPage;
OffsetNumber neighborOffno;
/* Skip neighbor tuples */
if (!HnswIsElementTuple(etup))
continue;
/* Skip deleted tuples */
if (etup->deleted)
continue;
/* Skip if being deleted */
if (!ItemPointerIsValid(&etup->heaptids[0]))
continue;
/* Get neighbor page */
neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
if (neighborPage == blkno)
{
nbuf = buf;
npage = page;
}
else
{
nbuf = ReadBufferExtended(index, MAIN_FORKNUM, neighborPage, RBM_NORMAL, bas);
LockBuffer(nbuf, BUFFER_LOCK_SHARE);
npage = BufferGetPage(nbuf);
}
ntup = (HnswNeighborTuple) PageGetItem(npage, PageGetItemId(npage, neighborOffno));
/* Check neighbors */
for (int i = 0; i < ntup->count; i++)
{
ItemPointer indextid = &ntup->indextids[i];
if (!ItemPointerIsValid(indextid))
continue;
/* Check if in deletion list */
if (DeletingElement(vacuumstate->deleting, indextid))
elog(ERROR, "hnsw graph not repaired");
}
if (nbuf != buf)
UnlockReleaseBuffer(nbuf);
}
blkno = HnswPageGetOpaque(page)->nextblkno;
UnlockReleaseBuffer(buf);
}
}
@@ -448,13 +598,17 @@ 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
* tuples about to be deleted. Scans after this point will not, since the
* graph has been repaired.
* Wait for inserts and index scans to complete. Inserts and scans before
* this point may visit tuples about to be deleted. Inserts and scans
* after this point will not, since the graph has been repaired.
*/
LockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
UnlockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
ConfirmRepaired(vacuumstate);
LockPage(index, HNSW_SCAN_LOCK, ExclusiveLock);
UnlockPage(index, HNSW_SCAN_LOCK, ExclusiveLock);
@@ -529,15 +683,9 @@ MarkDeleted(HnswVacuumState * vacuumstate)
ntup = (HnswNeighborTuple) PageGetItem(npage, PageGetItemId(npage, neighborOffno));
/* Overwrite element */
/* Use memset instead of MemSet to keep clang-tidy happy */
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++)
@@ -608,7 +756,7 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
HnswGetMetaPageInfo(index, &vacuumstate->m, NULL);
/* Create hash table */
vacuumstate->deleted = tidhash_create(CurrentMemoryContext, 256, NULL);
vacuumstate->deleting = tidhash_create(CurrentMemoryContext, 256, NULL);
}
/*
@@ -617,7 +765,7 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
static void
FreeVacuumState(HnswVacuumState * vacuumstate)
{
tidhash_destroy(vacuumstate->deleted);
tidhash_destroy(vacuumstate->deleting);
FreeAccessStrategy(vacuumstate->bas);
pfree(vacuumstate->ntup);
MemoryContextDelete(vacuumstate->tmpCtx);
@@ -635,13 +783,13 @@ hnswbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
InitVacuumState(&vacuumstate, info, stats, callback, callback_state);
/* Pass 1: Remove heap TIDs */
RemoveHeapTids(&vacuumstate);
HnswBench("RemoveHeapTids", RemoveHeapTids(&vacuumstate));
/* Pass 2: Repair graph */
RepairGraph(&vacuumstate);
HnswBench("RepairGraph", RepairGraph(&vacuumstate));
/* Pass 3: Mark as deleted */
MarkDeleted(&vacuumstate);
/* Passes 3 and 4: Confirm repaired and mark as deleted */
HnswBench("MarkDeleted", MarkDeleted(&vacuumstate));
FreeVacuumState(&vacuumstate);

