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...

52 Commits

Author SHA1 Message Date
Andrew Kane
47852e8d15 Started half indexing 2023-12-03 15:12:50 -08:00
Andrew Kane
422667f6c6 Added half type 2023-12-03 13:01:47 -08:00
Andrew Kane
4d6739a7af Added Lisp to readme [skip ci] 2023-12-03 10:58:54 -08:00
Andrew Kane
ff744214d0 Added Visual Basic to readme [skip ci] 2023-12-03 00:25:07 -08:00
Andrew Kane
7ca9298163 Updated badge [skip ci] 2023-12-01 15:36:49 -08:00
Andrew Kane
ff3bffd9a8 Moved FAQ [skip ci] 2023-11-29 22:09:09 -08:00
Andrew Kane
014753eb9c Added FAQ about memory [skip ci] 2023-11-29 22:02:27 -08:00
Andrew Kane
6763661d3d Added OCaml to readme [skip ci] 2023-11-28 21:42:30 -08:00
Andrew Kane
d287921d15 Added F# to readme [skip ci] 2023-11-28 01:22:12 -08:00
Andrew Kane
5b12ae8225 Added note about ef_construction [skip ci] 2023-11-16 18:53:48 -08:00
Japin Li
4549e8aeb1 Fix coredump about HnswFreeElement() (#357)
The HnswInitElement() allocate an element with not initialize value
filed, which may has garbage that lead HnswFreeElement() free an
invalid pointer.
2023-11-15 16:19:59 -08:00
Andrew Kane
3263b350f5 Updated HnswLoadElementFromTuple to be less vector-specific 2023-11-11 21:14:12 -08:00
Andrew Kane
dfee5d4045 Added support for on-disk parallel index builds for HNSW 2023-11-11 19:29:45 -08:00
Andrew Kane
69a2ce0d43 Use datumIsEqual to compare 2023-11-10 10:46:48 -08:00
Andrew Kane
c5e8c46b80 Switched from VECTOR_SIZE to VARSIZE_ANY [skip ci] 2023-11-09 19:41:38 -08:00
Andrew Kane
94f7304ccd Keep vector for now to be overly cautious about packing [skip ci] 2023-11-09 18:43:55 -08:00
Andrew Kane
d078db3d25 Switched HnswElementTuple to generic data and zero full section 2023-11-09 18:28:25 -08:00
Andrew Kane
fbb904ae2f Use pointer for VARSIZE_ANY 2023-11-09 17:50:28 -08:00
Andrew Kane
3cf6f62900 Switched to datum for HnswElement 2023-11-09 17:35:39 -08:00
Andrew Kane
2a69e22ca4 Switched from VECTOR_SIZE to VARSIZE_ANY where possible (less vector-specific) 2023-11-09 17:16:43 -08:00
Andrew Kane
84e073888c Removed vector-specific code from HNSW_ELEMENT_TUPLE_SIZE [skip ci] 2023-11-09 16:57:01 -08:00
Andrew Kane
81a62d55d1 Switched from HNSW_ELEMENT_TUPLE_SIZE to ItemIdGetLength where possible (less vector-specific) 2023-11-09 16:32:00 -08:00
Andrew Kane
3f3463bde5 Improved memory calculation for HNSW and removed vector-specific code 2023-11-09 16:21:26 -08:00
Andrew Kane
a01a72d812 Updated comment [skip ci] 2023-11-05 08:42:06 -08:00
Andrew Kane
0c2fc18a80 Updated comment [skip ci] 2023-11-05 08:40:21 -08:00
Andrew Kane
e860042d3c Improved variable name [skip ci] 2023-11-05 08:35:54 -08:00
Andrew Kane
5986862bd2 Added note about check constraint [skip ci] 2023-11-04 15:01:37 -07:00
Andrew Kane
5d24f5d09a Improved header installation on Windows 2023-11-04 11:16:40 -07:00
Andrew Kane
7c43b0d8ee Updated example [skip ci] 2023-11-03 23:54:50 -07:00
Andrew Kane
7be40036f4 Updated readme [skip ci] 2023-11-03 23:46:23 -07:00
Andrew Kane
9b5a1a69db Updated readme [skip ci] 2023-11-03 23:43:47 -07:00
Andrew Kane
04b96506f5 Added info on storing vectors with more precision [skip ci] 2023-11-03 20:14:28 -07:00
Andrew Kane
35cd7b63cb Updated readme [skip ci] 2023-11-03 17:02:30 -07:00
Andrew Kane
b5416d6f10 Updated readme [skip ci] 2023-11-03 16:48:57 -07:00
Andrew Kane
f361bf2704 Improved docs on indexing vectors with different dimensions [skip ci] 2023-11-03 16:42:14 -07:00
Andrew Kane
3d8c1921aa Improved upgrading docs - #339 [skip ci] 2023-11-03 16:15:06 -07:00
Andrew Kane
154207bc17 Added info on columns with different dimensions [skip ci] 2023-11-03 16:02:00 -07:00
Andrew Kane
8e507f3bf5 Free remaining allocation from deconstruct_array - #332 2023-11-02 21:20:21 -07:00
Andrew Kane
e115773a55 Removed unneeded allocation 2023-11-02 21:16:06 -07:00
Andrew Kane
9333bef046 Added link to setup-pgvector [skip ci] 2023-11-02 13:22:19 -07:00
Andrew Kane
4851e47d9f Added Reciprocal Rank Fusion example to readme [skip ci] 2023-11-01 13:20:49 -07:00
Andrew Kane
12aecfb4f5 Added Nim and Zig to readme [skip ci] 2023-10-31 02:26:18 -07:00
Andrew Kane
800697fb14 Updated column alias [skip ci] 2023-10-29 16:47:55 -07:00
Andrew Kane
de1f2b09dd Improved indexing progress queries [skip ci] 2023-10-29 16:41:39 -07:00
Andrew Kane
bcccb7f5a5 Improved docs for indexing progress - closes #320 and closes #321 [skip ci] 2023-10-29 16:13:12 -07:00
Andrew Kane
bec3d30d68 Added TypeScript to readme [skip ci] 2023-10-29 12:49:01 -07:00
Andrew Kane
588de60445 Added Groovy to readme [skip ci] 2023-10-29 12:39:53 -07:00
Andrew Kane
c599f92b52 Updated readme [skip ci] 2023-10-27 13:22:37 -07:00
Andrew Kane
2a17b335da Added Kotlin to readme [skip ci] 2023-10-26 12:25:58 -07:00
Andrew Kane
6ede6ac301 Added link to pgvector-c [skip ci] 2023-10-26 00:30:06 -07:00
Andrew Kane
3f49b95f01 Added Postgres 17 to CI [skip ci] 2023-10-19 00:37:24 -07:00
Andrew Kane
ef1bea7163 Updated checkout action [skip ci] 2023-10-19 00:36:53 -07:00
24 changed files with 1847 additions and 147 deletions

View File

@@ -8,6 +8,8 @@ jobs:
fail-fast: false
matrix:
include:
- postgres: 17
os: ubuntu-22.04
- postgres: 16
os: ubuntu-22.04
- postgres: 15
@@ -18,10 +20,8 @@ jobs:
os: ubuntu-20.04
- postgres: 12
os: ubuntu-20.04
- postgres: 11
os: ubuntu-20.04
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
@@ -43,7 +43,7 @@ jobs:
runs-on: macos-latest
if: ${{ !startsWith(github.ref_name, 'windows') }}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14
@@ -65,7 +65,7 @@ jobs:
runs-on: windows-latest
if: ${{ !startsWith(github.ref_name, 'mac') }}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14

View File

@@ -1,3 +1,7 @@
## 0.5.2 (unreleased)
- Added support for on-disk parallel index builds for HNSW
## 0.5.1 (2023-10-10)
- Improved performance of HNSW index builds

View File

@@ -3,8 +3,8 @@ EXTVERSION = 0.5.1
MODULE_big = vector
DATA = $(wildcard sql/*--*.sql)
OBJS = src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
HEADERS = src/vector.h
OBJS = src/half.o src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
HEADERS = src/half.h src/vector.h
TESTS = $(wildcard test/sql/*.sql)
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))

View File

@@ -1,8 +1,8 @@
EXTENSION = vector
EXTVERSION = 0.5.1
OBJS = src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
HEADERS = src\vector.h
OBJS = src\half.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
HEADERS = src\half.h src\vector.h
REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
@@ -56,7 +56,7 @@ install:
copy $(EXTENSION).control "$(SHAREDIR)\extension"
copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
mkdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
copy $(HEADERS) "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
for %f in ($(HEADERS)) do copy %f "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
installcheck:
"$(BINDIR)\pg_regress" --bindir="$(BINDIR)" $(REGRESS_OPTS) $(REGRESS)

