Compare commits

..

20 Commits

Author SHA1 Message Date
Andrew Kane
c01e76f2fa Added strict ordering [skip ci] 2024-09-28 11:31:03 -07:00
Andrew Kane
ab57217f48 Added todo [skip ci] 2024-09-28 10:07:09 -07:00
Andrew Kane
5f6e031ccc Updated changelog [skip ci] 2024-09-28 09:57:05 -07:00
Andrew Kane
1a1221f905 Merge branch 'master' into hnsw-streaming 2024-09-26 08:34:07 -07:00
Andrew Kane
40c3e402c7 Removed todo [skip ci] 2024-09-25 17:29:20 -07:00
Andrew Kane
058248fdcc Improved cost code [skip ci] 2024-09-25 17:23:29 -07:00
Andrew Kane
73c5145b77 Use int for ef [skip ci] 2024-09-25 16:52:41 -07:00
Andrew Kane
ec4a23fe49 Added cost estimation [skip ci] 2024-09-25 16:45:04 -07:00
Andrew Kane
38207f5640 Merge branch 'master' into hnsw-streaming 2024-09-25 16:09:09 -07:00
Andrew Kane
4e35c6abe3 Updated readme [skip ci] 2024-09-24 23:24:48 -07:00
Andrew Kane
11e4d040d9 Fixed test [skip ci] 2024-09-24 19:38:06 -07:00
Andrew Kane
b2fa625255 Fixed crash with empty index [skip ci] 2024-09-23 09:42:31 -07:00
Andrew Kane
a8e699c927 Improved message [skip ci] 2024-09-22 22:31:48 -07:00
Andrew Kane
91541fece6 Fixed example [skip ci] 2024-09-22 22:28:39 -07:00
Andrew Kane
f3de487da2 Started readme updates [skip ci] 2024-09-22 22:26:27 -07:00
Andrew Kane
721d4b7e3f Improved test for ef_stream [skip ci] 2024-09-22 18:51:38 -07:00
Andrew Kane
28066d8fe4 Added test for ef_stream [skip ci] 2024-09-22 18:35:35 -07:00
Andrew Kane
495041e43b Added option to limit tuples [skip ci] 2024-09-22 18:10:19 -07:00
Andrew Kane
52c385c03a Only pass discarded when streaming [skip ci] 2024-09-22 17:47:10 -07:00
Andrew Kane
80cbd32dab Added streaming option for HNSW 2024-09-22 12:02:48 -07:00
52 changed files with 967 additions and 2094 deletions

8
.dockerignore Normal file
View File

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

View File

@@ -8,29 +8,27 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
include: include:
- postgres: 19 # - postgres: 18
os: ubuntu-24.04 # os: ubuntu-24.04
- postgres: 18
os: ubuntu-24.04
- postgres: 17 - postgres: 17
os: ubuntu-24.04 os: ubuntu-24.04
- postgres: 16 - postgres: 16
os: ubuntu-24.04-arm os: ubuntu-22.04
- postgres: 15 - postgres: 15
os: ubuntu-22.04 os: ubuntu-22.04
- postgres: 14 - postgres: 14
os: ubuntu-22.04-arm os: ubuntu-20.04
- postgres: 13 - postgres: 13
os: ubuntu-22.04 os: ubuntu-20.04
steps: steps:
- uses: actions/checkout@v6 - uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1 - uses: ankane/setup-postgres@v1
with: with:
postgres-version: ${{ matrix.postgres }} postgres-version: ${{ matrix.postgres }}
dev-files: true dev-files: true
- run: make - run: make
env: env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare ${{ matrix.postgres >= 18 && '-Wno-missing-field-initializers' || '' }} PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
- run: | - run: |
export PG_CONFIG=`which pg_config` export PG_CONFIG=`which pg_config`
sudo --preserve-env=PG_CONFIG make install sudo --preserve-env=PG_CONFIG make install
@@ -48,18 +46,18 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
include: include:
- postgres: 18 - postgres: 16
os: macos-26 os: macos-14
- postgres: 14 - postgres: 14
os: macos-15-intel os: macos-12
steps: steps:
- uses: actions/checkout@v6 - uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1 - uses: ankane/setup-postgres@v1
with: with:
postgres-version: ${{ matrix.postgres }} postgres-version: ${{ matrix.postgres }}
- run: make - run: make
env: env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-unknown-warning-option ${{ matrix.postgres >= 18 && '-Wno-missing-field-initializers' || '' }} PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter
- run: make install - run: make install
- run: make installcheck - run: make installcheck
- if: ${{ failure() }} - if: ${{ failure() }}
@@ -72,35 +70,26 @@ jobs:
tar xf $TAG.tar.gz tar xf $TAG.tar.gz
mv postgres-$TAG postgres mv postgres-$TAG postgres
env: env:
TAG: ${{ matrix.postgres == 18 && 'REL_18_2' || 'REL_14_21' }} TAG: ${{ matrix.postgres == 16 && 'REL_16_2' || 'REL_14_11' }}
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres/src/test/perl -I ./test/perl" - run: make prove_installcheck PROVE_FLAGS="-I ./postgres/src/test/perl -I ./test/perl"
env: env:
PERL5LIB: /Users/runner/perl5/lib/perl5 PERL5LIB: /Users/runner/perl5/lib/perl5
- run: make clean && $(brew --prefix llvm@$LLVM_VERSION)/bin/scan-build --status-bugs make - run: make clean && $(brew --prefix llvm@15)/bin/scan-build --status-bugs make
env: env:
LLVM_VERSION: ${{ matrix.os == 'macos-26' && 20 || 18 }}
PG_CFLAGS: -DUSE_ASSERT_CHECKING PG_CFLAGS: -DUSE_ASSERT_CHECKING
windows: windows:
runs-on: ${{ matrix.os }} runs-on: windows-latest
if: ${{ !startsWith(github.ref_name, 'mac') }} if: ${{ !startsWith(github.ref_name, 'mac') }}
strategy:
fail-fast: false
matrix:
include:
- postgres: 17
os: windows-2025
- postgres: 14
os: windows-2022
steps: steps:
- uses: actions/checkout@v6 - uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1 - uses: ankane/setup-postgres@v1
with: with:
postgres-version: ${{ matrix.postgres }} postgres-version: 14
- run: | - run: |
call "C:\Program Files\Microsoft Visual Studio\${{ matrix.os == 'windows-2025' && 18 || 2022 }}\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^ call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
nmake /NOLOGO /F Makefile.win && ^ nmake /NOLOGO /F Makefile.win && ^
nmake /NOLOGO /F Makefile.win install && ^ nmake /NOLOGO /F Makefile.win install && ^
nmake /NOLOGO /F Makefile.win installcheck ${{ matrix.postgres != 17 && 'PG_REGRESS=$(PGROOT)\bin\pg_regress' || '' }} && ^ nmake /NOLOGO /F Makefile.win installcheck && ^
nmake /NOLOGO /F Makefile.win clean && ^ nmake /NOLOGO /F Makefile.win clean && ^
nmake /NOLOGO /F Makefile.win uninstall nmake /NOLOGO /F Makefile.win uninstall
shell: cmd shell: cmd
@@ -133,10 +122,10 @@ jobs:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }} if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest runs-on: ubuntu-latest
steps: steps:
- uses: actions/checkout@v6 - uses: actions/checkout@v4
- uses: ankane/setup-postgres-valgrind@v1 - uses: ankane/setup-postgres-valgrind@v1
with: with:
postgres-version: 18 postgres-version: 16
check-ub: yes check-ub: yes
- run: make OPTFLAGS="" - run: make OPTFLAGS=""
- run: sudo --preserve-env=PG_CONFIG make install - run: sudo --preserve-env=PG_CONFIG make install

View File

@@ -1,26 +1,9 @@
## 0.8.3 (2026-06-17) ## 0.8.0 (unreleased)
- 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
## 0.8.1 (2025-09-04)
- Added support for Postgres 18 rc1
- Improved performance of `binary_quantize` function
## 0.8.0 (2024-10-30)
- Added support for iterative index scans - Added support for iterative index scans
- Added casts for arrays to `sparsevec` - Added casts for arrays to `sparsevec`
- Improved cost estimation for better index selection when filtering - Improved cost estimation
- Improved performance of HNSW index scans - Reduced memory usage for HNSW index scans
- Improved performance of HNSW inserts and on-disk index builds
- Dropped support for Postgres 12 - Dropped support for Postgres 12
## 0.7.4 (2024-08-05) ## 0.7.4 (2024-08-05)

View File

@@ -1,11 +1,8 @@
# syntax=docker/dockerfile:1 ARG PG_MAJOR=16
FROM postgres:$PG_MAJOR
ARG PG_MAJOR=17
ARG DEBIAN_CODENAME=bookworm
FROM postgres:$PG_MAJOR-$DEBIAN_CODENAME
ARG PG_MAJOR ARG PG_MAJOR
ADD https://github.com/pgvector/pgvector.git#v0.8.3 /tmp/pgvector COPY . /tmp/pgvector
RUN apt-get update && \ RUN apt-get update && \
apt-mark hold locales && \ apt-mark hold locales && \

View File

@@ -1,4 +1,4 @@
Portions Copyright (c) 1996-2026, PostgreSQL Global Development Group Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
Portions Copyright (c) 1994, The Regents of the University of California Portions Copyright (c) 1994, The Regents of the University of California

View File

@@ -2,7 +2,7 @@
"name": "vector", "name": "vector",
"abstract": "Open-source vector similarity search for Postgres", "abstract": "Open-source vector similarity search for Postgres",
"description": "Supports L2 distance, inner product, and cosine distance", "description": "Supports L2 distance, inner product, and cosine distance",
"version": "0.8.3", "version": "0.7.4",
"maintainer": [ "maintainer": [
"Andrew Kane <andrew@ankane.org>" "Andrew Kane <andrew@ankane.org>"
], ],
@@ -12,7 +12,7 @@
"prereqs": { "prereqs": {
"runtime": { "runtime": {
"requires": { "requires": {
"PostgreSQL": "13.0.0" "PostgreSQL": "12.0.0"
} }
} }
}, },
@@ -20,7 +20,7 @@
"vector": { "vector": {
"file": "sql/vector.sql", "file": "sql/vector.sql",
"docfile": "README.md", "docfile": "README.md",
"version": "0.8.3", "version": "0.7.4",
"abstract": "Open-source vector similarity search for Postgres" "abstract": "Open-source vector similarity search for Postgres"
} }
}, },

View File

@@ -1,5 +1,5 @@
EXTENSION = vector EXTENSION = vector
EXTVERSION = 0.8.3 EXTVERSION = 0.7.4
MODULE_big = vector MODULE_big = vector
DATA = $(wildcard sql/*--*--*.sql) DATA = $(wildcard sql/*--*--*.sql)
@@ -27,11 +27,6 @@ ifneq ($(filter ppc64%, $(shell uname -m)), )
OPTFLAGS = OPTFLAGS =
endif endif
# RISC-V64 doesn't support -march=native
ifeq ($(shell uname -m), riscv64)
OPTFLAGS =
endif
# For auto-vectorization: # For auto-vectorization:
# - GCC (needs -ftree-vectorize OR -O3) - https://gcc.gnu.org/projects/tree-ssa/vectorization.html # - 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 # - Clang (could use pragma instead) - https://llvm.org/docs/Vectorizers.html
@@ -71,7 +66,7 @@ dist:
git archive --format zip --prefix=$(EXTENSION)-$(EXTVERSION)/ --output dist/$(EXTENSION)-$(EXTVERSION).zip master git archive --format zip --prefix=$(EXTENSION)-$(EXTVERSION)/ --output dist/$(EXTENSION)-$(EXTVERSION).zip master
# for Docker # for Docker
PG_MAJOR ?= 17 PG_MAJOR ?= 16
.PHONY: docker .PHONY: docker
@@ -81,9 +76,4 @@ docker:
.PHONY: docker-release .PHONY: docker-release
docker-release: docker-release:
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) --build-arg DEBIAN_CODENAME=bookworm -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR)-bookworm -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR)-bookworm . docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .
.PHONY: docker-release-trixie
docker-release-trixie:
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) --build-arg DEBIAN_CODENAME=trixie -t pgvector/pgvector:pg$(PG_MAJOR)-trixie -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR)-trixie .

View File

@@ -1,5 +1,5 @@
EXTENSION = vector EXTENSION = vector
EXTVERSION = 0.8.3 EXTVERSION = 0.7.4
DATA_built = sql\$(EXTENSION)--$(EXTVERSION).sql DATA_built = sql\$(EXTENSION)--$(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 OBJS = src\bitutils.obj src\bitvec.obj src\halfutils.obj src\halfvec.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\sparsevec.obj src\vector.obj
@@ -31,9 +31,6 @@ LIBDIR = $(PGROOT)\lib
PKGLIBDIR = $(PGROOT)\lib PKGLIBDIR = $(PGROOT)\lib
SHAREDIR = $(PGROOT)\share SHAREDIR = $(PGROOT)\share
# Use $(PGROOT)\bin\pg_regress for Postgres < 17
PG_REGRESS = $(LIBDIR)\pgxs\src\test\regress\pg_regress
CFLAGS = /nologo /I"$(INCLUDEDIR_SERVER)\port\win32_msvc" /I"$(INCLUDEDIR_SERVER)\port\win32" /I"$(INCLUDEDIR_SERVER)" /I"$(INCLUDEDIR)" CFLAGS = /nologo /I"$(INCLUDEDIR_SERVER)\port\win32_msvc" /I"$(INCLUDEDIR_SERVER)\port\win32" /I"$(INCLUDEDIR_SERVER)" /I"$(INCLUDEDIR)"
CFLAGS = $(CFLAGS) $(PG_CFLAGS) CFLAGS = $(CFLAGS) $(PG_CFLAGS)
@@ -57,11 +54,11 @@ install: all
copy $(SHLIB) "$(PKGLIBDIR)" copy $(SHLIB) "$(PKGLIBDIR)"
copy $(EXTENSION).control "$(SHAREDIR)\extension" copy $(EXTENSION).control "$(SHAREDIR)\extension"
copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension" copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
if not exist "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)" mkdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)" mkdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
for %f in ($(HEADERS)) do copy %f "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)" for %f in ($(HEADERS)) do copy %f "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
installcheck: installcheck:
"$(PG_REGRESS)" --bindir="$(BINDIR)" $(REGRESS_OPTS) $(REGRESS) "$(BINDIR)\pg_regress" --bindir="$(BINDIR)" $(REGRESS_OPTS) $(REGRESS)
uninstall: uninstall:
del /f "$(PKGLIBDIR)\$(SHLIB)" del /f "$(PKGLIBDIR)\$(SHLIB)"

