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1
.github/workflows/build.yml
vendored
1
.github/workflows/build.yml
vendored
@@ -73,6 +73,7 @@ jobs:
|
||||
postgres-version: 14
|
||||
- run: |
|
||||
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
|
||||
cd %TEMP% && ^
|
||||
nmake /NOLOGO /F Makefile.win && ^
|
||||
nmake /NOLOGO /F Makefile.win install && ^
|
||||
nmake /NOLOGO /F Makefile.win installcheck && ^
|
||||
|
||||
10
CHANGELOG.md
10
CHANGELOG.md
@@ -1,7 +1,15 @@
|
||||
## 0.7.0 (unreleased)
|
||||
|
||||
- Added `sparsevec` type
|
||||
|
||||
## 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 error with `shared_preload_libraries`
|
||||
- Fixed segmentation fault with `shared_preload_libraries`
|
||||
- Fixed vector subtraction being marked as commutative
|
||||
|
||||
## 0.6.0 (2024-01-29)
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
"name": "vector",
|
||||
"abstract": "Open-source vector similarity search for Postgres",
|
||||
"description": "Supports L2 distance, inner product, and cosine distance",
|
||||
"version": "0.6.1",
|
||||
"version": "0.6.2",
|
||||
"maintainer": [
|
||||
"Andrew Kane <andrew@ankane.org>"
|
||||
],
|
||||
@@ -20,7 +20,7 @@
|
||||
"vector": {
|
||||
"file": "sql/vector.sql",
|
||||
"docfile": "README.md",
|
||||
"version": "0.6.1",
|
||||
"version": "0.6.2",
|
||||
"abstract": "Open-source vector similarity search for Postgres"
|
||||
}
|
||||
},
|
||||
|
||||
6
Makefile
6
Makefile
@@ -1,10 +1,10 @@
|
||||
EXTENSION = vector
|
||||
EXTVERSION = 0.6.1
|
||||
EXTVERSION = 0.6.2
|
||||
|
||||
MODULE_big = vector
|
||||
DATA = $(wildcard sql/*--*.sql)
|
||||
OBJS = src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
|
||||
HEADERS = src/vector.h
|
||||
OBJS = src/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
|
||||
|
||||
TESTS = $(wildcard test/sql/*.sql)
|
||||
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))
|
||||
|
||||
@@ -1,8 +1,8 @@
|
||||
EXTENSION = vector
|
||||
EXTVERSION = 0.6.1
|
||||
EXTVERSION = 0.6.2
|
||||
|
||||
OBJS = src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
|
||||
HEADERS = src\vector.h
|
||||
OBJS = src\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
|
||||
|
||||
REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
|
||||
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
|
||||
|
||||
174
README.md
174
README.md
@@ -20,13 +20,13 @@ Compile and install the extension (supports Postgres 12+)
|
||||
|
||||
```sh
|
||||
cd /tmp
|
||||
git clone --branch v0.6.1 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
make
|
||||
make install # may need sudo
|
||||
```
|
||||
|
||||
See the [installation notes](#installation-notes) if you run into issues
|
||||
See the [installation notes](#installation-notes---linux-and-mac) if you run into issues
|
||||
|
||||
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [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).
|
||||
|
||||
@@ -44,12 +44,15 @@ Then use `nmake` to build:
|
||||
|
||||
```cmd
|
||||
set "PGROOT=C:\Program Files\PostgreSQL\16"
|
||||
git clone --branch v0.6.1 https://github.com/pgvector/pgvector.git
|
||||
cd %TEMP%
|
||||
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
nmake /F Makefile.win
|
||||
nmake /F Makefile.win install
|
||||
```
|
||||
|
||||
See the [installation notes](#installation-notes---windows) if you run into issues
|
||||
|
||||
You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
|
||||
|
||||
## Getting Started
|
||||
@@ -410,13 +413,51 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python
|
||||
|
||||
## Performance
|
||||
|
||||
### Tuning
|
||||
|
||||
Use a tool like [PgTune](https://pgtune.leopard.in.ua/) to set initial values for Postgres server parameters. For instance, `shared_buffers` should typically be 25% of the 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`.
|
||||
|
||||
@@ -430,7 +471,7 @@ 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).
|
||||
|
||||
@@ -438,7 +479,7 @@ To speed up queries with an IVFFlat index, increase the number of inverted lists
|
||||
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 1000);
|
||||
```
|
||||
|
||||
## Vacuuming
|
||||
### Vacuuming
|
||||
|
||||
Vacuuming can take a while for HNSW indexes. Speed it up by reindexing first.
|
||||
|
||||
@@ -447,6 +488,61 @@ 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.
|
||||
@@ -540,6 +636,18 @@ and query with:
|
||||
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
|
||||
```
|
||||
|
||||
#### Are binary vectors supported?
|
||||
|
||||
You can store binary vectors and perform exact nearest neighbor search by Hamming distance in Postgres without an extension ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py)).
|
||||
|
||||
```tsql
|
||||
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
|
||||
INSERT INTO items (embedding) VALUES (B'000'), (B'111');
|
||||
SELECT * FROM items ORDER BY bit_count(embedding # B'101') LIMIT 5;
|
||||
```
|
||||
|
||||
Indexing is not currently supported.
|
||||
|
||||
#### Do indexes need to fit into memory?
|
||||
|
||||
No, but like other index types, you’ll likely see better performance if they do. You can get the size of an index with:
|
||||
@@ -552,7 +660,17 @@ SELECT pg_size_pretty(pg_relation_size('index_name'));
|
||||
|
||||
#### Why isn’t a query using an index?
|
||||
|
||||
The cost estimation in pgvector < 0.4.3 does not always work well with the planner. You can encourage the planner to use an index for a query with:
|
||||
The query needs to have an `ORDER BY` and `LIMIT`, and the `ORDER BY` must be the result of a distance operator, not an expression.