111
README.md
View File

@@ -10,7 +10,7 @@ Store your vectors with the rest of your data. Supports:
Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recovery, JOINs, and all of the other [great features](https://www.postgresql.org/about/) of Postgres
[![Build Status](https://github.com/pgvector/pgvector/workflows/build/badge.svg?branch=master)](https://github.com/pgvector/pgvector/actions)
[![Build Status](https://github.com/pgvector/pgvector/actions/workflows/build.yml/badge.svg)](https://github.com/pgvector/pgvector/actions)
## Installation
@@ -26,7 +26,7 @@ make install # may need sudo
See the [installation notes](#installation-notes) if you run into issues
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres)
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
## Getting Started
@@ -215,6 +215,23 @@ SELECT ...
COMMIT;
```
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases for IVFFlat are:
1. `initializing`
2. `performing k-means`
3. `assigning tuples`
4. `loading tuples`
Note: `%` is only populated during the `loading tuples` phase
## HNSW
An HNSW index creates a multilayer graph. It has slower build times and uses more memory than IVFFlat, but has better query performance (in terms of speed-recall tradeoff). Theres no training step like IVFFlat, so the index can be created without any data in the table.
@@ -252,6 +269,8 @@ Specify HNSW parameters
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops) WITH (m = 16, ef_construction = 64);
```
A higher value of `ef_construction` provides better recall at the cost of index build time / insert speed.
### Query Options
Specify the size of the dynamic candidate list for search (40 by default)
@@ -271,22 +290,18 @@ SELECT ...
COMMIT;
```
## Indexing Progress
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, tuples_done, tuples_total FROM pg_stat_progress_create_index;
SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases are:
The phases for HNSW are:
1. `initializing`
2. `performing k-means` - IVFFlat only
3. `assigning tuples` - IVFFlat only
4. `loading tuples`
Note: `tuples_done` and `tuples_total` are only populated during the `loading tuples` phase
2. `loading tuples`
## Filtering
@@ -317,13 +332,15 @@ CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(cate
## Hybrid Search
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search ([Python example](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search.py)).
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search.
```sql
SELECT id, content FROM items, plainto_tsquery('hello search') query
WHERE textsearch @@ query ORDER BY ts_rank_cd(textsearch, query) DESC LIMIT 5;
```
You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search_rrf.py) or a [cross-encoder](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search.py) to combine results.
## Performance
Use `EXPLAIN ANALYZE` to debug performance.
@@ -360,17 +377,21 @@ Use pgvector from any language with a Postgres client. You can even generate and
Language | Libraries / Examples
--- | ---
C | [pgvector-c](https://github.com/pgvector/pgvector-c)
C++ | [pgvector-cpp](https://github.com/pgvector/pgvector-cpp)
C# | [pgvector-dotnet](https://github.com/pgvector/pgvector-dotnet)
C#, F#, Visual Basic | [pgvector-dotnet](https://github.com/pgvector/pgvector-dotnet)
Crystal | [pgvector-crystal](https://github.com/pgvector/pgvector-crystal)
Dart | [pgvector-dart](https://github.com/pgvector/pgvector-dart)
Elixir | [pgvector-elixir](https://github.com/pgvector/pgvector-elixir)
Go | [pgvector-go](https://github.com/pgvector/pgvector-go)
Haskell | [pgvector-haskell](https://github.com/pgvector/pgvector-haskell)
Java, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
Java, Kotlin, Groovy, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
JavaScript, TypeScript | [pgvector-node](https://github.com/pgvector/pgvector-node)
Julia | [pgvector-julia](https://github.com/pgvector/pgvector-julia)
Lisp | [pgvector-lisp](https://github.com/pgvector/pgvector-lisp)
Lua | [pgvector-lua](https://github.com/pgvector/pgvector-lua)
Node.js | [pgvector-node](https://github.com/pgvector/pgvector-node)
Nim | [pgvector-nim](https://github.com/pgvector/pgvector-nim)
OCaml | [pgvector-ocaml](https://github.com/pgvector/pgvector-ocaml)
Perl | [pgvector-perl](https://github.com/pgvector/pgvector-perl)
PHP | [pgvector-php](https://github.com/pgvector/pgvector-php)
Python | [pgvector-python](https://github.com/pgvector/pgvector-python)
@@ -378,6 +399,7 @@ R | [pgvector-r](https://github.com/pgvector/pgvector-r)
Ruby | [pgvector-ruby](https://github.com/pgvector/pgvector-ruby), [Neighbor](https://github.com/ankane/neighbor)
Rust | [pgvector-rust](https://github.com/pgvector/pgvector-rust)
Swift | [pgvector-swift](https://github.com/pgvector/pgvector-swift)
Zig | [pgvector-zig](https://github.com/pgvector/pgvector-zig)
## Frequently Asked Questions
@@ -393,6 +415,63 @@ Yes, pgvector uses the write-ahead log (WAL), which allows for replication and p
Youll need to use [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction) at the moment.
#### Can I store vectors with different dimensions in the same column?
You can use `vector` as the type (instead of `vector(3)`).
```sql
CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id));
```
However, you can only create indexes on rows with the same number of dimensions (using [expression](https://www.postgresql.org/docs/current/indexes-expressional.html) and [partial](https://www.postgresql.org/docs/current/indexes-partial.html) indexing):
```sql
CREATE INDEX ON embeddings USING hnsw ((embedding::vector(3)) vector_l2_ops) WHERE (model_id = 123);
```
and query with:
```sql
SELECT * FROM embeddings WHERE model_id = 123 ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
```
#### Can I store vectors with more precision?
You can use the `double precision[]` or `numeric[]` type to store vectors with more precision.
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding double precision[]);
-- use {} instead of [] for Postgres arrays
INSERT INTO items (embedding) VALUES ('{1,2,3}'), ('{4,5,6}');
```
Optionally, add a [check constraint](https://www.postgresql.org/docs/current/ddl-constraints.html) to ensure data can be converted to the `vector` type and has the expected dimensions.
```sql
ALTER TABLE items ADD CHECK (vector_dims(embedding::vector) = 3);
```
Use [expression indexing](https://www.postgresql.org/docs/current/indexes-expressional.html) to index (at a lower precision):
```sql
CREATE INDEX ON items USING hnsw ((embedding::vector(3)) vector_l2_ops);
```
and query with:
```sql
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
```
#### 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:
```sql
SELECT pg_size_pretty(pg_relation_size('index_name'));
```
## Troubleshooting
#### Why isnt a query using an index?
@@ -406,6 +485,8 @@ SELECT ...
COMMIT;
```
Also, if the table is small, a table scan may be faster.
#### Why isnt a query using a parallel table scan?
The planner doesnt consider [out-of-line storage](https://www.postgresql.org/docs/current/storage-toast.html) in cost estimates, which can make a serial scan look cheaper. You can reduce the cost of a parallel scan for a query with:
@@ -595,7 +676,7 @@ pgvector is available on [these providers](https://github.com/pgvector/pgvector/
## Upgrading
Install the latest version. Then in each database you want to upgrade, run:
[Install](#installation) the latest version (use the same method as the original installation). Then in each database you want to upgrade, run:
```sql
ALTER EXTENSION vector UPDATE;

View File

@@ -0,0 +1,82 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.6.0'" to load this file. \quit
CREATE TYPE half;
CREATE FUNCTION half_in(cstring, oid, integer) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION half_out(half) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION half_recv(internal, oid, integer) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION half_send(half) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE half (
INPUT = half_in,
OUTPUT = half_out,
RECEIVE = half_recv,
SEND = half_send,
INTERNALLENGTH = 2,
PASSEDBYVALUE,
ALIGNMENT = int2
);
CREATE FUNCTION l2_distance(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME', 'half_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME', 'half_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME', 'half_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME', 'half_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION half_l2_squared_distance(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION half_negative_inner_product(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION float4_to_half(real, integer, boolean) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION integer_to_half(integer, integer, boolean) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION numeric_to_half(numeric, integer, boolean) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (real AS half)
WITH FUNCTION float4_to_half(real, integer, boolean) AS IMPLICIT;
CREATE CAST (integer AS half)
WITH FUNCTION integer_to_half(integer, integer, boolean) AS IMPLICIT;
CREATE CAST (numeric AS half)
WITH FUNCTION numeric_to_half(numeric, integer, boolean) AS IMPLICIT;
CREATE OPERATOR <-> (
LEFTARG = half[], RIGHTARG = half[], PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = half[], RIGHTARG = half[], PROCEDURE = half_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = half[], RIGHTARG = half[], PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR CLASS half_l2_ops
FOR TYPE half[] USING hnsw AS
OPERATOR 1 <-> (half[], half[]) FOR ORDER BY float_ops,
FUNCTION 1 half_l2_squared_distance(half[], half[]);

View File

@@ -290,3 +290,97 @@ 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);
-- half type
CREATE TYPE half;
CREATE FUNCTION half_in(cstring, oid, integer) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION half_out(half) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION half_recv(internal, oid, integer) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION half_send(half) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE half (
INPUT = half_in,
OUTPUT = half_out,
RECEIVE = half_recv,
SEND = half_send,
INTERNALLENGTH = 2,
PASSEDBYVALUE,
ALIGNMENT = int2
);
-- half functions
CREATE FUNCTION l2_distance(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME', 'half_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME', 'half_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME', 'half_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME', 'half_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- half private functions
CREATE FUNCTION half_l2_squared_distance(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION half_negative_inner_product(half[], half[]) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- half cast functions
CREATE FUNCTION float4_to_half(real, integer, boolean) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION integer_to_half(integer, integer, boolean) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION numeric_to_half(numeric, integer, boolean) RETURNS half
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- half casts
CREATE CAST (real AS half)
WITH FUNCTION float4_to_half(real, integer, boolean) AS IMPLICIT;
CREATE CAST (integer AS half)
WITH FUNCTION integer_to_half(integer, integer, boolean) AS IMPLICIT;
CREATE CAST (numeric AS half)
WITH FUNCTION numeric_to_half(numeric, integer, boolean) AS IMPLICIT;
-- half operators
CREATE OPERATOR <-> (
LEFTARG = half[], RIGHTARG = half[], PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = half[], RIGHTARG = half[], PROCEDURE = half_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = half[], RIGHTARG = half[], PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
-- half opclasses
CREATE OPERATOR CLASS half_l2_ops
FOR TYPE half[] USING hnsw AS
OPERATOR 1 <-> (half[], half[]) FOR ORDER BY float_ops,
FUNCTION 1 half_l2_squared_distance(half[], half[]);

