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2 Commits
vector-ran
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hnsw-entry
| Author | SHA1 | Date | |
|---|---|---|---|
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75cf54a1e2 | ||
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569fd36396 |
1
.github/workflows/build.yml
vendored
1
.github/workflows/build.yml
vendored
@@ -73,7 +73,6 @@ jobs:
|
||||
postgres-version: 14
|
||||
- run: |
|
||||
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
|
||||
cd %TEMP% && ^
|
||||
nmake /NOLOGO /F Makefile.win && ^
|
||||
nmake /NOLOGO /F Makefile.win install && ^
|
||||
nmake /NOLOGO /F Makefile.win installcheck && ^
|
||||
|
||||
@@ -1,11 +1,11 @@
|
||||
## 0.6.2 (2024-03-18)
|
||||
## 0.6.2 (unreleased)
|
||||
|
||||
- Reduced lock contention with parallel HNSW index builds
|
||||
|
||||
## 0.6.1 (2024-03-04)
|
||||
|
||||
- Fixed error with `ANALYZE` and vectors with different dimensions
|
||||
- Fixed segmentation fault with `shared_preload_libraries`
|
||||
- Fixed error with `shared_preload_libraries`
|
||||
- Fixed vector subtraction being marked as commutative
|
||||
|
||||
## 0.6.0 (2024-01-29)
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
"name": "vector",
|
||||
"abstract": "Open-source vector similarity search for Postgres",
|
||||
"description": "Supports L2 distance, inner product, and cosine distance",
|
||||
"version": "0.6.2",
|
||||
"version": "0.6.1",
|
||||
"maintainer": [
|
||||
"Andrew Kane <andrew@ankane.org>"
|
||||
],
|
||||
@@ -20,7 +20,7 @@
|
||||
"vector": {
|
||||
"file": "sql/vector.sql",
|
||||
"docfile": "README.md",
|
||||
"version": "0.6.2",
|
||||
"version": "0.6.1",
|
||||
"abstract": "Open-source vector similarity search for Postgres"
|
||||
}
|
||||
},
|
||||
|
||||
2
Makefile
2
Makefile
@@ -1,5 +1,5 @@
|
||||
EXTENSION = vector
|
||||
EXTVERSION = 0.6.2
|
||||
EXTVERSION = 0.6.1
|
||||
|
||||
MODULE_big = vector
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||||
DATA = $(wildcard sql/*--*.sql)
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||||
|
||||
@@ -1,5 +1,5 @@
|
||||
EXTENSION = vector
|
||||
EXTVERSION = 0.6.2
|
||||
EXTVERSION = 0.6.1
|
||||
|
||||
OBJS = src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
|
||||
HEADERS = src\vector.h
|
||||
|
||||
148
README.md
148
README.md
@@ -20,13 +20,13 @@ Compile and install the extension (supports Postgres 12+)
|
||||
|
||||
```sh
|
||||
cd /tmp
|
||||
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.6.1 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
make
|
||||
make install # may need sudo
|
||||
```
|
||||
|
||||
See the [installation notes](#installation-notes---linux-and-mac) if you run into issues
|
||||
See the [installation notes](#installation-notes) if you run into issues
|
||||
|
||||
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), [pkg](#pkg), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
|
||||
|
||||
@@ -44,15 +44,12 @@ Then use `nmake` to build:
|
||||
|
||||
```cmd
|
||||
set "PGROOT=C:\Program Files\PostgreSQL\16"
|
||||
cd %TEMP%
|
||||
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.6.1 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
|
||||
@@ -413,51 +410,13 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python
|
||||
|
||||
## Performance
|
||||
|
||||
### Tuning
|
||||
|
||||
Use a tool like [PgTune](https://pgtune.leopard.in.ua/) to set initial values for Postgres server parameters. For instance, `shared_buffers` should typically be 25% of the server’s memory. You can find the config file with:
|
||||
|
||||
```sql
|
||||
SHOW config_file;
|
||||
```
|
||||
|
||||
And check individual settings with:
|
||||
|
||||
```sql
|
||||
SHOW shared_buffers;
|
||||
```
|
||||
|
||||
Be sure to restart Postgres for changes to take effect.