|
||||
|
||||
```sql
|
||||
-- index
|
||||
ORDER BY embedding <=> '[3,1,2]' LIMIT 5;
|
||||
|
||||
-- no index
|
||||
ORDER BY 1 - (embedding <=> '[3,1,2]') DESC LIMIT 5;
|
||||
```
|
||||
|
||||
You can encourage the planner to use an index for a query with:
|
||||
|
||||
```sql
|
||||
BEGIN;
|
||||
@@ -581,6 +699,12 @@ or choose to store vectors inline:
|
||||
ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
|
||||
```
|
||||
|
||||
#### Why are there less results for a query after adding an HNSW index?
|
||||
|
||||
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead.
|
||||
|
||||
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
|
||||
|
||||
#### Why are there less results for a query after adding an IVFFlat index?
|
||||
|
||||
The index was likely created with too little data for the number of lists. Drop the index until the table has more data.
|
||||
@@ -589,11 +713,15 @@ 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
|
||||
|
||||
@@ -617,14 +745,14 @@ 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 |
|
||||
|
||||
### Aggregate Functions
|
||||
### Vector Aggregate Functions
|
||||
|
||||
Function | Description | Added
|
||||
--- | --- | ---
|
||||
avg(vector) → vector | average |
|
||||
sum(vector) → vector | sum | 0.5.0
|
||||
|
||||
## Installation Notes
|
||||
## Installation Notes - Linux and Mac
|
||||
|
||||
### Postgres Location
|
||||
|
||||
@@ -666,12 +794,24 @@ If compilation fails and the output includes `warning: no such sysroot directory
|
||||
|
||||
### Portability
|
||||
|
||||
By default, pgvector compiles with `-march=native` on some platforms for best performance. However, this can lead to `Illegal instruction` errors if trying to run the compiled extension on a different machine.
|
||||
|
||||
To compile for portability, use:
|
||||
|
||||
```sh
|
||||
make OPTFLAGS=""
|
||||
```
|
||||
|
||||
## Installation Notes - Windows
|
||||
|
||||
### Missing Header
|
||||
|
||||
If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct.
|
||||
|
||||
### Permissions
|
||||
|
||||
If installation fails with `Access is denied`, re-run the installation instructions as an administrator.
|
||||
|
||||
## Additional Installation Methods
|
||||
|
||||
### Docker
|
||||
@@ -687,7 +827,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
|
||||
You can also build the image manually:
|
||||
|
||||
```sh
|
||||
git clone --branch v0.6.1 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
docker build --build-arg PG_MAJOR=16 -t myuser/pgvector .
|
||||
```
|
||||
@@ -856,6 +996,12 @@ make installcheck REGRESS=functions # regression test
|
||||
make prove_installcheck PROVE_TESTS=test/t/001_ivfflat_wal.pl # TAP test
|
||||
```
|
||||
|
||||
To enable assertions:
|
||||
|
||||
```sh
|
||||
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
|
||||
```
|
||||
|
||||
To enable benchmarking:
|
||||
|
||||
```sh
|
||||
@@ -868,12 +1014,6 @@ To show memory usage:
|
||||
make clean && PG_CFLAGS="-DHNSW_MEMORY -DIVFFLAT_MEMORY" make && make install
|
||||
```
|
||||
|
||||
To enable assertions:
|
||||
|
||||
```sh
|
||||
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
|
||||
```
|
||||
|
||||
To get k-means metrics:
|
||||
|
||||
```sh
|
||||
|
||||
2
sql/vector--0.6.1--0.6.2.sql
Normal file
2
sql/vector--0.6.1--0.6.2.sql
Normal file
@@ -0,0 +1,2 @@
|
||||
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
|
||||
\echo Use "ALTER EXTENSION vector UPDATE TO '0.6.2'" to load this file. \quit
|
||||
95
sql/vector--0.6.2--0.7.0.sql
Normal file
95
sql/vector--0.6.2--0.7.0.sql
Normal file
@@ -0,0 +1,95 @@
|
||||
-- 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);
|
||||
123
sql/vector.sql
123
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
|
||||
|
||||
-- type
|
||||
-- vector type
|
||||
|
||||
CREATE TYPE vector;
|
||||
|
||||
@@ -29,7 +29,7 @@ CREATE TYPE vector (
|
||||
STORAGE = external
|
||||
);
|
||||
|
||||
-- functions
|
||||
-- vector functions
|
||||
|
||||
CREATE FUNCTION l2_distance(vector, vector) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
@@ -58,7 +58,7 @@ 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;
|
||||
|
||||
-- private functions
|
||||
-- vector 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;
|
||||
|
||||
-- aggregates
|
||||
-- vector aggregates
|
||||
|
||||
CREATE AGGREGATE avg(vector) (
|
||||
SFUNC = vector_accum,
|
||||
@@ -117,7 +117,7 @@ CREATE AGGREGATE sum(vector) (
|
||||
PARALLEL = SAFE
|
||||
);
|
||||
|
||||
-- cast functions
|
||||
-- vector cast functions
|
||||
|
||||
CREATE FUNCTION vector(vector, integer, boolean) RETURNS vector
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
@@ -137,7 +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;
|
||||
|
||||
-- casts
|
||||
-- vector 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;
|
||||
|
||||
-- operators
|
||||
-- vector operators
|
||||
|
||||
CREATE OPERATOR <-> (
|
||||
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l2_distance,
|
||||
@@ -240,7 +240,7 @@ CREATE ACCESS METHOD hnsw TYPE INDEX HANDLER hnswhandler;
|
||||
|
||||
COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method';
|
||||
|
||||
-- opclasses
|
||||
-- vector opclasses
|
||||
|
||||
CREATE OPERATOR CLASS vector_ops
|
||||
DEFAULT FOR TYPE vector USING btree AS