599
src/half.c Normal file
View File

@@ -0,0 +1,599 @@
#include "postgres.h"
#include <math.h>
#include "common/shortest_dec.h"
#include "fmgr.h"
#include "half.h"
#include "lib/stringinfo.h"
#include "libpq/pqformat.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/float.h"
#include "utils/numeric.h"
#if PG_VERSION_NUM < 120003
static pg_noinline void
float_overflow_error(void)
{
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("value out of range: overflow")));
}
static pg_noinline void
float_underflow_error(void)
{
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("value out of range: underflow")));
}
#endif
/*
* Check if array is a vector
*/
static void
CheckArrayIsVector(ArrayType *array)
{
if (ARR_NDIM(array) > 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("array must be 1-D")));
if (ARR_HASNULL(array) && array_contains_nulls(array))
ereport(ERROR,
(errcode(ERRCODE_NULL_VALUE_NOT_ALLOWED),
errmsg("array must not contain nulls")));
}
/*
* Check if dimensions are the same
*/
static int
CheckDims(ArrayType *a, ArrayType *b)
{
int dima;
int dimb;
CheckArrayIsVector(a);
CheckArrayIsVector(b);
dima = ARR_DIMS(a)[0];
dimb = ARR_DIMS(b)[0];
if (dima != dimb)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different dimensions %d and %d", dima, dimb)));
return dima;
}
/*
* Return the datum representation for a half
*/
static inline Datum
HalfGetDatum(half X)
{
union
{
half value;
int16 retval;
} myunion;
myunion.value = X;
return Int16GetDatum(myunion.retval);
}
/*
* Return the half value of a datum
*/
static inline half
DatumGetHalf(Datum X)
{
union
{
int16 value;
half retval;
} myunion;
myunion.value = DatumGetInt16(X);
return myunion.retval;
}
/*
* Append a half to a StringInfo buffer
*/
static half
pq_getmsghalf(StringInfo msg)
{
union
{
half h;
uint16 i;
} swap;
/* TODO Likely use float4 for clients */
swap.i = pq_getmsgint(msg, 2);
return swap.h;
}
/*
* Get a half from a message buffer
*/
static void
pq_sendhalf(StringInfo buf, half h)
{
union
{
half h;
uint16 i;
} swap;
/* TODO Likely use float4 for clients */
swap.h = h;
pq_sendint16(buf, swap.i);
}
/*
* Convert a half to a float4
*/
static float
HalfToFloat4(half num)
{
#ifdef FLT16_SUPPORT
return (float) num;
#else
/* TODO Improve performance */
/* TODO Check endianness */
uint16 bin = *((uint16 *) &num);
uint32 exponent = (bin & 0x7C00) >> 10;
uint32 mantissa = bin & 0x03FF;
/* Sign */
uint32 result = (bin & 0x8000) << 16;
if (exponent == 31)
{
if (mantissa == 0)
{
/* Infinite */
result |= 0x7F800000;
}
else
{
/* NaN */
result |= 0x7FC00000;
result |= mantissa << 13;
}
}
else if (exponent == 0)
{
/* Subnormal */
if (mantissa != 0)
{
exponent = -14;
for (int i = 0; i < 10; i++)
{
mantissa <<= 1;
exponent -= 1;
if ((mantissa >> 10) % 2 == 1)
{
mantissa &= 0x03ff;
break;
}
}
result |= (exponent + 127) << 23;
result |= mantissa << 13;
}
}
else
{
/* Normal */
result |= (exponent - 15 + 127) << 23;
result |= mantissa << 13;
}
return *((float *) &result);
#endif
}
/*
* Convert a float4 to a half
*/
static half
Float4ToHalfUnchecked(float num)
{
#ifdef FLT16_SUPPORT
return (_Float16) num;
#else
/* TODO Improve performance */
/* TODO Check endianness */
uint32 bin = *((uint32 *) &num);
int exponent = (bin & 0x7F800000) >> 23;
int mantissa = bin & 0x007FFFFF;
/* Sign */
uint16 result = (bin & 0x80000000) >> 16;
if (isinf(num))
{
/* Infinite */
result |= 0x7C00;
}
else if (isnan(num))
{
/* NaN */
result |= 0x7E00;
result |= mantissa >> 13;
}
else if (exponent > 98)
{
int m;
int gr;
int s;
exponent -= 127;
s = mantissa & 0x00000FFF;
/* Subnormal */
if (exponent < -14)
{
int diff = -exponent - 14;
mantissa >>= diff;
mantissa += 1 << (23 - diff);
s |= mantissa & 0x00000FFF;
}
m = mantissa >> 13;
/* Round */
gr = (mantissa >> 12) % 4;
if (gr == 3 || (gr == 1 && s != 0))
m += 1;
if (m == 1024)
{
m = 0;
exponent += 1;
}
if (exponent > 15)
{
/* Infinite */
result |= 0x7C00;
}
else
{
if (exponent >= -14)
result |= (exponent + 15) << 10;
result |= m;
}
}
return *((half *) & result);
#endif
}
/*
* Convert a float4 to a half
*/
static half
Float4ToHalf(float num)
{
half result = Float4ToHalfUnchecked(num);
/* TODO Perform checks without HalfToFloat4 */
if (unlikely(isinf(HalfToFloat4(result))) && !isinf(num))
float_overflow_error();
if (unlikely(HalfToFloat4(result) == 0.0f) && num != 0.0)
float_underflow_error();
return result;
}
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_in);
Datum
half_in(PG_FUNCTION_ARGS)
{
char *num = PG_GETARG_CSTRING(0);
char *orig_num;
float val;
char *endptr;
orig_num = num;
/* Skip leading whitespace */
while (*num != '\0' && isspace((unsigned char) *num))
num++;
/*
* Check for an empty-string input to begin with, to avoid the vagaries of
* strtof() on different platforms.
*/
if (*num == '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type %s: \"%s\"",
"half", orig_num)));
val = strtof(num, &endptr);
if (val < -HALF_MAX || val > HALF_MAX)
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type %s",
orig_num, "half")));
/* Skip trailing whitespace */
while (*endptr != '\0' && isspace((unsigned char) *endptr))
endptr++;
/* If there is any junk left at the end of the string, bail out */
if (*endptr != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type %s: \"%s\"",
"half", orig_num)));
PG_RETURN_HALF(Float4ToHalf(val));
}
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_out);
Datum
half_out(PG_FUNCTION_ARGS)
{
float num = HalfToFloat4(PG_GETARG_HALF(0));
char *ascii = (char *) palloc(32);
int ndig = FLT_DIG + extra_float_digits;
if (extra_float_digits > 0)
{
float_to_shortest_decimal_buf(num, ascii);
PG_RETURN_CSTRING(ascii);
}
(void) pg_strfromd(ascii, 32, ndig, num);
PG_RETURN_CSTRING(ascii);
}
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_recv);
Datum
half_recv(PG_FUNCTION_ARGS)
{
StringInfo buf = (StringInfo) PG_GETARG_POINTER(0);
PG_RETURN_HALF(pq_getmsghalf(buf));
}
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_send);
Datum
half_send(PG_FUNCTION_ARGS)
{
half arg1 = PG_GETARG_HALF(0);
StringInfoData buf;
pq_begintypsend(&buf);
pq_sendhalf(&buf, arg1);
PG_RETURN_BYTEA_P(pq_endtypsend(&buf));
}
/*
* Convert integer to half
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(integer_to_half);
Datum
integer_to_half(PG_FUNCTION_ARGS)
{
int32 i = PG_GETARG_INT32(0);
/* TODO Figure out correct error */
float f = (float) i;
half h = Float4ToHalf(f);
PG_RETURN_HALF(h);
}
/*
* Convert numeric to half
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(numeric_to_half);
Datum
numeric_to_half(PG_FUNCTION_ARGS)
{
Numeric num = PG_GETARG_NUMERIC(0);
float f = DatumGetFloat4(DirectFunctionCall1(numeric_float4, NumericGetDatum(num)));
half h = Float4ToHalf(f);
PG_RETURN_HALF(h);
}
/*
* Convert float4 to half
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(float4_to_half);
Datum
float4_to_half(PG_FUNCTION_ARGS)
{
float f = PG_GETARG_FLOAT4(0);
half h = Float4ToHalf(f);
PG_RETURN_HALF(h);
}
/*
* Get the L2 distance between half arrays
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_l2_distance);
Datum
half_l2_distance(PG_FUNCTION_ARGS)
{
ArrayType *a = PG_GETARG_ARRAYTYPE_P(0);
ArrayType *b = PG_GETARG_ARRAYTYPE_P(1);
half *ax = (half *) ARR_DATA_PTR(a);
half *bx = (half *) ARR_DATA_PTR(b);
float distance = 0.0;
int dim = CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
PG_RETURN_FLOAT8(sqrt((double) distance));
}
/*
* Get the L2 squared distance between half arrays
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_l2_squared_distance);
Datum
half_l2_squared_distance(PG_FUNCTION_ARGS)
{
ArrayType *a = PG_GETARG_ARRAYTYPE_P(0);
ArrayType *b = PG_GETARG_ARRAYTYPE_P(1);
half *ax = (half *) ARR_DATA_PTR(a);
half *bx = (half *) ARR_DATA_PTR(b);
float distance = 0.0;
int dim = CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
PG_RETURN_FLOAT8((double) distance);
}
/*
* Get the inner product of two half arrays
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_inner_product);
Datum
half_inner_product(PG_FUNCTION_ARGS)
{
ArrayType *a = PG_GETARG_ARRAYTYPE_P(0);
ArrayType *b = PG_GETARG_ARRAYTYPE_P(1);
half *ax = (half *) ARR_DATA_PTR(a);
half *bx = (half *) ARR_DATA_PTR(b);
float distance = 0.0;
int dim = CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
PG_RETURN_FLOAT8((double) distance);
}
/*
* Get the negative inner product of two half arrays
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_negative_inner_product);
Datum
half_negative_inner_product(PG_FUNCTION_ARGS)
{
ArrayType *a = PG_GETARG_ARRAYTYPE_P(0);
ArrayType *b = PG_GETARG_ARRAYTYPE_P(1);
half *ax = (half *) ARR_DATA_PTR(a);
half *bx = (half *) ARR_DATA_PTR(b);
float distance = 0.0;
int dim = CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
PG_RETURN_FLOAT8((double) distance * -1);
}
/*
* Get the cosine distance between two half arrays
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_cosine_distance);
Datum
half_cosine_distance(PG_FUNCTION_ARGS)
{
ArrayType *a = PG_GETARG_ARRAYTYPE_P(0);
ArrayType *b = PG_GETARG_ARRAYTYPE_P(1);
half *ax = (half *) ARR_DATA_PTR(a);
half *bx = (half *) ARR_DATA_PTR(b);
float distance = 0.0;
float norma = 0.0;
float normb = 0.0;
double similarity;
int dim = CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float axi = HalfToFloat4(ax[i]);
float bxi = HalfToFloat4(bx[i]);
distance += axi * bxi;
norma += axi * axi;
normb += bxi * bxi;
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
similarity = (double) distance / 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;
else if (similarity < -1)
similarity = -1;
PG_RETURN_FLOAT8(1 - similarity);
}
/*
* Get the L1 distance between two half arrays
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(half_l1_distance);
Datum
half_l1_distance(PG_FUNCTION_ARGS)
{
ArrayType *a = PG_GETARG_ARRAYTYPE_P(0);
ArrayType *b = PG_GETARG_ARRAYTYPE_P(1);
half *ax = (half *) ARR_DATA_PTR(a);
half *bx = (half *) ARR_DATA_PTR(b);
float distance = 0.0;
int dim = CheckDims(a, b);
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += fabsf(HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]));
PG_RETURN_FLOAT8((double) distance);
}

