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https://github.com/pgvector/pgvector.git
synced 2026-07-22 12:07:34 +08:00
Compare commits
4 Commits
sparsevec
...
hamming-di
| Author | SHA1 | Date | |
|---|---|---|---|
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76418fc093 | ||
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34d5a8cf3f | ||
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f9ae736c57 | ||
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76c6dbb0a0 |
28
.github/workflows/build.yml
vendored
28
.github/workflows/build.yml
vendored
@@ -28,7 +28,7 @@ jobs:
|
||||
dev-files: true
|
||||
- run: make
|
||||
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: |
|
||||
export PG_CONFIG=`which pg_config`
|
||||
sudo --preserve-env=PG_CONFIG make install
|
||||
@@ -49,7 +49,7 @@ jobs:
|
||||
postgres-version: 14
|
||||
- run: make
|
||||
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 installcheck
|
||||
- if: ${{ failure() }}
|
||||
@@ -57,12 +57,10 @@ jobs:
|
||||
- run: |
|
||||
brew install cpanm
|
||||
cpanm --notest IPC::Run
|
||||
wget -q https://github.com/postgres/postgres/archive/refs/tags/REL_14_10.tar.gz
|
||||
tar xf REL_14_10.tar.gz
|
||||
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres-REL_14_10/src/test/perl" PERL5LIB="/Users/runner/perl5/lib/perl5"
|
||||
- run: make clean && /usr/local/opt/llvm@15/bin/scan-build --status-bugs make
|
||||
env:
|
||||
PG_CFLAGS: -DUSE_ASSERT_CHECKING
|
||||
wget -q https://github.com/postgres/postgres/archive/refs/tags/REL_14_5.tar.gz
|
||||
tar xf REL_14_5.tar.gz
|
||||
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres-REL_14_5/src/test/perl" PERL5LIB="/Users/runner/perl5/lib/perl5"
|
||||
- run: make clean && /usr/local/opt/llvm@15/bin/scan-build --status-bugs make PG_CFLAGS="-DUSE_ASSERT_CHECKING"
|
||||
windows:
|
||||
runs-on: windows-latest
|
||||
if: ${{ !startsWith(github.ref_name, 'mac') }}
|
||||
@@ -73,7 +71,6 @@ jobs:
|
||||
postgres-version: 14
|
||||
- run: |
|
||||
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
|
||||
cd %TEMP% && ^
|
||||
nmake /NOLOGO /F Makefile.win && ^
|
||||
nmake /NOLOGO /F Makefile.win install && ^
|
||||
nmake /NOLOGO /F Makefile.win installcheck && ^
|
||||
@@ -100,15 +97,4 @@ jobs:
|
||||
sudo -u postgres make installcheck
|
||||
sudo -u postgres make prove_installcheck
|
||||
env:
|
||||
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
|
||||
valgrind:
|
||||
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
|
||||
runs-on: ubuntu-latest
|
||||
steps:
|
||||
- uses: actions/checkout@v4
|
||||
- uses: ankane/setup-postgres-valgrind@v1
|
||||
with:
|
||||
postgres-version: 16
|
||||
- run: make
|
||||
- run: sudo --preserve-env=PG_CONFIG make install
|
||||
- run: make installcheck
|
||||
PG_CFLAGS: -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
|
||||
|
||||
31
CHANGELOG.md
31
CHANGELOG.md
@@ -1,31 +1,16 @@
|
||||
## 0.7.0 (unreleased)
|
||||
## 0.6.0 (unreleased)
|
||||
|
||||
- Added `sparsevec` type
|
||||
If upgrading with Postgres < 13, see [this note](https://github.com/pgvector/pgvector#060).
|
||||
|
||||
## 0.6.2 (2024-03-18)
|
||||
|
||||
- Reduced lock contention with parallel HNSW index builds
|
||||
|
||||
## 0.6.1 (2024-03-04)
|
||||
|
||||
- Fixed error with `ANALYZE` and vectors with different dimensions
|
||||
- Fixed segmentation fault with `shared_preload_libraries`
|
||||
- Fixed vector subtraction being marked as commutative
|
||||
|
||||
## 0.6.0 (2024-01-29)
|
||||
|
||||
If upgrading with Postgres 12 or Docker, see [these notes](https://github.com/pgvector/pgvector#060).
|
||||
|
||||
- Added support for parallel index builds for HNSW
|
||||
- Added validation for GUC parameters
|
||||
- Changed storage for vector from `extended` to `external`
|
||||
- Improved performance of HNSW
|
||||
- Added support for parallel index builds for HNSW
|
||||
- Added `hamming_distance` function
|
||||
- Added validation for GUC parameters
|
||||
- Reduced memory usage for HNSW index builds
|
||||
- Reduced WAL generation for HNSW index builds
|
||||
- Fixed error with logical replication
|
||||
- Fixed `invalid memory alloc request size` error with HNSW index builds
|
||||
- Moved Docker image to `pgvector` org
|
||||
- Added Docker tags for each supported version of Postgres
|
||||
- Fixed `invalid memory alloc request size` error with HNSW index build
|
||||
- Dropped support for Postgres 11
|
||||
|
||||
## 0.5.1 (2023-10-10)
|
||||
@@ -74,7 +59,7 @@ If upgrading with Postgres 12 or Docker, see [these notes](https://github.com/pg
|
||||
|
||||
## 0.4.0 (2023-01-11)
|
||||
|
||||
If upgrading with Postgres < 13, see [this note](https://github.com/pgvector/pgvector/blob/v0.4.0/README.md#040).
|
||||
If upgrading with Postgres < 13, see [this note](https://github.com/pgvector/pgvector#040).
|
||||
|
||||
- Changed text representation for vector elements to match `real`
|
||||
- Changed storage for vector from `plain` to `extended`
|
||||
@@ -91,7 +76,7 @@ If upgrading with Postgres < 13, see [this note](https://github.com/pgvector/pgv
|
||||
|
||||
## 0.3.1 (2022-11-02)
|
||||
|
||||
If upgrading from 0.2.7 or 0.3.0, [recreate](https://github.com/pgvector/pgvector/blob/v0.3.1/README.md#031) all `ivfflat` indexes after upgrading to ensure all data is indexed.
|
||||
If upgrading from 0.2.7 or 0.3.0, [recreate](https://github.com/pgvector/pgvector#031) all `ivfflat` indexes after upgrading to ensure all data is indexed.
|
||||
|
||||
- Fixed issue with inserts silently corrupting `ivfflat` indexes (introduced in 0.2.7)
|
||||
- Fixed segmentation fault with index creation when lists > 6500
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
ARG PG_MAJOR=16
|
||||
ARG PG_MAJOR=15
|
||||
FROM postgres:$PG_MAJOR
|
||||
ARG PG_MAJOR
|
||||
|
||||
|
||||
2
LICENSE
2
LICENSE
@@ -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
|
||||
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
"name": "vector",
|
||||
"abstract": "Open-source vector similarity search for Postgres",
|
||||
"description": "Supports L2 distance, inner product, and cosine distance",
|
||||
"version": "0.6.2",
|
||||
"version": "0.5.1",
|
||||
"maintainer": [
|
||||
"Andrew Kane <andrew@ankane.org>"
|
||||
],
|
||||
@@ -20,7 +20,7 @@
|
||||
"vector": {
|
||||
"file": "sql/vector.sql",
|
||||
"docfile": "README.md",
|
||||
"version": "0.6.2",
|
||||
"version": "0.5.1",
|
||||
"abstract": "Open-source vector similarity search for Postgres"
|
||||
}
|
||||
},
|
||||
|
||||
14
Makefile
14
Makefile
@@ -1,10 +1,10 @@
|
||||
EXTENSION = vector
|
||||
EXTVERSION = 0.6.2
|
||||
EXTVERSION = 0.5.1
|
||||
|
||||
MODULE_big = vector
|
||||
DATA = $(wildcard sql/*--*.sql)
|
||||
OBJS = src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/sparsevec.o src/vector.o
|
||||
HEADERS = src/sparsevec.h src/vector.h
|
||||
OBJS = src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
|
||||
HEADERS = src/vector.h
|
||||
|
||||
TESTS = $(wildcard test/sql/*.sql)
|
||||
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))
|
||||
@@ -65,15 +65,13 @@ dist:
|
||||
mkdir -p dist
|
||||
git archive --format zip --prefix=$(EXTENSION)-$(EXTVERSION)/ --output dist/$(EXTENSION)-$(EXTVERSION).zip master
|
||||
|
||||
# for Docker
|
||||
PG_MAJOR ?= 16
|
||||
|
||||
.PHONY: 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 --platform linux/amd64 -t ankane/pgvector:latest .
|
||||
|
||||
.PHONY: docker-release
|
||||
|
||||
docker-release:
|
||||
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 --build-arg PG_MAJOR=$(PG_MAJOR) -t pgvector/pgvector:pg$(PG_MAJOR) -t pgvector/pgvector:$(EXTVERSION)-pg$(PG_MAJOR) .
|
||||
docker buildx build --push --pull --no-cache --platform linux/amd64,linux/arm64 -t ankane/pgvector:latest .
|
||||
docker buildx build --push --platform linux/amd64,linux/arm64 -t ankane/pgvector:v$(EXTVERSION) .
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
EXTENSION = vector
|
||||
EXTVERSION = 0.6.2
|
||||
EXTVERSION = 0.5.1
|
||||
|
||||
OBJS = src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\sparsevec.obj src\vector.obj
|
||||
HEADERS = src\sparsevec.h src\vector.h
|
||||
OBJS = src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
|
||||
HEADERS = src\vector.h
|
||||
|
||||
REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
|
||||
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
|
||||
|
||||
294
README.md
294
README.md
@@ -14,46 +14,19 @@ Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recove
|
||||
|
||||
## Installation
|
||||
|
||||
### Linux and Mac
|
||||
|
||||
Compile and install the extension (supports Postgres 12+)
|
||||
Compile and install the extension (supports Postgres 11+)
|
||||
|
||||
```sh
|
||||
cd /tmp
|
||||
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
make
|
||||
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).
|
||||
|
||||
### 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:
|
||||
|
||||
```cmd
|
||||
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 v0.6.2 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
nmake /F Makefile.win
|
||||
nmake /F Makefile.win install
|
||||
```
|
||||
|
||||
See the [installation notes](#installation-notes---windows) if you run into issues
|
||||
|
||||
You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
|
||||
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).
|
||||
|
||||
## Getting Started
|
||||
|
||||
@@ -105,12 +78,6 @@ Insert vectors
|
||||
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
|
||||
```
|
||||
|
||||
Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py))
|
||||
|
||||
```sql
|
||||
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
|
||||
```
|
||||
|
||||
Upsert vectors
|
||||
|
||||
```sql
|
||||
@@ -273,16 +240,6 @@ 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
|
||||
|
||||
Like other index types, it’s faster to create an index after loading your initial data
|
||||
|
||||
Starting with 0.6.0, you can also speed up index creation by increasing the number of parallel workers (2 by default)
|
||||
|
||||
```sql
|
||||
SET max_parallel_maintenance_workers = 7; -- plus leader
|
||||
```
|
||||
|
||||
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) with Postgres 12+
|
||||
@@ -413,51 +370,13 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python
|
||||
|
||||
## Performance
|
||||
|
||||
### Tuning
|
||||
|
||||
Use a tool like [PgTune](https://pgtune.leopard.in.ua/) to set initial values for Postgres server parameters. For instance, `shared_buffers` should typically be 25% of the server’s memory. You can find the config file with:
|
||||
|
||||
```sql
|
||||
SHOW config_file;
|
||||
```
|
||||
|
||||
And check individual settings with:
|
||||
|
||||
```sql
|
||||
SHOW shared_buffers;
|
||||
```
|
||||
|
||||
Be sure to restart Postgres for changes to take effect.
|
||||
|
||||
### Loading
|
||||
|
||||
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py)).
|
||||
|
||||
```sql
|
||||
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
|
||||
```
|
||||
|
||||
Add any indexes *after* loading the initial data for best performance.
|
||||
|
||||
### Indexing
|
||||
|
||||
See index build time for [HNSW](#index-build-time) and [IVFFlat](#index-build-time-1).
|
||||
|
||||
In production environments, create indexes concurrently to avoid blocking writes.
|
||||
|
||||
```sql
|
||||
CREATE INDEX CONCURRENTLY ...
|
||||
```
|
||||
|
||||
### Querying
|
||||
|
||||
Use `EXPLAIN ANALYZE` to debug performance.
|
||||
|
||||
```sql
|
||||
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
|
||||
```
|
||||
|
||||
#### Exact Search
|
||||
### Exact Search
|
||||
|
||||
To speed up queries without an index, increase `max_parallel_workers_per_gather`.
|
||||
|
||||
@@ -471,7 +390,7 @@ If vectors are normalized to length 1 (like [OpenAI embeddings](https://platform
|
||||
SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5;
|
||||
```
|
||||
|
||||
#### Approximate Search
|
||||
### Approximate Search
|
||||
|
||||
To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
|
||||
|
||||
@@ -479,70 +398,6 @@ To speed up queries with an IVFFlat index, increase the number of inverted lists
|
||||
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 1000);
|
||||
```
|
||||
|
||||
### Vacuuming
|
||||
|
||||
Vacuuming can take a while for HNSW indexes. Speed it up by reindexing first.
|
||||
|
||||
```sql
|
||||
REINDEX INDEX CONCURRENTLY index_name;
|
||||
VACUUM table_name;
|
||||
```
|
||||
|
||||
## Monitoring
|
||||
|
||||
Monitor performance with [pg_stat_statements](https://www.postgresql.org/docs/current/pgstatstatements.html) (be sure to add it to `shared_preload_libraries`).
|
||||
|
||||
```sql
|
||||
CREATE EXTENSION pg_stat_statements;
|
||||
```
|
||||
|
||||
Get the most time-consuming queries with:
|
||||
|
||||
```sql
|
||||
SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_time_ms,
|
||||
ROUND((total_plan_time + total_exec_time) / 60000) AS total_time_min
|
||||
FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20;
|
||||
```
|
||||
|
||||
Note: Replace `total_plan_time + total_exec_time` with `total_time` for Postgres < 13
|
||||
|
||||
Monitor recall by comparing results from approximate search with exact search.
|
||||
|
||||
```sql
|
||||
BEGIN;
|
||||
SET LOCAL enable_indexscan = off; -- use exact search
|
||||
SELECT ...
|
||||
COMMIT;
|
||||
```
|
||||
|
||||
## Scaling
|
||||
|
||||
Scale pgvector the same way you scale Postgres.
|
||||
|
||||
Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
|
||||
|
||||
Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus.py)).
|
||||
|
||||
## Sparse Vectors
|
||||
|
||||
Create a sparse vector column with 10 dimensions
|
||||
|
||||
```sql
|
||||
CREATE TABLE items (id bigserial PRIMARY KEY, embedding sparsevec(10));
|
||||
```
|
||||
|
||||
Insert vectors
|
||||
|
||||
```sql
|
||||
INSERT INTO items (embedding) VALUES ('{0:1,1:2,2:3}/10'), ('{0:4,1:5,2:6}/10');
|
||||
```
|
||||
|
||||
Get the nearest neighbors by L2 distance
|
||||
|
||||
```sql
|
||||
SELECT * FROM items ORDER BY embedding <-> '{0:3,1:1,2:2}/10' LIMIT 5;
|
||||
```
|
||||
|
||||
## 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.
|
||||
@@ -636,18 +491,6 @@ and query with:
|
||||
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
|
||||
```
|
||||
|
||||
#### Are binary vectors supported?
|
||||
|
||||
You can store binary vectors and perform exact nearest neighbor search by Hamming distance in Postgres without an extension ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py)).
|
||||
|
||||
```tsql
|
||||
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
|
||||
INSERT INTO items (embedding) VALUES (B'000'), (B'111');
|
||||
SELECT * FROM items ORDER BY bit_count(embedding # B'101') LIMIT 5;
|
||||
```
|
||||
|
||||
Indexing is not currently supported.
|
||||
|
||||
#### Do indexes need to fit into memory?
|
||||
|
||||
No, but like other index types, you’ll likely see better performance if they do. You can get the size of an index with:
|
||||
@@ -660,17 +503,7 @@ SELECT pg_size_pretty(pg_relation_size('index_name'));
|
||||
|
||||
#### Why isn’t 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.
|
||||
|
||||
```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:
|
||||
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
|
||||
BEGIN;
|
||||
@@ -699,12 +532,6 @@ or choose to store vectors inline:
|
||||
ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
|
||||
```
|
||||
|
||||
#### Why are there less results for a query after adding an HNSW index?
|
||||
|
||||
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead.
|
||||
|
||||
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
|
||||
|
||||
#### Why are there less results for a query after adding an IVFFlat index?
|
||||
|
||||
The index was likely created with too little data for the number of lists. Drop the index until the table has more data.
|
||||
@@ -713,15 +540,11 @@ The index was likely created with too little data for the number of lists. Drop
|
||||
DROP INDEX index_name;
|
||||
```
|
||||
|
||||
Results can also be limited by the number of probes (`ivfflat.probes`).
|
||||
|
||||
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
|
||||
|
||||
## Reference
|
||||
|
||||
### Vector 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
|
||||
|
||||
@@ -745,14 +568,14 @@ l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
|
||||
vector_dims(vector) → integer | number of dimensions |
|
||||
vector_norm(vector) → double precision | Euclidean norm |
|
||||
|
||||
### Vector Aggregate Functions
|
||||
### Aggregate Functions
|
||||
|
||||
Function | Description | Added
|
||||
--- | --- | ---
|
||||
avg(vector) → vector | average |
|
||||
sum(vector) → vector | sum | 0.5.0
|
||||
|
||||
## Installation Notes - Linux and Mac
|
||||
## Installation Notes
|
||||
|
||||
### Postgres Location
|
||||
|
||||
@@ -792,44 +615,44 @@ Note: Replace `16` with your Postgres server version
|
||||
|
||||
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, reinstall Xcode Command Line Tools.