361
README.md
View File

@@ -11,19 +11,17 @@ 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 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) [![Build Status](https://github.com/pgvector/pgvector/actions/workflows/build.yml/badge.svg)](https://github.com/pgvector/pgvector/actions)
## Installation ## Installation
### Linux and Mac ### Linux and Mac
Compile and install the extension (supports Postgres 13+) Compile and install the extension (supports Postgres 12+)
```sh ```sh
cd /tmp cd /tmp
git clone --branch v0.8.3 https://github.com/pgvector/pgvector.git git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
cd pgvector cd pgvector
make make
make install # may need sudo make install # may need sudo
@@ -31,16 +29,24 @@ make install # may need sudo
See the [installation notes](#installation-notes---linux-and-mac) if you run into issues See the [installation notes](#installation-notes---linux-and-mac) if you run into issues
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [pkg](#pkg), [APK](#apk), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector). You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [pkg](#pkg), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
### Windows ### Windows
Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/build/building-on-the-command-line?view=msvc-170#download-and-install-the-tools) is installed and run `x64 Native Tools Command Prompt for VS [version]` as administrator. Then use `nmake` to build: Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/build/building-on-the-command-line?view=msvc-170#download-and-install-the-tools) is installed, and run:
```cmd ```cmd
set "PGROOT=C:\Program Files\PostgreSQL\18" call "C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvars64.bat"
```
Note: The exact path will vary depending on your Visual Studio version and edition
Then use `nmake` to build:
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16"
cd %TEMP% cd %TEMP%
git clone --branch v0.8.3 https://github.com/pgvector/pgvector.git git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
cd pgvector cd pgvector
nmake /F Makefile.win nmake /F Makefile.win
nmake /F Makefile.win install nmake /F Makefile.win install
@@ -76,7 +82,7 @@ Get the nearest neighbors by L2 distance
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5; SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
``` ```
Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`) Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`, added in 0.7.0)
Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators
@@ -94,8 +100,6 @@ Or add a vector column to an existing table
ALTER TABLE items ADD COLUMN embedding vector(3); ALTER TABLE items ADD COLUMN embedding vector(3);
``` ```
Also supports [half-precision](#half-precision-vectors), [binary](#binary-vectors), and [sparse](#sparse-vectors) vectors
Insert vectors Insert vectors
```sql ```sql
@@ -140,9 +144,7 @@ Supported distance functions are:
- `<->` - L2 distance - `<->` - L2 distance
- `<#>` - (negative) inner product - `<#>` - (negative) inner product
- `<=>` - cosine distance - `<=>` - cosine distance
- `<+>` - L1 distance - `<+>` - L1 distance (added in 0.7.0)
- `<~>` - Hamming distance (binary vectors)
- `<%>` - Jaccard distance (binary vectors)
Get the nearest neighbors to a row Get the nearest neighbors to a row
@@ -229,19 +231,19 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops); CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
``` ```
L1 distance L1 distance - added in 0.7.0
```sql ```sql
CREATE INDEX ON items USING hnsw (embedding vector_l1_ops); CREATE INDEX ON items USING hnsw (embedding vector_l1_ops);
``` ```
Hamming distance Hamming distance - added in 0.7.0
```sql ```sql
CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops); CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
``` ```
Jaccard distance Jaccard distance - added in 0.7.0
```sql ```sql
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops); CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
@@ -250,9 +252,9 @@ CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
Supported types are: Supported types are:
- `vector` - up to 2,000 dimensions - `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions - `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions - `bit` - up to 64,000 dimensions (added in 0.7.0)
- `sparsevec` - up to 1,000 non-zero elements - `sparsevec` - up to 1,000 non-zero elements (added in 0.7.0)
### Index Options ### Index Options
@@ -306,21 +308,17 @@ Note: Do not set `maintenance_work_mem` so high that it exhausts the memory on t
Like other index types, its faster to create an index after loading your initial data Like other index types, its faster to create an index after loading your initial data
You can also speed up index creation by increasing the number of parallel workers (2 by default) Starting with 0.6.0, you can also speed up index creation by increasing the number of parallel workers (2 by default)
```sql ```sql
SET max_parallel_maintenance_workers = 7; -- plus leader SET max_parallel_maintenance_workers = 7; -- plus leader
``` ```
For a large number of workers, you may need to increase `max_parallel_workers` (8 by default) For a large number of workers, you may also need to increase `max_parallel_workers` (8 by default)
The [index options](#index-options) also have a significant impact on build time (use the defaults unless seeing low recall)
Use [binary quantization](#binary-quantization) for faster build times at scale
### Indexing Progress ### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql ```sql
SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index; SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
@@ -363,7 +361,7 @@ Cosine distance
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100); CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
``` ```
Hamming distance Hamming distance - added in 0.7.0
```sql ```sql
CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100); CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100);
@@ -372,8 +370,8 @@ CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 10
Supported types are: Supported types are:
- `vector` - up to 2,000 dimensions - `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions - `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions - `bit` - up to 64,000 dimensions (added in 0.7.0)
### Query Options ### Query Options
@@ -406,7 +404,7 @@ For a large number of workers, you may also need to increase `max_parallel_worke
### Indexing Progress ### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql ```sql
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index; SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
@@ -423,110 +421,69 @@ Note: `%` is only populated during the `loading tuples` phase
## Filtering ## Filtering
There are a few ways to index nearest neighbor queries with a `WHERE` clause. There are a few ways to index nearest neighbor queries with a `WHERE` clause
```sql ```sql
SELECT * FROM items WHERE category_id = 123 ORDER BY embedding <-> '[3,1,2]' LIMIT 5; SELECT * FROM items WHERE category_id = 123 ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
``` ```
A good place to start is creating an index on the filter column. This can provide fast, exact nearest neighbor search in many cases. Postgres has a number of [index types](https://www.postgresql.org/docs/current/indexes-types.html) for this: B-tree (default), hash, GiST, SP-GiST, GIN, and BRIN. Create an index on one [or more](https://www.postgresql.org/docs/current/indexes-multicolumn.html) of the `WHERE` columns for exact search
```sql ```sql
CREATE INDEX ON items (category_id); CREATE INDEX ON items (category_id);
``` ```
For multiple columns, consider a [multicolumn index](https://www.postgresql.org/docs/current/indexes-multicolumn.html). Or a [partial index](https://www.postgresql.org/docs/current/indexes-partial.html) on the vector column for approximate search
```sql
CREATE INDEX ON items (location_id, category_id);
```
Exact indexes work well for conditions that match a low percentage of rows. Otherwise, [approximate indexes](#indexing) can work better.
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops);
```
With approximate indexes, filtering is applied *after* the index is scanned. If a condition matches 10% of rows, with HNSW and the default `hnsw.ef_search` of 40, only 4 rows will match on average. For more rows, enable [iterative index scans](#iterative-index-scans), which will automatically scan more of the index when needed.
```sql
SET hnsw.iterative_scan = strict_order;
```
If filtering by only a few distinct values, consider [partial indexing](https://www.postgresql.org/docs/current/indexes-partial.html).
```sql ```sql
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops) WHERE (category_id = 123); CREATE INDEX ON items USING hnsw (embedding vector_l2_ops) WHERE (category_id = 123);
``` ```
If filtering by many different values, consider [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html). Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html) for approximate search on many different values of the `WHERE` columns
```sql ```sql
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id); CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
``` ```
## Iterative Index Scans ## Streaming Queries [unreleased]
With approximate indexes, queries with filtering can return less results since filtering is applied *after* the index is scanned. Starting with 0.8.0, you can enable iterative index scans, which will automatically scan more of the index until enough results are found (or it reaches `hnsw.max_scan_tuples` or `ivfflat.max_probes`). *Added in 0.8.0*
Iterative scans can use strict or relaxed ordering. With approximate indexes, you can end up with less results than expected due to filtering conditions in the query.
Strict ensures results are in the exact order by distance Starting with 0.8.0, you can enable streaming queries. If too few results from the initial index scan match the query filters, it will resume scanning until enough results are found. This can significantly improve recall (at the cost of speed).
```sql ```tsql
SET hnsw.iterative_scan = strict_order; SET hnsw.streaming = on;
-- or
SET ivfflat.streaming = on;
``` ```
Relaxed allows results to be slightly out of order by distance, but provides better recall ### Streaming Options
```sql Since scanning a large portion of the index is expensive, there are options to control when the scan ends.
SET hnsw.iterative_scan = relaxed_order;
# or
SET ivfflat.iterative_scan = relaxed_order;
```
With relaxed ordering, you can use a [materialized CTE](https://www.postgresql.org/docs/current/queries-with.html#QUERIES-WITH-CTE-MATERIALIZATION) to get strict ordering
```sql
WITH relaxed_results AS MATERIALIZED (
SELECT id, embedding <-> '[1,2,3]' AS distance FROM items WHERE category_id = 123 ORDER BY distance LIMIT 5
) SELECT * FROM relaxed_results ORDER BY distance + 0;
```
Note: `+ 0` is needed for Postgres 17+
For queries that filter by distance, use a materialized CTE and place the distance filter outside of it for best performance (due to the [current behavior](https://www.postgresql.org/message-id/flat/CAOdR5yGUoMQ6j7M5hNUXrySzaqZVGf_Ne%2B8fwZMRKTFxU1nbJg%40mail.gmail.com) of the Postgres executor)
```sql
WITH nearest_results AS MATERIALIZED (
SELECT id, embedding <-> '[1,2,3]' AS distance FROM items ORDER BY distance LIMIT 5
) SELECT * FROM nearest_results WHERE distance < 5 ORDER BY distance;
```
Note: Place any other filters inside the CTE
### Iterative Scan Options
Since scanning a large portion of an approximate index is expensive, there are options to control when a scan ends.
#### HNSW #### HNSW
Specify the max number of tuples to visit (20,000 by default) Specify the max number of additional tuples visited
```sql ```sql
SET hnsw.max_scan_tuples = 20000; SET hnsw.ef_stream = 10000;
``` ```
Note: This is approximate and does not affect the initial scan The scan will also end if reaches `work_mem`, at which point a notice is shown
Specify the max amount of memory to use, as a multiple of `work_mem` (1 by default) ```text
NOTICE: hnsw index scan exceeded work_mem after 50000 tuples
HINT: Increase work_mem to scan more tuples.
```
Adjust this with:
```sql ```sql
SET hnsw.scan_mem_multiplier = 2; SET work_mem = '8MB';
``` ```
Note: Try increasing this if increasing `hnsw.max_scan_tuples` does not improve recall
#### IVFFlat #### IVFFlat
Specify the max number of probes Specify the max number of probes
@@ -535,10 +492,20 @@ Specify the max number of probes
SET ivfflat.max_probes = 100; SET ivfflat.max_probes = 100;
``` ```
Note: If this is lower than `ivfflat.probes`, `ivfflat.probes` will be used ### Streaming Order
With streaming queries, its possible for rows to be slightly out of order by distance. For strict ordering, use:
```sql
WITH approx_order AS MATERIALIZED (
SELECT *, embedding <-> '[1,2,3]' AS distance FROM items WHERE ... ORDER BY distance LIMIT 5
) SELECT * FROM approx_order ORDER BY distance;
```
## Half-Precision Vectors ## Half-Precision Vectors
*Added in 0.7.0*
Use the `halfvec` type to store half-precision vectors Use the `halfvec` type to store half-precision vectors
```sql ```sql
@@ -547,6 +514,8 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));
## Half-Precision Indexing ## Half-Precision Indexing
*Added in 0.7.0*
Index vectors at half precision for smaller indexes Index vectors at half precision for smaller indexes
```sql ```sql
@@ -568,16 +537,24 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES ('000'), ('111'); INSERT INTO items (embedding) VALUES ('000'), ('111');
``` ```
Get the nearest neighbors by Hamming distance Get the nearest neighbors by Hamming distance (added in 0.7.0)
```sql ```sql
SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5; SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
``` ```
Or (before 0.7.0)
```sql
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Also supports Jaccard distance (`<%>`) Also supports Jaccard distance (`<%>`)
## Binary Quantization ## Binary Quantization
*Added in 0.7.0*
Use expression indexing for binary quantization Use expression indexing for binary quantization
```sql ```sql
@@ -600,6 +577,8 @@ SELECT * FROM (
## Sparse Vectors ## Sparse Vectors
*Added in 0.7.0*
Use the `sparsevec` type to store sparse vectors Use the `sparsevec` type to store sparse vectors
```sql ```sql
@@ -633,6 +612,8 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python
## Indexing Subvectors ## Indexing Subvectors
*Added in 0.7.0*
Use expression indexing to index subvectors Use expression indexing to index subvectors
```sql ```sql
@@ -671,10 +652,6 @@ SHOW shared_buffers;
Be sure to restart Postgres for changes to take effect. Be sure to restart Postgres for changes to take effect.
### Storing
Use the `halfvec` type instead of `vector` for a smaller working set.
### Loading ### Loading
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py)). Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py)).
@@ -689,8 +666,6 @@ 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). 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. In production environments, create indexes concurrently to avoid blocking writes.
```sql ```sql
@@ -699,10 +674,10 @@ CREATE INDEX CONCURRENTLY ...
### Querying ### Querying
Use `EXPLAIN (ANALYZE, BUFFERS)` to debug performance. Use `EXPLAIN ANALYZE` to debug performance.
```sql ```sql
EXPLAIN (ANALYZE, BUFFERS) SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5; EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
``` ```
#### Exact Search #### Exact Search
@@ -721,8 +696,6 @@ SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5;
#### Approximate Search #### 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). To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
```sql ```sql
@@ -738,20 +711,23 @@ REINDEX INDEX CONCURRENTLY index_name;
VACUUM table_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 ## Monitoring
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 performance with [pg_stat_statements](https://www.postgresql.org/docs/current/pgstatstatements.html) (be sure to add it to `shared_preload_libraries`).
```sql
CREATE EXTENSION pg_stat_statements;
```
Get the most time-consuming queries with:
```sql
SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_time_ms,
ROUND((total_plan_time + total_exec_time) / 60000) AS total_time_min
FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20;
```
Note: Replace `total_plan_time + total_exec_time` with `total_time` for Postgres < 13
Monitor recall by comparing results from approximate search with exact search. Monitor recall by comparing results from approximate search with exact search.
@@ -762,46 +738,42 @@ SELECT ...
COMMIT; 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 ## 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. Use pgvector from any language with a Postgres client. You can even generate and store vectors in one language and query them in another.
Language | Libraries / Examples Language | Libraries / Examples
--- | --- --- | ---
Ada | [pgvector-ada](https://github.com/pgvector/pgvector-ada)
Algol | [pgvector-algol](https://github.com/pgvector/pgvector-algol)
C | [pgvector-c](https://github.com/pgvector/pgvector-c) C | [pgvector-c](https://github.com/pgvector/pgvector-c)
C++ | [pgvector-cpp](https://github.com/pgvector/pgvector-cpp) C++ | [pgvector-cpp](https://github.com/pgvector/pgvector-cpp)
C#, F#, Visual Basic | [pgvector-dotnet](https://github.com/pgvector/pgvector-dotnet) 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) 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) Dart | [pgvector-dart](https://github.com/pgvector/pgvector-dart)
Elixir | [pgvector-elixir](https://github.com/pgvector/pgvector-elixir) Elixir | [pgvector-elixir](https://github.com/pgvector/pgvector-elixir)
Erlang | [pgvector-erlang](https://github.com/pgvector/pgvector-erlang)
Fortran | [pgvector-fortran](https://github.com/pgvector/pgvector-fortran)
Gleam | [pgvector-gleam](https://github.com/pgvector/pgvector-gleam)
Go | [pgvector-go](https://github.com/pgvector/pgvector-go) Go | [pgvector-go](https://github.com/pgvector/pgvector-go)
Haskell | [pgvector-haskell](https://github.com/pgvector/pgvector-haskell) Haskell | [pgvector-haskell](https://github.com/pgvector/pgvector-haskell)
Java, Kotlin, Groovy, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java) Java, Kotlin, Groovy, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
JavaScript, TypeScript | [pgvector-node](https://github.com/pgvector/pgvector-node) JavaScript, TypeScript | [pgvector-node](https://github.com/pgvector/pgvector-node)
Julia | [Pgvector.jl](https://github.com/pgvector/Pgvector.jl) Julia | [pgvector-julia](https://github.com/pgvector/pgvector-julia)
Lisp | [pgvector-lisp](https://github.com/pgvector/pgvector-lisp) Lisp | [pgvector-lisp](https://github.com/pgvector/pgvector-lisp)
Lua | [pgvector-lua](https://github.com/pgvector/pgvector-lua) Lua | [pgvector-lua](https://github.com/pgvector/pgvector-lua)
Nim | [pgvector-nim](https://github.com/pgvector/pgvector-nim) Nim | [pgvector-nim](https://github.com/pgvector/pgvector-nim)
OCaml | [pgvector-ocaml](https://github.com/pgvector/pgvector-ocaml) OCaml | [pgvector-ocaml](https://github.com/pgvector/pgvector-ocaml)
Pascal | [pgvector-pascal](https://github.com/pgvector/pgvector-pascal)
Perl | [pgvector-perl](https://github.com/pgvector/pgvector-perl) Perl | [pgvector-perl](https://github.com/pgvector/pgvector-perl)
PHP | [pgvector-php](https://github.com/pgvector/pgvector-php) PHP | [pgvector-php](https://github.com/pgvector/pgvector-php)
Prolog | [pgvector-prolog](https://github.com/pgvector/pgvector-prolog)
Python | [pgvector-python](https://github.com/pgvector/pgvector-python) Python | [pgvector-python](https://github.com/pgvector/pgvector-python)
R | [pgvector-r](https://github.com/pgvector/pgvector-r) R | [pgvector-r](https://github.com/pgvector/pgvector-r)
Racket | [pgvector-racket](https://github.com/pgvector/pgvector-racket)
Raku | [pgvector-raku](https://github.com/pgvector/pgvector-raku)
Ruby | [pgvector-ruby](https://github.com/pgvector/pgvector-ruby), [Neighbor](https://github.com/ankane/neighbor) Ruby | [pgvector-ruby](https://github.com/pgvector/pgvector-ruby), [Neighbor](https://github.com/ankane/neighbor)
Rust | [pgvector-rust](https://github.com/pgvector/pgvector-rust) Rust | [pgvector-rust](https://github.com/pgvector/pgvector-rust)
Swift | [pgvector-swift](https://github.com/pgvector/pgvector-swift) 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) Zig | [pgvector-zig](https://github.com/pgvector/pgvector-zig)
## Frequently Asked Questions ## Frequently Asked Questions
@@ -816,11 +788,11 @@ Yes, pgvector uses the write-ahead log (WAL), which allows for replication and p
#### What if I want to index vectors with more than 2,000 dimensions? #### What if I want to index vectors with more than 2,000 dimensions?
You can use [half-precision vectors](#half-precision-vectors) or [half-precision indexing](#half-precision-indexing) to index up to 4,000 dimensions or [binary quantization](#binary-quantization) to index up to 64,000 dimensions. Other options are [indexing subvectors](#indexing-subvectors) (for models that support it) or [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction). You can use [half-precision indexing](#half-precision-indexing) to index up to 4,000 dimensions or [binary quantization](#binary-quantization) to index up to 64,000 dimensions. Another option is [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction).
#### Can I store vectors with different dimensions in the same column? #### Can I store vectors with different dimensions in the same column?
You can use `vector` as the type (instead of `vector(n)`). You can use `vector` as the type (instead of `vector(3)`).
```sql ```sql
CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id)); CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id));
@@ -875,8 +847,6 @@ No, but like other index types, youll likely see better performance if they d
SELECT pg_size_pretty(pg_relation_size('index_name')); 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 ## Troubleshooting
#### Why isnt a query using an index? #### Why isnt a query using an index?
@@ -922,7 +892,7 @@ ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
#### Why are there less results for a query after adding an HNSW index? #### Why are there less results for a query after adding an HNSW index?
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`), which is 40 by default. There may be even less results due to dead tuples or filtering conditions in the query. Enabling [iterative index scans](#iterative-index-scans) can help address this. Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead.
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance). Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
@@ -934,7 +904,7 @@ The index was likely created with too little data for the number of lists. Drop
DROP INDEX index_name; DROP INDEX index_name;
``` ```
Results can also be limited by the number of probes (`ivfflat.probes`). Enabling [iterative index scans](#iterative-index-scans) can address this. Results can also be limited by the number of probes (`ivfflat.probes`).
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance). Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
@@ -1070,7 +1040,7 @@ l2_normalize(sparsevec) → sparsevec | Normalize with Euclidean norm | 0.7.0
If your machine has multiple Postgres installations, specify the path to [pg_config](https://www.postgresql.org/docs/current/app-pgconfig.html) with: If your machine has multiple Postgres installations, specify the path to [pg_config](https://www.postgresql.org/docs/current/app-pgconfig.html) with:
```sh ```sh
export PG_CONFIG=/Library/PostgreSQL/18/bin/pg_config export PG_CONFIG=/Library/PostgreSQL/16/bin/pg_config
``` ```
Then re-run the installation instructions (run `make clean` before `make` if needed). If `sudo` is needed for `make install`, use: Then re-run the installation instructions (run `make clean` before `make` if needed). If `sudo` is needed for `make install`, use:
@@ -1081,11 +1051,11 @@ sudo --preserve-env=PG_CONFIG make install
A few common paths on Mac are: A few common paths on Mac are:
- EDB installer - `/Library/PostgreSQL/18/bin/pg_config` - EDB installer - `/Library/PostgreSQL/16/bin/pg_config`
- Homebrew (arm64) - `/opt/homebrew/opt/postgresql@18/bin/pg_config` - Homebrew (arm64) - `/opt/homebrew/opt/postgresql@16/bin/pg_config`
- Homebrew (x86-64) - `/usr/local/opt/postgresql@18/bin/pg_config` - Homebrew (x86-64) - `/usr/local/opt/postgresql@16/bin/pg_config`
Note: Replace `18` with your Postgres server version Note: Replace `16` with your Postgres server version
### Missing Header ### Missing Header
@@ -1094,20 +1064,14 @@ If compilation fails with `fatal error: postgres.h: No such file or directory`,
For Ubuntu and Debian, use: For Ubuntu and Debian, use:
```sh ```sh
sudo apt install postgresql-server-dev-18 sudo apt install postgresql-server-dev-16
``` ```
Note: Replace `18` with your Postgres server version Note: Replace `16` with your Postgres server version
### Missing SDK ### Missing SDK
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, your Postgres installation points to a path that no longer exists. If compilation fails and the output includes `warning: no such sysroot directory` on Mac, reinstall Xcode Command Line Tools.
```sh
pg_config --cppflags
```
Reinstall Postgres to fix this.
### Portability ### Portability
@@ -1125,14 +1089,6 @@ make OPTFLAGS=""
If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct. If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct.
### Mismatched Architecture
If compilation fails with `error C2196: case value '4' already used`, make sure youre using the `x64 Native Tools Command Prompt`. Then run `nmake /F Makefile.win clean` and re-run the installation instructions.
### Missing Symbol
If linking fails with `unresolved external symbol float_to_shortest_decimal_bufn` with Postgres 17.0-17.2, upgrade to Postgres 17.3+.
### Permissions ### Permissions
If installation fails with `Access is denied`, re-run the installation instructions as an administrator. If installation fails with `Access is denied`, re-run the installation instructions as an administrator.
@@ -1144,38 +1100,17 @@ If installation fails with `Access is denied`, re-run the installation instructi
Get the [Docker image](https://hub.docker.com/r/pgvector/pgvector) with: Get the [Docker image](https://hub.docker.com/r/pgvector/pgvector) with:
```sh ```sh
