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Author SHA1 Message Date
Andrew Kane
ec68b75892 Added bulk hashing [skip ci] 2024-10-29 11:41:57 -07:00
37 changed files with 228 additions and 383 deletions

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

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

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@@ -1,14 +1,4 @@
## 0.8.2 (unreleased)
- Improved `install` target on Windows
- Fixed `Index Searches` in `EXPLAIN` output for Postgres 18
## 0.8.1 (2025-09-04)
- Added support for Postgres 18 rc1
- Improved performance of `binary_quantize` function
## 0.8.0 (2024-10-30)
## 0.8.0 (unreleased)
- Added support for iterative index scans
- Added casts for arrays to `sparsevec`

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

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@@ -1,4 +1,4 @@
Portions Copyright (c) 1996-2025, PostgreSQL Global Development Group
Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group
Portions Copyright (c) 1994, The Regents of the University of California

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@@ -2,7 +2,7 @@
"name": "vector",
"abstract": "Open-source vector similarity search for Postgres",
"description": "Supports L2 distance, inner product, and cosine distance",
"version": "0.8.1",
"version": "0.7.4",
"maintainer": [
"Andrew Kane <andrew@ankane.org>"
],
@@ -12,7 +12,7 @@
"prereqs": {
"runtime": {
"requires": {
"PostgreSQL": "13.0.0"
"PostgreSQL": "12.0.0"
}
}
},
@@ -20,7 +20,7 @@
"vector": {
"file": "sql/vector.sql",
"docfile": "README.md",
"version": "0.8.1",
"version": "0.7.4",
"abstract": "Open-source vector similarity search for Postgres"
}
},

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

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

220
README.md
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@@ -17,11 +17,11 @@ Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recove
### Linux and Mac
Compile and install the extension (supports Postgres 13+)
Compile and install the extension (supports Postgres 12+)
```sh
cd /tmp
git clone --branch v0.8.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo
@@ -29,21 +29,31 @@ make install # may need sudo
See the [installation notes](#installation-notes---linux-and-mac) if you run into issues
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [pkg](#pkg), [APK](#apk), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [pkg](#pkg), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
### Windows
Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/build/building-on-the-command-line?view=msvc-170#download-and-install-the-tools) is installed and run `x64 Native Tools Command Prompt for VS [version]` as administrator. Then use `nmake` to build:
Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/build/building-on-the-command-line?view=msvc-170#download-and-install-the-tools) is installed, and run:
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\18"
call "C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvars64.bat"
```
Note: The exact path will vary depending on your Visual Studio version and edition
Then use `nmake` to build:
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16"
cd %TEMP%
git clone --branch v0.8.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
```
Note: Postgres 17 is not supported yet due to an upstream issue
See the [installation notes](#installation-notes---windows) if you run into issues
You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
@@ -74,7 +84,7 @@ Get the nearest neighbors by L2 distance
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`)
Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`, added in 0.7.0)
Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators
@@ -138,9 +148,9 @@ Supported distance functions are:
- `<->` - L2 distance
- `<#>` - (negative) inner product
- `<=>` - cosine distance
- `<+>` - L1 distance
- `<~>` - Hamming distance (binary vectors)
- `<%>` - Jaccard distance (binary vectors)
- `<+>` - L1 distance (added in 0.7.0)
- `<~>` - Hamming distance (binary vectors, added in 0.7.0)
- `<%>` - Jaccard distance (binary vectors, added in 0.7.0)
Get the nearest neighbors to a row
@@ -227,19 +237,19 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
```
L1 distance
L1 distance - added in 0.7.0
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l1_ops);
```
Hamming distance
Hamming distance - added in 0.7.0
```sql
CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
```
Jaccard distance
Jaccard distance - added in 0.7.0
```sql
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
@@ -248,9 +258,9 @@ CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions
- `bit` - up to 64,000 dimensions
- `sparsevec` - up to 1,000 non-zero elements
- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
- `sparsevec` - up to 1,000 non-zero elements (added in 0.7.0)
### Index Options
@@ -304,19 +314,17 @@ Note: Do not set `maintenance_work_mem` so high that it exhausts the memory on t
Like other index types, its faster to create an index after loading your initial data
You can also speed up index creation by increasing the number of parallel workers (2 by default)
Starting with 0.6.0, you can also speed up index creation by increasing the number of parallel workers (2 by default)
```sql
SET max_parallel_maintenance_workers = 7; -- plus leader
```
For a large number of workers, you may need to increase `max_parallel_workers` (8 by default)
The [index options](#index-options) also have a significant impact on build time (use the defaults unless seeing low recall)
For a large number of workers, you may also need to increase `max_parallel_workers` (8 by default)
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
@@ -359,7 +367,7 @@ Cosine distance
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
```
Hamming distance
Hamming distance - added in 0.7.0
```sql
CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100);
@@ -368,8 +376,8 @@ CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 10
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions
- `bit` - up to 64,000 dimensions
- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
### Query Options
@@ -402,7 +410,7 @@ For a large number of workers, you may also need to increase `max_parallel_worke
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
@@ -469,6 +477,8 @@ CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(cate
## Iterative Index Scans
*Unreleased*
With approximate indexes, queries with filtering can return less results since filtering is applied *after* the index is scanned. Starting with 0.8.0, you can enable iterative index scans, which will automatically scan more of the index until enough results are found (or it reaches `hnsw.max_scan_tuples` or `ivfflat.max_probes`).