View File

@@ -2,23 +2,33 @@
#include <float.h>
#include "access/genam.h"
#include "access/generic_xlog.h"
#include "access/itup.h"
#include "access/relscan.h"
#include "access/table.h"
#include "access/tableam.h"
#include "access/tupdesc.h"
#include "access/parallel.h"
#include "access/xact.h"
#include "bitvec.h"
#include "access/xloginsert.h"
#include "catalog/index.h"
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
#include "commands/progress.h"
#include "halfvec.h"
#include "fmgr.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "nodes/execnodes.h"
#include "optimizer/optimizer.h"
#include "storage/bufmgr.h"
#include "storage/condition_variable.h"
#include "tcop/tcopprot.h"
#include "utils/memutils.h"
#include "vector.h"
#include "utils/rel.h"
#include "utils/sampling.h"
#include "utils/snapmgr.h"
#include "utils/tuplesort.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
@@ -53,15 +63,13 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/*
* Normalize with KMEANS_NORM_PROC since spherical distance function
* expects unit vectors
* Check with KMEANS_NORM_PROC that the value can be normalized since
* spherical distance function expects unit vectors
*/
if (buildstate->kmeansnormprocinfo != NULL)
{
if (!IvfflatCheckNorm(buildstate->kmeansnormprocinfo, buildstate->collation, value))
return;
value = IvfflatNormValue(buildstate->typeInfo, buildstate->collation, value);
}
if (samples->length < targsamples)
@@ -72,7 +80,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
else
{
if (buildstate->rowstoskip < 0)
buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, samples->length, targsamples);
buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, buildstate->samplerows, targsamples);
if (buildstate->rowstoskip <= 0)
{
@@ -88,6 +96,9 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
buildstate->rowstoskip -= 1;
}
/* Increment after reservoir_get_next_S */
buildstate->samplerows += 1;
}
/*
@@ -124,6 +135,7 @@ SampleRows(IvfflatBuildState * buildstate)
int targsamples = buildstate->samples->maxlen;
BlockNumber totalblocks = RelationGetNumberOfBlocks(buildstate->heap);
buildstate->samplerows = 0;
buildstate->rowstoskip = -1;
BlockSampler_Init(&buildstate->bs, totalblocks, targsamples, RandomInt());
@@ -133,9 +145,14 @@ SampleRows(IvfflatBuildState * buildstate)
{
BlockNumber targblock = BlockSampler_Next(&buildstate->bs);
/* Set anyvisible to false like table_index_build_scan */
table_index_build_range_scan(buildstate->heap, buildstate->index, buildstate->indexInfo,
false, true, false, targblock, 1, SampleCallback, (void *) buildstate, NULL);
false, false, false, targblock, 1, SampleCallback, (void *) buildstate, NULL);
}
/* Normalize if needed */
if (buildstate->kmeansnormprocinfo != NULL)
IvfflatNormVectors(buildstate->typeInfo, buildstate->collation, buildstate->samples, buildstate->tmpCtx);
}
/*
@@ -365,10 +382,20 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 1, "list", INT4OID, -1, 0);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 3, "vector", TupleDescAttr(buildstate->tupdesc, 0)->atttypid, -1, 0);
#if PG_VERSION_NUM >= 190000
TupleDescFinalize(buildstate->sortdesc);
#endif
buildstate->slot = MakeSingleTupleTableSlot(buildstate->sortdesc, &TTSOpsVirtual);
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, buildstate->typeInfo->itemSize(buildstate->dimensions));
buildstate->memoryUsed = 0;
buildstate->itemsize = buildstate->typeInfo->itemSize(buildstate->dimensions);
buildstate->memoryUsed += VECTOR_ARRAY_SIZE(buildstate->lists, buildstate->itemsize);
IvfflatCheckMemoryUsage(buildstate->memoryUsed);
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, buildstate->itemsize);
/* TODO Move allocation to page creation */
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
@@ -411,22 +438,30 @@ ComputeCenters(IvfflatBuildState * buildstate)
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_KMEANS);
/* Target 50 samples per list, with at least 10000 samples */
/* The number of samples has a large effect on index build time */
numSamples = buildstate->lists * 50;
if (numSamples < 10000)
numSamples = 10000;
/* Skip samples for unlogged table */
if (buildstate->heap == NULL)
numSamples = 1;
else
{
int64 maxTuples = (int64) RelationGetNumberOfBlocks(buildstate->heap) * MaxHeapTuplesPerPage;
/* Target 50 samples per list, with at least 10000 samples */
/* The number of samples has a large effect on index build time */
numSamples = buildstate->lists * 50;
if (numSamples < 10000)
numSamples = 10000;
/* Save memory since will not have more than max tuples */
numSamples = Max(Min(numSamples, maxTuples), 1);
}
/* Sample rows */
/* TODO Ensure within maintenance_work_mem */
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions, buildstate->centers->itemsize);
buildstate->memoryUsed += VECTOR_ARRAY_SIZE(numSamples, buildstate->itemsize);
IvfflatCheckMemoryUsage(buildstate->memoryUsed);
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions, buildstate->itemsize);
if (buildstate->heap != NULL)
{
SampleRows(buildstate);
IvfflatBench("sample rows", SampleRows(buildstate));
if (buildstate->samples->length < buildstate->lists)
{
@@ -438,7 +473,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
}
/* Calculate centers */
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers, buildstate->typeInfo));
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers, buildstate->typeInfo, buildstate->memoryUsed));
/* Free samples before we allocate more memory */
VectorArrayFree(buildstate->samples);
@@ -641,7 +676,11 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
ivfspool->sortstate = InitBuildSortState(buildstate.sortdesc, sortmem, coordinate);
buildstate.sortstate = ivfspool->sortstate;
scan = table_beginscan_parallel(ivfspool->heap,
ParallelTableScanFromIvfflatShared(ivfshared));
ParallelTableScanFromIvfflatShared(ivfshared)
#if PG_VERSION_NUM >= 190000
,SO_NONE
#endif
);
reltuples = table_index_build_scan(ivfspool->heap, ivfspool->index, indexInfo,
true, progress, BuildCallback,
(void *) &buildstate, scan);