|
||||
@@ -287,3 +287,110 @@ CREATE OPERATOR CLASS vector_cosine_ops
|
||||
OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops,
|
||||
FUNCTION 1 vector_negative_inner_product(vector, vector),
|
||||
FUNCTION 2 vector_norm(vector);
|
||||
|
||||
--- sparsevec type
|
||||
|
||||
CREATE TYPE sparsevec;
|
||||
|
||||
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE TYPE sparsevec (
|
||||
INPUT = sparsevec_in,
|
||||
OUTPUT = sparsevec_out,
|
||||
TYPMOD_IN = sparsevec_typmod_in,
|
||||
RECEIVE = sparsevec_recv,
|
||||
SEND = sparsevec_send,
|
||||
STORAGE = external
|
||||
);
|
||||
|
||||
-- sparsevec functions
|
||||
|
||||
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
CREATE FUNCTION sparsevec_norm(sparsevec) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- 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);
|
||||
|
||||
22
src/hnsw.h
22
src/hnsw.h
@@ -17,6 +17,7 @@
|
||||
#endif
|
||||
|
||||
#define HNSW_MAX_DIM 2000
|
||||
#define HNSW_MAX_NNZ 1000
|
||||
|
||||
/* Support functions */
|
||||
#define HNSW_DISTANCE_PROC 1
|
||||
@@ -55,6 +56,12 @@
|
||||
#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
|
||||
@@ -129,7 +136,7 @@ HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr)
|
||||
HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
|
||||
HnswPtrDeclare(char, DatumRelptr, DatumPtr);
|
||||
|
||||
typedef struct HnswElementData
|
||||
struct HnswElementData
|
||||
{
|
||||
HnswElementPtr next;
|
||||
ItemPointerData heaptids[HNSW_HEAPTIDS];
|
||||
@@ -144,7 +151,7 @@ typedef struct HnswElementData
|
||||
BlockNumber neighborPage;
|
||||
DatumPtr value;
|
||||
LWLock lock;
|
||||
} HnswElementData;
|
||||
};
|
||||
|
||||
typedef HnswElementData * HnswElement;
|
||||
|
||||
@@ -155,12 +162,12 @@ typedef struct HnswCandidate
|
||||
bool closer;
|
||||
} HnswCandidate;
|
||||
|
||||
typedef struct HnswNeighborArray
|
||||
struct HnswNeighborArray
|
||||
{
|
||||
int length;
|
||||
bool closerSet;
|
||||
HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
|
||||
} HnswNeighborArray;
|
||||
};
|
||||
|
||||
typedef struct HnswPairingHeapNode
|
||||
{
|
||||
@@ -185,6 +192,7 @@ typedef struct HnswGraph
|
||||
|
||||
/* Entry state */
|
||||
LWLock entryLock;
|
||||
LWLock entryWaitLock;
|
||||
HnswElementPtr entryPoint;
|
||||
|
||||
/* Allocations state */
|
||||
@@ -241,6 +249,7 @@ typedef struct HnswBuildState
|
||||
Relation index;
|
||||
IndexInfo *indexInfo;
|
||||
ForkNumber forkNum;
|
||||
HnswType type;
|
||||
|
||||
/* Settings */
|
||||
int dimensions;
|
||||
@@ -261,7 +270,6 @@ typedef struct HnswBuildState
|
||||
HnswGraph *graph;
|
||||
double ml;
|
||||
int maxLevel;
|
||||
Vector *normvec;
|
||||
|
||||
/* Memory */
|
||||
MemoryContext graphCtx;
|
||||
@@ -366,7 +374,9 @@ typedef struct HnswVacuumState
|
||||
int HnswGetM(Relation index);
|
||||
int HnswGetEfConstruction(Relation index);
|
||||
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
|
||||
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
|
||||
HnswType HnswGetType(Relation index);
|
||||
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type);
|
||||
void HnswCheckValue(Datum value, HnswType type);
|
||||
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
|
||||
void HnswInitPage(Buffer buf, Page page);
|
||||
void HnswInit(void);
|
||||
|
||||
@@ -431,10 +431,15 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
|
||||
HnswGraph *graph = buildstate->graph;
|
||||
HnswElement entryPoint;
|
||||
LWLock *entryLock = &graph->entryLock;
|
||||
LWLock *entryWaitLock = &graph->entryWaitLock;
|
||||
int efConstruction = buildstate->efConstruction;
|
||||
int m = buildstate->m;
|
||||
char *base = buildstate->hnswarea;
|
||||
|
||||
/* Wait if another process needs exclusive lock on entry lock */
|
||||
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
|
||||
LWLockRelease(entryWaitLock);
|
||||
|
||||
/* Get entry point */
|
||||
LWLockAcquire(entryLock, LW_SHARED);
|
||||
entryPoint = HnswPtrAccess(base, graph->entryPoint);
|
||||
@@ -445,8 +450,10 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
|
||||
/* Release shared lock */
|
||||
LWLockRelease(entryLock);
|
||||
|
||||
/* Get exclusive lock */
|
||||
/* Tell other processes to wait and get exclusive lock */
|
||||
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
|
||||
LWLockAcquire(entryLock, LW_EXCLUSIVE);
|
||||
LWLockRelease(entryWaitLock);
|
||||
|
||||
/* Get latest entry point after lock is acquired */
|
||||
entryPoint = HnswPtrAccess(base, graph->entryPoint);
|
||||
@@ -479,10 +486,13 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
|
||||
/* Detoast once for all calls */
|
||||
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
|
||||
|
||||
/* Check value */
|
||||
HnswCheckValue(value, buildstate->type);
|
||||
|
||||
/* Normalize if needed */
|
||||
if (buildstate->normprocinfo != NULL)
|
||||
{
|
||||
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
|
||||
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->type))
|
||||
return false;
|
||||
}
|
||||
|
||||
@@ -612,6 +622,7 @@ InitGraph(HnswGraph * graph, char *base, long memoryTotal)
|
||||
graph->indtuples = 0;
|
||||
SpinLockInit(&graph->lock);
|
||||
LWLockInitialize(&graph->entryLock, hnsw_lock_tranche_id);
|
||||