|
||||
|
||||
### Portability
|
||||
### Windows
|
||||
|
||||
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.
|
||||
Support for Windows is currently experimental. 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:
|
||||
|
||||
To compile for portability, use:
|
||||
|
||||
```sh
|
||||
make OPTFLAGS=""
|
||||
```cmd
|
||||
call "C:\Program Files\Microsoft Visual Studio\2022\Community\VC\Auxiliary\Build\vcvars64.bat"
|
||||
```
|
||||
|
||||
## Installation Notes - Windows
|
||||
Note: The exact path will vary depending on your Visual Studio version and edition
|
||||
|
||||
### Missing Header
|
||||
Then use `nmake` to build:
|
||||
|
||||
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.
|
||||
```cmd
|
||||
set "PGROOT=C:\Program Files\PostgreSQL\16"
|
||||
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
nmake /F Makefile.win
|
||||
nmake /F Makefile.win install
|
||||
```
|
||||
|
||||
## Additional Installation Methods
|
||||
|
||||
### Docker
|
||||
|
||||
Get the [Docker image](https://hub.docker.com/r/pgvector/pgvector) with:
|
||||
Get the [Docker image](https://hub.docker.com/r/ankane/pgvector) with:
|
||||
|
||||
```sh
|
||||
docker pull pgvector/pgvector:pg16
|
||||
docker pull ankane/pgvector
|
||||
```
|
||||
|
||||
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `16` with your Postgres server version, and run it the same way).
|
||||
This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (run it the same way).
|
||||
|
||||
You can also build the image manually:
|
||||
|
||||
```sh
|
||||
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
docker build --build-arg PG_MAJOR=16 -t myuser/pgvector .
|
||||
docker build --build-arg PG_MAJOR=15 -t myuser/pgvector .
|
||||
```
|
||||
|
||||
### Homebrew
|
||||
@@ -872,21 +695,6 @@ sudo dnf install pgvector_16
|
||||
|
||||
Note: Replace `16` with your Postgres server version
|
||||
|
||||
### pkg
|
||||
|
||||
Install the FreeBSD package with:
|
||||
|
||||
```sh
|
||||
pkg install postgresql15-pg_vector
|
||||
```
|
||||
|
||||
or the port with:
|
||||
|
||||
```sh
|
||||
cd /usr/ports/databases/pgvector
|
||||
make install
|
||||
```
|
||||
|
||||
### conda-forge
|
||||
|
||||
With Conda Postgres, install from [conda-forge](https://anaconda.org/conda-forge/pgvector) with:
|
||||
@@ -921,11 +729,9 @@ SELECT extversion FROM pg_extension WHERE extname = 'vector';
|
||||
|
||||
## Upgrade Notes
|
||||
|
||||
### 0.6.0
|
||||
### 0.6.0 [unreleased]
|
||||
|
||||
#### Postgres 12
|
||||
|
||||
If upgrading with Postgres 12, remove this line from `sql/vector--0.5.1--0.6.0.sql`:
|
||||
If upgrading with Postgres < 13, remove this line from `sql/vector--0.5.1--0.6.0.sql`:
|
||||
|
||||
```sql
|
||||
ALTER TYPE vector SET (STORAGE = external);
|
||||
@@ -933,20 +739,28 @@ ALTER TYPE vector SET (STORAGE = external);
|
||||
|
||||
Then run `make install` and `ALTER EXTENSION vector UPDATE;`.
|
||||
|
||||
#### Docker
|
||||
### 0.4.0
|
||||
|
||||
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).
|
||||
If upgrading with Postgres < 13, remove this line from `sql/vector--0.3.2--0.4.0.sql`:
|
||||
|
||||
```sh
|
||||
docker pull pgvector/pgvector:pg16
|
||||
# or
|
||||
docker pull pgvector/pgvector:0.6.0-pg16
|
||||
```sql
|
||||
ALTER TYPE vector SET (STORAGE = extended);
|
||||
```
|
||||
|
||||
Also, if you’ve increased `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
|
||||
Then run `make install` and `ALTER EXTENSION vector UPDATE;`.
|
||||
|
||||
```sh
|
||||
docker run --shm-size=1g ...
|
||||
### 0.3.1
|
||||
|
||||
If upgrading from 0.2.7 or 0.3.0, recreate all `ivfflat` indexes after upgrading to ensure all data is indexed.
|
||||
|
||||
```sql
|
||||
-- Postgres 12+
|
||||
REINDEX INDEX CONCURRENTLY index_name;
|
||||
|
||||
-- Postgres < 12
|
||||
CREATE INDEX CONCURRENTLY temp_name ON table USING ivfflat (column opclass);
|
||||
DROP INDEX CONCURRENTLY index_name;
|
||||
ALTER INDEX temp_name RENAME TO index_name;
|
||||
```
|
||||
|
||||
## Thanks
|
||||
@@ -993,13 +807,7 @@ To run single tests:
|
||||
|
||||
```sh
|
||||
make installcheck REGRESS=functions # regression test
|
||||
make prove_installcheck PROVE_TESTS=test/t/001_ivfflat_wal.pl # TAP test
|
||||
```
|
||||
|
||||
To enable assertions:
|
||||
|
||||
```sh
|
||||
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
|
||||
make prove_installcheck PROVE_TESTS=test/t/001_wal.pl # TAP test
|
||||
```
|
||||
|
||||
To enable benchmarking:
|
||||
@@ -1014,6 +822,12 @@ To show memory usage:
|
||||
make clean && PG_CFLAGS="-DHNSW_MEMORY -DIVFFLAT_MEMORY" make && make install
|
||||
```
|
||||
|
||||
To enable assertions:
|
||||
|
||||
```sh
|
||||
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
|
||||
```
|
||||
|
||||
To get k-means metrics:
|
||||
|
||||
```sh
|
||||
|
||||
@@ -3,3 +3,6 @@
|
||||
|
||||
-- remove this single line for Postgres < 13
|
||||
ALTER TYPE vector SET (STORAGE = external);
|
||||
|
||||
CREATE FUNCTION hamming_distance(bytea, bytea) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
@@ -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
|
||||
);
|
||||
@@ -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
|
||||
@@ -1,95 +0,0 @@
|
||||
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
|
||||
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.0'" to load this file. \quit
|
||||
|
||||
CREATE TYPE sparsevec;
|
||||
|
||||
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE TYPE sparsevec (
|
||||
INPUT = sparsevec_in,
|
||||
OUTPUT = sparsevec_out,
|
||||
TYPMOD_IN = sparsevec_typmod_in,
|
||||
RECEIVE = sparsevec_recv,
|
||||
SEND = sparsevec_send,
|
||||
STORAGE = external
|
||||
);
|
||||
|
||||
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_norm(sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE CAST (sparsevec AS sparsevec)
|
||||
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
|
||||
|
||||
CREATE CAST (sparsevec AS vector)
|
||||
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS IMPLICIT;
|
||||
|
||||
CREATE CAST (vector AS sparsevec)
|
||||
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
|
||||
|
||||
CREATE OPERATOR <-> (
|
||||
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
|
||||
COMMUTATOR = '<->'
|
||||
);
|
||||
|
||||
CREATE OPERATOR <#> (
|
||||
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
|
||||
COMMUTATOR = '<#>'
|
||||
);
|
||||
|
||||
CREATE OPERATOR <=> (
|
||||
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
|
||||
COMMUTATOR = '<=>'
|
||||
);
|
||||
|
||||
CREATE OPERATOR CLASS sparsevec_l2_ops
|
||||
FOR TYPE sparsevec USING hnsw AS
|
||||
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
|
||||
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec);
|
||||
|
||||
CREATE OPERATOR CLASS sparsevec_ip_ops
|
||||
FOR TYPE sparsevec USING hnsw AS
|
||||
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
|
||||
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec);
|
||||
|
||||
CREATE OPERATOR CLASS sparsevec_cosine_ops
|
||||
FOR TYPE sparsevec USING hnsw AS
|
||||
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
|
||||
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
|
||||
FUNCTION 2 sparsevec_norm(sparsevec);
|
||||
131
sql/vector.sql
131
sql/vector.sql
@@ -1,7 +1,7 @@
|
||||
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
|
||||
\echo Use "CREATE EXTENSION vector" to load this file. \quit
|
||||
|
||||
-- vector type
|
||||
-- type
|
||||
|
||||
CREATE TYPE vector;
|
||||
|
||||
@@ -29,7 +29,7 @@ CREATE TYPE vector (
|
||||
STORAGE = external
|
||||
);
|
||||
|
||||
-- vector functions
|
||||
-- functions
|
||||
|
||||
CREATE FUNCTION l2_distance(vector, vector) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
@@ -58,7 +58,7 @@ CREATE FUNCTION vector_sub(vector, vector) RETURNS vector
|
||||
CREATE FUNCTION vector_mul(vector, vector) RETURNS vector
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- vector private functions
|
||||
-- private functions
|
||||
|
||||
CREATE FUNCTION vector_lt(vector, vector) RETURNS bool
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
@@ -99,7 +99,7 @@ CREATE FUNCTION vector_avg(double precision[]) RETURNS vector
|
||||
CREATE FUNCTION vector_combine(double precision[], double precision[]) RETURNS double precision[]
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- vector aggregates
|
||||
-- aggregates
|
||||
|
||||
CREATE AGGREGATE avg(vector) (
|
||||
SFUNC = vector_accum,
|
||||
@@ -117,7 +117,7 @@ CREATE AGGREGATE sum(vector) (
|
||||
PARALLEL = SAFE
|
||||
);
|
||||
|
||||
-- vector cast functions
|
||||
-- cast functions
|
||||
|
||||
CREATE FUNCTION vector(vector, integer, boolean) RETURNS vector
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
@@ -137,7 +137,7 @@ CREATE FUNCTION array_to_vector(numeric[], integer, boolean) RETURNS vector
|
||||
CREATE FUNCTION vector_to_float4(vector, integer, boolean) RETURNS real[]
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- vector casts
|
||||
-- casts
|
||||
|
||||
CREATE CAST (vector AS vector)
|
||||
WITH FUNCTION vector(vector, integer, boolean) AS IMPLICIT;
|
||||
@@ -157,7 +157,7 @@ CREATE CAST (double precision[] AS vector)
|
||||
CREATE CAST (numeric[] AS vector)
|
||||
WITH FUNCTION array_to_vector(numeric[], integer, boolean) AS ASSIGNMENT;
|
||||
|
||||
-- vector operators
|
||||
-- operators
|
||||
|
||||
CREATE OPERATOR <-> (
|
||||
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l2_distance,
|
||||
@@ -180,7 +180,8 @@ CREATE OPERATOR + (
|
||||
);
|
||||
|
||||
CREATE OPERATOR - (
|
||||
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub
|
||||
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_sub,
|
||||
COMMUTATOR = -
|
||||
);
|
||||
|
||||
CREATE OPERATOR * (
|
||||
@@ -194,10 +195,11 @@ CREATE OPERATOR < (
|
||||
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
|
||||
);
|
||||
|
||||
-- should use scalarlesel and scalarlejoinsel, but not supported in Postgres < 11
|
||||
CREATE OPERATOR <= (
|
||||
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_le,
|
||||
COMMUTATOR = >= , NEGATOR = > ,
|
||||
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
|
||||
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
|
||||
);
|
||||
|
||||
CREATE OPERATOR = (
|
||||
@@ -212,10 +214,11 @@ CREATE OPERATOR <> (
|
||||
RESTRICT = eqsel, JOIN = eqjoinsel
|
||||
);
|
||||
|
||||
-- should use scalargesel and scalargejoinsel, but not supported in Postgres < 11
|
||||
CREATE OPERATOR >= (
|
||||
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_ge,
|
||||
COMMUTATOR = <= , NEGATOR = < ,
|
||||
RESTRICT = scalargesel, JOIN = scalargejoinsel
|
||||
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
|
||||
);
|
||||
|
||||
CREATE OPERATOR > (
|
||||
@@ -240,7 +243,7 @@ CREATE ACCESS METHOD hnsw TYPE INDEX HANDLER hnswhandler;
|
||||
|
||||
COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method';
|
||||
|
||||
-- vector opclasses
|
||||
-- opclasses
|
||||
|
||||
CREATE OPERATOR CLASS vector_ops
|
||||
DEFAULT FOR TYPE vector USING btree AS
|
||||
@@ -288,109 +291,7 @@ CREATE OPERATOR CLASS vector_cosine_ops
|
||||
FUNCTION 1 vector_negative_inner_product(vector, vector),
|
||||
FUNCTION 2 vector_norm(vector);
|
||||
|
||||
--- sparsevec type
|
||||
-- bytea functions
|
||||
|
||||
CREATE TYPE sparsevec;
|
||||
|
||||
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
|
||||
CREATE FUNCTION hamming_distance(bytea, bytea) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE TYPE sparsevec (
|
||||
INPUT = sparsevec_in,
|
||||
OUTPUT = sparsevec_out,
|
||||
TYPMOD_IN = sparsevec_typmod_in,
|
||||
RECEIVE = sparsevec_recv,
|
||||
SEND = sparsevec_send,
|
||||
STORAGE = external
|
||||
);
|
||||
|
||||
-- sparsevec functions
|
||||
|
||||
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_norm(sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- sparsevec private functions
|
||||
|
||||
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- sparsevec cast functions
|
||||
|
||||
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- sparsevec casts
|
||||
|
||||
CREATE CAST (sparsevec AS sparsevec)
|
||||
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
|
||||
|
||||
CREATE CAST (sparsevec AS vector)
|
||||
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS IMPLICIT;
|
||||
|
||||
CREATE CAST (vector AS sparsevec)
|
||||
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
|
||||
|
||||
-- sparsevec operators
|
||||
|
||||
CREATE OPERATOR <-> (
|
||||
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
|
||||
COMMUTATOR = '<->'
|
||||
);
|
||||
|
||||
CREATE OPERATOR <#> (
|
||||
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
|
||||
COMMUTATOR = '<#>'
|
||||
);
|
||||
|
||||
CREATE OPERATOR <=> (
|
||||
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
|
||||
COMMUTATOR = '<=>'
|
||||
);
|
||||
|
||||
-- sparsevec opclasses
|
||||
|
||||
CREATE OPERATOR CLASS sparsevec_l2_ops
|
||||
FOR TYPE sparsevec USING hnsw AS
|
||||
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
|
||||
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec);
|
||||
|
||||
CREATE OPERATOR CLASS sparsevec_ip_ops
|
||||
FOR TYPE sparsevec USING hnsw AS
|
||||
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
|
||||
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec);
|
||||
|
||||
CREATE OPERATOR CLASS sparsevec_cosine_ops
|
||||
FOR TYPE sparsevec USING hnsw AS
|
||||
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
|
||||
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
|
||||
FUNCTION 2 sparsevec_norm(sparsevec);
|
||||
|
||||
@@ -8,7 +8,6 @@
|
||||
#include "commands/progress.h"
|
||||
#include "commands/vacuum.h"
|
||||
#include "hnsw.h"
|
||||
#include "miscadmin.h"
|
||||
#include "utils/guc.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
|
||||
* RequestAddinShmemSpace() to pre-reserve space for this.