28
src/half.h Normal file
View File

@@ -0,0 +1,28 @@
#ifndef HALF_H
#define HALF_H
#define __STDC_WANT_IEC_60559_TYPES_EXT__
#include <float.h>
/* _Float16 and __fp16 are not supported on x86_64 with GCC 11 */
#if defined(__is_identifier)
#if __is_identifier(_Float16)
#define FLT16_SUPPORT
#endif
#elif defined(FLT16_MAX)
#define FLT16_SUPPORT
#endif
#ifdef FLT16_SUPPORT
#define half _Float16
#define HALF_MAX FLT16_MAX
#else
#define half uint16
#define HALF_MAX 65504
#endif
#define PG_GETARG_HALF(n) DatumGetHalf(PG_GETARG_DATUM(n))
#define PG_RETURN_HALF(x) return HalfGetDatum(x)
#endif

View File

@@ -14,6 +14,7 @@
#endif
int hnsw_ef_search;
bool hnsw_enable_parallel_build;
static relopt_kind hnsw_relopt_kind;
/*
@@ -39,6 +40,11 @@ HnswInit(void)
DefineCustomIntVariable("hnsw.ef_search", "Sets the size of the dynamic candidate list for search",
"Valid range is 1..1000.", &hnsw_ef_search,
HNSW_DEFAULT_EF_SEARCH, HNSW_MIN_EF_SEARCH, HNSW_MAX_EF_SEARCH, PGC_USERSET, 0, NULL, NULL, NULL);
/* Behind a variable for now since can be slower than building in memory */
DefineCustomBoolVariable("hnsw.enable_parallel_build", "Enables or disables building indexes in parallel",
NULL, &hnsw_enable_parallel_build,
false, PGC_USERSET, 0, NULL, NULL, NULL);
}
/*

View File

@@ -4,6 +4,7 @@
#include "postgres.h"
#include "access/generic_xlog.h"
#include "access/parallel.h"
#include "access/reloptions.h"
#include "nodes/execnodes.h"
#include "port.h" /* for random() */
@@ -14,6 +15,10 @@
#error "Requires PostgreSQL 11+"
#endif
#if PG_VERSION_NUM < 120000
#include "access/relscan.h"
#endif
#define HNSW_MAX_DIM 2000
/* Support functions */
@@ -59,7 +64,7 @@
#define HNSW_MAX_SIZE (BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - sizeof(ItemIdData))
#define HNSW_ELEMENT_TUPLE_SIZE(_dim) MAXALIGN(offsetof(HnswElementTupleData, vec) + VECTOR_SIZE(_dim))
#define HNSW_ELEMENT_TUPLE_SIZE(size) MAXALIGN(offsetof(HnswElementTupleData, data) + (size))
#define HNSW_NEIGHBOR_TUPLE_SIZE(level, m) MAXALIGN(offsetof(HnswNeighborTupleData, indextids) + ((level) + 2) * (m) * sizeof(ItemPointerData))
#define HnswPageGetOpaque(page) ((HnswPageOpaque) PageGetSpecialPointer(page))
@@ -90,6 +95,7 @@
/* Variables */
extern int hnsw_ef_search;
extern bool hnsw_enable_parallel_build;
typedef struct HnswNeighborArray HnswNeighborArray;
@@ -103,7 +109,7 @@ typedef struct HnswElementData
OffsetNumber offno;
OffsetNumber neighborOffno;
BlockNumber neighborPage;
Vector *vec;
Datum value;
} HnswElementData;
typedef HnswElementData * HnswElement;
@@ -136,6 +142,49 @@ typedef struct HnswOptions
int efConstruction; /* size of dynamic candidate list */
} HnswOptions;
typedef struct HnswSpool
{
Relation heap;
Relation index;
} HnswSpool;
typedef struct HnswShared
{
/* Immutable state */
Oid heaprelid;
Oid indexrelid;
bool isconcurrent;
int scantuplesortstates;
/* Worker progress */
ConditionVariable workersdonecv;
/* Mutex for mutable state */
slock_t mutex;
/* Mutable state */
int nparticipantsdone;
double reltuples;
double indtuples;
#if PG_VERSION_NUM < 120000
ParallelHeapScanDescData heapdesc; /* must come last */
#endif
} HnswShared;
#if PG_VERSION_NUM >= 120000
#define ParallelTableScanFromHnswShared(shared) \
(ParallelTableScanDesc) ((char *) (shared) + BUFFERALIGN(sizeof(HnswShared)))
#endif
typedef struct HnswLeader
{
ParallelContext *pcxt;
int nparticipanttuplesorts;
HnswShared *hnswshared;
Snapshot snapshot;
} HnswLeader;
typedef struct HnswBuildState
{
/* Info */
@@ -163,12 +212,16 @@ typedef struct HnswBuildState
HnswElement entryPoint;
double ml;
int maxLevel;
double maxInMemoryElements;
long memoryLeft;
bool flushed;
Vector *normvec;
/* Memory */
MemoryContext tmpCtx;
/* Parallel builds */
HnswLeader *hnswleader;
HnswShared *hnswshared;
} HnswBuildState;
typedef struct HnswMetaPageData
@@ -204,7 +257,7 @@ typedef struct HnswElementTupleData
ItemPointerData heaptids[HNSW_HEAPTIDS];
ItemPointerData neighbortid;
uint16 unused2;
Vector vec;
Vector data;
} HnswElementTupleData;
typedef HnswElementTupleData * HnswElementTuple;
@@ -289,6 +342,7 @@ void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation i
void HnswSetElementTuple(HnswElementTuple etup, HnswElement element);
void HnswUpdateConnection(HnswElement element, HnswCandidate * hc, int m, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
void HnswLoadNeighbors(HnswElement element, Relation index, int m);
PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);
/* Index access methods */
IndexBuildResult *hnswbuild(Relation heap, Relation index, IndexInfo *indexInfo);

