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...

33 Commits

Author SHA1 Message Date
Andrew Kane
f90d52d562 Added test for explicit zeros [skip ci] 2023-11-06 14:29:52 -08:00
Andrew Kane
22a1b06924 Added todo [skip ci] 2023-11-05 21:26:28 -08:00
Andrew Kane
b17b9c1ca2 Updated version [skip ci] 2023-11-05 18:21:09 -08:00
Andrew Kane
492ae1225c Added support for sparse vectors 2023-11-05 18:12:19 -08:00
Andrew Kane
a01a72d812 Updated comment [skip ci] 2023-11-05 08:42:06 -08:00
Andrew Kane
0c2fc18a80 Updated comment [skip ci] 2023-11-05 08:40:21 -08:00
Andrew Kane
e860042d3c Improved variable name [skip ci] 2023-11-05 08:35:54 -08:00
Andrew Kane
5986862bd2 Added note about check constraint [skip ci] 2023-11-04 15:01:37 -07:00
Andrew Kane
5d24f5d09a Improved header installation on Windows 2023-11-04 11:16:40 -07:00
Andrew Kane
7c43b0d8ee Updated example [skip ci] 2023-11-03 23:54:50 -07:00
Andrew Kane
7be40036f4 Updated readme [skip ci] 2023-11-03 23:46:23 -07:00
Andrew Kane
9b5a1a69db Updated readme [skip ci] 2023-11-03 23:43:47 -07:00
Andrew Kane
04b96506f5 Added info on storing vectors with more precision [skip ci] 2023-11-03 20:14:28 -07:00
Andrew Kane
35cd7b63cb Updated readme [skip ci] 2023-11-03 17:02:30 -07:00
Andrew Kane
b5416d6f10 Updated readme [skip ci] 2023-11-03 16:48:57 -07:00
Andrew Kane
f361bf2704 Improved docs on indexing vectors with different dimensions [skip ci] 2023-11-03 16:42:14 -07:00
Andrew Kane
3d8c1921aa Improved upgrading docs - #339 [skip ci] 2023-11-03 16:15:06 -07:00
Andrew Kane
154207bc17 Added info on columns with different dimensions [skip ci] 2023-11-03 16:02:00 -07:00
Andrew Kane
8e507f3bf5 Free remaining allocation from deconstruct_array - #332 2023-11-02 21:20:21 -07:00
Andrew Kane
e115773a55 Removed unneeded allocation 2023-11-02 21:16:06 -07:00
Andrew Kane
9333bef046 Added link to setup-pgvector [skip ci] 2023-11-02 13:22:19 -07:00
Andrew Kane
4851e47d9f Added Reciprocal Rank Fusion example to readme [skip ci] 2023-11-01 13:20:49 -07:00
Andrew Kane
12aecfb4f5 Added Nim and Zig to readme [skip ci] 2023-10-31 02:26:18 -07:00
Andrew Kane
800697fb14 Updated column alias [skip ci] 2023-10-29 16:47:55 -07:00
Andrew Kane
de1f2b09dd Improved indexing progress queries [skip ci] 2023-10-29 16:41:39 -07:00
Andrew Kane
bcccb7f5a5 Improved docs for indexing progress - closes #320 and closes #321 [skip ci] 2023-10-29 16:13:12 -07:00
Andrew Kane
bec3d30d68 Added TypeScript to readme [skip ci] 2023-10-29 12:49:01 -07:00
Andrew Kane
588de60445 Added Groovy to readme [skip ci] 2023-10-29 12:39:53 -07:00
Andrew Kane
c599f92b52 Updated readme [skip ci] 2023-10-27 13:22:37 -07:00
Andrew Kane
2a17b335da Added Kotlin to readme [skip ci] 2023-10-26 12:25:58 -07:00
Andrew Kane
6ede6ac301 Added link to pgvector-c [skip ci] 2023-10-26 00:30:06 -07:00
Andrew Kane
3f49b95f01 Added Postgres 17 to CI [skip ci] 2023-10-19 00:37:24 -07:00
Andrew Kane
ef1bea7163 Updated checkout action [skip ci] 2023-10-19 00:36:53 -07:00
14 changed files with 1256 additions and 59 deletions