Iterative scans can use strict or relaxed ordering.
@@ -492,11 +502,9 @@ With relaxed ordering, you can use a [materialized CTE](https://www.postgresql.o
```sql
WITH relaxed_results AS MATERIALIZED (
SELECT id, embedding <-> '[1,2,3]' AS distance FROM items WHERE category_id = 123 ORDER BY distance LIMIT 5
) SELECT * FROM relaxed_results ORDER BY distance + 0;
) SELECT * FROM relaxed_results ORDER BY distance;
```
Note: `+ 0` is needed for Postgres 17+
For queries that filter by distance, use a materialized CTE and place the distance filter outside of it for best performance (due to the [current behavior](https://www.postgresql.org/message-id/flat/CAOdR5yGUoMQ6j7M5hNUXrySzaqZVGf_Ne%2B8fwZMRKTFxU1nbJg%40mail.gmail.com) of the Postgres executor)
```sql
@@ -541,6 +549,8 @@ Note: If this is lower than `ivfflat.probes`, `ivfflat.probes` will be used
## Half-Precision Vectors
*Added in 0.7.0*
Use the `halfvec` type to store half-precision vectors
```sql
@@ -549,6 +559,8 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));
## Half-Precision Indexing
*Added in 0.7.0*
Index vectors at half precision for smaller indexes
```sql
@@ -570,16 +582,24 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES ('000'), ('111');
```
Get the nearest neighbors by Hamming distance
Get the nearest neighbors by Hamming distance (added in 0.7.0)
```sql
SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
```
Or (before 0.7.0)
```sql
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Also supports Jaccard distance (`<%>`)
## Binary Quantization
*Added in 0.7.0*
Use expression indexing for binary quantization
```sql
@@ -602,6 +622,8 @@ SELECT * FROM (
## Sparse Vectors
*Added in 0.7.0*
Use the `sparsevec` type to store sparse vectors
```sql
@@ -635,6 +657,8 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python
## Indexing Subvectors
*Added in 0.7.0*
Use expression indexing to index subvectors
```sql
@@ -695,10 +719,10 @@ CREATE INDEX CONCURRENTLY ...
### Querying
Use `EXPLAIN (ANALYZE, BUFFERS)` to debug performance.
Use `EXPLAIN ANALYZE` to debug performance.
```sql
EXPLAIN (ANALYZE, BUFFERS) SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
```
#### Exact Search
@@ -748,6 +772,8 @@ SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_t
FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20;
```
Note: Replace `total_plan_time + total_exec_time` with `total_time` for Postgres < 13
Monitor recall by comparing results from approximate search with exact search.