docker pull pgvector/pgvector:pg18-trixie docker pull pgvector/pgvector:pg16
``` ```
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `18` with your Postgres server version, and run it the same way). This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `16` with your Postgres server version, and run it the same way).
Supported tags are:
- `pg18-trixie`, `0.8.3-pg18-trixie`
- `pg18-bookworm`, `0.8.3-pg18-bookworm`, `pg18`, `0.8.3-pg18`
- `pg17-trixie`, `0.8.3-pg17-trixie`
- `pg17-bookworm`, `0.8.3-pg17-bookworm`, `pg17`, `0.8.3-pg17`
- `pg16-trixie`, `0.8.3-pg16-trixie`
- `pg16-bookworm`, `0.8.3-pg16-bookworm`, `pg16`, `0.8.3-pg16`
- `pg15-trixie`, `0.8.3-pg15-trixie`
- `pg15-bookworm`, `0.8.3-pg15-bookworm`, `pg15`, `0.8.3-pg15`
- `pg14-trixie`, `0.8.3-pg14-trixie`
- `pg14-bookworm`, `0.8.3-pg14-bookworm`, `pg14`, `0.8.3-pg14`
- `pg13-trixie`, `0.8.3-pg13-trixie`
- `pg13-bookworm`, `0.8.3-pg13-bookworm`, `pg13`, `0.8.3-pg13`
You can also build the image manually: You can also build the image manually:
```sh ```sh
git clone --branch v0.8.3 https://github.com/pgvector/pgvector.git git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
cd pgvector cd pgvector
docker build --pull --build-arg PG_MAJOR=18 -t myuser/pgvector . docker build --pull --build-arg PG_MAJOR=16 -t myuser/pgvector .
```
If you increase `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
```sh
docker run --shm-size=1g ...
``` ```
### Homebrew ### Homebrew
@@ -1186,7 +1121,7 @@ With Homebrew Postgres, you can use:
brew install pgvector brew install pgvector
``` ```
Note: This only adds it to the `postgresql@18` and `postgresql@17` formulas Note: This only adds it to the `postgresql@14` formula
### PGXN ### PGXN
@@ -1201,29 +1136,29 @@ pgxn install vector
Debian and Ubuntu packages are available from the [PostgreSQL APT Repository](https://wiki.postgresql.org/wiki/Apt). Follow the [setup instructions](https://wiki.postgresql.org/wiki/Apt#Quickstart) and run: Debian and Ubuntu packages are available from the [PostgreSQL APT Repository](https://wiki.postgresql.org/wiki/Apt). Follow the [setup instructions](https://wiki.postgresql.org/wiki/Apt#Quickstart) and run:
```sh ```sh
sudo apt install postgresql-18-pgvector sudo apt install postgresql-16-pgvector
``` ```
Note: Replace `18` with your Postgres server version Note: Replace `16` with your Postgres server version
### Yum ### Yum
RPM packages are available from the [PostgreSQL Yum Repository](https://yum.postgresql.org/). Follow the [setup instructions](https://www.postgresql.org/download/linux/redhat/) for your distribution and run: RPM packages are available from the [PostgreSQL Yum Repository](https://yum.postgresql.org/). Follow the [setup instructions](https://www.postgresql.org/download/linux/redhat/) for your distribution and run:
```sh ```sh
sudo yum install pgvector_18 sudo yum install pgvector_16
# or # or
sudo dnf install pgvector_18 sudo dnf install pgvector_16
``` ```
Note: Replace `18` with your Postgres server version Note: Replace `16` with your Postgres server version
### pkg ### pkg
Install the FreeBSD package with: Install the FreeBSD package with:
```sh ```sh
pkg install postgresql17-pgvector pkg install postgresql15-pgvector
``` ```
or the port with: or the port with:
@@ -1233,14 +1168,6 @@ cd /usr/ports/databases/pgvector
make install make install
``` ```
### APK
Install the Alpine package with:
```sh
apk add postgresql-pgvector
```
### conda-forge ### conda-forge
With Conda Postgres, install from [conda-forge](https://anaconda.org/conda-forge/pgvector) with: With Conda Postgres, install from [conda-forge](https://anaconda.org/conda-forge/pgvector) with:
@@ -1273,6 +1200,36 @@ You can check the version in the current database with:
SELECT extversion FROM pg_extension WHERE extname = 'vector'; SELECT extversion FROM pg_extension WHERE extname = 'vector';
``` ```
## Upgrade Notes
### 0.6.0
#### Postgres 12
If upgrading with Postgres 12, remove this line from `sql/vector--0.5.1--0.6.0.sql`:
```sql
ALTER TYPE vector SET (STORAGE = external);
```
Then run `make install` and `ALTER EXTENSION vector UPDATE;`.
#### Docker
The Docker image is now published in the `pgvector` org, and there are tags for each supported version of Postgres (rather than a `latest` tag).
```sh
docker pull pgvector/pgvector:pg16
# or
docker pull pgvector/pgvector:0.6.0-pg16
```
Also, if youve increased `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
```sh
docker run --shm-size=1g ...
```
## Thanks ## Thanks
Thanks to: Thanks to:
@@ -1329,7 +1286,7 @@ make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
To enable benchmarking: To enable benchmarking:
```sh ```sh
make clean && PG_CFLAGS="-DHNSW_BENCH -DIVFFLAT_BENCH" make && make install make clean && PG_CFLAGS="-DIVFFLAT_BENCH" make && make install
``` ```
To show memory usage: To show memory usage:

View File

@@ -1,2 +0,0 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.8.1'" to load this file. \quit

View File

@@ -1,2 +0,0 @@
-- 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

@@ -1,2 +0,0 @@
-- 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

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

View File

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

View File

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

View File

@@ -13,20 +13,12 @@
#include "port.h" /* for strtof() */ #include "port.h" /* for strtof() */
#include "sparsevec.h" #include "sparsevec.h"
#include "utils/array.h" #include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h" #include "utils/float.h"
#include "utils/fmgrprotos.h"
#include "utils/lsyscache.h" #include "utils/lsyscache.h"
#include "utils/varbit.h" #include "utils/numeric.h"
#include "vector.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 STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1)) #define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
@@ -137,9 +129,9 @@ InitHalfVector(int dim)
return result; return result;
} }
#if PG_VERSION_NUM >= 170000 /*
#define halfvec_isspace(ch) scanner_isspace(ch) * Check for whitespace, since array_isspace() is static
#else */
static inline bool static inline bool
halfvec_isspace(char ch) halfvec_isspace(char ch)
{ {
@@ -152,7 +144,6 @@ halfvec_isspace(char ch)
return true; return true;
return false; return false;
} }
#endif
/* /*
* Check state array * Check state array
@@ -907,21 +898,8 @@ halfvec_binary_quantize(PG_FUNCTION_ARGS)
half *ax = a->x; half *ax = a->x;
VarBit *result = InitBitVector(a->dim); VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result); unsigned char *rx = VARBITS(result);
int i = 0;
int count = (a->dim / 8) * 8;
/* Auto-vectorized on aarch64 */ for (int i = 0; i < a->dim; i++)
for (; i < count; i += 8)
{
unsigned char result_byte = 0;
for (int j = 0; j < 8; j++)
result_byte |= (HalfToFloat4(ax[i + j]) > 0) << (7 - j);
rx[i / 8] = result_byte;
}
for (; i < a->dim; i++)
rx[i / 8] |= (HalfToFloat4(ax[i]) > 0) << (7 - (i % 8)); rx[i / 8] |= (HalfToFloat4(ax[i]) > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result); PG_RETURN_VARBIT_P(result);

View File

@@ -1,41 +1,26 @@
#include "postgres.h" #include "postgres.h"
#include <float.h> #include <float.h>
#include <limits.h>
#include <math.h> #include <math.h>
#include "access/amapi.h" #include "access/amapi.h"
#include "access/genam.h"
#include "access/reloptions.h" #include "access/reloptions.h"
#include "commands/progress.h" #include "commands/progress.h"
#include "commands/vacuum.h" #include "commands/vacuum.h"
#include "fmgr.h"
#include "hnsw.h" #include "hnsw.h"
#include "miscadmin.h" #include "miscadmin.h"
#include "nodes/pg_list.h"
#include "storage/lwlock.h"
#include "utils/float.h" #include "utils/float.h"
#include "utils/guc.h" #include "utils/guc.h"
#include "utils/relcache.h"
#include "utils/selfuncs.h" #include "utils/selfuncs.h"
#include "utils/spccache.h" #include "utils/spccache.h"
#include "vector.h"
#if PG_VERSION_NUM < 150000 #if PG_VERSION_NUM < 150000
#define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x) #define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
#endif #endif
static const struct config_enum_entry hnsw_iterative_scan_options[] = {
{"off", HNSW_ITERATIVE_SCAN_OFF, false},
{"relaxed_order", HNSW_ITERATIVE_SCAN_RELAXED, false},
{"strict_order", HNSW_ITERATIVE_SCAN_STRICT, false},
{NULL, 0, false}
};
int hnsw_ef_search; int hnsw_ef_search;
int hnsw_iterative_scan; int hnsw_ef_stream;
int hnsw_max_scan_tuples; bool hnsw_streaming;
double hnsw_scan_mem_multiplier;
int hnsw_lock_tranche_id; int hnsw_lock_tranche_id;
static relopt_kind hnsw_relopt_kind; static relopt_kind hnsw_relopt_kind;
@@ -59,20 +44,12 @@ HnswInitLockTranche(void)
sizeof(int) * 1, sizeof(int) * 1,
&found); &found);
if (!found) if (!found)
{
#if PG_VERSION_NUM >= 190000
tranche_ids[0] = LWLockNewTrancheId("HnswBuild");
#else
tranche_ids[0] = LWLockNewTrancheId(); tranche_ids[0] = LWLockNewTrancheId();
#endif
}
hnsw_lock_tranche_id = tranche_ids[0]; hnsw_lock_tranche_id = tranche_ids[0];
LWLockRelease(AddinShmemInitLock); LWLockRelease(AddinShmemInitLock);
#if PG_VERSION_NUM < 190000
/* Per-backend registration of the tranche ID */ /* Per-backend registration of the tranche ID */
LWLockRegisterTranche(hnsw_lock_tranche_id, "HnswBuild"); LWLockRegisterTranche(hnsw_lock_tranche_id, "HnswBuild");
#endif
} }
/* /*
@@ -94,19 +71,16 @@ HnswInit(void)
"Valid range is 1..1000.", &hnsw_ef_search, "Valid range is 1..1000.", &hnsw_ef_search,
HNSW_DEFAULT_EF_SEARCH, HNSW_MIN_EF_SEARCH, HNSW_MAX_EF_SEARCH, PGC_USERSET, 0, NULL, NULL, NULL); HNSW_DEFAULT_EF_SEARCH, HNSW_MIN_EF_SEARCH, HNSW_MAX_EF_SEARCH, PGC_USERSET, 0, NULL, NULL, NULL);
DefineCustomEnumVariable("hnsw.iterative_scan", "Sets the mode for iterative scans", /* TODO Figure out name */
NULL, &hnsw_iterative_scan, DefineCustomBoolVariable("hnsw.streaming", "Use streaming mode",
HNSW_ITERATIVE_SCAN_OFF, hnsw_iterative_scan_options, PGC_USERSET, 0, NULL, NULL, NULL); NULL, &hnsw_streaming,
HNSW_DEFAULT_STREAMING, PGC_USERSET, 0, NULL, NULL, NULL);
/* This is approximate and does not affect the initial scan */ /* TODO Figure out name */
DefineCustomIntVariable("hnsw.max_scan_tuples", "Sets the max number of tuples to visit for iterative scans", /* TODO Use same value as ivfflat.max_probes for "all" */
NULL, &hnsw_max_scan_tuples, DefineCustomIntVariable("hnsw.ef_stream", "Sets the max number of additional candidates to visit for streaming search",
20000, 1, INT_MAX, PGC_USERSET, 0, NULL, NULL, NULL); "-1 means all", &hnsw_ef_stream,
HNSW_DEFAULT_EF_STREAM, HNSW_MIN_EF_STREAM, HNSW_MAX_EF_STREAM, PGC_USERSET, 0, NULL, NULL, NULL);
/* Same range as hash_mem_multiplier */
DefineCustomRealVariable("hnsw.scan_mem_multiplier", "Sets the multiple of work_mem to use for iterative scans",
NULL, &hnsw_scan_mem_multiplier,
1, 1, 1000, PGC_USERSET, 0, NULL, NULL, NULL);
MarkGUCPrefixReserved("hnsw"); MarkGUCPrefixReserved("hnsw");
} }
@@ -128,6 +102,33 @@ hnswbuildphasename(int64 phasenum)
} }
} }
/*
* Estimate ef needed for iterative scans
*/
static int
EstimateEf(PlannerInfo *root, IndexPath *path)
{
double selectivity = 1;
ListCell *lc;
/* Cannot estimate without limit */
/* limit_tuples includes offset */
if (root->limit_tuples < 0)
return 0;
/* Get the selectivity of non-index conditions */
foreach(lc, path->indexinfo->indrestrictinfo)
{
RestrictInfo *rinfo = lfirst(lc);
/* Skip DEFAULT_INEQ_SEL since it may be a distance filter */
if (rinfo->norm_selec >= 0 && rinfo->norm_selec <= 1 && rinfo->norm_selec != (Selectivity) DEFAULT_INEQ_SEL)
selectivity *= rinfo->norm_selec;
}
return root->limit_tuples / Max(selectivity, 0.00001);
}
/* /*
* Estimate the cost of an index scan * Estimate the cost of an index scan
*/ */
@@ -139,34 +140,33 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
{ {
GenericCosts costs; GenericCosts costs;
int m; int m;
double ratio; int ef;
double startupPages; int entryLevel;
int layer0TuplesMax;
double layer0Selectivity;
double scalingFactor = 0.55;
double spc_seq_page_cost; double spc_seq_page_cost;
Relation index; Relation index;
/* Never use index without order */ /* Never use index without order */
if (path->indexorderbys == NIL) if (path->indexorderbys == NULL)
{ {
*indexStartupCost = get_float8_infinity(); *indexStartupCost = get_float8_infinity();
*indexTotalCost = get_float8_infinity(); *indexTotalCost = get_float8_infinity();
*indexSelectivity = 0; *indexSelectivity = 0;
*indexCorrelation = 0; *indexCorrelation = 0;
*indexPages = 0; *indexPages = 0;
#if PG_VERSION_NUM >= 180000
/* See "On disable_cost" thread on pgsql-hackers */
path->path.disabled_nodes = 2;
#endif
return; return;
} }
MemSet(&costs, 0, sizeof(costs)); MemSet(&costs, 0, sizeof(costs));
genericcostestimate(root, path, loop_count, &costs);
index = index_open(path->indexinfo->indexoid, NoLock); index = index_open(path->indexinfo->indexoid, NoLock);
HnswGetMetaPageInfo(index, &m, NULL); HnswGetMetaPageInfo(index, &m, NULL);
index_close(index, NoLock); index_close(index, NoLock);
ef = hnsw_streaming ? Max(hnsw_ef_search, EstimateEf(root, path)) : hnsw_ef_search;
/* /*
* HNSW cost estimation follows a formula that accounts for the total * HNSW cost estimation follows a formula that accounts for the total
* number of tuples indexed combined with the parameters that most * number of tuples indexed combined with the parameters that most
@@ -194,38 +194,30 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
* at L0, accounting for previously visited tuples, multiplied by the * at L0, accounting for previously visited tuples, multiplied by the
* "scalingFactor" (currently hardcoded). * "scalingFactor" (currently hardcoded).
*/ */
if (path->indexinfo->tuples > 0) entryLevel = (int) (log(path->indexinfo->tuples + 1) * HnswGetMl(m));
{ layer0TuplesMax = HnswGetLayerM(m, 0) * ef;
double scalingFactor = 0.55; layer0Selectivity = (scalingFactor * log(path->indexinfo->tuples + 1)) /
int entryLevel = (int) (log(path->indexinfo->tuples) * HnswGetMl(m)); (log(m) * (1 + log(ef)));
int layer0TuplesMax = HnswGetLayerM(m, 0) * hnsw_ef_search;
double layer0Selectivity = scalingFactor * log(path->indexinfo->tuples) / (log(m) * (1 + log(hnsw_ef_search)));
ratio = (entryLevel * m + layer0TuplesMax * layer0Selectivity) / path->indexinfo->tuples; costs.numIndexTuples = (entryLevel * m) +
(layer0TuplesMax * layer0Selectivity);
if (ratio > 1) genericcostestimate(root, path, loop_count, &costs);
ratio = 1;
}
else
ratio = 1;
get_tablespace_page_costs(path->indexinfo->reltablespace, NULL, &spc_seq_page_cost); get_tablespace_page_costs(path->indexinfo->reltablespace, NULL, &spc_seq_page_cost);
/* Startup cost is cost before returning the first row */
costs.indexStartupCost = costs.indexTotalCost * ratio;
/* Adjust cost if needed since TOAST not included in seq scan cost */ /* Adjust cost if needed since TOAST not included in seq scan cost */
startupPages = costs.numIndexPages * ratio; if (costs.numIndexPages > path->indexinfo->rel->pages)
if (startupPages > path->indexinfo->rel->pages && ratio < 0.5)
{ {
/* Change all page cost from random to sequential */ /* Change all page cost from random to sequential */
costs.indexStartupCost -= startupPages * (costs.spc_random_page_cost - spc_seq_page_cost); costs.indexTotalCost -= costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
/* Remove cost of extra pages */ /* Remove cost of extra pages */
costs.indexStartupCost -= (startupPages - path->indexinfo->rel->pages) * spc_seq_page_cost; costs.indexTotalCost -= (costs.numIndexPages - path->indexinfo->rel->pages) * spc_seq_page_cost;
} }
*indexStartupCost = costs.indexStartupCost; /* Use total cost since most work happens before first tuple is returned */
*indexStartupCost = costs.indexTotalCost;
*indexTotalCost = costs.indexTotalCost; *indexTotalCost = costs.indexTotalCost;
*indexSelectivity = costs.indexSelectivity; *indexSelectivity = costs.indexSelectivity;
*indexCorrelation = costs.indexCorrelation; *indexCorrelation = costs.indexCorrelation;
@@ -267,64 +259,6 @@ FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnswhandler);
Datum Datum
hnswhandler(PG_FUNCTION_ARGS) 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); IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0; amroutine->amstrategies = 0;
@@ -332,11 +266,6 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amoptsprocnum = 0; amroutine->amoptsprocnum = 0;
amroutine->amcanorder = false; amroutine->amcanorder = false;
amroutine->amcanorderbyop = true; amroutine->amcanorderbyop = true;
#if PG_VERSION_NUM >= 180000
amroutine->amcanhash = false;
amroutine->amconsistentequality = false;
amroutine->amconsistentordering = false;
#endif
amroutine->amcanbackward = false; /* can change direction mid-scan */ amroutine->amcanbackward = false; /* can change direction mid-scan */
amroutine->amcanunique = false; amroutine->amcanunique = false;
amroutine->amcanmulticol = false; amroutine->amcanmulticol = false;
@@ -369,9 +298,6 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amvacuumcleanup = hnswvacuumcleanup; amroutine->amvacuumcleanup = hnswvacuumcleanup;
amroutine->amcanreturn = NULL; amroutine->amcanreturn = NULL;
amroutine->amcostestimate = hnswcostestimate; amroutine->amcostestimate = hnswcostestimate;
#if PG_VERSION_NUM >= 180000
amroutine->amgettreeheight = NULL;
#endif
amroutine->amoptions = hnswoptions; amroutine->amoptions = hnswoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */ amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
amroutine->ambuildphasename = hnswbuildphasename; amroutine->ambuildphasename = hnswbuildphasename;
@@ -392,11 +318,5 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->aminitparallelscan = NULL; amroutine->aminitparallelscan = NULL;
amroutine->amparallelrescan = NULL; amroutine->amparallelrescan = NULL;
#if PG_VERSION_NUM >= 180000
amroutine->amtranslatestrategy = NULL;
amroutine->amtranslatecmptype = NULL;
#endif
PG_RETURN_POINTER(amroutine); PG_RETURN_POINTER(amroutine);
#endif
} }

View File

@@ -3,17 +3,11 @@
#include "postgres.h" #include "postgres.h"
#include <math.h>
#include "access/genam.h" #include "access/genam.h"
#include "access/parallel.h" #include "access/parallel.h"
#include "lib/pairingheap.h" #include "lib/pairingheap.h"
#include "nodes/execnodes.h" #include "nodes/execnodes.h"
#include "port.h" /* for random() */ #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/relptr.h"
#include "utils/sampling.h" #include "utils/sampling.h"
#include "vector.h" #include "vector.h"
@@ -22,10 +16,6 @@
#include "portability/instr_time.h" #include "portability/instr_time.h"
#endif #endif
#if PG_VERSION_NUM >= 190000
typedef Pointer Item;
#endif
#define HNSW_MAX_DIM 2000 #define HNSW_MAX_DIM 2000
#define HNSW_MAX_NNZ 1000 #define HNSW_MAX_NNZ 1000
@@ -56,6 +46,10 @@ typedef Pointer Item;
#define HNSW_DEFAULT_EF_SEARCH 40 #define HNSW_DEFAULT_EF_SEARCH 40
#define HNSW_MIN_EF_SEARCH 1 #define HNSW_MIN_EF_SEARCH 1
#define HNSW_MAX_EF_SEARCH 1000 #define HNSW_MAX_EF_SEARCH 1000
#define HNSW_DEFAULT_STREAMING false
#define HNSW_DEFAULT_EF_STREAM -1
#define HNSW_MIN_EF_STREAM -1
#define HNSW_MAX_EF_STREAM INT_MAX
/* Tuple types */ /* Tuple types */
#define HNSW_ELEMENT_TUPLE_TYPE 1 #define HNSW_ELEMENT_TUPLE_TYPE 1
@@ -117,9 +111,6 @@ typedef Pointer Item;
/* Ensure fits on page and in uint8 */ /* Ensure fits on page and in uint8 */
#define HnswGetMaxLevel(m) Min(((BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - offsetof(HnswNeighborTupleData, indextids) - sizeof(ItemIdData)) / (sizeof(ItemPointerData)) / (m)) - 2, 255) #define HnswGetMaxLevel(m) Min(((BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - offsetof(HnswNeighborTupleData, indextids) - sizeof(ItemIdData)) / (sizeof(ItemPointerData)) / (m)) - 2, 255)
#define HnswGetSearchCandidate(membername, ptr) pairingheap_container(HnswSearchCandidate, membername, ptr)
#define HnswGetSearchCandidateConst(membername, ptr) pairingheap_const_container(HnswSearchCandidate, membername, ptr)
#define HnswGetValue(base, element) PointerGetDatum(HnswPtrAccess(base, (element)->value)) #define HnswGetValue(base, element) PointerGetDatum(HnswPtrAccess(base, (element)->value))
#if PG_VERSION_NUM < 140005 #if PG_VERSION_NUM < 140005
@@ -138,24 +129,16 @@ typedef Pointer Item;
/* Variables */ /* Variables */
extern int hnsw_ef_search; extern int hnsw_ef_search;
extern int hnsw_iterative_scan; extern int hnsw_ef_stream;
extern int hnsw_max_scan_tuples; extern bool hnsw_streaming;
extern double hnsw_scan_mem_multiplier;
extern int hnsw_lock_tranche_id; extern int hnsw_lock_tranche_id;
typedef enum HnswIterativeScanMode
{
HNSW_ITERATIVE_SCAN_OFF,
HNSW_ITERATIVE_SCAN_RELAXED,
HNSW_ITERATIVE_SCAN_STRICT
} HnswIterativeScanMode;
typedef struct HnswElementData HnswElementData; typedef struct HnswElementData HnswElementData;
typedef struct HnswNeighborArray HnswNeighborArray; typedef struct HnswNeighborArray HnswNeighborArray;
#define HnswPtrDeclare(type, relptrtype, ptrtype) \ #define HnswPtrDeclare(type, relptrtype, ptrtype) \
relptr_declare(type, relptrtype); \ relptr_declare(type, relptrtype); \
typedef union { type *ptr; relptrtype relptr; } ptrtype typedef union { type *ptr; relptrtype relptr; } ptrtype;
/* Pointers that can be absolute or relative */ /* Pointers that can be absolute or relative */
/* Use char for DatumPtr so works with Pointer */ /* Use char for DatumPtr so works with Pointer */
@@ -203,9 +186,12 @@ typedef struct HnswSearchCandidate
pairingheap_node c_node; pairingheap_node c_node;
pairingheap_node w_node; pairingheap_node w_node;
HnswElementPtr element; HnswElementPtr element;
double distance; float distance;
} HnswSearchCandidate; } HnswSearchCandidate;
#define HnswGetSearchCandidate(membername, ptr) pairingheap_container(HnswSearchCandidate, membername, ptr)
#define HnswGetSearchCandidateConst(membername, ptr) pairingheap_const_container(HnswSearchCandidate, membername, ptr)
/* HNSW index options */ /* HNSW index options */
typedef struct HnswOptions typedef struct HnswOptions
{ {
@@ -228,8 +214,8 @@ typedef struct HnswGraph
/* Allocations state */ /* Allocations state */
LWLock allocatorLock; LWLock allocatorLock;
Size memoryUsed; long memoryUsed;
Size memoryTotal; long memoryTotal;
/* Flushed state */ /* Flushed state */
LWLock flushLock; LWLock flushLock;
@@ -280,18 +266,6 @@ typedef struct HnswTypeInfo
void (*checkValue) (Pointer v); void (*checkValue) (Pointer v);
} HnswTypeInfo; } HnswTypeInfo;
typedef struct HnswSupport
{
FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
Oid collation;
} HnswSupport;
typedef struct HnswQuery
{
Datum value;
} HnswQuery;
typedef struct HnswBuildState typedef struct HnswBuildState
{ {
/* Info */ /* Info */
@@ -311,7 +285,9 @@ typedef struct HnswBuildState
double reltuples; double reltuples;
/* Support functions */ /* Support functions */
HnswSupport support; FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
Oid collation;
/* Variables */ /* Variables */
HnswGraph graphData; HnswGraph graphData;
@@ -385,12 +361,6 @@ typedef union
struct tidhash_hash *tids; struct tidhash_hash *tids;
} visited_hash; } visited_hash;
typedef union
{
HnswElement element;
ItemPointerData indextid;
} HnswUnvisited;
typedef struct HnswScanOpaqueData typedef struct HnswScanOpaqueData
{ {
const HnswTypeInfo *typeInfo; const HnswTypeInfo *typeInfo;
@@ -398,15 +368,16 @@ typedef struct HnswScanOpaqueData
List *w; List *w;
visited_hash v; visited_hash v;
pairingheap *discarded; pairingheap *discarded;
HnswQuery q; Datum q;
int m; int m;
int64 tuples; int64 tuples;
double previousDistance; double previousDistance;
Size maxMemory;
MemoryContext tmpCtx; MemoryContext tmpCtx;
/* Support functions */ /* Support functions */
HnswSupport support; FmgrInfo *procinfo;
FmgrInfo *normprocinfo;
Oid collation;
} HnswScanOpaqueData; } HnswScanOpaqueData;
typedef HnswScanOpaqueData * HnswScanOpaque; typedef HnswScanOpaqueData * HnswScanOpaque;
@@ -424,14 +395,14 @@ typedef struct HnswVacuumState
int efConstruction; int efConstruction;
/* Support functions */ /* Support functions */
HnswSupport support; FmgrInfo *procinfo;
Oid collation;
/* Variables */ /* Variables */
struct tidhash_hash *deleted; struct tidhash_hash *deleted;
BufferAccessStrategy bas; BufferAccessStrategy bas;
HnswNeighborTuple ntup; HnswNeighborTuple ntup;
HnswElementData highestPoint; HnswElementData highestPoint;
HnswElementData fallbackPoint;
/* Memory */ /* Memory */
MemoryContext tmpCtx; MemoryContext tmpCtx;
@@ -441,33 +412,30 @@ typedef struct HnswVacuumState
int HnswGetM(Relation index); int HnswGetM(Relation index);
int HnswGetEfConstruction(Relation index); int HnswGetEfConstruction(Relation index);
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum); FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
void HnswInitSupport(HnswSupport * support, Relation index);
Datum HnswNormValue(const HnswTypeInfo * typeInfo, Oid collation, Datum value); Datum HnswNormValue(const HnswTypeInfo * typeInfo, Oid collation, Datum value);
bool HnswCheckNorm(HnswSupport * support, Datum value); bool HnswCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value);
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum); Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
void HnswInitPage(Buffer buf, Page page); void HnswInitPage(Buffer buf, Page page);
void HnswInit(void); 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, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples); List *HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples);
HnswElement HnswGetEntryPoint(Relation index); HnswElement HnswGetEntryPoint(Relation index);
void HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint); void HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint);
void *HnswAlloc(HnswAllocator * allocator, Size size); void *HnswAlloc(HnswAllocator * allocator, Size size);
HnswElement HnswInitElement(char *base, ItemPointer tid, int m, double ml, int maxLevel, HnswAllocator * alloc); HnswElement HnswInitElement(char *base, ItemPointer tid, int m, double ml, int maxLevel, HnswAllocator * alloc);
HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno); HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno);
void HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, HnswSupport * support, int m, int efConstruction, bool existing); void HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing);
HnswSearchCandidate *HnswEntryCandidate(char *base, HnswElement entryPoint, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec); HnswSearchCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum, bool building); void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum, bool building);
void HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m); void HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m);
