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99 Commits

Author SHA1 Message Date
Andrew Kane
5425dd2357 Fixed warning 2024-04-03 15:17:52 -07:00
Andrew Kane
7ca7a64dbb Added subvector function for sparsevec 2024-04-03 15:10:06 -07:00
Andrew Kane
aaa2d644ce Added quantize_binary and subvector functions for halfvec 2024-04-03 14:53:03 -07:00
Andrew Kane
253acbccf4 Updated readme [skip ci] 2024-04-03 11:05:55 -07:00
Andrew Kane
060d299e4b Improved error message for out of range elements 2024-04-03 10:12:17 -07:00
Andrew Kane
d7354a86a8 Updated readme [skip ci] 2024-04-02 14:45:25 -07:00
Andrew Kane
daba71694b Updated readme [skip ci] 2024-04-02 14:39:14 -07:00
Andrew Kane
506dd2b44a Updated changelog [skip ci] 2024-04-02 14:33:57 -07:00
Andrew Kane
bcf41f5f66 Fixed flaky test [skip ci] 2024-04-02 14:31:05 -07:00
Andrew Kane
abac7a3f77 Added sparsevec type 2024-04-02 14:25:09 -07:00
Andrew Kane
32a502c838 Added halfvec type 2024-04-02 13:55:45 -07:00
Andrew Kane
1134e52762 Renamed regression tests [skip ci] 2024-04-02 13:33:44 -07:00
Andrew Kane
3ef632e042 Added Mac arm64 to CI [skip ci] 2024-04-02 12:48:19 -07:00
Andrew Kane
e2a527ffda Fixed flaky test [skip ci] 2024-04-02 12:23:48 -07:00
Andrew Kane
835f010257 Fixed missing header for Postgres 12 2024-04-02 12:17:41 -07:00
Andrew Kane
d6044dd423 Added subvector function 2024-04-02 12:13:04 -07:00
Andrew Kane
c75634a03c Fixed type check [skip ci] 2024-04-01 22:31:02 -07:00
Andrew Kane
ab7b2ed39e Updated comparison operators to support vectors with different dimensions - #451 2024-04-01 22:12:06 -07:00
Andrew Kane
499b6bc2c9 Fixed regression test list for Windows [skip ci] 2024-04-01 21:32:28 -07:00
Andrew Kane
741c6a8a7b Renamed tests [skip ci] 2024-04-01 20:51:21 -07:00
Andrew Kane
1c82bdd932 Updated comments [skip ci] 2024-04-01 20:33:12 -07:00
Andrew Kane
94a444f029 Added support for bit vectors to HNSW 2024-04-01 20:30:55 -07:00
Andrew Kane
7ee9074a9c Updated comment [skip ci] 2024-03-31 18:33:26 -07:00
Andrew Kane
2f2f3631a8 Improved vector_out code 2024-03-31 09:55:07 -07:00
Andrew Kane
4b22851bbd Added more vector input tests [skip ci] 2024-03-30 10:17:55 -07:00
Andrew Kane
3acdbf99e8 Added casting to distance functions in tests [skip ci] 2024-03-30 09:05:15 -07:00
Andrew Kane
11ea3d8483 Updated SQL comments [skip ci] 2024-03-30 08:29:01 -07:00
Andrew Kane
2c48e3edc2 Mark type-specific code 2024-03-29 14:01:48 -07:00
Andrew Kane
7d63bb4b98 Fixed flaky test [skip ci] 2024-03-29 11:00:16 -07:00
Andrew Kane
de410a2915 Use variable for max dimemsions [skip ci] 2024-03-29 10:57:16 -07:00
Andrew Kane
64aa99aa31 Added todo [skip ci] 2024-03-29 10:56:24 -07:00
Andrew Kane
997fa167da Removed vector-specific code from HNSW 2024-03-29 10:50:06 -07:00
Andrew Kane
67eec4edbf Improved tuning section [skip ci] 2024-03-27 22:04:28 -07:00
Andrew Kane
396090d8e0 Improved code [skip ci] 2024-03-27 21:38:22 -07:00
Andrew Kane
ba18942fcf Removed normvec from IVFFlat for simplicity (no difference in performance) 2024-03-27 16:41:17 -07:00
Andrew Kane
8e59455c3c Removed normvec for simplicity (no difference in performance) 2024-03-27 16:33:11 -07:00
Andrew Kane
bd50e3067d Updated readme [skip ci] 2024-03-27 14:14:49 -07:00
Andrew Kane
af9d4ad659 Updated readme [skip ci] 2024-03-27 14:12:08 -07:00
Andrew Kane
08abb63cbe Added notes about NULL vectors [skip ci] 2024-03-27 11:50:37 -07:00
Andrew Kane
06b8556a49 Revert "Updated readme [skip ci]"
This reverts commit 3f674c9994.
2024-03-25 23:33:46 -07:00
Andrew Kane
3f674c9994 Updated readme [skip ci] 2024-03-25 23:33:17 -07:00
Andrew Kane
31e41b3ba9 Added FAQ about binary vectors [skip ci] 2024-03-24 11:07:34 -07:00
Andrew Kane
903a925662 Improved type modifier tests 2024-03-21 17:31:08 -07:00
Andrew Kane
96ff19be44 Version bump to 0.6.2 [skip ci] 2024-03-18 10:21:04 -07:00
Andrew Kane
6c969bebad Updated changelog [skip ci] 2024-03-18 10:11:45 -07:00
Andrew Kane
b64a1482d9 Moved example [skip ci] 2024-03-16 15:20:26 -07:00
Andrew Kane
a5f2d70bc2 Use temp directory for installation instructions on Windows [skip ci] 2024-03-16 12:02:45 -07:00
Andrew Kane
f3fcb5e005 Moved installation notes for Windows [skip ci] 2024-03-16 11:47:18 -07:00
Andrew Kane
3a6e0afb9c Added installation notes for Windows [skip ci] 2024-03-16 11:35:55 -07:00
Andrew Kane
183d50bdbd Added note about creating indexes concurrently [skip ci] 2024-03-16 10:45:09 -07:00
Andrew Kane
bd776fee68 Updated readme [skip ci] 2024-03-16 10:44:45 -07:00
Andrew Kane
d30b113e4b Updated readme [skip ci] 2024-03-15 21:54:58 -07:00
Andrew Kane
fd3200f718 Updated readme [skip ci] 2024-03-15 21:47:57 -07:00
Andrew Kane
02c815d876 Added docs on tuning, monitoring, and scaling [skip ci] 2024-03-15 19:00:49 -07:00
Andrew Kane
4b2a7cc49d Improved performance section [skip ci] 2024-03-15 17:54:14 -07:00
Andrew Kane
da0ff998e9 Updated readme [skip ci] 2024-03-15 14:23:56 -07:00
Andrew Kane
cb36e24289 Improved portability section [skip ci] 2024-03-15 14:23:04 -07:00
Andrew Kane
b1d0d4c7a3 Improved troubleshooting docs [skip ci] 2024-03-15 14:01:24 -07:00
Andrew Kane
1dc6514b66 Updated comment [skip ci] 2024-03-15 12:38:14 -07:00
Andrew Kane
6c53f7ca02 Updated comment [skip ci] 2024-03-15 12:37:47 -07:00
Heikki Linnakangas
0d35a14198 Fix compiler warnings in strict C99 mode (#487)
Redefining a typedef is a C11 feature:

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

I got these warnings when I built PostgreSQL with "CC=clang
CFLAGS=-std=gnu99"; other similar options would surely produce the
warnings too.
2024-03-12 02:02:33 -07:00
Andrew Kane
3ea2ce89be Reduced lock contention with parallel HNSW index builds 2024-03-11 20:16:55 -07:00
Andrew Kane
62350b1589 Added note about IVFFlat results [skip ci] 2024-03-06 00:29:55 -08:00
Andrew Kane
dd57309281 Added section about HNSW results - #480 [skip ci] 2024-03-06 00:27:50 -08:00
Andrew Kane
c6ddf62a29 Version bump to 0.6.1 [skip ci] 2024-03-04 10:27:59 -08:00
Andrew Kane
801be04d8b Updated CI [skip ci] 2024-03-02 17:06:11 -08:00
Andrew Kane
587e9ba97c Added link to bulk loading example [skip ci] 2024-02-29 21:25:11 -08:00
Andrew Kane
d57047a935 Moved COPY example and added FORMAT [skip ci] 2024-02-29 20:35:01 -08:00
oneturkmen
f1db1f17e3 Update README.md (#472) 2024-02-29 20:27:53 -08:00
Andrew Kane
2f48c0fac4 Updated changelog [skip ci] 2024-02-29 18:10:19 -08:00
Andrew Kane
84a8aa8176 Added note about HNSW build time [skip ci] 2024-02-29 16:25:58 -08:00
Andrew Kane
f64ebbef50 Added OPTFLAGS to readme [skip ci] 2024-02-29 16:15:22 -08:00
Andrew Kane
ac8156509b Updated vector operators for <= and >= 2024-02-29 15:43:29 -08:00
Andrew Kane
82bf69b479 Fixed vector subtraction being marked as commutative - fixes #475 2024-02-29 14:36:18 -08:00
Andrew Kane
4be2f57916 Updated license year [skip ci] 2024-02-29 13:44:58 -08:00
Andrew Kane
91e3d2905f Fixed sort function for Postgres 12 2024-02-28 16:26:41 -08:00
Andrew Kane
fe2406564f Replaced pairing heap with array in SelectNeighbors - closes #447
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2024-02-28 15:47:26 -08:00
Andrew Kane
fa52511eaa Fixed closer caching for Postgres 12 2024-02-28 15:44:38 -08:00
Andrew Kane
447ef4d27a Specify Postgres version for Valgrind [skip ci] 2024-02-28 14:16:48 -08:00
Andrew Kane
b36cd22ccc Enable assertions on CI 2024-02-28 14:15:34 -08:00
Andrew Kane
b447ae4989 Avoid base address for relptr for Postgres < 14.5 2024-02-28 14:10:14 -08:00
Andrew Kane
efed873a3e Revert "Replaced pairing heap with array in SelectNeighbors - closes #447"
This reverts commit 14b278dec9.
2024-02-28 11:33:14 -08:00
Andrew Kane
14b278dec9 Replaced pairing heap with array in SelectNeighbors - closes #447
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2024-02-28 11:25:12 -08:00
Andrew Kane
133a728e48 Updated changelog [skip ci] 2024-02-20 16:38:05 -08:00
Andrew Kane
ca10cbaa7d Revert "Remove offsethash"
This reverts commit 1cbd204f52.
2024-02-20 16:07:32 -08:00
Andrew Kane
eb29019a14 Revert "Eliminate a few HnswPtrAccess invocations"
This reverts commit 334c386a45.
2024-02-20 16:07:21 -08:00
Heikki Linnakangas
334c386a45 Eliminate a few HnswPtrAccess invocations
HnswPtrAccess() is pretty cheap, but it stills seems worthwhile to
avoid repeated calls in the hot paths when it can be easily avoided.
2024-02-19 14:13:18 +02:00
Heikki Linnakangas
1cbd204f52 Remove offsethash
The original motivation was to eliminate the superfluous HnswPtrAccess
call from AddToVisited. The caller has to call HnswPtrAccess() anyway,
so it makes sense to pass the HnswElement rather than HnswElementPtr
to AddToVisited(). But then I realized that we can use the
pointer-variant even with shared memory, because the visited-hash is
backend-private, and the addresses where the elements are mapped to in
shared memory are stable within the backend.
2024-02-19 14:12:26 +02:00
Andrew Kane
5ba62fca84 Fixed crash with shared_preload_libraries - fixes #460 2024-02-14 17:13:30 -08:00
Andrew Kane
22cb2a3fe7 Simplified Docker tasks [skip ci] 2024-02-07 12:03:33 -08:00
Andrew Kane
72b144906a Added Valgrind to CI 2024-02-07 09:43:01 -08:00
Andrew Kane
a618c1bc78 Updated port name [skip ci] 2024-02-06 12:43:20 -08:00
Andrew Kane
f43cd0ed98 Improved type [skip ci] 2024-02-05 19:38:52 -08:00
Andrew Kane
51df640961 Added instructions for pkg [skip ci] 2024-02-05 17:01:36 -08:00
Andrew Kane
2716a223a6 Fixed error with ANALYZE and vectors with different dimensions - fixes #451 2024-02-02 10:47:48 -08:00
Andrew Kane
3697043898 Added note about vacuuming - closes #450 [skip ci] 2024-01-31 14:35:27 -08:00
Andrew Kane
c22740962c Added note for Docker [skip ci] 2024-01-29 15:33:29 -08:00
Andrew Kane
a55ecf3281 Updated changelog [skip ci] 2024-01-29 11:20:33 -08:00
Andrew Kane
fecdd5794e Updated readme [skip ci] 2024-01-29 10:57:54 -08:00
81 changed files with 5053 additions and 441 deletions