|
||||
*/
|
||||
void
|
||||
static void
|
||||
HnswInitLockTranche(void)
|
||||
{
|
||||
int *tranche_ids;
|
||||
@@ -54,7 +53,6 @@ HnswInitLockTranche(void)
|
||||
void
|
||||
HnswInit(void)
|
||||
{
|
||||
if (!process_shared_preload_libraries_in_progress)
|
||||
HnswInitLockTranche();
|
||||
|
||||
hnsw_relopt_kind = add_reloption_kind();
|
||||
|
||||
30
src/hnsw.h
30
src/hnsw.h
@@ -17,7 +17,6 @@
|
||||
#endif
|
||||
|
||||
#define HNSW_MAX_DIM 2000
|
||||
#define HNSW_MAX_NNZ 1000
|
||||
|
||||
/* Support functions */
|
||||
#define HNSW_DISTANCE_PROC 1
|
||||
@@ -56,24 +55,15 @@
|
||||
#define HNSW_UPDATE_ENTRY_GREATER 1
|
||||
#define HNSW_UPDATE_ENTRY_ALWAYS 2
|
||||
|
||||
typedef enum HnswType
|
||||
{
|
||||
HNSW_TYPE_VECTOR,
|
||||
HNSW_TYPE_SPARSEVEC
|
||||
} HnswType;
|
||||
|
||||
/* Build phases */
|
||||
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
|
||||
#define PROGRESS_HNSW_PHASE_LOAD 2
|
||||
|
||||
#define HNSW_MAX_SIZE (BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - sizeof(ItemIdData))
|
||||
#define HNSW_TUPLE_ALLOC_SIZE BLCKSZ
|
||||
|
||||
#define HNSW_ELEMENT_TUPLE_SIZE(size) MAXALIGN(offsetof(HnswElementTupleData, data) + (size))
|
||||
#define HNSW_NEIGHBOR_TUPLE_SIZE(level, m) MAXALIGN(offsetof(HnswNeighborTupleData, indextids) + ((level) + 2) * (m) * sizeof(ItemPointerData))
|
||||
|
||||
#define HNSW_NEIGHBOR_ARRAY_SIZE(lm) (offsetof(HnswNeighborArray, items) + sizeof(HnswCandidate) * (lm))
|
||||
|
||||
#define HnswPageGetOpaque(page) ((HnswPageOpaque) PageGetSpecialPointer(page))
|
||||
#define HnswPageGetMeta(page) ((HnswMetaPageData *) PageGetContents(page))
|
||||
|
||||
@@ -87,7 +77,7 @@ typedef enum HnswType
|
||||
|
||||
#if PG_VERSION_NUM < 130000
|
||||
#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
|
||||
|
||||
#define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
|
||||
@@ -136,7 +126,7 @@ HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr)
|
||||
HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
|
||||
HnswPtrDeclare(char, DatumRelptr, DatumPtr);
|
||||
|
||||
struct HnswElementData
|
||||
typedef struct HnswElementData
|
||||
{
|
||||
HnswElementPtr next;
|
||||
ItemPointerData heaptids[HNSW_HEAPTIDS];
|
||||
@@ -151,7 +141,7 @@ struct HnswElementData
|
||||
BlockNumber neighborPage;
|
||||
DatumPtr value;
|
||||
LWLock lock;
|
||||
};
|
||||
} HnswElementData;
|
||||
|
||||
typedef HnswElementData * HnswElement;
|
||||
|
||||
@@ -162,12 +152,12 @@ typedef struct HnswCandidate
|
||||
bool closer;
|
||||
} HnswCandidate;
|
||||
|
||||
struct HnswNeighborArray
|
||||
typedef struct HnswNeighborArray
|
||||
{
|
||||
int length;
|
||||
bool closerSet;
|
||||
HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
|
||||
};
|
||||
} HnswNeighborArray;
|
||||
|
||||
typedef struct HnswPairingHeapNode
|
||||
{
|
||||
@@ -192,7 +182,6 @@ typedef struct HnswGraph
|
||||
|
||||
/* Entry state */
|
||||
LWLock entryLock;
|
||||
LWLock entryWaitLock;
|
||||
HnswElementPtr entryPoint;
|
||||
|
||||
/* Allocations state */
|
||||
@@ -249,7 +238,6 @@ typedef struct HnswBuildState
|
||||
Relation index;
|
||||
IndexInfo *indexInfo;
|
||||
ForkNumber forkNum;
|
||||
HnswType type;
|
||||
|
||||
/* Settings */
|
||||
int dimensions;
|
||||
@@ -270,6 +258,7 @@ typedef struct HnswBuildState
|
||||
HnswGraph *graph;
|
||||
double ml;
|
||||
int maxLevel;
|
||||
Vector *normvec;
|
||||
|
||||
/* Memory */
|
||||
MemoryContext graphCtx;
|
||||
@@ -374,9 +363,7 @@ typedef struct HnswVacuumState
|
||||
int HnswGetM(Relation index);
|
||||
int HnswGetEfConstruction(Relation index);
|
||||
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
|
||||
HnswType HnswGetType(Relation index);
|
||||
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type);
|
||||
void HnswCheckValue(Datum value, HnswType type);
|
||||
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
|
||||
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
|
||||
void HnswInitPage(Buffer buf, Page page);
|
||||
void HnswInit(void);
|
||||
@@ -392,14 +379,13 @@ void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint
|
||||
void HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m);
|
||||
void HnswAddHeapTid(HnswElement element, ItemPointer heaptid);
|
||||
void HnswInitNeighbors(char *base, HnswElement element, int m, HnswAllocator * alloc);
|
||||
bool HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building);
|
||||
bool HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel, bool building);
|
||||
void HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building);
|
||||
void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec);
|
||||
void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec);
|
||||
void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element);
|
||||
void HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
|
||||
void HnswLoadNeighbors(HnswElement element, Relation index, int m);
|
||||
void HnswInitLockTranche(void);
|
||||
PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);
|
||||
|
||||
/* Index access methods */
|
||||
|
||||
@@ -65,6 +65,8 @@
|
||||
#define CALLBACK_ITEM_POINTER HeapTuple hup
|
||||
#endif
|
||||
|
||||
#define UpdateProgress(index, val) pgstat_progress_update_param(index, val)
|
||||
|
||||
#if PG_VERSION_NUM >= 140000
|
||||
#include "utils/backend_status.h"
|
||||
#include "utils/wait_event.h"
|
||||
@@ -141,13 +143,14 @@ HnswBuildAppendPage(Relation index, Buffer *buf, Page *page, ForkNumber forkNum)
|
||||
}
|
||||
|
||||
/*
|
||||
* Create graph pages
|
||||
* Create element pages
|
||||
*/
|
||||
static void
|
||||
CreateGraphPages(HnswBuildState * buildstate)
|
||||
CreateElementPages(HnswBuildState * buildstate)
|
||||
{
|
||||
Relation index = buildstate->index;
|
||||
ForkNumber forkNum = buildstate->forkNum;
|
||||
Size etupAllocSize;
|
||||
Size maxSize;
|
||||
HnswElementTuple etup;
|
||||
HnswNeighborTuple ntup;
|
||||
@@ -159,11 +162,12 @@ CreateGraphPages(HnswBuildState * buildstate)
|
||||
char *base = buildstate->hnswarea;
|
||||
|
||||
/* Calculate sizes */
|
||||
etupAllocSize = BLCKSZ;
|
||||
maxSize = HNSW_MAX_SIZE;
|
||||
|
||||
/* Allocate once */
|
||||
etup = palloc0(HNSW_TUPLE_ALLOC_SIZE);
|
||||
ntup = palloc0(HNSW_TUPLE_ALLOC_SIZE);
|
||||
etup = palloc0(etupAllocSize);
|
||||
ntup = palloc0(BLCKSZ);
|
||||
|
||||
/* Prepare first page */
|
||||
buf = HnswNewBuffer(index, forkNum);
|
||||
@@ -176,13 +180,13 @@ CreateGraphPages(HnswBuildState * buildstate)
|
||||
Size etupSize;
|
||||
Size ntupSize;
|
||||
Size combinedSize;
|
||||
Pointer valuePtr = HnswPtrAccess(base, element->value);
|
||||
void *valuePtr = HnswPtrAccess(base, element->value);
|
||||
|
||||
/* Update iterator */
|
||||
iter = element->next;
|
||||
|
||||
/* Zero memory for each element */
|
||||
MemSet(etup, 0, HNSW_TUPLE_ALLOC_SIZE);
|
||||
MemSet(etup, 0, etupAllocSize);
|
||||
|
||||
/* Calculate sizes */
|
||||
etupSize = HNSW_ELEMENT_TUPLE_SIZE(VARSIZE_ANY(valuePtr));
|
||||
@@ -190,7 +194,7 @@ CreateGraphPages(HnswBuildState * buildstate)
|
||||
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
|
||||
|
||||
/* Initial size check */
|
||||
if (etupSize > HNSW_TUPLE_ALLOC_SIZE)
|
||||
if (etupSize > etupAllocSize)
|
||||
elog(ERROR, "index tuple too large");
|
||||
|
||||
HnswSetElementTuple(base, etup, element);
|
||||
@@ -242,10 +246,10 @@ CreateGraphPages(HnswBuildState * buildstate)
|
||||
}
|
||||
|
||||
/*
|
||||
* Write neighbor tuples
|
||||
* Create neighbor pages
|
||||
*/
|
||||
static void
|
||||
WriteNeighborTuples(HnswBuildState * buildstate)
|
||||
CreateNeighborPages(HnswBuildState * buildstate)
|
||||
{
|
||||
Relation index = buildstate->index;
|
||||
ForkNumber forkNum = buildstate->forkNum;
|
||||
@@ -255,32 +259,29 @@ WriteNeighborTuples(HnswBuildState * buildstate)
|
||||
HnswNeighborTuple ntup;
|
||||
|
||||
/* Allocate once */
|
||||
ntup = palloc0(HNSW_TUPLE_ALLOC_SIZE);
|
||||
ntup = palloc0(BLCKSZ);
|
||||
|
||||
while (!HnswPtrIsNull(base, iter))
|
||||
{
|
||||
HnswElement element = HnswPtrAccess(base, iter);
|
||||
HnswElement e = HnswPtrAccess(base, iter);
|
||||
Buffer buf;
|
||||
Page page;
|
||||
Size ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, m);
|
||||
Size ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
|
||||
|
||||
/* Update iterator */
|
||||
iter = element->next;
|
||||
|
||||
/* Zero memory for each element */
|
||||
MemSet(ntup, 0, HNSW_TUPLE_ALLOC_SIZE);
|
||||
iter = e->next;
|
||||
|
||||
/* Can take a while, so ensure we can interrupt */
|
||||
/* Needs to be called when no buffer locks are held */
|
||||
CHECK_FOR_INTERRUPTS();
|
||||
|
||||
buf = ReadBufferExtended(index, forkNum, element->neighborPage, RBM_NORMAL, NULL);
|
||||
buf = ReadBufferExtended(index, forkNum, e->neighborPage, RBM_NORMAL, NULL);
|
||||
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
|
||||
page = BufferGetPage(buf);
|
||||
|
||||
HnswSetNeighborTuple(base, ntup, element, m);
|
||||
HnswSetNeighborTuple(base, ntup, e, m);
|
||||
|
||||
if (!PageIndexTupleOverwrite(page, element->neighborOffno, (Item) ntup, ntupSize))
|
||||
if (!PageIndexTupleOverwrite(page, e->neighborOffno, (Item) ntup, ntupSize))
|
||||
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
|
||||
|
||||
/* Commit */
|
||||
@@ -302,8 +303,8 @@ FlushPages(HnswBuildState * buildstate)
|
||||
#endif
|
||||
|
||||
CreateMetaPage(buildstate);
|
||||
CreateGraphPages(buildstate);
|
||||
WriteNeighborTuples(buildstate);
|
||||
CreateElementPages(buildstate);
|
||||
CreateNeighborPages(buildstate);
|
||||
|
||||
buildstate->graph->flushed = true;
|
||||
MemoryContextReset(buildstate->graphCtx);
|
||||
@@ -431,15 +432,10 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
|
||||
HnswGraph *graph = buildstate->graph;
|
||||
HnswElement entryPoint;
|
||||
LWLock *entryLock = &graph->entryLock;
|
||||
LWLock *entryWaitLock = &graph->entryWaitLock;
|
||||
int efConstruction = buildstate->efConstruction;
|
||||
int m = buildstate->m;
|
||||
char *base = buildstate->hnswarea;
|
||||
|
||||
/* Wait if another process needs exclusive lock on entry lock */
|
||||
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
|
||||
LWLockRelease(entryWaitLock);
|
||||
|
||||
/* Get entry point */
|
||||
LWLockAcquire(entryLock, LW_SHARED);
|
||||
entryPoint = HnswPtrAccess(base, graph->entryPoint);
|
||||
@@ -450,10 +446,8 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
|
||||
/* Release shared lock */
|
||||
LWLockRelease(entryLock);
|
||||
|
||||
/* Tell other processes to wait and get exclusive lock */
|
||||
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
|
||||
/* Get exclusive lock */
|
||||
LWLockAcquire(entryLock, LW_EXCLUSIVE);
|
||||
LWLockRelease(entryWaitLock);
|
||||
|
||||
/* Get latest entry point after lock is acquired */
|
||||
entryPoint = HnswPtrAccess(base, graph->entryPoint);
|
||||
@@ -486,13 +480,10 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
|
||||
/* Detoast once for all calls */
|
||||
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
|
||||
|
||||
/* Check value */
|
||||
HnswCheckValue(value, buildstate->type);
|
||||
|
||||
/* Normalize if needed */
|
||||
if (buildstate->normprocinfo != NULL)
|
||||
{
|
||||
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->type))
|
||||
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
|
||||
return false;
|
||||
}
|
||||
|
||||
@@ -507,7 +498,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
|
||||
{
|
||||
LWLockRelease(flushLock);
|
||||
|
||||
return HnswInsertTupleOnDisk(index, value, values, isnull, heaptid, true);
|
||||
return HnswInsertTupleOnDisk(index, value, values, isnull, heaptid, buildstate->heap, true);
|
||||
}
|
||||
|
||||
/*
|
||||
@@ -539,7 +530,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
|
||||
|
||||
LWLockRelease(flushLock);
|
||||
|
||||
return HnswInsertTupleOnDisk(index, value, values, isnull, heaptid, true);
|
||||
return HnswInsertTupleOnDisk(index, value, values, isnull, heaptid, buildstate->heap, true);
|
||||
}
|
||||
|
||||
/* Ok, we can proceed to allocate the element */
|
||||
@@ -596,7 +587,7 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
|
||||
{
|
||||
/* Update progress */
|
||||
SpinLockAcquire(&graph->lock);
|
||||
pgstat_progress_update_param(PROGRESS_CREATEIDX_TUPLES_DONE, ++graph->indtuples);
|
||||
UpdateProgress(PROGRESS_CREATEIDX_TUPLES_DONE, ++graph->indtuples);
|
||||
SpinLockRelease(&graph->lock);
|
||||
}
|
||||
|
||||
@@ -611,9 +602,6 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
|
||||
static void
|
||||
InitGraph(HnswGraph * graph, char *base, long memoryTotal)
|
||||
{
|
||||
/* Initialize the lock tranche if needed */
|
||||
HnswInitLockTranche();
|
||||
|
||||
HnswPtrStore(base, graph->head, (HnswElement) NULL);
|
||||
HnswPtrStore(base, graph->entryPoint, (HnswElement) NULL);
|
||||
graph->memoryUsed = 0;
|
||||
@@ -622,7 +610,6 @@ InitGraph(HnswGraph * graph, char *base, long memoryTotal)
|
||||
graph->indtuples = 0;
|
||||
SpinLockInit(&graph->lock);
|
||||
LWLockInitialize(&graph->entryLock, hnsw_lock_tranche_id);
|
||||
LWLockInitialize(&graph->entryWaitLock, hnsw_lock_tranche_id);
|
||||
LWLockInitialize(&graph->allocatorLock, hnsw_lock_tranche_id);
|
||||
LWLockInitialize(&graph->flushLock, hnsw_lock_tranche_id);
|
||||
}
|
||||
@@ -674,28 +661,21 @@ HnswSharedMemoryAlloc(Size size, void *state)
|
||||
static void
|
||||
InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum)
|
||||
{
|
||||
int maxDimensions = HNSW_MAX_DIM;
|
||||
|
||||
buildstate->heap = heap;
|
||||
buildstate->index = index;
|
||||
buildstate->indexInfo = indexInfo;
|
||||
buildstate->forkNum = forkNum;
|
||||
buildstate->type = HnswGetType(index);
|
||||
|
||||
buildstate->m = HnswGetM(index);
|
||||
buildstate->efConstruction = HnswGetEfConstruction(index);
|
||||
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
|
||||
|
||||
/* No limit on sparse vector dimensions */
|
||||
if (buildstate->type == HNSW_TYPE_SPARSEVEC)
|
||||
maxDimensions = INT_MAX;
|
||||
|
||||
/* Require column to have dimensions to be indexed */
|
||||
if (buildstate->dimensions < 0)
|
||||
elog(ERROR, "column does not have dimensions");
|
||||
|
||||
if (buildstate->dimensions > maxDimensions)
|
||||
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", maxDimensions);
|
||||
if (buildstate->dimensions > HNSW_MAX_DIM)
|
||||
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", HNSW_MAX_DIM);
|
||||
|
||||
if (buildstate->efConstruction < 2 * buildstate->m)
|
||||
elog(ERROR, "ef_construction must be greater than or equal to 2 * m");
|
||||
@@ -713,6 +693,9 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
|
||||
buildstate->ml = HnswGetMl(buildstate->m);
|
||||
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
|
||||
|
||||
/* Reuse for each tuple */
|
||||
buildstate->normvec = InitVector(buildstate->dimensions);
|
||||
|
||||
buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext,
|
||||
"Hnsw build graph context",
|
||||
#if PG_VERSION_NUM >= 150000
|
||||
@@ -736,6 +719,7 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
|
||||
static void
|
||||
FreeBuildState(HnswBuildState * buildstate)
|
||||
{
|
||||
pfree(buildstate->normvec);
|
||||
MemoryContextDelete(buildstate->graphCtx);
|
||||
MemoryContextDelete(buildstate->tmpCtx);
|
||||
}
|
||||
@@ -991,14 +975,6 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
|
||||
/* Report less than allocated so never fails */
|
||||
InitGraph(&hnswshared->graphData, hnswarea, esthnswarea - 1024 * 1024);
|
||||
|
||||
/*
|
||||
* Avoid base address for relptr for Postgres < 14.5
|
||||
* https://github.com/postgres/postgres/commit/7201cd18627afc64850537806da7f22150d1a83b
|
||||
*/
|
||||
#if PG_VERSION_NUM < 140005
|
||||
hnswshared->graphData.memoryUsed += MAXALIGN(1);
|
||||
#endif
|
||||
|
||||
shm_toc_insert(pcxt->toc, PARALLEL_KEY_HNSW_SHARED, hnswshared);
|
||||
shm_toc_insert(pcxt->toc, PARALLEL_KEY_HNSW_AREA, hnswarea);
|
||||
|
||||
@@ -1072,7 +1048,7 @@ BuildGraph(HnswBuildState * buildstate, ForkNumber forkNum)
|
||||
{
|
||||
int parallel_workers = 0;
|
||||
|
||||
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_HNSW_PHASE_LOAD);
|
||||
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_HNSW_PHASE_LOAD);
|
||||
|
||||
/* Calculate parallel workers */
|
||||
if (buildstate->heap != NULL)
|
||||
|
||||
@@ -355,7 +355,9 @@ HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, Hns
|
||||
Buffer buf;
|
||||
Page page;
|
||||
GenericXLogState *state;
|
||||
ItemId itemid;
|
||||
HnswNeighborTuple ntup;
|
||||
Size ntupSize;
|
||||
int idx = -1;
|
||||
int startIdx;
|
||||
HnswElement neighborElement = HnswPtrAccess(base, hc->element);
|
||||