View File

@@ -3,14 +3,19 @@
#include <float.h>
#include "access/amapi.h"
#include "access/genam.h"
#include "access/reloptions.h"
#include "commands/progress.h"
#include "commands/vacuum.h"
#include "fmgr.h"
#include "ivfflat.h"
#include "nodes/pg_list.h"
#include "utils/float.h"
#include "utils/guc.h"
#include "utils/relcache.h"
#include "utils/selfuncs.h"
#include "utils/spccache.h"
#include "vector.h"
#if PG_VERSION_NUM < 150000
#define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
@@ -179,6 +184,64 @@ FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflathandler);
Datum
ivfflathandler(PG_FUNCTION_ARGS)
{
#if PG_VERSION_NUM >= 190000
static const IndexAmRoutine amroutine = {
.type = T_IndexAmRoutine,
.amstrategies = 0,
.amsupport = 5,
.amoptsprocnum = 0,
.amcanorder = false,
.amcanorderbyop = true,
.amcanhash = false,
.amconsistentequality = false,
.amconsistentordering = false,
.amcanbackward = false,
.amcanunique = false,
.amcanmulticol = false,
.amoptionalkey = true,
.amsearcharray = false,
.amsearchnulls = false,
.amstorage = false,
.amclusterable = false,
.ampredlocks = false,
.amcanparallel = false,
.amcanbuildparallel = true,
.amcaninclude = false,
.amusemaintenanceworkmem = false,
.amsummarizing = false,
.amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL,
.amkeytype = InvalidOid,
.ambuild = ivfflatbuild,
.ambuildempty = ivfflatbuildempty,
.aminsert = ivfflatinsert,
.aminsertcleanup = NULL,
.ambulkdelete = ivfflatbulkdelete,
.amvacuumcleanup = ivfflatvacuumcleanup,
.amcanreturn = NULL,
.amcostestimate = ivfflatcostestimate,
.amgettreeheight = NULL,
.amoptions = ivfflatoptions,
.amproperty = NULL,
.ambuildphasename = ivfflatbuildphasename,
.amvalidate = ivfflatvalidate,
.amadjustmembers = NULL,
.ambeginscan = ivfflatbeginscan,
.amrescan = ivfflatrescan,
.amgettuple = ivfflatgettuple,
.amgetbitmap = NULL,
.amendscan = ivfflatendscan,
.ammarkpos = NULL,
.amrestrpos = NULL,
.amestimateparallelscan = NULL,
.aminitparallelscan = NULL,
.amparallelrescan = NULL,
.amtranslatestrategy = NULL,
.amtranslatecmptype = NULL,
};
PG_RETURN_POINTER(&amroutine);
#else
IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0;
@@ -252,4 +315,5 @@ ivfflathandler(PG_FUNCTION_ARGS)
#endif
PG_RETURN_POINTER(amroutine);
#endif
}