View File

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

View File

@@ -1,10 +1,31 @@
## 0.7.0 (unreleased)
- Added `halfvec` type
- Added `sparsevec` type
- Added support for `bit` vectors to HNSW
- Added `hamming_distance` function
- Added `jaccard_distance` function
- Added `quantize_binary` function
- Added `subvector` function
- Updated comparison operators to support vectors with different dimensions
## 0.6.2 (2024-03-18)
- Reduced lock contention with parallel HNSW index builds
## 0.6.1 (2024-03-04)
- Fixed error with `ANALYZE` and vectors with different dimensions
- Fixed segmentation fault with `shared_preload_libraries`
- Fixed vector subtraction being marked as commutative
## 0.6.0 (2024-01-29)
If upgrading with Postgres 12 or Docker, see [these notes](https://github.com/pgvector/pgvector#060).
- Changed storage for vector from `extended` to `external`
- Added support for parallel index builds for HNSW
- Added validation for GUC parameters
- Changed storage for vector from `extended` to `external`
- Improved performance of HNSW
- Reduced memory usage for HNSW index builds
- Reduced WAL generation for HNSW index builds

View File

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

View File

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

View File

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

View File

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

290
README.md
View File

@@ -16,19 +16,19 @@ Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recove
### Linux and Mac
Compile and install the extension (supports Postgres 11+)
Compile and install the extension (supports Postgres 12+)
```sh
cd /tmp
git clone --branch v0.6.0 https://github.com/pgvector/pgvector.git
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo
```
See the [installation notes](#installation-notes) if you run into issues
See the [installation notes](#installation-notes---linux-and-mac) if you run into issues
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [pkg](#pkg), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
### Windows
@@ -44,12 +44,15 @@ Then use `nmake` to build:
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16"
git clone --branch v0.6.0 https://github.com/pgvector/pgvector.git
cd %TEMP%
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
```
See the [installation notes](#installation-notes---windows) if you run into issues
You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
## Getting Started
@@ -102,6 +105,12 @@ Insert vectors
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
```
Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py))
```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
```
Upsert vectors
```sql
@@ -212,7 +221,24 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
```
Vectors with up to 2,000 dimensions can be indexed.
Hamming distance - unreleased
```sql
CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
```
Jaccard distance - unreleased
```sql
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
```
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (unreleased)
- `bit` - up to 64,000 dimensions (unreleased)
- `sparsevec` - up to 1,000 non-zero elements (unreleased)
### Index Options
@@ -264,6 +290,8 @@ HINT: Increase maintenance_work_mem to speed up builds.
Note: Do not set `maintenance_work_mem` so high that it exhausts the memory on the server
Like other index types, its faster to create an index after loading your initial data
Starting with 0.6.0, you can also speed up index creation by increasing the number of parallel workers (2 by default)
```sql
@@ -315,7 +343,9 @@ Cosine distance
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
```
Vectors with up to 2,000 dimensions can be indexed.
Supported types are:
- `vector` - up to 2,000 dimensions
### Query Options
@@ -402,13 +432,51 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python
## Performance
### Tuning
Use a tool like [PgTune](https://pgtune.leopard.in.ua/) to set initial values for Postgres server parameters. For instance, `shared_buffers` should typically be 25% of the servers memory. You can find the config file with:
```sql
SHOW config_file;
```
And check individual settings with:
```sql
SHOW shared_buffers;
```
Be sure to restart Postgres for changes to take effect.
### Loading
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py)).
```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
```
Add any indexes *after* loading the initial data for best performance.
### Indexing
See index build time for [HNSW](#index-build-time) and [IVFFlat](#index-build-time-1).
In production environments, create indexes concurrently to avoid blocking writes.
```sql
CREATE INDEX CONCURRENTLY ...
```
### Querying
Use `EXPLAIN ANALYZE` to debug performance.
```sql
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
### Exact Search
#### Exact Search
To speed up queries without an index, increase `max_parallel_workers_per_gather`.
@@ -422,7 +490,7 @@ If vectors are normalized to length 1 (like [OpenAI embeddings](https://platform
SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5;
```
### Approximate Search
#### Approximate Search
To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
@@ -430,6 +498,50 @@ To speed up queries with an IVFFlat index, increase the number of inverted lists
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 1000);
```
### Vacuuming
Vacuuming can take a while for HNSW indexes. Speed it up by reindexing first.
```sql
REINDEX INDEX CONCURRENTLY index_name;
VACUUM table_name;
```
## Monitoring
Monitor performance with [pg_stat_statements](https://www.postgresql.org/docs/current/pgstatstatements.html) (be sure to add it to `shared_preload_libraries`).
```sql
CREATE EXTENSION pg_stat_statements;
```
Get the most time-consuming queries with:
```sql
SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_time_ms,
ROUND((total_plan_time + total_exec_time) / 60000) AS total_time_min
FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20;
```
Note: Replace `total_plan_time + total_exec_time` with `total_time` for Postgres < 13
Monitor recall by comparing results from approximate search with exact search.
```sql
BEGIN;
SET LOCAL enable_indexscan = off; -- use exact search
SELECT ...
COMMIT;
```
## Scaling
Scale pgvector the same way you scale Postgres.
Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus.py)).
## Languages
Use pgvector from any language with a Postgres client. You can even generate and store vectors in one language and query them in another.
@@ -523,6 +635,18 @@ and query with:
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
```
#### Are binary vectors supported?
You can store binary vectors and perform exact nearest neighbor search by Hamming distance in Postgres without an extension ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py)).
```tsql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES (B'000'), (B'111');
SELECT * FROM items ORDER BY bit_count(embedding # B'101') LIMIT 5;
```
Indexing is not currently supported.
#### Do indexes need to fit into memory?
No, but like other index types, youll likely see better performance if they do. You can get the size of an index with:
@@ -535,7 +659,17 @@ SELECT pg_size_pretty(pg_relation_size('index_name'));
#### Why isnt a query using an index?
The cost estimation in pgvector < 0.4.3 does not always work well with the planner. You can encourage the planner to use an index for a query with:
The query needs to have an `ORDER BY` and `LIMIT`, and the `ORDER BY` must be the result of a distance operator, not an expression.
```sql
-- index
ORDER BY embedding <=> '[3,1,2]' LIMIT 5;
-- no index
ORDER BY 1 - (embedding <=> '[3,1,2]') DESC LIMIT 5;
```
You can encourage the planner to use an index for a query with:
```sql
BEGIN;
@@ -564,6 +698,12 @@ or choose to store vectors inline:
ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
```
#### Why are there less results for a query after adding an HNSW index?
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead.
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
#### Why are there less results for a query after adding an IVFFlat index?
The index was likely created with too little data for the number of lists. Drop the index until the table has more data.
@@ -572,11 +712,20 @@ The index was likely created with too little data for the number of lists. Drop
DROP INDEX index_name;
```
Results can also be limited by the number of probes (`ivfflat.probes`).
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
## Reference
- [Vector](#vector-type)
- [Halfvec](#halfvec-type)
- [Bit](#bit-type)
- [Sparsevec](#sparsevec-type)
### Vector Type
Each vector takes `4 * dimensions + 8` bytes of storage. Each element is a single precision floating-point number (like the `real` type in Postgres), and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Vectors can have up to 16,000 dimensions.
Each vector takes `4 * dimensions + 8` bytes of storage. Each element is a single-precision floating-point number (like the `real` type in Postgres), and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Vectors can have up to 16,000 dimensions.
### Vector Operators
@@ -597,17 +746,81 @@ cosine_distance(vector, vector) → double precision | cosine distance |
inner_product(vector, vector) → double precision | inner product |
l2_distance(vector, vector) → double precision | Euclidean distance |
l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
quantize_binary(vector) → bit | quantize | unreleased
subvector(vector, integer, integer) → vector | subvector | unreleased
vector_dims(vector) → integer | number of dimensions |
vector_norm(vector) → double precision | Euclidean norm |
### Aggregate Functions
### Vector Aggregate Functions
Function | Description | Added
--- | --- | ---
avg(vector) → vector | average |
sum(vector) → vector | sum | 0.5.0
## Installation Notes
### Halfvec Type
Each half vector takes `2 * dimensions + 8` bytes of storage. Each element is a half-precision floating-point number, and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Half vectors can have up to 16,000 dimensions.
### Halfvec Operators
Operator | Description | Added
--- | --- | ---
<-> | Euclidean distance | unreleased
<#> | negative inner product | unreleased
<=> | cosine distance | unreleased
### Halfvec Functions
Function | Description | Added
--- | --- | ---
cosine_distance(halfvec, halfvec) → double precision | cosine distance | unreleased
inner_product(halfvec, halfvec) → double precision | inner product | unreleased
l2_distance(halfvec, halfvec) → double precision | Euclidean distance | unreleased
l1_distance(halfvec, halfvec) → double precision | taxicab distance | unreleased
quantize_binary(halfvec) → bit | quantize | unreleased
subvector(halfvec, integer, integer) → halfvec | subvector | unreleased
### Bit Type
Each bit vector takes `dimensions / 8 + 8` bytes of storage. See the [Postgres docs](https://www.postgresql.org/docs/current/datatype-bit.html) for more info.
### Bit Operators
Operator | Description | Added
--- | --- | ---
<~> | Hamming distance | unreleased
<%> | Jaccard distance | unreleased
### Bit Functions
Function | Description | Added
--- | --- | ---
hamming_distance(bit, bit) → double precision | Hamming distance | unreleased
jaccard_distance(bit, bit) → double precision | Jaccard distance | unreleased
### Sparsevec Type
Each sparse vector takes `8 * non-zero elements + 16` bytes of storage. Each element is a single-precision floating-point number, and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Sparse vectors can have up to 100,000 dimensions.
### Sparsevec Operators
Operator | Description | Added
--- | --- | ---
<-> | Euclidean distance | unreleased
<#> | negative inner product | unreleased
<=> | cosine distance | unreleased
### Sparsevec Functions
Function | Description | Added
--- | --- | ---
cosine_distance(sparsevec, sparsevec) → double precision | cosine distance | unreleased
inner_product(sparsevec, sparsevec) → double precision | inner product | unreleased
l2_distance(sparsevec, sparsevec) → double precision | Euclidean distance | unreleased
l1_distance(sparsevec, sparsevec) → double precision | taxicab distance | unreleased
## Installation Notes - Linux and Mac
### Postgres Location
@@ -647,6 +860,26 @@ Note: Replace `16` with your Postgres server version
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, reinstall Xcode Command Line Tools.
### Portability
By default, pgvector compiles with `-march=native` on some platforms for best performance. However, this can lead to `Illegal instruction` errors if trying to run the compiled extension on a different machine.
To compile for portability, use:
```sh
make OPTFLAGS=""
```
## Installation Notes - Windows
### Missing Header
If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct.
### Permissions
If installation fails with `Access is denied`, re-run the installation instructions as an administrator.
## Additional Installation Methods
### Docker
@@ -657,12 +890,12 @@ Get the [Docker image](https://hub.docker.com/r/pgvector/pgvector) with:
docker pull pgvector/pgvector:pg16
```
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (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).
You can also build the image manually:
```sh
git clone --branch v0.6.0 https://github.com/pgvector/pgvector.git
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector
docker build --build-arg PG_MAJOR=16 -t myuser/pgvector .
```
@@ -707,6 +940,21 @@ sudo dnf install pgvector_16
Note: Replace `16` with your Postgres server version
### pkg
Install the FreeBSD package with:
```sh
pkg install postgresql15-pg_vector
```
or the port with:
```sh
cd /usr/ports/databases/pgvector
make install
```
### conda-forge
With Conda Postgres, install from [conda-forge](https://anaconda.org/conda-forge/pgvector) with:
@@ -816,6 +1064,12 @@ make installcheck REGRESS=functions # regression test
make prove_installcheck PROVE_TESTS=test/t/001_ivfflat_wal.pl # TAP test
```
To enable assertions:
```sh
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
```
To enable benchmarking:
```sh
@@ -828,12 +1082,6 @@ To show memory usage:
make clean && PG_CFLAGS="-DHNSW_MEMORY -DIVFFLAT_MEMORY" make && make install
```
To enable assertions:
```sh
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
```
To get k-means metrics:
```sh

View File

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

View File

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

View File

@@ -0,0 +1,262 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.0'" to load this file. \quit
CREATE FUNCTION quantize_binary(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(vector, int, int) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
);
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit);
CREATE TYPE halfvec;
CREATE FUNCTION halfvec_in(cstring, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_out(halfvec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_recv(internal, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_send(halfvec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE halfvec (
INPUT = halfvec_in,
OUTPUT = halfvec_out,
TYPMOD_IN = halfvec_typmod_in,
RECEIVE = halfvec_recv,
SEND = halfvec_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_norm(halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION quantize_binary(halfvec) RETURNS bit
AS 'MODULE_PATHNAME', 'halfvec_quantize_binary' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(halfvec, int, int) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(integer[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(real[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(double precision[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(numeric[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_float4(halfvec, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (halfvec AS halfvec)
WITH FUNCTION halfvec(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS real[])
WITH FUNCTION halfvec_to_float4(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (integer[] AS halfvec)
WITH FUNCTION array_to_halfvec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS halfvec)
WITH FUNCTION array_to_halfvec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS halfvec)
WITH FUNCTION array_to_halfvec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS halfvec)
WITH FUNCTION array_to_halfvec(numeric[], integer, boolean) AS ASSIGNMENT;
CREATE OPERATOR <-> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 halfvec_norm(halfvec);
CREATE FUNCTION halfvec_to_vector(halfvec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_halfvec(vector, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (halfvec AS vector)
WITH FUNCTION halfvec_to_vector(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS halfvec)
WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT;
CREATE TYPE sparsevec;
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE sparsevec (
INPUT = sparsevec_in,
OUTPUT = sparsevec_out,
TYPMOD_IN = sparsevec_typmod_in,
RECEIVE = sparsevec_recv,
SEND = sparsevec_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_norm(sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(sparsevec, int, int) RETURNS sparsevec
AS 'MODULE_PATHNAME', 'sparsevec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (sparsevec AS sparsevec)
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS vector)
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS sparsevec)
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
CREATE OPERATOR <-> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR CLASS sparsevec_l2_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_ip_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_cosine_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 2 sparsevec_norm(sparsevec);