View File

@@ -8,6 +8,8 @@ jobs:
fail-fast: false
matrix:
include:
- postgres: 17
os: ubuntu-22.04
- postgres: 16
os: ubuntu-22.04
- postgres: 15
@@ -21,7 +23,7 @@ jobs:
- postgres: 11
os: ubuntu-20.04
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
@@ -43,7 +45,7 @@ jobs:
runs-on: macos-latest
if: ${{ !startsWith(github.ref_name, 'windows') }}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14
@@ -65,7 +67,7 @@ jobs:
runs-on: windows-latest
if: ${{ !startsWith(github.ref_name, 'mac') }}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14

View File

@@ -1,3 +1,7 @@
## 0.6.0 (unreleased)
- Added support for sparse vectors
## 0.5.1 (2023-10-10)
- Improved performance of HNSW index builds

View File

@@ -3,8 +3,8 @@ 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/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/svector.o src/vector.o
HEADERS = src/svector.h src/vector.h
TESTS = $(wildcard test/sql/*.sql)
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))

View File

@@ -1,8 +1,8 @@
EXTENSION = vector
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\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\svector.obj src\vector.obj
HEADERS = src\svector.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)
@@ -56,7 +56,7 @@ install:
copy $(EXTENSION).control "$(SHAREDIR)\extension"
copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
mkdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
copy $(HEADERS) "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
for %f in ($(HEADERS)) do copy %f "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
installcheck:
"$(BINDIR)\pg_regress" --bindir="$(BINDIR)" $(REGRESS_OPTS) $(REGRESS)