void HnswAddHeapTid(HnswElement element, ItemPointer heaptid); void HnswAddHeapTid(HnswElement element, ItemPointer heaptid);
HnswNeighborArray *HnswInitNeighborArray(int lm, HnswAllocator * allocator);
void HnswInitNeighbors(char *base, HnswElement element, int m, HnswAllocator * alloc); void HnswInitNeighbors(char *base, HnswElement element, int m, HnswAllocator * alloc);
bool HnswInsertTupleOnDisk(Relation index, HnswSupport * support, Datum value, ItemPointer heaptid, bool building); bool HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building);
void HnswUpdateNeighborsOnDisk(Relation index, HnswSupport * support, HnswElement e, int m, bool checkExisting, bool building); void HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building);
void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec); void 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); void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance);
bool HnswFormIndexValue(Datum *out, Datum *values, bool *isnull, const HnswTypeInfo * typeInfo, HnswSupport * support);
void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element); 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); void HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
bool HnswLoadNeighborTids(HnswElement element, ItemPointerData *indextids, Relation index, int m, int lm, int lc); void HnswLoadNeighbors(HnswElement element, Relation index, int m);
void HnswInitLockTranche(void); void HnswInitLockTranche(void);
const HnswTypeInfo *HnswGetTypeInfo(Relation index); const HnswTypeInfo *HnswGetTypeInfo(Relation index);
PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc); PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);

View File

@@ -36,14 +36,11 @@
*/ */
#include "postgres.h" #include "postgres.h"
#include <limits.h> #include <math.h>
#include "access/genam.h"
#include "access/parallel.h" #include "access/parallel.h"
#include "access/relscan.h"
#include "access/table.h" #include "access/table.h"
#include "access/tableam.h" #include "access/tableam.h"
#include "access/tupdesc.h"
#include "access/xact.h" #include "access/xact.h"
#include "access/xloginsert.h" #include "access/xloginsert.h"
#include "catalog/index.h" #include "catalog/index.h"
@@ -51,19 +48,11 @@
#include "commands/progress.h" #include "commands/progress.h"
#include "hnsw.h" #include "hnsw.h"
#include "miscadmin.h" #include "miscadmin.h"
#include "nodes/execnodes.h"
#include "optimizer/optimizer.h" #include "optimizer/optimizer.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "storage/condition_variable.h"
#include "tcop/tcopprot.h" #include "tcop/tcopprot.h"
#include "utils/datum.h" #include "utils/datum.h"
#include "utils/memutils.h" #include "utils/memutils.h"
#include "utils/rel.h"
#include "utils/snapmgr.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 140000 #if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h" #include "utils/backend_progress.h"
@@ -80,8 +69,6 @@
#define PARALLEL_KEY_HNSW_AREA UINT64CONST(0xA000000000000002) #define PARALLEL_KEY_HNSW_AREA UINT64CONST(0xA000000000000002)
#define PARALLEL_KEY_QUERY_TEXT UINT64CONST(0xA000000000000003) #define PARALLEL_KEY_QUERY_TEXT UINT64CONST(0xA000000000000003)
#define HNSW_MAX_GRAPH_MEMORY (SIZE_MAX / 2)
/* /*
* Create the metapage * Create the metapage
*/ */
@@ -379,7 +366,7 @@ AddElementInMemory(char *base, HnswGraph * graph, HnswElement element)
* Update neighbors * Update neighbors
*/ */
static void static void
UpdateNeighborsInMemory(char *base, HnswSupport * support, HnswElement e, int m) UpdateNeighborsInMemory(char *base, FmgrInfo *procinfo, Oid collation, HnswElement e, int m)
{ {
for (int lc = e->level; lc >= 0; lc--) for (int lc = e->level; lc >= 0; lc--)
{ {
@@ -401,7 +388,7 @@ UpdateNeighborsInMemory(char *base, HnswSupport * support, HnswElement e, int m)
Assert(neighborElement); Assert(neighborElement);
LWLockAcquire(&neighborElement->lock, LW_EXCLUSIVE); LWLockAcquire(&neighborElement->lock, LW_EXCLUSIVE);
HnswUpdateConnection(base, HnswGetNeighbors(base, neighborElement, lc), e, hc->distance, lm, NULL, NULL, support); HnswUpdateConnection(base, e, hc, lm, lc, NULL, NULL, procinfo, collation);
LWLockRelease(&neighborElement->lock); LWLockRelease(&neighborElement->lock);
} }
} }
@@ -411,7 +398,7 @@ UpdateNeighborsInMemory(char *base, HnswSupport * support, HnswElement e, int m)
* Update graph in memory * Update graph in memory
*/ */
static void static void
UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, HnswElement entryPoint, HnswBuildState * buildstate) UpdateGraphInMemory(FmgrInfo *procinfo, Oid collation, HnswElement element, int m, int efConstruction, HnswElement entryPoint, HnswBuildState * buildstate)
{ {
HnswGraph *graph = buildstate->graph; HnswGraph *graph = buildstate->graph;
char *base = buildstate->hnswarea; char *base = buildstate->hnswarea;
@@ -424,7 +411,7 @@ UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, HnswEleme
AddElementInMemory(base, graph, element); AddElementInMemory(base, graph, element);
/* Update neighbors */ /* Update neighbors */
UpdateNeighborsInMemory(base, support, element, m); UpdateNeighborsInMemory(base, procinfo, collation, element, m);
/* Update entry point if needed (already have lock) */ /* Update entry point if needed (already have lock) */
if (entryPoint == NULL || element->level > entryPoint->level) if (entryPoint == NULL || element->level > entryPoint->level)
@@ -437,8 +424,9 @@ UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, HnswEleme
static void static void
InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element) InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
{ {
FmgrInfo *procinfo = buildstate->procinfo;
Oid collation = buildstate->collation;
HnswGraph *graph = buildstate->graph; HnswGraph *graph = buildstate->graph;
HnswSupport *support = &buildstate->support;
HnswElement entryPoint; HnswElement entryPoint;
LWLock *entryLock = &graph->entryLock; LWLock *entryLock = &graph->entryLock;
LWLock *entryWaitLock = &graph->entryWaitLock; LWLock *entryWaitLock = &graph->entryWaitLock;
@@ -470,10 +458,10 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
} }
/* Find neighbors for element */ /* Find neighbors for element */
HnswFindElementNeighbors(base, element, entryPoint, NULL, support, m, efConstruction, false); HnswFindElementNeighbors(base, element, entryPoint, NULL, procinfo, collation, m, efConstruction, false);
/* Update graph in memory */ /* Update graph in memory */
UpdateGraphInMemory(support, element, m, entryPoint, buildstate); UpdateGraphInMemory(procinfo, collation, element, m, efConstruction, entryPoint, buildstate);
/* Release entry lock */ /* Release entry lock */
LWLockRelease(entryLock); LWLockRelease(entryLock);
@@ -485,27 +473,34 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
static bool static bool
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, HnswBuildState * buildstate) InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, HnswBuildState * buildstate)
{ {
const HnswTypeInfo *typeInfo = buildstate->typeInfo;
HnswGraph *graph = buildstate->graph; HnswGraph *graph = buildstate->graph;
HnswElement element; HnswElement element;
HnswAllocator *allocator = &buildstate->allocator; HnswAllocator *allocator = &buildstate->allocator;
HnswSupport *support = &buildstate->support;
Size valueSize; Size valueSize;
Pointer valuePtr; Pointer valuePtr;
LWLock *flushLock = &graph->flushLock; LWLock *flushLock = &graph->flushLock;
char *base = buildstate->hnswarea; char *base = buildstate->hnswarea;
Datum value;
Size memoryMargin;
/* Form index value */ /* Detoast once for all calls */
if (!HnswFormIndexValue(&value, values, isnull, buildstate->typeInfo, support)) Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
return false;
/* Check value */
if (typeInfo->checkValue != NULL)
typeInfo->checkValue(DatumGetPointer(value));
/* Normalize if needed */
if (buildstate->normprocinfo != NULL)
{
if (!HnswCheckNorm(buildstate->normprocinfo, buildstate->collation, value))
return false;
value = HnswNormValue(typeInfo, buildstate->collation, value);
}
/* Get datum size */ /* Get datum size */
valueSize = VARSIZE_ANY(DatumGetPointer(value)); 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 */ /* Ensure graph not flushed when inserting */
LWLockAcquire(flushLock, LW_SHARED); LWLockAcquire(flushLock, LW_SHARED);
@@ -514,7 +509,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
{ {
LWLockRelease(flushLock); LWLockRelease(flushLock);
return HnswInsertTupleOnDisk(index, support, value, heaptid, true); return HnswInsertTupleOnDisk(index, value, values, isnull, heaptid, true);
} }
/* /*
@@ -527,7 +522,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
* Check that we have enough memory available for the new element now that * Check that we have enough memory available for the new element now that
* we have the allocator lock, and flush pages if needed. * we have the allocator lock, and flush pages if needed.
*/ */
if (graph->memoryUsed + memoryMargin >= graph->memoryTotal) if (graph->memoryUsed >= graph->memoryTotal)
{ {
LWLockRelease(&graph->allocatorLock); LWLockRelease(&graph->allocatorLock);
@@ -546,7 +541,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
LWLockRelease(flushLock); LWLockRelease(flushLock);
return HnswInsertTupleOnDisk(index, support, value, heaptid, true); return HnswInsertTupleOnDisk(index, value, values, isnull, heaptid, true);
} }
/* Ok, we can proceed to allocate the element */ /* Ok, we can proceed to allocate the element */
@@ -562,7 +557,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
/* Copy the datum */ /* Copy the datum */
memcpy(valuePtr, DatumGetPointer(value), valueSize); memcpy(valuePtr, DatumGetPointer(value), valueSize);
HnswPtrStore(base, element->value, (char *) valuePtr); HnswPtrStore(base, element->value, valuePtr);
/* Create a lock for the element */ /* Create a lock for the element */
LWLockInitialize(&element->lock, hnsw_lock_tranche_id); LWLockInitialize(&element->lock, hnsw_lock_tranche_id);
@@ -612,7 +607,7 @@ BuildCallback(Relation index, ItemPointer tid, Datum *values,
* Initialize the graph * Initialize the graph
*/ */
static void static void
InitGraph(HnswGraph * graph, char *base, Size memoryTotal) InitGraph(HnswGraph * graph, char *base, long memoryTotal)
{ {
/* Initialize the lock tranche if needed */ /* Initialize the lock tranche if needed */
HnswInitLockTranche(); HnswInitLockTranche();
@@ -620,7 +615,7 @@ InitGraph(HnswGraph * graph, char *base, Size memoryTotal)
HnswPtrStore(base, graph->head, (HnswElement) NULL); HnswPtrStore(base, graph->head, (HnswElement) NULL);
HnswPtrStore(base, graph->entryPoint, (HnswElement) NULL); HnswPtrStore(base, graph->entryPoint, (HnswElement) NULL);
graph->memoryUsed = 0; graph->memoryUsed = 0;
graph->memoryTotal = Min(memoryTotal, HNSW_MAX_GRAPH_MEMORY); graph->memoryTotal = memoryTotal;
graph->flushed = false; graph->flushed = false;
graph->indtuples = 0; graph->indtuples = 0;
SpinLockInit(&graph->lock); SpinLockInit(&graph->lock);
@@ -661,17 +656,9 @@ static void *
HnswSharedMemoryAlloc(Size size, void *state) HnswSharedMemoryAlloc(Size size, void *state)
{ {
HnswBuildState *buildstate = (HnswBuildState *) state; HnswBuildState *buildstate = (HnswBuildState *) state;
Size alignedSize = MAXALIGN(size); void *chunk = buildstate->hnswarea + buildstate->graph->memoryUsed;
void *chunk;
if (alignedSize > 1024 * 1024) buildstate->graph->memoryUsed += MAXALIGN(size);
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; return chunk;
} }
@@ -717,9 +704,11 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->indtuples = 0; buildstate->indtuples = 0;
/* Get support functions */ /* Get support functions */
HnswInitSupport(&buildstate->support, index); buildstate->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
buildstate->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
buildstate->collation = index->rd_indcollation[0];
InitGraph(&buildstate->graphData, NULL, (Size) maintenance_work_mem * 1024L); InitGraph(&buildstate->graphData, NULL, maintenance_work_mem * 1024L);
buildstate->graph = &buildstate->graphData; buildstate->graph = &buildstate->graphData;
buildstate->ml = HnswGetMl(buildstate->m); buildstate->ml = HnswGetMl(buildstate->m);
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m); buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
@@ -803,11 +792,7 @@ HnswParallelScanAndInsert(Relation heapRel, Relation indexRel, HnswShared * hnsw
buildstate.hnswarea = hnswarea; buildstate.hnswarea = hnswarea;
InitAllocator(&buildstate.allocator, &HnswSharedMemoryAlloc, &buildstate); InitAllocator(&buildstate.allocator, &HnswSharedMemoryAlloc, &buildstate);
scan = table_beginscan_parallel(heapRel, 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, reltuples = table_index_build_scan(heapRel, indexRel, indexInfo,
true, progress, BuildCallback, true, progress, BuildCallback,
(void *) &buildstate, scan); (void *) &buildstate, scan);
@@ -961,8 +946,6 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
if (esthnswarea > estother) if (esthnswarea > estother)
esthnswarea -= estother; esthnswarea -= estother;
esthnswarea = Min(esthnswarea, HNSW_MAX_GRAPH_MEMORY);
shm_toc_estimate_chunk(&pcxt->estimator, esthnswarea); shm_toc_estimate_chunk(&pcxt->estimator, esthnswarea);
shm_toc_estimate_keys(&pcxt->estimator, 2); shm_toc_estimate_keys(&pcxt->estimator, 2);
@@ -1005,7 +988,8 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
snapshot); snapshot);
hnswarea = (char *) shm_toc_allocate(pcxt->toc, esthnswarea); hnswarea = (char *) shm_toc_allocate(pcxt->toc, esthnswarea);
InitGraph(&hnswshared->graphData, hnswarea, esthnswarea); /* Report less than allocated so never fails */
InitGraph(&hnswshared->graphData, hnswarea, esthnswarea - 1024 * 1024);
/* /*
* Avoid base address for relptr for Postgres < 14.5 * Avoid base address for relptr for Postgres < 14.5
@@ -1084,7 +1068,7 @@ ComputeParallelWorkers(Relation heap, Relation index)
* Build graph * Build graph
*/ */
static void static void
BuildGraph(HnswBuildState * buildstate) BuildGraph(HnswBuildState * buildstate, ForkNumber forkNum)
{ {
int parallel_workers = 0; int parallel_workers = 0;
@@ -1132,7 +1116,7 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
InitBuildState(buildstate, heap, index, indexInfo, forkNum); InitBuildState(buildstate, heap, index, indexInfo, forkNum);
BuildGraph(buildstate); BuildGraph(buildstate, forkNum);
if (RelationNeedsWAL(index) || forkNum == INIT_FORKNUM) if (RelationNeedsWAL(index) || forkNum == INIT_FORKNUM)
log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true); log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true);

View File

@@ -1,19 +1,13 @@
#include "postgres.h" #include "postgres.h"
#include "access/genam.h" #include <math.h>
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "hnsw.h" #include "hnsw.h"
#include "nodes/execnodes.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "storage/lmgr.h" #include "storage/lmgr.h"
#include "storage/lwlock.h"
#include "utils/datum.h" #include "utils/datum.h"
#include "utils/memutils.h" #include "utils/memutils.h"
#include "utils/rel.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/* /*
* Get the insert page * Get the insert page
@@ -346,107 +340,6 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
*updatedInsertPage = newInsertPage; *updatedInsertPage = newInsertPage;
} }
/*
* Load neighbors
*/
static HnswNeighborArray *
HnswLoadNeighbors(HnswElement element, Relation index, int m, int lm, int lc)
{
char *base = NULL;
HnswNeighborArray *neighbors = HnswInitNeighborArray(lm, NULL);
ItemPointerData indextids[HNSW_MAX_M * 2];
if (!HnswLoadNeighborTids(element, indextids, index, m, lm, lc))
return neighbors;
for (int i = 0; i < lm; i++)
{
ItemPointer indextid = &indextids[i];
HnswElement e;
HnswCandidate *hc;
if (!ItemPointerIsValid(indextid))
break;
e = HnswInitElementFromBlock(ItemPointerGetBlockNumber(indextid), ItemPointerGetOffsetNumber(indextid));
hc = &neighbors->items[neighbors->length++];
HnswPtrStore(base, hc->element, e);
}
return neighbors;
}
/*
* Load elements for insert
*/
static void
LoadElementsForInsert(HnswNeighborArray * neighbors, HnswQuery * q, int *idx, Relation index, HnswSupport * support)
{
char *base = NULL;
for (int i = 0; i < neighbors->length; i++)
{
HnswCandidate *hc = &neighbors->items[i];
HnswElement element = HnswPtrAccess(base, hc->element);
double distance;
HnswLoadElement(element, &distance, q, index, support, true, NULL);
hc->distance = distance;
/* Prune element if being deleted */
if (element->heaptidsLength == 0)
{
*idx = i;
break;
}
}
}
/*
* Get update index
*/
static int
GetUpdateIndex(HnswElement element, HnswElement newElement, float distance, int m, int lm, int lc, Relation index, HnswSupport * support, MemoryContext updateCtx)
{
char *base = NULL;
int idx = -1;
HnswNeighborArray *neighbors;
MemoryContext oldCtx = MemoryContextSwitchTo(updateCtx);
/*
* Get latest neighbors since they may have changed. Do not lock yet since
* selecting neighbors can take time. Could use optimistic locking to
* retry if another update occurs before getting exclusive lock.
*/
neighbors = HnswLoadNeighbors(element, index, m, lm, lc);
/*
* Could improve performance for vacuuming by checking neighbors against
* list of elements being deleted to find index. It's important to exclude
* already deleted elements for this since they can be replaced at any
* time.
*/
if (neighbors->length < lm)
idx = -2;
else
{
HnswQuery q;
q.value = HnswGetValue(base, element);
LoadElementsForInsert(neighbors, &q, &idx, index, support);
if (idx == -1)
HnswUpdateConnection(base, neighbors, newElement, distance, lm, &idx, index, support);
}
MemoryContextSwitchTo(oldCtx);
MemoryContextReset(updateCtx);
return idx;
}
/* /*
* Check if connection already exists * Check if connection already exists
*/ */
@@ -467,94 +360,14 @@ ConnectionExists(HnswElement e, HnswNeighborTuple ntup, int startIdx, int lm)
return false; return false;
} }
/*
* Update neighbor
*/
static void
UpdateNeighborOnDisk(HnswElement element, HnswElement newElement, int idx, int m, int lm, int lc, Relation index, bool checkExisting, bool building)
{
Buffer buf;
Page page;
GenericXLogState *state;
HnswNeighborTuple ntup;
int startIdx;
OffsetNumber offno = element->neighborOffno;
/* Register page */
buf = ReadBuffer(index, element->neighborPage);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
if (building)
{
state = NULL;
page = BufferGetPage(buf);
}
else
{
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
}
/* Get tuple */
ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, offno));
/* Calculate index for update */
startIdx = (element->level - lc) * m;
/* Check for existing connection */
if (checkExisting && ConnectionExists(newElement, ntup, startIdx, lm))
idx = -1;
else if (idx == -2)
{
/* Find free offset if still exists */
/* TODO Retry updating connections if not */
for (int j = 0; j < lm; j++)
{
if (!ItemPointerIsValid(&ntup->indextids[startIdx + j]))
{
idx = startIdx + j;
break;
}
}
}
else
idx += startIdx;
/* Make robust to issues */
if (idx >= 0 && idx < ntup->count)
{
ItemPointer indextid = &ntup->indextids[idx];
/* Update neighbor on the buffer */
ItemPointerSet(indextid, newElement->blkno, newElement->offno);
/* Commit */
if (building)
MarkBufferDirty(buf);
else
GenericXLogFinish(state);
}
else if (!building)
GenericXLogAbort(state);
UnlockReleaseBuffer(buf);
}
/* /*
* Update neighbors * Update neighbors
*/ */
void void
HnswUpdateNeighborsOnDisk(Relation index, HnswSupport * support, HnswElement e, int m, bool checkExisting, bool building) HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building)
{ {
char *base = NULL; char *base = NULL;
/* Use separate memory context to improve performance for larger vectors */
MemoryContext updateCtx = GenerationContextCreate(CurrentMemoryContext,
"Hnsw insert update context",
#if PG_VERSION_NUM >= 150000
128 * 1024, 128 * 1024,
#endif
128 * 1024);
for (int lc = e->level; lc >= 0; lc--) for (int lc = e->level; lc >= 0; lc--)
{ {
int lm = HnswGetLayerM(m, lc); int lm = HnswGetLayerM(m, lc);
@@ -563,20 +376,96 @@ HnswUpdateNeighborsOnDisk(Relation index, HnswSupport * support, HnswElement e,
for (int i = 0; i < neighbors->length; i++) for (int i = 0; i < neighbors->length; i++)
{ {
HnswCandidate *hc = &neighbors->items[i]; HnswCandidate *hc = &neighbors->items[i];
Buffer buf;
Page page;
GenericXLogState *state;
HnswNeighborTuple ntup;
int idx = -1;
int startIdx;
HnswElement neighborElement = HnswPtrAccess(base, hc->element); HnswElement neighborElement = HnswPtrAccess(base, hc->element);
int idx; OffsetNumber offno = neighborElement->neighborOffno;
idx = GetUpdateIndex(neighborElement, e, hc->distance, m, lm, lc, index, support, updateCtx); /*
* Get latest neighbors since they may have changed. Do not lock
* yet since selecting neighbors can take time. Could use
* optimistic locking to retry if another update occurs before
* getting exclusive lock.
*/
HnswLoadNeighbors(neighborElement, index, m);
/*
* Could improve performance for vacuuming by checking neighbors
* against list of elements being deleted to find index. It's
* important to exclude already deleted elements for this since
* they can be replaced at any time.
*/
/* Select neighbors */
HnswUpdateConnection(NULL, e, hc, lm, lc, &idx, index, procinfo, collation);
/* New element was not selected as a neighbor */ /* New element was not selected as a neighbor */
if (idx == -1) if (idx == -1)
continue; continue;
UpdateNeighborOnDisk(neighborElement, e, idx, m, lm, lc, index, checkExisting, building); /* Register page */
buf = ReadBuffer(index, neighborElement->neighborPage);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
if (building)
{
state = NULL;
page = BufferGetPage(buf);
}
else
{
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
}
/* Get tuple */
ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, offno));
/* Calculate index for update */
startIdx = (neighborElement->level - lc) * m;
/* Check for existing connection */
if (checkExisting && ConnectionExists(e, ntup, startIdx, lm))
idx = -1;
else if (idx == -2)
{
/* Find free offset if still exists */
/* TODO Retry updating connections if not */
for (int j = 0; j < lm; j++)
{
if (!ItemPointerIsValid(&ntup->indextids[startIdx + j]))
{
idx = startIdx + j;
break;
}
}
}
else
idx += startIdx;
/* Make robust to issues */
if (idx >= 0 && idx < ntup->count)
{
ItemPointer indextid = &ntup->indextids[idx];
/* Update neighbor on the buffer */
ItemPointerSet(indextid, e->blkno, e->offno);
/* Commit */
if (building)
MarkBufferDirty(buf);
else
GenericXLogFinish(state);
}
else if (!building)
GenericXLogAbort(state);
UnlockReleaseBuffer(buf);
} }
} }
MemoryContextDelete(updateCtx);
} }
/* /*
@@ -666,7 +555,7 @@ FindDuplicateOnDisk(Relation index, HnswElement element, bool building)
* Update graph on disk * Update graph on disk
*/ */
static void static void
UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, int m, HnswElement entryPoint, bool building) UpdateGraphOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement element, int m, int efConstruction, HnswElement entryPoint, bool building)
{ {
BlockNumber newInsertPage = InvalidBlockNumber; BlockNumber newInsertPage = InvalidBlockNumber;
@@ -682,7 +571,7 @@ UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, in
HnswUpdateMetaPage(index, 0, NULL, newInsertPage, MAIN_FORKNUM, building); HnswUpdateMetaPage(index, 0, NULL, newInsertPage, MAIN_FORKNUM, building);
/* Update neighbors */ /* Update neighbors */
HnswUpdateNeighborsOnDisk(index, support, element, m, false, building); HnswUpdateNeighborsOnDisk(index, procinfo, collation, element, m, false, building);
/* Update entry point if needed */ /* Update entry point if needed */
if (entryPoint == NULL || element->level > entryPoint->level) if (entryPoint == NULL || element->level > entryPoint->level)
@@ -693,12 +582,14 @@ UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, in
* Insert a tuple into the index * Insert a tuple into the index
*/ */
bool bool
HnswInsertTupleOnDisk(Relation index, HnswSupport * support, Datum value, ItemPointer heaptid, bool building) HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building)
{ {
HnswElement entryPoint; HnswElement entryPoint;
HnswElement element; HnswElement element;
int m; int m;
int efConstruction = HnswGetEfConstruction(index); int efConstruction = HnswGetEfConstruction(index);
FmgrInfo *procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
Oid collation = index->rd_indcollation[0];
LOCKMODE lockmode = ShareLock; LOCKMODE lockmode = ShareLock;
char *base = NULL; char *base = NULL;
@@ -713,8 +604,8 @@ HnswInsertTupleOnDisk(Relation index, HnswSupport * support, Datum value, ItemPo
HnswGetMetaPageInfo(index, &m, &entryPoint); HnswGetMetaPageInfo(index, &m, &entryPoint);
/* Create an element */ /* Create an element */
element = HnswInitElement(base, heaptid, m, HnswGetMl(m), HnswGetMaxLevel(m), NULL); element = HnswInitElement(base, heap_tid, m, HnswGetMl(m), HnswGetMaxLevel(m), NULL);
HnswPtrStore(base, element->value, (char *) DatumGetPointer(value)); HnswPtrStore(base, element->value, DatumGetPointer(value));
/* Prevent concurrent inserts when likely updating entry point */ /* Prevent concurrent inserts when likely updating entry point */
if (entryPoint == NULL || element->level > entryPoint->level) if (entryPoint == NULL || element->level > entryPoint->level)
@@ -731,10 +622,10 @@ HnswInsertTupleOnDisk(Relation index, HnswSupport * support, Datum value, ItemPo
} }
/* Find neighbors for element */ /* Find neighbors for element */
HnswFindElementNeighbors(base, element, entryPoint, index, support, m, efConstruction, false); HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, false);
/* Update graph on disk */ /* Update graph on disk */
UpdateGraphOnDisk(index, support, element, m, entryPoint, building); UpdateGraphOnDisk(index, procinfo, collation, element, m, efConstruction, entryPoint, building);
/* Release lock */ /* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode); UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);
@@ -746,19 +637,31 @@ HnswInsertTupleOnDisk(Relation index, HnswSupport * support, Datum value, ItemPo
* Insert a tuple into the index * Insert a tuple into the index
*/ */
static void static void
HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid) HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid)
{ {
Datum value; Datum value;
const HnswTypeInfo *typeInfo = HnswGetTypeInfo(index); const HnswTypeInfo *typeInfo = HnswGetTypeInfo(index);
HnswSupport support; FmgrInfo *normprocinfo;
Oid collation = index->rd_indcollation[0];