```sql
@@ -771,35 +797,25 @@ Use pgvector from any language with a Postgres client. You can even generate and
Language | Libraries / Examples
--- | ---
Ada | [pgvector-ada](https://github.com/pgvector/pgvector-ada)
Algol | [pgvector-algol](https://github.com/pgvector/pgvector-algol)
C | [pgvector-c](https://github.com/pgvector/pgvector-c)
C++ | [pgvector-cpp](https://github.com/pgvector/pgvector-cpp)
C#, F#, Visual Basic | [pgvector-dotnet](https://github.com/pgvector/pgvector-dotnet)
Crystal | [pgvector-crystal](https://github.com/pgvector/pgvector-crystal)
D | [pgvector-d](https://github.com/pgvector/pgvector-d)
Dart | [pgvector-dart](https://github.com/pgvector/pgvector-dart)
Elixir | [pgvector-elixir](https://github.com/pgvector/pgvector-elixir)
Erlang | [pgvector-erlang](https://github.com/pgvector/pgvector-erlang)
Fortran | [pgvector-fortran](https://github.com/pgvector/pgvector-fortran)
Gleam | [pgvector-gleam](https://github.com/pgvector/pgvector-gleam)
Go | [pgvector-go](https://github.com/pgvector/pgvector-go)
Haskell | [pgvector-haskell](https://github.com/pgvector/pgvector-haskell)
Java, Kotlin, Groovy, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
JavaScript, TypeScript | [pgvector-node](https://github.com/pgvector/pgvector-node)
Julia | [Pgvector.jl](https://github.com/pgvector/Pgvector.jl)
Julia | [pgvector-julia](https://github.com/pgvector/pgvector-julia)
Lisp | [pgvector-lisp](https://github.com/pgvector/pgvector-lisp)
Lua | [pgvector-lua](https://github.com/pgvector/pgvector-lua)
Nim | [pgvector-nim](https://github.com/pgvector/pgvector-nim)
OCaml | [pgvector-ocaml](https://github.com/pgvector/pgvector-ocaml)
Pascal | [pgvector-pascal](https://github.com/pgvector/pgvector-pascal)
Perl | [pgvector-perl](https://github.com/pgvector/pgvector-perl)
PHP | [pgvector-php](https://github.com/pgvector/pgvector-php)
Prolog | [pgvector-prolog](https://github.com/pgvector/pgvector-prolog)
Python | [pgvector-python](https://github.com/pgvector/pgvector-python)
R | [pgvector-r](https://github.com/pgvector/pgvector-r)
Racket | [pgvector-racket](https://github.com/pgvector/pgvector-racket)
Raku | [pgvector-raku](https://github.com/pgvector/pgvector-raku)
Ruby | [pgvector-ruby](https://github.com/pgvector/pgvector-ruby), [Neighbor](https://github.com/ankane/neighbor)
Rust | [pgvector-rust](https://github.com/pgvector/pgvector-rust)
Swift | [pgvector-swift](https://github.com/pgvector/pgvector-swift)
@@ -817,11 +833,11 @@ Yes, pgvector uses the write-ahead log (WAL), which allows for replication and p
#### What if I want to index vectors with more than 2,000 dimensions?
You can use [half-precision vectors](#half-precision-vectors) or [half-precision indexing](#half-precision-indexing) to index up to 4,000 dimensions or [binary quantization](#binary-quantization) to index up to 64,000 dimensions. Other options are [indexing subvectors](#indexing-subvectors) (for models that support it) or [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction).
You can use [half-precision indexing](#half-precision-indexing) to index up to 4,000 dimensions or [binary quantization](#binary-quantization) to index up to 64,000 dimensions. Another option is [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction).
#### Can I store vectors with different dimensions in the same column?
You can use `vector` as the type (instead of `vector(n)`).
You can use `vector` as the type (instead of `vector(3)`).
```sql
CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id));
@@ -921,7 +937,7 @@ ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
#### Why are there less results for a query after adding an HNSW index?
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`), which is 40 by default. There may be even less results due to dead tuples or filtering conditions in the query. Enabling [iterative index scans](#iterative-index-scans) can help address this.
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead.
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
@@ -933,7 +949,7 @@ The index was likely created with too little data for the number of lists. Drop
DROP INDEX index_name;
```
Results can also be limited by the number of probes (`ivfflat.probes`). Enabling [iterative index scans](#iterative-index-scans) can address this.
Results can also be limited by the number of probes (`ivfflat.probes`).
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
@@ -1069,7 +1085,7 @@ l2_normalize(sparsevec) → sparsevec | Normalize with Euclidean norm | 0.7.0
If your machine has multiple Postgres installations, specify the path to [pg_config](https://www.postgresql.org/docs/current/app-pgconfig.html) with:
```sh
export PG_CONFIG=/Library/PostgreSQL/18/bin/pg_config
export PG_CONFIG=/Library/PostgreSQL/17/bin/pg_config
```
Then re-run the installation instructions (run `make clean` before `make` if needed). If `sudo` is needed for `make install`, use:
@@ -1080,11 +1096,11 @@ sudo --preserve-env=PG_CONFIG make install
A few common paths on Mac are:
- EDB installer - `/Library/PostgreSQL/18/bin/pg_config`
- Homebrew (arm64) - `/opt/homebrew/opt/postgresql@18/bin/pg_config`
- Homebrew (x86-64) - `/usr/local/opt/postgresql@18/bin/pg_config`
- EDB installer - `/Library/PostgreSQL/17/bin/pg_config`
- Homebrew (arm64) - `/opt/homebrew/opt/postgresql@17/bin/pg_config`
- Homebrew (x86-64) - `/usr/local/opt/postgresql@17/bin/pg_config`
Note: Replace `18` with your Postgres server version
Note: Replace `17` with your Postgres server version
### Missing Header
@@ -1093,20 +1109,14 @@ If compilation fails with `fatal error: postgres.h: No such file or directory`,
For Ubuntu and Debian, use:
```sh
sudo apt install postgresql-server-dev-18
sudo apt install postgresql-server-dev-17
```
Note: Replace `18` with your Postgres server version
Note: Replace `17` with your Postgres server version
### Missing SDK
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, your Postgres installation points to a path that no longer exists.