View File

@@ -1,7 +1,7 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "CREATE EXTENSION vector" to load this file. \quit
-- type
-- vector type
CREATE TYPE vector;
@@ -29,7 +29,7 @@ CREATE TYPE vector (
STORAGE = external
);
-- functions
-- vector functions
CREATE FUNCTION l2_distance(vector, vector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -58,7 +58,13 @@ CREATE FUNCTION vector_sub(vector, vector) RETURNS vector
CREATE FUNCTION vector_mul(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- private functions
CREATE FUNCTION quantize_binary(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(vector, int, int) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- vector private functions
CREATE FUNCTION vector_lt(vector, vector) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -99,7 +105,7 @@ CREATE FUNCTION vector_avg(double precision[]) RETURNS vector
CREATE FUNCTION vector_combine(double precision[], double precision[]) RETURNS double precision[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- aggregates
-- vector aggregates
CREATE AGGREGATE avg(vector) (
SFUNC = vector_accum,
@@ -117,7 +123,7 @@ CREATE AGGREGATE sum(vector) (
PARALLEL = SAFE
);
-- cast functions
-- vector cast functions
CREATE FUNCTION vector(vector, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -137,7 +143,7 @@ CREATE FUNCTION array_to_vector(numeric[], integer, boolean) RETURNS vector
CREATE FUNCTION vector_to_float4(vector, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- casts
-- vector casts
CREATE CAST (vector AS vector)
WITH FUNCTION vector(vector, integer, boolean) AS IMPLICIT;
@@ -157,7 +163,7 @@ CREATE CAST (double precision[] AS vector)
CREATE CAST (numeric[] AS vector)
WITH FUNCTION array_to_vector(numeric[], integer, boolean) AS ASSIGNMENT;
-- operators
-- vector operators
CREATE OPERATOR <-> (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l2_distance,
@@ -180,8 +186,7 @@ CREATE OPERATOR + (
);
CREATE OPERATOR - (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub,
COMMUTATOR = -
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub
);
CREATE OPERATOR * (
@@ -195,11 +200,10 @@ CREATE OPERATOR < (
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
);
-- should use scalarlesel and scalarlejoinsel, but not supported in Postgres < 11
CREATE OPERATOR <= (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_le,
COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
CREATE OPERATOR = (
@@ -214,11 +218,10 @@ CREATE OPERATOR <> (
RESTRICT = eqsel, JOIN = eqjoinsel
);
-- should use scalargesel and scalargejoinsel, but not supported in Postgres < 11
CREATE OPERATOR >= (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_ge,
COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
RESTRICT = scalargesel, JOIN = scalargejoinsel
);
CREATE OPERATOR > (
@@ -243,7 +246,7 @@ CREATE ACCESS METHOD hnsw TYPE INDEX HANDLER hnswhandler;
COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method';
-- opclasses
-- vector opclasses
CREATE OPERATOR CLASS vector_ops
DEFAULT FOR TYPE vector USING btree AS
@@ -290,3 +293,289 @@ CREATE OPERATOR CLASS vector_cosine_ops
OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_negative_inner_product(vector, vector),
FUNCTION 2 vector_norm(vector);
-- bit functions
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
);
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit);
-- halfvec type
CREATE TYPE halfvec;
CREATE FUNCTION halfvec_in(cstring, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_out(halfvec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_recv(internal, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_send(halfvec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE halfvec (
INPUT = halfvec_in,
OUTPUT = halfvec_out,
TYPMOD_IN = halfvec_typmod_in,
RECEIVE = halfvec_recv,
SEND = halfvec_send,
STORAGE = external
);
-- halfvec functions
CREATE FUNCTION l2_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_norm(halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION quantize_binary(halfvec) RETURNS bit
AS 'MODULE_PATHNAME', 'halfvec_quantize_binary' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(halfvec, int, int) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec private functions
CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec cast functions
CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(integer[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(real[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(double precision[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(numeric[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_float4(halfvec, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec casts
CREATE CAST (halfvec AS halfvec)
WITH FUNCTION halfvec(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS real[])
WITH FUNCTION halfvec_to_float4(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (integer[] AS halfvec)
WITH FUNCTION array_to_halfvec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS halfvec)
WITH FUNCTION array_to_halfvec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS halfvec)
WITH FUNCTION array_to_halfvec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS halfvec)
WITH FUNCTION array_to_halfvec(numeric[], integer, boolean) AS ASSIGNMENT;
-- halfvec operators
CREATE OPERATOR <-> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
-- halfvec opclasses
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 halfvec_norm(halfvec);
-- extension casts
CREATE FUNCTION halfvec_to_vector(halfvec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_halfvec(vector, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (halfvec AS vector)
WITH FUNCTION halfvec_to_vector(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS halfvec)
WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT;
--- sparsevec type
CREATE TYPE sparsevec;
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE sparsevec (
INPUT = sparsevec_in,
OUTPUT = sparsevec_out,
TYPMOD_IN = sparsevec_typmod_in,
RECEIVE = sparsevec_recv,
SEND = sparsevec_send,
STORAGE = external
);
-- sparsevec functions
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_norm(sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(sparsevec, int, int) RETURNS sparsevec
AS 'MODULE_PATHNAME', 'sparsevec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec private functions
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec cast functions
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec casts
CREATE CAST (sparsevec AS sparsevec)
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS vector)
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS sparsevec)
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
-- sparsevec operators
CREATE OPERATOR <-> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
-- sparsevec opclasses
CREATE OPERATOR CLASS sparsevec_l2_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_ip_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_cosine_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 2 sparsevec_norm(sparsevec);

90
src/bitvector.c Normal file
View File

@@ -0,0 +1,90 @@
#include "postgres.h"
#include "bitvector.h"
#include "port/pg_bitutils.h"
#include "utils/varbit.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/*
* Allocate and initialize a new bit vector
*/
VarBit *
InitBitVector(int dim)
{
VarBit *result;
int size;
size = VARBITTOTALLEN(dim);
result = (VarBit *) palloc0(size);
SET_VARSIZE(result, size);
VARBITLEN(result) = dim;
return result;
}
/*
* Ensure same dimensions
*/
static inline void
CheckDims(VarBit *a, VarBit *b)
{
if (VARBITLEN(a) != VARBITLEN(b))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different bit lengths %u and %u", VARBITLEN(a), VARBITLEN(b))));
}
/*
* Get the Hamming distance between two bit vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(hamming_distance);
Datum
hamming_distance(PG_FUNCTION_ARGS)
{
VarBit *a = PG_GETARG_VARBIT_P(0);
VarBit *b = PG_GETARG_VARBIT_P(1);
unsigned char *ax = VARBITS(a);
unsigned char *bx = VARBITS(b);
uint64 distance = 0;
CheckDims(a, b);
/* TODO Improve performance */
for (uint32 i = 0; i < VARBITBYTES(a); i++)
distance += pg_number_of_ones[ax[i] ^ bx[i]];
PG_RETURN_FLOAT8((double) distance);
}
/*
* Get the Jaccard distance between two bit vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(jaccard_distance);
Datum
jaccard_distance(PG_FUNCTION_ARGS)
{
VarBit *a = PG_GETARG_VARBIT_P(0);
VarBit *b = PG_GETARG_VARBIT_P(1);
unsigned char *ax = VARBITS(a);
unsigned char *bx = VARBITS(b);
uint64 ab = 0;
uint64 aa;
uint64 bb;
CheckDims(a, b);
/* TODO Improve performance */
for (uint32 i = 0; i < VARBITBYTES(a); i++)
ab += pg_number_of_ones[ax[i] & bx[i]];
if (ab == 0)
PG_RETURN_FLOAT8(1);
aa = pg_popcount((char *) ax, VARBITBYTES(a));
bb = pg_popcount((char *) bx, VARBITBYTES(b));
PG_RETURN_FLOAT8(1 - (ab / ((double) (aa + bb - ab))));
}

8
src/bitvector.h Normal file
View File

@@ -0,0 +1,8 @@
#ifndef BITVECTOR_H
#define BITVECTOR_H
#include "utils/varbit.h"
VarBit *InitBitVector(int dim);
#endif

1020
src/halfvec.c Normal file

File diff suppressed because it is too large Load Diff

43
src/halfvec.h Normal file
View File

@@ -0,0 +1,43 @@
#ifndef HALFVEC_H
#define HALFVEC_H
#define __STDC_WANT_IEC_60559_TYPES_EXT__
#include <float.h>
#include "vector.h"
#ifdef __FLT16_MAX__
#define FLT16_SUPPORT
#endif
#ifdef FLT16_SUPPORT
#define half _Float16
#define HALF_MAX FLT16_MAX
#else
/* TODO #pragma message("")? */
#define half uint16
#define HALF_MAX 65504
#endif
#define HALFVEC_MAX_DIM VECTOR_MAX_DIM
#define HALFVEC_SIZE(_dim) (offsetof(HalfVector, x) + sizeof(half)*(_dim))
#define DatumGetHalfVector(x) ((HalfVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_HALFVEC_P(x) DatumGetHalfVector(PG_GETARG_DATUM(x))
#define PG_RETURN_HALFVEC_P(x) PG_RETURN_POINTER(x)
typedef struct HalfVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int16 dim; /* number of dimensions */
int16 unused;
half x[FLEXIBLE_ARRAY_MEMBER];
} HalfVector;
HalfVector *InitHalfVector(int dim);
float HalfToFloat4(half num);
half Float4ToHalf(float num);
half Float4ToHalfUnchecked(float num);
#endif

View File

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

View File

@@ -17,6 +17,7 @@
#endif
#define HNSW_MAX_DIM 2000
#define HNSW_MAX_NNZ 1000
/* Support functions */
#define HNSW_DISTANCE_PROC 1
@@ -55,6 +56,14 @@
#define HNSW_UPDATE_ENTRY_GREATER 1
#define HNSW_UPDATE_ENTRY_ALWAYS 2
typedef enum HnswType
{
HNSW_TYPE_VECTOR,
HNSW_TYPE_HALFVEC,
HNSW_TYPE_BIT,
HNSW_TYPE_SPARSEVEC
} HnswType;
/* Build phases */
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
#define PROGRESS_HNSW_PHASE_LOAD 2
@@ -80,7 +89,7 @@
#if PG_VERSION_NUM < 130000
#define list_delete_last(list) list_truncate(list, list_length(list) - 1)
#define list_sort(list, cmp) list_qsort(list, cmp)
#define list_sort(list, cmp) ((list) = list_qsort(list, cmp))
#endif
#define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
@@ -129,7 +138,7 @@ HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr)
HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
HnswPtrDeclare(char, DatumRelptr, DatumPtr);
typedef struct HnswElementData
struct HnswElementData
{
HnswElementPtr next;
ItemPointerData heaptids[HNSW_HEAPTIDS];
@@ -144,7 +153,7 @@ typedef struct HnswElementData
BlockNumber neighborPage;
DatumPtr value;
LWLock lock;
} HnswElementData;
};
typedef HnswElementData * HnswElement;
@@ -155,12 +164,12 @@ typedef struct HnswCandidate
bool closer;
} HnswCandidate;
typedef struct HnswNeighborArray
struct HnswNeighborArray
{
int length;
bool closerSet;
HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
} HnswNeighborArray;
};
typedef struct HnswPairingHeapNode
{
@@ -185,6 +194,7 @@ typedef struct HnswGraph
/* Entry state */
LWLock entryLock;
LWLock entryWaitLock;
HnswElementPtr entryPoint;
/* Allocations state */
@@ -241,6 +251,7 @@ typedef struct HnswBuildState
Relation index;
IndexInfo *indexInfo;
ForkNumber forkNum;
HnswType type;
/* Settings */
int dimensions;
@@ -261,7 +272,6 @@ typedef struct HnswBuildState
HnswGraph *graph;
double ml;
int maxLevel;
Vector *normvec;
/* Memory */
MemoryContext graphCtx;
@@ -366,7 +376,9 @@ typedef struct HnswVacuumState
int HnswGetM(Relation index);
int HnswGetEfConstruction(Relation index);
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
HnswType HnswGetType(Relation index);
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type);
void HnswCheckValue(Datum value, HnswType type);
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
void HnswInitPage(Buffer buf, Page page);
void HnswInit(void);
@@ -389,6 +401,7 @@ void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation i
void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element);
void HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
void HnswLoadNeighbors(HnswElement element, Relation index, int m);
void HnswInitLockTranche(void);
PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);
/* Index access methods */