View File

@@ -2,12 +2,16 @@
#include <math.h>
#include "access/parallel.h"
#include "access/xact.h"
#include "catalog/index.h"
#include "hnsw.h"
#include "miscadmin.h"
#include "lib/pairingheap.h"
#include "nodes/pg_list.h"
#include "storage/bufmgr.h"
#include "tcop/tcopprot.h"
#include "utils/datum.h"
#include "utils/memutils.h"
#if PG_VERSION_NUM >= 140000
@@ -35,6 +39,23 @@
#define UpdateProgress(index, val) ((void)val)
#endif
#if PG_VERSION_NUM >= 140000
#include "utils/backend_status.h"
#include "utils/wait_event.h"
#endif
#if PG_VERSION_NUM >= 120000
#include "access/table.h"
#include "optimizer/optimizer.h"
#else
#include "access/heapam.h"
#include "optimizer/planner.h"
#include "pgstat.h"
#endif
#define PARALLEL_KEY_HNSW_SHARED UINT64CONST(0xA000000000000001)
#define PARALLEL_KEY_QUERY_TEXT UINT64CONST(0xA000000000000002)
/*
* Create the metapage
*/
@@ -105,8 +126,7 @@ CreateElementPages(HnswBuildState * buildstate)
{
Relation index = buildstate->index;
ForkNumber forkNum = buildstate->forkNum;
int dimensions = buildstate->dimensions;
Size etupSize;
Size etupAllocSize;
Size maxSize;
HnswElementTuple etup;
HnswNeighborTuple ntup;
@@ -117,11 +137,11 @@ CreateElementPages(HnswBuildState * buildstate)
ListCell *lc;
/* Calculate sizes */
etupAllocSize = BLCKSZ;
maxSize = HNSW_MAX_SIZE;
etupSize = HNSW_ELEMENT_TUPLE_SIZE(dimensions);
/* Allocate once */
etup = palloc0(etupSize);
etup = palloc0(etupAllocSize);
ntup = palloc0(BLCKSZ);
/* Prepare first page */
@@ -133,15 +153,24 @@ CreateElementPages(HnswBuildState * buildstate)
foreach(lc, buildstate->elements)
{
HnswElement element = lfirst(lc);
Size etupSize;
Size ntupSize;
Size combinedSize;
HnswSetElementTuple(etup, element);
/* Zero memory for each element */
MemSet(etup, 0, etupAllocSize);
/* Calculate sizes */
etupSize = HNSW_ELEMENT_TUPLE_SIZE(VARSIZE_ANY(DatumGetPointer(element->value)));
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, buildstate->m);
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
/* Initial size check */
if (etupSize > etupAllocSize)
elog(ERROR, "index tuple too large");
HnswSetElementTuple(etup, element);
/* Keep element and neighbors on the same page if possible */
if (PageGetFreeSpace(page) < etupSize || (combinedSize <= maxSize && PageGetFreeSpace(page) < combinedSize))
HnswBuildAppendPage(index, &buf, &page, &state, forkNum);
@@ -264,13 +293,14 @@ FlushPages(HnswBuildState * buildstate)
* Insert tuple
*/
static bool
InsertTuple(Relation index, Datum *values, HnswElement element, HnswBuildState * buildstate, HnswElement * dup)
InsertTuple(Relation index, Datum *values, HnswElement element, HnswBuildState * buildstate, HnswElement * dup, MemoryContext outerCtx)
{
FmgrInfo *procinfo = buildstate->procinfo;
Oid collation = buildstate->collation;
HnswElement entryPoint = buildstate->entryPoint;
int efConstruction = buildstate->efConstruction;
int m = buildstate->m;
MemoryContext oldCtx;
/* Detoast once for all calls */
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
@@ -283,7 +313,9 @@ InsertTuple(Relation index, Datum *values, HnswElement element, HnswBuildState *
}
/* Copy value to element so accessible outside of memory context */
memcpy(element->vec, DatumGetVector(value), VECTOR_SIZE(buildstate->dimensions));
oldCtx = MemoryContextSwitchTo(outerCtx);
element->value = datumCopy(value, false, -1);
MemoryContextSwitchTo(oldCtx);
/* Insert element in graph */
HnswInsertElement(element, entryPoint, NULL, procinfo, collation, m, efConstruction, false);
@@ -313,6 +345,21 @@ InsertTuple(Relation index, Datum *values, HnswElement element, HnswBuildState *
return *dup == NULL;
}
/*
* Get the memory used by an element
*/
static long
HnswElementMemory(HnswElement e, int m)
{
long elementSize = sizeof(HnswElementData);
elementSize += sizeof(HnswNeighborArray) * (e->level + 1);
elementSize += sizeof(HnswCandidate) * (m * (e->level + 2));
elementSize += sizeof(ItemPointerData);
elementSize += VARSIZE_ANY(DatumGetPointer(e->value));
return elementSize;
}
/*
* Callback for table_index_build_scan
*/
@@ -334,7 +381,7 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
if (isnull[0])
return;
if (buildstate->indtuples >= buildstate->maxInMemoryElements)
if (buildstate->memoryLeft <= 0)
{
if (!buildstate->flushed)
{
@@ -349,7 +396,18 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
if (HnswInsertTuple(buildstate->index, values, isnull, tid, buildstate->heap))
{
if (buildstate->hnswshared)
{
HnswShared *hnswshared = buildstate->hnswshared;
SpinLockAcquire(&hnswshared->mutex);
UpdateProgress(PROGRESS_CREATEIDX_TUPLES_DONE, ++hnswshared->indtuples);
SpinLockRelease(&hnswshared->mutex);
}
else
UpdateProgress(PROGRESS_CREATEIDX_TUPLES_DONE, ++buildstate->indtuples);
}
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
@@ -360,13 +418,12 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
/* Allocate necessary memory outside of memory context */
element = HnswInitElement(tid, buildstate->m, buildstate->ml, buildstate->maxLevel);
element->vec = palloc(VECTOR_SIZE(buildstate->dimensions));
/* Use memory context since detoast can allocate */
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
/* Insert tuple */
inserted = InsertTuple(index, values, element, buildstate, &dup);
inserted = InsertTuple(index, values, element, buildstate, &dup, oldCtx);
/* Reset memory context */
MemoryContextSwitchTo(oldCtx);
@@ -374,31 +431,21 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
/* Add outside memory context */
if (dup != NULL)
{
HnswAddHeapTid(dup, tid);
buildstate->memoryLeft -= sizeof(ItemPointerData);
}
/* Add to buildstate or free */
if (inserted)
{
buildstate->elements = lappend(buildstate->elements, element);
buildstate->memoryLeft -= HnswElementMemory(element, buildstate->m);
}
else
HnswFreeElement(element);
}
/*
* Get the max number of elements that fit into maintenance_work_mem
*/
static double
HnswGetMaxInMemoryElements(int m, double ml, int dimensions)
{
Size elementSize = sizeof(HnswElementData);
double avgLevel = -log(0.5) * ml;
elementSize += sizeof(HnswNeighborArray) * (avgLevel + 1);
elementSize += sizeof(HnswCandidate) * (m * (avgLevel + 2));
elementSize += sizeof(ItemPointerData);
elementSize += VECTOR_SIZE(dimensions);
return (maintenance_work_mem * 1024L) / elementSize;
}
/*
* Initialize the build state
*/
@@ -415,8 +462,8 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
/* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0)
elog(ERROR, "column does not have dimensions");
// 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);
@@ -436,7 +483,7 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->entryPoint = NULL;
buildstate->ml = HnswGetMl(buildstate->m);
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
buildstate->maxInMemoryElements = HnswGetMaxInMemoryElements(buildstate->m, buildstate->ml, buildstate->dimensions);
buildstate->memoryLeft = maintenance_work_mem * 1024L;
buildstate->flushed = false;
/* Reuse for each tuple */
@@ -445,6 +492,9 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw build temporary context",
ALLOCSET_DEFAULT_SIZES);
buildstate->hnswleader = NULL;
buildstate->hnswshared = NULL;
}
/*
@@ -457,14 +507,362 @@ FreeBuildState(HnswBuildState * buildstate)
MemoryContextDelete(buildstate->tmpCtx);
}
/*
* Within leader, wait for end of heap scan
*/
static double
ParallelHeapScan(HnswBuildState * buildstate)
{
HnswShared *hnswshared = buildstate->hnswleader->hnswshared;
int nparticipanttuplesorts;
double reltuples;
nparticipanttuplesorts = buildstate->hnswleader->nparticipanttuplesorts;
for (;;)
{
SpinLockAcquire(&hnswshared->mutex);
if (hnswshared->nparticipantsdone == nparticipanttuplesorts)
{
buildstate->indtuples = hnswshared->indtuples;
reltuples = hnswshared->reltuples;
SpinLockRelease(&hnswshared->mutex);
break;
}
SpinLockRelease(&hnswshared->mutex);
ConditionVariableSleep(&hnswshared->workersdonecv,
WAIT_EVENT_PARALLEL_CREATE_INDEX_SCAN);
}
ConditionVariableCancelSleep();
return reltuples;
}
/*
* Perform a worker's portion of a parallel insert
*/
static void
HnswParallelScanAndInsert(HnswSpool * hnswspool, HnswShared * hnswshared, bool progress)
{
HnswBuildState buildstate;
#if PG_VERSION_NUM >= 120000
TableScanDesc scan;
#else
HeapScanDesc scan;
#endif
double reltuples;
IndexInfo *indexInfo;
/* Join parallel scan */
indexInfo = BuildIndexInfo(hnswspool->index);
indexInfo->ii_Concurrent = hnswshared->isconcurrent;
InitBuildState(&buildstate, hnswspool->heap, hnswspool->index, indexInfo, MAIN_FORKNUM);
/* TODO Support in-memory builds */
buildstate.memoryLeft = 0;
buildstate.flushed = true;
buildstate.hnswshared = hnswshared;
#if PG_VERSION_NUM >= 120000