@@ -394,7 +396,9 @@ HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, Hns
|
||||
}
|
||||
|
||||
/* Get tuple */
|
||||
ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, offno));
|
||||
itemid = PageGetItemId(page, offno);
|
||||
ntup = (HnswNeighborTuple) PageGetItem(page, itemid);
|
||||
ntupSize = ItemIdGetLength(itemid);
|
||||
|
||||
/* Calculate index for update */
|
||||
startIdx = (neighborElement->level - lc) * m;
|
||||
@@ -423,9 +427,13 @@ HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, Hns
|
||||
{
|
||||
ItemPointer indextid = &ntup->indextids[idx];
|
||||
|
||||
/* Update neighbor on the buffer */
|
||||
/* Update neighbor */
|
||||
ItemPointerSet(indextid, e->blkno, e->offno);
|
||||
|
||||
/* Overwrite tuple */
|
||||
if (!PageIndexTupleOverwrite(page, offno, (Item) ntup, ntupSize))
|
||||
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
|
||||
|
||||
/* Commit */
|
||||
if (building)
|
||||
MarkBufferDirty(buf);
|
||||
@@ -449,7 +457,9 @@ AddDuplicateOnDisk(Relation index, HnswElement element, HnswElement dup, bool bu
|
||||
Buffer buf;
|
||||
Page page;
|
||||
GenericXLogState *state;
|
||||
ItemId itemid;
|
||||
HnswElementTuple etup;
|
||||
Size etupSize;
|
||||
int i;
|
||||
|
||||
/* Read page */
|
||||
@@ -467,7 +477,9 @@ AddDuplicateOnDisk(Relation index, HnswElement element, HnswElement dup, bool bu
|
||||
}
|
||||
|
||||
/* Find space */
|
||||
etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, dup->offno));
|
||||
itemid = PageGetItemId(page, dup->offno);
|
||||
etup = (HnswElementTuple) PageGetItem(page, itemid);
|
||||
etupSize = ItemIdGetLength(itemid);
|
||||
for (i = 0; i < HNSW_HEAPTIDS; i++)
|
||||
{
|
||||
if (!ItemPointerIsValid(&etup->heaptids[i]))
|
||||
@@ -483,9 +495,13 @@ AddDuplicateOnDisk(Relation index, HnswElement element, HnswElement dup, bool bu
|
||||
return false;
|
||||
}
|
||||
|
||||
/* Add heap TID, modifying the tuple on the page directly */
|
||||
/* Add heap TID */
|
||||
etup->heaptids[i] = element->heaptids[0];
|
||||
|
||||
/* Overwrite tuple */
|
||||
if (!PageIndexTupleOverwrite(page, dup->offno, (Item) etup, etupSize))
|
||||
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
|
||||
|
||||
/* Commit */
|
||||
if (building)
|
||||
MarkBufferDirty(buf);
|
||||
@@ -554,7 +570,7 @@ UpdateGraphOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement
|
||||
* Insert a tuple into the index
|
||||
*/
|
||||
bool
|
||||
HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building)
|
||||
HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel, bool building)
|
||||
{
|
||||
HnswElement entryPoint;
|
||||
HnswElement element;
|
||||
@@ -609,28 +625,24 @@ HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull,
|
||||
* Insert a tuple into the index
|
||||
*/
|
||||
static void
|
||||
HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid)
|
||||
HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
|
||||
{
|
||||
Datum value;
|
||||
FmgrInfo *normprocinfo;
|
||||
Oid collation = index->rd_indcollation[0];
|
||||
HnswType type = HnswGetType(index);
|
||||
|
||||
/* Detoast once for all calls */
|
||||
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
|
||||
|
||||
/* Check value */
|
||||
HnswCheckValue(value, type);
|
||||
|
||||
/* Normalize if needed */
|
||||
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
|
||||
if (normprocinfo != NULL)
|
||||
{
|
||||
if (!HnswNormValue(normprocinfo, collation, &value, type))
|
||||
if (!HnswNormValue(normprocinfo, collation, &value, NULL))
|
||||
return;
|
||||
}
|
||||
|
||||
HnswInsertTupleOnDisk(index, value, values, isnull, heap_tid, false);
|
||||
HnswInsertTupleOnDisk(index, value, values, isnull, heap_tid, heapRel, false);
|
||||
}
|
||||
|
||||
/*
|
||||
@@ -659,7 +671,7 @@ hnswinsert(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid,
|
||||
oldCtx = MemoryContextSwitchTo(insertCtx);
|
||||
|
||||
/* Insert tuple */
|
||||
HnswInsertTuple(index, values, isnull, heap_tid);
|
||||
HnswInsertTuple(index, values, isnull, heap_tid, heap);
|
||||
|
||||
/* Delete memory context */
|
||||
MemoryContextSwitchTo(oldCtx);
|
||||
|
||||
@@ -40,6 +40,29 @@ GetScanItems(IndexScanDesc scan, Datum q)
|
||||
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
|
||||
}
|
||||
|
||||
/*
|
||||
* Get dimensions from metapage
|
||||
*/
|
||||
static int
|
||||
GetDimensions(Relation index)
|
||||
{
|
||||
Buffer buf;
|
||||
Page page;
|
||||
HnswMetaPage metap;
|
||||
int dimensions;
|
||||
|
||||
buf = ReadBuffer(index, HNSW_METAPAGE_BLKNO);
|
||||
LockBuffer(buf, BUFFER_LOCK_SHARE);
|
||||
page = BufferGetPage(buf);
|
||||
metap = HnswPageGetMeta(page);
|
||||
|
||||
dimensions = metap->dimensions;
|
||||
|
||||
UnlockReleaseBuffer(buf);
|
||||
|
||||
return dimensions;
|
||||
}
|
||||
|
||||
/*
|
||||
* Get scan value
|
||||
*/
|
||||
@@ -50,7 +73,7 @@ GetScanValue(IndexScanDesc scan)
|
||||
Datum value;
|
||||
|
||||
if (scan->orderByData->sk_flags & SK_ISNULL)
|
||||
value = PointerGetDatum(NULL);
|
||||
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
|
||||
else
|
||||
{
|
||||
value = scan->orderByData->sk_argument;
|
||||
@@ -61,7 +84,7 @@ GetScanValue(IndexScanDesc scan)
|
||||
|
||||
/* Fine if normalization fails */
|
||||
if (so->normprocinfo != NULL)
|
||||
HnswNormValue(so->normprocinfo, so->collation, &value, HnswGetType(scan->indexRelation));
|
||||
HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
|
||||
}
|
||||
|
||||
return value;
|
||||
@@ -179,7 +202,6 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
MemoryContextSwitchTo(oldCtx);
|
||||
|
||||
scan->xs_heaptid = *heaptid;
|
||||
scan->xs_recheck = false;
|
||||
scan->xs_recheckorderby = false;
|
||||
return true;
|
||||
}
|
||||
|
||||
197
src/hnswutils.c
197
src/hnswutils.c
@@ -3,15 +3,11 @@
|
||||
#include <math.h>
|
||||
|
||||
#include "access/generic_xlog.h"
|
||||
#include "catalog/pg_type.h"
|
||||
#include "hnsw.h"
|
||||
#include "lib/pairingheap.h"
|
||||
#include "sparsevec.h"
|
||||
#include "storage/bufmgr.h"
|
||||
#include "utils/datum.h"
|
||||
#include "utils/memdebug.h"
|
||||
#include "utils/rel.h"
|
||||
#include "utils/syscache.h"
|
||||
#include "vector.h"
|
||||
|
||||
#if PG_VERSION_NUM >= 130000
|
||||
@@ -152,32 +148,6 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
|
||||
return index_getprocinfo(index, 1, procnum);
|
||||
}
|
||||
|
||||
/*
|
||||
* Get vector type
|
||||
*/
|
||||
HnswType
|
||||
HnswGetType(Relation index)
|
||||
{
|
||||
Oid typeOid = TupleDescAttr(index->rd_att, 0)->atttypid;
|
||||
HeapTuple tuple;
|
||||
Form_pg_type type;
|
||||
int result;
|
||||
|
||||
tuple = SearchSysCache1(TYPEOID, ObjectIdGetDatum(typeOid));
|
||||
if (!HeapTupleIsValid(tuple))
|
||||
elog(ERROR, "cache lookup failed for type %u", typeOid);
|
||||
|
||||
type = (Form_pg_type) GETSTRUCT(tuple);
|
||||
if (strcmp(NameStr(type->typname), "sparsevec") == 0)
|
||||
result = HNSW_TYPE_SPARSEVEC;
|
||||
else
|
||||
result = HNSW_TYPE_VECTOR;
|
||||
|
||||
ReleaseSysCache(tuple);
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
/*
|
||||
* Divide by the norm
|
||||
*
|
||||
@@ -187,40 +157,21 @@ HnswGetType(Relation index)
|
||||
* if it's different than the original value
|
||||
*/
|
||||
bool
|
||||
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type)
|
||||
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
|
||||
{
|
||||
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
|
||||
|
||||
if (norm > 0)
|
||||
{
|
||||
/* TODO Remove vector-specific code */
|
||||
if (type == HNSW_TYPE_VECTOR)
|
||||
{
|
||||
Vector *v = DatumGetVector(*value);
|
||||
Vector *result = InitVector(v->dim);
|
||||
|
||||
if (result == NULL)
|
||||
result = InitVector(v->dim);
|
||||
|
||||
for (int i = 0; i < v->dim; i++)
|
||||
result->x[i] = v->x[i] / norm;
|
||||
|
||||
*value = PointerGetDatum(result);
|
||||
}
|
||||
else if (type == HNSW_TYPE_SPARSEVEC)
|
||||
{
|
||||
SparseVector *v = DatumGetSparseVector(*value);
|
||||
SparseVector *result = InitSparseVector(v->dim, v->nnz);
|
||||
float *vx = SPARSEVEC_VALUES(v);
|
||||
float *rx = SPARSEVEC_VALUES(result);
|
||||
|
||||
for (int i = 0; i < v->nnz; i++)
|
||||
{
|
||||
result->indices[i] = v->indices[i];
|
||||
rx[i] = vx[i] / norm;
|
||||
}
|
||||
|
||||
*value = PointerGetDatum(result);
|
||||
}
|
||||
else
|
||||
elog(ERROR, "Unsupported type");
|
||||
|
||||
return true;
|
||||
}
|
||||
@@ -228,21 +179,6 @@ HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type)
|
||||
return false;
|
||||
}
|
||||
|
||||
/*
|
||||
* Check if a value can be indexed
|
||||
*/
|
||||
void
|
||||
HnswCheckValue(Datum value, HnswType type)
|
||||
{
|
||||
if (type == HNSW_TYPE_SPARSEVEC)
|
||||
{
|
||||
SparseVector *vec = DatumGetSparseVector(value);
|
||||
|
||||
if (vec->nnz > HNSW_MAX_NNZ)
|
||||
elog(ERROR, "sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ);
|
||||
}
|
||||
}
|
||||
|
||||
/*
|
||||
* New buffer
|
||||
*/
|
||||
@@ -266,19 +202,6 @@ HnswInitPage(Buffer buf, Page page)
|
||||
HnswPageGetOpaque(page)->page_id = HNSW_PAGE_ID;
|
||||
}
|
||||
|
||||
/*
|
||||
* Allocate a neighbor array
|
||||
*/
|
||||
static HnswNeighborArray *
|
||||
HnswInitNeighborArray(int lm, HnswAllocator * allocator)
|
||||
{
|
||||
HnswNeighborArray *a = HnswAlloc(allocator, HNSW_NEIGHBOR_ARRAY_SIZE(lm));
|
||||
|
||||
a->length = 0;
|
||||
a->closerSet = false;
|
||||
return a;
|
||||
}
|
||||
|
||||
/*
|
||||
* Allocate neighbors
|
||||
*/
|
||||
@@ -286,12 +209,22 @@ void
|
||||
HnswInitNeighbors(char *base, HnswElement element, int m, HnswAllocator * allocator)
|
||||
{
|
||||
int level = element->level;
|
||||
|
||||
HnswNeighborArrayPtr *neighborList = (HnswNeighborArrayPtr *) HnswAlloc(allocator, sizeof(HnswNeighborArrayPtr) * (level + 1));
|
||||
|
||||
HnswPtrStore(base, element->neighbors, neighborList);
|
||||
|
||||
for (int lc = 0; lc <= level; lc++)
|
||||
HnswPtrStore(base, neighborList[lc], HnswInitNeighborArray(HnswGetLayerM(m, lc), allocator));
|
||||
{
|
||||
HnswNeighborArray *a;
|
||||
int lm = HnswGetLayerM(m, lc);
|
||||
|
||||
HnswPtrStore(base, neighborList[lc], (HnswNeighborArray *) HnswAlloc(allocator, offsetof(HnswNeighborArray, items) + sizeof(HnswCandidate) * lm));
|
||||
|
||||
a = HnswGetNeighbors(base, element, lc);
|
||||
a->length = 0;
|
||||
a->closerSet = false;
|
||||
}
|
||||
}
|
||||
|
||||
/*
|
||||
@@ -379,10 +312,7 @@ HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint)
|
||||
if (entryPoint != NULL)
|
||||
{
|
||||
if (BlockNumberIsValid(metap->entryBlkno))
|
||||
{
|
||||
*entryPoint = HnswInitElementFromBlock(metap->entryBlkno, metap->entryOffno);
|
||||
(*entryPoint)->level = metap->entryLevel;
|
||||
}
|
||||
else
|
||||
*entryPoint = NULL;
|
||||
}
|
||||
@@ -638,12 +568,7 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
|
||||
|
||||
/* Calculate distance */
|
||||
if (distance != NULL)
|
||||
{
|
||||
if (DatumGetPointer(*q) == NULL)
|
||||
*distance = 0;
|
||||
else
|
||||
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
|
||||
}
|
||||
|
||||
UnlockReleaseBuffer(buf);
|
||||
}
|
||||
@@ -806,7 +731,7 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
|
||||
/* Create local memory for neighborhood if needed */
|
||||
if (index == NULL)
|
||||
{
|
||||
neighborhoodSize = HNSW_NEIGHBOR_ARRAY_SIZE(HnswGetLayerM(m, lc));
|
||||
neighborhoodSize = offsetof(HnswNeighborArray, items) + sizeof(HnswCandidate) * HnswGetLayerM(m, lc);
|
||||
neighborhoodData = palloc(neighborhoodSize);
|
||||
}
|
||||
|
||||
@@ -928,15 +853,12 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
|
||||
static int
|
||||
#if PG_VERSION_NUM >= 130000
|
||||
CompareCandidateDistances(const ListCell *a, const ListCell *b)
|
||||
{
|
||||
HnswCandidate *hca = lfirst(a);
|
||||
HnswCandidate *hcb = lfirst(b);
|
||||
#else
|
||||
CompareCandidateDistances(const void *a, const void *b)
|
||||
{
|
||||
HnswCandidate *hca = lfirst(*(ListCell **) a);
|
||||
HnswCandidate *hcb = lfirst(*(ListCell **) b);
|
||||
#endif
|
||||
{
|
||||
HnswCandidate *hca = lfirst((ListCell *) a);
|
||||
HnswCandidate *hcb = lfirst((ListCell *) b);
|
||||
|
||||
if (hca->distance < hcb->distance)
|
||||
return 1;
|
||||
@@ -959,15 +881,12 @@ CompareCandidateDistances(const void *a, const void *b)
|
||||
static int
|
||||
#if PG_VERSION_NUM >= 130000
|
||||
CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b)
|
||||
{
|
||||
HnswCandidate *hca = lfirst(a);
|
||||
HnswCandidate *hcb = lfirst(b);
|
||||
#else
|
||||
CompareCandidateDistancesOffset(const void *a, const void *b)
|
||||
{
|
||||
HnswCandidate *hca = lfirst(*(ListCell **) a);
|
||||
HnswCandidate *hcb = lfirst(*(ListCell **) b);
|
||||
#endif
|
||||
{
|
||||
HnswCandidate *hca = lfirst((ListCell *) a);
|
||||
HnswCandidate *hcb = lfirst((ListCell *) b);
|
||||
|
||||
if (hca->distance < hcb->distance)
|
||||
return 1;
|
||||
@@ -988,10 +907,40 @@ CompareCandidateDistancesOffset(const void *a, const void *b)
|
||||
* Calculate the distance between elements
|
||||
*/
|
||||
static float
|
||||
HnswGetDistance(char *base, HnswElement a, HnswElement b, FmgrInfo *procinfo, Oid collation)
|
||||
HnswGetDistance(char *base, HnswElement a, HnswElement b, int lc, FmgrInfo *procinfo, Oid collation)
|
||||
{
|
||||
Datum aValue = HnswGetValue(base, a);
|
||||
Datum bValue = HnswGetValue(base, b);
|
||||
Datum aValue;
|
||||
Datum bValue;
|
||||
|
||||
/* Look for cached distance */
|
||||
if (!HnswPtrIsNull(base, a->neighbors))
|
||||
{
|
||||
HnswNeighborArray *neighbors = HnswGetNeighbors(base, a, lc);
|
||||
|
||||
for (int i = 0; i < neighbors->length; i++)
|
||||
{
|
||||
HnswElement element = HnswPtrAccess(base, neighbors->items[i].element);
|
||||
|
||||
if (element == b)
|
||||
return neighbors->items[i].distance;
|
||||
}
|
||||
}
|
||||
|
||||
if (!HnswPtrIsNull(base, b->neighbors))
|
||||
{
|
||||
HnswNeighborArray *neighbors = HnswGetNeighbors(base, b, lc);
|
||||
|
||||
for (int i = 0; i < neighbors->length; i++)
|
||||
{
|
||||
HnswElement element = HnswPtrAccess(base, neighbors->items[i].element);
|
||||
|
||||
if (element == a)
|
||||
return neighbors->items[i].distance;
|
||||
}
|
||||
}
|
||||
|
||||
aValue = HnswGetValue(base, a);
|
||||
bValue = HnswGetValue(base, b);
|
||||
|
||||
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, aValue, bValue));
|
||||
}
|
||||
@@ -1000,7 +949,7 @@ HnswGetDistance(char *base, HnswElement a, HnswElement b, FmgrInfo *procinfo, Oi
|
||||
* Check if an element is closer to q than any element from R
|
||||
*/
|
||||
static bool
|
||||
CheckElementCloser(char *base, HnswCandidate * e, List *r, FmgrInfo *procinfo, Oid collation)
|
||||
CheckElementCloser(char *base, HnswCandidate * e, List *r, int lc, FmgrInfo *procinfo, Oid collation)
|
||||
{
|
||||
HnswElement eElement = HnswPtrAccess(base, e->element);
|
||||
ListCell *lc2;
|
||||
@@ -1009,7 +958,7 @@ CheckElementCloser(char *base, HnswCandidate * e, List *r, FmgrInfo *procinfo, O
|
||||
{
|
||||
HnswCandidate *ri = lfirst(lc2);
|
||||
HnswElement riElement = HnswPtrAccess(base, ri->element);
|
||||
float distance = HnswGetDistance(base, eElement, riElement, procinfo, collation);
|
||||
float distance = HnswGetDistance(base, eElement, riElement, lc, procinfo, collation);
|
||||
|
||||
if (distance <= e->distance)
|
||||
return false;
|
||||
@@ -1026,9 +975,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
|
||||
{
|
||||
List *r = NIL;
|
||||
List *w = list_copy(c);
|
||||
HnswCandidate **wd;
|
||||
int wdlen = 0;
|
||||
int wdoff = 0;
|
||||
pairingheap *wd;
|
||||
HnswNeighborArray *neighbors = HnswGetNeighbors(base, e2, lc);
|
||||
bool mustCalculate = !neighbors->closerSet;
|
||||
List *added = NIL;
|
||||
@@ -1037,7 +984,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
|
||||
if (list_length(w) <= lm)
|
||||
return w;
|
||||
|
||||
wd = palloc(sizeof(HnswCandidate *) * list_length(w));
|
||||
wd = pairingheap_allocate(CompareNearestCandidates, NULL);
|
||||
|
||||
/* Ensure order of candidates is deterministic for closer caching */
|
||||
if (sortCandidates)
|
||||
@@ -1057,20 +1004,16 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
|
||||
|
||||
/* Use previous state of r and wd to skip work when possible */
|
||||
if (mustCalculate)
|
||||
e->closer = CheckElementCloser(base, e, r, procinfo, collation);
|
||||
e->closer = CheckElementCloser(base, e, r, lc, procinfo, collation);
|
||||
else if (list_length(added) > 0)
|
||||
{
|
||||
/* Keep Valgrind happy for in-memory, parallel builds */
|
||||
if (base != NULL)
|
||||
VALGRIND_MAKE_MEM_DEFINED(&e->closer, 1);
|
||||
|
||||
/*
|
||||
* If the current candidate was closer, we only need to compare it
|
||||
* with the other candidates that we have added.