115
README.md
View File

@@ -26,7 +26,7 @@ make install # may need sudo
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), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres)
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
@@ -215,6 +215,23 @@ SELECT ...
COMMIT;
```
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases for IVFFlat are:
1. `initializing`
2. `performing k-means`
3. `assigning tuples`
4. `loading tuples`
Note: `%` is only populated during the `loading tuples` phase
## HNSW
An HNSW index creates a multilayer graph. It has slower build times and uses more memory than IVFFlat, but has better query performance (in terms of speed-recall tradeoff). Theres no training step like IVFFlat, so the index can be created without any data in the table.
@@ -271,22 +288,18 @@ SELECT ...
COMMIT;
```
## Indexing Progress
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, tuples_done, tuples_total FROM pg_stat_progress_create_index;
SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases are:
The phases for HNSW are:
1. `initializing`
2. `performing k-means` - IVFFlat only
3. `assigning tuples` - IVFFlat only
4. `loading tuples`
Note: `tuples_done` and `tuples_total` are only populated during the `loading tuples` phase
2. `loading tuples`
## Filtering
@@ -317,13 +330,15 @@ CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(cate
## Hybrid Search
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search ([Python example](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search.py)).
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search.
```sql
SELECT id, content FROM items, plainto_tsquery('hello search') query
WHERE textsearch @@ query ORDER BY ts_rank_cd(textsearch, query) DESC LIMIT 5;
```
You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search_rrf.py) or a [cross-encoder](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search.py) to combine results.
## Performance
Use `EXPLAIN ANALYZE` to debug performance.
@@ -354,12 +369,33 @@ 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);
```
## Sparse Vectors
Create a sparse vector column with 10 dimensions
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding svector(10));
```
Insert vectors
```sql
INSERT INTO items (embedding) VALUES ('(0,1),(1,2),(2,3)|10|'), ('(0,4),(1,5),(4,6)|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.
Language | Libraries / Examples
--- | ---
C | [pgvector-c](https://github.com/pgvector/pgvector-c)
C++ | [pgvector-cpp](https://github.com/pgvector/pgvector-cpp)
C# | [pgvector-dotnet](https://github.com/pgvector/pgvector-dotnet)
Crystal | [pgvector-crystal](https://github.com/pgvector/pgvector-crystal)
@@ -367,10 +403,11 @@ Dart | [pgvector-dart](https://github.com/pgvector/pgvector-dart)
Elixir | [pgvector-elixir](https://github.com/pgvector/pgvector-elixir)
Go | [pgvector-go](https://github.com/pgvector/pgvector-go)
Haskell | [pgvector-haskell](https://github.com/pgvector/pgvector-haskell)
Java, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
Java, Kotlin, Groovy, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
JavaScript, TypeScript | [pgvector-node](https://github.com/pgvector/pgvector-node)
Julia | [pgvector-julia](https://github.com/pgvector/pgvector-julia)
Lua | [pgvector-lua](https://github.com/pgvector/pgvector-lua)
Node.js | [pgvector-node](https://github.com/pgvector/pgvector-node)
Nim | [pgvector-nim](https://github.com/pgvector/pgvector-nim)
Perl | [pgvector-perl](https://github.com/pgvector/pgvector-perl)
PHP | [pgvector-php](https://github.com/pgvector/pgvector-php)
Python | [pgvector-python](https://github.com/pgvector/pgvector-python)
@@ -378,6 +415,7 @@ R | [pgvector-r](https://github.com/pgvector/pgvector-r)
Ruby | [pgvector-ruby](https://github.com/pgvector/pgvector-ruby), [Neighbor](https://github.com/ankane/neighbor)
Rust | [pgvector-rust](https://github.com/pgvector/pgvector-rust)
Swift | [pgvector-swift](https://github.com/pgvector/pgvector-swift)
Zig | [pgvector-zig](https://github.com/pgvector/pgvector-zig)
## Frequently Asked Questions
@@ -393,6 +431,55 @@ Yes, pgvector uses the write-ahead log (WAL), which allows for replication and p
Youll need to use [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction) at the moment.
#### Can I store vectors with different dimensions in the same column?
You can use `vector` as the type (instead of `vector(3)`).
```sql
CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id));
```
However, you can only create indexes on rows with the same number of dimensions (using [expression](https://www.postgresql.org/docs/current/indexes-expressional.html) and [partial](https://www.postgresql.org/docs/current/indexes-partial.html) indexing):
```sql
CREATE INDEX ON embeddings USING hnsw ((embedding::vector(3)) vector_l2_ops) WHERE (model_id = 123);
```
and query with:
```sql
SELECT * FROM embeddings WHERE model_id = 123 ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
```
#### Can I store vectors with more precision?
You can use the `double precision[]` or `numeric[]` type to store vectors with more precision.
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding double precision[]);
-- use {} instead of [] for Postgres arrays
INSERT INTO items (embedding) VALUES ('{1,2,3}'), ('{4,5,6}');
```
Optionally, add a [check constraint](https://www.postgresql.org/docs/current/ddl-constraints.html) to ensure data can be converted to the `vector` type and has the expected dimensions.
```sql
ALTER TABLE items ADD CHECK (vector_dims(embedding::vector) = 3);
```
Use [expression indexing](https://www.postgresql.org/docs/current/indexes-expressional.html) to index (at a lower precision):
```sql
CREATE INDEX ON items USING hnsw ((embedding::vector(3)) vector_l2_ops);
```
and query with:
```sql
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
```
## Troubleshooting
#### Why isnt a query using an index?
@@ -406,6 +493,8 @@ SELECT ...
COMMIT;
```
Also, if the table is small, a table scan may be faster.
#### Why isnt a query using a parallel table scan?
The planner doesnt consider [out-of-line storage](https://www.postgresql.org/docs/current/storage-toast.html) in cost estimates, which can make a serial scan look cheaper. You can reduce the cost of a parallel scan for a query with:
@@ -595,7 +684,7 @@ pgvector is available on [these providers](https://github.com/pgvector/pgvector/
## Upgrading
Install the latest version. Then in each database you want to upgrade, run:
[Install](#installation) the latest version (use the same method as the original installation). Then in each database you want to upgrade, run:
```sql
ALTER EXTENSION vector UPDATE;

View File

@@ -0,0 +1,79 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.6.0'" to load this file. \quit
CREATE TYPE svector;
CREATE FUNCTION svector_in(cstring, oid, integer) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_out(svector) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_recv(internal, oid, integer) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_send(svector) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE svector (
INPUT = svector_in,
OUTPUT = svector_out,
TYPMOD_IN = svector_typmod_in,
RECEIVE = svector_recv,
SEND = svector_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_jaccard_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_l2_squared_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_negative_inner_product(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector(svector, integer, boolean) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_svector(vector, integer, boolean) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_to_vector(svector, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (svector AS svector)
WITH FUNCTION svector(svector, integer, boolean) AS IMPLICIT;
CREATE CAST (svector AS vector)
WITH FUNCTION svector_to_vector(svector, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS svector)
WITH FUNCTION vector_to_svector(vector, integer, boolean) AS IMPLICIT;
CREATE OPERATOR <-> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = svector_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);