```sh
pg_config --cppflags
```
Reinstall Postgres to fix this.
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, reinstall Xcode Command Line Tools.
### Portability
@@ -1124,14 +1134,6 @@ make OPTFLAGS=""
If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct.
### Mismatched Architecture
If compilation fails with `error C2196: case value '4' already used`, make sure youre using the `x64 Native Tools Command Prompt`. Then run `nmake /F Makefile.win clean` and re-run the installation instructions.
### Missing Symbol
If linking fails with `unresolved external symbol float_to_shortest_decimal_bufn` with Postgres 17.0-17.2, upgrade to Postgres 17.3+.
### Permissions
If installation fails with `Access is denied`, re-run the installation instructions as an administrator.
@@ -1143,38 +1145,17 @@ If installation fails with `Access is denied`, re-run the installation instructi
Get the [Docker image](https://hub.docker.com/r/pgvector/pgvector) with:
```sh
docker pull pgvector/pgvector:pg18-trixie
docker pull pgvector/pgvector:pg17
```
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `18` with your Postgres server version, and run it the same way).
Supported tags are:
- `pg18-trixie`, `0.8.1-pg18-trixie`
- `pg18-bookworm`, `0.8.1-pg18-bookworm`, `pg18`, `0.8.1-pg18`
- `pg17-trixie`, `0.8.1-pg17-trixie`
- `pg17-bookworm`, `0.8.1-pg17-bookworm`, `pg17`, `0.8.1-pg17`
- `pg16-trixie`, `0.8.1-pg16-trixie`
- `pg16-bookworm`, `0.8.1-pg16-bookworm`, `pg16`, `0.8.1-pg16`
- `pg15-trixie`, `0.8.1-pg15-trixie`
- `pg15-bookworm`, `0.8.1-pg15-bookworm`, `pg15`, `0.8.1-pg15`
- `pg14-trixie`, `0.8.1-pg14-trixie`
- `pg14-bookworm`, `0.8.1-pg14-bookworm`, `pg14`, `0.8.1-pg14`
- `pg13-trixie`, `0.8.1-pg13-trixie`
- `pg13-bookworm`, `0.8.1-pg13-bookworm`, `pg13`, `0.8.1-pg13`
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `17` with your Postgres server version, and run it the same way).
You can also build the image manually:
```sh
git clone --branch v0.8.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
cd pgvector
docker build --pull --build-arg PG_MAJOR=18 -t myuser/pgvector .
```
If you increase `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
```sh
docker run --shm-size=1g ...
docker build --pull --build-arg PG_MAJOR=17 -t myuser/pgvector .
```
### Homebrew
@@ -1185,7 +1166,7 @@ With Homebrew Postgres, you can use:
brew install pgvector
```
Note: This only adds it to the `postgresql@18` and `postgresql@17` formulas
Note: This only adds it to the `postgresql@17` and `postgresql@14` formulas
### PGXN
@@ -1200,29 +1181,29 @@ pgxn install vector
Debian and Ubuntu packages are available from the [PostgreSQL APT Repository](https://wiki.postgresql.org/wiki/Apt). Follow the [setup instructions](https://wiki.postgresql.org/wiki/Apt#Quickstart) and run:
```sh
sudo apt install postgresql-18-pgvector
sudo apt install postgresql-17-pgvector
```
Note: Replace `18` with your Postgres server version
Note: Replace `17` with your Postgres server version
### Yum
RPM packages are available from the [PostgreSQL Yum Repository](https://yum.postgresql.org/). Follow the [setup instructions](https://www.postgresql.org/download/linux/redhat/) for your distribution and run:
```sh
sudo yum install pgvector_18
sudo yum install pgvector_17
# or
sudo dnf install pgvector_18
sudo dnf install pgvector_17
```
Note: Replace `18` with your Postgres server version
Note: Replace `17` with your Postgres server version
### pkg
Install the FreeBSD package with:
```sh
pkg install postgresql17-pgvector
pkg install postgresql15-pgvector
```
or the port with:
@@ -1232,14 +1213,6 @@ cd /usr/ports/databases/pgvector
make install
```
### APK
Install the Alpine package with:
```sh
apk add postgresql-pgvector
```
### conda-forge
With Conda Postgres, install from [conda-forge](https://anaconda.org/conda-forge/pgvector) with:
@@ -1272,6 +1245,36 @@ You can check the version in the current database with:
SELECT extversion FROM pg_extension WHERE extname = 'vector';
```
## Upgrade Notes
### 0.6.0
#### Postgres 12
If upgrading with Postgres 12, remove this line from `sql/vector--0.5.1--0.6.0.sql`:
```sql
ALTER TYPE vector SET (STORAGE = external);
```
Then run `make install` and `ALTER EXTENSION vector UPDATE;`.