|
||||
*/
|
||||
if (e->closer)
|
||||
{
|
||||
e->closer = CheckElementCloser(base, e, added, procinfo, collation);
|
||||
e->closer = CheckElementCloser(base, e, added, lc, procinfo, collation);
|
||||
|
||||
if (!e->closer)
|
||||
removedAny = true;
|
||||
@@ -1083,7 +1026,7 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
|
||||
*/
|
||||
if (removedAny)
|
||||
{
|
||||
e->closer = CheckElementCloser(base, e, r, procinfo, collation);
|
||||
e->closer = CheckElementCloser(base, e, r, lc, procinfo, collation);
|
||||
if (e->closer)
|
||||
added = lappend(added, e);
|
||||
}
|
||||
@@ -1091,33 +1034,29 @@ SelectNeighbors(char *base, List *c, int lm, int lc, FmgrInfo *procinfo, Oid col
|
||||
}
|
||||
else if (e == newCandidate)
|
||||
{
|
||||
e->closer = CheckElementCloser(base, e, r, procinfo, collation);
|
||||
e->closer = CheckElementCloser(base, e, r, lc, procinfo, collation);
|
||||
if (e->closer)
|
||||
added = lappend(added, e);
|
||||
}
|
||||
|
||||
/* Keep Valgrind happy for in-memory, parallel builds */
|
||||
if (base != NULL)
|
||||
VALGRIND_MAKE_MEM_DEFINED(&e->closer, 1);
|
||||
|
||||
if (e->closer)
|
||||
r = lappend(r, e);
|
||||
else
|
||||
wd[wdlen++] = e;
|
||||
pairingheap_add(wd, &(CreatePairingHeapNode(e)->ph_node));
|
||||
}
|
||||
|
||||
/* Cached value can only be used in future if sorted deterministically */
|
||||
neighbors->closerSet = sortCandidates;
|
||||
|
||||
/* Keep pruned connections */
|
||||
while (wdoff < wdlen && list_length(r) < lm)
|
||||
r = lappend(r, wd[wdoff++]);
|
||||
while (!pairingheap_is_empty(wd) && list_length(r) < lm)
|
||||
r = lappend(r, ((HnswPairingHeapNode *) pairingheap_remove_first(wd))->inner);
|
||||
|
||||
/* Return pruned for update connections */
|
||||
if (pruned != NULL)
|
||||
{
|
||||
if (wdoff < wdlen)
|
||||
*pruned = wd[wdoff];
|
||||
if (!pairingheap_is_empty(wd))
|
||||
*pruned = ((HnswPairingHeapNode *) pairingheap_first(wd))->inner;
|
||||
else
|
||||
*pruned = linitial(w);
|
||||
}
|
||||
|
||||
@@ -60,7 +60,8 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
|
||||
/* Iterate over nodes */
|
||||
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
|
||||
{
|
||||
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
|
||||
ItemId itemid = PageGetItemId(page, offno);
|
||||
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, itemid);
|
||||
int idx = 0;
|
||||
bool itemUpdated = false;
|
||||
|
||||
@@ -91,10 +92,15 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
|
||||
|
||||
if (itemUpdated)
|
||||
{
|
||||
Size etupSize = ItemIdGetLength(itemid);
|
||||
|
||||
/* Mark rest as invalid */
|
||||
for (int i = idx; i < HNSW_HEAPTIDS; i++)
|
||||
ItemPointerSetInvalid(&etup->heaptids[i]);
|
||||
|
||||
if (!PageIndexTupleOverwrite(page, offno, (Item) etup, etupSize))
|
||||
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
|
||||
|
||||
updated = true;
|
||||
}
|
||||
}
|
||||
@@ -207,9 +213,6 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
|
||||
/* Find neighbors for element, skipping itself */
|
||||
HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, true);
|
||||
|
||||
/* Zero memory for each element */
|
||||
MemSet(ntup, 0, HNSW_TUPLE_ALLOC_SIZE);
|
||||
|
||||
/* Update neighbor tuple */
|
||||
/* Do this before getting page to minimize locking */
|
||||
HnswSetNeighborTuple(base, ntup, element, m);
|
||||
@@ -476,8 +479,11 @@ MarkDeleted(HnswVacuumState * vacuumstate)
|
||||
/* Update element and neighbors together */
|
||||
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
|
||||
{
|
||||
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
|
||||
ItemId itemid = PageGetItemId(page, offno);
|
||||
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, itemid);
|
||||
HnswNeighborTuple ntup;
|
||||
Size etupSize;
|
||||
Size ntupSize;
|
||||
Buffer nbuf;
|
||||
Page npage;
|
||||
BlockNumber neighborPage;
|
||||
@@ -501,6 +507,10 @@ MarkDeleted(HnswVacuumState * vacuumstate)
|
||||
if (ItemPointerIsValid(&etup->heaptids[0]))
|
||||
continue;
|
||||
|
||||
/* Calculate sizes */
|
||||
etupSize = ItemIdGetLength(itemid);
|
||||
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(etup->level, vacuumstate->m);
|
||||
|
||||
/* Get neighbor page */
|
||||
neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
|
||||
neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
|
||||
@@ -527,10 +537,13 @@ MarkDeleted(HnswVacuumState * vacuumstate)
|
||||
for (int i = 0; i < ntup->count; i++)
|
||||
ItemPointerSetInvalid(&ntup->indextids[i]);
|
||||
|
||||
/*
|
||||
* We modified the tuples in place, no need to call
|
||||
* PageIndexTupleOverwrite
|
||||
*/
|
||||
/* Overwrite element tuple */
|
||||
if (!PageIndexTupleOverwrite(page, offno, (Item) etup, etupSize))
|
||||
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
|
||||
|
||||
/* Overwrite neighbor tuple */
|
||||
if (!PageIndexTupleOverwrite(npage, neighborOffno, (Item) ntup, ntupSize))
|
||||
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
|
||||
|
||||
/* Commit */
|
||||
GenericXLogFinish(state);
|
||||
@@ -575,7 +588,7 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
|
||||
vacuumstate->bas = GetAccessStrategy(BAS_BULKREAD);
|
||||
vacuumstate->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
|
||||
vacuumstate->collation = index->rd_indcollation[0];
|
||||
vacuumstate->ntup = palloc0(HNSW_TUPLE_ALLOC_SIZE);
|
||||
vacuumstate->ntup = palloc0(BLCKSZ);
|
||||
vacuumstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
|
||||
"Hnsw vacuum temporary context",
|
||||
ALLOCSET_DEFAULT_SIZES);
|
||||
|
||||
@@ -29,6 +29,8 @@
|
||||
#define CALLBACK_ITEM_POINTER HeapTuple hup
|
||||
#endif
|
||||
|
||||
#define UpdateProgress(index, val) pgstat_progress_update_param(index, val)
|
||||
|
||||
#if PG_VERSION_NUM >= 140000
|
||||
#include "utils/backend_status.h"
|
||||
#include "utils/wait_event.h"
|
||||
@@ -57,7 +59,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
|
||||
*/
|
||||
if (buildstate->kmeansnormprocinfo != NULL)
|
||||
{
|
||||
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value))
|
||||
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->normvec))
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -105,7 +107,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
|
||||
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
|
||||
|
||||
/* Add sample */
|
||||
AddSample(values, buildstate);
|
||||
AddSample(values, state);
|
||||
|
||||
/* Reset memory context */
|
||||
MemoryContextSwitchTo(oldCtx);
|
||||
@@ -153,7 +155,7 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
|
||||
/* Normalize if needed */
|
||||
if (buildstate->normprocinfo != NULL)
|
||||
{
|
||||
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value))
|
||||
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -260,9 +262,9 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
|
||||
TupleTableSlot *slot = MakeSingleTupleTableSlot(buildstate->tupdesc, &TTSOpsMinimalTuple);
|
||||
TupleDesc tupdesc = RelationGetDescr(index);
|
||||
|
||||
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_LOAD);
|
||||
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_LOAD);
|
||||
|
||||
pgstat_progress_update_param(PROGRESS_CREATEIDX_TUPLES_TOTAL, buildstate->indtuples);
|
||||
UpdateProgress(PROGRESS_CREATEIDX_TUPLES_TOTAL, buildstate->indtuples);
|
||||
|
||||
GetNextTuple(buildstate->sortstate, tupdesc, slot, &itup, &list);
|
||||
|
||||
@@ -298,7 +300,7 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
|
||||
|
||||
pfree(itup);
|
||||
|
||||
pgstat_progress_update_param(PROGRESS_CREATEIDX_TUPLES_DONE, ++inserted);
|
||||
UpdateProgress(PROGRESS_CREATEIDX_TUPLES_DONE, ++inserted);
|
||||
|
||||
GetNextTuple(buildstate->sortstate, tupdesc, slot, &itup, &list);
|
||||
}
|
||||
@@ -356,6 +358,9 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
|
||||
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions);
|
||||
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
|
||||
|
||||
/* Reuse for each tuple */
|
||||
buildstate->normvec = InitVector(buildstate->dimensions);
|
||||
|
||||
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
|
||||
"Ivfflat build temporary context",
|
||||
ALLOCSET_DEFAULT_SIZES);
|
||||
@@ -377,6 +382,7 @@ FreeBuildState(IvfflatBuildState * buildstate)
|
||||
{
|
||||
VectorArrayFree(buildstate->centers);
|
||||
pfree(buildstate->listInfo);
|
||||
pfree(buildstate->normvec);
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
pfree(buildstate->listSums);
|
||||
@@ -394,7 +400,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
|
||||
{
|
||||
int numSamples;
|
||||
|
||||
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_KMEANS);
|
||||
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_KMEANS);
|
||||
|
||||
/* Target 50 samples per list, with at least 10000 samples */
|
||||
/* The number of samples has a large effect on index build time */
|
||||
@@ -469,7 +475,7 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
|
||||
IvfflatList list;
|
||||
|
||||
listSize = MAXALIGN(IVFFLAT_LIST_SIZE(dimensions));
|
||||
list = palloc0(listSize);
|
||||
list = palloc(listSize);
|
||||
|
||||
buf = IvfflatNewBuffer(index, forkNum);
|
||||
IvfflatInitRegisterPage(index, &buf, &page, &state);
|
||||
@@ -915,7 +921,7 @@ AssignTuples(IvfflatBuildState * buildstate)
|
||||
Oid sortCollations[] = {InvalidOid};
|
||||
bool nullsFirstFlags[] = {false};
|
||||
|
||||
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_ASSIGN);
|
||||
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_ASSIGN);
|
||||
|
||||
/* Calculate parallel workers */
|
||||
if (buildstate->heap != NULL)
|
||||
|
||||
@@ -172,6 +172,7 @@ typedef struct IvfflatBuildState
|
||||
VectorArray samples;
|
||||
VectorArray centers;
|
||||
ListInfo *listInfo;
|
||||
Vector *normvec;
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
double inertia;
|
||||
@@ -266,7 +267,7 @@ void VectorArrayFree(VectorArray arr);
|
||||
void PrintVectorArray(char *msg, VectorArray arr);
|
||||
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
|
||||
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
|
||||
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value);
|
||||
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
|
||||
int IvfflatGetLists(Relation index);
|
||||
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
|
||||
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);
|
||||
|
||||
@@ -85,7 +85,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
|
||||
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
|
||||
if (normprocinfo != NULL)
|
||||
{
|
||||
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value))
|
||||
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
|
||||
return;
|
||||
}
|
||||
|
||||
|
||||
@@ -293,7 +293,7 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
|
||||
/* Fine if normalization fails */
|
||||
if (so->normprocinfo != NULL)
|
||||
IvfflatNormValue(so->normprocinfo, so->collation, &value);
|
||||
IvfflatNormValue(so->normprocinfo, so->collation, &value, NULL);
|
||||
}
|
||||
|
||||
IvfflatBench("GetScanLists", GetScanLists(scan, value));
|
||||
@@ -310,7 +310,6 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
|
||||
|
||||
scan->xs_heaptid = *heaptid;
|
||||
scan->xs_recheck = false;
|
||||
scan->xs_recheckorderby = false;
|
||||
return true;
|
||||
}
|
||||
|
||||
@@ -75,14 +75,16 @@ IvfflatOptionalProcInfo(Relation index, uint16 procnum)
|
||||
* if it's different than the original value
|
||||
*/
|
||||
bool
|
||||
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value)
|
||||
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
|
||||
{
|
||||
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
|
||||
|
||||
if (norm > 0)
|
||||
{
|
||||
Vector *v = DatumGetVector(*value);
|
||||
Vector *result = InitVector(v->dim);
|
||||
|
||||
if (result == NULL)
|
||||
result = InitVector(v->dim);
|
||||
|
||||
for (int i = 0; i < v->dim; i++)
|
||||
result->x[i] = v->x[i] / norm;
|
||||
|
||||
779
src/sparsevec.c
779
src/sparsevec.c
@@ -1,779 +0,0 @@
|
||||
#include "postgres.h"
|
||||
|
||||
#include <limits.h>
|
||||
#include <math.h>
|
||||
|
||||
#include "fmgr.h"
|
||||
#include "libpq/pqformat.h"
|
||||
#include "sparsevec.h"
|
||||
#include "utils/array.h"
|
||||
#include "utils/builtins.h"
|
||||
#include "vector.h"
|
||||
|
||||
#if PG_VERSION_NUM >= 120000
|
||||
#include "common/shortest_dec.h"
|
||||
#include "utils/float.h"
|
||||
#else
|
||||
#include <float.h>
|
||||
#include "utils/builtins.h"
|
||||
#endif
|
||||
|
||||
/*
|
||||
* Ensure same dimensions
|
||||
*/
|
||||
static inline void
|
||||
CheckDims(SparseVector * a, SparseVector * b)
|
||||
{
|
||||
if (a->dim != b->dim)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("different sparsevec dimensions %d and %d", a->dim, b->dim)));
|
||||
}
|
||||
|
||||
/*
|
||||
* Ensure expected dimensions
|
||||
*/
|
||||
static inline void
|
||||
CheckExpectedDim(int32 typmod, int dim)
|
||||
{
|
||||
if (typmod != -1 && typmod != dim)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("expected %d dimensions, not %d", typmod, dim)));
|
||||
}
|
||||
|
||||
/*
|
||||
* Ensure valid dimensions
|
||||
*/
|
||||
static inline void
|
||||
CheckDim(int dim)
|
||||
{
|
||||
if (dim < 1)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("sparsevec must have at least 1 dimension")));
|
||||
|
||||
if (dim > SPARSEVEC_MAX_DIM)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
|
||||
errmsg("sparsevec cannot have more than %d dimensions", SPARSEVEC_MAX_DIM)));
|
||||
}
|
||||
|
||||
/*
|
||||
* Ensure valid nnz
|
||||
*/
|
||||
static inline void
|
||||
CheckNnz(int nnz, int dim)
|
||||
{
|
||||
if (nnz < 0)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("sparsevec must have at least one element")));
|
||||
|
||||
if (nnz > dim)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
|
||||
errmsg("sparsevec cannot have more elements than dimensions")));
|
||||
}
|
||||
|
||||
/*
|
||||
* Ensure valid index
|
||||
*/
|
||||
static inline void
|
||||
CheckIndex(int32 *indices, int i, int dim)
|
||||
{
|
||||
int32 index = indices[i];
|
||||
|
||||
if (index < 0)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("index must not be negative")));
|
||||
|
||||
if (index >= dim)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("index must be less than dimensions")));
|
||||
|
||||
if (i > 0)
|
||||
{
|
||||
if (index < indices[i - 1])
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("indexes must be in ascending order")));
|
||||
|
||||
if (index == indices[i - 1])
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("indexes must not contain duplicates")));
|
||||
}
|
||||
}
|
||||
|
||||
/*
|
||||
* Ensure finite element
|
||||
*/
|
||||
static inline void
|
||||
CheckElement(float value)
|
||||
{
|
||||
if (isnan(value))
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("NaN not allowed in sparsevec")));
|
||||
|
||||
if (isinf(value))
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("infinite value not allowed in sparsevec")));
|
||||
}
|
||||
|
||||
/*
|
||||
* Allocate and initialize a new sparse vector
|
||||
*/
|
||||
SparseVector *
|
||||
InitSparseVector(int dim, int nnz)
|
||||
{
|
||||
SparseVector *result;
|
||||
int size;
|
||||
|
||||
size = SPARSEVEC_SIZE(nnz);
|
||||
result = (SparseVector *) palloc0(size);
|
||||
SET_VARSIZE(result, size);
|
||||
result->dim = dim;
|
||||
result->nnz = nnz;
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
/*
|
||||
* Check for whitespace, since array_isspace() is static
|
||||
*/
|
||||
static inline bool