scan = table_beginscan_parallel(hnswspool->heap,
ParallelTableScanFromHnswShared(hnswshared));
reltuples = table_index_build_scan(hnswspool->heap, hnswspool->index, indexInfo,
true, progress, BuildCallback,
(void *) &buildstate, scan);
#else
scan = heap_beginscan_parallel(hnswspool->heap, &hnswshared->heapdesc);
reltuples = IndexBuildHeapScan(hnswspool->heap, hnswspool->index, indexInfo,
true, BuildCallback,
(void *) &buildstate, scan);
#endif
/* Record statistics */
SpinLockAcquire(&hnswshared->mutex);
hnswshared->nparticipantsdone++;
hnswshared->reltuples += reltuples;
SpinLockRelease(&hnswshared->mutex);
/* Log statistics */
if (progress)
ereport(DEBUG1, (errmsg("leader processed " INT64_FORMAT " tuples", (int64) reltuples)));
else
ereport(DEBUG1, (errmsg("worker processed " INT64_FORMAT " tuples", (int64) reltuples)));
/* Notify leader */
ConditionVariableSignal(&hnswshared->workersdonecv);
FreeBuildState(&buildstate);
}
/*
* Perform work within a launched parallel process
*/
void
HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc)
{
char *sharedquery;
HnswSpool *hnswspool;
HnswShared *hnswshared;
Relation heapRel;
Relation indexRel;
LOCKMODE heapLockmode;
LOCKMODE indexLockmode;
/* Set debug_query_string for individual workers first */
sharedquery = shm_toc_lookup(toc, PARALLEL_KEY_QUERY_TEXT, true);
debug_query_string = sharedquery;
/* Report the query string from leader */
pgstat_report_activity(STATE_RUNNING, debug_query_string);
/* Look up shared state */
hnswshared = shm_toc_lookup(toc, PARALLEL_KEY_HNSW_SHARED, false);
/* Open relations using lock modes known to be obtained by index.c */
if (!hnswshared->isconcurrent)
{
heapLockmode = ShareLock;
indexLockmode = AccessExclusiveLock;
}
else
{
heapLockmode = ShareUpdateExclusiveLock;
indexLockmode = RowExclusiveLock;
}
/* Open relations within worker */
#if PG_VERSION_NUM >= 120000
heapRel = table_open(hnswshared->heaprelid, heapLockmode);
#else
heapRel = heap_open(hnswshared->heaprelid, heapLockmode);
#endif
indexRel = index_open(hnswshared->indexrelid, indexLockmode);
/* Initialize worker's own spool */
hnswspool = (HnswSpool *) palloc0(sizeof(HnswSpool));
hnswspool->heap = heapRel;
hnswspool->index = indexRel;
/* Perform inserts */
HnswParallelScanAndInsert(hnswspool, hnswshared, false);
/* Close relations within worker */
index_close(indexRel, indexLockmode);
#if PG_VERSION_NUM >= 120000
table_close(heapRel, heapLockmode);
#else
heap_close(heapRel, heapLockmode);
#endif
}
/*
* End parallel build
*/
static void
HnswEndParallel(HnswLeader * hnswleader)
{
/* Shutdown worker processes */
WaitForParallelWorkersToFinish(hnswleader->pcxt);
/* Free last reference to MVCC snapshot, if one was used */
if (IsMVCCSnapshot(hnswleader->snapshot))
UnregisterSnapshot(hnswleader->snapshot);
DestroyParallelContext(hnswleader->pcxt);
ExitParallelMode();
}
/*
* Return size of shared memory required for parallel index build
*/
static Size
ParallelEstimateShared(Relation heap, Snapshot snapshot)
{
#if PG_VERSION_NUM >= 120000
return add_size(BUFFERALIGN(sizeof(HnswShared)), table_parallelscan_estimate(heap, snapshot));
#else
if (!IsMVCCSnapshot(snapshot))
{
Assert(snapshot == SnapshotAny);
return sizeof(HnswShared);
}
return add_size(offsetof(HnswShared, heapdesc) +
offsetof(ParallelHeapScanDescData, phs_snapshot_data),
EstimateSnapshotSpace(snapshot));
#endif
}
/*
* Within leader, participate as a parallel worker
*/
static void
HnswLeaderParticipateAsWorker(HnswBuildState * buildstate)
{
HnswLeader *hnswleader = buildstate->hnswleader;
HnswSpool *leaderworker;
/* Allocate memory and initialize private spool */
leaderworker = (HnswSpool *) palloc0(sizeof(HnswSpool));
leaderworker->heap = buildstate->heap;
leaderworker->index = buildstate->index;
/* Perform work common to all participants */
HnswParallelScanAndInsert(leaderworker, hnswleader->hnswshared, true);
}
/*
* Begin parallel build
*/
static void
HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
{
ParallelContext *pcxt;
int scantuplesortstates;
Snapshot snapshot;
Size esthnswshared;
HnswShared *hnswshared;
HnswLeader *hnswleader = (HnswLeader *) palloc0(sizeof(HnswLeader));
bool leaderparticipates = true;
int querylen;
#ifdef DISABLE_LEADER_PARTICIPATION
leaderparticipates = false;
#endif
/* Enter parallel mode and create context */
EnterParallelMode();
Assert(request > 0);
#if PG_VERSION_NUM >= 120000
pcxt = CreateParallelContext("vector", "HnswParallelBuildMain", request);
#else
pcxt = CreateParallelContext("vector", "HnswParallelBuildMain", request, true);
#endif
scantuplesortstates = leaderparticipates ? request + 1 : request;
/* Get snapshot for table scan */
if (!isconcurrent)
snapshot = SnapshotAny;
else
snapshot = RegisterSnapshot(GetTransactionSnapshot());
/* Estimate size of workspaces */
esthnswshared = ParallelEstimateShared(buildstate->heap, snapshot);
shm_toc_estimate_chunk(&pcxt->estimator, esthnswshared);
shm_toc_estimate_keys(&pcxt->estimator, 1);
/* Finally, estimate PARALLEL_KEY_QUERY_TEXT space */
if (debug_query_string)
{
querylen = strlen(debug_query_string);
shm_toc_estimate_chunk(&pcxt->estimator, querylen + 1);
shm_toc_estimate_keys(&pcxt->estimator, 1);
}
else
querylen = 0; /* keep compiler quiet */
/* Everyone's had a chance to ask for space, so now create the DSM */
InitializeParallelDSM(pcxt);
/* If no DSM segment was available, back out (do serial build) */
if (pcxt->seg == NULL)
{
if (IsMVCCSnapshot(snapshot))
UnregisterSnapshot(snapshot);
DestroyParallelContext(pcxt);
ExitParallelMode();
return;
}
/* Store shared build state, for which we reserved space */
hnswshared = (HnswShared *) shm_toc_allocate(pcxt->toc, esthnswshared);
/* Initialize immutable state */
hnswshared->heaprelid = RelationGetRelid(buildstate->heap);
hnswshared->indexrelid = RelationGetRelid(buildstate->index);
hnswshared->isconcurrent = isconcurrent;
hnswshared->scantuplesortstates = scantuplesortstates;
ConditionVariableInit(&hnswshared->workersdonecv);
SpinLockInit(&hnswshared->mutex);
/* Initialize mutable state */
hnswshared->nparticipantsdone = 0;
hnswshared->reltuples = 0;
hnswshared->indtuples = 0;
#if PG_VERSION_NUM >= 120000
table_parallelscan_initialize(buildstate->heap,
ParallelTableScanFromHnswShared(hnswshared),
snapshot);
#else
heap_parallelscan_initialize(&hnswshared->heapdesc, buildstate->heap, snapshot);
#endif
shm_toc_insert(pcxt->toc, PARALLEL_KEY_HNSW_SHARED, hnswshared);
/* Store query string for workers */
if (debug_query_string)
{
char *sharedquery;
sharedquery = (char *) shm_toc_allocate(pcxt->toc, querylen + 1);
memcpy(sharedquery, debug_query_string, querylen + 1);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_QUERY_TEXT, sharedquery);
}
/* Launch workers, saving status for leader/caller */
LaunchParallelWorkers(pcxt);
hnswleader->pcxt = pcxt;
hnswleader->nparticipanttuplesorts = pcxt->nworkers_launched;
if (leaderparticipates)
hnswleader->nparticipanttuplesorts++;
hnswleader->hnswshared = hnswshared;
hnswleader->snapshot = snapshot;
/* If no workers were successfully launched, back out (do serial build) */
if (pcxt->nworkers_launched == 0)
{
HnswEndParallel(hnswleader);
return;
}
/* Log participants */
ereport(DEBUG1, (errmsg("using %d parallel workers", pcxt->nworkers_launched)));
/* Save leader state now that it's clear build will be parallel */
buildstate->hnswleader = hnswleader;
/* Join heap scan ourselves */
if (leaderparticipates)
HnswLeaderParticipateAsWorker(buildstate);
/* Wait for all launched workers */
WaitForParallelWorkersToAttach(pcxt);
}
/*
* Build graph
*/
static void
BuildGraph(HnswBuildState * buildstate, ForkNumber forkNum)
{
int parallel_workers = 0;
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_HNSW_PHASE_LOAD);
/* Calculate parallel workers */
if (hnsw_enable_parallel_build)
parallel_workers = plan_create_index_workers(RelationGetRelid(buildstate->heap), RelationGetRelid(buildstate->index));
/* Attempt to launch parallel worker scan when required */
if (parallel_workers > 0)
{
/* TODO Support in-memory builds */
FlushPages(buildstate);
HnswBeginParallel(buildstate, buildstate->indexInfo->ii_Concurrent, parallel_workers);
}
/* Add tuples to sort */
if (buildstate->hnswleader)
buildstate->reltuples = ParallelHeapScan(buildstate);
else
{
#if PG_VERSION_NUM >= 120000
buildstate->reltuples = table_index_build_scan(buildstate->heap, buildstate->index, buildstate->indexInfo,
true, true, BuildCallback, (void *) buildstate, NULL);
@@ -474,6 +872,11 @@ BuildGraph(HnswBuildState * buildstate, ForkNumber forkNum)
#endif
}
/* End parallel build */
if (buildstate->hnswleader)
HnswEndParallel(buildstate->hnswleader);
}
/*
* Build the index
*/