View File

@@ -44,6 +44,7 @@
#include "access/xact.h"
#include "access/xloginsert.h"
#include "catalog/index.h"
#include "catalog/pg_type_d.h"
#include "commands/progress.h"
#include "hnsw.h"
#include "miscadmin.h"
@@ -176,7 +177,7 @@ CreateGraphPages(HnswBuildState * buildstate)
Size etupSize;
Size ntupSize;
Size combinedSize;
void *valuePtr = HnswPtrAccess(base, element->value);
Pointer valuePtr = HnswPtrAccess(base, element->value);
/* Update iterator */
iter = element->next;
@@ -431,10 +432,15 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
HnswGraph *graph = buildstate->graph;
HnswElement entryPoint;
LWLock *entryLock = &graph->entryLock;
LWLock *entryWaitLock = &graph->entryWaitLock;
int efConstruction = buildstate->efConstruction;
int m = buildstate->m;
char *base = buildstate->hnswarea;
/* Wait if another process needs exclusive lock on entry lock */
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
LWLockRelease(entryWaitLock);
/* Get entry point */
LWLockAcquire(entryLock, LW_SHARED);
entryPoint = HnswPtrAccess(base, graph->entryPoint);
@@ -445,8 +451,10 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
/* Release shared lock */
LWLockRelease(entryLock);
/* Get exclusive lock */
/* Tell other processes to wait and get exclusive lock */
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
LWLockAcquire(entryLock, LW_EXCLUSIVE);
LWLockRelease(entryWaitLock);
/* Get latest entry point after lock is acquired */
entryPoint = HnswPtrAccess(base, graph->entryPoint);
@@ -479,10 +487,13 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
/* Detoast once for all calls */
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Check value */
HnswCheckValue(value, buildstate->type);
/* Normalize if needed */
if (buildstate->normprocinfo != NULL)
{
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->type))
return false;
}
@@ -601,6 +612,9 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
static void
InitGraph(HnswGraph * graph, char *base, long memoryTotal)
{
/* Initialize the lock tranche if needed */
HnswInitLockTranche();
HnswPtrStore(base, graph->head, (HnswElement) NULL);
HnswPtrStore(base, graph->entryPoint, (HnswElement) NULL);
graph->memoryUsed = 0;
@@ -609,6 +623,7 @@ InitGraph(HnswGraph * graph, char *base, long memoryTotal)
graph->indtuples = 0;
SpinLockInit(&graph->lock);
LWLockInitialize(&graph->entryLock, hnsw_lock_tranche_id);
LWLockInitialize(&graph->entryWaitLock, hnsw_lock_tranche_id);
LWLockInitialize(&graph->allocatorLock, hnsw_lock_tranche_id);
LWLockInitialize(&graph->flushLock, hnsw_lock_tranche_id);
}
@@ -654,27 +669,50 @@ HnswSharedMemoryAlloc(Size size, void *state)
return chunk;
}
/*
* Get max dimensions
*/
static int
GetMaxDimensions(HnswType type)
{
int maxDimensions = HNSW_MAX_DIM;
if (type == HNSW_TYPE_HALFVEC)
maxDimensions *= 2;
else if (type == HNSW_TYPE_BIT)
maxDimensions *= 32;
else if (type == HNSW_TYPE_SPARSEVEC)
maxDimensions = INT_MAX;
return maxDimensions;
}
/*
* Initialize the build state
*/
static void
InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum)
{
int maxDimensions;
buildstate->heap = heap;
buildstate->index = index;
buildstate->indexInfo = indexInfo;
buildstate->forkNum = forkNum;
buildstate->type = HnswGetType(index);
buildstate->m = HnswGetM(index);
buildstate->efConstruction = HnswGetEfConstruction(index);
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
maxDimensions = GetMaxDimensions(buildstate->type);
/* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0)
elog(ERROR, "column does not have dimensions");
if (buildstate->dimensions > HNSW_MAX_DIM)
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", HNSW_MAX_DIM);
if (buildstate->dimensions > maxDimensions)
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", maxDimensions);
if (buildstate->efConstruction < 2 * buildstate->m)
elog(ERROR, "ef_construction must be greater than or equal to 2 * m");
@@ -692,9 +730,6 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->ml = HnswGetMl(buildstate->m);
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
/* Reuse for each tuple */
buildstate->normvec = InitVector(buildstate->dimensions);
buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext,
"Hnsw build graph context",
#if PG_VERSION_NUM >= 150000
@@ -718,7 +753,6 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
static void
FreeBuildState(HnswBuildState * buildstate)
{
pfree(buildstate->normvec);
MemoryContextDelete(buildstate->graphCtx);
MemoryContextDelete(buildstate->tmpCtx);
}
@@ -974,6 +1008,14 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
/* Report less than allocated so never fails */
InitGraph(&hnswshared->graphData, hnswarea, esthnswarea - 1024 * 1024);
/*
* Avoid base address for relptr for Postgres < 14.5
* https://github.com/postgres/postgres/commit/7201cd18627afc64850537806da7f22150d1a83b
*/
#if PG_VERSION_NUM < 140005
hnswshared->graphData.memoryUsed += MAXALIGN(1);
#endif
shm_toc_insert(pcxt->toc, PARALLEL_KEY_HNSW_SHARED, hnswshared);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_HNSW_AREA, hnswarea);

View File

@@ -614,15 +614,19 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
Datum value;
FmgrInfo *normprocinfo;
Oid collation = index->rd_indcollation[0];
HnswType type = HnswGetType(index);
/* Detoast once for all calls */
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Check value */
HnswCheckValue(value, type);
/* Normalize if needed */
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
if (normprocinfo != NULL)
{
if (!HnswNormValue(normprocinfo, collation, &value, NULL))
if (!HnswNormValue(normprocinfo, collation, &value, type))
return;
}

View File

@@ -40,29 +40,6 @@ GetScanItems(IndexScanDesc scan, Datum q)
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
}
/*
* Get dimensions from metapage
*/
static int
GetDimensions(Relation index)
{
Buffer buf;
Page page;
HnswMetaPage metap;
int dimensions;
buf = ReadBuffer(index, HNSW_METAPAGE_BLKNO);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
metap = HnswPageGetMeta(page);
dimensions = metap->dimensions;
UnlockReleaseBuffer(buf);
return dimensions;
}
/*
* Get scan value
*/
@@ -73,7 +50,7 @@ GetScanValue(IndexScanDesc scan)
Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
value = PointerGetDatum(NULL);
else
{
value = scan->orderByData->sk_argument;
@@ -84,7 +61,7 @@ GetScanValue(IndexScanDesc scan)
/* Fine if normalization fails */
if (so->normprocinfo != NULL)
HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
HnswNormValue(so->normprocinfo, so->collation, &value, HnswGetType(scan->indexRelation));
}
return value;

View File

@@ -3,12 +3,17 @@
#include <math.h>
#include "access/generic_xlog.h"
#include "catalog/pg_type.h"
#include "catalog/pg_type_d.h"
#include "halfvec.h"
#include "hnsw.h"
#include "lib/pairingheap.h"
#include "sparsevec.h"
#include "storage/bufmgr.h"
#include "utils/datum.h"
#include "utils/memdebug.h"
#include "utils/rel.h"
#include "utils/syscache.h"
#include "vector.h"
#if PG_VERSION_NUM >= 130000
@@ -149,6 +154,39 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
return index_getprocinfo(index, 1, procnum);
}
/*
* Get type
*/
HnswType
HnswGetType(Relation index)
{
Oid typid = TupleDescAttr(index->rd_att, 0)->atttypid;
HeapTuple tuple;
Form_pg_type type;
int result;
if (typid == BITOID || typid == VARBITOID)
return HNSW_TYPE_BIT;
tuple = SearchSysCache1(TYPEOID, ObjectIdGetDatum(typid));
if (!HeapTupleIsValid(tuple))
elog(ERROR, "cache lookup failed for type %u", typid);
type = (Form_pg_type) GETSTRUCT(tuple);
if (strcmp(NameStr(type->typname), "vector") == 0)
result = HNSW_TYPE_VECTOR;
else if (strcmp(NameStr(type->typname), "halfvec") == 0)
result = HNSW_TYPE_HALFVEC;
else if (strcmp(NameStr(type->typname), "sparsevec") == 0)
result = HNSW_TYPE_SPARSEVEC;
else
elog(ERROR, "Unsupported type");
ReleaseSysCache(tuple);
return result;
}
/*
* Divide by the norm
*
@@ -158,21 +196,53 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
* if it's different than the original value
*/
bool
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type)
{
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0)
{
Vector *v = DatumGetVector(*value);
/* TODO Remove vector-specific code */
if (type == HNSW_TYPE_VECTOR)
{
Vector *v = DatumGetVector(*value);
Vector *result = InitVector(v->dim);
if (result == NULL)
result = InitVector(v->dim);
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
*value = PointerGetDatum(result);
}
else if (type == HNSW_TYPE_HALFVEC)
{
HalfVector *v = DatumGetHalfVector(*value);
HalfVector *result = InitHalfVector(v->dim);
*value = PointerGetDatum(result);
for (int i = 0; i < v->dim; i++)
{
/* TODO Fix */
result->x[i] = Float4ToHalfUnchecked(HalfToFloat4(v->x[i]) / norm);
}
*value = PointerGetDatum(result);
}
else if (type == HNSW_TYPE_SPARSEVEC)
{
SparseVector *v = DatumGetSparseVector(*value);
SparseVector *result = InitSparseVector(v->dim, v->nnz);
float *vx = SPARSEVEC_VALUES(v);
float *rx = SPARSEVEC_VALUES(result);
for (int i = 0; i < v->nnz; i++)
{
result->indices[i] = v->indices[i];
rx[i] = vx[i] / norm;
}
*value = PointerGetDatum(result);
}
else
elog(ERROR, "Unsupported type");
return true;
}
@@ -180,6 +250,21 @@ HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
return false;
}
/*
* Check if a value can be indexed
*/
void
HnswCheckValue(Datum value, HnswType type)
{
if (type == HNSW_TYPE_SPARSEVEC)
{
SparseVector *vec = DatumGetSparseVector(value);
if (vec->nnz > HNSW_MAX_NNZ)
elog(ERROR, "sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ);
}
}
/*
* New buffer
*/
@@ -575,7 +660,12 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
/* Calculate distance */
if (distance != NULL)
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
{
if (DatumGetPointer(*q) == NULL)
*distance = 0;
else
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
}
UnlockReleaseBuffer(buf);
}
@@ -860,12 +950,15 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistances(const ListCell *a, const ListCell *b)
{
HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b);
#else
CompareCandidateDistances(const void *a, const void *b)
#endif
{
HnswCandidate *hca = lfirst((ListCell *) a);
HnswCandidate *hcb = lfirst((ListCell *) b);
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif
if (hca->distance < hcb->distance)
return 1;
@@ -888,12 +981,15 @@ CompareCandidateDistances(const void *a, const void *b)
static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b)
{
HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b);
#else
CompareCandidateDistancesOffset(const void *a, const void *b)
#endif
{
HnswCandidate *hca = lfirst((ListCell *) a);
HnswCandidate *hcb = lfirst((ListCell *) b);
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif
if (hca->distance < hcb->distance)
return 1;
@@ -952,7 +1048,9 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
{
List *r = NIL;
List *w = list_copy(c);
pairingheap *wd;
HnswCandidate **wd;
int wdlen = 0;
int wdoff = 0;
HnswNeighborArray *neighbors = HnswGetNeighbors(base, e2, lc);
bool mustCalculate = !neighbors->closerSet;
List *added = NIL;
@@ -961,7 +1059,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
if (list_length(w) <= lm)
return w;
wd = pairingheap_allocate(CompareNearestCandidates, NULL);
wd = palloc(sizeof(HnswCandidate *) * list_length(w));
/* Ensure order of candidates is deterministic for closer caching */
if (sortCandidates)
@@ -1027,21 +1125,21 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
if (e->closer)
r = lappend(r, e);
else
pairingheap_add(wd, &(CreatePairingHeapNode(e)->ph_node));
wd[wdlen++] = e;
}
/* Cached value can only be used in future if sorted deterministically */
neighbors->closerSet = sortCandidates;
/* Keep pruned connections */
while (!pairingheap_is_empty(wd) && list_length(r) < lm)
r = lappend(r, ((HnswPairingHeapNode *) pairingheap_remove_first(wd))->inner);
while (wdoff < wdlen && list_length(r) < lm)
r = lappend(r, wd[wdoff++]);
/* Return pruned for update connections */
if (pruned != NULL)
{
if (!pairingheap_is_empty(wd))
*pruned = ((HnswPairingHeapNode *) pairingheap_first(wd))->inner;
if (wdoff < wdlen)
*pruned = wd[wdoff];
else
*pruned = linitial(w);
}

View File

@@ -57,7 +57,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
*/
if (buildstate->kmeansnormprocinfo != NULL)
{
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->normvec))
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value))
return;
}
@@ -105,7 +105,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
/* Add sample */
AddSample(values, state);
AddSample(values, buildstate);
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
@@ -153,7 +153,7 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
/* Normalize if needed */
if (buildstate->normprocinfo != NULL)
{
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value))
return;
}
@@ -356,9 +356,6 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions);
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
/* Reuse for each tuple */
buildstate->normvec = InitVector(buildstate->dimensions);
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat build temporary context",
ALLOCSET_DEFAULT_SIZES);
@@ -380,7 +377,6 @@ FreeBuildState(IvfflatBuildState * buildstate)
{
VectorArrayFree(buildstate->centers);
pfree(buildstate->listInfo);
pfree(buildstate->normvec);
#ifdef IVFFLAT_KMEANS_DEBUG
pfree(buildstate->listSums);