LWLockInitialize(&graph->entryWaitLock, hnsw_lock_tranche_id);
|
||||
LWLockInitialize(&graph->allocatorLock, hnsw_lock_tranche_id);
|
||||
LWLockInitialize(&graph->flushLock, hnsw_lock_tranche_id);
|
||||
}
|
||||
@@ -663,21 +674,28 @@ 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 > HNSW_MAX_DIM)
|
||||
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", HNSW_MAX_DIM);
|
||||
if (buildstate->dimensions > maxDimensions)
|
||||
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", maxDimensions);
|
||||
|
||||
if (buildstate->efConstruction < 2 * buildstate->m)
|
||||
elog(ERROR, "ef_construction must be greater than or equal to 2 * m");
|
||||
@@ -695,9 +713,6 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
|
||||
buildstate->ml = HnswGetMl(buildstate->m);
|
||||
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
|
||||
|
||||
/* Reuse for each tuple */
|
||||
buildstate->normvec = InitVector(buildstate->dimensions);
|
||||
|
||||
buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext,
|
||||
"Hnsw build graph context",
|
||||
#if PG_VERSION_NUM >= 150000
|
||||
@@ -721,7 +736,6 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
|
||||
static void
|
||||
FreeBuildState(HnswBuildState * buildstate)
|
||||
{
|
||||
pfree(buildstate->normvec);
|
||||
MemoryContextDelete(buildstate->graphCtx);
|
||||
MemoryContextDelete(buildstate->tmpCtx);
|
||||
}
|
||||
|
||||
@@ -614,15 +614,19 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
|
||||
Datum value;
|
||||
FmgrInfo *normprocinfo;
|
||||
Oid collation = index->rd_indcollation[0];
|
||||
HnswType type = HnswGetType(index);
|
||||
|
||||
/* Detoast once for all calls */
|
||||
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
|
||||
|
||||
/* Check value */
|
||||
HnswCheckValue(value, type);
|
||||
|
||||
/* Normalize if needed */
|
||||
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
|
||||
if (normprocinfo != NULL)
|
||||
{
|
||||
if (!HnswNormValue(normprocinfo, collation, &value, NULL))
|
||||
if (!HnswNormValue(normprocinfo, collation, &value, type))
|
||||
return;
|
||||
}
|
||||
|
||||
|
||||
@@ -40,29 +40,6 @@ GetScanItems(IndexScanDesc scan, Datum q)
|
||||
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
|
||||
}
|
||||
|
||||
/*
|
||||
* Get dimensions from metapage
|
||||
*/
|
||||
static int
|
||||
GetDimensions(Relation index)
|
||||
{
|
||||
Buffer buf;
|
||||
Page page;
|
||||
HnswMetaPage metap;
|
||||
int dimensions;
|
||||
|
||||
buf = ReadBuffer(index, HNSW_METAPAGE_BLKNO);
|
||||
LockBuffer(buf, BUFFER_LOCK_SHARE);
|
||||
page = BufferGetPage(buf);
|
||||
metap = HnswPageGetMeta(page);
|
||||
|
||||
dimensions = metap->dimensions;
|
||||
|
||||
UnlockReleaseBuffer(buf);
|
||||
|
||||
return dimensions;
|
||||
}
|
||||
|
||||
/*
|
||||
* Get scan value
|
||||
*/
|
||||
@@ -73,7 +50,7 @@ GetScanValue(IndexScanDesc scan)
|
||||
Datum value;
|
||||
|
||||
if (scan->orderByData->sk_flags & SK_ISNULL)
|
||||
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
|
||||
value = PointerGetDatum(NULL);
|
||||
else
|
||||
{
|
||||
value = scan->orderByData->sk_argument;
|
||||
@@ -84,7 +61,7 @@ GetScanValue(IndexScanDesc scan)
|
||||
|
||||
/* Fine if normalization fails */
|
||||
if (so->normprocinfo != NULL)
|
||||
HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
|
||||
HnswNormValue(so->normprocinfo, so->collation, &value, HnswGetType(scan->indexRelation));
|
||||
}
|
||||
|
||||
return value;
|
||||
|
||||
@@ -3,12 +3,15 @@
|
||||
#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
|
||||
@@ -149,6 +152,32 @@ 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
|
||||
*
|
||||
@@ -158,21 +187,40 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
|
||||
* if it's different than the original value
|
||||
*/
|
||||
bool
|
||||
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
|
||||
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type)
|
||||
{
|
||||
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
|
||||
|
||||
if (norm > 0)
|
||||
{
|
||||
Vector *v = DatumGetVector(*value);
|
||||
/* TODO Remove vector-specific code */
|
||||
if (type == HNSW_TYPE_VECTOR)
|
||||
{
|
||||
Vector *v = DatumGetVector(*value);
|
||||
Vector *result = InitVector(v->dim);
|
||||
|
||||
if (result == NULL)
|
||||
result = InitVector(v->dim);
|
||||
for (int i = 0; i < v->dim; i++)
|
||||
result->x[i] = v->x[i] / norm;
|
||||
|
||||
for (int i = 0; i < v->dim; i++)
|
||||
result->x[i] = v->x[i] / norm;
|
||||
*value = PointerGetDatum(result);
|
||||
}
|
||||
else if (type == HNSW_TYPE_SPARSEVEC)
|
||||
{
|
||||
SparseVector *v = DatumGetSparseVector(*value);
|
||||
SparseVector *result = InitSparseVector(v->dim, v->nnz);
|
||||
float *vx = SPARSEVEC_VALUES(v);
|
||||
float *rx = SPARSEVEC_VALUES(result);
|
||||
|
||||
*value = PointerGetDatum(result);
|
||||
for (int i = 0; i < v->nnz; i++)
|
||||
{
|
||||
result->indices[i] = v->indices[i];
|
||||
rx[i] = vx[i] / norm;
|
||||
}
|
||||
|
||||
*value = PointerGetDatum(result);
|
||||
}
|
||||
else
|
||||
elog(ERROR, "Unsupported type");
|
||||
|
||||
return true;
|
||||
}
|
||||
@@ -180,6 +228,21 @@ HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
|
||||
return false;
|
||||
}
|
||||
|
||||
/*
|
||||
* Check if a value can be indexed
|
||||
*/
|
||||
void