View File

@@ -9,6 +9,7 @@
#include "lib/pairingheap.h"
#include "nodes/execnodes.h"
#include "port.h" /* for random() */
#include "storage/condition_variable.h"
#include "utils/sampling.h"
#include "utils/tuplesort.h"
#include "vector.h"
@@ -25,6 +26,10 @@
#include "portability/instr_time.h"
#endif
#if PG_VERSION_NUM >= 190000
typedef Pointer Item;
#endif
#define IVFFLAT_MAX_DIM 2000
/* Support functions */
@@ -199,6 +204,7 @@ typedef struct IvfflatBuildState
VectorArray samples;
VectorArray centers;
ListInfo *listInfo;
Size itemsize;
#ifdef IVFFLAT_KMEANS_DEBUG
double inertia;
@@ -209,7 +215,8 @@ typedef struct IvfflatBuildState
/* Sampling */
BlockSamplerData bs;
ReservoirStateData rstate;
int rowstoskip;
double samplerows;
double rowstoskip;
/* Sorting */
Tuplesortstate *sortstate;
@@ -217,6 +224,7 @@ typedef struct IvfflatBuildState
TupleTableSlot *slot;
/* Memory */
Size memoryUsed;
MemoryContext tmpCtx;
/* Parallel builds */
@@ -297,22 +305,32 @@ typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
static inline Pointer
VectorArrayGet(VectorArray arr, int offset)
{
if (offset >= arr->maxlen)
elog(ERROR, "safety check failed");
return ((char *) arr->items) + (offset * arr->itemsize);
}
static inline void
VectorArraySet(VectorArray arr, int offset, Pointer val)
{
memcpy(VectorArrayGet(arr, offset), val, VARSIZE_ANY(val));
Size size = VARSIZE_ANY(val);
if (size > arr->itemsize)
elog(ERROR, "safety check failed");
memcpy(VectorArrayGet(arr, offset), val, size);
}
/* Methods */
VectorArray VectorArrayInit(int maxlen, int dimensions, Size itemsize);
void VectorArrayFree(VectorArray arr);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo, Size memoryUsed);
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
Datum IvfflatNormValue(const IvfflatTypeInfo * typeInfo, Oid collation, Datum value);
bool IvfflatCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value);
void IvfflatNormVectors(const IvfflatTypeInfo * typeInfo, Oid collation, VectorArray arr, MemoryContext tmpCtx);
void IvfflatCheckMemoryUsage(Size totalSize);
int IvfflatGetLists(Relation index);
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);

View File

@@ -2,11 +2,16 @@
#include <float.h>
#include "access/genam.h"
#include "access/generic_xlog.h"
#include "access/itup.h"
#include "fmgr.h"
#include "ivfflat.h"
#include "nodes/execnodes.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h"
#include "utils/memutils.h"
#include "utils/rel.h"
/*
* Find the list that minimizes the distance function

View File

@@ -1,17 +1,16 @@
#include "postgres.h"
#include <float.h>
#include <limits.h>
#include <math.h>
#include "bitvec.h"
#include "halfutils.h"
#include "halfvec.h"
#include "access/genam.h"
#include "fmgr.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "utils/builtins.h"
#include "utils/datum.h"
#include "utils/memutils.h"
#include "vector.h"
#include "utils/relcache.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
@@ -101,36 +100,50 @@ NormCenters(const IvfflatTypeInfo * typeInfo, Oid collation, VectorArray centers
MemoryContext normCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat norm temporary context",
ALLOCSET_DEFAULT_SIZES);
MemoryContext oldCtx = MemoryContextSwitchTo(normCtx);
for (int j = 0; j < centers->length; j++)
{
Datum center = PointerGetDatum(VectorArrayGet(centers, j));
Datum newCenter = IvfflatNormValue(typeInfo, collation, center);
Size size = VARSIZE_ANY(DatumGetPointer(newCenter));
if (size > centers->itemsize)
elog(ERROR, "safety check failed");
memcpy(DatumGetPointer(center), DatumGetPointer(newCenter), size);
MemoryContextReset(normCtx);
}
MemoryContextSwitchTo(oldCtx);
IvfflatNormVectors(typeInfo, collation, centers, normCtx);
MemoryContextDelete(normCtx);
}
/*
* Quick approach if we have no data
* Check if vector array contains a vector
*/
static bool
VectorArrayContains(VectorArray arr, Pointer val)
{
Datum d = PointerGetDatum(val);
for (int i = 0; i < arr->length; i++)
{
if (datumIsEqual(d, PointerGetDatum(VectorArrayGet(arr, i)), false, -1))
return true;
}
return false;
}
/*
* Quick approach if we have little data
*/
static void
RandomCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeInfo)
QuickCenters(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo)
{
int dimensions = centers->dim;
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
Oid collation = index->rd_indcollation[0];
float *x = (float *) palloc(sizeof(float) * dimensions);
/* Fill with unique samples (already normalized) */
for (int i = 0; i < samples->length; i++)
{
Pointer sample = VectorArrayGet(samples, i);
if (!VectorArrayContains(centers, sample))
{
VectorArraySet(centers, centers->length, sample);
centers->length++;
}
}
/* Fill with random data */
while (centers->length < centers->maxlen)
{
@@ -260,7 +273,7 @@ ComputeNewCenters(VectorArray samples, float *agg, VectorArray newCenters, int *
* https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
*/
static void
ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo)
ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo, Size memoryUsed)
{
FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
@@ -279,8 +292,6 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
float *newcdist;
/* Calculate allocation sizes */
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->itemsize);
Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->itemsize);
Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, centers->itemsize);
Size aggSize = sizeof(float) * (int64) numCenters * dimensions;
Size centerCountsSize = sizeof(int) * numCenters;
@@ -292,18 +303,13 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
Size newcdistSize = sizeof(float) * numCenters;
/* Calculate total size */
Size totalSize = samplesSize + centersSize + newCentersSize + aggSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
Size totalSize = memoryUsed + newCentersSize + aggSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
/* Check memory requirements */
/* Add one to error message to ceil */
if (totalSize > (Size) maintenance_work_mem * 1024L)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("memory required is %zu MB, maintenance_work_mem is %d MB",
totalSize / (1024 * 1024) + 1, maintenance_work_mem / 1024)));
IvfflatCheckMemoryUsage(totalSize);
/* Ensure indexing does not overflow */
if (numCenters * numCenters > INT_MAX)
if (numCenters > INT_MAX / numCenters)
elog(ERROR, "Indexing overflow detected. Please report a bug.");
/* Set support functions */
@@ -564,17 +570,17 @@ CheckCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeIn
* We use spherical k-means for inner product and cosine
*/
void
IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo)
IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo, Size memoryUsed)
{
MemoryContext kmeansCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat kmeans temporary context",
ALLOCSET_DEFAULT_SIZES);
MemoryContext oldCtx = MemoryContextSwitchTo(kmeansCtx);
if (samples->length == 0)
RandomCenters(index, centers, typeInfo);
if (samples->length <= centers->maxlen)
QuickCenters(index, samples, centers, typeInfo);
else
ElkanKmeans(index, samples, centers, typeInfo);
ElkanKmeans(index, samples, centers, typeInfo, memoryUsed);
CheckCenters(index, centers, typeInfo);