|
||||
|
||||
### Loading
|
||||
|
||||
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py)).
|
||||
|
||||
```sql
|
||||
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
|
||||
```
|
||||
|
||||
Add any indexes *after* loading the initial data for best performance.
|
||||
|
||||
### Indexing
|
||||
|
||||
See index build time for [HNSW](#index-build-time) and [IVFFlat](#index-build-time-1).
|
||||
|
||||
In production environments, create indexes concurrently to avoid blocking writes.
|
||||
|
||||
```sql
|
||||
CREATE INDEX CONCURRENTLY ...
|
||||
```
|
||||
|
||||
### Querying
|
||||
|
||||
Use `EXPLAIN ANALYZE` to debug performance.
|
||||
|
||||
```sql
|
||||
EXPLAIN ANALYZE SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
|
||||
```
|
||||
|
||||
#### Exact Search
|
||||
### Exact Search
|
||||
|
||||
To speed up queries without an index, increase `max_parallel_workers_per_gather`.
|
||||
|
||||
@@ -471,7 +430,7 @@ If vectors are normalized to length 1 (like [OpenAI embeddings](https://platform
|
||||
SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5;
|
||||
```
|
||||
|
||||
#### Approximate Search
|
||||
### Approximate Search
|
||||
|
||||
To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
|
||||
|
||||
@@ -479,7 +438,7 @@ 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.
|
||||
|
||||
@@ -488,41 +447,6 @@ 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)).
|
||||
|
||||
## 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.
|
||||
@@ -616,18 +540,6 @@ and query with:
|
||||
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
|
||||
```
|
||||
|
||||
#### Are binary vectors supported?
|
||||
|
||||
You can store binary vectors and perform exact nearest neighbor search by Hamming distance in Postgres without an extension ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py)).
|
||||
|
||||
```tsql
|
||||
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
|
||||
INSERT INTO items (embedding) VALUES (B'000'), (B'111');
|
||||
SELECT * FROM items ORDER BY bit_count(embedding # B'101') LIMIT 5;
|
||||
```
|
||||
|
||||
Indexing is not currently supported.
|
||||
|
||||
#### Do indexes need to fit into memory?
|
||||
|
||||
No, but like other index types, you’ll likely see better performance if they do. You can get the size of an index with:
|
||||
@@ -640,17 +552,7 @@ SELECT pg_size_pretty(pg_relation_size('index_name'));
|
||||
|
||||
#### Why isn’t a query using an index?
|
||||
|
||||
The query needs to have an `ORDER BY` and `LIMIT`, and the `ORDER BY` must be the result of a distance operator, not an expression.
|
||||
|
||||
```sql
|
||||
-- index
|
||||
ORDER BY embedding <=> '[3,1,2]' LIMIT 5;
|
||||
|
||||
-- no index
|
||||
ORDER BY 1 - (embedding <=> '[3,1,2]') DESC LIMIT 5;
|
||||
```
|
||||
|
||||
You can encourage the planner to use an index for a query with:
|
||||
The cost estimation in pgvector < 0.4.3 does not always work well with the planner. You can encourage the planner to use an index for a query with:
|
||||
|
||||
```sql
|
||||
BEGIN;
|
||||
@@ -683,8 +585,6 @@ ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
|
||||
|
||||
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.
|
||||
@@ -695,13 +595,11 @@ 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
|
||||
|
||||
@@ -725,14 +623,14 @@ l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
|
||||
vector_dims(vector) → integer | number of dimensions |
|
||||
vector_norm(vector) → double precision | Euclidean norm |
|
||||
|
||||
### Vector Aggregate Functions
|
||||
### Aggregate Functions
|
||||
|
||||
Function | Description | Added
|
||||
--- | --- | ---
|
||||
avg(vector) → vector | average |
|
||||
sum(vector) → vector | sum | 0.5.0
|
||||
|
||||
## Installation Notes - Linux and Mac
|
||||
## Installation Notes
|
||||
|
||||
### Postgres Location
|
||||
|
||||
@@ -774,24 +672,12 @@ 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
|
||||
@@ -807,7 +693,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
|
||||
You can also build the image manually:
|
||||
|
||||
```sh
|
||||
git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.6.1 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
docker build --build-arg PG_MAJOR=16 -t myuser/pgvector .