View File

@@ -123,7 +123,6 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
Size minCombinedSize;
HnswElementTuple etup;
BlockNumber currentPage = insertPage;
int dimensions = e->vec->dim;
HnswNeighborTuple ntup;
Buffer nbuf;
Page npage;
@@ -132,7 +131,7 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
BlockNumber newInsertPage = InvalidBlockNumber;
/* Calculate sizes */
etupSize = HNSW_ELEMENT_TUPLE_SIZE(dimensions);
etupSize = HNSW_ELEMENT_TUPLE_SIZE(VARSIZE_ANY(DatumGetPointer(e->value)));
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
maxSize = HNSW_MAX_SIZE;
@@ -405,8 +404,9 @@ HnswAddDuplicate(Relation index, HnswElement element, HnswElement dup)
Buffer buf;
Page page;
GenericXLogState *state;
Size etupSize = HNSW_ELEMENT_TUPLE_SIZE(dup->vec->dim);
ItemId itemid;
HnswElementTuple etup;
Size etupSize;
int i;
/* Read page */
@@ -416,7 +416,9 @@ HnswAddDuplicate(Relation index, HnswElement element, HnswElement dup)
page = GenericXLogRegisterBuffer(state, buf, 0);
/* Find space */
etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, dup->offno));
itemid = PageGetItemId(page, dup->offno);
etup = (HnswElementTuple) PageGetItem(page, itemid);
etupSize = ItemIdGetLength(itemid);
for (i = 0; i < HNSW_HEAPTIDS; i++)
{
if (!ItemPointerIsValid(&etup->heaptids[i]))
@@ -515,7 +517,7 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
/* Create an element */
element = HnswInitElement(heap_tid, m, HnswGetMl(m), HnswGetMaxLevel(m));
element->vec = DatumGetVector(value);
element->value = value;
/* Prevent concurrent inserts when likely updating entry point */
if (entryPoint == NULL || element->level > entryPoint->level)

View File

@@ -4,6 +4,7 @@
#include "hnsw.h"
#include "storage/bufmgr.h"
#include "utils/datum.h"
#include "vector.h"
/*
@@ -176,6 +177,8 @@ HnswInitElement(ItemPointer heaptid, int m, double ml, int maxLevel)
HnswInitNeighbors(element, m);
element->value = PointerGetDatum(NULL);
return element;
}
@@ -187,7 +190,8 @@ HnswFreeElement(HnswElement element)
{
HnswFreeNeighbors(element);
list_free_deep(element->heaptids);
pfree(element->vec);
if (DatumGetPointer(element->value))
pfree(DatumGetPointer(element->value));
pfree(element);
}
@@ -214,7 +218,7 @@ HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno)
element->blkno = blkno;
element->offno = offno;
element->neighbors = NULL;
element->vec = NULL;
element->value = PointerGetDatum(NULL);
return element;
}
@@ -324,7 +328,7 @@ HnswSetElementTuple(HnswElementTuple etup, HnswElement element)
else
ItemPointerSetInvalid(&etup->heaptids[i]);
}
memcpy(&etup->vec, element->vec, VECTOR_SIZE(element->vec->dim));
memcpy(&etup->data, DatumGetPointer(element->value), VARSIZE_ANY(DatumGetPointer(element->value)));
}
/*
@@ -446,10 +450,7 @@ HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHe
}
if (loadVec)
{
element->vec = palloc(VECTOR_SIZE(etup->vec.dim));
memcpy(element->vec, &etup->vec, VECTOR_SIZE(etup->vec.dim));
}
element->value = datumCopy(PointerGetDatum(&etup->data), false, -1);
}
/*
@@ -476,7 +477,7 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
/* Calculate distance */
if (distance != NULL)
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->vec)));
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
UnlockReleaseBuffer(buf);
}
@@ -487,7 +488,7 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
static float
GetCandidateDistance(HnswCandidate * hc, Datum q, FmgrInfo *procinfo, Oid collation)
{
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, q, PointerGetDatum(hc->element->vec)));
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, q, hc->element->value));
}
/*
@@ -750,7 +751,7 @@ HnswGetDistance(HnswElement a, HnswElement b, int lc, FmgrInfo *procinfo, Oid co
}
}
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(a->vec), PointerGetDatum(b->vec)));
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, a->value, b->value));
}
/*
@@ -877,7 +878,7 @@ HnswFindDuplicate(HnswElement e)
HnswCandidate *neighbor = &neighbors->items[i];
/* Exit early since ordered by distance */
if (vector_cmp_internal(e->vec, neighbor->element->vec) != 0)
if (!datumIsEqual(e->value, neighbor->element->value, false, -1))
break;
/* Check for space */
@@ -930,13 +931,13 @@ HnswUpdateConnection(HnswElement element, HnswCandidate * hc, int m, int lc, int
/* Load elements on insert */
if (index != NULL)
{
Datum q = PointerGetDatum(hc->element->vec);
Datum q = hc->element->value;
for (int i = 0; i < currentNeighbors->length; i++)
{
HnswCandidate *hc3 = &currentNeighbors->items[i];
if (hc3->element->vec == NULL)
if (DatumGetPointer(hc3->element->value) == NULL)
HnswLoadElement(hc3->element, &hc3->distance, &q, index, procinfo, collation, true);
else
hc3->distance = GetCandidateDistance(hc3, q, procinfo, collation);
@@ -1017,7 +1018,7 @@ HnswInsertElement(HnswElement element, HnswElement entryPoint, Relation index, F
List *w;
int level = element->level;
int entryLevel;
Datum q = PointerGetDatum(element->vec);
Datum q = element->value;
HnswElement skipElement = existing ? element : NULL;
/* No neighbors if no entry point */

View File

@@ -62,7 +62,8 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
/* Iterate over nodes */
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
ItemId itemid = PageGetItemId(page, offno);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, itemid);
int idx = 0;
bool itemUpdated = false;
@@ -93,7 +94,7 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
if (itemUpdated)
{
Size etupSize = HNSW_ELEMENT_TUPLE_SIZE(etup->vec.dim);
Size etupSize = ItemIdGetLength(itemid);
/* Mark rest as invalid */
for (int i = idx; i < HNSW_HEAPTIDS; i++)
@@ -477,7 +478,8 @@ MarkDeleted(HnswVacuumState * vacuumstate)
/* Update element and neighbors together */
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
ItemId itemid = PageGetItemId(page, offno);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, itemid);
HnswNeighborTuple ntup;
Size etupSize;
Size ntupSize;
@@ -505,7 +507,7 @@ MarkDeleted(HnswVacuumState * vacuumstate)
continue;
/* Calculate sizes */
etupSize = HNSW_ELEMENT_TUPLE_SIZE(etup->vec.dim);
etupSize = ItemIdGetLength(itemid);
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(etup->level, vacuumstate->m);
/* Get neighbor page */
@@ -528,7 +530,7 @@ MarkDeleted(HnswVacuumState * vacuumstate)
/* Overwrite element */
etup->deleted = 1;
MemSet(&etup->vec.x, 0, etup->vec.dim * sizeof(float));
MemSet(&etup->data, 0, VARSIZE_ANY(&etup->data));
/* Overwrite neighbors */
for (int i = 0; i < ntup->count; i++)