#### Docker
The Docker image is now published in the `pgvector` org, and there are tags for each supported version of Postgres (rather than a `latest` tag).
```sh
docker pull pgvector/pgvector:pg16
# or
docker pull pgvector/pgvector:0.6.0-pg16
```
Also, if youve increased `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
```sh
docker run --shm-size=1g ...
```
## Thanks
Thanks to:
@@ -1282,7 +1285,6 @@ Thanks to:
- [k-means++: The Advantage of Careful Seeding](https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf)
- [Concept Decompositions for Large Sparse Text Data using Clustering](https://www.cs.utexas.edu/users/inderjit/public_papers/concept_mlj.pdf)
- [Efficient and Robust Approximate Nearest Neighbor Search using Hierarchical Navigable Small World Graphs](https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf)
- [Distance Adaptive Beam Search for Provably Accurate Graph-Based Nearest Neighbor Search](https://arxiv.org/pdf/2505.15636)
## History

View File

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

View File

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

View File

@@ -52,20 +52,12 @@ HnswInitLockTranche(void)
sizeof(int) * 1,
&found);
if (!found)
{
#if PG_VERSION_NUM >= 190000
tranche_ids[0] = LWLockNewTrancheId("HnswBuild");
#else
tranche_ids[0] = LWLockNewTrancheId();
#endif
}
hnsw_lock_tranche_id = tranche_ids[0];
LWLockRelease(AddinShmemInitLock);
#if PG_VERSION_NUM < 190000
/* Per-backend registration of the tranche ID */
LWLockRegisterTranche(hnsw_lock_tranche_id, "HnswBuild");
#endif
}
/*
@@ -138,7 +130,7 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
Relation index;
/* Never use index without order */
if (path->indexorderbys == NIL)
if (path->indexorderbys == NULL)
{
*indexStartupCost = get_float8_infinity();
*indexTotalCost = get_float8_infinity();
@@ -267,11 +259,6 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amoptsprocnum = 0;
amroutine->amcanorder = false;
amroutine->amcanorderbyop = true;
#if PG_VERSION_NUM >= 180000
amroutine->amcanhash = false;
amroutine->amconsistentequality = false;
amroutine->amconsistentordering = false;
#endif
amroutine->amcanbackward = false; /* can change direction mid-scan */
amroutine->amcanunique = false;
amroutine->amcanmulticol = false;
@@ -304,9 +291,6 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amvacuumcleanup = hnswvacuumcleanup;
amroutine->amcanreturn = NULL;
amroutine->amcostestimate = hnswcostestimate;
#if PG_VERSION_NUM >= 180000
amroutine->amgettreeheight = NULL;
#endif
amroutine->amoptions = hnswoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
amroutine->ambuildphasename = hnswbuildphasename;
@@ -327,10 +311,5 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->aminitparallelscan = NULL;
amroutine->amparallelrescan = NULL;
#if PG_VERSION_NUM >= 180000
amroutine->amtranslatestrategy = NULL;
amroutine->amtranslatecmptype = NULL;
#endif
PG_RETURN_POINTER(amroutine);
}

View File

@@ -126,7 +126,7 @@ typedef struct HnswNeighborArray HnswNeighborArray;
#define HnswPtrDeclare(type, relptrtype, ptrtype) \
relptr_declare(type, relptrtype); \
typedef union { type *ptr; relptrtype relptr; } ptrtype
typedef union { type *ptr; relptrtype relptr; } ptrtype;
/* Pointers that can be absolute or relative */
/* Use char for DatumPtr so works with Pointer */

View File

@@ -54,10 +54,6 @@
#include "utils/datum.h"
#include "utils/memutils.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h"
#else
@@ -402,7 +398,7 @@ UpdateNeighborsInMemory(char *base, HnswSupport * support, HnswElement e, int m)
* Update graph in memory
*/
static void
UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, HnswElement entryPoint, HnswBuildState * buildstate)
UpdateGraphInMemory(HnswSupport * support, HnswElement element, int m, int efConstruction, HnswElement entryPoint, HnswBuildState * buildstate)
{
HnswGraph *graph = buildstate->graph;
char *base = buildstate->hnswarea;
@@ -464,7 +460,7 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
HnswFindElementNeighbors(base, element, entryPoint, NULL, support, m, efConstruction, false);
/* Update graph in memory */
UpdateGraphInMemory(support, element, m, entryPoint, buildstate);
UpdateGraphInMemory(support, element, m, efConstruction, entryPoint, buildstate);
/* Release entry lock */
LWLockRelease(entryLock);
@@ -1058,7 +1054,7 @@ ComputeParallelWorkers(Relation heap, Relation index)