|
||||
```
|
||||
@@ -976,12 +862,6 @@ 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
|
||||
@@ -994,6 +874,12 @@ To show memory usage:
|
||||
make clean && PG_CFLAGS="-DHNSW_MEMORY -DIVFFLAT_MEMORY" make && make install
|
||||
```
|
||||
|
||||
To enable assertions:
|
||||
|
||||
```sh
|
||||
make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
|
||||
```
|
||||
|
||||
To get k-means metrics:
|
||||
|
||||
```sh
|
||||
|
||||
@@ -1,2 +0,0 @@
|
||||
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
|
||||
\echo Use "ALTER EXTENSION vector UPDATE TO '0.6.2'" to load this file. \quit
|
||||
@@ -1,7 +1,7 @@
|
||||
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
|
||||
\echo Use "CREATE EXTENSION vector" to load this file. \quit
|
||||
|
||||
-- vector type
|
||||
-- type
|
||||
|
||||
CREATE TYPE vector;
|
||||
|
||||
@@ -29,7 +29,7 @@ CREATE TYPE vector (
|
||||
STORAGE = external
|
||||
);
|
||||
|
||||
-- vector functions
|
||||
-- functions
|
||||
|
||||
CREATE FUNCTION l2_distance(vector, vector) RETURNS float8
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
@@ -58,7 +58,7 @@ CREATE FUNCTION vector_sub(vector, vector) RETURNS vector
|
||||
CREATE FUNCTION vector_mul(vector, vector) RETURNS vector
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- vector private functions
|
||||
-- private functions
|
||||
|
||||
CREATE FUNCTION vector_lt(vector, vector) RETURNS bool
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
@@ -99,7 +99,7 @@ CREATE FUNCTION vector_avg(double precision[]) RETURNS vector
|
||||
CREATE FUNCTION vector_combine(double precision[], double precision[]) RETURNS double precision[]
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- vector aggregates
|
||||
-- aggregates
|
||||
|
||||
CREATE AGGREGATE avg(vector) (
|
||||
SFUNC = vector_accum,
|
||||
@@ -117,7 +117,7 @@ CREATE AGGREGATE sum(vector) (
|
||||
PARALLEL = SAFE
|
||||
);
|
||||
|
||||
-- vector cast functions
|
||||
-- cast functions
|
||||
|
||||
CREATE FUNCTION vector(vector, integer, boolean) RETURNS vector
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
@@ -137,7 +137,7 @@ CREATE FUNCTION array_to_vector(numeric[], integer, boolean) RETURNS vector
|
||||
CREATE FUNCTION vector_to_float4(vector, integer, boolean) RETURNS real[]
|
||||
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
|
||||
|
||||
-- vector casts
|
||||
-- casts
|
||||
|
||||
CREATE CAST (vector AS vector)
|
||||
WITH FUNCTION vector(vector, integer, boolean) AS IMPLICIT;
|
||||
@@ -157,7 +157,7 @@ CREATE CAST (double precision[] AS vector)
|
||||
CREATE CAST (numeric[] AS vector)
|
||||
WITH FUNCTION array_to_vector(numeric[], integer, boolean) AS ASSIGNMENT;
|
||||
|
||||
-- vector operators
|
||||
-- operators
|
||||
|
||||
CREATE OPERATOR <-> (
|
||||
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l2_distance,
|
||||
@@ -240,7 +240,7 @@ CREATE ACCESS METHOD hnsw TYPE INDEX HANDLER hnswhandler;
|
||||
|
||||
COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method';
|
||||
|
||||
-- vector opclasses
|
||||
-- opclasses
|
||||
|
||||
CREATE OPERATOR CLASS vector_ops
|
||||
DEFAULT FOR TYPE vector USING btree AS
|
||||
|
||||
18
src/hnsw.h
18
src/hnsw.h
@@ -55,11 +55,6 @@
|
||||
#define HNSW_UPDATE_ENTRY_GREATER 1
|
||||
#define HNSW_UPDATE_ENTRY_ALWAYS 2
|
||||
|
||||
typedef enum HnswType
|
||||
{
|
||||
HNSW_TYPE_VECTOR
|
||||
} HnswType;
|
||||
|
||||
