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Author SHA1 Message Date
Andrew Kane
c8e4bf1c3c Added test for arrays 2024-02-03 16:50:17 -08:00
26 changed files with 231 additions and 343 deletions

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@@ -28,7 +28,7 @@ jobs:
dev-files: true dev-files: true
- run: make - run: make
env: env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
- run: | - run: |
export PG_CONFIG=`which pg_config` export PG_CONFIG=`which pg_config`
sudo --preserve-env=PG_CONFIG make install sudo --preserve-env=PG_CONFIG make install
@@ -49,7 +49,7 @@ jobs:
postgres-version: 14 postgres-version: 14
- run: make - run: make
env: env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter
- run: make install - run: make install
- run: make installcheck - run: make installcheck
- if: ${{ failure() }} - if: ${{ failure() }}
@@ -60,9 +60,7 @@ jobs:
wget -q https://github.com/postgres/postgres/archive/refs/tags/REL_14_10.tar.gz wget -q https://github.com/postgres/postgres/archive/refs/tags/REL_14_10.tar.gz
tar xf 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 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 - run: make clean && /usr/local/opt/llvm@15/bin/scan-build --status-bugs make PG_CFLAGS="-DUSE_ASSERT_CHECKING"
env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING
windows: windows:
runs-on: windows-latest runs-on: windows-latest
if: ${{ !startsWith(github.ref_name, 'mac') }} if: ${{ !startsWith(github.ref_name, 'mac') }}
@@ -73,7 +71,6 @@ jobs:
postgres-version: 14 postgres-version: 14
- run: | - run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^ 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 && ^
nmake /NOLOGO /F Makefile.win install && ^ nmake /NOLOGO /F Makefile.win install && ^
nmake /NOLOGO /F Makefile.win installcheck && ^ nmake /NOLOGO /F Makefile.win installcheck && ^
@@ -100,15 +97,4 @@ jobs:
sudo -u postgres make installcheck sudo -u postgres make installcheck
sudo -u postgres make prove_installcheck sudo -u postgres make prove_installcheck
env: env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare PG_CFLAGS: -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

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@@ -1,12 +1,6 @@
## 0.6.2 (2024-03-18) ## 0.6.1 (unreleased)
- Reduced lock contention with parallel HNSW index builds
## 0.6.1 (2024-03-04)
- Fixed error with `ANALYZE` and vectors with different dimensions - 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) ## 0.6.0 (2024-01-29)

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

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

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@@ -1,5 +1,5 @@
EXTENSION = vector EXTENSION = vector
EXTVERSION = 0.6.2 EXTVERSION = 0.6.0
MODULE_big = vector MODULE_big = vector
DATA = $(wildcard sql/*--*.sql) DATA = $(wildcard sql/*--*.sql)
@@ -10,15 +10,21 @@ TESTS = $(wildcard test/sql/*.sql)
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS)) REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION) REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
OPTFLAGS =
# Since runtime dispatch not supported
ifeq ($(shell uname -s), Darwin)
ifeq ($(shell uname -m), x86_64)
OPTFLAGS = -march=native OPTFLAGS = -march=native
# Mac ARM doesn't support -march=native
ifeq ($(shell uname -s), Darwin)
ifeq ($(shell uname -p), arm)
# no difference with -march=armv8.5-a
OPTFLAGS =
endif endif
endif endif
# PowerPC doesn't support -march=native
ifneq ($(filter ppc64%, $(shell uname -m)), )
OPTFLAGS =
endif
# For auto-vectorization: # For auto-vectorization:
# - GCC (needs -ftree-vectorize OR -O3) - https://gcc.gnu.org/projects/tree-ssa/vectorization.html # - GCC (needs -ftree-vectorize OR -O3) - https://gcc.gnu.org/projects/tree-ssa/vectorization.html
# - Clang (could use pragma instead) - https://llvm.org/docs/Vectorizers.html # - Clang (could use pragma instead) - https://llvm.org/docs/Vectorizers.html
@@ -65,9 +71,11 @@ PG_MAJOR ?= 16
.PHONY: docker .PHONY: docker
docker: docker:
docker build --pull --no-cache --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) . docker build --pull --no-cache --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) .
docker build --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .
.PHONY: docker-release .PHONY: docker-release
docker-release: docker-release:
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) . docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) .
docker buildx build --push --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .

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@@ -1,5 +1,5 @@
EXTENSION = vector EXTENSION = vector
EXTVERSION = 0.6.2 EXTVERSION = 0.6.0
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 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 HEADERS = src\vector.h

175
README.md
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@@ -20,15 +20,15 @@ Compile and install the extension (supports Postgres 12+)
```sh ```sh
cd /tmp cd /tmp
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git git clone --branch v0.6.0 https://github.com/pgvector/pgvector.git
cd pgvector cd pgvector
make make
make install # may need sudo make install # may need sudo
``` ```
See the [installation notes](#installation-notes---linux-and-mac) if you run into issues See the [installation notes](#installation-notes) if you run into issues
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). 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).
### Windows ### Windows
@@ -44,15 +44,12 @@ Then use `nmake` to build:
```cmd ```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16" set "PGROOT=C:\Program Files\PostgreSQL\16"
cd %TEMP% 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 cd pgvector
nmake /F Makefile.win nmake /F Makefile.win
nmake /F Makefile.win install 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). You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
## Getting Started ## Getting Started
@@ -105,12 +102,6 @@ Insert vectors
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]'); 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 Upsert vectors
```sql ```sql
@@ -273,8 +264,6 @@ 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 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) Starting with 0.6.0, you can also speed up index creation by increasing the number of parallel workers (2 by default)
```sql ```sql
@@ -413,39 +402,13 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python
## Performance ## Performance
### Tuning
Use a tool like [PgTune](https://pgtune.leopard.in.ua/) to set initial values for Postgres server parameters.
### 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. Use `EXPLAIN ANALYZE` to debug performance.
```sql ```sql
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5; EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
``` ```
#### Exact Search ### Exact Search
To speed up queries without an index, increase `max_parallel_workers_per_gather`. To speed up queries without an index, increase `max_parallel_workers_per_gather`.
@@ -459,7 +422,7 @@ If vectors are normalized to length 1 (like [OpenAI embeddings](https://platform
SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5; 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). To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
@@ -467,7 +430,7 @@ 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); CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 1000);
``` ```
### Vacuuming ## Vacuuming
Vacuuming can take a while for HNSW indexes. Speed it up by reindexing first. Vacuuming can take a while for HNSW indexes. Speed it up by reindexing first.
@@ -476,41 +439,6 @@ REINDEX INDEX CONCURRENTLY index_name;
VACUUM table_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 ## Languages
Use pgvector from any language with a Postgres client. You can even generate and store vectors in one language and query them in another. Use pgvector from any language with a Postgres client. You can even generate and store vectors in one language and query them in another.
@@ -604,18 +532,6 @@ and query with:
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5; 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? #### 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: No, but like other index types, youll likely see better performance if they do. You can get the size of an index with:
@@ -628,17 +544,7 @@ SELECT pg_size_pretty(pg_relation_size('index_name'));
#### Why isnt a query using an index? #### Why isnt a query using an index?
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. 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:
```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 ```sql
BEGIN; BEGIN;
@@ -667,12 +573,6 @@ or choose to store vectors inline:
ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN; 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? #### 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. The index was likely created with too little data for the number of lists. Drop the index until the table has more data.
@@ -681,15 +581,11 @@ The index was likely created with too little data for the number of lists. Drop
DROP INDEX index_name; DROP INDEX index_name;
``` ```
Results can also be limited by the number of probes (`ivfflat.probes`).
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
## Reference ## Reference
### Vector 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 ### Vector Operators
@@ -713,14 +609,14 @@ l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
vector_dims(vector) → integer | number of dimensions | vector_dims(vector) → integer | number of dimensions |
vector_norm(vector) → double precision | Euclidean norm | vector_norm(vector) → double precision | Euclidean norm |
### Vector Aggregate Functions ### Aggregate Functions
Function | Description | Added Function | Description | Added
--- | --- | --- --- | --- | ---
avg(vector) → vector | average | avg(vector) → vector | average |
sum(vector) → vector | sum | 0.5.0 sum(vector) → vector | sum | 0.5.0
## Installation Notes - Linux and Mac ## Installation Notes
### Postgres Location ### Postgres Location
@@ -760,26 +656,6 @@ 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. 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 ## Additional Installation Methods
### Docker ### Docker
@@ -795,7 +671,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
You can also build the image manually: You can also build the image manually:
```sh ```sh
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git git clone --branch v0.6.0 https://github.com/pgvector/pgvector.git
cd pgvector cd pgvector
docker build --build-arg PG_MAJOR=16 -t myuser/pgvector . docker build --build-arg PG_MAJOR=16 -t myuser/pgvector .
``` ```
@@ -840,21 +716,6 @@ sudo dnf install pgvector_16
Note: Replace `16` with your Postgres server version 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 ### conda-forge
With Conda Postgres, install from [conda-forge](https://anaconda.org/conda-forge/pgvector) with: With Conda Postgres, install from [conda-forge](https://anaconda.org/conda-forge/pgvector) with:
@@ -964,12 +825,6 @@ make installcheck REGRESS=functions # regression test
make prove_installcheck PROVE_TESTS=test/t/001_ivfflat_wal.pl # TAP 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: To enable benchmarking:
```sh ```sh
@@ -982,6 +837,12 @@ To show memory usage:
make clean && PG_CFLAGS="-DHNSW_MEMORY -DIVFFLAT_MEMORY" make && make install 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: To get k-means metrics:
```sh ```sh

