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34 Commits

Author SHA1 Message Date
Andrew Kane
2b125a1956 Moved bit functions to separate file 2024-03-27 13:42:24 -07:00
Andrew Kane
fcd655d2a3 Improved test [skip ci] 2024-03-26 19:26:52 -07:00
Andrew Kane
97fe28940d Updated readme [skip ci] 2024-03-25 23:33:59 -07:00
Andrew Kane
23c5bf6ef6 Fixed CI [skip ci] 2024-03-25 23:22:03 -07:00
Andrew Kane
9ed4303a5e Fixed test 2024-03-25 23:16:38 -07:00
Andrew Kane
acd066463a Added Jaccard distance to test 2024-03-25 23:15:14 -07:00
Andrew Kane
be936075eb Improved test [skip ci] 2024-03-25 23:13:30 -07:00
Andrew Kane
a9959fede2 Improved code [skip ci] 2024-03-25 23:03:12 -07:00
Andrew Kane
02c4f4884c Added support for indexing Jaccard distance 2024-03-25 22:44:51 -07:00
Andrew Kane
791fc2436f Added jaccard_distance function 2024-03-25 22:35:53 -07:00
Andrew Kane
e7a7936bb2 Improved code [skip ci] 2024-03-25 19:23:30 -07:00
Andrew Kane
ce2ba65906 Fixed CI 2024-03-25 19:07:09 -07:00
Andrew Kane
023633a274 Added test for build recall 2024-03-25 19:02:37 -07:00
Andrew Kane
9baa051b5b Fixed CI 2024-03-25 17:20:35 -07:00
Andrew Kane
ac94ac7cf1 Updated changelog [skip ci] 2024-03-25 17:18:09 -07:00
Andrew Kane
8b819dfdc2 Moved bit code to separate files 2024-03-25 17:10:01 -07:00
Andrew Kane
d9ca850faf Updated max dimensions [skip ci] 2024-03-25 16:56:32 -07:00
Andrew Kane
131782999b Updated changelog [skip ci] 2024-03-25 16:47:25 -07:00
Andrew Kane
d57ef873c2 Improved test [skip ci] 2024-03-25 16:43:15 -07:00
Andrew Kane
30c86fb05a Improved test [skip ci] 2024-03-25 16:41:40 -07:00
Andrew Kane
833f379ebe Added quantize_binary function 2024-03-25 16:39:55 -07:00
Andrew Kane
709fc75ce0 Updated changelog [skip ci] 2024-03-25 16:11:52 -07:00
Andrew Kane
2bc959b3eb Updated readme [skip ci] 2024-03-25 15:53:44 -07:00
Andrew Kane
ec9e13b5fb Improved test [skip ci] 2024-03-25 15:50:38 -07:00
Andrew Kane
95e476d570 Fixed CI 2024-03-25 15:49:18 -07:00
Andrew Kane
6bc0c47a0a Updated comments [skip ci] 2024-03-25 15:43:05 -07:00
Andrew Kane
58eeefeef4 Handle nulls 2024-03-25 15:40:15 -07:00
Andrew Kane
263e684824 Started indexing 2024-03-25 15:25:04 -07:00
Andrew Kane
21dfed5719 Fixed CI 2024-03-25 14:24:19 -07:00
Andrew Kane
f3aec9fd03 Added hamming_distance function 2024-03-25 14:22:23 -07:00
Andrew Kane
31e41b3ba9 Added FAQ about binary vectors [skip ci] 2024-03-24 11:07:34 -07:00
Andrew Kane
903a925662 Improved type modifier tests 2024-03-21 17:31:08 -07:00
Andrew Kane
96ff19be44 Version bump to 0.6.2 [skip ci] 2024-03-18 10:21:04 -07:00
Andrew Kane
6c969bebad Updated changelog [skip ci] 2024-03-18 10:11:45 -07:00
25 changed files with 577 additions and 65 deletions