/* Build phases */
|
||||
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
|
||||
#define PROGRESS_HNSW_PHASE_LOAD 2
|
||||
@@ -134,7 +129,7 @@ HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr)
|
||||
HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
|
||||
HnswPtrDeclare(char, DatumRelptr, DatumPtr);
|
||||
|
||||
struct HnswElementData
|
||||
typedef struct HnswElementData
|
||||
{
|
||||
HnswElementPtr next;
|
||||
ItemPointerData heaptids[HNSW_HEAPTIDS];
|
||||
@@ -149,7 +144,7 @@ struct HnswElementData
|
||||
BlockNumber neighborPage;
|
||||
DatumPtr value;
|
||||
LWLock lock;
|
||||
};
|
||||
} HnswElementData;
|
||||
|
||||
typedef HnswElementData * HnswElement;
|
||||
|
||||
@@ -160,12 +155,12 @@ typedef struct HnswCandidate
|
||||
bool closer;
|
||||
} HnswCandidate;
|
||||
|
||||
struct HnswNeighborArray
|
||||
typedef struct HnswNeighborArray
|
||||
{
|
||||
int length;
|
||||
bool closerSet;
|
||||
HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
|
||||
};
|
||||
} HnswNeighborArray;
|
||||
|
||||
typedef struct HnswPairingHeapNode
|
||||
{
|
||||
@@ -247,7 +242,6 @@ typedef struct HnswBuildState
|
||||
Relation index;
|
||||
IndexInfo *indexInfo;
|
||||
ForkNumber forkNum;
|
||||
HnswType type;
|
||||
|
||||
/* Settings */
|
||||
int dimensions;
|
||||
@@ -268,6 +262,7 @@ typedef struct HnswBuildState
|
||||
HnswGraph *graph;
|
||||
double ml;
|
||||
int maxLevel;
|
||||
Vector *normvec;
|
||||
|
||||
/* Memory */
|
||||
MemoryContext graphCtx;
|
||||
@@ -372,8 +367,7 @@ typedef struct HnswVacuumState
|
||||
int HnswGetM(Relation index);
|
||||
int HnswGetEfConstruction(Relation index);
|
||||
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
|
||||
HnswType HnswGetType(Relation index);
|
||||
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type);
|
||||
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
|
||||
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
|
||||
void HnswInitPage(Buffer buf, Page page);
|
||||
void HnswInit(void);
|
||||
|
||||
@@ -436,7 +436,7 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
|
||||
int m = buildstate->m;
|
||||
char *base = buildstate->hnswarea;
|
||||
|
||||
/* Wait if another process needs exclusive lock on entry lock */
|
||||
/* Wait if another process needs exclusive lock */
|
||||
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
|
||||
LWLockRelease(entryWaitLock);
|
||||
|
||||
@@ -450,7 +450,7 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
|
||||
/* Release shared lock */
|
||||
LWLockRelease(entryLock);
|
||||
|
||||
/* Tell other processes to wait and get exclusive lock */
|
||||
/* Get exclusive lock */
|
||||
LWLockAcquire(entryWaitLock, LW_EXCLUSIVE);
|
||||
LWLockAcquire(entryLock, LW_EXCLUSIVE);
|
||||
LWLockRelease(entryWaitLock);
|
||||
@@ -489,7 +489,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
|
||||
/* Normalize if needed */
|
||||
if (buildstate->normprocinfo != NULL)
|
||||
{
|
||||
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->type))
|
||||
if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
|
||||
return false;
|
||||
}
|
||||
|
||||
@@ -671,13 +671,10 @@ 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);
|
||||
@@ -687,8 +684,8 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
|
||||
if (buildstate->dimensions < 0)
|
||||
elog(ERROR, "column does not have dimensions");
|
||||
|
||||