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@@ -1,16 +0,0 @@
-- 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

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

@@ -180,7 +180,8 @@ CREATE OPERATOR + (
); );
CREATE OPERATOR - ( CREATE OPERATOR - (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub,
COMMUTATOR = -
); );
CREATE OPERATOR * ( CREATE OPERATOR * (
@@ -194,10 +195,11 @@ CREATE OPERATOR < (
RESTRICT = scalarltsel, JOIN = scalarltjoinsel RESTRICT = scalarltsel, JOIN = scalarltjoinsel
); );
-- should use scalarlesel and scalarlejoinsel, but not supported in Postgres < 11
CREATE OPERATOR <= ( CREATE OPERATOR <= (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_le, LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_le,
COMMUTATOR = >= , NEGATOR = > , COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarlesel, JOIN = scalarlejoinsel RESTRICT = scalarltsel, JOIN = scalarltjoinsel
); );
CREATE OPERATOR = ( CREATE OPERATOR = (
@@ -212,10 +214,11 @@ CREATE OPERATOR <> (
RESTRICT = eqsel, JOIN = eqjoinsel RESTRICT = eqsel, JOIN = eqjoinsel
); );
-- should use scalargesel and scalargejoinsel, but not supported in Postgres < 11
CREATE OPERATOR >= ( CREATE OPERATOR >= (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_ge, LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_ge,
COMMUTATOR = <= , NEGATOR = < , COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargesel, JOIN = scalargejoinsel RESTRICT = scalargtsel, JOIN = scalargtjoinsel
); );
CREATE OPERATOR > ( CREATE OPERATOR > (