|
||||
sparsevec_isspace(char ch)
|
||||
{
|
||||
if (ch == ' ' ||
|
||||
ch == '\t' ||
|
||||
ch == '\n' ||
|
||||
ch == '\r' ||
|
||||
ch == '\v' ||
|
||||
ch == '\f')
|
||||
return true;
|
||||
return false;
|
||||
}
|
||||
|
||||
/*
|
||||
* Convert textual representation to internal representation
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_in);
|
||||
Datum
|
||||
sparsevec_in(PG_FUNCTION_ARGS)
|
||||
{
|
||||
char *lit = PG_GETARG_CSTRING(0);
|
||||
int32 typmod = PG_GETARG_INT32(2);
|
||||
int dim;
|
||||
char *pt;
|
||||
char *stringEnd;
|
||||
SparseVector *result;
|
||||
float *rvalues;
|
||||
char *litcopy = pstrdup(lit);
|
||||
char *str = litcopy;
|
||||
int32 *indices;
|
||||
float *values;
|
||||
int maxNnz;
|
||||
int nnz = 0;
|
||||
|
||||
maxNnz = 1;
|
||||
pt = str;
|
||||
while (*pt != '\0')
|
||||
{
|
||||
if (*pt == ',')
|
||||
maxNnz++;
|
||||
|
||||
pt++;
|
||||
}
|
||||
|
||||
indices = palloc(maxNnz * sizeof(int32));
|
||||
values = palloc(maxNnz * sizeof(float));
|
||||
|
||||
while (sparsevec_isspace(*str))
|
||||
str++;
|
||||
|
||||
if (*str != '{')
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("malformed sparsevec literal: \"%s\"", lit),
|
||||
errdetail("Vector contents must start with \"{\".")));
|
||||
|
||||
str++;
|
||||
pt = strtok(str, ",");
|
||||
stringEnd = pt;
|
||||
|
||||
while (pt != NULL && *stringEnd != '}')
|
||||
{
|
||||
long index;
|
||||
float value;
|
||||
|
||||
/* TODO Better error */
|
||||
if (nnz == maxNnz)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("ran out of buffer: \"%s\"", lit)));
|
||||
|
||||
while (sparsevec_isspace(*pt))
|
||||
pt++;
|
||||
|
||||
/* Check for empty string like float4in */
|
||||
if (*pt == '\0')
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
|
||||
|
||||
/* Use similar logic as int2vectorin */
|
||||
errno = 0;
|
||||
index = strtol(pt, &stringEnd, 10);
|
||||
|
||||
if (stringEnd == pt)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
|
||||
|
||||
if (errno == ERANGE || index < 0 || index > INT_MAX)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
|
||||
errmsg("index \"%ld\" is out of range for type sparsevec", index)));
|
||||
|
||||
if (stringEnd == pt)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
|
||||
|
||||
while (sparsevec_isspace(*stringEnd))
|
||||
stringEnd++;
|
||||
|
||||
if (*stringEnd != ':')
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
|
||||
|
||||
stringEnd++;
|
||||
|
||||
while (sparsevec_isspace(*stringEnd))
|
||||
stringEnd++;
|
||||
|
||||
errno = 0;
|
||||
pt = stringEnd;
|
||||
value = strtof(pt, &stringEnd);
|
||||
|
||||
if (stringEnd == pt)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
|
||||
|
||||
/* Check for range error like float4in */
|
||||
if (errno == ERANGE && (value == 0 || isinf(value)))
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
|
||||
errmsg("\"%s\" is out of range for type sparsevec", pt)));
|
||||
|
||||
/* TODO Decide whether to store zero values */
|
||||
if (value != 0)
|
||||
{
|
||||
indices[nnz] = index;
|
||||
values[nnz] = value;
|
||||
nnz++;
|
||||
}
|
||||
|
||||
if (*stringEnd != '\0' && *stringEnd != '}')
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
|
||||
|
||||
pt = strtok(NULL, ",");
|
||||
}
|
||||
|
||||
if (stringEnd == NULL || *stringEnd != '}')
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("malformed sparsevec literal: \"%s\"", lit),
|
||||
errdetail("Unexpected end of input.")));
|
||||
|
||||
stringEnd++;
|
||||
|
||||
if (*stringEnd != '/')
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("malformed sparsevec literal: \"%s\"", lit),
|
||||
errdetail("Unexpected end of input.")));
|
||||
|
||||
stringEnd++;
|
||||
|
||||
/* Use similar logic as int2vectorin */
|
||||
errno = 0;
|
||||
pt = stringEnd;
|
||||
dim = strtol(pt, &stringEnd, 10);
|
||||
|
||||
if (stringEnd == pt)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
|
||||
|
||||
/* Only whitespace is allowed after the closing brace */
|
||||
while (sparsevec_isspace(*stringEnd))
|
||||
stringEnd++;
|
||||
|
||||
if (*stringEnd != '\0')
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("malformed sparsevec literal: \"%s\"", lit),
|
||||
errdetail("Junk after closing.")));
|
||||
|
||||
pfree(litcopy);
|
||||
|
||||
CheckDim(dim);
|
||||
CheckExpectedDim(typmod, dim);
|
||||
|
||||
result = InitSparseVector(dim, nnz);
|
||||
rvalues = SPARSEVEC_VALUES(result);
|
||||
for (int i = 0; i < nnz; i++)
|
||||
{
|
||||
result->indices[i] = indices[i];
|
||||
rvalues[i] = values[i];
|
||||
|
||||
CheckIndex(result->indices, i, dim);
|
||||
CheckElement(rvalues[i]);
|
||||
}
|
||||
|
||||
PG_RETURN_POINTER(result);
|
||||
}
|
||||
|
||||
#define AppendChar(ptr, c) (*(ptr)++ = (c))
|
||||
#define AppendFloat(ptr, f) ((ptr) += float_to_shortest_decimal_bufn((f), (ptr)))
|
||||
|
||||
#if PG_VERSION_NUM >= 140000
|
||||
#define AppendInt(ptr, i) ((ptr) += pg_ltoa((i), (ptr)))
|
||||
#else
|
||||
#define AppendInt(ptr, i) \
|
||||
do { \
|
||||
pg_ltoa(i, ptr); \
|
||||
while (*ptr != '\0') \
|
||||
ptr++; \
|
||||
} while (0)
|
||||
#endif
|
||||
|
||||
/*
|
||||
* Convert internal representation to textual representation
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_out);
|
||||
Datum
|
||||
sparsevec_out(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *sparsevec = PG_GETARG_SPARSEVEC_P(0);
|
||||
float *values = SPARSEVEC_VALUES(sparsevec);
|
||||
char *buf;
|
||||
char *ptr;
|
||||
|
||||
/*
|
||||
* Need:
|
||||
*
|
||||
* nnz * 10 bytes for index (positive integer)
|
||||
*
|
||||
* nnz bytes for :
|
||||
*
|
||||
* nnz * (FLOAT_SHORTEST_DECIMAL_LEN - 1) bytes for
|
||||
* float_to_shortest_decimal_bufn
|
||||
*
|
||||
* nnz - 1 bytes for ,
|
||||
*
|
||||
* 10 bytes for dimensions
|
||||
*
|
||||
* 4 bytes for {, }, /, and \0
|
||||
*/
|
||||
buf = (char *) palloc((11 + FLOAT_SHORTEST_DECIMAL_LEN) * sparsevec->nnz + 13);
|
||||
ptr = buf;
|
||||
|
||||
AppendChar(ptr, '{');
|
||||
|
||||
for (int i = 0; i < sparsevec->nnz; i++)
|
||||
{
|
||||
if (i > 0)
|
||||
AppendChar(ptr, ',');
|
||||
|
||||
AppendInt(ptr, sparsevec->indices[i]);
|
||||
AppendChar(ptr, ':');
|
||||
AppendFloat(ptr, values[i]);
|
||||
}
|
||||
|
||||
AppendChar(ptr, '}');
|
||||
AppendChar(ptr, '/');
|
||||
AppendInt(ptr, sparsevec->dim);
|
||||
|
||||
*ptr = '\0';
|
||||
|
||||
PG_FREE_IF_COPY(sparsevec, 0);
|
||||
PG_RETURN_CSTRING(buf);
|
||||
}
|
||||
|
||||
/*
|
||||
* Convert type modifier
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_typmod_in);
|
||||
Datum
|
||||
sparsevec_typmod_in(PG_FUNCTION_ARGS)
|
||||
{
|
||||
ArrayType *ta = PG_GETARG_ARRAYTYPE_P(0);
|
||||
int32 *tl;
|
||||
int n;
|
||||
|
||||
tl = ArrayGetIntegerTypmods(ta, &n);
|
||||
|
||||
if (n != 1)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
|
||||
errmsg("invalid type modifier")));
|
||||
|
||||
if (*tl < 1)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
|
||||
errmsg("dimensions for type sparsevec must be at least 1")));
|
||||
|
||||
if (*tl > SPARSEVEC_MAX_DIM)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
|
||||
errmsg("dimensions for type sparsevec cannot exceed %d", SPARSEVEC_MAX_DIM)));
|
||||
|
||||
PG_RETURN_INT32(*tl);
|
||||
}
|
||||
|
||||
/*
|
||||
* Convert external binary representation to internal representation
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_recv);
|
||||
Datum
|
||||
sparsevec_recv(PG_FUNCTION_ARGS)
|
||||
{
|
||||
StringInfo buf = (StringInfo) PG_GETARG_POINTER(0);
|
||||
int32 typmod = PG_GETARG_INT32(2);
|
||||
SparseVector *result;
|
||||
int32 dim;
|
||||
int32 nnz;
|
||||
int32 unused;
|
||||
float *values;
|
||||
|
||||
dim = pq_getmsgint(buf, sizeof(int32));
|
||||
nnz = pq_getmsgint(buf, sizeof(int32));
|
||||
unused = pq_getmsgint(buf, sizeof(int32));
|
||||
|
||||
CheckDim(dim);
|
||||
CheckNnz(nnz, dim);
|
||||
CheckExpectedDim(typmod, dim);
|
||||
|
||||
if (unused != 0)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("expected unused to be 0, not %d", unused)));
|
||||
|
||||
result = InitSparseVector(dim, nnz);
|
||||
values = SPARSEVEC_VALUES(result);
|
||||
|
||||
for (int i = 0; i < nnz; i++)
|
||||
{
|
||||
result->indices[i] = pq_getmsgint(buf, sizeof(int32));
|
||||
CheckIndex(result->indices, i, dim);
|
||||
}
|
||||
|
||||
for (int i = 0; i < nnz; i++)
|
||||
{
|
||||
values[i] = pq_getmsgfloat4(buf);
|
||||
CheckElement(values[i]);
|
||||
}
|
||||
|
||||
PG_RETURN_POINTER(result);
|
||||
}
|
||||
|
||||
/*
|
||||
* Convert internal representation to the external binary representation
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_send);
|
||||
Datum
|
||||
sparsevec_send(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
|
||||
float *values = SPARSEVEC_VALUES(svec);
|
||||
StringInfoData buf;
|
||||
|
||||
pq_begintypsend(&buf);
|
||||
pq_sendint(&buf, svec->dim, sizeof(int32));
|
||||
pq_sendint(&buf, svec->nnz, sizeof(int32));
|
||||
pq_sendint(&buf, svec->unused, sizeof(int32));
|
||||
for (int i = 0; i < svec->nnz; i++)
|
||||
pq_sendint(&buf, svec->indices[i], sizeof(int32));
|
||||
for (int i = 0; i < svec->nnz; i++)
|
||||
pq_sendfloat4(&buf, values[i]);
|
||||
|
||||
PG_RETURN_BYTEA_P(pq_endtypsend(&buf));
|
||||
}
|
||||
|
||||
/*
|
||||
* Convert sparse vector to sparse vector
|
||||
* This is needed to check the type modifier
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec);
|
||||
Datum
|
||||
sparsevec(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
|
||||
int32 typmod = PG_GETARG_INT32(1);
|
||||
|
||||
CheckExpectedDim(typmod, svec->dim);
|
||||
|
||||
PG_RETURN_POINTER(svec);
|
||||
}
|
||||
|
||||
/*
|
||||
* Convert dense vector to sparse vector
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_sparsevec);
|
||||
Datum
|
||||
vector_to_sparsevec(PG_FUNCTION_ARGS)
|
||||
{
|
||||
Vector *vec = PG_GETARG_VECTOR_P(0);
|
||||
int32 typmod = PG_GETARG_INT32(1);
|
||||
SparseVector *result;
|
||||
int dim = vec->dim;
|
||||
int nnz = 0;
|
||||
float *values;
|
||||
int j = 0;
|
||||
|
||||
CheckDim(dim);
|
||||
CheckExpectedDim(typmod, dim);
|
||||
|
||||
for (int i = 0; i < dim; i++)
|
||||
{
|
||||
if (vec->x[i] != 0)
|
||||
nnz++;
|
||||
}
|
||||
|
||||
result = InitSparseVector(dim, nnz);
|
||||
values = SPARSEVEC_VALUES(result);
|
||||
for (int i = 0; i < dim; i++)
|
||||
{
|
||||
if (vec->x[i] != 0)
|
||||
{
|
||||
/* Safety check */
|
||||
if (j == nnz)
|
||||
elog(ERROR, "safety check failed");
|
||||
|
||||
result->indices[j] = i;
|
||||
values[j] = vec->x[i];
|
||||
j++;
|
||||
}
|
||||
}
|
||||
|
||||
PG_RETURN_POINTER(result);
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the L2 squared distance between sparse vectors
|
||||
*/
|
||||
static double
|
||||
l2_distance_squared_internal(SparseVector * a, SparseVector * b)
|
||||
{
|
||||
float *ax = SPARSEVEC_VALUES(a);
|
||||
float *bx = SPARSEVEC_VALUES(b);
|
||||
double distance = 0.0;
|
||||
int bpos = 0;
|
||||
|
||||
for (int i = 0; i < a->nnz; i++)
|
||||
{
|
||||
int ai = a->indices[i];
|
||||
int bi = -1;
|
||||
|
||||
for (int j = bpos; j < b->nnz; j++)
|
||||
{
|
||||
bi = b->indices[j];
|
||||
|
||||
if (ai == bi)
|
||||
{
|
||||
double diff = ax[i] - bx[j];
|
||||
|
||||
distance += diff * diff;
|
||||
}
|
||||
else if (ai > bi)
|
||||
distance += bx[j] * bx[j];
|
||||
|
||||
/* Update start for next iteration */
|
||||
if (ai >= bi)
|
||||
bpos = j + 1;
|
||||
|
||||
/* Found or passed it */
|
||||
if (bi >= ai)
|
||||
break;
|
||||
}
|
||||
|
||||
if (ai != bi)
|
||||
distance += ax[i] * ax[i];
|
||||
}
|
||||
|
||||
for (int j = bpos; j < b->nnz; j++)
|
||||
distance += bx[j] * bx[j];
|
||||
|
||||
return distance;
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the L2 distance between sparse vectors
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_distance);
|
||||
Datum
|
||||
sparsevec_l2_distance(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
|
||||
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
|
||||
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_FLOAT8(sqrt(l2_distance_squared_internal(a, b)));
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the L2 squared distance between sparse vectors
|
||||
* This saves a sqrt calculation
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_squared_distance);
|
||||
Datum
|
||||
sparsevec_l2_squared_distance(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
|
||||
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
|
||||
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_FLOAT8(l2_distance_squared_internal(a, b));
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the inner product of two sparse vectors
|
||||
*/
|
||||
static double
|
||||
inner_product_internal(SparseVector * a, SparseVector * b)
|
||||
{
|
||||
float *ax = SPARSEVEC_VALUES(a);
|
||||
float *bx = SPARSEVEC_VALUES(b);
|
||||
double distance = 0.0;
|
||||
int bpos = 0;
|
||||
|
||||
for (int i = 0; i < a->nnz; i++)
|
||||
{
|
||||
int ai = a->indices[i];
|
||||
|
||||
for (int j = bpos; j < b->nnz; j++)
|
||||
{
|
||||
int bi = b->indices[j];
|
||||
|
||||
/* Only update when the same index */
|
||||
if (ai == bi)
|
||||
distance += ax[i] * bx[j];
|
||||
|
||||
/* Update start for next iteration */
|
||||
if (ai >= bi)
|
||||
bpos = j + 1;
|
||||
|
||||
/* Found or passed it */
|
||||
if (bi >= ai)
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
return distance;
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the inner product of two sparse vectors
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_inner_product);
|
||||
Datum
|
||||
sparsevec_inner_product(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
|
||||
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
|
||||
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_FLOAT8(inner_product_internal(a, b));
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the negative inner product of two sparse vectors
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_negative_inner_product);
|
||||
Datum
|
||||
sparsevec_negative_inner_product(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
|
||||
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
|
||||
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_FLOAT8(-inner_product_internal(a, b));
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the cosine distance between two sparse vectors
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_cosine_distance);
|
||||
Datum
|
||||
sparsevec_cosine_distance(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
|
||||
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
|
||||
float *ax = SPARSEVEC_VALUES(a);
|
||||
float *bx = SPARSEVEC_VALUES(b);
|
||||
float norma = 0.0;
|
||||
float normb = 0.0;
|
||||
double similarity;
|
||||
|
||||
CheckDims(a, b);
|
||||
|
||||
similarity = inner_product_internal(a, b);
|
||||
|
||||
/* Auto-vectorized */
|
||||
for (int i = 0; i < a->nnz; i++)
|
||||
norma += ax[i] * ax[i];
|
||||
|
||||
/* Auto-vectorized */
|
||||
for (int i = 0; i < b->nnz; i++)
|
||||
normb += bx[i] * bx[i];
|
||||
|
||||
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
|
||||
similarity /= sqrt((double) norma * (double) normb);
|
||||
|
||||
#ifdef _MSC_VER
|
||||
/* /fp:fast may not propagate NaN */
|
||||
if (isnan(similarity))
|
||||
PG_RETURN_FLOAT8(NAN);
|
||||
#endif
|
||||
|
||||
/* Keep in range */
|
||||
if (similarity > 1)
|
||||
similarity = 1.0;
|
||||
else if (similarity < -1)
|
||||
similarity = -1.0;
|
||||
|
||||
PG_RETURN_FLOAT8(1.0 - similarity);
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the L2 norm of a sparse vector