View File

@@ -2,15 +2,26 @@
#include <float.h>
#include "access/genam.h"
#include "access/itup.h"
#include "access/relscan.h"
#include "access/tupdesc.h"
#include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h"
#include "fmgr.h"
#include "lib/pairingheap.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "pgstat.h"
#include "storage/bufmgr.h"
#include "utils/memutils.h"
#include "utils/rel.h"
#include "utils/snapmgr.h"
#include "utils/tuplesort.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#define GetScanList(ptr) pairingheap_container(IvfflatScanList, ph_node, ptr)
#define GetScanListConst(ptr) pairingheap_const_container(IvfflatScanList, ph_node, ptr)
@@ -287,6 +298,9 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
so->tupdesc = CreateTemplateTupleDesc(2);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
#if PG_VERSION_NUM >= 190000
TupleDescFinalize(so->tupdesc);
#endif
/* Prep sort */
so->sortstate = InitScanSortState(so->tupdesc);

View File

@@ -1,13 +1,21 @@
#include "postgres.h"
#include "access/genam.h"
#include "access/generic_xlog.h"
#include "bitvec.h"
#include "catalog/pg_type.h"
#include "fmgr.h"
#include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h"
#include "miscadmin.h"
#include "storage/bufmgr.h"
#include "utils/memutils.h"
#include "utils/relcache.h"
#include "utils/varbit.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/*
* Allocate a vector array
@@ -15,11 +23,15 @@
VectorArray
VectorArrayInit(int maxlen, int dimensions, Size itemsize)
{
VectorArray res = palloc(sizeof(VectorArrayData));
VectorArray res;
if (maxlen < 1 || dimensions < 1 || itemsize == 0)
elog(ERROR, "cannot create vector array");
/* Ensure items are aligned to prevent UB */
itemsize = MAXALIGN(itemsize);
res = palloc(sizeof(VectorArrayData));
res->length = 0;
res->maxlen = maxlen;
res->dim = dimensions;
@@ -82,6 +94,40 @@ IvfflatCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value)
return DatumGetFloat8(FunctionCall1Coll(procinfo, collation, value)) > 0;
}
/*
* Normalize vectors
*/
void
IvfflatNormVectors(const IvfflatTypeInfo * typeInfo, Oid collation, VectorArray arr, MemoryContext tmpCtx)
{
MemoryContext oldCtx = MemoryContextSwitchTo(tmpCtx);
for (int i = 0; i < arr->length; i++)
{
Datum value = PointerGetDatum(VectorArrayGet(arr, i));
Datum newValue = IvfflatNormValue(typeInfo, collation, value);
VectorArraySet(arr, i, DatumGetPointer(newValue));
MemoryContextReset(tmpCtx);
}
MemoryContextSwitchTo(oldCtx);
}
/*
* Check memory usage
*/
void
IvfflatCheckMemoryUsage(Size totalSize)
{
/* Add one to error message to ceil */
if (totalSize > maintenance_work_mem * (Size) 1024)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("memory required is %zu MB, maintenance_work_mem is %d MB",
totalSize / (1024 * 1024) + 1, maintenance_work_mem / 1024)));
}
/*
* New buffer
*/