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

View File

@@ -80,7 +80,7 @@
#if PG_VERSION_NUM < 130000 #if PG_VERSION_NUM < 130000
#define list_delete_last(list) list_truncate(list, list_length(list) - 1) #define list_delete_last(list) list_truncate(list, list_length(list) - 1)
#define list_sort(list, cmp) ((list) = list_qsort(list, cmp)) #define list_sort(list, cmp) list_qsort(list, cmp)
#endif #endif
#define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE) #define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
@@ -129,7 +129,7 @@ HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr)
HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr); HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
HnswPtrDeclare(char, DatumRelptr, DatumPtr); HnswPtrDeclare(char, DatumRelptr, DatumPtr);
struct HnswElementData typedef struct HnswElementData
{ {
HnswElementPtr next; HnswElementPtr next;
ItemPointerData heaptids[HNSW_HEAPTIDS]; ItemPointerData heaptids[HNSW_HEAPTIDS];
@@ -144,7 +144,7 @@ struct HnswElementData
BlockNumber neighborPage; BlockNumber neighborPage;
DatumPtr value; DatumPtr value;
LWLock lock; LWLock lock;
}; } HnswElementData;
typedef HnswElementData * HnswElement; typedef HnswElementData * HnswElement;
@@ -155,12 +155,12 @@ typedef struct HnswCandidate
bool closer; bool closer;
} HnswCandidate; } HnswCandidate;
struct HnswNeighborArray typedef struct HnswNeighborArray
{ {
int length; int length;
bool closerSet; bool closerSet;
HnswCandidate items[FLEXIBLE_ARRAY_MEMBER]; HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
}; } HnswNeighborArray;
typedef struct HnswPairingHeapNode typedef struct HnswPairingHeapNode
{ {
@@ -185,7 +185,6 @@ typedef struct HnswGraph
/* Entry state */ /* Entry state */
LWLock entryLock; LWLock entryLock;
LWLock entryWaitLock;
HnswElementPtr entryPoint; HnswElementPtr entryPoint;
/* Allocations state */ /* Allocations state */
@@ -262,6 +261,7 @@ typedef struct HnswBuildState
HnswGraph *graph; HnswGraph *graph;
double ml; double ml;
int maxLevel; int maxLevel;
Vector *normvec;
/* Memory */ /* Memory */
MemoryContext graphCtx; MemoryContext graphCtx;
@@ -366,7 +366,7 @@ typedef struct HnswVacuumState
int HnswGetM(Relation index); int HnswGetM(Relation index);
int HnswGetEfConstruction(Relation index); int HnswGetEfConstruction(Relation index);
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum); FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value); bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum); Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
void HnswInitPage(Buffer buf, Page page); void HnswInitPage(Buffer buf, Page page);
void HnswInit(void); void HnswInit(void);
@@ -389,7 +389,6 @@ void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation i
void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element); 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 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 HnswLoadNeighbors(HnswElement element, Relation index, int m);
void HnswInitLockTranche(void);
PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc); PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);
/* Index access methods */ /* Index access methods */