View File

@@ -290,3 +290,92 @@ 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);
--- svector type
CREATE TYPE svector;
CREATE FUNCTION svector_in(cstring, oid, integer) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_out(svector) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_recv(internal, oid, integer) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_send(svector) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE svector (
INPUT = svector_in,
OUTPUT = svector_out,
TYPMOD_IN = svector_typmod_in,
RECEIVE = svector_recv,
SEND = svector_send,
STORAGE = external
);
-- svector functions
CREATE FUNCTION l2_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_jaccard_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- svector private functions
CREATE FUNCTION svector_l2_squared_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_negative_inner_product(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- svector cast functions
CREATE FUNCTION svector(svector, integer, boolean) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_svector(vector, integer, boolean) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_to_vector(svector, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- svector casts
CREATE CAST (svector AS svector)
WITH FUNCTION svector(svector, integer, boolean) AS IMPLICIT;
CREATE CAST (svector AS vector)
WITH FUNCTION svector_to_vector(svector, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS svector)
WITH FUNCTION vector_to_svector(vector, integer, boolean) AS IMPLICIT;
-- svector operators
CREATE OPERATOR <-> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = svector_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);

705
src/svector.c Normal file
View File

@@ -0,0 +1,705 @@
#include "postgres.h"
#include <math.h>
#include "fmgr.h"
#include "libpq/pqformat.h"
#include "svector.h"
#include "utils/array.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(SVector * a, SVector * b)
{
if (a->dim != b->dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different svector 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("svector must have at least 1 dimension")));
if (dim > SVECTOR_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("svector cannot have more than %d dimensions", SVECTOR_MAX_DIM)));
}
/*
* Ensure valid nnz
*/
static inline void
CheckNnz(int nnz, int dim)
{
if (nnz < 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("svector must have at least one element")));
if (nnz > dim)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("svector 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 svector")));
if (isinf(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("infinite value not allowed in svector")));
}
/*
* Allocate and initialize a new sparse vector
*/
SVector *
InitSVector(int dim, int nnz)
{
SVector *result;
int size;
size = SVECTOR_SIZE(nnz);
result = (SVector *) palloc0(size);
SET_VARSIZE(result, size);
result->dim = dim;
result->nnz = nnz;
return result;
}
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_in);
Datum
svector_in(PG_FUNCTION_ARGS)
{
char *str = PG_GETARG_CSTRING(0);
int32 typmod = PG_GETARG_INT32(2);
int dim;
char *pt;
SVector *result;
float *rvalues;
char *lit = pstrdup(str);
int n;
int32 *indices;
float *values;
int index;
float value;
int maxNnz;
int nnz = 0;
/* TODO Improve code and checks after deciding on format */
maxNnz = 1;
pt = str;
while (*pt != '\0')
{
if (*pt == ',')
maxNnz++;
pt++;
}
maxNnz /= 2;
indices = palloc(maxNnz * sizeof(int32));
values = palloc(maxNnz * sizeof(float));
while (sscanf(str, "(%d,%f)%n", &index, &value, &n) == 2)
{
/* TODO Better error */
if (nnz == maxNnz)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("ran out of buffer: \"%s\"", lit)));
/* TODO Decide whether to store zero values */
indices[nnz] = index;
values[nnz] = value;
nnz++;
str += n;
if (*str == ',')
str++;
else if (*str == '|')
break;
else
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed svector literal: \"%s\"", lit)));
}
if (sscanf(str, "|%d|%n", &dim, &n) != 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed svector literal: \"%s\"", lit)));
str += n;
if (*str != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed svector literal: \"%s\"", lit),
errdetail("Junk after closing pipe.")));
pfree(lit);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitSVector(dim, nnz);