* Build graph
*/
static void
BuildGraph(HnswBuildState * buildstate)
BuildGraph(HnswBuildState * buildstate, ForkNumber forkNum)
{
int parallel_workers = 0;
@@ -1106,7 +1102,7 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
InitBuildState(buildstate, heap, index, indexInfo, forkNum);
BuildGraph(buildstate);
BuildGraph(buildstate, forkNum);
if (RelationNeedsWAL(index) || forkNum == INIT_FORKNUM)
log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true);

View File

@@ -9,10 +9,6 @@
#include "utils/datum.h"
#include "utils/memutils.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/*
* Get the insert page
*/
@@ -664,7 +660,7 @@ FindDuplicateOnDisk(Relation index, HnswElement element, bool building)
* Update graph on disk
*/
static void
UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, int m, HnswElement entryPoint, bool building)
UpdateGraphOnDisk(Relation index, HnswSupport * support, HnswElement element, int m, int efConstruction, HnswElement entryPoint, bool building)
{
BlockNumber newInsertPage = InvalidBlockNumber;
@@ -732,7 +728,7 @@ HnswInsertTupleOnDisk(Relation index, HnswSupport * support, Datum value, ItemPo
HnswFindElementNeighbors(base, element, entryPoint, index, support, m, efConstruction, false);
/* Update graph on disk */
UpdateGraphOnDisk(index, support, element, m, entryPoint, building);
UpdateGraphOnDisk(index, support, element, m, efConstruction, entryPoint, building);
/* Release lock */
UnlockPage(index, HNSW_UPDATE_LOCK, lockmode);

View File

@@ -193,10 +193,6 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
/* Count index scan for stats */
pgstat_count_index_scan(scan->indexRelation);
#if PG_VERSION_NUM >= 180000
if (scan->instrument)
scan->instrument->nsearches++;
#endif
/* Safety check */
if (scan->orderByData == NULL)

View File

@@ -15,10 +15,6 @@
#include "utils/memdebug.h"
#include "utils/rel.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM < 170000
static inline uint64
murmurhash64(uint64 data)
@@ -726,6 +722,8 @@ CountElement(HnswElement skipElement, HnswElement e)
static void
HnswLoadUnvisitedFromMemory(char *base, HnswElement element, HnswUnvisited * unvisited, int *unvisitedLength, visited_hash * v, int lc, HnswNeighborArray * localNeighborhood, Size neighborhoodSize)
{
uint32 hashes[HNSW_MAX_M * 2];
/* Get the neighborhood at layer lc */
HnswNeighborArray *neighborhood = HnswGetNeighbors(base, element, lc);
@@ -737,14 +735,33 @@ HnswLoadUnvisitedFromMemory(char *base, HnswElement element, HnswUnvisited * unv
*unvisitedLength = 0;
for (int i = 0; i < localNeighborhood->length; i++)
hashes[i] = HnswPtrAccess(base, localNeighborhood->items[i].element)->hash;
if (base != NULL)
{
HnswCandidate *hc = &localNeighborhood->items[i];
bool found;
for (int i = 0; i < localNeighborhood->length; i++)
{
HnswCandidate *hc = &localNeighborhood->items[i];
bool found;
AddToVisited(base, v, hc->element, true, &found);
offsethash_insert_hash(v->offsets, HnswPtrOffset(hc->element), hashes[i], &found);
if (!found)
unvisited[(*unvisitedLength)++].element = HnswPtrAccess(base, hc->element);
if (!found)
unvisited[(*unvisitedLength)++].element = HnswPtrAccess(base, hc->element);
}
}
else
{
for (int i = 0; i < localNeighborhood->length; i++)
{
HnswCandidate *hc = &localNeighborhood->items[i];
bool found;
pointerhash_insert_hash(v->pointers, (uintptr_t) HnswPtrPointer(hc->element), hashes[i], &found);
if (!found)
unvisited[(*unvisitedLength)++].element = HnswPtrAccess(base, hc->element);
}
}
}
@@ -829,7 +846,6 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
HnswUnvisited *unvisited = palloc(lm * sizeof(HnswUnvisited));
int unvisitedLength;
bool inMemory = index == NULL;
double lambda = 0.12;
if (v == NULL)
{
@@ -885,7 +901,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
HnswSearchCandidate *f = HnswGetSearchCandidate(w_node, pairingheap_first(W));
HnswElement cElement;
if (c->distance > f->distance * (1 + lambda))
if (c->distance > f->distance)
break;
cElement = HnswPtrAccess(base, c->element);
@@ -905,10 +921,8 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
HnswSearchCandidate *e;
double eDistance;
bool alwaysAdd = wlen < ef;
double fDistance;
f = HnswGetSearchCandidate(w_node, pairingheap_first(W));
fDistance = f->distance * (1 + lambda);
if (inMemory)
{
@@ -923,13 +937,13 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