View File

@@ -176,7 +176,7 @@ CreateGraphPages(HnswBuildState * buildstate)
Size etupSize; Size etupSize;
Size ntupSize; Size ntupSize;
Size combinedSize; Size combinedSize;
Pointer valuePtr = HnswPtrAccess(base, element->value); void *valuePtr = HnswPtrAccess(base, element->value);
/* Update iterator */ /* Update iterator */
iter = element->next; iter = element->next;
@@ -431,15 +431,10 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
HnswGraph *graph = buildstate->graph; HnswGraph *graph = buildstate->graph;
HnswElement entryPoint; HnswElement entryPoint;
LWLock *entryLock = &graph->entryLock; LWLock *entryLock = &graph->entryLock;
LWLock *entryWaitLock = &graph->entryWaitLock;
int efConstruction = buildstate->efConstruction; int efConstruction = buildstate->efConstruction;
int m = buildstate->m; int m = buildstate->m;
char *base = buildstate->hnswarea; char *base = buildstate->hnswarea;
/* Wait if another process needs exclusive lock on entry lock */
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
LWLockRelease(entryWaitLock);
/* Get entry point */ /* Get entry point */
LWLockAcquire(entryLock, LW_SHARED); LWLockAcquire(entryLock, LW_SHARED);
entryPoint = HnswPtrAccess(base, graph->entryPoint); entryPoint = HnswPtrAccess(base, graph->entryPoint);
@@ -450,10 +445,8 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
/* Release shared lock */ /* Release shared lock */
LWLockRelease(entryLock); LWLockRelease(entryLock);
/* Tell other processes to wait and get exclusive lock */ /* Get exclusive lock */
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
LWLockAcquire(entryLock, LW_EXCLUSIVE); LWLockAcquire(entryLock, LW_EXCLUSIVE);
LWLockRelease(entryWaitLock);
/* Get latest entry point after lock is acquired */ /* Get latest entry point after lock is acquired */
entryPoint = HnswPtrAccess(base, graph->entryPoint); entryPoint = HnswPtrAccess(base, graph->entryPoint);
@@ -489,7 +482,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
/* Normalize if needed */ /* Normalize if needed */
if (buildstate->normprocinfo != NULL) if (buildstate->normprocinfo != NULL)
{ {
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value)) if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
return false; return false;
} }
@@ -608,9 +601,6 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
static void static void
InitGraph(HnswGraph * graph, char *base, long memoryTotal) InitGraph(HnswGraph * graph, char *base, long memoryTotal)
{ {
/* Initialize the lock tranche if needed */
HnswInitLockTranche();
HnswPtrStore(base, graph->head, (HnswElement) NULL); HnswPtrStore(base, graph->head, (HnswElement) NULL);
HnswPtrStore(base, graph->entryPoint, (HnswElement) NULL); HnswPtrStore(base, graph->entryPoint, (HnswElement) NULL);
graph->memoryUsed = 0; graph->memoryUsed = 0;
@@ -619,7 +609,6 @@ InitGraph(HnswGraph * graph, char *base, long memoryTotal)
graph->indtuples = 0; graph->indtuples = 0;
SpinLockInit(&graph->lock); SpinLockInit(&graph->lock);
LWLockInitialize(&graph->entryLock, hnsw_lock_tranche_id); LWLockInitialize(&graph->entryLock, hnsw_lock_tranche_id);
LWLockInitialize(&graph->entryWaitLock, hnsw_lock_tranche_id);
LWLockInitialize(&graph->allocatorLock, hnsw_lock_tranche_id); LWLockInitialize(&graph->allocatorLock, hnsw_lock_tranche_id);
LWLockInitialize(&graph->flushLock, hnsw_lock_tranche_id); LWLockInitialize(&graph->flushLock, hnsw_lock_tranche_id);
} }
@@ -680,10 +669,6 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->efConstruction = HnswGetEfConstruction(index); buildstate->efConstruction = HnswGetEfConstruction(index);
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod; buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
/* 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) if (buildstate->dimensions > HNSW_MAX_DIM)
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", HNSW_MAX_DIM); elog(ERROR, "column cannot have more than %d dimensions for hnsw index", HNSW_MAX_DIM);
@@ -703,6 +688,9 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->ml = HnswGetMl(buildstate->m); buildstate->ml = HnswGetMl(buildstate->m);
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m); buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
/* Reuse for each tuple */
buildstate->normvec = InitVector(buildstate->dimensions);
buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext, buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext,
"Hnsw build graph context", "Hnsw build graph context",
#if PG_VERSION_NUM >= 150000 #if PG_VERSION_NUM >= 150000
@@ -726,6 +714,7 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
static void static void
FreeBuildState(HnswBuildState * buildstate) FreeBuildState(HnswBuildState * buildstate)
{ {
pfree(buildstate->normvec);
MemoryContextDelete(buildstate->graphCtx); MemoryContextDelete(buildstate->graphCtx);
MemoryContextDelete(buildstate->tmpCtx); MemoryContextDelete(buildstate->tmpCtx);
} }
@@ -981,14 +970,6 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
/* Report less than allocated so never fails */ /* Report less than allocated so never fails */
InitGraph(&hnswshared->graphData, hnswarea, esthnswarea - 1024 * 1024); 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_SHARED, hnswshared);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_HNSW_AREA, hnswarea); shm_toc_insert(pcxt->toc, PARALLEL_KEY_HNSW_AREA, hnswarea);

View File

@@ -622,7 +622,7 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC); normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
if (normprocinfo != NULL) if (normprocinfo != NULL)
{ {
if (!HnswNormValue(normprocinfo, collation, &value)) if (!HnswNormValue(normprocinfo, collation, &value, NULL))
return; return;
} }

View File

@@ -84,7 +84,7 @@ GetScanValue(IndexScanDesc scan)
/* Fine if normalization fails */ /* Fine if normalization fails */
if (so->normprocinfo != NULL) if (so->normprocinfo != NULL)
HnswNormValue(so->normprocinfo, so->collation, &value); HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
} }
return value; return value;