rvalues = SVECTOR_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);
}
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_out);
Datum
svector_out(PG_FUNCTION_ARGS)
{
SVector *svector = PG_GETARG_SVECTOR_P(0);
float *values = SVECTOR_VALUES(svector);
char *buf;
char *ptr;
int n;
/* TODO Improve code after deciding on format */
#if PG_VERSION_NUM < 120000
int ndig = FLT_DIG + extra_float_digits;
if (ndig < 1)
ndig = 1;
#define FLOAT_SHORTEST_DECIMAL_LEN (ndig + 10)
#endif
/* TODO Move */
#define APPEND_CHAR(ptr, ch) (*(ptr)++ = (ch))
/* TODO Improve */
buf = (char *) palloc((FLOAT_SHORTEST_DECIMAL_LEN + 20) * svector->nnz + 20);
ptr = buf;
for (int i = 0; i < svector->nnz; i++)
{
if (i > 0)
APPEND_CHAR(ptr, ',');
n = sprintf(ptr, "(%d,", svector->indices[i]);
ptr += n;
#if PG_VERSION_NUM >= 120000
n = float_to_shortest_decimal_bufn(values[i], ptr);
#else
n = sprintf(ptr, "%.*g", ndig, values[i]);
#endif
ptr += n;
APPEND_CHAR(ptr, ')');
}
n = sprintf(ptr, "|%d|", svector->dim);
ptr += n;
APPEND_CHAR(ptr, '\0');
PG_FREE_IF_COPY(svector, 0);
PG_RETURN_CSTRING(buf);
}
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_typmod_in);
Datum
svector_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 svector must be at least 1")));
if (*tl > SVECTOR_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type svector cannot exceed %d", SVECTOR_MAX_DIM)));
PG_RETURN_INT32(*tl);
}
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_recv);
Datum
svector_recv(PG_FUNCTION_ARGS)
{
StringInfo buf = (StringInfo) PG_GETARG_POINTER(0);
int32 typmod = PG_GETARG_INT32(2);
SVector *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 = InitSVector(dim, nnz);
values = SVECTOR_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(svector_send);
Datum
svector_send(PG_FUNCTION_ARGS)
{
SVector *svec = PG_GETARG_SVECTOR_P(0);
float *values = SVECTOR_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(svector);
Datum
svector(PG_FUNCTION_ARGS)
{
SVector *svec = PG_GETARG_SVECTOR_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_svector);
Datum
vector_to_svector(PG_FUNCTION_ARGS)
{
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
SVector *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 = InitSVector(dim, nnz);
values = SVECTOR_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(SVector * a, SVector * b)
{
float *ax = SVECTOR_VALUES(a);
float *bx = SVECTOR_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(svector_l2_distance);
Datum
svector_l2_distance(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_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(svector_l2_squared_distance);
Datum
svector_l2_squared_distance(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_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(SVector * a, SVector * b)
{
float *ax = SVECTOR_VALUES(a);
float *bx = SVECTOR_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(svector_inner_product);
Datum
svector_inner_product(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_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(svector_negative_inner_product);
Datum
svector_negative_inner_product(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_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(svector_cosine_distance);
Datum
svector_cosine_distance(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_P(1);
float *ax = SVECTOR_VALUES(a);
float *bx = SVECTOR_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 weighted Jaccard distance between two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_jaccard_distance);
Datum
svector_jaccard_distance(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_P(1);
float *ax = SVECTOR_VALUES(a);
float *bx = SVECTOR_VALUES(b);
double num = 0.0;
double denom = 0.0;
int bpos = 0;
CheckDims(a, b);
/*
* Weighted Jaccard distance is not defined for vectors with negative
* values. Could check and return NaN if minimal impact on performance.
*/
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)
{
num += ax[i] < bx[j] ? ax[i] : bx[j];
denom += ax[i] > bx[j] ? ax[i] : bx[j];
}
else if (ai > bi)
denom += bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
if (ai != bi)
denom += ax[i];
}
for (int j = bpos; j < b->nnz; j++)
denom += bx[j];
if (denom > 0)
PG_RETURN_FLOAT8(1.0 - (num / denom));
else
PG_RETURN_FLOAT8(NAN);
}