View File

@@ -1,9 +1,12 @@
#include "postgres.h"
#include "access/genam.h"
#include "access/generic_xlog.h"
#include "access/itup.h"
#include "commands/vacuum.h"
#include "ivfflat.h"
#include "storage/bufmgr.h"
#include "utils/relcache.h"
#if PG_VERSION_NUM >= 180000
#define vacuum_delay_point() vacuum_delay_point(false)

View File

@@ -5,18 +5,27 @@
#include "catalog/pg_type.h"
#include "common/shortest_dec.h"
#include "common/string.h"
#include "fmgr.h"
#include "halfutils.h"
#include "halfvec.h"
#include "lib/stringinfo.h"
#include "libpq/pqformat.h"
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
#include "utils/fmgrprotos.h"
#include "utils/lsyscache.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 170000
#include "parser/scansup.h"
#endif
typedef struct SparseInputElement
{
int32 index;
@@ -150,9 +159,9 @@ InitSparseVector(int dim, int nnz)
return result;
}
/*
* Check for whitespace, since array_isspace() is static
*/
#if PG_VERSION_NUM >= 170000
#define sparsevec_isspace(ch) scanner_isspace(ch)
#else
static inline bool
sparsevec_isspace(char ch)
{
@@ -165,6 +174,7 @@ sparsevec_isspace(char ch)
return true;
return false;
}
#endif
/*
* Compare indices
@@ -172,10 +182,10 @@ sparsevec_isspace(char ch)
static int
CompareIndices(const void *a, const void *b)
{
if (((SparseInputElement *) a)->index < ((SparseInputElement *) b)->index)
if (((const SparseInputElement *) a)->index < ((const SparseInputElement *) b)->index)
return -1;
if (((SparseInputElement *) a)->index > ((SparseInputElement *) b)->index)
if (((const SparseInputElement *) a)->index > ((const SparseInputElement *) b)->index)
return 1;
return 0;

View File

@@ -16,16 +16,20 @@
#include "port.h" /* for strtof() */
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
#include "utils/fmgrprotos.h"
#include "utils/lsyscache.h"
#include "utils/numeric.h"
#include "utils/varbit.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 170000
#include "parser/scansup.h"
#endif
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
@@ -36,7 +40,7 @@
#endif
#if PG_VERSION_NUM >= 180000
PG_MODULE_MAGIC_EXT(.name = "vector",.version = "0.8.1");
PG_MODULE_MAGIC_EXT(.name = "vector", .version = "0.8.5");
#else
PG_MODULE_MAGIC;
#endif
@@ -129,9 +133,9 @@ InitVector(int dim)
return result;
}
/*
* Check for whitespace, since array_isspace() is static
*/
#if PG_VERSION_NUM >= 170000
#define vector_isspace(ch) scanner_isspace(ch)
#else
static inline bool
vector_isspace(char ch)
{
@@ -144,6 +148,7 @@ vector_isspace(char ch)
return true;
return false;
}
#endif
/*
* Check state array

View File

@@ -49,3 +49,11 @@ CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
ERROR: column cannot have more than 64000 dimensions for hnsw index
DROP TABLE t;
-- dimensions
CREATE TABLE t (val bit(64000));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
DROP TABLE t;
CREATE TABLE t (val bit(64001));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
ERROR: column cannot have more than 64000 dimensions for hnsw index
DROP TABLE t;

View File

@@ -100,3 +100,11 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::halfvec)) t
(1 row)
DROP TABLE t;
-- dimensions
CREATE TABLE t (val halfvec(4000));
CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
DROP TABLE t;
CREATE TABLE t (val halfvec(4001));
CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
ERROR: column cannot have more than 4000 dimensions for hnsw index
DROP TABLE t;

View File

@@ -161,6 +161,7 @@ ERROR: value 1001 out of bounds for option "ef_construction"
DETAIL: Valid values are between "4" and "1000".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
ERROR: ef_construction must be greater than or equal to 2 * m
DROP TABLE t;
SHOW hnsw.ef_search;
hnsw.ef_search
----------------
@@ -198,4 +199,11 @@ 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)
-- dimensions
CREATE TABLE t (val vector(2000));
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
DROP TABLE t;
CREATE TABLE t (val vector(2001));
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
ERROR: column cannot have more than 2000 dimensions for hnsw index
DROP TABLE t;

View File

@@ -35,3 +35,32 @@ NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
-- dimensions
CREATE TABLE t (val bit(64000));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
CREATE TABLE t (val bit(64001));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
ERROR: column cannot have more than 64000 dimensions for ivfflat index
DROP TABLE t;
-- memory
SET maintenance_work_mem = '1MB';
CREATE TABLE t (val bit(64000));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
RESET maintenance_work_mem;
SET maintenance_work_mem = '29MB';
CREATE TABLE t (val bit(64000));
INSERT INTO t (val) VALUES (B'0'::bit(64000));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
RESET maintenance_work_mem;