View File

@@ -172,7 +172,6 @@ typedef struct IvfflatBuildState
VectorArray samples;
VectorArray centers;
ListInfo *listInfo;
Vector *normvec;
#ifdef IVFFLAT_KMEANS_DEBUG
double inertia;
@@ -267,7 +266,7 @@ void VectorArrayFree(VectorArray arr);
void PrintVectorArray(char *msg, VectorArray arr);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value);
int IvfflatGetLists(Relation index);
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);

View File

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

View File

@@ -293,7 +293,7 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
/* Fine if normalization fails */
if (so->normprocinfo != NULL)
IvfflatNormValue(so->normprocinfo, so->collation, &value, NULL);
IvfflatNormValue(so->normprocinfo, so->collation, &value);
}
IvfflatBench("GetScanLists", GetScanLists(scan, value));

View File

@@ -75,16 +75,14 @@ IvfflatOptionalProcInfo(Relation index, uint16 procnum)
* if it's different than the original value
*/
bool
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value)
{
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0)
{
Vector *v = DatumGetVector(*value);
if (result == NULL)
result = InitVector(v->dim);
Vector *result = InitVector(v->dim);
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;

830
src/sparsevec.c Normal file
View File

@@ -0,0 +1,830 @@
#include "postgres.h"
#include <limits.h>
#include <math.h>
#include "fmgr.h"
#include "libpq/pqformat.h"
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "vector.h"
#if PG_VERSION_NUM >= 120000
#include "common/shortest_dec.h"
#include "utils/float.h"
#else
#include <float.h>
#include "utils/builtins.h"
#endif
/*
* Ensure same dimensions
*/
static inline void
CheckDims(SparseVector * a, SparseVector * b)
{
if (a->dim != b->dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different sparsevec dimensions %d and %d", a->dim, b->dim)));
}
/*
* Ensure expected dimensions
*/
static inline void
CheckExpectedDim(int32 typmod, int dim)
{
if (typmod != -1 && typmod != dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected %d dimensions, not %d", typmod, dim)));
}
/*
* Ensure valid dimensions
*/
static inline void
CheckDim(int dim)
{
if (dim < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("sparsevec must have at least 1 dimension")));
if (dim > SPARSEVEC_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d dimensions", SPARSEVEC_MAX_DIM)));
}
/*
* Ensure valid nnz
*/
static inline void
CheckNnz(int nnz, int dim)
{
if (nnz < 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("sparsevec must have at least one element")));
if (nnz > dim)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more elements than dimensions")));
}
/*
* Ensure valid index
*/
static inline void
CheckIndex(int32 *indices, int i, int dim)
{
int32 index = indices[i];
if (index < 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("index must not be negative")));
if (index >= dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("index must be less than dimensions")));
if (i > 0)
{
if (index < indices[i - 1])
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("indexes must be in ascending order")));
if (index == indices[i - 1])
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("indexes must not contain duplicates")));
}
}
/*
* Ensure finite element
*/
static inline void
CheckElement(float value)
{
if (isnan(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("NaN not allowed in sparsevec")));
if (isinf(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("infinite value not allowed in sparsevec")));
}
/*
* Allocate and initialize a new sparse vector
*/
SparseVector *
InitSparseVector(int dim, int nnz)
{
SparseVector *result;
int size;
size = SPARSEVEC_SIZE(nnz);
result = (SparseVector *) palloc0(size);
SET_VARSIZE(result, size);
result->dim = dim;
result->nnz = nnz;
return result;
}
/*
* Check for whitespace, since array_isspace() is static
*/
static inline bool
sparsevec_isspace(char ch)
{
if (ch == ' ' ||
ch == '\t' ||
ch == '\n' ||
ch == '\r' ||
ch == '\v' ||
ch == '\f')
return true;
return false;
}
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_in);
Datum
sparsevec_in(PG_FUNCTION_ARGS)
{
char *lit = PG_GETARG_CSTRING(0);
int32 typmod = PG_GETARG_INT32(2);
int dim;
char *pt;
char *stringEnd;
SparseVector *result;
float *rvalues;
char *litcopy = pstrdup(lit);
char *str = litcopy;
int32 *indices;
float *values;
int maxNnz;
int nnz = 0;
maxNnz = 1;
pt = str;
while (*pt != '\0')
{
if (*pt == ',')
maxNnz++;
pt++;
}
indices = palloc(maxNnz * sizeof(int32));
values = palloc(maxNnz * sizeof(float));
while (sparsevec_isspace(*str))
str++;
if (*str != '{')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed sparsevec literal: \"%s\"", lit),
errdetail("Vector contents must start with \"{\".")));
str++;
pt = strtok(str, ",");
stringEnd = pt;
while (pt != NULL && *stringEnd != '}')
{
long index;
float value;
/* TODO Better error */
if (nnz == maxNnz)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("ran out of buffer: \"%s\"", lit)));
while (sparsevec_isspace(*pt))
pt++;
/* Check for empty string like float4in */
if (*pt == '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
/* Use similar logic as int2vectorin */
errno = 0;
index = strtol(pt, &stringEnd, 10);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
if (errno == ERANGE || index < 0 || index > INT_MAX)
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("index \"%ld\" is out of range for type sparsevec", index)));
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
while (sparsevec_isspace(*stringEnd))
stringEnd++;
if (*stringEnd != ':')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
stringEnd++;
while (sparsevec_isspace(*stringEnd))
stringEnd++;
errno = 0;
pt = stringEnd;
value = strtof(pt, &stringEnd);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
/* Check for range error like float4in */
if (errno == ERANGE && (value == 0 || isinf(value)))
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type sparsevec", pt)));
/* TODO Decide whether to store zero values */
if (value != 0)
{
indices[nnz] = index;
values[nnz] = value;
nnz++;
}
if (*stringEnd != '\0' && *stringEnd != '}')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
pt = strtok(NULL, ",");
}
if (stringEnd == NULL || *stringEnd != '}')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed sparsevec literal: \"%s\"", lit),
errdetail("Unexpected end of input.")));
stringEnd++;
if (*stringEnd != '/')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed sparsevec literal: \"%s\"", lit),
errdetail("Unexpected end of input.")));
stringEnd++;
/* Use similar logic as int2vectorin */
errno = 0;
pt = stringEnd;
dim = strtol(pt, &stringEnd, 10);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
/* Only whitespace is allowed after the closing brace */
while (sparsevec_isspace(*stringEnd))
stringEnd++;
if (*stringEnd != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed sparsevec literal: \"%s\"", lit),
errdetail("Junk after closing.")));
pfree(litcopy);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitSparseVector(dim, nnz);
rvalues = SPARSEVEC_VALUES(result);
for (int i = 0; i < nnz; i++)
{
result->indices[i] = indices[i];
rvalues[i] = values[i];
CheckIndex(result->indices, i, dim);
CheckElement(rvalues[i]);
}
PG_RETURN_POINTER(result);
}
#define AppendChar(ptr, c) (*(ptr)++ = (c))
#define AppendFloat(ptr, f) ((ptr) += float_to_shortest_decimal_bufn((f), (ptr)))
#if PG_VERSION_NUM >= 140000
#define AppendInt(ptr, i) ((ptr) += pg_ltoa((i), (ptr)))
#else
#define AppendInt(ptr, i) \
do { \
pg_ltoa(i, ptr); \
while (*ptr != '\0') \
ptr++; \
} while (0)
#endif
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_out);
Datum
sparsevec_out(PG_FUNCTION_ARGS)
{
SparseVector *sparsevec = PG_GETARG_SPARSEVEC_P(0);
float *values = SPARSEVEC_VALUES(sparsevec);
char *buf;
char *ptr;
/*
* Need:
*
* nnz * 10 bytes for index (positive integer)
*
* nnz bytes for :
*
* nnz * (FLOAT_SHORTEST_DECIMAL_LEN - 1) bytes for
* float_to_shortest_decimal_bufn
*
* nnz - 1 bytes for ,
*
* 10 bytes for dimensions
*
* 4 bytes for {, }, /, and \0
*/
buf = (char *) palloc((11 + FLOAT_SHORTEST_DECIMAL_LEN) * sparsevec->nnz + 13);
ptr = buf;
AppendChar(ptr, '{');
for (int i = 0; i < sparsevec->nnz; i++)
{
if (i > 0)
AppendChar(ptr, ',');
AppendInt(ptr, sparsevec->indices[i]);
AppendChar(ptr, ':');
AppendFloat(ptr, values[i]);
}
AppendChar(ptr, '}');
AppendChar(ptr, '/');
AppendInt(ptr, sparsevec->dim);
*ptr = '\0';
PG_FREE_IF_COPY(sparsevec, 0);
PG_RETURN_CSTRING(buf);
}
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_typmod_in);
Datum
sparsevec_typmod_in(PG_FUNCTION_ARGS)
{
ArrayType *ta = PG_GETARG_ARRAYTYPE_P(0);
int32 *tl;
int n;
tl = ArrayGetIntegerTypmods(ta, &n);
if (n != 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("invalid type modifier")));
if (*tl < 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type sparsevec must be at least 1")));
if (*tl > SPARSEVEC_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type sparsevec cannot exceed %d", SPARSEVEC_MAX_DIM)));
PG_RETURN_INT32(*tl);
}
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_recv);
Datum
sparsevec_recv(PG_FUNCTION_ARGS)
{
StringInfo buf = (StringInfo) PG_GETARG_POINTER(0);
int32 typmod = PG_GETARG_INT32(2);
SparseVector *result;
int32 dim;
int32 nnz;
int32 unused;
float *values;
dim = pq_getmsgint(buf, sizeof(int32));
nnz = pq_getmsgint(buf, sizeof(int32));
unused = pq_getmsgint(buf, sizeof(int32));
CheckDim(dim);
CheckNnz(nnz, dim);
CheckExpectedDim(typmod, dim);
if (unused != 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected unused to be 0, not %d", unused)));
result = InitSparseVector(dim, nnz);
values = SPARSEVEC_VALUES(result);
for (int i = 0; i < nnz; i++)
{
result->indices[i] = pq_getmsgint(buf, sizeof(int32));
CheckIndex(result->indices, i, dim);
}
for (int i = 0; i < nnz; i++)
{
values[i] = pq_getmsgfloat4(buf);
CheckElement(values[i]);
}
PG_RETURN_POINTER(result);
}
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_send);
Datum
sparsevec_send(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
float *values = SPARSEVEC_VALUES(svec);
StringInfoData buf;
pq_begintypsend(&buf);
pq_sendint(&buf, svec->dim, sizeof(int32));
pq_sendint(&buf, svec->nnz, sizeof(int32));
pq_sendint(&buf, svec->unused, sizeof(int32));
for (int i = 0; i < svec->nnz; i++)
pq_sendint(&buf, svec->indices[i], sizeof(int32));
for (int i = 0; i < svec->nnz; i++)
pq_sendfloat4(&buf, values[i]);
PG_RETURN_BYTEA_P(pq_endtypsend(&buf));
}
/*
* Convert sparse vector to sparse vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec);
Datum
sparsevec(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
CheckExpectedDim(typmod, svec->dim);
PG_RETURN_POINTER(svec);
}
/*
* Convert dense vector to sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_sparsevec);
Datum
vector_to_sparsevec(PG_FUNCTION_ARGS)
{
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
SparseVector *result;
int dim = vec->dim;
int nnz = 0;
float *values;
int j = 0;
CheckDim(dim);
CheckExpectedDim(typmod, dim);
for (int i = 0; i < dim; i++)
{
if (vec->x[i] != 0)
nnz++;
}
result = InitSparseVector(dim, nnz);
values = SPARSEVEC_VALUES(result);
for (int i = 0; i < dim; i++)
{
if (vec->x[i] != 0)
{
/* Safety check */
if (j == nnz)
elog(ERROR, "safety check failed");
result->indices[j] = i;
values[j] = vec->x[i];
j++;
}
}
PG_RETURN_POINTER(result);
}
/*
* Get the L2 squared distance between sparse vectors
*/
static double
l2_distance_squared_internal(SparseVector * a, SparseVector * b)
{
float *ax = SPARSEVEC_VALUES(a);
float *bx = SPARSEVEC_VALUES(b);
double distance = 0.0;
int bpos = 0;
for (int i = 0; i < a->nnz; i++)
{
int ai = a->indices[i];
int bi = -1;
for (int j = bpos; j < b->nnz; j++)
{
bi = b->indices[j];
if (ai == bi)
{
double diff = ax[i] - bx[j];
distance += diff * diff;
}
else if (ai > bi)
distance += bx[j] * bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
if (ai != bi)
distance += ax[i] * ax[i];
}
for (int j = bpos; j < b->nnz; j++)
distance += bx[j] * bx[j];
return distance;
}
/*
* Get the L2 distance between sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_distance);
Datum
sparsevec_l2_distance(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(sqrt(l2_distance_squared_internal(a, b)));
}
/*
* Get the L2 squared distance between sparse vectors
* This saves a sqrt calculation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_squared_distance);
Datum
sparsevec_l2_squared_distance(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(l2_distance_squared_internal(a, b));
}
/*
* Get the inner product of two sparse vectors
*/
static double
inner_product_internal(SparseVector * a, SparseVector * b)
{
float *ax = SPARSEVEC_VALUES(a);
float *bx = SPARSEVEC_VALUES(b);
double distance = 0.0;
int bpos = 0;
for (int i = 0; i < a->nnz; i++)
{
int ai = a->indices[i];
for (int j = bpos; j < b->nnz; j++)
{
int bi = b->indices[j];
/* Only update when the same index */
if (ai == bi)
distance += ax[i] * bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
}
return distance;
}
/*
* Get the inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_inner_product);
Datum
sparsevec_inner_product(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(inner_product_internal(a, b));
}
/*
* Get the negative inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_negative_inner_product);
Datum
sparsevec_negative_inner_product(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(-inner_product_internal(a, b));
}
/*
* Get the cosine distance between two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_cosine_distance);
Datum
sparsevec_cosine_distance(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
float *ax = SPARSEVEC_VALUES(a);
float *bx = SPARSEVEC_VALUES(b);
float norma = 0.0;
float normb = 0.0;
double similarity;
CheckDims(a, b);
similarity = inner_product_internal(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->nnz; i++)
norma += ax[i] * ax[i];
/* Auto-vectorized */
for (int i = 0; i < b->nnz; i++)
normb += bx[i] * bx[i];
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
similarity /= sqrt((double) norma * (double) normb);
#ifdef _MSC_VER
/* /fp:fast may not propagate NaN */
if (isnan(similarity))
PG_RETURN_FLOAT8(NAN);
#endif
/* Keep in range */
if (similarity > 1)
similarity = 1.0;
else if (similarity < -1)
similarity = -1.0;
PG_RETURN_FLOAT8(1.0 - similarity);
}
/*
* Get the L2 norm of a sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_norm);
Datum
sparsevec_norm(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
float *ax = SPARSEVEC_VALUES(a);
double norm = 0.0;
/* Auto-vectorized */
for (int i = 0; i < a->nnz; i++)
norm += (double) ax[i] * (double) ax[i];
PG_RETURN_FLOAT8(sqrt(norm));
}
/*
* Get a subvector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_subvector);
Datum
sparsevec_subvector(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
int32 start = PG_GETARG_INT32(1);
int32 count = PG_GETARG_INT32(2);
int32 end = start + count;
float *ax = SPARSEVEC_VALUES(a);
SparseVector *result;
float *rx;
int dim;
int nnz = 0;
int startIndex;
/* Indexing starts at 1, like substring */
if (start < 1)
start = 1;
if (end > a->dim)
end = a->dim + 1;
dim = end - start;
CheckDim(dim);
for (startIndex = 0; startIndex < a->nnz; startIndex++)
{
if (a->indices[startIndex] >= start - 1)
break;
}
for (int i = startIndex; i < a->nnz; i++)
{
if (a->indices[i] < end - 1)
nnz++;
}
result = InitSparseVector(dim, nnz);
rx = SPARSEVEC_VALUES(result);
for (int i = 0; i < nnz; i++)
{
result->indices[i] = a->indices[startIndex + i];
rx[i] = ax[startIndex + i];
}
PG_RETURN_POINTER(result);
}