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_norm);
|
||||
Datum
|
||||
sparsevec_norm(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
|
||||
float *ax = SPARSEVEC_VALUES(a);
|
||||
double norm = 0.0;
|
||||
|
||||
/* Auto-vectorized */
|
||||
for (int i = 0; i < a->nnz; i++)
|
||||
norm += (double) ax[i] * (double) ax[i];
|
||||
|
||||
PG_RETURN_FLOAT8(sqrt(norm));
|
||||
}
|
||||
@@ -1,23 +0,0 @@
|
||||
#ifndef SPARSEVEC_H
|
||||
#define SPARSEVEC_H
|
||||
|
||||
#define SPARSEVEC_MAX_DIM 100000
|
||||
|
||||
#define SPARSEVEC_SIZE(_nnz) (offsetof(SparseVector, indices) + MAXALIGN((_nnz) * sizeof(int32)) + (_nnz * sizeof(float)))
|
||||
#define SPARSEVEC_VALUES(x) ((float *) (((char *) (x)) + offsetof(SparseVector, indices) + MAXALIGN((x)->nnz * sizeof(int32))))
|
||||
#define DatumGetSparseVector(x) ((SparseVector *) PG_DETOAST_DATUM(x))
|
||||
#define PG_GETARG_SPARSEVEC_P(x) DatumGetSparseVector(PG_GETARG_DATUM(x))
|
||||
#define PG_RETURN_SPARSEVEC_P(x) PG_RETURN_POINTER(x)
|
||||
|
||||
typedef struct SparseVector
|
||||
{
|
||||
int32 vl_len_; /* varlena header (do not touch directly!) */
|
||||
int32 dim; /* number of dimensions */
|
||||
int32 nnz;
|
||||
int32 unused;
|
||||
int32 indices[FLEXIBLE_ARRAY_MEMBER];
|
||||
} SparseVector;
|
||||
|
||||
SparseVector *InitSparseVector(int dim, int nnz);
|
||||
|
||||
#endif
|
||||
85
src/vector.c
85
src/vector.c
@@ -10,7 +10,7 @@
|
||||
#include "lib/stringinfo.h"
|
||||
#include "libpq/pqformat.h"
|
||||
#include "port.h" /* for strtof() */
|
||||
#include "sparsevec.h"
|
||||
#include "port/pg_bitutils.h"
|
||||
#include "utils/array.h"
|
||||
#include "utils/builtins.h"
|
||||
#include "utils/float.h"
|
||||
@@ -867,10 +867,9 @@ vector_mul(PG_FUNCTION_ARGS)
|
||||
int
|
||||
vector_cmp_internal(Vector * a, Vector * b)
|
||||
{
|
||||
int dim = Min(a->dim, b->dim);
|
||||
CheckDims(a, b);
|
||||
|
||||
/* Check values before dimensions to be consistent with Postgres arrays */
|
||||
for (int i = 0; i < dim; i++)
|
||||
for (int i = 0; i < a->dim; i++)
|
||||
{
|
||||
if (a->x[i] < b->x[i])
|
||||
return -1;
|
||||
@@ -878,13 +877,6 @@ vector_cmp_internal(Vector * a, Vector * b)
|
||||
if (a->x[i] > b->x[i])
|
||||
return 1;
|
||||
}
|
||||
|
||||
if (a->dim < b->dim)
|
||||
return -1;
|
||||
|
||||
if (a->dim > b->dim)
|
||||
return 1;
|
||||
|
||||
return 0;
|
||||
}
|
||||
|
||||
@@ -898,9 +890,6 @@ vector_lt(PG_FUNCTION_ARGS)
|
||||
Vector *a = PG_GETARG_VECTOR_P(0);
|
||||
Vector *b = PG_GETARG_VECTOR_P(1);
|
||||
|
||||
/* TODO Remove in 0.7.0 */
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_BOOL(vector_cmp_internal(a, b) < 0);
|
||||
}
|
||||
|
||||
@@ -914,9 +903,6 @@ vector_le(PG_FUNCTION_ARGS)
|
||||
Vector *a = PG_GETARG_VECTOR_P(0);
|
||||
Vector *b = PG_GETARG_VECTOR_P(1);
|
||||
|
||||
/* TODO Remove in 0.7.0 */
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_BOOL(vector_cmp_internal(a, b) <= 0);
|
||||
}
|
||||
|
||||
@@ -930,9 +916,6 @@ vector_eq(PG_FUNCTION_ARGS)
|
||||
Vector *a = PG_GETARG_VECTOR_P(0);
|
||||
Vector *b = PG_GETARG_VECTOR_P(1);
|
||||
|
||||
/* TODO Remove in 0.7.0 */
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_BOOL(vector_cmp_internal(a, b) == 0);
|
||||
}
|
||||
|
||||
@@ -946,9 +929,6 @@ vector_ne(PG_FUNCTION_ARGS)
|
||||
Vector *a = PG_GETARG_VECTOR_P(0);
|
||||
Vector *b = PG_GETARG_VECTOR_P(1);
|
||||
|
||||
/* TODO Remove in 0.7.0 */
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_BOOL(vector_cmp_internal(a, b) != 0);
|
||||
}
|
||||
|
||||
@@ -962,9 +942,6 @@ vector_ge(PG_FUNCTION_ARGS)
|
||||
Vector *a = PG_GETARG_VECTOR_P(0);
|
||||
Vector *b = PG_GETARG_VECTOR_P(1);
|
||||
|
||||
/* TODO Remove in 0.7.0 */
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_BOOL(vector_cmp_internal(a, b) >= 0);
|
||||
}
|
||||
|
||||
@@ -978,9 +955,6 @@ vector_gt(PG_FUNCTION_ARGS)
|
||||
Vector *a = PG_GETARG_VECTOR_P(0);
|
||||
Vector *b = PG_GETARG_VECTOR_P(1);
|
||||
|
||||
/* TODO Remove in 0.7.0 */
|
||||
CheckDims(a, b);
|
||||
|
||||
PG_RETURN_BOOL(vector_cmp_internal(a, b) > 0);
|
||||
}
|
||||
|
||||
@@ -1163,24 +1137,41 @@ vector_avg(PG_FUNCTION_ARGS)
|
||||
}
|
||||
|
||||
/*
|
||||
* Convert sparse vector to dense vector
|
||||
* Ensure same number of bytes
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_to_vector);
|
||||
Datum
|
||||
sparsevec_to_vector(PG_FUNCTION_ARGS)
|
||||
static inline void
|
||||
CheckByteLengths(uint32 aLen, uint32 bLen)
|
||||
{
|
||||
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
|
||||
int32 typmod = PG_GETARG_INT32(1);
|
||||
Vector *result;
|
||||
int dim = svec->dim;
|
||||
float *values = SPARSEVEC_VALUES(svec);
|
||||
|
||||
CheckDim(dim);
|
||||
CheckExpectedDim(typmod, dim);
|
||||
|
||||
result = InitVector(dim);
|
||||
for (int i = 0; i < svec->nnz; i++)
|
||||
result->x[svec->indices[i]] = values[i];
|
||||
|
||||
PG_RETURN_POINTER(result);
|
||||
if (aLen != bLen)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_DATA_EXCEPTION),
|
||||
errmsg("different byte lengths %u and %u", aLen, bLen)));
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the Hamming distance between two binary strings
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(hamming_distance);
|
||||
Datum
|
||||
hamming_distance(PG_FUNCTION_ARGS)
|
||||
{
|
||||
bytea *a = PG_GETARG_BYTEA_PP(0);
|
||||
bytea *b = PG_GETARG_BYTEA_PP(1);
|
||||
char *ax = VARDATA_ANY(a);
|
||||
char *bx = VARDATA_ANY(b);
|
||||
uint32 aLen = VARSIZE_ANY_EXHDR(a);
|
||||
uint32 bLen = VARSIZE_ANY_EXHDR(b);
|
||||
uint64 distance = 0;
|
||||
|
||||
CheckByteLengths(aLen, bLen);
|
||||
|
||||
for (uint32 i = 0; i < aLen; i++)
|
||||
{
|
||||
unsigned char diff = (unsigned char) (ax[i] ^ bx[i]);
|
||||
|
||||
distance += pg_number_of_ones[diff];
|
||||
}
|
||||
|
||||
/* TODO Decide on return type */
|
||||
PG_RETURN_FLOAT8((double) distance);
|
||||
}
|
||||
|
||||
@@ -24,56 +24,6 @@ SELECT '[1e37]'::vector * '[1e37]';
|
||||
ERROR: value out of range: overflow
|
||||
SELECT '[1e-37]'::vector * '[1e-37]';
|
||||
ERROR: value out of range: underflow
|
||||
SELECT '[1,2,3]'::vector = '[1,2,3]';
|
||||
?column?
|
||||
----------
|
||||
t
|
||||
(1 row)
|
||||
|
||||
SELECT '[1,2,3]'::vector = '[1,2]';
|
||||
ERROR: different vector dimensions 3 and 2
|
||||
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
|
||||
vector_cmp
|
||||
------------
|
||||
0
|
||||
(1 row)
|
||||
|
||||
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
|
||||
vector_cmp
|
||||
------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
|
||||
vector_cmp
|
||||
------------
|
||||
-1
|
||||
(1 row)
|
||||
|
||||
SELECT vector_cmp('[1,2]', '[1,2,3]');
|
||||
vector_cmp
|
||||
------------
|
||||
-1
|
||||
(1 row)
|
||||
|
||||
SELECT vector_cmp('[1,2,3]', '[1,2]');
|
||||
vector_cmp
|
||||
------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT vector_cmp('[1,2]', '[2,3,4]');
|
||||
vector_cmp
|
||||
------------
|
||||
-1
|
||||
(1 row)
|
||||
|
||||
SELECT vector_cmp('[2,3]', '[1,2,3]');
|
||||
vector_cmp
|
||||
------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT vector_dims('[1,2,3]');
|
||||
vector_dims
|
||||
-------------
|
||||
@@ -104,110 +54,136 @@ SELECT vector_norm('[3e37,4e37]')::real;
|
||||
5e+37
|
||||
(1 row)
|
||||
|
||||
SELECT l2_distance('[0,0]'::vector, '[3,4]');
|
||||
SELECT l2_distance('[0,0]', '[3,4]');
|
||||
l2_distance
|
||||
-------------
|
||||
5
|
||||
(1 row)
|
||||
|
||||
SELECT l2_distance('[0,0]'::vector, '[0,1]');
|
||||
SELECT l2_distance('[0,0]', '[0,1]');
|
||||
l2_distance
|
||||
-------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT l2_distance('[1,2]'::vector, '[3]');
|
||||
SELECT l2_distance('[1,2]', '[3]');
|
||||
ERROR: different vector dimensions 2 and 1
|
||||
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
|
||||
SELECT l2_distance('[3e38]', '[-3e38]');
|
||||
l2_distance
|
||||
-------------
|
||||
Infinity
|
||||
(1 row)
|
||||
|
||||
SELECT inner_product('[1,2]'::vector, '[3,4]');
|
||||
SELECT inner_product('[1,2]', '[3,4]');
|
||||
inner_product
|
||||
---------------
|
||||
11
|
||||
(1 row)
|
||||
|
||||
SELECT inner_product('[1,2]'::vector, '[3]');
|
||||
SELECT inner_product('[1,2]', '[3]');
|
||||
ERROR: different vector dimensions 2 and 1
|
||||
SELECT inner_product('[3e38]'::vector, '[3e38]');
|
||||
SELECT inner_product('[3e38]', '[3e38]');
|
||||
inner_product
|
||||
---------------
|
||||
Infinity
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
|
||||
SELECT cosine_distance('[1,2]', '[2,4]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
0
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
|
||||
SELECT cosine_distance('[1,2]', '[0,0]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
NaN
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
|
||||
SELECT cosine_distance('[1,1]', '[1,1]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
0
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
|
||||
SELECT cosine_distance('[1,0]', '[0,2]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
|
||||
SELECT cosine_distance('[1,1]', '[-1,-1]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
2
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,2]'::vector, '[3]');
|
||||
SELECT cosine_distance('[1,2]', '[3]');
|
||||
ERROR: different vector dimensions 2 and 1
|
||||
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
|
||||
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
0
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
|
||||
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
2
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
|
||||
SELECT cosine_distance('[3e38]', '[3e38]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
NaN
|
||||
(1 row)
|
||||
|
||||
SELECT l1_distance('[0,0]'::vector, '[3,4]');
|
||||
SELECT l1_distance('[0,0]', '[3,4]');
|
||||
l1_distance
|
||||
-------------
|
||||
7
|
||||
(1 row)
|
||||
|
||||
SELECT l1_distance('[0,0]'::vector, '[0,1]');
|
||||
SELECT l1_distance('[0,0]', '[0,1]');
|
||||
l1_distance
|
||||
-------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT l1_distance('[1,2]'::vector, '[3]');
|
||||
SELECT l1_distance('[1,2]', '[3]');
|
||||
ERROR: different vector dimensions 2 and 1
|
||||
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
|
||||
SELECT l1_distance('[3e38]', '[-3e38]');
|
||||
l1_distance
|
||||
-------------
|
||||
Infinity
|
||||
(1 row)
|
||||
|
||||
SELECT hamming_distance('\xFFFF', '\xFFFF');
|
||||
hamming_distance
|
||||
------------------
|
||||
0
|
||||
(1 row)
|
||||
|
||||
SELECT hamming_distance('\xFFFF', '\xFFFE');
|
||||
hamming_distance
|
||||
------------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT hamming_distance('\xFFFF', '\xFFFC');
|
||||
hamming_distance
|
||||
------------------
|
||||
2
|
||||
(1 row)
|
||||
|
||||
SELECT hamming_distance('\xFFFF', '\x0000');
|
||||
hamming_distance
|
||||
------------------
|
||||
16
|
||||
(1 row)
|
||||
|
||||
SELECT hamming_distance('\xFFFF', '\x00');
|
||||
ERROR: different byte lengths 2 and 1
|
||||
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
|
||||
avg
|
||||
-----------
|
||||
|
||||
@@ -12,11 +12,14 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
[0,0,0]
|
||||
(4 rows)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
|
||||
count
|
||||
-------
|
||||
4
|
||||
(1 row)
|
||||
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
|
||||
val
|
||||
---------
|
||||
[0,0,0]
|
||||
[1,1,1]
|
||||
[1,2,3]
|
||||
[1,2,4]
|
||||
(4 rows)
|
||||
|
||||
SELECT COUNT(*) FROM t;
|
||||
count
|
||||
|
||||
@@ -1,26 +0,0 @@
|
||||
SET enable_seqscan = off;
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_cosine_ops);
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
SELECT * FROM t ORDER BY val <=> '{0:3,1:3,2:3}/3';
|
||||
val
|
||||
-----------------
|
||||
{0:1,1:1,2:1}/3
|
||||
{0:1,1:2,2:3}/3
|
||||
{0:1,1:2,2:4}/3
|
||||
(3 rows)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '{}/3') t2;
|
||||
count
|
||||
-------
|
||||
3
|
||||
(1 row)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::sparsevec)) t2;
|
||||
count
|
||||
-------
|
||||
3
|
||||
(1 row)
|
||||
|
||||
DROP TABLE t;
|
||||
@@ -1,21 +0,0 @@
|
||||
SET enable_seqscan = off;
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_ip_ops);
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
SELECT * FROM t ORDER BY val <#> '{0:3,1:3,2:3}/3';
|
||||
val
|
||||
-----------------
|
||||
{0:1,1:2,2:4}/3
|
||||
{0:1,1:2,2:3}/3
|
||||
{0:1,1:1,2:1}/3
|
||||
{}/3
|
||||
(4 rows)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::sparsevec)) t2;
|
||||
count
|
||||
-------
|
||||
4
|
||||
(1 row)
|
||||
|
||||
DROP TABLE t;
|
||||
@@ -1,43 +0,0 @@
|
||||
SET enable_seqscan = off;
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
SELECT * FROM t ORDER BY val <-> '{0:3,1:3,2:3}/3';
|
||||
val
|
||||
-----------------
|
||||
{0:1,1:2,2:3}/3
|
||||
{0:1,1:2,2:4}/3
|
||||
{0:1,1:1,2:1}/3
|
||||
{}/3
|
||||
(4 rows)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
|
||||
count
|
||||
-------
|
||||
4
|
||||
(1 row)
|
||||
|
||||
SELECT COUNT(*) FROM t;
|
||||
count
|
||||
-------
|
||||
5
|
||||
(1 row)
|
||||
|
||||
TRUNCATE t;
|
||||
SELECT * FROM t ORDER BY val <-> '{0:3,1:3,2:3}/3';
|
||||
val
|
||||
-----
|
||||
(0 rows)
|
||||
|
||||
DROP TABLE t;
|
||||
-- TODO move
|
||||
CREATE TABLE t (val sparsevec(1001));
|
||||
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
|
||||
TRUNCATE t;
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
|
||||
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
|
||||
DROP TABLE t;
|
||||
@@ -66,22 +66,6 @@ SELECT '[4e38,1]'::vector;
|
||||
ERROR: infinite value not allowed in vector
|
||||
LINE 1: SELECT '[4e38,1]'::vector;
|
||||
^
|
||||
SELECT '[-4e38,1]'::vector;
|
||||
ERROR: infinite value not allowed in vector
|
||||
LINE 1: SELECT '[-4e38,1]'::vector;
|
||||
^
|
||||
SELECT '[1e-46,1]'::vector;
|
||||
vector
|
||||
--------
|
||||
[0,1]
|
||||
(1 row)
|
||||
|
||||
SELECT '[-1e-46,1]'::vector;
|
||||
vector
|
||||
--------
|
||||
[-0,1]
|
||||
(1 row)
|
||||
|
||||
SELECT '[1,2,3'::vector;
|
||||
ERROR: malformed vector literal: "[1,2,3"
|
||||
LINE 1: SELECT '[1,2,3'::vector;
|
||||
@@ -132,30 +116,8 @@ SELECT '[1, ,3]'::vector;
|
||||
ERROR: invalid input syntax for type vector: "[1, ,3]"
|
||||
LINE 1: SELECT '[1, ,3]'::vector;
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(3);
|
||||
vector
|
||||
---------
|
||||
[1,2,3]
|
||||
(1 row)
|
||||
|
||||
SELECT '[1,2,3]'::vector(2);
|
||||
ERROR: expected 2 dimensions, not 3
|
||||
SELECT '[1,2,3]'::vector(3, 2);
|
||||
ERROR: invalid type modifier
|
||||
LINE 1: SELECT '[1,2,3]'::vector(3, 2);
|
||||
^
|
||||
SELECT '[1,2,3]'::vector('a');
|
||||
ERROR: invalid input syntax for type integer: "a"
|
||||
LINE 1: SELECT '[1,2,3]'::vector('a');
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(0);
|
||||
ERROR: dimensions for type vector must be at least 1
|
||||
LINE 1: SELECT '[1,2,3]'::vector(0);
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(16001);
|
||||
ERROR: dimensions for type vector cannot exceed 16000
|
||||
LINE 1: SELECT '[1,2,3]'::vector(16001);
|
||||
^
|
||||
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
|
||||
unnest
|
||||
---------
|
||||
|
||||
@@ -1,62 +0,0 @@
|
||||
SELECT l2_distance('{}/2'::sparsevec, '{0:3,1:4}/2');
|
||||
l2_distance
|
||||
-------------
|
||||
5
|
||||
(1 row)
|
||||
|
||||
SELECT l2_distance('{}/2'::sparsevec, '{1:1}/2');
|
||||
l2_distance
|
||||
-------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT '{}/2'::sparsevec <-> '{0:3,1:4}/2';
|
||||
?column?