View File

@@ -82,3 +82,32 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t
(1 row)
DROP TABLE t;
-- dimensions
CREATE TABLE t (val halfvec(4000));
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
CREATE TABLE t (val halfvec(4001));
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
ERROR: column cannot have more than 4000 dimensions for ivfflat index
DROP TABLE t;
-- memory
SET maintenance_work_mem = '1MB';
CREATE TABLE t (val halfvec(4000));
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
RESET maintenance_work_mem;
SET maintenance_work_mem = '6MB';
CREATE TABLE t (val halfvec(4000));
INSERT INTO t (val) VALUES (array_fill(0, ARRAY[4000]));
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
RESET maintenance_work_mem;

View File

@@ -143,6 +143,7 @@ DETAIL: Valid values are between "1" and "32768".
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
ERROR: value 32769 out of bounds for option "lists"
DETAIL: Valid values are between "1" and "32768".
DROP TABLE t;
SHOW ivfflat.probes;
ivfflat.probes
----------------
@@ -172,4 +173,32 @@ 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)
-- dimensions
CREATE TABLE t (val vector(2000));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
CREATE TABLE t (val vector(2001));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
ERROR: column cannot have more than 2000 dimensions for ivfflat index
DROP TABLE t;
-- memory
SET maintenance_work_mem = '1MB';
CREATE TABLE t (val vector(2000));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
RESET maintenance_work_mem;
SET maintenance_work_mem = '5MB';
CREATE TABLE t (val vector(2000));
INSERT INTO t (val) VALUES (array_fill(0, ARRAY[2000]));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;
RESET maintenance_work_mem;

View File

@@ -33,3 +33,13 @@ CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
DROP TABLE t;
-- dimensions
CREATE TABLE t (val bit(64000));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
DROP TABLE t;
CREATE TABLE t (val bit(64001));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
DROP TABLE t;

View File

@@ -56,3 +56,13 @@ SELECT * FROM t ORDER BY val <+> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::halfvec)) t2;
DROP TABLE t;
-- dimensions
CREATE TABLE t (val halfvec(4000));
CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
DROP TABLE t;
CREATE TABLE t (val halfvec(4001));
CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
DROP TABLE t;

View File

@@ -95,23 +95,28 @@ CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
DROP TABLE t;
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;
-- dimensions
CREATE TABLE t (val vector(2000));
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
DROP TABLE t;
CREATE TABLE t (val vector(2001));
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
DROP TABLE t;

View File

@@ -21,3 +21,28 @@ CREATE INDEX ON t USING ivfflat ((val::bit(3)) bit_hamming_ops) WITH (lists = 1)
CREATE INDEX ON t USING ivfflat ((val::bit(64001)) bit_hamming_ops) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat ((val::bit(2)) bit_hamming_ops) WITH (lists = 5);
DROP TABLE t;
-- dimensions
CREATE TABLE t (val bit(64000));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
DROP TABLE t;
CREATE TABLE t (val bit(64001));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
DROP TABLE t;
-- memory
SET maintenance_work_mem = '1MB';
CREATE TABLE t (val bit(64000));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
DROP TABLE t;
RESET maintenance_work_mem;
SET maintenance_work_mem = '29MB';
CREATE TABLE t (val bit(64000));
INSERT INTO t (val) VALUES (B'0'::bit(64000));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
DROP TABLE t;
RESET maintenance_work_mem;

View File

@@ -43,3 +43,28 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t2;
DROP TABLE t;
-- dimensions
CREATE TABLE t (val halfvec(4000));
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
DROP TABLE t;
CREATE TABLE t (val halfvec(4001));
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
DROP TABLE t;
-- memory
SET maintenance_work_mem = '1MB';
CREATE TABLE t (val halfvec(4000));
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
DROP TABLE t;
RESET maintenance_work_mem;
SET maintenance_work_mem = '6MB';
CREATE TABLE t (val halfvec(4000));
INSERT INTO t (val) VALUES (array_fill(0, ARRAY[4000]));
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
DROP TABLE t;
RESET maintenance_work_mem;

View File

@@ -81,19 +81,40 @@ DROP TABLE t;
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 0);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
DROP TABLE t;
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;
-- dimensions
CREATE TABLE t (val vector(2000));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
DROP TABLE t;
CREATE TABLE t (val vector(2001));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
DROP TABLE t;
-- memory
SET maintenance_work_mem = '1MB';
CREATE TABLE t (val vector(2000));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
DROP TABLE t;
RESET maintenance_work_mem;
SET maintenance_work_mem = '5MB';
CREATE TABLE t (val vector(2000));
INSERT INTO t (val) VALUES (array_fill(0, ARRAY[2000]));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
DROP TABLE t;
RESET maintenance_work_mem;