24
src/sparsevec.h Normal file
View File

@@ -0,0 +1,24 @@
#ifndef SPARSEVEC_H
#define SPARSEVEC_H
#define SPARSEVEC_MAX_DIM 100000
/* Ensure values are aligned */
#define SPARSEVEC_SIZE(_nnz) (offsetof(SparseVector, indices) + MAXALIGN((_nnz) * sizeof(int32)) + (_nnz * sizeof(float)))
#define SPARSEVEC_VALUES(x) ((float *) (((char *) (x)) + offsetof(SparseVector, indices) + MAXALIGN((x)->nnz * sizeof(int32))))
#define DatumGetSparseVector(x) ((SparseVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_SPARSEVEC_P(x) DatumGetSparseVector(PG_GETARG_DATUM(x))
#define PG_RETURN_SPARSEVEC_P(x) PG_RETURN_POINTER(x)
typedef struct SparseVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int32 dim; /* number of dimensions */
int32 nnz;
int32 unused;
int32 indices[FLEXIBLE_ARRAY_MEMBER];
} SparseVector;
SparseVector *InitSparseVector(int dim, int nnz);
#endif

View File

@@ -2,14 +2,17 @@
#include <math.h>
#include "bitvector.h"
#include "catalog/pg_type.h"
#include "common/shortest_dec.h"
#include "fmgr.h"
#include "halfvec.h"
#include "hnsw.h"
#include "ivfflat.h"
#include "lib/stringinfo.h"
#include "libpq/pqformat.h"
#include "port.h" /* for strtof() */
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
@@ -197,6 +200,8 @@ vector_in(PG_FUNCTION_ARGS)
while (pt != NULL && *stringEnd != ']')
{
float val;
if (dim == VECTOR_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
@@ -212,15 +217,23 @@ vector_in(PG_FUNCTION_ARGS)
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
/* Use strtof like float4in to avoid a double-rounding problem */
x[dim] = strtof(pt, &stringEnd);
CheckElement(x[dim]);
dim++;
errno = 0;
val = strtof(pt, &stringEnd);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
/* Check for range error like float4in */
if (errno == ERANGE && isinf(val))
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type vector", pt)));
CheckElement(val);
x[dim++] = val;
while (vector_isspace(*stringEnd))
stringEnd++;
@@ -275,6 +288,9 @@ vector_in(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
#define AppendChar(ptr, c) (*(ptr)++ = (c))
#define AppendFloat(ptr, f) ((ptr) += float_to_shortest_decimal_bufn((f), (ptr)))
/*
* Convert internal representation to textual representation
*/
@@ -286,7 +302,6 @@ vector_out(PG_FUNCTION_ARGS)
int dim = vector->dim;
char *buf;
char *ptr;
int n;
/*
* Need:
@@ -301,21 +316,17 @@ vector_out(PG_FUNCTION_ARGS)
buf = (char *) palloc(FLOAT_SHORTEST_DECIMAL_LEN * dim + 2);
ptr = buf;
*ptr = '[';
ptr++;
AppendChar(ptr, '[');
for (int i = 0; i < dim; i++)
{
if (i > 0)
{
*ptr = ',';
ptr++;
}
AppendChar(ptr, ',');
n = float_to_shortest_decimal_bufn(vector->x[i], ptr);
ptr += n;
AppendFloat(ptr, vector->x[i]);
}
*ptr = ']';
ptr++;
AppendChar(ptr, ']');
*ptr = '\0';
PG_FREE_IF_COPY(vector, 0);
@@ -532,6 +543,28 @@ vector_to_float4(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Convert half vector to vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_to_vector);
Datum
halfvec_to_vector(PG_FUNCTION_ARGS)
{
HalfVector *vec = PG_GETARG_HALFVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
CheckDim(vec->dim);
CheckExpectedDim(typmod, vec->dim);
result = InitVector(vec->dim);
for (int i = 0; i < vec->dim; i++)
result->x[i] = HalfToFloat4(vec->x[i]);
PG_RETURN_POINTER(result);
}
/*
* Get the L2 distance between vectors
*/
@@ -860,15 +893,66 @@ vector_mul(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Quantize a vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(quantize_binary);
Datum
quantize_binary(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
float *ax = a->x;
VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result);
for (int i = 0; i < a->dim; i++)
rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result);
}
/*
* Get a subvector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(subvector);
Datum
subvector(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
int32 start = PG_GETARG_INT32(1);
int32 count = PG_GETARG_INT32(2);
int32 end = start + count;
float *ax = a->x;
Vector *result;
int dim;
/* Indexing starts at 1, like substring */
if (start < 1)
start = 1;
if (end > a->dim)
end = a->dim + 1;
dim = end - start;
CheckDim(dim);
result = InitVector(dim);
for (int i = 0; i < dim; i++)
result->x[i] = ax[start - 1 + i];
PG_RETURN_POINTER(result);
}
/*
* Internal helper to compare vectors
*/
int
vector_cmp_internal(Vector * a, Vector * b)
{
CheckDims(a, b);
int dim = Min(a->dim, b->dim);
for (int i = 0; i < a->dim; i++)
/* Check values before dimensions to be consistent with Postgres arrays */
for (int i = 0; i < dim; i++)
{
if (a->x[i] < b->x[i])
return -1;
@@ -876,6 +960,13 @@ vector_cmp_internal(Vector * a, Vector * b)
if (a->x[i] > b->x[i])
return 1;
}
if (a->dim < b->dim)
return -1;
if (a->dim > b->dim)
return 1;
return 0;
}
@@ -1134,3 +1225,26 @@ vector_avg(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Convert sparse vector to dense vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_to_vector);
Datum
sparsevec_to_vector(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
int dim = svec->dim;
float *values = SPARSEVEC_VALUES(svec);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitVector(dim);
for (int i = 0; i < svec->nnz; i++)
result->x[svec->indices[i]] = values[i];
PG_RETURN_POINTER(result);
}

View File

@@ -0,0 +1,64 @@
SELECT hamming_distance(B'111', B'111');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance(B'111', B'110');
hamming_distance
------------------
1
(1 row)
SELECT hamming_distance(B'111', B'100');
hamming_distance
------------------
2
(1 row)
SELECT hamming_distance(B'111', B'000');
hamming_distance
------------------
3
(1 row)
SELECT hamming_distance(B'111', B'00');
ERROR: different bit lengths 3 and 2
SELECT jaccard_distance(B'1111', B'1111');
jaccard_distance
------------------
0
(1 row)
SELECT jaccard_distance(B'1111', B'1110');
jaccard_distance
------------------
0.25
(1 row)
SELECT jaccard_distance(B'1111', B'1100');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance(B'1111', B'1000');
jaccard_distance
------------------
0.75
(1 row)
SELECT jaccard_distance(B'1111', B'0000');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance(B'1100', B'1000');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance(B'1111', B'000');
ERROR: different bit lengths 4 and 3

View File

@@ -46,6 +46,30 @@ SELECT '[1,2,3]'::vector::real[];
{1,2,3}
(1 row)
SELECT '[1,2,3]'::vector::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::halfvec::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '[65520]'::vector::halfvec;
ERROR: infinite value not allowed in halfvec
SELECT '[1e-8]'::vector::halfvec;
halfvec
---------
[0]
(1 row)
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
ERROR: vector cannot have more than 16000 dimensions
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;

View File

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

View File

@@ -1,210 +0,0 @@
SELECT '[1,2,3]'::vector + '[4,5,6]';
?column?
----------
[5,7,9]
(1 row)
SELECT '[3e38]'::vector + '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2,3]'::vector - '[4,5,6]';
?column?
------------
[-3,-3,-3]
(1 row)
SELECT '[-3e38]'::vector - '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2,3]'::vector * '[4,5,6]';
?column?
-----------
[4,10,18]
(1 row)
SELECT '[1e37]'::vector * '[1e37]';
ERROR: value out of range: overflow
SELECT '[1e-37]'::vector * '[1e-37]';
ERROR: value out of range: underflow
SELECT vector_dims('[1,2,3]');
vector_dims
-------------
3
(1 row)
SELECT round(vector_norm('[1,1]')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT vector_norm('[3,4]');
vector_norm
-------------
5
(1 row)
SELECT vector_norm('[0,1]');
vector_norm
-------------
1
(1 row)
SELECT vector_norm('[3e37,4e37]')::real;
vector_norm
-------------
5e+37
(1 row)
SELECT l2_distance('[0,0]', '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]', '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l2_distance('[3e38]', '[-3e38]');
l2_distance
-------------
Infinity
(1 row)
SELECT inner_product('[1,2]', '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT inner_product('[3e38]', '[3e38]');
inner_product
---------------
Infinity
(1 row)
SELECT cosine_distance('[1,2]', '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]', '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]', '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]', '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]', '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[3e38]', '[3e38]');
cosine_distance
-----------------
NaN
(1 row)
SELECT l1_distance('[0,0]', '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]', '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l1_distance('[3e38]', '[-3e38]');
l1_distance
-------------
Infinity
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
avg
-----
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: expected 2 dimensions, not 1
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
avg
---------
[3e+38]
(1 row)
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
ERROR: vector cannot have more than 16000 dimensions
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
sum
-----
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: different vector dimensions 2 and 1
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
ERROR: value out of range: overflow

View File

@@ -0,0 +1,146 @@
SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT '[0,0]'::halfvec <-> '[3,4]';
?column?
----------
5
(1 row)
SELECT inner_product('[1,2]'::halfvec, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT inner_product('[65504]'::halfvec, '[65504]');
inner_product
---------------
4290774016
(1 row)
SELECT '[1,2]'::halfvec <#> '[3,4]';
?column?
----------
-11
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]'::halfvec, '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT cosine_distance('[1,1]'::halfvec, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT '[1,2]'::halfvec <=> '[2,4]';
?column?
----------
0
(1 row)
SELECT l1_distance('[0,0]'::halfvec, '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT quantize_binary('[1,0,-1]'::halfvec);
quantize_binary
-----------------
100
(1 row)
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
quantize_binary
-----------------
01001110101
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
subvector
-----------
[1,2,3]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2);
subvector
-----------
[3,4]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 3);
subvector
-----------
[1]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 9);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 0);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, -1);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 2);
ERROR: halfvec must have at least 1 dimension