23
src/svector.h Normal file
View File

@@ -0,0 +1,23 @@
#ifndef SVECTOR_H
#define SVECTOR_H
#define SVECTOR_MAX_DIM 100000
#define SVECTOR_SIZE(_nnz) (offsetof(SVector, indices) + (_nnz) * sizeof(int32) + (_nnz * sizeof(float)))
#define SVECTOR_VALUES(x) ((float *) (((char *) (x)) + offsetof(SVector, indices) + (x)->nnz * sizeof(int32)))
#define DatumGetSVector(x) ((SVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_SVECTOR_P(x) DatumGetSVector(PG_GETARG_DATUM(x))
#define PG_RETURN_SVECTOR_P(x) PG_RETURN_POINTER(x)
typedef struct SVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int32 dim; /* number of dimensions */
int32 nnz;
int32 unused;
int32 indices[FLEXIBLE_ARRAY_MEMBER];
} SVector;
SVector *InitSVector(int dim, int nnz);
#endif

View File

@@ -9,6 +9,7 @@
#include "lib/stringinfo.h"
#include "libpq/pqformat.h"
#include "port.h" /* for strtof() */
#include "svector.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/lsyscache.h"
@@ -89,7 +90,7 @@ CheckDim(int dim)
}
/*
* Ensure finite elements
* Ensure finite element
*/
static inline void
CheckElement(float value)
@@ -437,17 +438,18 @@ vector_send(PG_FUNCTION_ARGS)
/*
* Convert vector to vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector);
Datum
vector(PG_FUNCTION_ARGS)
{
Vector *arg = PG_GETARG_VECTOR_P(0);
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
CheckExpectedDim(typmod, arg->dim);
CheckExpectedDim(typmod, vec->dim);
PG_RETURN_POINTER(arg);
PG_RETURN_POINTER(vec);
}
/*
@@ -464,7 +466,6 @@ array_to_vector(PG_FUNCTION_ARGS)
bool typbyval;
char typalign;
Datum *elemsp;
bool *nullsp;
int nelemsp;
if (ARR_NDIM(array) > 1)
@@ -478,7 +479,7 @@ array_to_vector(PG_FUNCTION_ARGS)
errmsg("array must not contain nulls")));
get_typlenbyvalalign(ARR_ELEMTYPE(array), &typlen, &typbyval, &typalign);
deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, &nullsp, &nelemsp);
deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, NULL, &nelemsp);
CheckDim(nelemsp);
CheckExpectedDim(typmod, nelemsp);
@@ -512,6 +513,12 @@ array_to_vector(PG_FUNCTION_ARGS)
errmsg("unsupported array type")));
}
/*
* Free allocation from deconstruct_array. Do not free individual elements
* when pass-by-reference since they point to original array.
*/
pfree(elemsp);
/* Check elements */
for (int i = 0; i < result->dim; i++)
CheckElement(result->x[i]);
@@ -1145,3 +1152,26 @@ vector_avg(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Convert sparse vector to dense vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_to_vector);
Datum
svector_to_vector(PG_FUNCTION_ARGS)
{
SVector *svec = PG_GETARG_SVECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
int dim = svec->dim;
float *values = SVECTOR_VALUES(svec);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitVector(dim);
for (int i = 0; i < svec->nnz; i++)
result->x[svec->indices[i]] = values[i];
PG_RETURN_POINTER(result);
}