|
||||
----------
|
||||
5
|
||||
(1 row)
|
||||
|
||||
SELECT inner_product('{0:1,1:2}/2'::sparsevec, '{0:2,1:4}/2');
|
||||
inner_product
|
||||
---------------
|
||||
10
|
||||
(1 row)
|
||||
|
||||
SELECT sparsevec_negative_inner_product('{0:1,1:2}/2', '{0:2,1:4}/2');
|
||||
sparsevec_negative_inner_product
|
||||
----------------------------------
|
||||
-10
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('{0:1,1:2}/2'::sparsevec, '{0:2,1:4}/2');
|
||||
cosine_distance
|
||||
-----------------
|
||||
0
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('{0:1,1:2}/2'::sparsevec, '{}/2');
|
||||
cosine_distance
|
||||
-----------------
|
||||
NaN
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('{0:1,1:1}/2'::sparsevec, '{0:-1,1:-1}/2');
|
||||
cosine_distance
|
||||
-----------------
|
||||
2
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('{0:1}/2'::sparsevec, '{1:2}/2');
|
||||
cosine_distance
|
||||
-----------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
|
||||
cosine_distance
|
||||
-----------------
|
||||
NaN
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('{0:1}/2'::sparsevec, '{0:1}/3');
|
||||
ERROR: different sparsevec dimensions 2 and 3
|
||||
@@ -1,62 +0,0 @@
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec;
|
||||
sparsevec
|
||||
-----------------
|
||||
{0:1.5,2:3.5}/5
|
||||
(1 row)
|
||||
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector;
|
||||
vector
|
||||
-----------------
|
||||
[1.5,0,3.5,0,0]
|
||||
(1 row)
|
||||
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(5);
|
||||
vector
|
||||
-----------------
|
||||
[1.5,0,3.5,0,0]
|
||||
(1 row)
|
||||
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(4);
|
||||
ERROR: expected 4 dimensions, not 5
|
||||
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
|
||||
sparsevec
|
||||
-----------------
|
||||
{1:1.5,3:3.5}/5
|
||||
(1 row)
|
||||
|
||||
SELECT '{0:0,1:1,2:0}/3'::sparsevec;
|
||||
sparsevec
|
||||
-----------
|
||||
{1:1}/3
|
||||
(1 row)
|
||||
|
||||
SELECT '{1:1,0:1}/2'::sparsevec;
|
||||
ERROR: indexes must be in ascending order
|
||||
LINE 1: SELECT '{1:1,0:1}/2'::sparsevec;
|
||||
^
|
||||
SELECT '{}/5'::sparsevec;
|
||||
sparsevec
|
||||
-----------
|
||||
{}/5
|
||||
(1 row)
|
||||
|
||||
SELECT '{}/-1'::sparsevec;
|
||||
ERROR: sparsevec must have at least 1 dimension
|
||||
LINE 1: SELECT '{}/-1'::sparsevec;
|
||||
^
|
||||
SELECT '{}/100001'::sparsevec;
|
||||
ERROR: sparsevec cannot have more than 100000 dimensions
|
||||
LINE 1: SELECT '{}/100001'::sparsevec;
|
||||
^
|
||||
SELECT '{}/16001'::sparsevec::vector;
|
||||
ERROR: vector cannot have more than 16000 dimensions
|
||||
SELECT '{-1:1}/1'::sparsevec;
|
||||
ERROR: index "-1" is out of range for type sparsevec
|
||||
LINE 1: SELECT '{-1:1}/1'::sparsevec;
|
||||
^
|
||||
SELECT '{1:1}/1'::sparsevec;
|
||||
ERROR: index must be less than dimensions
|
||||
LINE 1: SELECT '{1:1}/1'::sparsevec;
|
||||
^
|
||||
SELECT '{}/1'::sparsevec(2);
|
||||
ERROR: expected 2 dimensions, not 1
|
||||
@@ -6,17 +6,6 @@ SELECT '[1,2,3]'::vector * '[4,5,6]';
|
||||
SELECT '[1e37]'::vector * '[1e37]';
|
||||
SELECT '[1e-37]'::vector * '[1e-37]';
|
||||
|
||||
SELECT '[1,2,3]'::vector = '[1,2,3]';
|
||||
SELECT '[1,2,3]'::vector = '[1,2]';
|
||||
|
||||
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
|
||||
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
|
||||
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
|
||||
SELECT vector_cmp('[1,2]', '[1,2,3]');
|
||||
SELECT vector_cmp('[1,2,3]', '[1,2]');
|
||||
SELECT vector_cmp('[1,2]', '[2,3,4]');
|
||||
SELECT vector_cmp('[2,3]', '[1,2,3]');
|
||||
|
||||
SELECT vector_dims('[1,2,3]');
|
||||
|
||||
SELECT round(vector_norm('[1,1]')::numeric, 5);
|
||||
@@ -24,29 +13,35 @@ SELECT vector_norm('[3,4]');
|
||||
SELECT vector_norm('[0,1]');
|
||||
SELECT vector_norm('[3e37,4e37]')::real;
|
||||
|
||||
SELECT l2_distance('[0,0]'::vector, '[3,4]');
|
||||
SELECT l2_distance('[0,0]'::vector, '[0,1]');
|
||||
SELECT l2_distance('[1,2]'::vector, '[3]');
|
||||
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
|
||||
SELECT l2_distance('[0,0]', '[3,4]');
|
||||
SELECT l2_distance('[0,0]', '[0,1]');
|
||||
SELECT l2_distance('[1,2]', '[3]');
|
||||
SELECT l2_distance('[3e38]', '[-3e38]');
|
||||
|
||||
SELECT inner_product('[1,2]'::vector, '[3,4]');
|
||||
SELECT inner_product('[1,2]'::vector, '[3]');
|
||||
SELECT inner_product('[3e38]'::vector, '[3e38]');
|
||||
SELECT inner_product('[1,2]', '[3,4]');
|
||||
SELECT inner_product('[1,2]', '[3]');
|
||||
SELECT inner_product('[3e38]', '[3e38]');
|
||||
|
||||
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
|
||||
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
|
||||
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
|
||||
SELECT cosine_distance('[1,2]'::vector, '[3]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
|
||||
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
|
||||
SELECT cosine_distance('[1,2]', '[2,4]');
|
||||
SELECT cosine_distance('[1,2]', '[0,0]');
|
||||
SELECT cosine_distance('[1,1]', '[1,1]');
|
||||
SELECT cosine_distance('[1,0]', '[0,2]');
|
||||
SELECT cosine_distance('[1,1]', '[-1,-1]');
|
||||
SELECT cosine_distance('[1,2]', '[3]');
|
||||
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
|
||||
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
|
||||
SELECT cosine_distance('[3e38]', '[3e38]');
|
||||
|
||||
SELECT l1_distance('[0,0]'::vector, '[3,4]');
|
||||
SELECT l1_distance('[0,0]'::vector, '[0,1]');
|
||||
SELECT l1_distance('[1,2]'::vector, '[3]');
|
||||
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
|
||||
SELECT l1_distance('[0,0]', '[3,4]');
|
||||
SELECT l1_distance('[0,0]', '[0,1]');
|
||||
SELECT l1_distance('[1,2]', '[3]');
|
||||
SELECT l1_distance('[3e38]', '[-3e38]');
|
||||
|
||||
SELECT hamming_distance('\xFFFF', '\xFFFF');
|
||||
SELECT hamming_distance('\xFFFF', '\xFFFE');
|
||||
SELECT hamming_distance('\xFFFF', '\xFFFC');
|
||||
SELECT hamming_distance('\xFFFF', '\x0000');
|
||||
SELECT hamming_distance('\xFFFF', '\x00');
|
||||
|
||||
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
|
||||
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
|
||||
|
||||
@@ -7,7 +7,7 @@ CREATE INDEX ON t USING hnsw (val vector_l2_ops);
|
||||
INSERT INTO t (val) VALUES ('[1,2,4]');
|
||||
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
|
||||
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
|
||||
SELECT COUNT(*) FROM t;
|
||||
|
||||
TRUNCATE t;
|
||||
|
||||
@@ -1,13 +0,0 @@
|
||||
SET enable_seqscan = off;
|
||||
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_cosine_ops);
|
||||
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
|
||||
SELECT * FROM t ORDER BY val <=> '{0:3,1:3,2:3}/3';
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '{}/3') t2;
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::sparsevec)) t2;
|
||||
|
||||
DROP TABLE t;
|
||||
@@ -1,12 +0,0 @@
|
||||
SET enable_seqscan = off;
|
||||
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_ip_ops);
|
||||
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
|
||||
SELECT * FROM t ORDER BY val <#> '{0:3,1:3,2:3}/3';
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::sparsevec)) t2;
|
||||
|
||||
DROP TABLE t;
|
||||
@@ -1,25 +0,0 @@
|
||||
SET enable_seqscan = off;
|
||||
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
|
||||
SELECT * FROM t ORDER BY val <-> '{0:3,1:3,2:3}/3';
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
|
||||
SELECT COUNT(*) FROM t;
|
||||
|
||||
TRUNCATE t;
|
||||
SELECT * FROM t ORDER BY val <-> '{0:3,1:3,2:3}/3';
|
||||
|
||||
DROP TABLE t;
|
||||
|
||||
-- TODO move
|
||||
CREATE TABLE t (val sparsevec(1001));
|
||||
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
TRUNCATE t;
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
|
||||
DROP TABLE t;
|
||||
@@ -11,9 +11,6 @@ SELECT '[1.5e38,-1.5e38]'::vector;
|
||||
SELECT '[1.5e+38,-1.5e+38]'::vector;
|
||||
SELECT '[1.5e-38,-1.5e-38]'::vector;
|
||||
SELECT '[4e38,1]'::vector;
|
||||
SELECT '[-4e38,1]'::vector;
|
||||
SELECT '[1e-46,1]'::vector;
|
||||
SELECT '[-1e-46,1]'::vector;
|
||||
SELECT '[1,2,3'::vector;
|
||||
SELECT '[1,2,3]9'::vector;
|
||||
SELECT '1,2,3'::vector;
|
||||
@@ -25,13 +22,7 @@ SELECT '[1,]'::vector;
|
||||
SELECT '[1a]'::vector;
|
||||
SELECT '[1,,3]'::vector;
|
||||
SELECT '[1, ,3]'::vector;
|
||||
|
||||
SELECT '[1,2,3]'::vector(3);
|
||||
SELECT '[1,2,3]'::vector(2);
|
||||
SELECT '[1,2,3]'::vector(3, 2);
|
||||
SELECT '[1,2,3]'::vector('a');
|
||||
SELECT '[1,2,3]'::vector(0);
|
||||
SELECT '[1,2,3]'::vector(16001);
|
||||
|
||||
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
|
||||
SELECT '{"[1,2,3]"}'::vector(2)[];
|
||||
|
||||
@@ -1,13 +0,0 @@
|
||||
SELECT l2_distance('{}/2'::sparsevec, '{0:3,1:4}/2');
|
||||
SELECT l2_distance('{}/2'::sparsevec, '{1:1}/2');
|
||||
SELECT '{}/2'::sparsevec <-> '{0:3,1:4}/2';
|
||||
|
||||
SELECT inner_product('{0:1,1:2}/2'::sparsevec, '{0:2,1:4}/2');
|
||||
SELECT sparsevec_negative_inner_product('{0:1,1:2}/2', '{0:2,1:4}/2');
|
||||
|
||||
SELECT cosine_distance('{0:1,1:2}/2'::sparsevec, '{0:2,1:4}/2');
|
||||
SELECT cosine_distance('{0:1,1:2}/2'::sparsevec, '{}/2');
|
||||
SELECT cosine_distance('{0:1,1:1}/2'::sparsevec, '{0:-1,1:-1}/2');
|
||||
SELECT cosine_distance('{0:1}/2'::sparsevec, '{1:2}/2');
|
||||
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
|
||||
SELECT cosine_distance('{0:1}/2'::sparsevec, '{0:1}/3');
|
||||
@@ -1,19 +0,0 @@
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec;
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector;
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(5);
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(4);
|
||||
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
|
||||
|
||||
SELECT '{0:0,1:1,2:0}/3'::sparsevec;
|
||||
|
||||
SELECT '{1:1,0:1}/2'::sparsevec;
|
||||
|
||||
SELECT '{}/5'::sparsevec;
|
||||
SELECT '{}/-1'::sparsevec;
|
||||
SELECT '{}/100001'::sparsevec;
|
||||
SELECT '{}/16001'::sparsevec::vector;
|
||||
|
||||
SELECT '{-1:1}/1'::sparsevec;
|
||||
SELECT '{1:1}/1'::sparsevec;
|
||||
|
||||
SELECT '{}/1'::sparsevec(2);
|
||||
@@ -86,7 +86,7 @@ foreach (@queries)
|
||||
push(@expected, $res);
|
||||
}
|
||||
|
||||
test_recall(0.19, $limit, "before vacuum");
|
||||
test_recall(0.20, $limit, "before vacuum");
|
||||
test_recall(0.95, 100, "before vacuum");
|
||||
|
||||
# TODO Test concurrent inserts with vacuum
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
comment = 'vector data type and ivfflat and hnsw access methods'
|
||||
default_version = '0.6.2'
|
||||
default_version = '0.5.1'
|
||||
module_pathname = '$libdir/vector'
|
||||
relocatable = true
|
||||
|
||||
Reference in New Issue
Block a user