View File

@@ -0,0 +1,147 @@
SELECT '[1,2,3]'::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[-1,-2,-3]'::halfvec;
halfvec
------------
[-1,-2,-3]
(1 row)
SELECT '[1.,2.,3.]'::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT ' [ 1, 2 , 3 ] '::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1.23456]'::halfvec;
halfvec
------------
[1.234375]
(1 row)
SELECT '[hello,1]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[hello,1]"
LINE 1: SELECT '[hello,1]'::halfvec;
^
SELECT '[NaN,1]'::halfvec;
ERROR: NaN not allowed in halfvec
LINE 1: SELECT '[NaN,1]'::halfvec;
^
SELECT '[Infinity,1]'::halfvec;
ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[Infinity,1]'::halfvec;
^
SELECT '[-Infinity,1]'::halfvec;
ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[-Infinity,1]'::halfvec;
^
SELECT '[65519,-65519]'::halfvec;
halfvec
----------------
[65504,-65504]
(1 row)
SELECT '[65520,-65520]'::halfvec;
ERROR: value out of range: overflow
LINE 1: SELECT '[65520,-65520]'::halfvec;
^
SELECT '[1e-8,-1e-8]'::halfvec;
ERROR: value out of range: underflow
LINE 1: SELECT '[1e-8,-1e-8]'::halfvec;
^
SELECT '[4e38,1]'::halfvec;
ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[4e38,1]'::halfvec;
^
SELECT '[1,2,3'::halfvec;
ERROR: malformed halfvec literal: "[1,2,3"
LINE 1: SELECT '[1,2,3'::halfvec;
^
DETAIL: Unexpected end of input.
SELECT '[1,2,3]9'::halfvec;
ERROR: malformed halfvec literal: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::halfvec;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::halfvec;
ERROR: malformed halfvec literal: "1,2,3"
LINE 1: SELECT '1,2,3'::halfvec;
^
DETAIL: Vector contents must start with "[".
SELECT ''::halfvec;
ERROR: malformed halfvec literal: ""
LINE 1: SELECT ''::halfvec;
^
DETAIL: Vector contents must start with "[".
SELECT '['::halfvec;
ERROR: malformed halfvec literal: "["
LINE 1: SELECT '['::halfvec;
^
DETAIL: Unexpected end of input.
SELECT '[,'::halfvec;
ERROR: malformed halfvec literal: "[,"
LINE 1: SELECT '[,'::halfvec;
^
DETAIL: Unexpected end of input.
SELECT '[]'::halfvec;
ERROR: halfvec must have at least 1 dimension
LINE 1: SELECT '[]'::halfvec;
^
SELECT '[1,]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,]"
LINE 1: SELECT '[1,]'::halfvec;
^
SELECT '[1a]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1a]"
LINE 1: SELECT '[1a]'::halfvec;
^
SELECT '[1,,3]'::halfvec;
ERROR: malformed halfvec literal: "[1,,3]"
LINE 1: SELECT '[1,,3]'::halfvec;
^
SELECT '[1, ,3]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::halfvec;
^
SELECT '[1,2,3]'::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::halfvec(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::halfvec(3, 2);
^
SELECT '[1,2,3]'::halfvec('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::halfvec('a');
^
SELECT '[1,2,3]'::halfvec(0);
ERROR: dimensions for type halfvec must be at least 1
LINE 1: SELECT '[1,2,3]'::halfvec(0);
^
SELECT '[1,2,3]'::halfvec(16001);
ERROR: dimensions for type halfvec cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::halfvec(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::halfvec[]);
unnest
---------
[1,2,3]
[4,5,6]
(2 rows)
SELECT '{"[1,2,3]"}'::halfvec(2)[];
ERROR: expected 2 dimensions, not 3

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@@ -0,0 +1,21 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
val
-----
111
110
100
000
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

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

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

@@ -0,0 +1,92 @@
SELECT l2_distance('{}/2'::sparsevec, '{0:3,1:4}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{}/2'::sparsevec, '{1:1}/2');
l2_distance
-------------
1
(1 row)
SELECT '{}/2'::sparsevec <-> '{0:3,1:4}/2';
?column?
----------
5
(1 row)
SELECT inner_product('{0:1,1:2}/2'::sparsevec, '{0:2,1:4}/2');
inner_product
---------------
10
(1 row)
SELECT sparsevec_negative_inner_product('{0:1,1:2}/2', '{0:2,1:4}/2');
sparsevec_negative_inner_product
----------------------------------
-10
(1 row)
SELECT cosine_distance('{0:1,1:2}/2'::sparsevec, '{0:2,1:4}/2');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{0:1,1:2}/2'::sparsevec, '{}/2');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{0:1,1:1}/2'::sparsevec, '{0:-1,1:-1}/2');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('{0:1}/2'::sparsevec, '{1:2}/2');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{0:1}/2'::sparsevec, '{0:1}/3');
ERROR: different sparsevec dimensions 2 and 3
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 1, 3);
subvector
-----------------
{0:1,1:2,2:3}/3
(1 row)
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 3, 2);
subvector
-------------
{2:3,3:4}/2
(1 row)
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, -1, 3);
subvector
-----------
{0:1}/1
(1 row)
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 3, 9);
subvector
-----------------
{2:3,3:4,4:5}/3
(1 row)
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 1, 0);
ERROR: sparsevec must have at least 1 dimension
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 3, -1);
ERROR: sparsevec must have at least 1 dimension
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, -1, 2);
ERROR: sparsevec must have at least 1 dimension

View File

@@ -0,0 +1,62 @@
SELECT '{0:1.5,2:3.5}/5'::sparsevec;
sparsevec
-----------------
{0:1.5,2:3.5}/5
(1 row)
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector;
vector
-----------------
[1.5,0,3.5,0,0]
(1 row)
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(5);
vector
-----------------
[1.5,0,3.5,0,0]
(1 row)
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(4);
ERROR: expected 4 dimensions, not 5
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
sparsevec
-----------------
{1:1.5,3:3.5}/5
(1 row)
SELECT '{0:0,1:1,2:0}/3'::sparsevec;
sparsevec
-----------
{1:1}/3
(1 row)
SELECT '{1:1,0:1}/2'::sparsevec;
ERROR: indexes must be in ascending order
LINE 1: SELECT '{1:1,0:1}/2'::sparsevec;
^
SELECT '{}/5'::sparsevec;
sparsevec
-----------
{}/5
(1 row)
SELECT '{}/-1'::sparsevec;
ERROR: sparsevec must have at least 1 dimension
LINE 1: SELECT '{}/-1'::sparsevec;
^
SELECT '{}/100001'::sparsevec;
ERROR: sparsevec cannot have more than 100000 dimensions
LINE 1: SELECT '{}/100001'::sparsevec;
^
SELECT '{}/16001'::sparsevec::vector;
ERROR: vector cannot have more than 16000 dimensions
SELECT '{-1:1}/1'::sparsevec;
ERROR: index "-1" is out of range for type sparsevec
LINE 1: SELECT '{-1:1}/1'::sparsevec;
^
SELECT '{1:1}/1'::sparsevec;
ERROR: index must be less than dimensions
LINE 1: SELECT '{1:1}/1'::sparsevec;
^
SELECT '{}/1'::sparsevec(2);
ERROR: expected 2 dimensions, not 1

View File

@@ -0,0 +1,366 @@
SELECT '[1,2,3]'::vector + '[4,5,6]';
?column?
----------
[5,7,9]
(1 row)
SELECT '[3e38]'::vector + '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2,3]'::vector - '[4,5,6]';
?column?
------------
[-3,-3,-3]
(1 row)
SELECT '[-3e38]'::vector - '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2,3]'::vector * '[4,5,6]';
?column?
-----------
[4,10,18]
(1 row)
SELECT '[1e37]'::vector * '[1e37]';
ERROR: value out of range: overflow
SELECT '[1e-37]'::vector * '[1e-37]';
ERROR: value out of range: underflow
SELECT '[1,2,3]'::vector < '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector < '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector <= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector <= '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector = '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector = '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector != '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector != '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector >= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector >= '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector > '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector > '[1,2]';
?column?
----------
t
(1 row)
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
vector_cmp
------------
0
(1 row)
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
vector_cmp
------------
1
(1 row)
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[1,2]', '[1,2,3]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[1,2,3]', '[1,2]');
vector_cmp
------------
1
(1 row)
SELECT vector_cmp('[1,2]', '[2,3,4]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[2,3]', '[1,2,3]');
vector_cmp
------------
1
(1 row)
SELECT vector_dims('[1,2,3]');
vector_dims
-------------
3
(1 row)
SELECT round(vector_norm('[1,1]')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT vector_norm('[3,4]');
vector_norm
-------------
5
(1 row)
SELECT vector_norm('[0,1]');
vector_norm
-------------
1
(1 row)
SELECT vector_norm('[3e37,4e37]')::real;
vector_norm
-------------
5e+37
(1 row)
SELECT l2_distance('[0,0]'::vector, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]'::vector, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
l2_distance
-------------
Infinity
(1 row)
SELECT inner_product('[1,2]'::vector, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT inner_product('[3e38]'::vector, '[3e38]');
inner_product
---------------
Infinity
(1 row)
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
cosine_distance
-----------------
NaN
(1 row)
SELECT l1_distance('[0,0]'::vector, '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]'::vector, '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
l1_distance
-------------
Infinity
(1 row)
SELECT quantize_binary('[1,0,-1]'::vector);
quantize_binary
-----------------
100
(1 row)
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
quantize_binary
-----------------
01001110101
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
subvector
-----------
[1,2,3]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);
subvector
-----------
[3,4]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, -1, 3);
subvector
-----------
[1]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 3, 9);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 1, 0);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, 3, -1);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, -1, 2);
ERROR: vector must have at least 1 dimension
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
avg
-----
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: expected 2 dimensions, not 1
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
avg
---------
[3e+38]
(1 row)
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
ERROR: vector cannot have more than 16000 dimensions
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
sum
-----
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: different vector dimensions 2 and 1
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
ERROR: value out of range: overflow

View File

@@ -63,9 +63,25 @@ SELECT '[1.5e-38,-1.5e-38]'::vector;
(1 row)
SELECT '[4e38,1]'::vector;
ERROR: infinite value not allowed in vector
ERROR: "4e38" is out of range for type vector
LINE 1: SELECT '[4e38,1]'::vector;
^
SELECT '[-4e38,1]'::vector;
ERROR: "-4e38" is out of range for type vector
LINE 1: SELECT '[-4e38,1]'::vector;
^
SELECT '[1e-46,1]'::vector;
vector
--------
[0,1]
(1 row)
SELECT '[-1e-46,1]'::vector;
vector
--------
[-0,1]
(1 row)
SELECT '[1,2,3'::vector;
ERROR: malformed vector literal: "[1,2,3"
LINE 1: SELECT '[1,2,3'::vector;
@@ -116,8 +132,30 @@ SELECT '[1, ,3]'::vector;
ERROR: invalid input syntax for type vector: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::vector;
^
SELECT '[1,2,3]'::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::vector(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::vector(3, 2);
^
SELECT '[1,2,3]'::vector('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::vector('a');
^
SELECT '[1,2,3]'::vector(0);
ERROR: dimensions for type vector must be at least 1
LINE 1: SELECT '[1,2,3]'::vector(0);
^
SELECT '[1,2,3]'::vector(16001);
ERROR: dimensions for type vector cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::vector(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
unnest
---------

View File

@@ -0,0 +1,13 @@
SELECT hamming_distance(B'111', B'111');
SELECT hamming_distance(B'111', B'110');
SELECT hamming_distance(B'111', B'100');
SELECT hamming_distance(B'111', B'000');
SELECT hamming_distance(B'111', B'00');
SELECT jaccard_distance(B'1111', B'1111');
SELECT jaccard_distance(B'1111', B'1110');
SELECT jaccard_distance(B'1111', B'1100');
SELECT jaccard_distance(B'1111', B'1000');
SELECT jaccard_distance(B'1111', B'0000');
SELECT jaccard_distance(B'1100', B'1000');
SELECT jaccard_distance(B'1111', B'000');

View File

@@ -10,6 +10,12 @@ SELECT '{-Infinity}'::real[]::vector;
SELECT '{}'::real[]::vector;
SELECT '{{1}}'::real[]::vector;
SELECT '[1,2,3]'::vector::real[];
SELECT '[1,2,3]'::vector::halfvec;
SELECT '[1,2,3]'::halfvec::vector;
SELECT '[1,2,3]'::vector::halfvec(2);
SELECT '[1,2,3]'::halfvec::vector(2);
SELECT '[65520]'::vector::halfvec;
SELECT '[1e-8]'::vector::halfvec;
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;