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@@ -1,15 +1,18 @@
## 0.7.0 (unreleased) ## 0.7.0 (unreleased)
- Added concatenate operator for vectors - Added support for binary vectors to HNSW
- Added `hamming_distance` function
- Added `jaccard_distance` function
- Added `quantize_binary` function
## 0.6.2 (unreleased) ## 0.6.2 (2024-03-18)
- Reduced lock contention with parallel HNSW index builds - Reduced lock contention with parallel HNSW index builds
## 0.6.1 (2024-03-04) ## 0.6.1 (2024-03-04)
- Fixed error with `ANALYZE` and vectors with different dimensions - Fixed error with `ANALYZE` and vectors with different dimensions
- Fixed error with `shared_preload_libraries` - Fixed segmentation fault with `shared_preload_libraries`
- Fixed vector subtraction being marked as commutative - Fixed vector subtraction being marked as commutative
## 0.6.0 (2024-01-29) ## 0.6.0 (2024-01-29)

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@@ -2,7 +2,7 @@
"name": "vector", "name": "vector",
"abstract": "Open-source vector similarity search for Postgres", "abstract": "Open-source vector similarity search for Postgres",
"description": "Supports L2 distance, inner product, and cosine distance", "description": "Supports L2 distance, inner product, and cosine distance",
"version": "0.6.1", "version": "0.6.2",
"maintainer": [ "maintainer": [
"Andrew Kane <andrew@ankane.org>" "Andrew Kane <andrew@ankane.org>"
], ],
@@ -20,7 +20,7 @@
"vector": { "vector": {
"file": "sql/vector.sql", "file": "sql/vector.sql",
"docfile": "README.md", "docfile": "README.md",
"version": "0.6.1", "version": "0.6.2",
"abstract": "Open-source vector similarity search for Postgres" "abstract": "Open-source vector similarity search for Postgres"
} }
}, },

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@@ -1,9 +1,9 @@
EXTENSION = vector EXTENSION = vector
EXTVERSION = 0.6.1 EXTVERSION = 0.6.2
MODULE_big = vector MODULE_big = vector
DATA = $(wildcard sql/*--*.sql) 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 OBJS = src/bitvector.o 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 HEADERS = src/vector.h
TESTS = $(wildcard test/sql/*.sql) TESTS = $(wildcard test/sql/*.sql)

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@@ -1,7 +1,7 @@
EXTENSION = vector 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 OBJS = src\bitvector.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
HEADERS = src\vector.h HEADERS = src\vector.h
REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged

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@@ -5,7 +5,7 @@ Open-source vector similarity search for Postgres
Store your vectors with the rest of your data. Supports: Store your vectors with the rest of your data. Supports:
- exact and approximate nearest neighbor search - exact and approximate nearest neighbor search
- L2 distance, inner product, and cosine distance - L2 distance, inner product, cosine distance, and more
- any [language](#languages) with a Postgres client - any [language](#languages) with a Postgres client
Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recovery, JOINs, and all of the other [great features](https://www.postgresql.org/about/) of Postgres Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recovery, JOINs, and all of the other [great features](https://www.postgresql.org/about/) of Postgres
@@ -20,7 +20,7 @@ Compile and install the extension (supports Postgres 12+)
```sh ```sh
cd /tmp 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 cd pgvector
make make
make install # may need sudo make install # may need sudo
@@ -45,7 +45,7 @@ Then use `nmake` to build:
```cmd ```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16" set "PGROOT=C:\Program Files\PostgreSQL\16"
cd %TEMP% cd %TEMP%
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 cd pgvector
nmake /F Makefile.win nmake /F Makefile.win
nmake /F Makefile.win install nmake /F Makefile.win install
@@ -221,7 +221,19 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops); CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
``` ```
Vectors with up to 2,000 dimensions can be indexed. Hamming distance - added in 0.7.0
```sql
CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
```
Jaccard distance - added in 0.7.0
```sql
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
```
Vectors with up to 2,000 dimensions can be indexed, or bit vectors with up to 64,000 dimensions.
### Index Options ### Index Options
@@ -604,6 +616,18 @@ and query with:
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5; SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
``` ```
#### Are binary vectors supported?
You can store binary vectors and perform exact nearest neighbor search by Hamming distance in Postgres without an extension ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py)).
```tsql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES (B'000'), (B'111');
SELECT * FROM items ORDER BY bit_count(embedding # B'101') LIMIT 5;
```
Indexing is not currently supported.
#### Do indexes need to fit into memory? #### Do indexes need to fit into memory?
No, but like other index types, youll likely see better performance if they do. You can get the size of an index with: No, but like other index types, youll likely see better performance if they do. You can get the size of an index with:
@@ -682,7 +706,6 @@ Operator | Description | Added
\+ | element-wise addition | \+ | element-wise addition |
\- | element-wise subtraction | \- | element-wise subtraction |
\* | element-wise multiplication | 0.5.0 \* | element-wise multiplication | 0.5.0
\|\| | concatenate | 0.7.0
<-> | Euclidean distance | <-> | Euclidean distance |
<#> | negative inner product | <#> | negative inner product |
<=> | cosine distance | <=> | cosine distance |
@@ -695,6 +718,7 @@ cosine_distance(vector, vector) → double precision | cosine distance |
inner_product(vector, vector) → double precision | inner product | inner_product(vector, vector) → double precision | inner product |
l2_distance(vector, vector) → double precision | Euclidean distance | l2_distance(vector, vector) → double precision | Euclidean distance |
l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0 l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
quantize_binary(vector) → bit | quantize | 0.7.0
vector_dims(vector) → integer | number of dimensions | vector_dims(vector) → integer | number of dimensions |
vector_norm(vector) → double precision | Euclidean norm | vector_norm(vector) → double precision | Euclidean norm |
@@ -705,6 +729,20 @@ Function | Description | Added
avg(vector) → vector | average | avg(vector) → vector | average |
sum(vector) → vector | sum | 0.5.0 sum(vector) → vector | sum | 0.5.0
### Bit Operators
Operator | Description | Added
--- | --- | ---
<~> | Hamming distance | 0.7.0
<%> | Jaccard distance | 0.7.0
### Bit Functions
Function | Description | Added
--- | --- | ---
hamming_distance(bit, bit) → double precision | Hamming distance | 0.7.0
jaccard_distance(bit, bit) → double precision | Jaccard distance | 0.7.0
## Installation Notes - Linux and Mac ## Installation Notes - Linux and Mac
### Postgres Location ### Postgres Location
@@ -780,7 +818,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
You can also build the image manually: You can also build the image manually:
```sh ```sh
git clone --branch v0.6.1 https://github.com/pgvector/pgvector.git git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector cd pgvector
docker build --build-arg PG_MAJOR=16 -t myuser/pgvector . docker build --build-arg PG_MAJOR=16 -t myuser/pgvector .
``` ```

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@@ -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

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@@ -1,9 +1,31 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION -- 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 \echo Use "ALTER EXTENSION vector UPDATE TO '0.7.0'" to load this file. \quit
CREATE FUNCTION vector_concat(vector, vector) RETURNS vector CREATE FUNCTION quantize_binary(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR || ( CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_concat AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
); );
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit);