|
||||
HnswCheckValue(Datum value, HnswType type)
|
||||
{
|
||||
if (type == HNSW_TYPE_SPARSEVEC)
|
||||
{
|
||||
SparseVector *vec = DatumGetSparseVector(value);
|
||||
|
||||
if (vec->nnz > HNSW_MAX_NNZ)
|
||||
elog(ERROR, "sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ);
|
||||
}
|
||||
}
|
||||
|
||||
/*
|
||||
* New buffer
|
||||
*/
|
||||
@@ -575,7 +638,12 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
|
||||
|
||||
/* Calculate distance */
|
||||
if (distance != NULL)
|
||||
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
|
||||
{
|
||||
if (DatumGetPointer(*q) == NULL)
|
||||
*distance = 0;
|
||||
else
|
||||
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
|
||||
}
|
||||
|
||||
UnlockReleaseBuffer(buf);
|
||||
}
|
||||
|
||||
@@ -57,7 +57,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
|
||||
*/
|
||||
if (buildstate->kmeansnormprocinfo != NULL)
|
||||
{
|
||||
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->normvec))
|
||||
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value))
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -105,7 +105,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
|
||||
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
|
||||
|
||||
/* Add sample */
|
||||
AddSample(values, state);
|
||||
AddSample(values, buildstate);
|
||||
|
||||
/* Reset memory context */
|
||||
MemoryContextSwitchTo(oldCtx);
|
||||
@@ -153,7 +153,7 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
|
||||
/* Normalize if needed */
|
||||
if (buildstate->normprocinfo != NULL)
|
||||
{
|
||||
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
|
||||
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value))
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -356,9 +356,6 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
|
||||
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions);
|
||||
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
|
||||
|
||||
/* Reuse for each tuple */
|
||||
buildstate->normvec = InitVector(buildstate->dimensions);
|
||||
|
||||
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
|
||||
"Ivfflat build temporary context",
|
||||
ALLOCSET_DEFAULT_SIZES);
|
||||
@@ -380,7 +377,6 @@ FreeBuildState(IvfflatBuildState * buildstate)
|
||||
{
|
||||
VectorArrayFree(buildstate->centers);
|
||||
pfree(buildstate->listInfo);
|
||||
pfree(buildstate->normvec);
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
pfree(buildstate->listSums);
|
||||
|
||||
@@ -172,7 +172,6 @@ typedef struct IvfflatBuildState
|
||||
VectorArray samples;
|
||||
VectorArray centers;
|
||||
ListInfo *listInfo;
|
||||
Vector *normvec;
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
double inertia;
|
||||
@@ -267,7 +266,7 @@ void VectorArrayFree(VectorArray arr);
|
||||
void PrintVectorArray(char *msg, VectorArray arr);
|
||||
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
|
||||
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
|
||||
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
|
||||
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value);
|
||||
int IvfflatGetLists(Relation index);
|
||||
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
|
||||
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);
|
||||
|
||||
@@ -85,7 +85,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
|
||||
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
|
||||
if (normprocinfo != NULL)
|
||||
{
|
||||
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
|
||||
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value))
|
||||
return;
|
||||
}
|
||||
|
||||
|
||||
@@ -293,7 +293,7 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
|
||||
/* Fine if normalization fails */
|
||||
if (so->normprocinfo != NULL)
|
||||
IvfflatNormValue(so->normprocinfo, so->collation, &value, NULL);
|
||||
IvfflatNormValue(so->normprocinfo, so->collation, &value);
|
||||
}
|
||||
|
||||
IvfflatBench("GetScanLists", GetScanLists(scan, value));
|
||||
|
||||
@@ -75,16 +75,14 @@ IvfflatOptionalProcInfo(Relation index, uint16 procnum)
|
||||
* if it's different than the original value
|
||||
*/
|
||||
bool
|
||||
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
|
||||
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value)
|
||||
{
|
||||
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
|
||||
|
||||
if (norm > 0)
|
||||
{
|
||||
Vector *v = DatumGetVector(*value);
|
||||
|
||||
if (result == NULL)
|
||||
result = InitVector(v->dim);
|
||||
Vector *result = InitVector(v->dim);
|
||||
|
||||
for (int i = 0; i < v->dim; i++)
|
||||
result->x[i] = v->x[i] / norm;
|
||||
|
||||
779
src/sparsevec.c
Normal file
779
src/sparsevec.c
Normal file
@@ -0,0 +1,779 @@
|
||||
#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));
|
||||
}
|
||||
23
src/sparsevec.h
Normal file
23
src/sparsevec.h
Normal file
@@ -0,0 +1,23 @@
|
||||
#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
|
||||
24
src/vector.c
24
src/vector.c
@@ -10,6 +10,7 @@
|
||||
#include "lib/stringinfo.h"
|
||||
#include "libpq/pqformat.h"
|
||||
#include "port.h" /* for strtof() */
|
||||
#include "sparsevec.h"
|
||||
#include "utils/array.h"
|
||||
#include "utils/builtins.h"
|
||||
#include "utils/float.h"
|
||||
@@ -1160,3 +1161,26 @@ vector_avg(PG_FUNCTION_ARGS)
|