View File

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

View File

@@ -1,51 +0,0 @@
SELECT '[1,2,3]'::vector + '[4,5,6]';
SELECT '[3e38]'::vector + '[3e38]';
SELECT '[1,2,3]'::vector - '[4,5,6]';
SELECT '[-3e38]'::vector - '[3e38]';
SELECT '[1,2,3]'::vector * '[4,5,6]';
SELECT '[1e37]'::vector * '[1e37]';
SELECT '[1e-37]'::vector * '[1e-37]';
SELECT vector_dims('[1,2,3]');
SELECT round(vector_norm('[1,1]')::numeric, 5);
SELECT vector_norm('[3,4]');
SELECT vector_norm('[0,1]');
SELECT vector_norm('[3e37,4e37]')::real;
SELECT l2_distance('[0,0]', '[3,4]');
SELECT l2_distance('[0,0]', '[0,1]');
SELECT l2_distance('[1,2]', '[3]');
SELECT l2_distance('[3e38]', '[-3e38]');
SELECT inner_product('[1,2]', '[3,4]');
SELECT inner_product('[1,2]', '[3]');
SELECT inner_product('[3e38]', '[3e38]');
SELECT cosine_distance('[1,2]', '[2,4]');
SELECT cosine_distance('[1,2]', '[0,0]');
SELECT cosine_distance('[1,1]', '[1,1]');
SELECT cosine_distance('[1,0]', '[0,2]');
SELECT cosine_distance('[1,1]', '[-1,-1]');
SELECT cosine_distance('[1,2]', '[3]');
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
SELECT cosine_distance('[3e38]', '[3e38]');
SELECT l1_distance('[0,0]', '[3,4]');
SELECT l1_distance('[0,0]', '[0,1]');
SELECT l1_distance('[1,2]', '[3]');
SELECT l1_distance('[3e38]', '[-3e38]');
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;

View File

@@ -0,0 +1,34 @@
SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
SELECT l2_distance('[1,2]'::halfvec, '[3]');
SELECT '[0,0]'::halfvec <-> '[3,4]';
SELECT inner_product('[1,2]'::halfvec, '[3,4]');
SELECT inner_product('[1,2]'::halfvec, '[3]');
SELECT inner_product('[65504]'::halfvec, '[65504]');
SELECT '[1,2]'::halfvec <#> '[3,4]';
SELECT cosine_distance('[1,2]'::halfvec, '[2,4]');
SELECT cosine_distance('[1,2]'::halfvec, '[0,0]');
SELECT cosine_distance('[1,1]'::halfvec, '[1,1]');
SELECT cosine_distance('[1,0]'::halfvec, '[0,2]');
SELECT cosine_distance('[1,1]'::halfvec, '[-1,-1]');
SELECT cosine_distance('[1,2]'::halfvec, '[3]');
SELECT cosine_distance('[1,1]'::halfvec, '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::halfvec, '[-1.1,-1.1]');
SELECT '[1,2]'::halfvec <=> '[2,4]';
SELECT l1_distance('[0,0]'::halfvec, '[3,4]');
SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
SELECT l1_distance('[1,2]'::halfvec, '[3]');
SELECT quantize_binary('[1,0,-1]'::halfvec);
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2);
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 3);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 9);
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 0);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, -1);
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 2);

View File

@@ -0,0 +1,34 @@
SELECT '[1,2,3]'::halfvec;
SELECT '[-1,-2,-3]'::halfvec;
SELECT '[1.,2.,3.]'::halfvec;
SELECT ' [ 1, 2 , 3 ] '::halfvec;
SELECT '[1.23456]'::halfvec;
SELECT '[hello,1]'::halfvec;
SELECT '[NaN,1]'::halfvec;
SELECT '[Infinity,1]'::halfvec;
SELECT '[-Infinity,1]'::halfvec;
SELECT '[65519,-65519]'::halfvec;
SELECT '[65520,-65520]'::halfvec;
SELECT '[1e-8,-1e-8]'::halfvec;
SELECT '[4e38,1]'::halfvec;
SELECT '[1,2,3'::halfvec;
SELECT '[1,2,3]9'::halfvec;
SELECT '1,2,3'::halfvec;
SELECT ''::halfvec;
SELECT '['::halfvec;
SELECT '[,'::halfvec;
SELECT '[]'::halfvec;
SELECT '[1,]'::halfvec;
SELECT '[1a]'::halfvec;
SELECT '[1,,3]'::halfvec;
SELECT '[1, ,3]'::halfvec;
SELECT '[1,2,3]'::halfvec(3);
SELECT '[1,2,3]'::halfvec(2);
SELECT '[1,2,3]'::halfvec(3, 2);
SELECT '[1,2,3]'::halfvec('a');
SELECT '[1,2,3]'::halfvec(0);
SELECT '[1,2,3]'::halfvec(16001);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::halfvec[]);
SELECT '{"[1,2,3]"}'::halfvec(2)[];

View File

@@ -0,0 +1,12 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
DROP TABLE t;

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

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

View File

@@ -0,0 +1,21 @@
SELECT l2_distance('{}/2'::sparsevec, '{0:3,1:4}/2');
SELECT l2_distance('{}/2'::sparsevec, '{1:1}/2');
SELECT '{}/2'::sparsevec <-> '{0:3,1:4}/2';
SELECT inner_product('{0:1,1:2}/2'::sparsevec, '{0:2,1:4}/2');
SELECT sparsevec_negative_inner_product('{0:1,1:2}/2', '{0:2,1:4}/2');
SELECT cosine_distance('{0:1,1:2}/2'::sparsevec, '{0:2,1:4}/2');
SELECT cosine_distance('{0:1,1:2}/2'::sparsevec, '{}/2');
SELECT cosine_distance('{0:1,1:1}/2'::sparsevec, '{0:-1,1:-1}/2');
SELECT cosine_distance('{0:1}/2'::sparsevec, '{1:2}/2');
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
SELECT cosine_distance('{0:1}/2'::sparsevec, '{0:1}/3');
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 1, 3);
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 3, 2);
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, -1, 3);
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 3, 9);
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 1, 0);
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, 3, -1);
SELECT subvector('{0:1,1:2,2:3,3:4,4:5}/5'::sparsevec, -1, 2);

View File

@@ -0,0 +1,19 @@
SELECT '{0:1.5,2:3.5}/5'::sparsevec;
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector;
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(5);
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(4);
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
SELECT '{0:0,1:1,2:0}/3'::sparsevec;
SELECT '{1:1,0:1}/2'::sparsevec;
SELECT '{}/5'::sparsevec;
SELECT '{}/-1'::sparsevec;
SELECT '{}/100001'::sparsevec;
SELECT '{}/16001'::sparsevec::vector;
SELECT '{-1:1}/1'::sparsevec;
SELECT '{1:1}/1'::sparsevec;
SELECT '{}/1'::sparsevec(2);

View File

@@ -0,0 +1,83 @@
SELECT '[1,2,3]'::vector + '[4,5,6]';
SELECT '[3e38]'::vector + '[3e38]';
SELECT '[1,2,3]'::vector - '[4,5,6]';
SELECT '[-3e38]'::vector - '[3e38]';
SELECT '[1,2,3]'::vector * '[4,5,6]';
SELECT '[1e37]'::vector * '[1e37]';
SELECT '[1e-37]'::vector * '[1e-37]';
SELECT '[1,2,3]'::vector < '[1,2,3]';
SELECT '[1,2,3]'::vector < '[1,2]';
SELECT '[1,2,3]'::vector <= '[1,2,3]';
SELECT '[1,2,3]'::vector <= '[1,2]';
SELECT '[1,2,3]'::vector = '[1,2,3]';
SELECT '[1,2,3]'::vector = '[1,2]';
SELECT '[1,2,3]'::vector != '[1,2,3]';
SELECT '[1,2,3]'::vector != '[1,2]';
SELECT '[1,2,3]'::vector >= '[1,2,3]';
SELECT '[1,2,3]'::vector >= '[1,2]';
SELECT '[1,2,3]'::vector > '[1,2,3]';
SELECT '[1,2,3]'::vector > '[1,2]';
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
SELECT vector_cmp('[1,2]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[1,2]');
SELECT vector_cmp('[1,2]', '[2,3,4]');
SELECT vector_cmp('[2,3]', '[1,2,3]');
SELECT vector_dims('[1,2,3]');
SELECT round(vector_norm('[1,1]')::numeric, 5);
SELECT vector_norm('[3,4]');
SELECT vector_norm('[0,1]');
SELECT vector_norm('[3e37,4e37]')::real;
SELECT l2_distance('[0,0]'::vector, '[3,4]');
SELECT l2_distance('[0,0]'::vector, '[0,1]');
SELECT l2_distance('[1,2]'::vector, '[3]');
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
SELECT inner_product('[1,2]'::vector, '[3,4]');
SELECT inner_product('[1,2]'::vector, '[3]');
SELECT inner_product('[3e38]'::vector, '[3e38]');
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
SELECT cosine_distance('[1,2]'::vector, '[3]');
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
SELECT l1_distance('[0,0]'::vector, '[3,4]');
SELECT l1_distance('[0,0]'::vector, '[0,1]');
SELECT l1_distance('[1,2]'::vector, '[3]');
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
SELECT quantize_binary('[1,0,-1]'::vector);
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);
SELECT subvector('[1,2,3,4,5]'::vector, -1, 3);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 9);
SELECT subvector('[1,2,3,4,5]'::vector, 1, 0);
SELECT subvector('[1,2,3,4,5]'::vector, 3, -1);
SELECT subvector('[1,2,3,4,5]'::vector, -1, 2);
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;

View File

@@ -11,6 +11,9 @@ SELECT '[1.5e38,-1.5e38]'::vector;
SELECT '[1.5e+38,-1.5e+38]'::vector;
SELECT '[1.5e-38,-1.5e-38]'::vector;
SELECT '[4e38,1]'::vector;
SELECT '[-4e38,1]'::vector;
SELECT '[1e-46,1]'::vector;
SELECT '[-1e-46,1]'::vector;
SELECT '[1,2,3'::vector;
SELECT '[1,2,3]9'::vector;
SELECT '1,2,3'::vector;
@@ -22,7 +25,13 @@ SELECT '[1,]'::vector;
SELECT '[1a]'::vector;
SELECT '[1,,3]'::vector;
SELECT '[1, ,3]'::vector;
SELECT '[1,2,3]'::vector(3);
SELECT '[1,2,3]'::vector(2);
SELECT '[1,2,3]'::vector(3, 2);
SELECT '[1,2,3]'::vector('a');
SELECT '[1,2,3]'::vector(0);
SELECT '[1,2,3]'::vector(16001);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
SELECT '{"[1,2,3]"}'::vector(2)[];

View File

@@ -86,7 +86,7 @@ foreach (@queries)
push(@expected, $res);
}
test_recall(0.20, $limit, "before vacuum");
test_recall(0.19, $limit, "before vacuum");
test_recall(0.95, 100, "before vacuum");
# TODO Test concurrent inserts with vacuum

View File

@@ -0,0 +1,137 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 52;
my $max = 2**$dim;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator $queries[0] LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
SELECT i FROM tst ORDER BY v $operator $queries[$i] LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v bit($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, (random() * $max)::bigint::bit($dim) FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1 .. 20)
{
my $r = int(rand() * $max);
push(@queries, "${r}::bigint::bit($dim)");
}
# Check each index type
my @operators = ("<~>", "<\%>");
my @opclasses = ("bit_hamming_ops", "bit_jaccard_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Get exact results
@expected = ();
foreach (@queries)
{
# Handle ties
my $res = $node->safe_psql("postgres", qq(
WITH top AS (
SELECT v $operator $_ AS distance FROM tst ORDER BY v $operator $_ LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator $_) <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
# Build index serially
$node->safe_psql("postgres", qq(
SET max_parallel_maintenance_workers = 0;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
# Test approximate results
my $min = $operator eq "<\%>" ? 0.96 : 0.98;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel in memory
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel on disk
# Set parallel_workers on table to use workers with low maintenance_work_mem
($ret, $stdout, $stderr) = $node->psql("postgres", qq(
ALTER TABLE tst SET (parallel_workers = 2);
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '4MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
ALTER TABLE tst RESET (parallel_workers);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem/);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

View File

@@ -0,0 +1,132 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 10;
my $array_sql = join(",", ('random()') x $dim);
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SELECT i FROM tst ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my %actual_set = map { $_ => 1 } @actual_ids;
my @expected_ids = split("\n", $expected[$i]);
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
}
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v halfvec($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1 .. 20)
{
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
push(@queries, "[" . join(",", @r) . "]");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("halfvec_l2_ops", "halfvec_ip_ops", "halfvec_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", "SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;");
push(@expected, $res);
}
# Build index serially
$node->safe_psql("postgres", qq(
SET max_parallel_maintenance_workers = 0;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
# Test approximate results
my $min = $operator eq "<#>" ? 0.95 : 0.98;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel in memory
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel on disk
# Set parallel_workers on table to use workers with low maintenance_work_mem
($ret, $stdout, $stderr) = $node->psql("postgres", qq(
ALTER TABLE tst SET (parallel_workers = 2);
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '4MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
ALTER TABLE tst RESET (parallel_workers);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem/);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

View File

@@ -1,4 +1,4 @@
comment = 'vector data type and ivfflat and hnsw access methods'
default_version = '0.6.0'
default_version = '0.6.2'
module_pathname = '$libdir/vector'
relocatable = true