View File

@@ -158,14 +158,16 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
* if it's different than the original value * if it's different than the original value
*/ */
bool bool
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value) HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
{ {
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value)); double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0) if (norm > 0)
{ {
Vector *v = DatumGetVector(*value); Vector *v = DatumGetVector(*value);
Vector *result = InitVector(v->dim);
if (result == NULL)
result = InitVector(v->dim);
for (int i = 0; i < v->dim; i++) for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm; result->x[i] = v->x[i] / norm;
@@ -858,15 +860,12 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
static int static int
#if PG_VERSION_NUM >= 130000 #if PG_VERSION_NUM >= 130000
CompareCandidateDistances(const ListCell *a, const ListCell *b) CompareCandidateDistances(const ListCell *a, const ListCell *b)
{
HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b);
#else #else
CompareCandidateDistances(const void *a, const void *b) CompareCandidateDistances(const void *a, const void *b)
{
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif #endif
{
HnswCandidate *hca = lfirst((ListCell *) a);
HnswCandidate *hcb = lfirst((ListCell *) b);
if (hca->distance < hcb->distance) if (hca->distance < hcb->distance)
return 1; return 1;
@@ -889,15 +888,12 @@ CompareCandidateDistances(const void *a, const void *b)
static int static int
#if PG_VERSION_NUM >= 130000 #if PG_VERSION_NUM >= 130000
CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b) CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b)
{
HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b);
#else #else
CompareCandidateDistancesOffset(const void *a, const void *b) CompareCandidateDistancesOffset(const void *a, const void *b)
{
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif #endif
{
HnswCandidate *hca = lfirst((ListCell *) a);
HnswCandidate *hcb = lfirst((ListCell *) b);
if (hca->distance < hcb->distance) if (hca->distance < hcb->distance)
return 1; return 1;
@@ -956,9 +952,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
{ {
List *r = NIL; List *r = NIL;
List *w = list_copy(c); List *w = list_copy(c);
HnswCandidate **wd; pairingheap *wd;
int wdlen = 0;
int wdoff = 0;
HnswNeighborArray *neighbors = HnswGetNeighbors(base, e2, lc); HnswNeighborArray *neighbors = HnswGetNeighbors(base, e2, lc);
bool mustCalculate = !neighbors->closerSet; bool mustCalculate = !neighbors->closerSet;
List *added = NIL; List *added = NIL;
@@ -967,7 +961,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
if (list_length(w) <= lm) if (list_length(w) <= lm)
return w; return w;
wd = palloc(sizeof(HnswCandidate *) * list_length(w)); wd = pairingheap_allocate(CompareNearestCandidates, NULL);
/* Ensure order of candidates is deterministic for closer caching */ /* Ensure order of candidates is deterministic for closer caching */
if (sortCandidates) if (sortCandidates)
@@ -1033,21 +1027,21 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
if (e->closer) if (e->closer)
r = lappend(r, e); r = lappend(r, e);
else else
wd[wdlen++] = e; pairingheap_add(wd, &(CreatePairingHeapNode(e)->ph_node));
} }
/* Cached value can only be used in future if sorted deterministically */ /* Cached value can only be used in future if sorted deterministically */
neighbors->closerSet = sortCandidates; neighbors->closerSet = sortCandidates;
/* Keep pruned connections */ /* Keep pruned connections */
while (wdoff < wdlen && list_length(r) < lm) while (!pairingheap_is_empty(wd) && list_length(r) < lm)
r = lappend(r, wd[wdoff++]); r = lappend(r, ((HnswPairingHeapNode *) pairingheap_remove_first(wd))->inner);
/* Return pruned for update connections */ /* Return pruned for update connections */
if (pruned != NULL) if (pruned != NULL)
{ {
if (wdoff < wdlen) if (!pairingheap_is_empty(wd))
*pruned = wd[wdoff]; *pruned = ((HnswPairingHeapNode *) pairingheap_first(wd))->inner;
else else
*pruned = linitial(w); *pruned = linitial(w);
} }

View File

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

View File

@@ -172,6 +172,7 @@ typedef struct IvfflatBuildState
VectorArray samples; VectorArray samples;
VectorArray centers; VectorArray centers;
ListInfo *listInfo; ListInfo *listInfo;
Vector *normvec;
#ifdef IVFFLAT_KMEANS_DEBUG #ifdef IVFFLAT_KMEANS_DEBUG
double inertia; double inertia;
@@ -266,7 +267,7 @@ void VectorArrayFree(VectorArray arr);
void PrintVectorArray(char *msg, VectorArray arr); void PrintVectorArray(char *msg, VectorArray arr);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers); void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum); FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value); bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
int IvfflatGetLists(Relation index); int IvfflatGetLists(Relation index);
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions); void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum); 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); normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL) if (normprocinfo != NULL)
{ {
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value)) if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
return; return;
} }