if (buildstate->dimensions > maxDimensions)
|
||||
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", maxDimensions);
|
||||
if (buildstate->dimensions > HNSW_MAX_DIM)
|
||||
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", HNSW_MAX_DIM);
|
||||
|
||||
if (buildstate->efConstruction < 2 * buildstate->m)
|
||||
elog(ERROR, "ef_construction must be greater than or equal to 2 * m");
|
||||
@@ -706,6 +703,9 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
|
||||
buildstate->ml = HnswGetMl(buildstate->m);
|
||||
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
|
||||
|
||||
/* Reuse for each tuple */
|
||||
buildstate->normvec = InitVector(buildstate->dimensions);
|
||||
|
||||
buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext,
|
||||
"Hnsw build graph context",
|
||||
#if PG_VERSION_NUM >= 150000
|
||||
@@ -729,6 +729,7 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
|
||||
static void
|
||||
FreeBuildState(HnswBuildState * buildstate)
|
||||
{
|
||||
pfree(buildstate->normvec);
|
||||
MemoryContextDelete(buildstate->graphCtx);
|
||||
MemoryContextDelete(buildstate->tmpCtx);
|
||||
}
|
||||
|
||||
@@ -622,7 +622,7 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
|
||||
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
|
||||
if (normprocinfo != NULL)
|
||||
{
|
||||
if (!HnswNormValue(normprocinfo, collation, &value, HnswGetType(index)))
|
||||
if (!HnswNormValue(normprocinfo, collation, &value, NULL))
|
||||
return;
|
||||
}
|
||||
|
||||
|
||||
@@ -40,6 +40,29 @@ GetScanItems(IndexScanDesc scan, Datum q)
|
||||
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
|
||||
}
|
||||
|
||||
/*
|
||||
* Get dimensions from metapage
|
||||
*/
|
||||
static int
|
||||
GetDimensions(Relation index)
|
||||
{
|
||||
Buffer buf;
|
||||
Page page;
|
||||
HnswMetaPage metap;
|
||||
int dimensions;
|
||||
|
||||
buf = ReadBuffer(index, HNSW_METAPAGE_BLKNO);
|
||||
LockBuffer(buf, BUFFER_LOCK_SHARE);
|
||||
page = BufferGetPage(buf);
|
||||
metap = HnswPageGetMeta(page);
|
||||
|
||||
dimensions = metap->dimensions;
|
||||
|
||||
UnlockReleaseBuffer(buf);
|
||||
|
||||
return dimensions;
|
||||
}
|
||||
|
||||
/*
|
||||
* Get scan value
|
||||
*/
|
||||
@@ -50,7 +73,7 @@ GetScanValue(IndexScanDesc scan)
|
||||
Datum value;
|
||||
|
||||
if (scan->orderByData->sk_flags & SK_ISNULL)
|
||||
value = PointerGetDatum(NULL);
|
||||
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
|
||||
else
|
||||
{
|
||||
value = scan->orderByData->sk_argument;
|
||||
@@ -61,7 +84,7 @@ GetScanValue(IndexScanDesc scan)
|
||||
|
||||
/* Fine if normalization fails */
|
||||
if (so->normprocinfo != NULL)
|
||||
HnswNormValue(so->normprocinfo, so->collation, &value, HnswGetType(scan->indexRelation));
|
||||
HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
|
||||
}
|
||||
|
||||
return value;
|
||||
|
||||
@@ -149,15 +149,6 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
|
||||
return index_getprocinfo(index, 1, procnum);
|
||||
}
|
||||
|
||||
/*
|
||||
* Get vector type
|
||||
*/
|
||||
HnswType
|
||||
HnswGetType(Relation index)
|
||||
{
|
||||
return HNSW_TYPE_VECTOR;
|
||||
}
|
||||
|
||||
/*
|
||||
* Divide by the norm
|
||||
*
|
||||
@@ -167,25 +158,21 @@ HnswGetType(Relation index)
|
||||
* if it's different than the original value
|
||||
*/
|
||||
bool
|
||||
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type)
|
||||
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