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@@ -58,6 +58,9 @@ CREATE FUNCTION vector_sub(vector, vector) RETURNS vector
CREATE FUNCTION vector_mul(vector, vector) RETURNS vector CREATE FUNCTION vector_mul(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION quantize_binary(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- private functions -- private functions
CREATE FUNCTION vector_lt(vector, vector) RETURNS bool CREATE FUNCTION vector_lt(vector, vector) RETURNS bool
@@ -99,9 +102,6 @@ CREATE FUNCTION vector_avg(double precision[]) RETURNS vector
CREATE FUNCTION vector_combine(double precision[], double precision[]) RETURNS double precision[] CREATE FUNCTION vector_combine(double precision[], double precision[]) RETURNS double precision[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_concat(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- aggregates -- aggregates
CREATE AGGREGATE avg(vector) ( CREATE AGGREGATE avg(vector) (
@@ -227,10 +227,6 @@ CREATE OPERATOR > (
RESTRICT = scalargtsel, JOIN = scalargtjoinsel RESTRICT = scalargtsel, JOIN = scalargtjoinsel
); );
CREATE OPERATOR || (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_concat
);
-- access methods -- access methods
CREATE FUNCTION ivfflathandler(internal) RETURNS index_am_handler CREATE FUNCTION ivfflathandler(internal) RETURNS index_am_handler
@@ -294,3 +290,31 @@ CREATE OPERATOR CLASS vector_cosine_ops
OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops, OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_negative_inner_product(vector, vector), FUNCTION 1 vector_negative_inner_product(vector, vector),
FUNCTION 2 vector_norm(vector); FUNCTION 2 vector_norm(vector);
-- bit functions
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
);
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit);

90
src/bitvector.c Normal file
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@@ -0,0 +1,90 @@
#include "postgres.h"
#include "bitvector.h"
#include "port/pg_bitutils.h"
#include "utils/varbit.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
#endif
/*
* Allocate and initialize a new bit vector
*/
VarBit *
InitBitVector(int dim)
{
VarBit *result;
int size;
size = VARBITTOTALLEN(dim);
result = (VarBit *) palloc0(size);
SET_VARSIZE(result, size);
VARBITLEN(result) = dim;
return result;
}
/*
* Ensure same number of bits
*/
static inline void
CheckBitLengths(uint32 aLen, uint32 bLen)
{
if (aLen != bLen)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different bit lengths %u and %u", aLen, bLen)));
}
/*
* Get the Hamming distance between two bit strings
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(hamming_distance);
Datum
hamming_distance(PG_FUNCTION_ARGS)
{
VarBit *a = PG_GETARG_VARBIT_P(0);
VarBit *b = PG_GETARG_VARBIT_P(1);
unsigned char *ax = VARBITS(a);
unsigned char *bx = VARBITS(b);
uint64 distance = 0;
CheckBitLengths(VARBITLEN(a), VARBITLEN(b));
/* TODO Improve performance */
for (uint32 i = 0; i < VARBITBYTES(a); i++)
distance += pg_number_of_ones[ax[i] ^ bx[i]];
PG_RETURN_FLOAT8((double) distance);
}
/*
* Get the Jaccard distance between two bit strings
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(jaccard_distance);
Datum
jaccard_distance(PG_FUNCTION_ARGS)
{
VarBit *a = PG_GETARG_VARBIT_P(0);
VarBit *b = PG_GETARG_VARBIT_P(1);
unsigned char *ax = VARBITS(a);
unsigned char *bx = VARBITS(b);
uint64 ab = 0;
uint64 aa;
uint64 bb;
CheckBitLengths(VARBITLEN(a), VARBITLEN(b));
/* TODO Improve performance */
for (uint32 i = 0; i < VARBITBYTES(a); i++)
ab += pg_number_of_ones[ax[i] & bx[i]];
if (ab == 0)
PG_RETURN_FLOAT8(1);
aa = pg_popcount((char *) ax, VARBITBYTES(a));
bb = pg_popcount((char *) bx, VARBITBYTES(b));
PG_RETURN_FLOAT8(1 - (ab / ((double) (aa + bb - ab))));
}

8
src/bitvector.h Normal file
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@@ -0,0 +1,8 @@
#ifndef BITVECTOR_H
#define BITVECTOR_H
#include "utils/varbit.h"
VarBit *InitBitVector(int dim);
#endif

