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42 Commits

Author SHA1 Message Date
Andrew Kane
27db2b7145 Align values [skip ci] 2024-03-30 23:52:33 -07:00
Andrew Kane
bb6d3f81f3 Added sparsevec type 2024-03-30 22:48:25 -07:00
Andrew Kane
4b22851bbd Added more vector input tests [skip ci] 2024-03-30 10:17:55 -07:00
Andrew Kane
3acdbf99e8 Added casting to distance functions in tests [skip ci] 2024-03-30 09:05:15 -07:00
Andrew Kane
11ea3d8483 Updated SQL comments [skip ci] 2024-03-30 08:29:01 -07:00
Andrew Kane
2c48e3edc2 Mark type-specific code 2024-03-29 14:01:48 -07:00
Andrew Kane
7d63bb4b98 Fixed flaky test [skip ci] 2024-03-29 11:00:16 -07:00
Andrew Kane
de410a2915 Use variable for max dimemsions [skip ci] 2024-03-29 10:57:16 -07:00
Andrew Kane
64aa99aa31 Added todo [skip ci] 2024-03-29 10:56:24 -07:00
Andrew Kane
997fa167da Removed vector-specific code from HNSW 2024-03-29 10:50:06 -07:00
Andrew Kane
67eec4edbf Improved tuning section [skip ci] 2024-03-27 22:04:28 -07:00
Andrew Kane
396090d8e0 Improved code [skip ci] 2024-03-27 21:38:22 -07:00
Andrew Kane
ba18942fcf Removed normvec from IVFFlat for simplicity (no difference in performance) 2024-03-27 16:41:17 -07:00
Andrew Kane
8e59455c3c Removed normvec for simplicity (no difference in performance) 2024-03-27 16:33:11 -07:00
Andrew Kane
bd50e3067d Updated readme [skip ci] 2024-03-27 14:14:49 -07:00
Andrew Kane
af9d4ad659 Updated readme [skip ci] 2024-03-27 14:12:08 -07:00
Andrew Kane
08abb63cbe Added notes about NULL vectors [skip ci] 2024-03-27 11:50:37 -07:00
Andrew Kane
06b8556a49 Revert "Updated readme [skip ci]"
This reverts commit 3f674c9994.
2024-03-25 23:33:46 -07:00
Andrew Kane
3f674c9994 Updated readme [skip ci] 2024-03-25 23:33:17 -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
Andrew Kane
b64a1482d9 Moved example [skip ci] 2024-03-16 15:20:26 -07:00
Andrew Kane
a5f2d70bc2 Use temp directory for installation instructions on Windows [skip ci] 2024-03-16 12:02:45 -07:00
Andrew Kane
f3fcb5e005 Moved installation notes for Windows [skip ci] 2024-03-16 11:47:18 -07:00
Andrew Kane
3a6e0afb9c Added installation notes for Windows [skip ci] 2024-03-16 11:35:55 -07:00
Andrew Kane
183d50bdbd Added note about creating indexes concurrently [skip ci] 2024-03-16 10:45:09 -07:00
Andrew Kane
bd776fee68 Updated readme [skip ci] 2024-03-16 10:44:45 -07:00
Andrew Kane
d30b113e4b Updated readme [skip ci] 2024-03-15 21:54:58 -07:00
Andrew Kane
fd3200f718 Updated readme [skip ci] 2024-03-15 21:47:57 -07:00
Andrew Kane
02c815d876 Added docs on tuning, monitoring, and scaling [skip ci] 2024-03-15 19:00:49 -07:00
Andrew Kane
4b2a7cc49d Improved performance section [skip ci] 2024-03-15 17:54:14 -07:00
Andrew Kane
da0ff998e9 Updated readme [skip ci] 2024-03-15 14:23:56 -07:00
Andrew Kane
cb36e24289 Improved portability section [skip ci] 2024-03-15 14:23:04 -07:00
Andrew Kane
b1d0d4c7a3 Improved troubleshooting docs [skip ci] 2024-03-15 14:01:24 -07:00
Andrew Kane
1dc6514b66 Updated comment [skip ci] 2024-03-15 12:38:14 -07:00
Andrew Kane
6c53f7ca02 Updated comment [skip ci] 2024-03-15 12:37:47 -07:00
Heikki Linnakangas
0d35a14198 Fix compiler warnings in strict C99 mode (#487)
Redefining a typedef is a C11 feature:

    In file included from src/hnsw.c:10:
    src/hnsw.h:147:5: warning: redefinition of typedef 'HnswElementData' is a C11 feature [-Wtypedef-redefinition]
    }                       HnswElementData;
                            ^
    src/hnsw.h:118:32: note: previous definition is here
    typedef struct HnswElementData HnswElementData;
                                   ^
    src/hnsw.h:163:5: warning: redefinition of typedef 'HnswNeighborArray' is a C11 feature [-Wtypedef-redefinition]
    }                       HnswNeighborArray;
                            ^
    src/hnsw.h:119:34: note: previous definition is here
    typedef struct HnswNeighborArray HnswNeighborArray;
                                     ^
    2 warnings generated.

I got these warnings when I built PostgreSQL with "CC=clang
CFLAGS=-std=gnu99"; other similar options would surely produce the
warnings too.
2024-03-12 02:02:33 -07:00
Andrew Kane
3ea2ce89be Reduced lock contention with parallel HNSW index builds 2024-03-11 20:16:55 -07:00
Andrew Kane
62350b1589 Added note about IVFFlat results [skip ci] 2024-03-06 00:29:55 -08:00
Andrew Kane
dd57309281 Added section about HNSW results - #480 [skip ci] 2024-03-06 00:27:50 -08:00
40 changed files with 1733 additions and 148 deletions

View File

@@ -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 && ^

View File

@@ -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)

View File

@@ -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"
}
},

View File

@@ -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))

View File

@@ -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
View File

@@ -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 servers 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, youll 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 isnt 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

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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

View 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);

View File

@@ -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);

View File

@@ -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);

View File

@@ -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);
}

View File

@@ -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;
}

View File

@@ -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;

View File

@@ -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);
}

View File

@@ -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);

View File

@@ -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);

View File

@@ -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;
}

View File

@@ -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));

View File

@@ -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
View 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
View 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

View File

@@ -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);
}

View File

@@ -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

View File

@@ -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

View 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;

View 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;

View 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;

View File

@@ -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
---------

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@@ -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

View 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

View File

@@ -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;

View File

@@ -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;

View 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;

View 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;

View 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;

View File

@@ -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)[];

View 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');

View 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);

View File

@@ -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

View File

@@ -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