HnswInitSupport(&support, index); /* Detoast once for all calls */
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Form index value */ /* Check value */
if (!HnswFormIndexValue(&value, values, isnull, typeInfo, &support)) if (typeInfo->checkValue != NULL)
return; typeInfo->checkValue(DatumGetPointer(value));
HnswInsertTupleOnDisk(index, &support, value, heaptid, false); /* Normalize if needed */
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
if (normprocinfo != NULL)
{
if (!HnswCheckNorm(normprocinfo, collation, value))
return;
value = HnswNormValue(typeInfo, collation, value);
}
HnswInsertTupleOnDisk(index, value, values, isnull, heap_tid, false);
} }
/* /*

View File

@@ -1,58 +1,48 @@
#include "postgres.h" #include "postgres.h"
#include <limits.h> #include <float.h>
#include "access/genam.h"
#include "access/relscan.h" #include "access/relscan.h"
#include "hnsw.h" #include "hnsw.h"
#include "lib/pairingheap.h"
#include "miscadmin.h"
#include "nodes/pg_list.h"
#include "pgstat.h" #include "pgstat.h"
#include "storage/bufmgr.h"
#include "storage/lmgr.h" #include "storage/lmgr.h"
#include "utils/float.h"
#include "utils/memutils.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 * Algorithm 5 from paper
*/ */
static List * static List *
GetScanItems(IndexScanDesc scan, Datum value) GetScanItems(IndexScanDesc scan, Datum q)
{ {
HnswScanOpaque so = (HnswScanOpaque) scan->opaque; HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
Relation index = scan->indexRelation; Relation index = scan->indexRelation;
HnswSupport *support = &so->support; FmgrInfo *procinfo = so->procinfo;
Oid collation = so->collation;
List *ep; List *ep;
List *w; List *w;
int m; int m;
HnswElement entryPoint; HnswElement entryPoint;
char *base = NULL; char *base = NULL;
HnswQuery *q = &so->q;
/* Get m and entry point */ /* Get m and entry point */
HnswGetMetaPageInfo(index, &m, &entryPoint); HnswGetMetaPageInfo(index, &m, &entryPoint);
q->value = value; so->q = q;
so->m = m; so->m = m;
if (entryPoint == NULL) if (entryPoint == NULL)
return NIL; return NIL;
ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, support, false)); ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, procinfo, collation, false));
for (int lc = entryPoint->level; lc >= 1; lc--) for (int lc = entryPoint->level; lc >= 1; lc--)
{ {
w = HnswSearchLayer(base, q, ep, 1, lc, index, support, m, false, NULL, NULL, NULL, true, NULL); w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, false, NULL, NULL, NULL, true, NULL);
ep = w; ep = w;
} }
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); return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL, &so->v, hnsw_streaming ? &so->discarded : NULL, true, &so->tuples);
} }
/* /*
@@ -63,6 +53,8 @@ ResumeScanItems(IndexScanDesc scan)
{ {
HnswScanOpaque so = (HnswScanOpaque) scan->opaque; HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
Relation index = scan->indexRelation; Relation index = scan->indexRelation;
FmgrInfo *procinfo = so->procinfo;
Oid collation = so->collation;
List *ep = NIL; List *ep = NIL;
char *base = NULL; char *base = NULL;
int batch_size = hnsw_ef_search; int batch_size = hnsw_ef_search;
@@ -73,17 +65,17 @@ ResumeScanItems(IndexScanDesc scan)
/* Get next batch of candidates */ /* Get next batch of candidates */
for (int i = 0; i < batch_size; i++) for (int i = 0; i < batch_size; i++)
{ {
HnswSearchCandidate *sc; HnswSearchCandidate *hc;
if (pairingheap_is_empty(so->discarded)) if (pairingheap_is_empty(so->discarded))
break; break;
sc = HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded)); hc = HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded));
ep = lappend(ep, sc); ep = lappend(ep, hc);
} }
return HnswSearchLayer(base, &so->q, ep, batch_size, 0, index, &so->support, so->m, false, NULL, &so->v, &so->discarded, false, &so->tuples); return HnswSearchLayer(base, so->q, ep, batch_size, 0, index, procinfo, collation, so->m, false, NULL, &so->v, &so->discarded, false, &so->tuples);
} }
/* /*
@@ -106,24 +98,13 @@ GetScanValue(IndexScanDesc scan)
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value))); Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Normalize if needed */ /* Normalize if needed */
if (so->support.normprocinfo != NULL) if (so->normprocinfo != NULL)
value = HnswNormValue(so->typeInfo, so->support.collation, value); value = HnswNormValue(so->typeInfo, so->collation, value);
} }
return value; return value;
} }
#if defined(HNSW_MEMORY)
/*
* Show memory usage
*/
static void
ShowMemoryUsage(HnswScanOpaque so)
{
elog(INFO, "memory: %zu KB, tuples: " INT64_FORMAT, MemoryContextMemAllocated(so->tmpCtx, false) / 1024, so->tuples);
}
#endif
/* /*
* Prepare for an index scan * Prepare for an index scan
*/ */
@@ -132,28 +113,22 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
{ {
IndexScanDesc scan; IndexScanDesc scan;
HnswScanOpaque so; HnswScanOpaque so;
double maxMemory;
scan = RelationGetIndexScan(index, nkeys, norderbys); scan = RelationGetIndexScan(index, nkeys, norderbys);
so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData)); so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData));
so->typeInfo = HnswGetTypeInfo(index); so->typeInfo = HnswGetTypeInfo(index);
so->first = true;
/* Set support functions */ so->v.tids = NULL;
HnswInitSupport(&so->support, index); so->discarded = NULL;
/*
* Use a lower max allocation size than default to allow scanning more
* tuples for iterative search before exceeding work_mem
*/
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext, so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw scan temporary context", "Hnsw scan temporary context",
0, 8 * 1024, 256 * 1024); ALLOCSET_DEFAULT_SIZES);
/* Calculate max memory */ /* Set support functions */
/* Add 256 extra bytes to fill last block when close */ so->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
maxMemory = (double) work_mem * hnsw_scan_mem_multiplier * 1024.0 + 256; so->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
so->maxMemory = Min(maxMemory, (double) (SIZE_MAX / 2)); so->collation = index->rd_indcollation[0];
scan->opaque = so; scan->opaque = so;
@@ -168,12 +143,15 @@ hnswrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int no
{ {
HnswScanOpaque so = (HnswScanOpaque) scan->opaque; HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
if (so->v.tids != NULL)
tidhash_reset(so->v.tids);
if (so->discarded != NULL)
pairingheap_reset(so->discarded);
so->first = true; so->first = true;
/* v and discarded are allocated in tmpCtx */
so->v.tids = NULL;
so->discarded = NULL;
so->tuples = 0; so->tuples = 0;
so->previousDistance = -get_float8_infinity(); so->previousDistance = -INFINITY;
MemoryContextReset(so->tmpCtx); MemoryContextReset(so->tmpCtx);
if (keys && scan->numberOfKeys > 0) if (keys && scan->numberOfKeys > 0)
@@ -204,10 +182,6 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
/* Count index scan for stats */ /* Count index scan for stats */
pgstat_count_index_scan(scan->indexRelation); pgstat_count_index_scan(scan->indexRelation);
#if PG_VERSION_NUM >= 180000
if (scan->instrument)
scan->instrument->nsearches++;
#endif
/* Safety check */ /* Safety check */
if (scan->orderByData == NULL) if (scan->orderByData == NULL)
@@ -227,7 +201,7 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
*/ */
LockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock); LockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
so->w = GetScanItems(scan, value); HnswBench("scan iteration", so->w = GetScanItems(scan, value));
/* Release shared lock */ /* Release shared lock */
UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock); UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
@@ -235,28 +209,28 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
so->first = false; so->first = false;
#if defined(HNSW_MEMORY) #if defined(HNSW_MEMORY)
ShowMemoryUsage(so); elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(so->tmpCtx, false) / 1024);
#endif #endif
} }
for (;;) for (;;)
{ {
char *base = NULL; char *base = NULL;
HnswSearchCandidate *sc; HnswSearchCandidate *hc;
HnswElement element; HnswElement element;
ItemPointer heaptid; ItemPointer heaptid;
if (list_length(so->w) == 0) if (list_length(so->w) == 0)
{ {
if (hnsw_iterative_scan == HNSW_ITERATIVE_SCAN_OFF) if (!hnsw_streaming)
break; break;
/* Empty index */ /* Empty index */
if (so->discarded == NULL) if (so->discarded == NULL)
break; break;
/* Reached max number of tuples or memory limit */ /* Reached max number of additional tuples */
if (so->tuples >= hnsw_max_scan_tuples || MemoryContextMemAllocated(so->tmpCtx, false) > so->maxMemory) if (hnsw_ef_stream != -1 && so->tuples >= hnsw_ef_search + hnsw_ef_stream)
{ {
if (pairingheap_is_empty(so->discarded)) if (pairingheap_is_empty(so->discarded))
break; break;
@@ -264,6 +238,21 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
/* Return remaining tuples */ /* Return remaining tuples */
so->w = lappend(so->w, HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded))); so->w = lappend(so->w, HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded)));
} }
/* Prevent scans from consuming too much memory */
else if (MemoryContextMemAllocated(so->tmpCtx, false) > (Size) work_mem * 1024L)
{
if (pairingheap_is_empty(so->discarded))
{
ereport(NOTICE,
(errmsg("hnsw index scan exceeded work_mem after " INT64_FORMAT " tuples", so->tuples),
errhint("Increase work_mem to scan more tuples.")));
break;
}
/* Return remaining tuples */
so->w = lappend(so->w, HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded)));
}
else else
{ {
/* /*
@@ -277,12 +266,12 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
*/ */
LockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock); LockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
so->w = ResumeScanItems(scan); HnswBench("scan iteration", so->w = ResumeScanItems(scan));
UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock); UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
#if defined(HNSW_MEMORY) #if defined(HNSW_MEMORY)
ShowMemoryUsage(so); elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(so->tmpCtx, false) / 1024);
#endif #endif
} }
@@ -290,8 +279,8 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
break; break;
} }
sc = llast(so->w); hc = llast(so->w);
element = HnswPtrAccess(base, sc->element); element = HnswPtrAccess(base, hc->element);
/* Move to next element if no valid heap TIDs */ /* Move to next element if no valid heap TIDs */
if (element->heaptidsLength == 0) if (element->heaptidsLength == 0)
@@ -299,10 +288,10 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
so->w = list_delete_last(so->w); so->w = list_delete_last(so->w);
/* Mark memory as free for next iteration */ /* Mark memory as free for next iteration */
if (hnsw_iterative_scan != HNSW_ITERATIVE_SCAN_OFF) if (hnsw_streaming)
{ {
pfree(element); pfree(element);
pfree(sc); pfree(hc);
} }
continue; continue;
@@ -310,13 +299,10 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
heaptid = &element->heaptids[--element->heaptidsLength]; heaptid = &element->heaptids[--element->heaptidsLength];
if (hnsw_iterative_scan == HNSW_ITERATIVE_SCAN_STRICT) if (hc->distance < so->previousDistance)
{ continue;
if (sc->distance < so->previousDistance)
continue;
so->previousDistance = sc->distance; so->previousDistance = hc->distance;
}
MemoryContextSwitchTo(oldCtx); MemoryContextSwitchTo(oldCtx);

View File

@@ -2,24 +2,18 @@
#include <math.h> #include <math.h>
#include "access/genam.h"
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "catalog/pg_type.h"
#include "catalog/pg_type_d.h"
#include "common/hashfn.h" #include "common/hashfn.h"
#include "fmgr.h" #include "fmgr.h"
#include "hnsw.h" #include "hnsw.h"
#include "lib/pairingheap.h" #include "lib/pairingheap.h"
#include "nodes/pg_list.h"
#include "port/atomics.h"
#include "sparsevec.h" #include "sparsevec.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "utils/datum.h" #include "utils/datum.h"
#include "utils/memdebug.h" #include "utils/memdebug.h"
#include "utils/rel.h" #include "utils/rel.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM < 170000 #if PG_VERSION_NUM < 170000
static inline uint64 static inline uint64
@@ -106,6 +100,12 @@ hash_offset(Size offset)
#define SH_DEFINE #define SH_DEFINE
#include "lib/simplehash.h" #include "lib/simplehash.h"
typedef union
{
HnswElement element;
ItemPointerData indextid;
} HnswUnvisited;
/* /*
* Get the max number of connections in an upper layer for each element in the index * Get the max number of connections in an upper layer for each element in the index
*/ */
@@ -146,17 +146,6 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
return index_getprocinfo(index, 1, procnum); return index_getprocinfo(index, 1, procnum);
} }
/*
* Init support functions
*/
void
HnswInitSupport(HnswSupport * support, Relation index)
{
support->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
support->collation = index->rd_indcollation[0];
support->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
}
/* /*
* Normalize value * Normalize value
*/ */
@@ -170,9 +159,9 @@ HnswNormValue(const HnswTypeInfo * typeInfo, Oid collation, Datum value)
* Check if non-zero norm * Check if non-zero norm
*/ */
bool bool
HnswCheckNorm(HnswSupport * support, Datum value) HnswCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value)
{ {
return DatumGetFloat8(FunctionCall1Coll(support->normprocinfo, support->collation, value)) > 0; return DatumGetFloat8(FunctionCall1Coll(procinfo, collation, value)) > 0;
} }
/* /*
@@ -201,7 +190,7 @@ HnswInitPage(Buffer buf, Page page)
/* /*
* Allocate a neighbor array * Allocate a neighbor array
*/ */
HnswNeighborArray * static HnswNeighborArray *
HnswInitNeighborArray(int lm, HnswAllocator * allocator) HnswInitNeighborArray(int lm, HnswAllocator * allocator)
{ {
HnswNeighborArray *a = HnswAlloc(allocator, HNSW_NEIGHBOR_ARRAY_SIZE(lm)); HnswNeighborArray *a = HnswAlloc(allocator, HNSW_NEIGHBOR_ARRAY_SIZE(lm));
@@ -262,7 +251,7 @@ HnswInitElement(char *base, ItemPointer heaptid, int m, double ml, int maxLevel,
HnswInitNeighbors(base, element, m, allocator); HnswInitNeighbors(base, element, m, allocator);
HnswPtrStore(base, element->value, (char *) NULL); HnswPtrStore(base, element->value, (Pointer) NULL);
return element; return element;
} }
@@ -288,7 +277,7 @@ HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno)
element->blkno = blkno; element->blkno = blkno;
element->offno = offno; element->offno = offno;
HnswPtrStore(base, element->neighbors, (HnswNeighborArrayPtr *) NULL); HnswPtrStore(base, element->neighbors, (HnswNeighborArrayPtr *) NULL);
HnswPtrStore(base, element->value, (char *) NULL); HnswPtrStore(base, element->value, (Pointer) NULL);
return element; return element;
} }
@@ -400,33 +389,6 @@ HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, Bloc
UnlockReleaseBuffer(buf); UnlockReleaseBuffer(buf);
} }
/*
* Form index value
*/
bool
HnswFormIndexValue(Datum *out, Datum *values, bool *isnull, const HnswTypeInfo * typeInfo, HnswSupport * support)
{
/* Detoast once for all calls */
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Check value */
if (typeInfo->checkValue != NULL)
typeInfo->checkValue(DatumGetPointer(value));
/* Normalize if needed */
if (support->normprocinfo != NULL)
{
if (!HnswCheckNorm(support, value))
return false;
value = HnswNormValue(typeInfo, support->collation, value);
}
*out = value;
return true;
}
/* /*
* Set element tuple, except for neighbor info * Set element tuple, except for neighbor info
*/ */
@@ -484,6 +446,69 @@ HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m)
ntup->version = e->version; ntup->version = e->version;
} }
/*
* Load neighbors from page
*/
static void
LoadNeighborsFromPage(HnswElement element, Relation index, Page page, int m)
{
char *base = NULL;
HnswNeighborTuple ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, element->neighborOffno));
int neighborCount = (element->level + 2) * m;
Assert(HnswIsNeighborTuple(ntup));
HnswInitNeighbors(base, element, m, NULL);
/* Ensure expected neighbors */
if (ntup->count != neighborCount)
return;
for (int i = 0; i < neighborCount; i++)
{
HnswElement e;
int level;
HnswCandidate *hc;
ItemPointer indextid;
HnswNeighborArray *neighbors;
indextid = &ntup->indextids[i];
if (!ItemPointerIsValid(indextid))
continue;
e = HnswInitElementFromBlock(ItemPointerGetBlockNumber(indextid), ItemPointerGetOffsetNumber(indextid));
/* Calculate level based on offset */
level = element->level - i / m;
if (level < 0)
level = 0;
neighbors = HnswGetNeighbors(base, element, level);
hc = &neighbors->items[neighbors->length++];
HnswPtrStore(base, hc->element, e);
}
}
/*
* Load neighbors
*/
void
HnswLoadNeighbors(HnswElement element, Relation index, int m)
{
Buffer buf;
Page page;
buf = ReadBuffer(index, element->neighborPage);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
LoadNeighborsFromPage(element, index, page, m);
UnlockReleaseBuffer(buf);
}
/* /*
* Load an element from a tuple * Load an element from a tuple
*/ */
@@ -514,24 +539,15 @@ HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHe
char *base = NULL; char *base = NULL;
Datum value = datumCopy(PointerGetDatum(&etup->data), false, -1); Datum value = datumCopy(PointerGetDatum(&etup->data), false, -1);
HnswPtrStore(base, element->value, (char *) DatumGetPointer(value)); HnswPtrStore(base, element->value, DatumGetPointer(value));
} }
} }
/*
* Calculate the distance between values
*/
static inline double
HnswGetDistance(Datum a, Datum b, HnswSupport * support)
{
return DatumGetFloat8(FunctionCall2Coll(support->procinfo, support->collation, a, b));
}
/* /*
* Load an element and optionally get its distance from q * Load an element and optionally get its distance from q
*/ */
static void static void
HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, double *distance, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, double *maxDistance, HnswElement * element) HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance, HnswElement * element)
{ {
Buffer buf; Buffer buf;
Page page; Page page;
@@ -546,16 +562,13 @@ HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, double *distance, Hns
Assert(HnswIsElementTuple(etup)); Assert(HnswIsElementTuple(etup));
if (unlikely(etup->deleted))
elog(ERROR, "cannot load deleted element");
/* Calculate distance */ /* Calculate distance */
if (distance != NULL) if (distance != NULL)
{ {
if (DatumGetPointer(q->value) == NULL) if (DatumGetPointer(*q) == NULL)
*distance = 0; *distance = 0;
else else
*distance = HnswGetDistance(q->value, PointerGetDatum(&etup->data), support); *distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
} }
/* Load element */ /* Load element */
@@ -574,50 +587,36 @@ HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, double *distance, Hns
* Load an element and optionally get its distance from q * Load an element and optionally get its distance from q
*/ */
void void
HnswLoadElement(HnswElement element, double *distance, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec, double *maxDistance) HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance)
{ {
HnswLoadElementImpl(element->blkno, element->offno, distance, q, index, support, loadVec, maxDistance, &element); HnswLoadElementImpl(element->blkno, element->offno, distance, q, index, procinfo, collation, loadVec, maxDistance, &element);
} }
/* /*
* Get the distance for an element * Get the distance for an element
*/ */
static double static float
GetElementDistance(char *base, HnswElement element, HnswQuery * q, HnswSupport * support) GetElementDistance(char *base, HnswElement element, Datum q, FmgrInfo *procinfo, Oid collation)
{ {
Datum value = HnswGetValue(base, element); Datum value = HnswGetValue(base, element);
return HnswGetDistance(q->value, value, support); return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, q, value));
}
/*
* Allocate a search candidate
*/
static HnswSearchCandidate *
HnswInitSearchCandidate(char *base, HnswElement element, double distance)
{
HnswSearchCandidate *sc = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, sc->element, element);
sc->distance = distance;
return sc;
} }
/* /*
* Create a candidate for the entry point * Create a candidate for the entry point
*/ */
HnswSearchCandidate * HnswSearchCandidate *
HnswEntryCandidate(char *base, HnswElement entryPoint, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec) HnswEntryCandidate(char *base, HnswElement entryPoint, Datum q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec)
{ {
bool inMemory = index == NULL; HnswSearchCandidate *hc = palloc(sizeof(HnswSearchCandidate));
double distance;
if (inMemory) HnswPtrStore(base, hc->element, entryPoint);
distance = GetElementDistance(base, entryPoint, q, support); if (index == NULL)
hc->distance = GetElementDistance(base, entryPoint, q, procinfo, collation);
else else
HnswLoadElement(entryPoint, &distance, q, index, support, loadVec, NULL); HnswLoadElement(entryPoint, &hc->distance, &q, index, procinfo, collation, loadVec, NULL);
return hc;
return HnswInitSearchCandidate(base, entryPoint, distance);
} }
/* /*
@@ -669,9 +668,9 @@ CompareFurthestCandidates(const pairingheap_node *a, const pairingheap_node *b,
* Init visited * Init visited
*/ */
static inline void static inline void
InitVisited(char *base, visited_hash * v, bool inMemory, int ef, int m) InitVisited(char *base, visited_hash * v, Relation index, int ef, int m)
{ {
if (!inMemory) if (index != NULL)
v->tids = tidhash_create(CurrentMemoryContext, ef * m * 2, NULL); v->tids = tidhash_create(CurrentMemoryContext, ef * m * 2, NULL);
else if (base != NULL) else if (base != NULL)
v->offsets = offsethash_create(CurrentMemoryContext, ef * m * 2, NULL); v->offsets = offsethash_create(CurrentMemoryContext, ef * m * 2, NULL);
@@ -683,9 +682,9 @@ InitVisited(char *base, visited_hash * v, bool inMemory, int ef, int m)
* Add to visited * Add to visited
*/ */
static inline void static inline void
AddToVisited(char *base, visited_hash * v, HnswElementPtr elementPtr, bool inMemory, bool *found) AddToVisited(char *base, visited_hash * v, HnswElementPtr elementPtr, Relation index, bool *found)
{ {
if (!inMemory) if (index != NULL)
{ {
HnswElement element = HnswPtrAccess(base, elementPtr); HnswElement element = HnswPtrAccess(base, elementPtr);
ItemPointerData indextid; ItemPointerData indextid;
@@ -746,7 +745,7 @@ HnswLoadUnvisitedFromMemory(char *base, HnswElement element, HnswUnvisited * unv
HnswCandidate *hc = &localNeighborhood->items[i]; HnswCandidate *hc = &localNeighborhood->items[i];
bool found; bool found;
AddToVisited(base, v, hc->element, true, &found); AddToVisited(base, v, hc->element, NULL, &found);
if (!found) if (!found)
unvisited[(*unvisitedLength)++].element = HnswPtrAccess(base, hc->element); unvisited[(*unvisitedLength)++].element = HnswPtrAccess(base, hc->element);
@@ -754,15 +753,18 @@ HnswLoadUnvisitedFromMemory(char *base, HnswElement element, HnswUnvisited * unv
} }
/* /*
* Load neighbor index TIDs * Load unvisited neighbors from disk
*/ */
bool static void
HnswLoadNeighborTids(HnswElement element, ItemPointerData *indextids, Relation index, int m, int lm, int lc) HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *unvisitedLength, visited_hash * v, Relation index, int m, int lm, int lc)
{ {
Buffer buf; Buffer buf;
Page page; Page page;
HnswNeighborTuple ntup; HnswNeighborTuple ntup;
int start; int start;
ItemPointerData indextids[HNSW_MAX_M * 2];
*unvisitedLength = 0;
buf = ReadBuffer(index, element->neighborPage); buf = ReadBuffer(index, element->neighborPage);
LockBuffer(buf, BUFFER_LOCK_SHARE); LockBuffer(buf, BUFFER_LOCK_SHARE);
@@ -777,29 +779,14 @@ HnswLoadNeighborTids(HnswElement element, ItemPointerData *indextids, Relation i
if (ntup->version != element->version || ntup->count != (element->level + 2) * m) if (ntup->version != element->version || ntup->count != (element->level + 2) * m)
{ {
UnlockReleaseBuffer(buf); UnlockReleaseBuffer(buf);
return false; return;
} }
/* Copy to minimize lock time */ /* Copy to minimize lock time */
start = (element->level - lc) * m; start = (element->level - lc) * m;
memcpy(indextids, ntup->indextids + start, lm * sizeof(ItemPointerData)); memcpy(&indextids, ntup->indextids + start, lm * sizeof(ItemPointerData));
UnlockReleaseBuffer(buf); UnlockReleaseBuffer(buf);
return true;
}
/*
* Load unvisited neighbors from disk
*/
static void
HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *unvisitedLength, visited_hash * v, Relation index, int m, int lm, int lc)
{
ItemPointerData indextids[HNSW_MAX_M * 2];
*unvisitedLength = 0;
if (!HnswLoadNeighborTids(element, indextids, index, m, lm, lc))
return;
for (int i = 0; i < lm; i++) for (int i = 0; i < lm; i++)
{ {
@@ -820,7 +807,7 @@ HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *u
* Algorithm 2 from paper * Algorithm 2 from paper
*/ */
List * 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) HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples)
{ {
List *w = NIL; List *w = NIL;
pairingheap *C = pairingheap_allocate(CompareNearestCandidates, NULL); pairingheap *C = pairingheap_allocate(CompareNearestCandidates, NULL);
@@ -833,7 +820,6 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
int lm = HnswGetLayerM(m, lc); int lm = HnswGetLayerM(m, lc);
HnswUnvisited *unvisited = palloc(lm * sizeof(HnswUnvisited)); HnswUnvisited *unvisited = palloc(lm * sizeof(HnswUnvisited));
int unvisitedLength; int unvisitedLength;
bool inMemory = index == NULL;
if (v == NULL) if (v == NULL)
{ {
@@ -843,14 +829,14 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
if (initVisited) if (initVisited)
{ {
InitVisited(base, v, inMemory, ef, m); InitVisited(base, v, index, ef, m);
if (discarded != NULL) if (discarded != NULL)
*discarded = pairingheap_allocate(CompareNearestDiscardedCandidates, NULL); *discarded = pairingheap_allocate(CompareNearestDiscardedCandidates, NULL);
} }
/* Create local memory for neighborhood if needed */ /* Create local memory for neighborhood if needed */
if (inMemory) if (index == NULL)
{ {
neighborhoodSize = HNSW_NEIGHBOR_ARRAY_SIZE(lm); neighborhoodSize = HNSW_NEIGHBOR_ARRAY_SIZE(lm);
localNeighborhood = palloc(neighborhoodSize); localNeighborhood = palloc(neighborhoodSize);
@@ -859,27 +845,26 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
/* Add entry points to v, C, and W */ /* Add entry points to v, C, and W */
foreach(lc2, ep) foreach(lc2, ep)
{ {
HnswSearchCandidate *sc = (HnswSearchCandidate *) lfirst(lc2); HnswSearchCandidate *hc = (HnswSearchCandidate *) lfirst(lc2);
bool found; bool found;
if (initVisited) if (initVisited)
{ {
AddToVisited(base, v, sc->element, inMemory, &found); AddToVisited(base, v, hc->element, index, &found);
/* OK to count elements instead of tuples */