|
||||
{
|
||||
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
|
||||
|
||||
if (norm > 0)
|
||||
{
|
||||
/* TODO Remove vector-specific code */
|
||||
if (type == HNSW_TYPE_VECTOR)
|
||||
{
|
||||
Vector *v = DatumGetVector(*value);
|
||||
Vector *result = InitVector(v->dim);
|
||||
Vector *v = DatumGetVector(*value);
|
||||
|
||||
for (int i = 0; i < v->dim; i++)
|
||||
result->x[i] = v->x[i] / norm;
|
||||
if (result == NULL)
|
||||
result = InitVector(v->dim);
|
||||
|
||||
*value = PointerGetDatum(result);
|
||||
}
|
||||
else
|
||||
elog(ERROR, "Unsupported type");
|
||||
for (int i = 0; i < v->dim; i++)
|
||||
result->x[i] = v->x[i] / norm;
|
||||
|
||||
*value = PointerGetDatum(result);
|
||||
|
||||
return true;
|
||||
}
|
||||
@@ -588,12 +575,7 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
|
||||
|
||||
/* Calculate distance */
|
||||
if (distance != NULL)
|
||||
{
|
||||
if (DatumGetPointer(*q) == NULL)
|
||||
*distance = 0;
|
||||
else
|
||||
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
|
||||
}
|
||||
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
|
||||
|
||||
UnlockReleaseBuffer(buf);
|
||||
}
|
||||
|
||||
@@ -57,7 +57,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
|
||||
*/
|
||||
if (buildstate->kmeansnormprocinfo != NULL)
|
||||
{
|
||||
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value))
|
||||
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->normvec))
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -105,7 +105,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
|
||||
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
|
||||
|
||||
/* Add sample */
|
||||
AddSample(values, buildstate);
|
||||
AddSample(values, state);
|
||||
|
||||
/* Reset memory context */
|
||||
MemoryContextSwitchTo(oldCtx);
|
||||
@@ -153,7 +153,7 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
|
||||
/* Normalize if needed */
|
||||
if (buildstate->normprocinfo != NULL)
|
||||
{
|
||||
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value))
|
||||
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
|
||||
return;
|
||||
}
|
||||
|
||||
@@ -356,6 +356,9 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
|
||||
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions);
|
||||
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
|
||||
|
||||
/* Reuse for each tuple */
|
||||
buildstate->normvec = InitVector(buildstate->dimensions);
|
||||
|
||||
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
|
||||
"Ivfflat build temporary context",
|
||||
ALLOCSET_DEFAULT_SIZES);
|
||||
@@ -377,6 +380,7 @@ FreeBuildState(IvfflatBuildState * buildstate)
|
||||
{
|
||||
VectorArrayFree(buildstate->centers);
|
||||
pfree(buildstate->listInfo);
|
||||
pfree(buildstate->normvec);
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
pfree(buildstate->listSums);
|
||||
|
||||
@@ -172,6 +172,7 @@ typedef struct IvfflatBuildState
|
||||
VectorArray samples;
|
||||
VectorArray centers;
|
||||
ListInfo *listInfo;
|
||||
Vector *normvec;
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
double inertia;
|
||||
@@ -266,7 +267,7 @@ void VectorArrayFree(VectorArray arr);
|
||||
void PrintVectorArray(char *msg, VectorArray arr);
|
||||
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
|
||||
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
|
||||
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value);