/* Avoid any allocations if not adding */
eElement = NULL;
HnswLoadElementImpl(blkno, offno, &eDistance, q, index, support, inserting, alwaysAdd || discarded != NULL ? NULL : &fDistance, &eElement);
HnswLoadElementImpl(blkno, offno, &eDistance, q, index, support, inserting, alwaysAdd || discarded != NULL ? NULL : &f->distance, &eElement);
if (eElement == NULL)
continue;
}
if (eElement == NULL || !(eDistance < fDistance || alwaysAdd))
if (eElement == NULL || !(eDistance < f->distance || alwaysAdd))
{
if (discarded != NULL)
{
@@ -1400,7 +1414,7 @@ hnsw_halfvec_support(PG_FUNCTION_ARGS)
};
PG_RETURN_POINTER(&typeInfo);
}
};
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_bit_support);
Datum
@@ -1413,7 +1427,7 @@ hnsw_bit_support(PG_FUNCTION_ARGS)
};
PG_RETURN_POINTER(&typeInfo);
}
};
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_sparsevec_support);
Datum
@@ -1426,4 +1440,4 @@ hnsw_sparsevec_support(PG_FUNCTION_ARGS)
};
PG_RETURN_POINTER(&typeInfo);
}
};

View File

@@ -9,14 +9,6 @@
#include "storage/lmgr.h"
#include "utils/memutils.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 180000
#define vacuum_delay_point() vacuum_delay_point(false)
#endif
/*
* Check if deleted list contains an index TID
*/

View File

@@ -20,10 +20,6 @@
#include "utils/memutils.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h"
#else
@@ -142,7 +138,7 @@ SampleRows(IvfflatBuildState * buildstate)
* Add tuple to sort
*/
static void
AddTupleToSort(ItemPointer tid, Datum *values, IvfflatBuildState * buildstate)
AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState * buildstate)
{
double distance;
double minDistance = DBL_MAX;
@@ -219,7 +215,7 @@ BuildCallback(Relation index, ItemPointer tid, Datum *values,
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
/* Add tuple to sort */
AddTupleToSort(tid, values, buildstate);
AddTupleToSort(index, tid, values, buildstate);
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
@@ -364,7 +360,7 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->sortdesc = CreateTemplateTupleDesc(3);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 1, "list", INT4OID, -1, 0);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 3, "vector", TupleDescAttr(buildstate->tupdesc, 0)->atttypid, -1, 0);
TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 3, "vector", buildstate->tupdesc->attrs[0].atttypid, -1, 0);
buildstate->slot = MakeSingleTupleTableSlot(buildstate->sortdesc, &TTSOpsVirtual);
@@ -474,8 +470,8 @@ CreateMetaPage(Relation index, int dimensions, int lists, ForkNumber forkNum)
* Create list pages
*/
static void
CreateListPages(Relation index, VectorArray centers, int lists,
ForkNumber forkNum, ListInfo * *listInfo)
CreateListPages(Relation index, VectorArray centers, int dimensions,
int lists, ForkNumber forkNum, ListInfo * *listInfo)
{
Buffer buf;
Page page;
@@ -1008,7 +1004,7 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
/* Create pages */
CreateMetaPage(index, buildstate->dimensions, buildstate->lists, forkNum);
CreateListPages(index, buildstate->centers, buildstate->lists, forkNum, &buildstate->listInfo);
CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo);
CreateEntryPages(buildstate, forkNum);
/* Write WAL for initialization fork since GenericXLog functions do not */
@@ -1027,10 +1023,6 @@ ivfflatbuild(Relation heap, Relation index, IndexInfo *indexInfo)
IndexBuildResult *result;
IvfflatBuildState buildstate;
#ifdef IVFFLAT_BENCH
SeedRandom(42);
#endif
BuildIndex(heap, index, indexInfo, &buildstate, MAIN_FORKNUM);
result = (IndexBuildResult *) palloc(sizeof(IndexBuildResult));

View File

@@ -92,7 +92,7 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
Relation index;
/* Never use index without order */
if (path->indexorderbys == NIL)
if (path->indexorderbys == NULL)
{
*indexStartupCost = get_float8_infinity();
*indexTotalCost = get_float8_infinity();
@@ -186,11 +186,6 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amoptsprocnum = 0;
amroutine->amcanorder = false;
amroutine->amcanorderbyop = true;
#if PG_VERSION_NUM >= 180000
amroutine->amcanhash = false;
amroutine->amconsistentequality = false;
amroutine->amconsistentordering = false;
#endif
amroutine->amcanbackward = false; /* can change direction mid-scan */
amroutine->amcanunique = false;
amroutine->amcanmulticol = false;