if (tuples != NULL) if (tuples != NULL)
(*tuples)++; (*tuples)++;
} }
pairingheap_add(C, &sc->c_node); pairingheap_add(C, &hc->c_node);
pairingheap_add(W, &sc->w_node); pairingheap_add(W, &hc->w_node);
/* /*
* Do not count elements being deleted towards ef when vacuuming. It * Do not count elements being deleted towards ef when vacuuming. It
* would be ideal to do this for inserts as well, but this could * would be ideal to do this for inserts as well, but this could
* affect insert performance. * affect insert performance.
*/ */
if (CountElement(skipElement, HnswPtrAccess(base, sc->element))) if (CountElement(skipElement, HnswPtrAccess(base, hc->element)))
wlen++; wlen++;
} }
@@ -894,12 +879,11 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
cElement = HnswPtrAccess(base, c->element); cElement = HnswPtrAccess(base, c->element);
if (inMemory) if (index == NULL)
HnswLoadUnvisitedFromMemory(base, cElement, unvisited, &unvisitedLength, v, lc, localNeighborhood, neighborhoodSize); HnswLoadUnvisitedFromMemory(base, cElement, unvisited, &unvisitedLength, v, lc, localNeighborhood, neighborhoodSize);
else else
HnswLoadUnvisitedFromDisk(cElement, unvisited, &unvisitedLength, v, index, m, lm, lc); HnswLoadUnvisitedFromDisk(cElement, unvisited, &unvisitedLength, v, index, m, lm, lc);
/* OK to count elements instead of tuples */
if (tuples != NULL) if (tuples != NULL)
(*tuples) += unvisitedLength; (*tuples) += unvisitedLength;
@@ -907,15 +891,15 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
{ {
HnswElement eElement; HnswElement eElement;
HnswSearchCandidate *e; HnswSearchCandidate *e;
double eDistance; float eDistance;
bool alwaysAdd = wlen < ef; bool alwaysAdd = wlen < ef;
f = HnswGetSearchCandidate(w_node, pairingheap_first(W)); f = HnswGetSearchCandidate(w_node, pairingheap_first(W));
if (inMemory) if (index == NULL)
{ {
eElement = unvisited[i].element; eElement = unvisited[i].element;
eDistance = GetElementDistance(base, eElement, q, support); eDistance = GetElementDistance(base, eElement, q, procinfo, collation);
} }
else else
{ {
@@ -925,18 +909,17 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
/* Avoid any allocations if not adding */ /* Avoid any allocations if not adding */
eElement = NULL; eElement = NULL;
HnswLoadElementImpl(blkno, offno, &eDistance, q, index, support, inserting, alwaysAdd || discarded != NULL ? NULL : &f->distance, &eElement); HnswLoadElementImpl(blkno, offno, &eDistance, &q, index, procinfo, collation, inserting, alwaysAdd || discarded != NULL ? NULL : &f->distance, &eElement);
if (eElement == NULL)
continue;
} }
if (!(eDistance < f->distance || alwaysAdd)) if (eElement == NULL || !(eDistance < f->distance || alwaysAdd))
{ {
if (discarded != NULL) if (discarded != NULL)
{ {
/* Create a new candidate */ /* Create a new candidate */
e = HnswInitSearchCandidate(base, eElement, eDistance); e = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, e->element, eElement);
e->distance = eDistance;
pairingheap_add(*discarded, &e->w_node); pairingheap_add(*discarded, &e->w_node);
} }
@@ -948,7 +931,9 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
continue; continue;
/* Create a new candidate */ /* Create a new candidate */
e = HnswInitSearchCandidate(base, eElement, eDistance); e = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, e->element, eElement);
e->distance = eDistance;
pairingheap_add(C, &e->c_node); pairingheap_add(C, &e->c_node);
pairingheap_add(W, &e->w_node); pairingheap_add(W, &e->w_node);
@@ -976,9 +961,9 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
/* Add each element of W to w */ /* Add each element of W to w */
while (!pairingheap_is_empty(W)) while (!pairingheap_is_empty(W))
{ {
HnswSearchCandidate *sc = HnswGetSearchCandidate(w_node, pairingheap_remove_first(W)); HnswSearchCandidate *hc = HnswGetSearchCandidate(w_node, pairingheap_remove_first(W));
w = lappend(w, sc); w = lappend(w, hc);
} }
return w; return w;
@@ -1032,22 +1017,32 @@ CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b)
return 0; return 0;
} }
/*
* Calculate the distance between elements
*/
static float
HnswGetDistance(char *base, HnswElement a, HnswElement b, FmgrInfo *procinfo, Oid collation)
{
Datum aValue = HnswGetValue(base, a);
Datum bValue = HnswGetValue(base, b);
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, aValue, bValue));
}
/* /*
* Check if an element is closer to q than any element from R * Check if an element is closer to q than any element from R
*/ */
static bool static bool
CheckElementCloser(char *base, HnswCandidate * e, List *r, HnswSupport * support) CheckElementCloser(char *base, HnswCandidate * e, List *r, FmgrInfo *procinfo, Oid collation)
{ {
HnswElement eElement = HnswPtrAccess(base, e->element); HnswElement eElement = HnswPtrAccess(base, e->element);
Datum eValue = HnswGetValue(base, eElement);
ListCell *lc2; ListCell *lc2;
foreach(lc2, r) foreach(lc2, r)
{ {
HnswCandidate *ri = lfirst(lc2); HnswCandidate *ri = lfirst(lc2);
HnswElement riElement = HnswPtrAccess(base, ri->element); HnswElement riElement = HnswPtrAccess(base, ri->element);
Datum riValue = HnswGetValue(base, riElement); float distance = HnswGetDistance(base, eElement, riElement, procinfo, collation);
float distance = HnswGetDistance(eValue, riValue, support);
if (distance <= e->distance) if (distance <= e->distance)
return false; return false;
@@ -1060,14 +1055,15 @@ CheckElementCloser(char *base, HnswCandidate * e, List *r, HnswSupport * support
* Algorithm 4 from paper * Algorithm 4 from paper
*/ */
static List * static List *
SelectNeighbors(char *base, List *c, int lm, HnswSupport * support, bool *closerSet, HnswCandidate * newCandidate, HnswCandidate * *pruned, bool sortCandidates) SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid collation, HnswElement e2, HnswCandidate * newCandidate, HnswCandidate * *pruned, bool sortCandidates)
{ {
List *r = NIL; List *r = NIL;
List *w = list_copy(c); List *w = list_copy(c);
HnswCandidate **wd; HnswCandidate **wd;
int wdlen = 0; int wdlen = 0;
int wdoff = 0; int wdoff = 0;
bool mustCalculate = !(*closerSet); HnswNeighborArray *neighbors = HnswGetNeighbors(base, e2, lc);
bool mustCalculate = !neighbors->closerSet;
List *added = NIL; List *added = NIL;
bool removedAny = false; bool removedAny = false;
@@ -1094,7 +1090,7 @@ SelectNeighbors(char *base, List *c, int lm, HnswSupport * support, bool *closer
/* Use previous state of r and wd to skip work when possible */ /* Use previous state of r and wd to skip work when possible */
if (mustCalculate) if (mustCalculate)
e->closer = CheckElementCloser(base, e, r, support); e->closer = CheckElementCloser(base, e, r, procinfo, collation);
else if (list_length(added) > 0) else if (list_length(added) > 0)
{ {
/* Keep Valgrind happy for in-memory, parallel builds */ /* Keep Valgrind happy for in-memory, parallel builds */
@@ -1107,7 +1103,7 @@ SelectNeighbors(char *base, List *c, int lm, HnswSupport * support, bool *closer
*/ */
if (e->closer) if (e->closer)
{ {
e->closer = CheckElementCloser(base, e, added, support); e->closer = CheckElementCloser(base, e, added, procinfo, collation);
if (!e->closer) if (!e->closer)
removedAny = true; removedAny = true;
@@ -1120,7 +1116,7 @@ SelectNeighbors(char *base, List *c, int lm, HnswSupport * support, bool *closer
*/ */
if (removedAny) if (removedAny)
{ {
e->closer = CheckElementCloser(base, e, r, support); e->closer = CheckElementCloser(base, e, r, procinfo, collation);
if (e->closer) if (e->closer)
added = lappend(added, e); added = lappend(added, e);
} }
@@ -1128,7 +1124,7 @@ SelectNeighbors(char *base, List *c, int lm, HnswSupport * support, bool *closer
} }
else if (e == newCandidate) else if (e == newCandidate)
{ {
e->closer = CheckElementCloser(base, e, r, support); e->closer = CheckElementCloser(base, e, r, procinfo, collation);
if (e->closer) if (e->closer)
added = lappend(added, e); added = lappend(added, e);
} }
@@ -1144,7 +1140,7 @@ SelectNeighbors(char *base, List *c, int lm, HnswSupport * support, bool *closer
} }
/* Cached value can only be used in future if sorted deterministically */ /* Cached value can only be used in future if sorted deterministically */
*closerSet = sortCandidates; neighbors->closerSet = sortCandidates;
/* Keep pruned connections */ /* Keep pruned connections */
while (wdoff < wdlen && list_length(r) < lm) while (wdoff < wdlen && list_length(r) < lm)
@@ -1179,16 +1175,18 @@ AddConnections(char *base, HnswElement element, List *neighbors, int lc)
* Update connections * Update connections
*/ */
void void
HnswUpdateConnection(char *base, HnswNeighborArray * neighbors, HnswElement newElement, float distance, int lm, int *updateIdx, Relation index, HnswSupport * support) HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation)
{ {
HnswCandidate newHc; HnswElement hce = HnswPtrAccess(base, hc->element);
HnswNeighborArray *currentNeighbors = HnswGetNeighbors(base, hce, lc);
HnswCandidate hc2;
HnswPtrStore(base, newHc.element, newElement); HnswPtrStore(base, hc2.element, element);
newHc.distance = distance; hc2.distance = hc->distance;
if (neighbors->length < lm) if (currentNeighbors->length < lm)
{ {
neighbors->items[neighbors->length++] = newHc; currentNeighbors->items[currentNeighbors->length++] = hc2;
/* Track update */ /* Track update */
if (updateIdx != NULL) if (updateIdx != NULL)
@@ -1197,26 +1195,54 @@ HnswUpdateConnection(char *base, HnswNeighborArray * neighbors, HnswElement newE
else else
{ {
/* Shrink connections */ /* Shrink connections */
List *c = NIL;
HnswCandidate *pruned = NULL; HnswCandidate *pruned = NULL;
/* Add candidates */ /* Load elements on insert */
for (int i = 0; i < neighbors->length; i++) if (index != NULL)
c = lappend(c, &neighbors->items[i]); {
c = lappend(c, &newHc); Datum q = HnswGetValue(base, hce);
SelectNeighbors(base, c, lm, support, &neighbors->closerSet, &newHc, &pruned, true); for (int i = 0; i < currentNeighbors->length; i++)
{
HnswCandidate *hc3 = &currentNeighbors->items[i];
HnswElement hc3Element = HnswPtrAccess(base, hc3->element);
if (HnswPtrIsNull(base, hc3Element->value))
HnswLoadElement(hc3Element, &hc3->distance, &q, index, procinfo, collation, true, NULL);
else
hc3->distance = GetElementDistance(base, hc3Element, q, procinfo, collation);
/* Prune element if being deleted */
if (hc3Element->heaptidsLength == 0)
{
pruned = &currentNeighbors->items[i];
break;
}
}
}
/* Should not happen */
if (pruned == NULL) if (pruned == NULL)
return; {
List *c = NIL;
/* Add candidates */
for (int i = 0; i < currentNeighbors->length; i++)
c = lappend(c, &currentNeighbors->items[i]);
c = lappend(c, &hc2);
SelectNeighbors(base, c, lm, lc, procinfo, collation, hce, &hc2, &pruned, true);
/* Should not happen */
if (pruned == NULL)
return;
}
/* Find and replace the pruned element */ /* Find and replace the pruned element */
for (int i = 0; i < neighbors->length; i++) for (int i = 0; i < currentNeighbors->length; i++)
{ {
if (HnswPtrEqual(base, neighbors->items[i].element, pruned->element)) if (HnswPtrEqual(base, currentNeighbors->items[i].element, pruned->element))
{ {
neighbors->items[i] = newHc; currentNeighbors->items[i] = hc2;
/* Track update */ /* Track update */
if (updateIdx != NULL) if (updateIdx != NULL)
@@ -1276,20 +1302,17 @@ PrecomputeHash(char *base, HnswElement element)
* Algorithm 1 from paper * Algorithm 1 from paper
*/ */
void void
HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, HnswSupport * support, int m, int efConstruction, bool existing) HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing)
{ {
List *ep; List *ep;
List *w; List *w;
int level = element->level; int level = element->level;
int entryLevel; int entryLevel;
HnswQuery q; Datum q = HnswGetValue(base, element);
HnswElement skipElement = existing ? element : NULL; HnswElement skipElement = existing ? element : NULL;
bool inMemory = index == NULL;
q.value = HnswGetValue(base, element);
/* Precompute hash */ /* Precompute hash */
if (inMemory) if (index == NULL)
PrecomputeHash(base, element); PrecomputeHash(base, element);
/* No neighbors if no entry point */ /* No neighbors if no entry point */
@@ -1297,13 +1320,13 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
return; return;
/* Get entry point and level */ /* Get entry point and level */
ep = list_make1(HnswEntryCandidate(base, entryPoint, &q, index, support, true)); ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, procinfo, collation, true));
entryLevel = entryPoint->level; entryLevel = entryPoint->level;
/* 1st phase: greedy search to insert level */ /* 1st phase: greedy search to insert level */
for (int lc = entryLevel; lc >= level + 1; lc--) for (int lc = entryLevel; lc >= level + 1; lc--)
{ {
w = HnswSearchLayer(base, &q, ep, 1, lc, index, support, m, true, skipElement, NULL, NULL, true, NULL); w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, true, skipElement, NULL, NULL, true, NULL);
ep = w; ep = w;
} }
@@ -1322,7 +1345,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
List *lw = NIL; List *lw = NIL;
ListCell *lc2; ListCell *lc2;
w = HnswSearchLayer(base, &q, ep, efConstruction, lc, index, support, m, true, skipElement, NULL, NULL, true, NULL); w = HnswSearchLayer(base, q, ep, efConstruction, lc, index, procinfo, collation, m, true, skipElement, NULL, NULL, true, NULL);
/* Convert search candidates to candidates */ /* Convert search candidates to candidates */
foreach(lc2, w) foreach(lc2, w)
@@ -1338,7 +1361,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
/* Elements being deleted or skipped can help with search */ /* Elements being deleted or skipped can help with search */
/* but should be removed before selecting neighbors */ /* but should be removed before selecting neighbors */
if (!inMemory) if (index != NULL)
lw = RemoveElements(base, lw, skipElement); lw = RemoveElements(base, lw, skipElement);
/* /*
@@ -1346,7 +1369,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
* sortCandidates to true for in-memory builds to enable closer * sortCandidates to true for in-memory builds to enable closer
* caching, but there does not seem to be a difference in performance. * caching, but there does not seem to be a difference in performance.
*/ */
neighbors = SelectNeighbors(base, lw, lm, support, &HnswGetNeighbors(base, element, lc)->closerSet, NULL, NULL, false); neighbors = SelectNeighbors(base, lw, lm, lc, procinfo, collation, element, NULL, NULL, false);
AddConnections(base, element, neighbors, lc); AddConnections(base, element, neighbors, lc);
@@ -1402,7 +1425,7 @@ hnsw_halfvec_support(PG_FUNCTION_ARGS)
}; };
PG_RETURN_POINTER(&typeInfo); PG_RETURN_POINTER(&typeInfo);
} };
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_bit_support); FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_bit_support);
Datum Datum
@@ -1415,7 +1438,7 @@ hnsw_bit_support(PG_FUNCTION_ARGS)
}; };
PG_RETURN_POINTER(&typeInfo); PG_RETURN_POINTER(&typeInfo);
} };
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_sparsevec_support); FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_sparsevec_support);
Datum Datum
@@ -1428,4 +1451,4 @@ hnsw_sparsevec_support(PG_FUNCTION_ARGS)
}; };
PG_RETURN_POINTER(&typeInfo); PG_RETURN_POINTER(&typeInfo);
} };

View File

@@ -1,22 +1,13 @@
#include "postgres.h" #include "postgres.h"
#include "access/genam.h" #include <math.h>
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "commands/vacuum.h" #include "commands/vacuum.h"
#include "hnsw.h" #include "hnsw.h"
#include "nodes/pg_list.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "storage/lmgr.h" #include "storage/lmgr.h"
#include "utils/memutils.h" #include "utils/memutils.h"
#include "utils/rel.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 180000
#define vacuum_delay_point() vacuum_delay_point(false)
#endif
/* /*
* Check if deleted list contains an index TID * Check if deleted list contains an index TID
@@ -37,20 +28,17 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
{ {
BlockNumber blkno = HNSW_HEAD_BLKNO; BlockNumber blkno = HNSW_HEAD_BLKNO;
HnswElement highestPoint = &vacuumstate->highestPoint; HnswElement highestPoint = &vacuumstate->highestPoint;
HnswElement fallbackPoint = &vacuumstate->fallbackPoint;
Relation index = vacuumstate->index; Relation index = vacuumstate->index;
BufferAccessStrategy bas = vacuumstate->bas; BufferAccessStrategy bas = vacuumstate->bas;
HnswElement entryPoint = HnswGetEntryPoint(vacuumstate->index);
IndexBulkDeleteResult *stats = vacuumstate->stats; IndexBulkDeleteResult *stats = vacuumstate->stats;
/* Store separately since HnswElement level is uint8 */ /* Store separately since highestPoint.level is uint8 */
int highestLevel = -1; int highestLevel = -1;
int fallbackLevel = -1;
/* Initialize highest point and fallback point */ /* Initialize highest point */
highestPoint->blkno = InvalidBlockNumber; highestPoint->blkno = InvalidBlockNumber;
highestPoint->offno = InvalidOffsetNumber; highestPoint->offno = InvalidOffsetNumber;
fallbackPoint->blkno = InvalidBlockNumber;
fallbackPoint->offno = InvalidOffsetNumber;
while (BlockNumberIsValid(blkno)) while (BlockNumberIsValid(blkno))
{ {
@@ -122,31 +110,14 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
tidhash_insert(vacuumstate->deleted, ip, &found); tidhash_insert(vacuumstate->deleted, ip, &found);
Assert(!found); Assert(!found);
} }
else if (etup->level > highestLevel) else if (etup->level > highestLevel && !(entryPoint != NULL && blkno == entryPoint->blkno && offno == entryPoint->offno))
{ {
if (BlockNumberIsValid(highestPoint->blkno)) /* Keep track of highest non-entry point */
{
/* 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->blkno = blkno;
highestPoint->offno = offno; highestPoint->offno = offno;
highestPoint->level = etup->level; highestPoint->level = etup->level;
highestLevel = 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; blkno = HnswPageGetOpaque(page)->nextblkno;
@@ -158,10 +129,6 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
UnlockReleaseBuffer(buf); UnlockReleaseBuffer(buf);
} }
#ifdef HNSW_MEMORY
elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(CurrentMemoryContext, true) / 1024);
#endif
} }
/* /*
@@ -203,12 +170,7 @@ NeedsUpdated(HnswVacuumState * vacuumstate, HnswElement element)
/* Also update if layer 0 is not full */ /* Also update if layer 0 is not full */
/* This could indicate too many candidates being deleted during insert */ /* This could indicate too many candidates being deleted during insert */
if (!needsUpdated) if (!needsUpdated)
{
/* Keep clang-tidy happy */
Assert(ntup->count > 0);
needsUpdated = !ItemPointerIsValid(&ntup->indextids[ntup->count - 1]); needsUpdated = !ItemPointerIsValid(&ntup->indextids[ntup->count - 1]);
}
UnlockReleaseBuffer(buf); UnlockReleaseBuffer(buf);
@@ -222,12 +184,13 @@ static void
RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswElement entryPoint) RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswElement entryPoint)
{ {
Relation index = vacuumstate->index; Relation index = vacuumstate->index;
HnswSupport *support = &vacuumstate->support;
Buffer buf; Buffer buf;
Page page; Page page;
GenericXLogState *state; GenericXLogState *state;
int m = vacuumstate->m; int m = vacuumstate->m;
int efConstruction = vacuumstate->efConstruction; int efConstruction = vacuumstate->efConstruction;
FmgrInfo *procinfo = vacuumstate->procinfo;
Oid collation = vacuumstate->collation;
BufferAccessStrategy bas = vacuumstate->bas; BufferAccessStrategy bas = vacuumstate->bas;
HnswNeighborTuple ntup = vacuumstate->ntup; HnswNeighborTuple ntup = vacuumstate->ntup;
Size ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, m); Size ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, m);
@@ -242,7 +205,7 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
element->heaptidsLength = 0; element->heaptidsLength = 0;
/* Find neighbors for element, skipping itself */ /* Find neighbors for element, skipping itself */
HnswFindElementNeighbors(base, element, entryPoint, index, support, m, efConstruction, true); HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, true);
/* Zero memory for each element */ /* Zero memory for each element */
MemSet(ntup, 0, HNSW_TUPLE_ALLOC_SIZE); MemSet(ntup, 0, HNSW_TUPLE_ALLOC_SIZE);
@@ -266,7 +229,7 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
UnlockReleaseBuffer(buf); UnlockReleaseBuffer(buf);
/* Update neighbors */ /* Update neighbors */
HnswUpdateNeighborsOnDisk(index, support, element, m, true, false); HnswUpdateNeighborsOnDisk(index, procinfo, collation, element, m, true, false);
} }
/* /*
@@ -276,7 +239,6 @@ static void
RepairGraphEntryPoint(HnswVacuumState * vacuumstate) RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
{ {
Relation index = vacuumstate->index; Relation index = vacuumstate->index;
HnswSupport *support = &vacuumstate->support;
HnswElement highestPoint = &vacuumstate->highestPoint; HnswElement highestPoint = &vacuumstate->highestPoint;
HnswElement entryPoint; HnswElement entryPoint;
MemoryContext oldCtx = MemoryContextSwitchTo(vacuumstate->tmpCtx); MemoryContext oldCtx = MemoryContextSwitchTo(vacuumstate->tmpCtx);
@@ -293,27 +255,12 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
/* Get a shared lock */ /* Get a shared lock */
LockPage(index, HNSW_UPDATE_LOCK, ShareLock); LockPage(index, HNSW_UPDATE_LOCK, ShareLock);
/* Get latest entry point */ /* Load element */
entryPoint = HnswGetEntryPoint(index); HnswLoadElement(highestPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true, NULL);
/* Use fallback point if highest point is entry point */ /* Repair if needed */
if (entryPoint != NULL && entryPoint->blkno == highestPoint->blkno && entryPoint->offno == highestPoint->offno) if (NeedsUpdated(vacuumstate, highestPoint))
{ RepairGraphElement(vacuumstate, highestPoint, HnswGetEntryPoint(index));
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 */ /* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, ShareLock); UnlockPage(index, HNSW_UPDATE_LOCK, ShareLock);
@@ -347,7 +294,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
* is outdated, this can remove connections at higher levels in * is outdated, this can remove connections at higher levels in
* the graph until they are repaired, but this should be fine. * the graph until they are repaired, but this should be fine.
*/ */
HnswLoadElement(entryPoint, NULL, NULL, index, support, true, NULL); HnswLoadElement(entryPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true, NULL);
if (NeedsUpdated(vacuumstate, entryPoint)) if (NeedsUpdated(vacuumstate, entryPoint))
{ {
@@ -480,99 +427,6 @@ RepairGraph(HnswVacuumState * vacuumstate)
/* Reset memory context */ /* Reset memory context */
MemoryContextSwitchTo(oldCtx); MemoryContextSwitchTo(oldCtx);
MemoryContextReset(vacuumstate->tmpCtx); 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 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 deleted list */
if (DeletedContains(vacuumstate->deleted, indextid))
elog(ERROR, "hnsw graph not repaired");
}
if (nbuf != buf)
UnlockReleaseBuffer(nbuf);
}
blkno = HnswPageGetOpaque(page)->nextblkno;
UnlockReleaseBuffer(buf);
} }
} }
@@ -666,9 +520,8 @@ MarkDeleted(HnswVacuumState * vacuumstate)
ntup = (HnswNeighborTuple) PageGetItem(npage, PageGetItemId(npage, neighborOffno)); ntup = (HnswNeighborTuple) PageGetItem(npage, PageGetItemId(npage, neighborOffno));
/* Overwrite element */ /* Overwrite element */
/* Use memset instead of MemSet to keep clang-tidy happy */
etup->deleted = 1; etup->deleted = 1;
memset(&etup->data, 0, VARSIZE_ANY(&etup->data)); MemSet(&etup->data, 0, VARSIZE_ANY(&etup->data));
/* Overwrite neighbors */ /* Overwrite neighbors */
for (int i = 0; i < ntup->count; i++) for (int i = 0; i < ntup->count; i++)
@@ -728,13 +581,13 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
vacuumstate->callback_state = callback_state; vacuumstate->callback_state = callback_state;
vacuumstate->efConstruction = HnswGetEfConstruction(index); vacuumstate->efConstruction = HnswGetEfConstruction(index);
vacuumstate->bas = GetAccessStrategy(BAS_BULKREAD); vacuumstate->bas = GetAccessStrategy(BAS_BULKREAD);
vacuumstate->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
vacuumstate->collation = index->rd_indcollation[0];
vacuumstate->ntup = palloc0(HNSW_TUPLE_ALLOC_SIZE); vacuumstate->ntup = palloc0(HNSW_TUPLE_ALLOC_SIZE);
vacuumstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext, vacuumstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw vacuum temporary context", "Hnsw vacuum temporary context",
ALLOCSET_DEFAULT_SIZES); ALLOCSET_DEFAULT_SIZES);
HnswInitSupport(&vacuumstate->support, index);
/* Get m from metapage */ /* Get m from metapage */
HnswGetMetaPageInfo(index, &vacuumstate->m, NULL); HnswGetMetaPageInfo(index, &vacuumstate->m, NULL);
@@ -766,16 +619,13 @@ hnswbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
InitVacuumState(&vacuumstate, info, stats, callback, callback_state); InitVacuumState(&vacuumstate, info, stats, callback, callback_state);
/* Pass 1: Remove heap TIDs */ /* Pass 1: Remove heap TIDs */
HnswBench("RemoveHeapTids", RemoveHeapTids(&vacuumstate)); RemoveHeapTids(&vacuumstate);
/* Pass 2: Repair graph */ /* Pass 2: Repair graph */
HnswBench("RepairGraph", RepairGraph(&vacuumstate)); RepairGraph(&vacuumstate);
/* Pass 3: Confirm repaired */ /* Pass 3: Mark as deleted */
HnswBench("ConfirmRepaired", ConfirmRepaired(&vacuumstate)); MarkDeleted(&vacuumstate);
/* Pass 4: Mark as deleted */
HnswBench("MarkDeleted", MarkDeleted(&vacuumstate));
FreeVacuumState(&vacuumstate); FreeVacuumState(&vacuumstate);

View File

@@ -2,37 +2,23 @@
#include <float.h> #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/table.h"
#include "access/tableam.h" #include "access/tableam.h"
#include "access/tupdesc.h"
#include "access/parallel.h" #include "access/parallel.h"
#include "access/xact.h" #include "access/xact.h"
#include "access/xloginsert.h" #include "bitvec.h"
#include "catalog/index.h" #include "catalog/index.h"
#include "catalog/pg_operator_d.h" #include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h" #include "catalog/pg_type_d.h"
#include "commands/progress.h" #include "commands/progress.h"
#include "fmgr.h" #include "halfvec.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "miscadmin.h" #include "miscadmin.h"
#include "nodes/execnodes.h"
#include "optimizer/optimizer.h" #include "optimizer/optimizer.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "storage/condition_variable.h"
#include "tcop/tcopprot.h" #include "tcop/tcopprot.h"
#include "utils/memutils.h" #include "utils/memutils.h"
#include "utils/rel.h" #include "vector.h"
#include "utils/sampling.h"
#include "utils/snapmgr.h"
#include "utils/tuplesort.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 140000 #if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h" #include "utils/backend_progress.h"