||||
|
||||
PG_RETURN_POINTER(result);
|
||||
}
|
||||
|
||||
/*
|
||||
* Convert sparse vector to dense vector
|
||||
*/
|
||||
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_to_vector);
|
||||
Datum
|
||||
sparsevec_to_vector(PG_FUNCTION_ARGS)
|
||||
{
|
||||
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
|
||||
int32 typmod = PG_GETARG_INT32(1);
|
||||
Vector *result;
|
||||
int dim = svec->dim;
|
||||
float *values = SPARSEVEC_VALUES(svec);
|
||||
|
||||
CheckDim(dim);
|
||||
CheckExpectedDim(typmod, dim);
|
||||
|
||||
result = InitVector(dim);
|
||||
for (int i = 0; i < svec->nnz; i++)
|
||||
result->x[svec->indices[i]] = values[i];
|
||||
|
||||
PG_RETURN_POINTER(result);
|
||||
}
|
||||
|
||||
@@ -104,105 +104,105 @@ SELECT vector_norm('[3e37,4e37]')::real;
|
||||
5e+37
|
||||
(1 row)
|
||||
|
||||
SELECT l2_distance('[0,0]', '[3,4]');
|
||||
SELECT l2_distance('[0,0]'::vector, '[3,4]');
|
||||
l2_distance
|
||||
-------------
|
||||
5
|
||||
(1 row)
|
||||
|
||||
SELECT l2_distance('[0,0]', '[0,1]');
|
||||
SELECT l2_distance('[0,0]'::vector, '[0,1]');
|
||||
l2_distance
|
||||
-------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT l2_distance('[1,2]', '[3]');
|
||||
SELECT l2_distance('[1,2]'::vector, '[3]');
|
||||
ERROR: different vector dimensions 2 and 1
|
||||
SELECT l2_distance('[3e38]', '[-3e38]');
|
||||
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
|
||||
l2_distance
|
||||
-------------
|
||||
Infinity
|
||||
(1 row)
|
||||
|
||||
SELECT inner_product('[1,2]', '[3,4]');
|
||||
SELECT inner_product('[1,2]'::vector, '[3,4]');
|
||||
inner_product
|
||||
---------------
|
||||
11
|
||||
(1 row)
|
||||
|
||||
SELECT inner_product('[1,2]', '[3]');
|
||||
SELECT inner_product('[1,2]'::vector, '[3]');
|
||||
ERROR: different vector dimensions 2 and 1
|
||||
SELECT inner_product('[3e38]', '[3e38]');
|
||||
SELECT inner_product('[3e38]'::vector, '[3e38]');
|
||||
inner_product
|
||||
---------------
|
||||
Infinity
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,2]', '[2,4]');
|
||||
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
0
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,2]', '[0,0]');
|
||||
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
NaN
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,1]', '[1,1]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
0
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,0]', '[0,2]');
|
||||
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,1]', '[-1,-1]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
2
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,2]', '[3]');
|
||||
SELECT cosine_distance('[1,2]'::vector, '[3]');
|
||||
ERROR: different vector dimensions 2 and 1
|
||||
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
0
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
2
|
||||
(1 row)
|
||||
|
||||
SELECT cosine_distance('[3e38]', '[3e38]');
|
||||
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
|
||||
cosine_distance
|
||||
-----------------
|
||||
NaN
|
||||
(1 row)
|
||||
|
||||
SELECT l1_distance('[0,0]', '[3,4]');
|
||||
SELECT l1_distance('[0,0]'::vector, '[3,4]');
|
||||
l1_distance
|
||||
-------------
|
||||
7
|
||||
(1 row)
|
||||
|
||||
SELECT l1_distance('[0,0]', '[0,1]');
|
||||
SELECT l1_distance('[0,0]'::vector, '[0,1]');
|
||||
l1_distance
|
||||
-------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SELECT l1_distance('[1,2]', '[3]');
|
||||
SELECT l1_distance('[1,2]'::vector, '[3]');
|
||||
ERROR: different vector dimensions 2 and 1
|
||||
SELECT l1_distance('[3e38]', '[-3e38]');
|
||||
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
|
||||
l1_distance
|
||||
-------------
|
||||
Infinity
|
||||
|
||||
@@ -12,14 +12,11 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
[0,0,0]
|
||||
(4 rows)
|
||||
|
||||
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
|
||||
val
|
||||
---------
|
||||
[0,0,0]
|
||||
[1,1,1]
|
||||
[1,2,3]
|
||||
[1,2,4]
|
||||
(4 rows)
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
|
||||
count
|
||||
-------
|
||||
4
|
||||
(1 row)
|
||||
|
||||
SELECT COUNT(*) FROM t;
|
||||
count
|
||||
|
||||
26
test/expected/hnsw_sparsevec_cosine.out
Normal file
26
test/expected/hnsw_sparsevec_cosine.out
Normal file
@@ -0,0 +1,26 @@
|
||||
SET enable_seqscan = off;
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_cosine_ops);
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
SELECT * FROM t ORDER BY val <=> '{0:3,1:3,2:3}/3';
|
||||
val
|
||||
-----------------
|
||||
{0:1,1:1,2:1}/3
|
||||
{0:1,1:2,2:3}/3
|
||||
{0:1,1:2,2:4}/3
|
||||
(3 rows)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '{}/3') t2;
|
||||
count
|
||||
-------
|
||||
3
|
||||
(1 row)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::sparsevec)) t2;
|
||||
count
|
||||
-------
|
||||
3
|
||||
(1 row)
|
||||
|
||||
DROP TABLE t;
|
||||
21
test/expected/hnsw_sparsevec_ip.out
Normal file
21
test/expected/hnsw_sparsevec_ip.out
Normal file
@@ -0,0 +1,21 @@
|
||||
SET enable_seqscan = off;
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_ip_ops);
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
SELECT * FROM t ORDER BY val <#> '{0:3,1:3,2:3}/3';
|
||||
val
|
||||
-----------------
|
||||
{0:1,1:2,2:4}/3
|
||||
{0:1,1:2,2:3}/3