View File

@@ -54,85 +54,85 @@ 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

140
test/expected/svector.out Normal file
View File

@@ -0,0 +1,140 @@
SELECT '(0,1.5),(2,3.5)|5|'::svector;
svector
--------------------
(0,1.5),(2,3.5)|5|
(1 row)
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector;
vector
-----------------
[1.5,0,3.5,0,0]
(1 row)
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector(5);
vector
-----------------
[1.5,0,3.5,0,0]
(1 row)
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector(4);
ERROR: expected 4 dimensions, not 5
SELECT '[0,1.5,0,3.5,0]'::vector::svector;
svector
--------------------
(1,1.5),(3,3.5)|5|
(1 row)
SELECT '(0,0),(1,1),(2,0)|3|'::svector;
svector
----------------------
(0,0),(1,1),(2,0)|3|
(1 row)
SELECT '|5|'::svector;
svector
---------
|5|
(1 row)
SELECT '|-1|'::svector;
ERROR: svector must have at least 1 dimension
LINE 1: SELECT '|-1|'::svector;
^
SELECT '|100001|'::svector;
ERROR: svector cannot have more than 100000 dimensions
LINE 1: SELECT '|100001|'::svector;
^
SELECT '|16001|'::svector::vector;
ERROR: vector cannot have more than 16000 dimensions
SELECT '(-1,1)|1|'::svector;
ERROR: index must not be negative
LINE 1: SELECT '(-1,1)|1|'::svector;
^
SELECT '(1,1)|1|'::svector;
ERROR: index must be less than dimensions
LINE 1: SELECT '(1,1)|1|'::svector;
^
SELECT '|1|'::svector(2);
ERROR: expected 2 dimensions, not 1
SELECT l2_distance('|2|'::svector, '(0,3),(1,4)|2|');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('|2|'::svector, '(1,1)|2|');
l2_distance
-------------
1
(1 row)
SELECT '|2|'::svector <-> '(0,3),(1,4)|2|';
?column?
----------
5
(1 row)
SELECT inner_product('(0,1),(1,2)|2|'::svector, '(0,2),(1,4)|2|');
inner_product
---------------
10
(1 row)
SELECT svector_negative_inner_product('(0,1),(1,2)|2|', '(0,2),(1,4)|2|');
svector_negative_inner_product
--------------------------------
-10
(1 row)
SELECT cosine_distance('(0,1),(1,2)|2|'::svector, '(0,2),(1,4)|2|');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('(0,1),(1,2)|2|'::svector, '|2|');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('(0,1),(1,1)|2|'::svector, '(0,-1),(1,-1)|2|');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('(0,1)|2|'::svector, '(1,2)|2|');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('|1|'::svector, '|1|');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('(0,1)|2|'::svector, '(0,1)|3|');
ERROR: different svector dimensions 2 and 3
SELECT jaccard_distance('(0,1)|2|', '(0,1)|2|');
jaccard_distance
------------------
0
(1 row)
SELECT jaccard_distance('(0,1)|2|', '(1,1)|2|');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('|1|', '|1|');
jaccard_distance
------------------
NaN
(1 row)
SELECT jaccard_distance('(0,1)|2|', '(0,1)|3|');
ERROR: different svector dimensions 2 and 3

View File

@@ -13,24 +13,24 @@ 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]');

36
test/sql/svector.sql Normal file
View File

@@ -0,0 +1,36 @@
SELECT '(0,1.5),(2,3.5)|5|'::svector;
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector;
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector(5);
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector(4);
SELECT '[0,1.5,0,3.5,0]'::vector::svector;
SELECT '(0,0),(1,1),(2,0)|3|'::svector;
SELECT '|5|'::svector;
SELECT '|-1|'::svector;
SELECT '|100001|'::svector;
SELECT '|16001|'::svector::vector;
SELECT '(-1,1)|1|'::svector;
SELECT '(1,1)|1|'::svector;
SELECT '|1|'::svector(2);
SELECT l2_distance('|2|'::svector, '(0,3),(1,4)|2|');
SELECT l2_distance('|2|'::svector, '(1,1)|2|');
SELECT '|2|'::svector <-> '(0,3),(1,4)|2|';
SELECT inner_product('(0,1),(1,2)|2|'::svector, '(0,2),(1,4)|2|');
SELECT svector_negative_inner_product('(0,1),(1,2)|2|', '(0,2),(1,4)|2|');
SELECT cosine_distance('(0,1),(1,2)|2|'::svector, '(0,2),(1,4)|2|');
SELECT cosine_distance('(0,1),(1,2)|2|'::svector, '|2|');
SELECT cosine_distance('(0,1),(1,1)|2|'::svector, '(0,-1),(1,-1)|2|');
SELECT cosine_distance('(0,1)|2|'::svector, '(1,2)|2|');
SELECT cosine_distance('|1|'::svector, '|1|');
SELECT cosine_distance('(0,1)|2|'::svector, '(0,1)|3|');
SELECT jaccard_distance('(0,1)|2|', '(0,1)|2|');
SELECT jaccard_distance('(0,1)|2|', '(1,1)|2|');
SELECT jaccard_distance('|1|', '|1|');
SELECT jaccard_distance('(0,1)|2|', '(0,1)|3|');