|
||||
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
|
||||
int IvfflatGetLists(Relation index);
|
||||
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
|
||||
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);
|
||||
|
||||
@@ -85,7 +85,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
|
||||
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
|
||||
if (normprocinfo != NULL)
|
||||
{
|
||||
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value))
|
||||
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
|
||||
return;
|
||||
}
|
||||
|
||||
|
||||
@@ -293,7 +293,7 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
|
||||
/* Fine if normalization fails */
|
||||
if (so->normprocinfo != NULL)
|
||||
IvfflatNormValue(so->normprocinfo, so->collation, &value);
|
||||
IvfflatNormValue(so->normprocinfo, so->collation, &value, NULL);
|
||||
}
|
||||
|
||||
IvfflatBench("GetScanLists", GetScanLists(scan, value));
|
||||
|
||||
@@ -75,14 +75,16 @@ IvfflatOptionalProcInfo(Relation index, uint16 procnum)
|
||||
* if it's different than the original value
|
||||
*/
|
||||
bool
|
||||
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value)
|
||||
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
|
||||
{
|
||||
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
|
||||
|
||||
if (norm > 0)
|
||||
{
|
||||
Vector *v = DatumGetVector(*value);
|
||||
Vector *result = InitVector(v->dim);
|
||||
|
||||
if (result == NULL)
|
||||
result = InitVector(v->dim);
|
||||
|
||||
for (int i = 0; i < v->dim; i++)
|
||||
result->x[i] = v->x[i] / norm;
|
||||
|
||||
16
src/vector.c
16
src/vector.c
@@ -197,8 +197,6 @@ vector_in(PG_FUNCTION_ARGS)
|
||||
|
||||
while (pt != NULL && *stringEnd != ']')
|
||||
{
|
||||
float val;
|
||||
|
||||
if (dim == VECTOR_MAX_DIM)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
|
||||
@@ -214,23 +212,15 @@ vector_in(PG_FUNCTION_ARGS)
|
||||
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
|
||||
|
||||
/* Use strtof like float4in to avoid a double-rounding problem */
|
||||
errno = 0;
|
||||
val = strtof(pt, &stringEnd);
|
||||
x[dim] = strtof(pt, &stringEnd);
|
||||
CheckElement(x[dim]);
|
||||
dim++;
|
||||
|
||||
if (stringEnd == pt)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
|
||||
errmsg("invalid input syntax for type vector: \"%s\"", lit)));
|
||||
|
||||
/* Check for range error like float4in */
|
||||
if (errno == ERANGE && (val == 0 || isinf(val)))
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
|
||||
errmsg("\"%s\" is out of range for type vector", pt)));
|
||||
|
||||
CheckElement(val);
|
||||
x[dim++] = val;
|
||||
|
||||
while (vector_isspace(*stringEnd))
|
||||
stringEnd++;
|
||||
|
||||
|
||||
@@ -12,11 +12,14 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
[0,0,0]
|
||||
(4 rows)
|
||||
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
|
||||
count
|
||||
-------
|
||||
4
|
||||
(1 row)
|
||||
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
|
||||
val
|
||||
---------
|
||||
[0,0,0]
|
||||
[1,1,1]
|
||||
[1,2,3]
|
||||
[1,2,4]
|
||||
(4 rows)
|
||||
|
||||
SELECT COUNT(*) FROM t;
|
||||
count
|
||||
|
||||
@@ -63,21 +63,9 @@ SELECT '[1.5e-38,-1.5e-38]'::vector;
|
||||
(1 row)
|
||||
|
||||
SELECT '[4e38,1]'::vector;
|
||||
ERROR: "4e38" is out of range for type vector
|
||||
ERROR: infinite value not allowed in vector
|
||||