@@ -223,9 +218,6 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amvacuumcleanup = ivfflatvacuumcleanup;
amroutine->amcanreturn = NULL; /* tuple not included in heapsort */
amroutine->amcostestimate = ivfflatcostestimate;
#if PG_VERSION_NUM >= 180000
amroutine->amgettreeheight = NULL;
#endif
amroutine->amoptions = ivfflatoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
amroutine->ambuildphasename = ivfflatbuildphasename;
@@ -246,10 +238,5 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->aminitparallelscan = NULL;
amroutine->amparallelrescan = NULL;
#if PG_VERSION_NUM >= 180000
amroutine->amtranslatestrategy = NULL;
amroutine->amtranslatecmptype = NULL;
#endif
PG_RETURN_POINTER(amroutine);
}

View File

@@ -13,10 +13,6 @@
#include "utils/tuplesort.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
#if PG_VERSION_NUM >= 150000
#include "common/pg_prng.h"
#endif
@@ -77,11 +73,9 @@
#if PG_VERSION_NUM >= 150000
#define RandomDouble() pg_prng_double(&pg_global_prng_state)
#define RandomInt() pg_prng_uint32(&pg_global_prng_state)
#define SeedRandom(seed) pg_prng_seed(&pg_global_prng_state, seed)
#else
#define RandomDouble() (((double) random()) / MAX_RANDOM_VALUE)
#define RandomInt() random()
#define SeedRandom(seed) srandom(seed)
#endif
/* Variables */

View File

@@ -65,7 +65,7 @@ FindInsertPage(Relation index, Datum *values, BlockNumber *insertPage, ListInfo
* Insert a tuple into the index
*/
static void
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid)
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
{
const IvfflatTypeInfo *typeInfo = IvfflatGetTypeInfo(index);
IndexTuple itup;
@@ -204,7 +204,7 @@ ivfflatinsert(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid,
oldCtx = MemoryContextSwitchTo(insertCtx);
/* Insert tuple */
InsertTuple(index, values, isnull, heap_tid);
InsertTuple(index, values, isnull, heap_tid, heap);
/* Delete memory context */
MemoryContextSwitchTo(oldCtx);

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

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@@ -355,10 +355,6 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
/* Count index scan for stats */
pgstat_count_index_scan(scan->indexRelation);
#if PG_VERSION_NUM >= 180000
if (scan->instrument)
scan->instrument->nsearches++;
#endif
/* Safety check */
if (scan->orderByData == NULL)

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

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

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@@ -4,7 +4,6 @@
#include <math.h>
#include "catalog/pg_type.h"
#include "common/shortest_dec.h"
#include "common/string.h"
#include "fmgr.h"
#include "halfutils.h"
@@ -13,10 +12,17 @@
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
#include "utils/lsyscache.h"
#include "vector.h"
#if PG_VERSION_NUM >= 120000
#include "common/shortest_dec.h"
#include "utils/float.h"
#else
#include <float.h>
#include "utils/builtins.h"
#endif
typedef struct SparseInputElement
{
int32 index;

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

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

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@@ -123,12 +123,6 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
[0,0,0]
(3 rows)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
RESET hnsw.iterative_scan;
RESET hnsw.ef_search;
DROP TABLE t;

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@@ -110,15 +110,6 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
[1,1,1]
(2 rows)
TRUNCATE t;
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
RESET ivfflat.iterative_scan;
RESET ivfflat.max_probes;
DROP TABLE t;

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

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

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@@ -70,9 +70,6 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SET hnsw.iterative_scan = relaxed_order;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
RESET hnsw.iterative_scan;
RESET hnsw.ef_search;
DROP TABLE t;

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@@ -59,9 +59,6 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SET ivfflat.max_probes = 2;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
RESET ivfflat.iterative_scan;
RESET ivfflat.max_probes;
DROP TABLE t;

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

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