View File

@@ -89,7 +89,7 @@ CheckDim(int dim)
}
/*
* Ensure finite elements
* Ensure finite element
*/
static inline void
CheckElement(float value)
@@ -437,17 +437,18 @@ vector_send(PG_FUNCTION_ARGS)
/*
* Convert vector to vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector);
Datum
vector(PG_FUNCTION_ARGS)
{
Vector *arg = PG_GETARG_VECTOR_P(0);
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
CheckExpectedDim(typmod, arg->dim);
CheckExpectedDim(typmod, vec->dim);
PG_RETURN_POINTER(arg);
PG_RETURN_POINTER(vec);
}
/*
@@ -464,7 +465,6 @@ array_to_vector(PG_FUNCTION_ARGS)
bool typbyval;
char typalign;
Datum *elemsp;
bool *nullsp;
int nelemsp;
if (ARR_NDIM(array) > 1)
@@ -478,7 +478,7 @@ array_to_vector(PG_FUNCTION_ARGS)
errmsg("array must not contain nulls")));
get_typlenbyvalalign(ARR_ELEMTYPE(array), &typlen, &typbyval, &typalign);
deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, &nullsp, &nelemsp);
deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, NULL, &nelemsp);
CheckDim(nelemsp);
CheckExpectedDim(typmod, nelemsp);
@@ -512,6 +512,12 @@ array_to_vector(PG_FUNCTION_ARGS)
errmsg("unsupported array type")));
}
/*
* Free allocation from deconstruct_array. Do not free individual elements
* when pass-by-reference since they point to original array.
*/
pfree(elemsp);
/* Check elements */
for (int i = 0; i < result->dim; i++)
CheckElement(result->x[i]);

View File

@@ -1,15 +1,15 @@
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val vector(3));
CREATE TABLE t (val vector(3), val2 half[]);
INSERT INTO t (val, val2) VALUES ('[0,0,0]', '{0,0,0}'), ('[1,2,3]', '{1,2,3}'), ('[1,1,1]', '{1,1,1}'), (NULL, NULL);
CREATE TABLE t2 (val vector(3), val2 half[]);
\copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/data.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
val | val2
---------+---------
[0,0,0] | {0,0,0}
[1,1,1] | {1,1,1}
[1,2,3] | {1,2,3}
|
(4 rows)
DROP TABLE t;

View File

@@ -54,105 +54,105 @@ 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

182
test/expected/half.out Normal file
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@@ -0,0 +1,182 @@
SELECT '1.5'::half;
half
------
1.5
(1 row)
SELECT '65504'::half;
half
-------
65504
(1 row)
SELECT '65505'::half;
ERROR: "65505" is out of range for type half
LINE 1: SELECT '65505'::half;
^
SELECT '-65504'::half;
half
--------
-65504
(1 row)
SELECT '-65505'::half;
ERROR: "-65505" is out of range for type half
LINE 1: SELECT '-65505'::half;
^
SELECT ''::half;
ERROR: invalid input syntax for type half: ""
LINE 1: SELECT ''::half;
^
SELECT ' '::half;
ERROR: invalid input syntax for type half: " "
LINE 1: SELECT ' '::half;
^
SELECT '-'::half;
ERROR: invalid input syntax for type half: "-"
LINE 1: SELECT '-'::half;
^
SELECT ' 1.5'::half;
half
------
1.5
(1 row)
SELECT '1.5 '::half;
half
------
1.5
(1 row)
SELECT '1.5a'::half;
ERROR: invalid input syntax for type half: "1.5a"
LINE 1: SELECT '1.5a'::half;
^
SELECT '{1,2,3}'::half[];
half
---------
{1,2,3}
(1 row)
SELECT '65505'::integer::half;
half
-------
65504
(1 row)
SELECT 'NaN'::real::half;
half
------
NaN
(1 row)
SELECT 'Infinity'::real::half;
half
----------
Infinity
(1 row)
SELECT l2_distance('{0,0}'::half[], '{3,4}'::half[]);
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{0,0}'::half[], '{0,1}'::half[]);
l2_distance
-------------
1
(1 row)
SELECT l2_distance('{1,2}'::half[], '{3}'::half[]);
ERROR: different dimensions 2 and 1
SELECT '{0,0}'::half[] <-> '{3,4}'::half[];
?column?
----------
5
(1 row)
SELECT inner_product('{1,2}'::half[], '{3,4}'::half[]);
inner_product
---------------
11
(1 row)
SELECT inner_product('{1,2}'::half[], '{3}'::half[]);
ERROR: different dimensions 2 and 1
SELECT inner_product('{65504}'::half[], '{65504}'::half[]);
inner_product
---------------
4290774016
(1 row)
SELECT '{1,2}'::half[] <#> '{3,4}'::half[];
?column?
----------
-11
(1 row)
SELECT cosine_distance('{1,2}'::half[], '{2,4}'::half[]);
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{1,2}'::half[], '{0,0}'::half[]);
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{1,1}'::half[], '{1,1}'::half[]);
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{1,0}'::half[], '{0,2}'::half[]);
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('{1,1}'::half[], '{-1,-1}'::half[]);
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('{1,2}'::half[], '{3}'::half[]);
ERROR: different dimensions 2 and 1
SELECT cosine_distance('{1,1}'::half[], '{1.1,1.1}'::half[]);
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{1,1}'::half[], '{-1.1,-1.1}'::half[]);
cosine_distance
-----------------
2
(1 row)
SELECT '{1,2}'::half[] <=> '{2,4}'::half[];
?column?
----------
0
(1 row)
SELECT l1_distance('{0,0}'::half[], '{3,4}');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('{0,0}'::half[], '{0,1}');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('{1,2}'::half[], '{3}');
ERROR: different dimensions 2 and 1

View File

@@ -1,7 +1,7 @@
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t (val vector(3), val2 half[]);
INSERT INTO t (val, val2) VALUES ('[0,0,0]', '{0,0,0}'), ('[1,2,3]', '{1,2,3}'), ('[1,1,1]', '{1,1,1}'), (NULL, NULL);
CREATE TABLE t2 (val vector(3));
CREATE TABLE t2 (val vector(3), val2 half[]);
\copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/data.bin' WITH (FORMAT binary)

View File

@@ -13,29 +13,29 @@ 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;

42
test/sql/half.sql Normal file
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@@ -0,0 +1,42 @@
SELECT '1.5'::half;
SELECT '65504'::half;
SELECT '65505'::half;
SELECT '-65504'::half;
SELECT '-65505'::half;
SELECT ''::half;
SELECT ' '::half;
SELECT '-'::half;
SELECT ' 1.5'::half;
SELECT '1.5 '::half;
SELECT '1.5a'::half;
SELECT '{1,2,3}'::half[];
SELECT '65505'::integer::half;
SELECT 'NaN'::real::half;
SELECT 'Infinity'::real::half;
SELECT l2_distance('{0,0}'::half[], '{3,4}'::half[]);
SELECT l2_distance('{0,0}'::half[], '{0,1}'::half[]);
SELECT l2_distance('{1,2}'::half[], '{3}'::half[]);
SELECT '{0,0}'::half[] <-> '{3,4}'::half[];
SELECT inner_product('{1,2}'::half[], '{3,4}'::half[]);
SELECT inner_product('{1,2}'::half[], '{3}'::half[]);
SELECT inner_product('{65504}'::half[], '{65504}'::half[]);
SELECT '{1,2}'::half[] <#> '{3,4}'::half[];
SELECT cosine_distance('{1,2}'::half[], '{2,4}'::half[]);
SELECT cosine_distance('{1,2}'::half[], '{0,0}'::half[]);
SELECT cosine_distance('{1,1}'::half[], '{1,1}'::half[]);
SELECT cosine_distance('{1,0}'::half[], '{0,2}'::half[]);
SELECT cosine_distance('{1,1}'::half[], '{-1,-1}'::half[]);
SELECT cosine_distance('{1,2}'::half[], '{3}'::half[]);
SELECT cosine_distance('{1,1}'::half[], '{1.1,1.1}'::half[]);
SELECT cosine_distance('{1,1}'::half[], '{-1.1,-1.1}'::half[]);
SELECT '{1,2}'::half[] <=> '{2,4}'::half[];
SELECT l1_distance('{0,0}'::half[], '{3,4}');
SELECT l1_distance('{0,0}'::half[], '{0,1}');
SELECT l1_distance('{1,2}'::half[], '{3}');

View File

@@ -83,11 +83,32 @@ for my $i (0 .. $#operators)
push(@expected, $res);
}
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v $opclass);");
# Build index serially
$node->safe_psql("postgres", qq(
SET max_parallel_maintenance_workers = 0;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
# Test approximate results
my $min = $operator eq "<#>" ? 0.80 : 0.99;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
SET hnsw.enable_parallel_build = on;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

93
test/t/019_hnsw_half.pl Normal file
View File

@@ -0,0 +1,93 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SELECT i FROM tst ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my %actual_set = map { $_ => 1 } @actual_ids;
my @expected_ids = split("\n", $expected[$i]);
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
}
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v half[3]);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()]::numeric[]::half[] FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "{$r1,$r2,$r3}");
}
# Check each index type
my @operators = ("<->");
my @opclasses = ("half_l2_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", "SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;");
push(@expected, $res);
}
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v $opclass);");
my $min = $operator eq "<#>" ? 0.80 : 0.99;
test_recall($min, $operator);
}
done_testing();