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@@ -44,6 +44,7 @@
#include "access/xact.h" #include "access/xact.h"
#include "access/xloginsert.h" #include "access/xloginsert.h"
#include "catalog/index.h" #include "catalog/index.h"
#include "catalog/pg_type_d.h"
#include "commands/progress.h" #include "commands/progress.h"
#include "hnsw.h" #include "hnsw.h"
#include "miscadmin.h" #include "miscadmin.h"
@@ -671,6 +672,12 @@ HnswSharedMemoryAlloc(Size size, void *state)
static void static void
InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum) InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum)
{ {
int maxDimensions = HNSW_MAX_DIM;
Oid typid = TupleDescAttr(index->rd_att, 0)->atttypid;
if (typid == BITOID || typid == VARBITOID)
maxDimensions *= 32;
buildstate->heap = heap; buildstate->heap = heap;
buildstate->index = index; buildstate->index = index;
buildstate->indexInfo = indexInfo; buildstate->indexInfo = indexInfo;
@@ -684,8 +691,8 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
if (buildstate->dimensions < 0) if (buildstate->dimensions < 0)
elog(ERROR, "column does not have dimensions"); elog(ERROR, "column does not have dimensions");
if (buildstate->dimensions > HNSW_MAX_DIM) if (buildstate->dimensions > maxDimensions)
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", HNSW_MAX_DIM); elog(ERROR, "column cannot have more than %d dimensions for hnsw index", maxDimensions);
if (buildstate->efConstruction < 2 * buildstate->m) if (buildstate->efConstruction < 2 * buildstate->m)
elog(ERROR, "ef_construction must be greater than or equal to 2 * m"); elog(ERROR, "ef_construction must be greater than or equal to 2 * m");

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@@ -1,6 +1,8 @@
#include "postgres.h" #include "postgres.h"
#include "access/relscan.h" #include "access/relscan.h"
#include "bitvector.h"
#include "catalog/pg_type_d.h"
#include "hnsw.h" #include "hnsw.h"
#include "pgstat.h" #include "pgstat.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
@@ -73,7 +75,15 @@ GetScanValue(IndexScanDesc scan)
Datum value; Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL) if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation))); {
Oid typid = TupleDescAttr(scan->indexRelation->rd_att, 0)->atttypid;
int dimensions = GetDimensions(scan->indexRelation);
if (typid == BITOID || typid == VARBITOID)
value = PointerGetDatum(InitBitVector(dimensions));
else
value = PointerGetDatum(InitVector(dimensions));
}
else else
{ {
value = scan->orderByData->sk_argument; value = scan->orderByData->sk_argument;

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@@ -2,6 +2,7 @@
#include <math.h> #include <math.h>
#include "bitvector.h"
#include "catalog/pg_type.h" #include "catalog/pg_type.h"
#include "common/shortest_dec.h" #include "common/shortest_dec.h"
#include "fmgr.h" #include "fmgr.h"
@@ -860,6 +861,26 @@ vector_mul(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
/*
* Quantize a vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(quantize_binary);
Datum
quantize_binary(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
float *ax = a->x;
VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result);
/* TODO Improve */
for (int i = 0; i < a->dim; i++)
rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result);
}
/* /*
* Internal helper to compare vectors * Internal helper to compare vectors
*/ */
@@ -1160,28 +1181,3 @@ vector_avg(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
/*
* Concat vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_concat);
Datum
vector_concat(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
Vector *result;
int dim = a->dim + b->dim;
CheckDim(dim);
result = InitVector(dim);
for (int i = 0; i < a->dim; i++)
result->x[i] = a->x[i];
for (int i = 0; i < b->dim; i++)
result->x[i + a->dim] = b->x[i];
PG_RETURN_POINTER(result);
}

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@@ -0,0 +1,64 @@
SELECT hamming_distance(B'111', B'111');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance(B'111', B'110');
hamming_distance
------------------
1
(1 row)
SELECT hamming_distance(B'111', B'100');
hamming_distance
------------------
2
(1 row)
SELECT hamming_distance(B'111', B'000');
hamming_distance
------------------
3
(1 row)
SELECT hamming_distance(B'111', B'00');
ERROR: different bit lengths 3 and 2
SELECT jaccard_distance(B'1111', B'1111');
jaccard_distance
------------------
0
(1 row)
SELECT jaccard_distance(B'1111', B'1110');
jaccard_distance
------------------
0.25
(1 row)
SELECT jaccard_distance(B'1111', B'1100');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance(B'1111', B'1000');
jaccard_distance
------------------
0.75
(1 row)
SELECT jaccard_distance(B'1111', B'0000');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance(B'1100', B'1000');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance(B'1111', B'000');
ERROR: different bit lengths 4 and 3