|
||||
{0:1,1:1,2:1}/3
|
||||
{}/3
|
||||
(4 rows)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::sparsevec)) t2;
|
||||
count
|
||||
-------
|
||||
4
|
||||
(1 row)
|
||||
|
||||
DROP TABLE t;
|
||||
43
test/expected/hnsw_sparsevec_l2.out
Normal file
43
test/expected/hnsw_sparsevec_l2.out
Normal file
@@ -0,0 +1,43 @@
|
||||
SET enable_seqscan = off;
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
SELECT * FROM t ORDER BY val <-> '{0:3,1:3,2:3}/3';
|
||||
val
|
||||
-----------------
|
||||
{0:1,1:2,2:3}/3
|
||||
{0:1,1:2,2:4}/3
|
||||
{0:1,1:1,2:1}/3
|
||||
{}/3
|
||||
(4 rows)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
|
||||
count
|
||||
-------
|
||||
4
|
||||
(1 row)
|
||||
|
||||
SELECT COUNT(*) FROM t;
|
||||
count
|
||||
-------
|
||||
5
|
||||
(1 row)
|
||||
|
||||
TRUNCATE t;
|
||||
SELECT * FROM t ORDER BY val <-> '{0:3,1:3,2:3}/3';
|
||||
val
|
||||
-----
|
||||
(0 rows)
|
||||
|
||||
DROP TABLE t;
|
||||
-- TODO move
|
||||
CREATE TABLE t (val sparsevec(1001));
|
||||
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
|
||||
TRUNCATE t;
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
|
||||
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
|
||||
DROP TABLE t;
|
||||
@@ -66,6 +66,22 @@ 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;
|
||||
@@ -116,8 +132,30 @@ SELECT '[1, ,3]'::vector;
|
||||
ERROR: invalid input syntax for type vector: "[1, ,3]"
|
||||
LINE 1: SELECT '[1, ,3]'::vector;
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(3);
|
||||
vector
|
||||
---------
|
||||
[1,2,3]
|
||||
(1 row)
|
||||
|
||||
SELECT '[1,2,3]'::vector(2);
|
||||
ERROR: expected 2 dimensions, not 3
|
||||
SELECT '[1,2,3]'::vector(3, 2);
|
||||
ERROR: invalid type modifier
|
||||
LINE 1: SELECT '[1,2,3]'::vector(3, 2);
|
||||
^
|
||||
SELECT '[1,2,3]'::vector('a');
|
||||
ERROR: invalid input syntax for type integer: "a"
|
||||
LINE 1: SELECT '[1,2,3]'::vector('a');
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(0);
|
||||
ERROR: dimensions for type vector must be at least 1
|
||||
LINE 1: SELECT '[1,2,3]'::vector(0);
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(16001);
|
||||
ERROR: dimensions for type vector cannot exceed 16000
|
||||
LINE 1: SELECT '[1,2,3]'::vector(16001);
|
||||
^
|
||||
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
|
||||
unnest
|
||||
---------
|
||||
|
||||
62
test/expected/sparsevec_functions.out
Normal file
62
test/expected/sparsevec_functions.out
Normal file
@@ -0,0 +1,62 @@
|
||||
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
|
||||
62
test/expected/sparsevec_input.out
Normal file
62
test/expected/sparsevec_input.out
Normal file
@@ -0,0 +1,62 @@
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec;
|
||||
sparsevec
|
||||
-----------------
|
||||
{0:1.5,2:3.5}/5
|
||||
(1 row)
|
||||
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector;
|
||||
vector
|
||||
-----------------
|
||||
[1.5,0,3.5,0,0]
|
||||
(1 row)
|
||||
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(5);
|
||||
vector
|
||||
-----------------
|
||||
[1.5,0,3.5,0,0]
|
||||
(1 row)
|
||||
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(4);
|
||||
ERROR: expected 4 dimensions, not 5
|
||||
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
|
||||
sparsevec
|
||||
-----------------
|
||||
{1:1.5,3:3.5}/5
|
||||
(1 row)
|
||||
|
||||
SELECT '{0:0,1:1,2:0}/3'::sparsevec;
|
||||
sparsevec
|
||||
-----------
|
||||
{1:1}/3
|
||||
(1 row)
|
||||
|
||||
SELECT '{1:1,0:1}/2'::sparsevec;
|
||||
ERROR: indexes must be in ascending order
|
||||
LINE 1: SELECT '{1:1,0:1}/2'::sparsevec;
|
||||
^
|
||||
SELECT '{}/5'::sparsevec;
|
||||
sparsevec
|
||||
-----------
|
||||
{}/5
|
||||
(1 row)
|
||||
|
||||
SELECT '{}/-1'::sparsevec;
|
||||
ERROR: sparsevec must have at least 1 dimension
|
||||
LINE 1: SELECT '{}/-1'::sparsevec;
|
||||
^
|
||||
SELECT '{}/100001'::sparsevec;
|
||||
ERROR: sparsevec cannot have more than 100000 dimensions
|
||||
LINE 1: SELECT '{}/100001'::sparsevec;
|
||||
^
|
||||
SELECT '{}/16001'::sparsevec::vector;
|
||||
ERROR: vector cannot have more than 16000 dimensions
|
||||
SELECT '{-1:1}/1'::sparsevec;
|
||||
ERROR: index "-1" is out of range for type sparsevec
|
||||
LINE 1: SELECT '{-1:1}/1'::sparsevec;
|
||||
^
|
||||
SELECT '{1:1}/1'::sparsevec;
|
||||
ERROR: index must be less than dimensions
|
||||
LINE 1: SELECT '{1:1}/1'::sparsevec;
|
||||
^
|
||||
SELECT '{}/1'::sparsevec(2);
|
||||
ERROR: expected 2 dimensions, not 1
|
||||
@@ -24,29 +24,29 @@ SELECT vector_norm('[3,4]');
|
||||
SELECT vector_norm('[0,1]');
|
||||
SELECT vector_norm('[3e37,4e37]')::real;
|
||||
|
||||
SELECT l2_distance('[0,0]', '[3,4]');
|
||||
SELECT l2_distance('[0,0]', '[0,1]');
|
||||
SELECT l2_distance('[1,2]', '[3]');
|
||||
SELECT l2_distance('[3e38]', '[-3e38]');
|
||||
SELECT l2_distance('[0,0]'::vector, '[3,4]');
|
||||
SELECT l2_distance('[0,0]'::vector, '[0,1]');
|
||||
SELECT l2_distance('[1,2]'::vector, '[3]');
|
||||
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
|
||||
|
||||
SELECT inner_product('[1,2]', '[3,4]');
|
||||
SELECT inner_product('[1,2]', '[3]');
|
||||
SELECT inner_product('[3e38]', '[3e38]');
|
||||
SELECT inner_product('[1,2]'::vector, '[3,4]');
|
||||
SELECT inner_product('[1,2]'::vector, '[3]');
|