@@ -63,13 +49,15 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0])); Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* /*
* Check with KMEANS_NORM_PROC that the value can be normalized since * Normalize with KMEANS_NORM_PROC since spherical distance function
* spherical distance function expects unit vectors * expects unit vectors
*/ */
if (buildstate->kmeansnormprocinfo != NULL) if (buildstate->kmeansnormprocinfo != NULL)
{ {
if (!IvfflatCheckNorm(buildstate->kmeansnormprocinfo, buildstate->collation, value)) if (!IvfflatCheckNorm(buildstate->kmeansnormprocinfo, buildstate->collation, value))
return; return;
value = IvfflatNormValue(buildstate->typeInfo, buildstate->collation, value);
} }
if (samples->length < targsamples) if (samples->length < targsamples)
@@ -80,7 +68,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
else else
{ {
if (buildstate->rowstoskip < 0) if (buildstate->rowstoskip < 0)
buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, buildstate->samplerows, targsamples); buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, samples->length, targsamples);
if (buildstate->rowstoskip <= 0) if (buildstate->rowstoskip <= 0)
{ {
@@ -96,9 +84,6 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
buildstate->rowstoskip -= 1; buildstate->rowstoskip -= 1;
} }
/* Increment after reservoir_get_next_S */
buildstate->samplerows += 1;
} }
/* /*
@@ -135,7 +120,6 @@ SampleRows(IvfflatBuildState * buildstate)
int targsamples = buildstate->samples->maxlen; int targsamples = buildstate->samples->maxlen;
BlockNumber totalblocks = RelationGetNumberOfBlocks(buildstate->heap); BlockNumber totalblocks = RelationGetNumberOfBlocks(buildstate->heap);
buildstate->samplerows = 0;
buildstate->rowstoskip = -1; buildstate->rowstoskip = -1;
BlockSampler_Init(&buildstate->bs, totalblocks, targsamples, RandomInt()); BlockSampler_Init(&buildstate->bs, totalblocks, targsamples, RandomInt());
@@ -145,24 +129,8 @@ SampleRows(IvfflatBuildState * buildstate)
{ {
BlockNumber targblock = BlockSampler_Next(&buildstate->bs); 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, table_index_build_range_scan(buildstate->heap, buildstate->index, buildstate->indexInfo,
false, false, false, targblock, 1, SampleCallback, (void *) buildstate, NULL); false, true, false, targblock, 1, SampleCallback, (void *) buildstate, NULL);
}
/* Normalize if needed */
if (buildstate->kmeansnormprocinfo != NULL)
{
VectorArray samples = buildstate->samples;
for (int i = 0; i < samples->length; i++)
{
Datum value = PointerGetDatum(VectorArrayGet(samples, i));
Datum normValue = IvfflatNormValue(buildstate->typeInfo, buildstate->collation, value);
VectorArraySet(samples, i, DatumGetPointer(normValue));
pfree(DatumGetPointer(normValue));
}
} }
} }
@@ -170,7 +138,7 @@ SampleRows(IvfflatBuildState * buildstate)
* Add tuple to sort * Add tuple to sort
*/ */
static void static void
AddTupleToSort(ItemPointer tid, Datum *values, IvfflatBuildState * buildstate) AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState * buildstate)
{ {
double distance; double distance;
double minDistance = DBL_MAX; double minDistance = DBL_MAX;
@@ -247,7 +215,7 @@ BuildCallback(Relation index, ItemPointer tid, Datum *values,
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx); oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
/* Add tuple to sort */ /* Add tuple to sort */
AddTupleToSort(tid, values, buildstate); AddTupleToSort(index, tid, values, buildstate);
/* Reset memory context */ /* Reset memory context */
MemoryContextSwitchTo(oldCtx); MemoryContextSwitchTo(oldCtx);
@@ -260,11 +228,11 @@ BuildCallback(Relation index, ItemPointer tid, Datum *values,
static inline void static inline void
GetNextTuple(Tuplesortstate *sortstate, TupleDesc tupdesc, TupleTableSlot *slot, IndexTuple *itup, int *list) GetNextTuple(Tuplesortstate *sortstate, TupleDesc tupdesc, TupleTableSlot *slot, IndexTuple *itup, int *list)
{ {
Datum value;
bool isnull;
if (tuplesort_gettupleslot(sortstate, true, false, slot, NULL)) if (tuplesort_gettupleslot(sortstate, true, false, slot, NULL))
{ {
Datum value;
bool isnull;
*list = DatumGetInt32(slot_getattr(slot, 1, &isnull)); *list = DatumGetInt32(slot_getattr(slot, 1, &isnull));
value = slot_getattr(slot, 3, &isnull); value = slot_getattr(slot, 3, &isnull);
@@ -286,8 +254,8 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
IndexTuple itup = NULL; /* silence compiler warning */ IndexTuple itup = NULL; /* silence compiler warning */
int64 inserted = 0; int64 inserted = 0;
TupleTableSlot *slot = MakeSingleTupleTableSlot(buildstate->sortdesc, &TTSOpsMinimalTuple); TupleTableSlot *slot = MakeSingleTupleTableSlot(buildstate->tupdesc, &TTSOpsMinimalTuple);
TupleDesc tupdesc = buildstate->tupdesc; TupleDesc tupdesc = RelationGetDescr(index);
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_LOAD); pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_LOAD);
@@ -351,7 +319,6 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->index = index; buildstate->index = index;
buildstate->indexInfo = indexInfo; buildstate->indexInfo = indexInfo;
buildstate->typeInfo = IvfflatGetTypeInfo(index); buildstate->typeInfo = IvfflatGetTypeInfo(index);
buildstate->tupdesc = RelationGetDescr(index);
buildstate->lists = IvfflatGetLists(index); buildstate->lists = IvfflatGetLists(index);
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod; buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
@@ -389,17 +356,13 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
errmsg("dimensions must be greater than one for this opclass"))); errmsg("dimensions must be greater than one for this opclass")));
/* Create tuple description for sorting */ /* Create tuple description for sorting */
buildstate->sortdesc = CreateTemplateTupleDesc(3); buildstate->tupdesc = CreateTemplateTupleDesc(3);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 1, "list", INT4OID, -1, 0); TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 1, "list", INT4OID, -1, 0);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0); TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 3, "vector", TupleDescAttr(buildstate->tupdesc, 0)->atttypid, -1, 0); TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 3, "vector", RelationGetDescr(index)->attrs[0].atttypid, -1, 0);
#if PG_VERSION_NUM >= 190000
TupleDescFinalize(buildstate->sortdesc);
#endif
buildstate->slot = MakeSingleTupleTableSlot(buildstate->sortdesc, &TTSOpsVirtual); buildstate->slot = MakeSingleTupleTableSlot(buildstate->tupdesc, &TTSOpsVirtual);
/* TODO Ensure within maintenance_work_mem */
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, buildstate->typeInfo->itemSize(buildstate->dimensions)); buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, buildstate->typeInfo->itemSize(buildstate->dimensions));
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists); buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
@@ -458,7 +421,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions, buildstate->centers->itemsize); buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions, buildstate->centers->itemsize);
if (buildstate->heap != NULL) if (buildstate->heap != NULL)
{ {
IvfflatBench("sample rows", SampleRows(buildstate)); SampleRows(buildstate);
if (buildstate->samples->length < buildstate->lists) if (buildstate->samples->length < buildstate->lists)
{ {
@@ -506,8 +469,8 @@ CreateMetaPage(Relation index, int dimensions, int lists, ForkNumber forkNum)
* Create list pages * Create list pages
*/ */
static void static void
CreateListPages(Relation index, VectorArray centers, int lists, CreateListPages(Relation index, VectorArray centers, int dimensions,
ForkNumber forkNum, ListInfo * *listInfo) int lists, ForkNumber forkNum, ListInfo * *listInfo)
{ {
Buffer buf; Buffer buf;
Page page; Page page;
@@ -670,14 +633,10 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
InitBuildState(&buildstate, ivfspool->heap, ivfspool->index, indexInfo); InitBuildState(&buildstate, ivfspool->heap, ivfspool->index, indexInfo);
memcpy(buildstate.centers->items, ivfcenters, buildstate.centers->itemsize * buildstate.centers->maxlen); memcpy(buildstate.centers->items, ivfcenters, buildstate.centers->itemsize * buildstate.centers->maxlen);
buildstate.centers->length = buildstate.centers->maxlen; buildstate.centers->length = buildstate.centers->maxlen;
ivfspool->sortstate = InitBuildSortState(buildstate.sortdesc, sortmem, coordinate); ivfspool->sortstate = InitBuildSortState(buildstate.tupdesc, sortmem, coordinate);
buildstate.sortstate = ivfspool->sortstate; buildstate.sortstate = ivfspool->sortstate;
scan = table_beginscan_parallel(ivfspool->heap, 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, reltuples = table_index_build_scan(ivfspool->heap, ivfspool->index, indexInfo,
true, progress, BuildCallback, true, progress, BuildCallback,
(void *) &buildstate, scan); (void *) &buildstate, scan);
@@ -991,7 +950,7 @@ AssignTuples(IvfflatBuildState * buildstate)
} }
/* Begin serial/leader tuplesort */ /* Begin serial/leader tuplesort */
buildstate->sortstate = InitBuildSortState(buildstate->sortdesc, maintenance_work_mem, coordinate); buildstate->sortstate = InitBuildSortState(buildstate->tupdesc, maintenance_work_mem, coordinate);
/* Add tuples to sort */ /* Add tuples to sort */
if (buildstate->heap != NULL) if (buildstate->heap != NULL)
@@ -1044,7 +1003,7 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
/* Create pages */ /* Create pages */
CreateMetaPage(index, buildstate->dimensions, buildstate->lists, forkNum); CreateMetaPage(index, buildstate->dimensions, buildstate->lists, forkNum);
CreateListPages(index, buildstate->centers, buildstate->lists, forkNum, &buildstate->listInfo); CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo);
CreateEntryPages(buildstate, forkNum); CreateEntryPages(buildstate, forkNum);
/* Write WAL for initialization fork since GenericXLog functions do not */ /* Write WAL for initialization fork since GenericXLog functions do not */
@@ -1063,10 +1022,6 @@ ivfflatbuild(Relation heap, Relation index, IndexInfo *indexInfo)
IndexBuildResult *result; IndexBuildResult *result;
IvfflatBuildState buildstate; IvfflatBuildState buildstate;
#ifdef IVFFLAT_BENCH
SeedRandom(42);
#endif
BuildIndex(heap, index, indexInfo, &buildstate, MAIN_FORKNUM); BuildIndex(heap, index, indexInfo, &buildstate, MAIN_FORKNUM);
result = (IndexBuildResult *) palloc(sizeof(IndexBuildResult)); result = (IndexBuildResult *) palloc(sizeof(IndexBuildResult));

View File

@@ -3,35 +3,22 @@
#include <float.h> #include <float.h>
#include "access/amapi.h" #include "access/amapi.h"
#include "access/genam.h"
#include "access/reloptions.h" #include "access/reloptions.h"
#include "commands/progress.h" #include "commands/progress.h"
#include "commands/vacuum.h" #include "commands/vacuum.h"
#include "fmgr.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "nodes/pg_list.h"
#include "utils/float.h" #include "utils/float.h"
#include "utils/guc.h" #include "utils/guc.h"
#include "utils/relcache.h"
#include "utils/selfuncs.h" #include "utils/selfuncs.h"
#include "utils/spccache.h" #include "utils/spccache.h"
#include "vector.h"
#if PG_VERSION_NUM < 150000 #if PG_VERSION_NUM < 150000
#define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x) #define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
#endif #endif
int ivfflat_probes; int ivfflat_probes;
int ivfflat_iterative_scan;
int ivfflat_max_probes;
static relopt_kind ivfflat_relopt_kind; static relopt_kind ivfflat_relopt_kind;
static const struct config_enum_entry ivfflat_iterative_scan_options[] = {
{"off", IVFFLAT_ITERATIVE_SCAN_OFF, false},
{"relaxed_order", IVFFLAT_ITERATIVE_SCAN_RELAXED, false},
{NULL, 0, false}
};
/* /*
* Initialize index options and variables * Initialize index options and variables
*/ */
@@ -46,15 +33,6 @@ IvfflatInit(void)
"Valid range is 1..lists.", &ivfflat_probes, "Valid range is 1..lists.", &ivfflat_probes,
IVFFLAT_DEFAULT_PROBES, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL); IVFFLAT_DEFAULT_PROBES, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
DefineCustomEnumVariable("ivfflat.iterative_scan", "Sets the mode for iterative scans",
NULL, &ivfflat_iterative_scan,
IVFFLAT_ITERATIVE_SCAN_OFF, ivfflat_iterative_scan_options, PGC_USERSET, 0, NULL, NULL, NULL);
/* If this is less than probes, probes is used */
DefineCustomIntVariable("ivfflat.max_probes", "Sets the max number of probes for iterative scans",
NULL, &ivfflat_max_probes,
IVFFLAT_MAX_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
MarkGUCPrefixReserved("ivfflat"); MarkGUCPrefixReserved("ivfflat");
} }
@@ -91,30 +69,22 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
GenericCosts costs; GenericCosts costs;
int lists; int lists;
double ratio; double ratio;
double sequentialRatio = 0.5;
double startupPages;
double spc_seq_page_cost; double spc_seq_page_cost;
Relation index; Relation index;
/* Never use index without order */ /* Never use index without order */
if (path->indexorderbys == NIL) if (path->indexorderbys == NULL)
{ {
*indexStartupCost = get_float8_infinity(); *indexStartupCost = get_float8_infinity();
*indexTotalCost = get_float8_infinity(); *indexTotalCost = get_float8_infinity();
*indexSelectivity = 0; *indexSelectivity = 0;
*indexCorrelation = 0; *indexCorrelation = 0;
*indexPages = 0; *indexPages = 0;
#if PG_VERSION_NUM >= 180000
/* See "On disable_cost" thread on pgsql-hackers */
path->path.disabled_nodes = 2;
#endif
return; return;
} }
MemSet(&costs, 0, sizeof(costs)); MemSet(&costs, 0, sizeof(costs));
genericcostestimate(root, path, loop_count, &costs);
index = index_open(path->indexinfo->indexoid, NoLock); index = index_open(path->indexinfo->indexoid, NoLock);
IvfflatGetMetaPageInfo(index, &lists, NULL); IvfflatGetMetaPageInfo(index, &lists, NULL);
index_close(index, NoLock); index_close(index, NoLock);
@@ -124,26 +94,34 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
if (ratio > 1.0) if (ratio > 1.0)
ratio = 1.0; ratio = 1.0;
/*
* This gives us the subset of tuples to visit. This value is passed into
* the generic cost estimator to determine the number of pages to visit
* during the index scan.
*/
costs.numIndexTuples = path->indexinfo->tuples * ratio;
genericcostestimate(root, path, loop_count, &costs);
get_tablespace_page_costs(path->indexinfo->reltablespace, NULL, &spc_seq_page_cost); get_tablespace_page_costs(path->indexinfo->reltablespace, NULL, &spc_seq_page_cost);
/* Change some page cost from random to sequential */
costs.indexTotalCost -= sequentialRatio * costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
/* Startup cost is cost before returning the first row */
costs.indexStartupCost = costs.indexTotalCost * ratio;
/* Adjust cost if needed since TOAST not included in seq scan cost */ /* Adjust cost if needed since TOAST not included in seq scan cost */
startupPages = costs.numIndexPages * ratio; if (costs.numIndexPages > path->indexinfo->rel->pages && ratio < 0.5)
if (startupPages > path->indexinfo->rel->pages && ratio < 0.5)
{ {
/* Change rest of page cost from random to sequential */ /* Change all page cost from random to sequential */
costs.indexStartupCost -= (1 - sequentialRatio) * startupPages * (costs.spc_random_page_cost - spc_seq_page_cost); costs.indexTotalCost -= costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
/* Remove cost of extra pages */ /* Remove cost of extra pages */
costs.indexStartupCost -= (startupPages - path->indexinfo->rel->pages) * spc_seq_page_cost; costs.indexTotalCost -= (costs.numIndexPages - path->indexinfo->rel->pages) * spc_seq_page_cost;
}
else
{
/* Change some page cost from random to sequential */
costs.indexTotalCost -= 0.5 * costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
} }
*indexStartupCost = costs.indexStartupCost; /* Use total cost since most work happens before first tuple is returned */
*indexStartupCost = costs.indexTotalCost;
*indexTotalCost = costs.indexTotalCost; *indexTotalCost = costs.indexTotalCost;
*indexSelectivity = costs.indexSelectivity; *indexSelectivity = costs.indexSelectivity;
*indexCorrelation = costs.indexCorrelation; *indexCorrelation = costs.indexCorrelation;
@@ -184,64 +162,6 @@ FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflathandler);
Datum Datum
ivfflathandler(PG_FUNCTION_ARGS) 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); IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0; amroutine->amstrategies = 0;
@@ -249,11 +169,6 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amoptsprocnum = 0; amroutine->amoptsprocnum = 0;
amroutine->amcanorder = false; amroutine->amcanorder = false;
amroutine->amcanorderbyop = true; amroutine->amcanorderbyop = true;
#if PG_VERSION_NUM >= 180000
amroutine->amcanhash = false;
amroutine->amconsistentequality = false;
amroutine->amconsistentordering = false;
#endif
amroutine->amcanbackward = false; /* can change direction mid-scan */ amroutine->amcanbackward = false; /* can change direction mid-scan */
amroutine->amcanunique = false; amroutine->amcanunique = false;
amroutine->amcanmulticol = false; amroutine->amcanmulticol = false;
@@ -286,9 +201,6 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amvacuumcleanup = ivfflatvacuumcleanup; amroutine->amvacuumcleanup = ivfflatvacuumcleanup;
amroutine->amcanreturn = NULL; /* tuple not included in heapsort */ amroutine->amcanreturn = NULL; /* tuple not included in heapsort */
amroutine->amcostestimate = ivfflatcostestimate; amroutine->amcostestimate = ivfflatcostestimate;
#if PG_VERSION_NUM >= 180000
amroutine->amgettreeheight = NULL;
#endif
amroutine->amoptions = ivfflatoptions; amroutine->amoptions = ivfflatoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */ amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
amroutine->ambuildphasename = ivfflatbuildphasename; amroutine->ambuildphasename = ivfflatbuildphasename;
@@ -309,11 +221,5 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->aminitparallelscan = NULL; amroutine->aminitparallelscan = NULL;
amroutine->amparallelrescan = NULL; amroutine->amparallelrescan = NULL;
#if PG_VERSION_NUM >= 180000
amroutine->amtranslatestrategy = NULL;
amroutine->amtranslatecmptype = NULL;
#endif
PG_RETURN_POINTER(amroutine); PG_RETURN_POINTER(amroutine);
#endif
} }

View File

@@ -9,15 +9,10 @@
#include "lib/pairingheap.h" #include "lib/pairingheap.h"
#include "nodes/execnodes.h" #include "nodes/execnodes.h"
#include "port.h" /* for random() */ #include "port.h" /* for random() */
#include "storage/condition_variable.h"
#include "utils/sampling.h" #include "utils/sampling.h"
#include "utils/tuplesort.h" #include "utils/tuplesort.h"
#include "vector.h" #include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 150000 #if PG_VERSION_NUM >= 150000
#include "common/pg_prng.h" #include "common/pg_prng.h"
#endif #endif
@@ -26,10 +21,6 @@
#include "portability/instr_time.h" #include "portability/instr_time.h"
#endif #endif
#if PG_VERSION_NUM >= 190000
typedef Pointer Item;
#endif
#define IVFFLAT_MAX_DIM 2000 #define IVFFLAT_MAX_DIM 2000
/* Support functions */ /* Support functions */
@@ -82,23 +73,13 @@ typedef Pointer Item;
#if PG_VERSION_NUM >= 150000 #if PG_VERSION_NUM >= 150000
#define RandomDouble() pg_prng_double(&pg_global_prng_state) #define RandomDouble() pg_prng_double(&pg_global_prng_state)
#define RandomInt() pg_prng_uint32(&pg_global_prng_state) #define RandomInt() pg_prng_uint32(&pg_global_prng_state)
#define SeedRandom(seed) pg_prng_seed(&pg_global_prng_state, seed)
#else #else
#define RandomDouble() (((double) random()) / MAX_RANDOM_VALUE) #define RandomDouble() (((double) random()) / MAX_RANDOM_VALUE)
#define RandomInt() random() #define RandomInt() random()
#define SeedRandom(seed) srandom(seed)
#endif #endif
/* Variables */ /* Variables */
extern int ivfflat_probes; extern int ivfflat_probes;
extern int ivfflat_iterative_scan;
extern int ivfflat_max_probes;
typedef enum IvfflatIterativeScanMode
{
IVFFLAT_ITERATIVE_SCAN_OFF,
IVFFLAT_ITERATIVE_SCAN_RELAXED
} IvfflatIterativeScanMode;
typedef struct VectorArrayData typedef struct VectorArrayData
{ {
@@ -184,7 +165,6 @@ typedef struct IvfflatBuildState
Relation index; Relation index;
IndexInfo *indexInfo; IndexInfo *indexInfo;
const IvfflatTypeInfo *typeInfo; const IvfflatTypeInfo *typeInfo;
TupleDesc tupdesc;
/* Settings */ /* Settings */
int dimensions; int dimensions;
@@ -214,12 +194,11 @@ typedef struct IvfflatBuildState
/* Sampling */ /* Sampling */
BlockSamplerData bs; BlockSamplerData bs;
ReservoirStateData rstate; ReservoirStateData rstate;
double samplerows; int rowstoskip;
double rowstoskip;
/* Sorting */ /* Sorting */
Tuplesortstate *sortstate; Tuplesortstate *sortstate;
TupleDesc sortdesc; TupleDesc tupdesc;
TupleTableSlot *slot; TupleTableSlot *slot;
/* Memory */ /* Memory */
@@ -268,11 +247,8 @@ typedef struct IvfflatScanOpaqueData
{ {
const IvfflatTypeInfo *typeInfo; const IvfflatTypeInfo *typeInfo;
int probes; int probes;
int maxProbes;
int dimensions; int dimensions;
bool first; bool first;
Datum value;
MemoryContext tmpCtx;
/* Sorting */ /* Sorting */
Tuplesortstate *sortstate; Tuplesortstate *sortstate;
@@ -289,9 +265,7 @@ typedef struct IvfflatScanOpaqueData
/* Lists */ /* Lists */
pairingheap *listQueue; pairingheap *listQueue;
BlockNumber *listPages; IvfflatScanList lists[FLEXIBLE_ARRAY_MEMBER]; /* must come last */
int listIndex;
IvfflatScanList *lists;
} IvfflatScanOpaqueData; } IvfflatScanOpaqueData;
typedef IvfflatScanOpaqueData * IvfflatScanOpaque; typedef IvfflatScanOpaqueData * IvfflatScanOpaque;

View File

@@ -2,16 +2,11 @@
#include <float.h> #include <float.h>
#include "access/genam.h"
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "access/itup.h"
#include "fmgr.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "nodes/execnodes.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "storage/lmgr.h" #include "storage/lmgr.h"
#include "utils/memutils.h" #include "utils/memutils.h"
#include "utils/rel.h"
/* /*
* Find the list that minimizes the distance function * Find the list that minimizes the distance function
@@ -70,7 +65,7 @@ FindInsertPage(Relation index, Datum *values, BlockNumber *insertPage, ListInfo
* Insert a tuple into the index * Insert a tuple into the index
*/ */
static void static void
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid) InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
{ {
const IvfflatTypeInfo *typeInfo = IvfflatGetTypeInfo(index); const IvfflatTypeInfo *typeInfo = IvfflatGetTypeInfo(index);
IndexTuple itup; IndexTuple itup;
@@ -103,7 +98,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid)
IvfflatGetMetaPageInfo(index, NULL, NULL); IvfflatGetMetaPageInfo(index, NULL, NULL);
/* Find the insert page - sets the page and list info */ /* Find the insert page - sets the page and list info */
FindInsertPage(index, &value, &insertPage, &listInfo); FindInsertPage(index, values, &insertPage, &listInfo);
Assert(BlockNumberIsValid(insertPage)); Assert(BlockNumberIsValid(insertPage));
originalInsertPage = insertPage; originalInsertPage = insertPage;
@@ -209,7 +204,7 @@ ivfflatinsert(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid,
oldCtx = MemoryContextSwitchTo(insertCtx); oldCtx = MemoryContextSwitchTo(insertCtx);
/* Insert tuple */ /* Insert tuple */
InsertTuple(index, values, isnull, heap_tid); InsertTuple(index, values, isnull, heap_tid, heap);
/* Delete memory context */ /* Delete memory context */
MemoryContextSwitchTo(oldCtx); MemoryContextSwitchTo(oldCtx);

View File

@@ -1,19 +1,17 @@
#include "postgres.h" #include "postgres.h"
#include <float.h> #include <float.h>
#include <limits.h>
#include <math.h> #include <math.h>
#include "access/genam.h" #include "bitvec.h"
#include "fmgr.h" #include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "miscadmin.h" #include "miscadmin.h"
#include "utils/builtins.h"
#include "utils/datum.h"
#include "utils/memutils.h" #include "utils/memutils.h"
#include "utils/relcache.h" #include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/* /*
* Initialize with kmeans++ * Initialize with kmeans++

View File

@@ -2,25 +2,17 @@
#include <float.h> #include <float.h>
#include "access/genam.h"
#include "access/itup.h"
#include "access/relscan.h" #include "access/relscan.h"
#include "access/tupdesc.h"
#include "catalog/pg_operator_d.h" #include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h" #include "catalog/pg_type_d.h"
#include "fmgr.h"
#include "lib/pairingheap.h" #include "lib/pairingheap.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "miscadmin.h" #include "miscadmin.h"
#include "pgstat.h" #include "pgstat.h"
#include "storage/bufmgr.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 #ifdef IVFFLAT_MEMORY
#include "varatt.h" #include "utils/memutils.h"
#endif #endif
#define GetScanList(ptr) pairingheap_container(IvfflatScanList, ph_node, ptr) #define GetScanList(ptr) pairingheap_container(IvfflatScanList, ph_node, ptr)
@@ -73,7 +65,7 @@ GetScanLists(IndexScanDesc scan, Datum value)
/* Use procinfo from the index instead of scan key for performance */ /* Use procinfo from the index instead of scan key for performance */
distance = DatumGetFloat8(so->distfunc(so->procinfo, so->collation, PointerGetDatum(&list->center), value)); distance = DatumGetFloat8(so->distfunc(so->procinfo, so->collation, PointerGetDatum(&list->center), value));
if (listCount < so->maxProbes) if (listCount < so->probes)
{ {
IvfflatScanList *scanlist; IvfflatScanList *scanlist;
@@ -86,7 +78,7 @@ GetScanLists(IndexScanDesc scan, Datum value)
pairingheap_add(so->listQueue, &scanlist->ph_node); pairingheap_add(so->listQueue, &scanlist->ph_node);
/* Calculate max distance */ /* Calculate max distance */
if (listCount == so->maxProbes) if (listCount == so->probes)
maxDistance = GetScanList(pairingheap_first(so->listQueue))->distance; maxDistance = GetScanList(pairingheap_first(so->listQueue))->distance;
} }
else if (distance < maxDistance) else if (distance < maxDistance)
@@ -110,11 +102,6 @@ GetScanLists(IndexScanDesc scan, Datum value)
UnlockReleaseBuffer(cbuf); UnlockReleaseBuffer(cbuf);
} }
for (int i = listCount - 1; i >= 0; i--)
so->listPages[i] = GetScanList(pairingheap_remove_first(so->listQueue))->startPage;
Assert(pairingheap_is_empty(so->listQueue));
} }
/* /*
@@ -125,15 +112,13 @@ GetScanItems(IndexScanDesc scan, Datum value)
{ {
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque; IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
TupleDesc tupdesc = RelationGetDescr(scan->indexRelation); TupleDesc tupdesc = RelationGetDescr(scan->indexRelation);
double tuples = 0;
TupleTableSlot *slot = so->vslot; TupleTableSlot *slot = so->vslot;