LINE 1: SELECT '[4e38,1]'::vector;
|
||||
^
|
||||
SELECT '[-4e38,1]'::vector;
|
||||
ERROR: "-4e38" is out of range for type vector
|
||||
LINE 1: SELECT '[-4e38,1]'::vector;
|
||||
^
|
||||
SELECT '[1e-46,1]'::vector;
|
||||
ERROR: "1e-46" is out of range for type vector
|
||||
LINE 1: SELECT '[1e-46,1]'::vector;
|
||||
^
|
||||
SELECT '[-1e-46,1]'::vector;
|
||||
ERROR: "-1e-46" is out of range for type vector
|
||||
LINE 1: SELECT '[-1e-46,1]'::vector;
|
||||
^
|
||||
SELECT '[1,2,3'::vector;
|
||||
ERROR: malformed vector literal: "[1,2,3"
|
||||
LINE 1: SELECT '[1,2,3'::vector;
|
||||
@@ -128,30 +116,8 @@ SELECT '[1, ,3]'::vector;
|
||||
ERROR: invalid input syntax for type vector: "[1, ,3]"
|
||||
LINE 1: SELECT '[1, ,3]'::vector;
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(3);
|
||||
vector
|
||||
---------
|
||||
[1,2,3]
|
||||
(1 row)
|
||||
|
||||
SELECT '[1,2,3]'::vector(2);
|
||||
ERROR: expected 2 dimensions, not 3
|
||||
SELECT '[1,2,3]'::vector(3, 2);
|
||||
ERROR: invalid type modifier
|
||||
LINE 1: SELECT '[1,2,3]'::vector(3, 2);
|
||||
^
|
||||
SELECT '[1,2,3]'::vector('a');
|
||||
ERROR: invalid input syntax for type integer: "a"
|
||||
LINE 1: SELECT '[1,2,3]'::vector('a');
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(0);
|
||||
ERROR: dimensions for type vector must be at least 1
|
||||
LINE 1: SELECT '[1,2,3]'::vector(0);
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(16001);
|
||||
ERROR: dimensions for type vector cannot exceed 16000
|
||||
LINE 1: SELECT '[1,2,3]'::vector(16001);
|
||||
^
|
||||
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
|
||||
unnest
|
||||
---------
|
||||
|
||||
@@ -7,7 +7,7 @@ CREATE INDEX ON t USING hnsw (val vector_l2_ops);
|
||||
INSERT INTO t (val) VALUES ('[1,2,4]');
|
||||
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
|
||||
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
|
||||
SELECT COUNT(*) FROM t;
|
||||
|
||||
TRUNCATE t;
|
||||
|
||||
@@ -11,9 +11,6 @@ SELECT '[1.5e38,-1.5e38]'::vector;
|
||||
SELECT '[1.5e+38,-1.5e+38]'::vector;
|
||||
SELECT '[1.5e-38,-1.5e-38]'::vector;
|
||||
SELECT '[4e38,1]'::vector;
|
||||
SELECT '[-4e38,1]'::vector;
|
||||
SELECT '[1e-46,1]'::vector;
|
||||
SELECT '[-1e-46,1]'::vector;
|
||||
SELECT '[1,2,3'::vector;
|
||||
SELECT '[1,2,3]9'::vector;
|
||||
SELECT '1,2,3'::vector;
|
||||
@@ -25,13 +22,7 @@ SELECT '[1,]'::vector;
|
||||
SELECT '[1a]'::vector;
|
||||
SELECT '[1,,3]'::vector;
|
||||
SELECT '[1, ,3]'::vector;
|
||||
|
||||
SELECT '[1,2,3]'::vector(3);
|
||||
SELECT '[1,2,3]'::vector(2);
|
||||
SELECT '[1,2,3]'::vector(3, 2);
|
||||
SELECT '[1,2,3]'::vector('a');
|
||||
SELECT '[1,2,3]'::vector(0);
|
||||
SELECT '[1,2,3]'::vector(16001);
|
||||
|
||||
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
|
||||
SELECT '{"[1,2,3]"}'::vector(2)[];
|
||||
|
||||
@@ -86,7 +86,7 @@ foreach (@queries)
|
||||
push(@expected, $res);
|
||||
}
|
||||
|
||||
test_recall(0.19, $limit, "before vacuum");
|
||||
test_recall(0.20, $limit, "before vacuum");
|
||||
test_recall(0.95, 100, "before vacuum");
|
||||
|
||||
# TODO Test concurrent inserts with vacuum
|
||||
|
||||
@@ -1,4 +1,4 @@
|
||||
comment = 'vector data type and ivfflat and hnsw access methods'
|
||||
default_version = '0.6.2'
|
||||
default_version = '0.6.1'
|
||||
module_pathname = '$libdir/vector'
|
||||
relocatable = true
|
||||
|
||||
Reference in New Issue
Block a user