||||
SELECT inner_product('[3e38]'::vector, '[3e38]');
|
||||
|
||||
SELECT cosine_distance('[1,2]', '[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 cosine_distance('[1,2]'::vector, '[2,4]');
|
||||
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
|
||||
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
|
||||
SELECT cosine_distance('[1,2]'::vector, '[3]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
|
||||
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
|
||||
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
|
||||
|
||||
SELECT l1_distance('[0,0]', '[3,4]');
|
||||
SELECT l1_distance('[0,0]', '[0,1]');
|
||||
SELECT l1_distance('[1,2]', '[3]');
|
||||
SELECT l1_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 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 * FROM t ORDER BY val <-> (SELECT NULL::vector);
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
|
||||
SELECT COUNT(*) FROM t;
|
||||
|
||||
TRUNCATE t;
|
||||
|
||||
13
test/sql/hnsw_sparsevec_cosine.sql
Normal file
13
test/sql/hnsw_sparsevec_cosine.sql
Normal file
@@ -0,0 +1,13 @@
|
||||
SET enable_seqscan = off;
|
||||
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_cosine_ops);
|
||||
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
|
||||
SELECT * FROM t ORDER BY val <=> '{0:3,1:3,2:3}/3';
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '{}/3') t2;
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::sparsevec)) t2;
|
||||
|
||||
DROP TABLE t;
|
||||
12
test/sql/hnsw_sparsevec_ip.sql
Normal file
12
test/sql/hnsw_sparsevec_ip.sql
Normal file
@@ -0,0 +1,12 @@
|
||||
SET enable_seqscan = off;
|
||||
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_ip_ops);
|
||||
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
|
||||
SELECT * FROM t ORDER BY val <#> '{0:3,1:3,2:3}/3';
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::sparsevec)) t2;
|
||||
|
||||
DROP TABLE t;
|
||||
25
test/sql/hnsw_sparsevec_l2.sql
Normal file
25
test/sql/hnsw_sparsevec_l2.sql
Normal file
@@ -0,0 +1,25 @@
|
||||
SET enable_seqscan = off;
|
||||
|
||||
CREATE TABLE t (val sparsevec(3));
|
||||
INSERT INTO t (val) VALUES ('{}/3'), ('{0:1,1:2,2:3}/3'), ('{0:1,1:1,2:1}/3'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
|
||||
INSERT INTO t (val) VALUES ('{0:1,1:2,2:4}/3');
|
||||
|
||||
SELECT * FROM t ORDER BY val <-> '{0:3,1:3,2:3}/3';
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
|
||||
SELECT COUNT(*) FROM t;
|
||||
|
||||
TRUNCATE t;
|
||||
SELECT * FROM t ORDER BY val <-> '{0:3,1:3,2:3}/3';
|
||||
|
||||
DROP TABLE t;
|
||||
|
||||
-- TODO move
|
||||
CREATE TABLE t (val sparsevec(1001));
|
||||
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
TRUNCATE t;
|
||||
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
|
||||
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
|
||||
DROP TABLE t;
|
||||
@@ -11,6 +11,9 @@ SELECT '[1.5e38,-1.5e38]'::vector;
|
||||
SELECT '[1.5e+38,-1.5e+38]'::vector;
|
||||
SELECT '[1.5e-38,-1.5e-38]'::vector;
|
||||
SELECT '[4e38,1]'::vector;
|
||||
SELECT '[-4e38,1]'::vector;
|
||||
SELECT '[1e-46,1]'::vector;
|
||||
SELECT '[-1e-46,1]'::vector;
|
||||
SELECT '[1,2,3'::vector;
|
||||
SELECT '[1,2,3]9'::vector;
|
||||
SELECT '1,2,3'::vector;
|
||||
@@ -22,7 +25,13 @@ SELECT '[1,]'::vector;
|
||||
SELECT '[1a]'::vector;
|
||||
SELECT '[1,,3]'::vector;
|
||||
SELECT '[1, ,3]'::vector;
|
||||
|
||||
SELECT '[1,2,3]'::vector(3);
|
||||
SELECT '[1,2,3]'::vector(2);
|
||||
SELECT '[1,2,3]'::vector(3, 2);
|
||||
SELECT '[1,2,3]'::vector('a');
|
||||
SELECT '[1,2,3]'::vector(0);
|
||||
SELECT '[1,2,3]'::vector(16001);
|
||||
|
||||
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
|
||||
SELECT '{"[1,2,3]"}'::vector(2)[];
|
||||
|
||||
13
test/sql/sparsevec_functions.sql
Normal file
13
test/sql/sparsevec_functions.sql
Normal file
@@ -0,0 +1,13 @@
|
||||
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');
|
||||
19
test/sql/sparsevec_input.sql
Normal file
19
test/sql/sparsevec_input.sql
Normal file
@@ -0,0 +1,19 @@
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec;
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector;
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(5);
|
||||
SELECT '{0:1.5,2:3.5}/5'::sparsevec::vector(4);
|
||||
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
|
||||
|
||||
SELECT '{0:0,1:1,2:0}/3'::sparsevec;
|
||||
|
||||
SELECT '{1:1,0:1}/2'::sparsevec;
|
||||
|
||||
SELECT '{}/5'::sparsevec;
|
||||
SELECT '{}/-1'::sparsevec;
|
||||
SELECT '{}/100001'::sparsevec;
|
||||
SELECT '{}/16001'::sparsevec::vector;
|
||||
|
||||
SELECT '{-1:1}/1'::sparsevec;
|
||||
SELECT '{1:1}/1'::sparsevec;
|
||||
|
||||
SELECT '{}/1'::sparsevec(2);
|
||||
@@ -86,7 +86,7 @@ foreach (@queries)
|
||||
push(@expected, $res);
|
||||
}
|
||||
|
||||
test_recall(0.20, $limit, "before vacuum");
|
||||
test_recall(0.19, $limit, "before vacuum");
|
||||
test_recall(0.95, 100, "before vacuum");
|
||||
|
||||
# TODO Test concurrent inserts with vacuum
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
comment = 'vector data type and ivfflat and hnsw access methods'
|
||||
default_version = '0.6.1'
|
||||
default_version = '0.6.2'
|
||||
module_pathname = '$libdir/vector'
|
||||
relocatable = true
|
||||
|
||||
Reference in New Issue
Block a user