View File

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

View File

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

View File

@@ -29,15 +29,6 @@
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1) #define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1)) #define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
#if defined(__x86_64__) && defined(__gnu_linux__) && defined(__has_attribute) && __has_attribute(target_clones)
#define RUNTIME_DISPATCH __attribute__((target_clones("default", "avx", "fma", "avx512f")))
#elif defined(__aarch64__) && defined(__gnu_linux__) && defined(__has_attribute) && __has_attribute(target_clones)
/* TODO Fix error: target does not support function version dispatcher */
#define RUNTIME_DISPATCH __attribute__((target_clones("default", "arch=armv8.5-a")))
#else
#define RUNTIME_DISPATCH
#endif
PG_MODULE_MAGIC; PG_MODULE_MAGIC;
/* /*
@@ -541,23 +532,6 @@ vector_to_float4(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
RUNTIME_DISPATCH
static float
l2_squared_distance_impl(int16 dim, float *ax, float *bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int16 i = 0; i < dim; i++)
{
float diff = ax[i] - bx[i];
distance += diff * diff;
}
return distance;
}
/* /*
* Get the L2 distance between vectors * Get the L2 distance between vectors
*/ */
@@ -567,11 +541,19 @@ l2_distance(PG_FUNCTION_ARGS)
{ {
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
float distance; float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
float diff;
CheckDims(a, b); CheckDims(a, b);
distance = l2_squared_distance_impl(a->dim, a->x, b->x); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
diff = ax[i] - bx[i];
distance += diff * diff;
}
PG_RETURN_FLOAT8(sqrt((double) distance)); PG_RETURN_FLOAT8(sqrt((double) distance));
} }
@@ -586,11 +568,19 @@ vector_l2_squared_distance(PG_FUNCTION_ARGS)
{ {
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
float distance; float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
float diff;
CheckDims(a, b); CheckDims(a, b);
distance = l2_squared_distance_impl(a->dim, a->x, b->x); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
diff = ax[i] - bx[i];
distance += diff * diff;
}
PG_RETURN_FLOAT8((double) distance); PG_RETURN_FLOAT8((double) distance);
} }

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@@ -116,30 +116,8 @@ SELECT '[1, ,3]'::vector;
ERROR: invalid input syntax for type vector: "[1, ,3]" ERROR: invalid input syntax for type vector: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::vector; LINE 1: SELECT '[1, ,3]'::vector;
^ ^
SELECT '[1,2,3]'::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector(2); SELECT '[1,2,3]'::vector(2);
ERROR: expected 2 dimensions, not 3 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[]); SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
unnest unnest
--------- ---------

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@@ -22,13 +22,7 @@ SELECT '[1,]'::vector;
SELECT '[1a]'::vector; SELECT '[1a]'::vector;
SELECT '[1,,3]'::vector; SELECT '[1,,3]'::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(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 unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
SELECT '{"[1,2,3]"}'::vector(2)[]; SELECT '{"[1,2,3]"}'::vector(2)[];

113
test/t/020_hnsw_array.pl Normal file
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@@ -0,0 +1,113 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
sub test_recall
{
my ($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 float4[3]);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 10000) i;"
);
$node->safe_psql("postgres", qq(
CREATE FUNCTION float4_l2_distance(float4[], float4[]) RETURNS float8
AS 'BEGIN RETURN l2_distance(\$1::vector, \$2::vector); END;'
LANGUAGE plpgsql IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION float4_l2_squared_distance(float4[], float4[]) RETURNS float8
AS 'BEGIN RETURN vector_l2_squared_distance(\$1::vector, \$2::vector); END;'
LANGUAGE plpgsql IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <-> (
LEFTARG = float4[], RIGHTARG = float4[], PROCEDURE = float4_l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR CLASS float4_l2_ops
FOR TYPE float4[] USING hnsw AS
OPERATOR 1 <-> (float4[], float4[]) FOR ORDER BY float_ops,
FUNCTION 1 float4_l2_squared_distance(float4[], float4[]);
));
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "{$r1,$r2,$r3}");
}
# Check each index type
my @operators = ("<->");
my @opclasses = ("float4_l2_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);
}
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v $opclass);");
my $min = $operator eq "<#>" ? 0.80 : 0.99;
test_recall($min, $operator);
}
done_testing();

View File

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