View File

@@ -24,14 +24,6 @@ SELECT '[1e37]'::vector * '[1e37]';
ERROR: value out of range: overflow ERROR: value out of range: overflow
SELECT '[1e-37]'::vector * '[1e-37]'; SELECT '[1e-37]'::vector * '[1e-37]';
ERROR: value out of range: underflow ERROR: value out of range: underflow
SELECT '[1,2,3]'::vector || '[4,5]'::vector;
?column?
-------------
[1,2,3,4,5]
(1 row)
SELECT array_fill(0, ARRAY[16000])::vector || '[1]'::vector;
ERROR: vector cannot have more than 16000 dimensions
SELECT '[1,2,3]'::vector = '[1,2,3]'; SELECT '[1,2,3]'::vector = '[1,2,3]';
?column? ?column?
---------- ----------
@@ -216,6 +208,18 @@ SELECT l1_distance('[3e38]', '[-3e38]');
Infinity Infinity
(1 row) (1 row)
SELECT quantize_binary('[1,0,-1]');
quantize_binary
-----------------
100
(1 row)
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]');
quantize_binary
-----------------
01001110101
(1 row)
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]']) v;
avg avg
----------- -----------

View File

@@ -0,0 +1,21 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
val
-----
111
110
100
000
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

@@ -0,0 +1,21 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(4));
INSERT INTO t (val) VALUES (B'0000'), (B'1100'), (B'1111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_jaccard_ops);
INSERT INTO t (val) VALUES (B'1110');
SELECT * FROM t ORDER BY val <%> B'1111';
val
------
1111
1110
1100
0000
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <%> (SELECT NULL::bit)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

@@ -116,8 +116,30 @@ SELECT '[1, ,3]'::vector;
ERROR: invalid input syntax for type vector: "[1, ,3]" ERROR: invalid input syntax for type vector: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::vector; LINE 1: SELECT '[1, ,3]'::vector;
^ ^
SELECT '[1,2,3]'::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector(2); SELECT '[1,2,3]'::vector(2);
ERROR: expected 2 dimensions, not 3 ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::vector(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::vector(3, 2);
^
SELECT '[1,2,3]'::vector('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::vector('a');
^
SELECT '[1,2,3]'::vector(0);
ERROR: dimensions for type vector must be at least 1
LINE 1: SELECT '[1,2,3]'::vector(0);
^
SELECT '[1,2,3]'::vector(16001);
ERROR: dimensions for type vector cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::vector(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]); SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
unnest unnest
--------- ---------

View File

@@ -0,0 +1,13 @@
SELECT hamming_distance(B'111', B'111');
SELECT hamming_distance(B'111', B'110');
SELECT hamming_distance(B'111', B'100');
SELECT hamming_distance(B'111', B'000');
SELECT hamming_distance(B'111', B'00');
SELECT jaccard_distance(B'1111', B'1111');
SELECT jaccard_distance(B'1111', B'1110');
SELECT jaccard_distance(B'1111', B'1100');
SELECT jaccard_distance(B'1111', B'1000');
SELECT jaccard_distance(B'1111', B'0000');
SELECT jaccard_distance(B'1100', B'1000');
SELECT jaccard_distance(B'1111', B'000');