int batchProbes = 0;
tuplesort_reset(so->sortstate);
/* Search closest probes lists */ /* Search closest probes lists */
while (so->listIndex < so->maxProbes && (++batchProbes) <= so->probes) while (!pairingheap_is_empty(so->listQueue))
{ {
BlockNumber searchPage = so->listPages[so->listIndex++]; BlockNumber searchPage = GetScanList(pairingheap_remove_first(so->listQueue))->startPage;
/* Search all entry pages for list */ /* Search all entry pages for list */
while (BlockNumberIsValid(searchPage)) while (BlockNumberIsValid(searchPage))
@@ -171,6 +156,8 @@ GetScanItems(IndexScanDesc scan, Datum value)
ExecStoreVirtualTuple(slot); ExecStoreVirtualTuple(slot);
tuplesort_puttupleslot(so->sortstate, slot); tuplesort_puttupleslot(so->sortstate, slot);
tuples++;
} }
searchPage = IvfflatPageGetOpaque(page)->nextblkno; searchPage = IvfflatPageGetOpaque(page)->nextblkno;
@@ -179,11 +166,13 @@ GetScanItems(IndexScanDesc scan, Datum value)
} }
} }
tuplesort_performsort(so->sortstate); if (tuples < 100)
ereport(DEBUG1,
(errmsg("index scan found few tuples"),
errdetail("Index may have been created with little data."),
errhint("Recreate the index and possibly decrease lists.")));
#if defined(IVFFLAT_MEMORY) tuplesort_performsort(so->sortstate);
elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(CurrentMemoryContext, true) / (1024 * 1024));
#endif
} }
/* /*
@@ -220,13 +209,7 @@ GetScanValue(IndexScanDesc scan)
/* Normalize if needed */ /* Normalize if needed */
if (so->normprocinfo != NULL) if (so->normprocinfo != NULL)
{
MemoryContext oldCtx = MemoryContextSwitchTo(so->tmpCtx);
value = IvfflatNormValue(so->typeInfo, so->collation, value); value = IvfflatNormValue(so->typeInfo, so->collation, value);
MemoryContextSwitchTo(oldCtx);
}
} }
return value; return value;
@@ -257,30 +240,19 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
int lists; int lists;
int dimensions; int dimensions;
int probes = ivfflat_probes; int probes = ivfflat_probes;
int maxProbes;
MemoryContext oldCtx;
scan = RelationGetIndexScan(index, nkeys, norderbys); scan = RelationGetIndexScan(index, nkeys, norderbys);
/* Get lists and dimensions from metapage */ /* Get lists and dimensions from metapage */
IvfflatGetMetaPageInfo(index, &lists, &dimensions); IvfflatGetMetaPageInfo(index, &lists, &dimensions);
if (ivfflat_iterative_scan != IVFFLAT_ITERATIVE_SCAN_OFF)
maxProbes = Max(ivfflat_max_probes, probes);
else
maxProbes = probes;
if (probes > lists) if (probes > lists)
probes = lists; probes = lists;
if (maxProbes > lists) so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
maxProbes = lists;
so = (IvfflatScanOpaque) palloc(sizeof(IvfflatScanOpaqueData));
so->typeInfo = IvfflatGetTypeInfo(index); so->typeInfo = IvfflatGetTypeInfo(index);
so->first = true; so->first = true;
so->probes = probes; so->probes = probes;
so->maxProbes = maxProbes;
so->dimensions = dimensions; so->dimensions = dimensions;
/* Set support functions */ /* Set support functions */
@@ -288,19 +260,10 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
so->normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC); so->normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
so->collation = index->rd_indcollation[0]; so->collation = index->rd_indcollation[0];
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat scan temporary context",
ALLOCSET_DEFAULT_SIZES);
oldCtx = MemoryContextSwitchTo(so->tmpCtx);
/* Create tuple description for sorting */ /* Create tuple description for sorting */
so->tupdesc = CreateTemplateTupleDesc(2); so->tupdesc = CreateTemplateTupleDesc(2);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0); TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0); TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
#if PG_VERSION_NUM >= 190000
TupleDescFinalize(so->tupdesc);
#endif
/* Prep sort */ /* Prep sort */
so->sortstate = InitScanSortState(so->tupdesc); so->sortstate = InitScanSortState(so->tupdesc);
@@ -317,11 +280,6 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
so->bas = GetAccessStrategy(BAS_BULKREAD); so->bas = GetAccessStrategy(BAS_BULKREAD);
so->listQueue = pairingheap_allocate(CompareLists, scan); so->listQueue = pairingheap_allocate(CompareLists, scan);
so->listPages = palloc(maxProbes * sizeof(BlockNumber));
so->listIndex = 0;
so->lists = palloc(maxProbes * sizeof(IvfflatScanList));
MemoryContextSwitchTo(oldCtx);
scan->opaque = so; scan->opaque = so;
@@ -336,9 +294,11 @@ ivfflatrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int
{ {
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque; IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
if (!so->first)
tuplesort_reset(so->sortstate);
so->first = true; so->first = true;
pairingheap_reset(so->listQueue); pairingheap_reset(so->listQueue);
so->listIndex = 0;
if (keys && scan->numberOfKeys > 0) if (keys && scan->numberOfKeys > 0)
memmove(scan->keyData, keys, scan->numberOfKeys * sizeof(ScanKeyData)); memmove(scan->keyData, keys, scan->numberOfKeys * sizeof(ScanKeyData));
@@ -354,8 +314,6 @@ bool
ivfflatgettuple(IndexScanDesc scan, ScanDirection dir) ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
{ {
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque; IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
ItemPointer heaptid;
bool isnull;
/* /*
* Index can be used to scan backward, but Postgres doesn't support * Index can be used to scan backward, but Postgres doesn't support
@@ -369,10 +327,6 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
/* Count index scan for stats */ /* Count index scan for stats */
pgstat_count_index_scan(scan->indexRelation); pgstat_count_index_scan(scan->indexRelation);
#if PG_VERSION_NUM >= 180000
if (scan->instrument)
scan->instrument->nsearches++;
#endif
/* Safety check */ /* Safety check */
if (scan->orderByData == NULL) if (scan->orderByData == NULL)
@@ -387,23 +341,28 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
IvfflatBench("GetScanLists", GetScanLists(scan, value)); IvfflatBench("GetScanLists", GetScanLists(scan, value));
IvfflatBench("GetScanItems", GetScanItems(scan, value)); IvfflatBench("GetScanItems", GetScanItems(scan, value));
so->first = false; so->first = false;
so->value = value;
#if defined(IVFFLAT_MEMORY)
elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(CurrentMemoryContext, true) / (1024 * 1024));
#endif
/* Clean up if we allocated a new value */
if (value != scan->orderByData->sk_argument)
pfree(DatumGetPointer(value));
} }
while (!tuplesort_gettupleslot(so->sortstate, true, false, so->mslot, NULL)) if (tuplesort_gettupleslot(so->sortstate, true, false, so->mslot, NULL))
{ {
if (so->listIndex == so->maxProbes) bool isnull;
return false; ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->mslot, 2, &isnull));
IvfflatBench("GetScanItems", GetScanItems(scan, so->value)); scan->xs_heaptid = *heaptid;
scan->xs_recheck = false;
scan->xs_recheckorderby = false;
return true;
} }
heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->mslot, 2, &isnull)); return false;
scan->xs_heaptid = *heaptid;
scan->xs_recheck = false;
scan->xs_recheckorderby = false;
return true;
} }
/* /*
@@ -414,10 +373,12 @@ ivfflatendscan(IndexScanDesc scan)
{ {
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque; IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
/* Free any temporary files */ pairingheap_free(so->listQueue);
tuplesort_end(so->sortstate); tuplesort_end(so->sortstate);
FreeAccessStrategy(so->bas);
FreeTupleDesc(so->tupdesc);
MemoryContextDelete(so->tmpCtx); /* TODO Free vslot and mslot without freeing TupleDesc */
pfree(so); pfree(so);
scan->opaque = NULL; scan->opaque = NULL;

View File

@@ -1,19 +1,13 @@
#include "postgres.h" #include "postgres.h"
#include "access/genam.h"
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "bitvec.h"
#include "catalog/pg_type.h"
#include "fmgr.h" #include "fmgr.h"
#include "halfutils.h" #include "halfutils.h"
#include "halfvec.h" #include "halfvec.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.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 * Allocate a vector array
@@ -265,8 +259,8 @@ VectorUpdateCenter(Pointer v, int dimensions, float *x)
SET_VARSIZE(vec, VECTOR_SIZE(dimensions)); SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions; vec->dim = dimensions;
for (int i = 0; i < dimensions; i++) for (int k = 0; k < dimensions; k++)
vec->x[i] = x[i]; vec->x[k] = x[k];
} }
static void static void
@@ -277,8 +271,8 @@ HalfvecUpdateCenter(Pointer v, int dimensions, float *x)
SET_VARSIZE(vec, HALFVEC_SIZE(dimensions)); SET_VARSIZE(vec, HALFVEC_SIZE(dimensions));
vec->dim = dimensions; vec->dim = dimensions;
for (int i = 0; i < dimensions; i++) for (int k = 0; k < dimensions; k++)
vec->x[i] = Float4ToHalfUnchecked(x[i]); vec->x[k] = Float4ToHalfUnchecked(x[k]);
} }
static void static void
@@ -290,33 +284,29 @@ BitUpdateCenter(Pointer v, int dimensions, float *x)
SET_VARSIZE(vec, VARBITTOTALLEN(dimensions)); SET_VARSIZE(vec, VARBITTOTALLEN(dimensions));
VARBITLEN(vec) = dimensions; VARBITLEN(vec) = dimensions;
for (uint32 i = 0; i < VARBITBYTES(vec); i++) for (uint32 k = 0; k < VARBITBYTES(vec); k++)
nx[i] = 0; nx[k] = 0;
for (int i = 0; i < dimensions; i++) for (int k = 0; k < dimensions; k++)
nx[i / 8] |= (x[i] > 0.5 ? 1 : 0) << (7 - (i % 8)); nx[k / 8] |= (x[k] > 0.5 ? 1 : 0) << (7 - (k % 8));
} }
static void static void
VectorSumCenter(Pointer v, float *x) VectorSumCenter(Pointer v, float *x)
{ {
Vector *vec = (Vector *) v; Vector *vec = (Vector *) v;
int dim = vec->dim;
/* Auto-vectorized */ for (int k = 0; k < vec->dim; k++)
for (int i = 0; i < dim; i++) x[k] += vec->x[k];
x[i] += vec->x[i];
} }
static void static void
HalfvecSumCenter(Pointer v, float *x) HalfvecSumCenter(Pointer v, float *x)
{ {
HalfVector *vec = (HalfVector *) v; HalfVector *vec = (HalfVector *) v;
int dim = vec->dim;
/* Auto-vectorized on aarch64 */ for (int k = 0; k < vec->dim; k++)
for (int i = 0; i < dim; i++) x[k] += HalfToFloat4(vec->x[k]);
x[i] += HalfToFloat4(vec->x[i]);
} }
static void static void
@@ -324,8 +314,8 @@ BitSumCenter(Pointer v, float *x)
{ {
VarBit *vec = (VarBit *) v; VarBit *vec = (VarBit *) v;
for (int i = 0; i < VARBITLEN(vec); i++) for (int k = 0; k < VARBITLEN(vec); k++)
x[i] += (float) (((VARBITS(vec)[i / 8]) >> (7 - (i % 8))) & 0x01); x[k] += (float) (((VARBITS(vec)[k / 8]) >> (7 - (k % 8))) & 0x01);
} }
/* /*
@@ -365,7 +355,7 @@ ivfflat_halfvec_support(PG_FUNCTION_ARGS)
}; };
PG_RETURN_POINTER(&typeInfo); PG_RETURN_POINTER(&typeInfo);
} };
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_bit_support); FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_bit_support);
Datum Datum
@@ -380,4 +370,4 @@ ivfflat_bit_support(PG_FUNCTION_ARGS)
}; };
PG_RETURN_POINTER(&typeInfo); PG_RETURN_POINTER(&typeInfo);
} };

View File

@@ -1,16 +1,9 @@
#include "postgres.h" #include "postgres.h"
#include "access/genam.h"
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "access/itup.h"
#include "commands/vacuum.h" #include "commands/vacuum.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "utils/relcache.h"
#if PG_VERSION_NUM >= 180000
#define vacuum_delay_point() vacuum_delay_point(false)
#endif
/* /*
* Bulk delete tuples from the index * Bulk delete tuples from the index
@@ -33,7 +26,7 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
Page cpage; Page cpage;
OffsetNumber coffno; OffsetNumber coffno;
OffsetNumber cmaxoffno; OffsetNumber cmaxoffno;
BlockNumber listPages[MaxOffsetNumber]; BlockNumber startPages[MaxOffsetNumber];
ListInfo listInfo; ListInfo listInfo;
cbuf = ReadBuffer(index, blkno); cbuf = ReadBuffer(index, blkno);
@@ -47,7 +40,7 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
{ {
IvfflatList list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, coffno)); IvfflatList list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, coffno));
listPages[coffno - FirstOffsetNumber] = list->startPage; startPages[coffno - FirstOffsetNumber] = list->startPage;
} }
listInfo.blkno = blkno; listInfo.blkno = blkno;
@@ -57,7 +50,7 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
for (coffno = FirstOffsetNumber; coffno <= cmaxoffno; coffno = OffsetNumberNext(coffno)) for (coffno = FirstOffsetNumber; coffno <= cmaxoffno; coffno = OffsetNumberNext(coffno))
{ {
BlockNumber searchPage = listPages[coffno - FirstOffsetNumber]; BlockNumber searchPage = startPages[coffno - FirstOffsetNumber];
BlockNumber insertPage = InvalidBlockNumber; BlockNumber insertPage = InvalidBlockNumber;
/* Iterate over entry pages */ /* Iterate over entry pages */

View File

@@ -4,26 +4,23 @@
#include <math.h> #include <math.h>
#include "catalog/pg_type.h" #include "catalog/pg_type.h"
#include "common/shortest_dec.h" #include "common/string.h"
#include "fmgr.h" #include "fmgr.h"
#include "halfutils.h" #include "halfutils.h"
#include "halfvec.h" #include "halfvec.h"
#include "lib/stringinfo.h"
#include "libpq/pqformat.h" #include "libpq/pqformat.h"
#include "sparsevec.h" #include "sparsevec.h"
#include "utils/array.h" #include "utils/array.h"
#include "utils/builtins.h" #include "utils/builtins.h"
#include "utils/float.h"
#include "utils/fmgrprotos.h"
#include "utils/lsyscache.h" #include "utils/lsyscache.h"
#include "vector.h" #include "vector.h"
#if PG_VERSION_NUM >= 160000 #if PG_VERSION_NUM >= 120000
#include "varatt.h" #include "common/shortest_dec.h"
#endif #include "utils/float.h"
#else
#if PG_VERSION_NUM >= 170000 #include <float.h>
#include "parser/scansup.h" #include "utils/builtins.h"
#endif #endif
typedef struct SparseInputElement typedef struct SparseInputElement
@@ -159,9 +156,9 @@ InitSparseVector(int dim, int nnz)
return result; return result;
} }
#if PG_VERSION_NUM >= 170000 /*
#define sparsevec_isspace(ch) scanner_isspace(ch) * Check for whitespace, since array_isspace() is static
#else */
static inline bool static inline bool
sparsevec_isspace(char ch) sparsevec_isspace(char ch)
{ {
@@ -174,7 +171,6 @@ sparsevec_isspace(char ch)
return true; return true;
return false; return false;
} }
#endif
/* /*
* Compare indices * Compare indices
@@ -182,10 +178,10 @@ sparsevec_isspace(char ch)
static int static int
CompareIndices(const void *a, const void *b) CompareIndices(const void *a, const void *b)
{ {
if (((const SparseInputElement *) a)->index < ((const SparseInputElement *) b)->index) if (((SparseInputElement *) a)->index < ((SparseInputElement *) b)->index)
return -1; return -1;
if (((const SparseInputElement *) a)->index > ((const SparseInputElement *) b)->index) if (((SparseInputElement *) a)->index > ((SparseInputElement *) b)->index)
return 1; return 1;
return 0; return 0;

View File

@@ -16,20 +16,16 @@
#include "port.h" /* for strtof() */ #include "port.h" /* for strtof() */
#include "sparsevec.h" #include "sparsevec.h"
#include "utils/array.h" #include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h" #include "utils/float.h"
#include "utils/fmgrprotos.h"
#include "utils/lsyscache.h" #include "utils/lsyscache.h"
#include "utils/varbit.h" #include "utils/numeric.h"
#include "vector.h" #include "vector.h"
#if PG_VERSION_NUM >= 160000 #if PG_VERSION_NUM >= 160000
#include "varatt.h" #include "varatt.h"
#endif #endif
#if PG_VERSION_NUM >= 170000
#include "parser/scansup.h"
#endif
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1) #define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1)) #define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
@@ -39,11 +35,7 @@
#define VECTOR_TARGET_CLONES #define VECTOR_TARGET_CLONES
#endif #endif
#if PG_VERSION_NUM >= 180000
PG_MODULE_MAGIC_EXT(.name = "vector", .version = "0.8.3");
#else
PG_MODULE_MAGIC; PG_MODULE_MAGIC;
#endif
/* /*
* Initialize index options and variables * Initialize index options and variables
@@ -133,9 +125,9 @@ InitVector(int dim)
return result; return result;
} }
#if PG_VERSION_NUM >= 170000 /*
#define vector_isspace(ch) scanner_isspace(ch) * Check for whitespace, since array_isspace() is static
#else */
static inline bool static inline bool
vector_isspace(char ch) vector_isspace(char ch)
{ {
@@ -148,7 +140,6 @@ vector_isspace(char ch)
return true; return true;
return false; return false;
} }
#endif
/* /*
* Check state array * Check state array
@@ -929,13 +920,11 @@ vector_concat(PG_FUNCTION_ARGS)
CheckDim(dim); CheckDim(dim);
result = InitVector(dim); result = InitVector(dim);
/* Auto-vectorized */ for (int i = 0; i < a->dim; i++)
for (int i = 0, imax = a->dim; i < imax; i++)
result->x[i] = a->x[i]; result->x[i] = a->x[i];
/* Auto-vectorized */ for (int i = 0; i < b->dim; i++)
for (int i = 0, imax = b->dim, start = a->dim; i < imax; i++) result->x[i + a->dim] = b->x[i];
result->x[i + start] = b->x[i];
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
@@ -951,21 +940,8 @@ binary_quantize(PG_FUNCTION_ARGS)
float *ax = a->x; float *ax = a->x;
VarBit *result = InitBitVector(a->dim); VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result); unsigned char *rx = VARBITS(result);
int i = 0;
int count = (a->dim / 8) * 8;
/* Auto-vectorized */ for (int i = 0; i < a->dim; i++)
for (; i < count; i += 8)
{
unsigned char result_byte = 0;
for (int j = 0; j < 8; j++)
result_byte |= (ax[i + j] > 0) << (7 - j);
rx[i / 8] = result_byte;
}
for (; i < a->dim; i++)
rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8)); rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result); PG_RETURN_VARBIT_P(result);

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

@@ -6,7 +6,13 @@ use Test::More;
my $dim = 3; my $dim = 3;
my $array_sql = join(",", ('random()') x $dim); my @r = ();
for (1 .. $dim)
{
my $v = int(rand(1000)) + 1;
push(@r, "i % $v");
}
my $array_sql = join(", ", @r);
# Initialize node # Initialize node
my $node = PostgreSQL::Test::Cluster->new('node'); my $node = PostgreSQL::Test::Cluster->new('node');
@@ -17,20 +23,19 @@ $node->start;
$node->safe_psql("postgres", "CREATE EXTENSION vector;"); $node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));"); $node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
$node->safe_psql("postgres", $node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 100000) i;" "INSERT INTO tst SELECT i % 10, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
); );
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);"); $node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);");
# Get size # Get size
my $size = $node->safe_psql("postgres", "SELECT pg_total_relation_size('tst_v_idx');"); my $size = $node->safe_psql("postgres", "SELECT pg_total_relation_size('tst_v_idx');");
# Store values
$node->safe_psql("postgres", "CREATE TABLE tmp AS SELECT * FROM tst;");
# Delete all, vacuum, and insert same data # Delete all, vacuum, and insert same data
$node->safe_psql("postgres", "DELETE FROM tst;"); $node->safe_psql("postgres", "DELETE FROM tst;");
$node->safe_psql("postgres", "VACUUM tst;"); $node->safe_psql("postgres", "VACUUM tst;");
$node->safe_psql("postgres", "INSERT INTO tst SELECT * FROM tmp;"); $node->safe_psql("postgres",
"INSERT INTO tst SELECT i % 10, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
);
# Check size # Check size
my $new_size = $node->safe_psql("postgres", "SELECT pg_total_relation_size('tst_v_idx');"); my $new_size = $node->safe_psql("postgres", "SELECT pg_total_relation_size('tst_v_idx');");

View File

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

View File

@@ -41,7 +41,8 @@ my $c = int(rand() * $nc);
my $explain = $node->safe_psql("postgres", qq( my $explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit; EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit;
)); ));
like($explain, qr/Seq Scan/); # TODO Do not use index
like($explain, qr/Index Scan using idx/);
# Test attribute filtering with few rows removed # Test attribute filtering with few rows removed
$explain = $node->safe_psql("postgres", qq( $explain = $node->safe_psql("postgres", qq(
@@ -59,7 +60,8 @@ like($explain, qr/Index Scan using idx/);
$explain = $node->safe_psql("postgres", qq( $explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c < 1 ORDER BY v <-> '$query' LIMIT $limit; EXPLAIN ANALYZE SELECT i FROM tst WHERE c < 1 ORDER BY v <-> '$query' LIMIT $limit;
)); ));
like($explain, qr/Seq Scan/); # TODO Do not use index
like($explain, qr/Index Scan using idx/);
# Test attribute filtering with few rows removed like # Test attribute filtering with few rows removed like
$explain = $node->safe_psql("postgres", qq( $explain = $node->safe_psql("postgres", qq(

View File

@@ -17,11 +17,12 @@ $node->safe_psql("postgres", "CREATE EXTENSION vector;");
for my $dim (@dims) for my $dim (@dims)
{ {
my $array_sql = join(",", ('random()') x $dim); my $array_sql = join(",", ('random()') x $dim);
my $n = $dim == 384 ? 2000 : 1000;
# Create table and index # Create table and index
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));"); $node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
$node->safe_psql("postgres", $node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 2000) i;" "INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, $n) i;"
); );
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v vector_l2_ops);"); $node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v vector_l2_ops);");
$node->safe_psql("postgres", "ANALYZE tst;"); $node->safe_psql("postgres", "ANALYZE tst;");
@@ -39,21 +40,6 @@ for my $dim (@dims)
)); ));
like($explain, qr/Index Scan using idx/); like($explain, qr/Index Scan using idx/);
# 3x the rows are needed for distance filters
# since the planner uses DEFAULT_INEQ_SEL for the selectivity (should be 1)
# Recreate index for performance
$node->safe_psql("postgres", "DROP INDEX idx;");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(2001, 6000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v vector_l2_ops);");
$node->safe_psql("postgres", "ANALYZE tst;");
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' < 1 ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
$node->safe_psql("postgres", "DROP TABLE tst;"); $node->safe_psql("postgres", "DROP TABLE tst;");
} }

View File

@@ -39,11 +39,6 @@ for my $dim (@dims)
)); ));
like($explain, qr/Index Scan using idx/); like($explain, qr/Index Scan using idx/);
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' < 1 ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
$node->safe_psql("postgres", "DROP TABLE tst;"); $node->safe_psql("postgres", "DROP TABLE tst;");
} }

View File

@@ -26,26 +26,25 @@ $node->safe_psql("postgres", qq(
my $count = $node->safe_psql("postgres", qq( my $count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off; SET enable_seqscan = off;
SET hnsw.iterative_scan = relaxed_order; SET hnsw.streaming = on;
SET hnsw.max_scan_tuples = 100000; SET work_mem = '8MB';
SET hnsw.scan_mem_multiplier = 2;
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t; SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
)); ));
is($count, 10); is($count, 10);
foreach ((30000, 50000, 70000)) foreach ((30000, 50000, 70000))
{ {
my $max_tuples = $_; my $ef_stream = $_;
my $expected = $max_tuples / 10000; my $expected = $ef_stream / 10000;
my $sum = 0; my $sum = 0;
for my $i (1 .. 20) for my $i (1 .. 20)
{ {
$count = $node->safe_psql("postgres", qq( $count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off; SET enable_seqscan = off;
SET hnsw.iterative_scan = relaxed_order; SET hnsw.streaming = on;
SET hnsw.max_scan_tuples = $max_tuples; SET hnsw.ef_stream = $ef_stream;
SET hnsw.scan_mem_multiplier = 2; SET work_mem = '8MB';
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst WHERE i = $i) LIMIT 11) t; SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst WHERE i = $i) LIMIT 11) t;
)); ));
$sum += $count; $sum += $count;
@@ -56,4 +55,12 @@ foreach ((30000, 50000, 70000))
cmp_ok($avg, '<', $expected + 2); cmp_ok($avg, '<', $expected + 2);
} }
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.streaming = on;
SET work_mem = '2MB';
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
));
like($stderr, qr/hnsw index scan exceeded work_mem after \d+ tuples/);
done_testing(); done_testing();

View File

@@ -1,54 +0,0 @@
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
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4 PRIMARY KEY, v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);");
my $count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = 10;
SET ivfflat.iterative_scan = relaxed_order;
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
));
is($count, 10);
foreach ((30, 50, 70))
{
my $max_probes = $_;
my $expected = $max_probes / 10;
my $sum = 0;
for my $i (1 .. 20)
{
$count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = 10;
SET ivfflat.iterative_scan = relaxed_order;
SET ivfflat.max_probes = $max_probes;
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst WHERE i = $i) LIMIT 11) t;
));
$sum += $count;
}
my $avg = $sum / 20;
cmp_ok($avg, '>', $expected - 2);
cmp_ok($avg, '<', $expected + 2);
}
done_testing();

View File

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

View File

@@ -1,125 +0,0 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my @cs = (100, 1000);
sub test_recall
{
my ($c, $probes, $min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
SET ivfflat.iterative_scan = relaxed_order;
EXPLAIN ANALYZE SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan using idx on tst/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
SET ivfflat.iterative_scan = relaxed_order;
SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, "$operator $c");
}
# 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(3));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 100000) i;"
);
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "[$r1,$r2,$r3]");
}
# Check each index type
my @operators = ("<->", "<=>");
my @opclasses = ("vector_l2_ops", "vector_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING ivfflat (v $opclass);");
foreach (@cs)
{
my $c = $_;
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
WITH top AS (
SELECT v $operator '$_' AS distance FROM tst WHERE i % $c = 0 ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator '$_') <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
if ($c == 100)
{
test_recall($c, 1, 0.57, $operator);
test_recall($c, 10, 0.98, $operator);
}
else
{
if ($operator eq "<->")
{
test_recall($c, 1, 0.80, $operator);
}
else
{
test_recall($c, 1, 0.88, $operator);
}
}
}
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

View File

@@ -1,29 +0,0 @@
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();

View File

@@ -1,4 +1,4 @@
comment = 'vector data type and ivfflat and hnsw access methods' comment = 'vector data type and ivfflat and hnsw access methods'
default_version = '0.8.3' default_version = '0.7.4'
module_pathname = '$libdir/vector' module_pathname = '$libdir/vector'
relocatable = true relocatable = true