View File

@@ -16,29 +16,19 @@ $node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 100000) i;"
);
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("vector_l2_ops", "vector_ip_ops", "vector_cosine_ops");
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);");
for my $i (0 .. $#operators)
# Test 100% recall
for (1 .. 20)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v $opclass);");
# Test 100% recall
for (1 .. 20)
{
my $id = int(rand() * 100000);
my $query = $node->safe_psql("postgres", "SELECT v FROM tst WHERE i = $id;");
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SELECT v FROM tst ORDER BY v <-> '$query' LIMIT 1;
));
is($res, $query);
}
my $id = int(rand() * 100000);
my $query = $node->safe_psql("postgres", "SELECT v FROM tst WHERE i = $id;");
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SELECT v FROM tst ORDER BY v <-> '$query' LIMIT 1;
));
is($res, $query);
}
done_testing();

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@@ -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();

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@@ -0,0 +1,29 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $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 (v vector(3));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT ARRAY[random(), random(), random()] FROM generate_series(1, 1000) i;"
);
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '3073kB';
ALTER TABLE tst SET (parallel_workers = 1);
CREATE INDEX ON tst USING hnsw (v vector_l2_ops);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem after 0 tuples/);
done_testing();

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@@ -0,0 +1,38 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 3;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
# Create table and index
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector($dim));");
$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
$node->safe_psql("postgres",
"INSERT INTO tst (v) SELECT ARRAY[$array_sql] FROM generate_series(1, 1000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops);");
$node->safe_psql("postgres", "DELETE FROM tst");
# Test HNSW_SCAN_LOCK at the beginning of MarkDeleted is effective
$node->pgbench(
"--no-vacuum --client=5 --transactions=1000",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent SELECTs and VACUUM",
{
"046_hnsw_vacuum_scan_select\@1000" => "SELECT i FROM tst ORDER BY v <-> '[0,0,0]' LIMIT 10;",
"046_hnsw_vacuum_scan_vacuum\@1" => "VACUUM tst;"
}
);
done_testing();

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@@ -0,0 +1,39 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 3;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
# Create table and index
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector($dim));");
$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
$node->safe_psql("postgres",
"INSERT INTO tst (v) SELECT ARRAY[$array_sql] FROM generate_series(1, 1000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops);");
# Test no "hnsw graph not repaired" errors
$node->pgbench(
"--no-vacuum --client=5 --transactions=1000",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs, DELETEs, SELECTs, and VACUUM",
{
"047_hnsw_vacuum_insert_insert\@500" => "INSERT INTO tst (v) VALUES (ARRAY[$array_sql]);",
"047_hnsw_vacuum_insert_delete\@500" => "DELETE FROM tst WHERE i = (SELECT i FROM tst LIMIT 1);",
"047_hnsw_vacuum_insert_select\@20" => "SELECT i FROM tst ORDER BY v <-> (SELECT ARRAY[$array_sql]::vector) LIMIT 10;",
"047_hnsw_vacuum_insert_vacuum\@1" => "VACUUM tst;"
}
);
done_testing();

View File

@@ -0,0 +1,39 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 3;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
# Create table and index
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector($dim));");
$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
$node->safe_psql("postgres",
"INSERT INTO tst (v) SELECT ARRAY[$array_sql] FROM generate_series(1, 1000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops) WITH (lists = 10);");
# Test no errors
$node->pgbench(
"--no-vacuum --client=5 --transactions=1500",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs, DELETEs, SELECTs, and VACUUM",
{
"048_ivfflat_vacuum_insert_insert\@500" => "INSERT INTO tst (v) VALUES (ARRAY[$array_sql]);",
"048_ivfflat_vacuum_insert_delete\@500" => "DELETE FROM tst WHERE i = (SELECT i FROM tst LIMIT 1);",
"048_ivfflat_vacuum_insert_select\@500" => "SELECT i FROM tst ORDER BY v <-> (SELECT ARRAY[$array_sql]::vector) LIMIT 10;",
"048_ivfflat_vacuum_insert_vacuum\@1" => "VACUUM tst;"
}
);
done_testing();

View File

@@ -1,4 +1,4 @@
comment = 'vector data type and ivfflat and hnsw access methods'
default_version = '0.8.1'
default_version = '0.8.5'
module_pathname = '$libdir/vector'
relocatable = true