View File

@@ -6,9 +6,6 @@ SELECT '[1,2,3]'::vector * '[4,5,6]';
SELECT '[1e37]'::vector * '[1e37]'; SELECT '[1e37]'::vector * '[1e37]';
SELECT '[1e-37]'::vector * '[1e-37]'; SELECT '[1e-37]'::vector * '[1e-37]';
SELECT '[1,2,3]'::vector || '[4,5]'::vector;
SELECT array_fill(0, ARRAY[16000])::vector || '[1]'::vector;
SELECT '[1,2,3]'::vector = '[1,2,3]'; SELECT '[1,2,3]'::vector = '[1,2,3]';
SELECT '[1,2,3]'::vector = '[1,2]'; SELECT '[1,2,3]'::vector = '[1,2]';
@@ -51,6 +48,9 @@ SELECT l1_distance('[0,0]', '[0,1]');
SELECT l1_distance('[1,2]', '[3]'); SELECT l1_distance('[1,2]', '[3]');
SELECT l1_distance('[3e38]', '[-3e38]'); SELECT l1_distance('[3e38]', '[-3e38]');
SELECT quantize_binary('[1,0,-1]');
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]');
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]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v; SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v; SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;

12
test/sql/hnsw_hamming.sql Normal file
View File

@@ -0,0 +1,12 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
DROP TABLE t;

12
test/sql/hnsw_jaccard.sql Normal file
View File

@@ -0,0 +1,12 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(4));
INSERT INTO t (val) VALUES (B'0000'), (B'1100'), (B'1111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_jaccard_ops);
INSERT INTO t (val) VALUES (B'1110');
SELECT * FROM t ORDER BY val <%> B'1111';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <%> (SELECT NULL::bit)) t2;
DROP TABLE t;

View File

@@ -22,7 +22,13 @@ SELECT '[1,]'::vector;
SELECT '[1a]'::vector; SELECT '[1a]'::vector;
SELECT '[1,,3]'::vector; SELECT '[1,,3]'::vector;
SELECT '[1, ,3]'::vector; SELECT '[1, ,3]'::vector;
SELECT '[1,2,3]'::vector(3);
SELECT '[1,2,3]'::vector(2); SELECT '[1,2,3]'::vector(2);
SELECT '[1,2,3]'::vector(3, 2);
SELECT '[1,2,3]'::vector('a');
SELECT '[1,2,3]'::vector(0);
SELECT '[1,2,3]'::vector(16001);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]); SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
SELECT '{"[1,2,3]"}'::vector(2)[]; SELECT '{"[1,2,3]"}'::vector(2)[];

View File

@@ -0,0 +1,137 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 52;
my $max = 2**$dim;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator $queries[0] LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
SELECT i FROM tst ORDER BY v $operator $queries[$i] LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v bit($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, (random() * $max)::bigint::bit($dim) FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1 .. 20)
{
my $r = int(rand() * $max);
push(@queries, "${r}::bigint::bit($dim)");
}
# Check each index type
my @operators = ("<~>", "<\%>");
my @opclasses = ("bit_hamming_ops", "bit_jaccard_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Get exact results
@expected = ();
foreach (@queries)
{
# Handle ties
my $res = $node->safe_psql("postgres", qq(
WITH top AS (
SELECT v $operator $_ AS distance FROM tst ORDER BY v $operator $_ LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator $_) <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
# Build index serially
$node->safe_psql("postgres", qq(
SET max_parallel_maintenance_workers = 0;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
# Test approximate results
my $min = $operator eq "<\%>" ? 0.96 : 0.99;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel in memory
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel on disk
# Set parallel_workers on table to use workers with low maintenance_work_mem
($ret, $stdout, $stderr) = $node->psql("postgres", qq(
ALTER TABLE tst SET (parallel_workers = 2);
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '4MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
ALTER TABLE tst RESET (parallel_workers);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem/);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

View File

@@ -1,4 +1,4 @@
comment = 'vector data type and ivfflat and hnsw access methods' comment = 'vector data type and ivfflat and hnsw access methods'
default_version = '0.6.1' default_version = '0.6.2'
module_pathname = '$libdir/vector' module_pathname = '$libdir/vector'
relocatable = true relocatable = true