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22 Commits

Author SHA1 Message Date
Andrew Kane
3c09df83f6 Updated readme [skip ci] 2024-03-31 22:52:51 -07:00
Andrew Kane
17e0058927 Improved recall test 2024-03-31 22:42:34 -07:00
Andrew Kane
3fc734fb36 Improved recall test [skip ci] 2024-03-31 22:38:17 -07:00
Andrew Kane
caca8990fc Use union to swap [skip ci] 2024-03-31 20:27:04 -07:00
Andrew Kane
b640d84381 Added todo [skip ci] 2024-03-31 20:13:15 -07:00
Andrew Kane
3efa99fe77 Added test for overflow [skip ci] 2024-03-31 20:11:28 -07:00
Andrew Kane
7087a45ea3 Improved halfvec_out code [skip ci] 2024-03-31 10:08:26 -07:00
Andrew Kane
5a229ba984 Check typmod when casting [skip ci] 2024-03-30 23:32:07 -07:00
Andrew Kane
56622e73fb Fixed underflow error 2024-03-30 15:04:33 -07:00
Andrew Kane
968173690e Changed casting to implicit 2024-03-30 10:28:38 -07:00
Andrew Kane
d82f6634fe Added dimension checks [skip ci] 2024-03-30 10:23:56 -07:00
Andrew Kane
4d041d9282 Fixed CI 2024-03-30 10:19:48 -07:00
Andrew Kane
e68db812aa Fixed underflow error 2024-03-30 10:06:21 -07:00
Andrew Kane
49bc34caf3 Make max dimensions consistent across types [skip ci] 2024-03-28 16:41:13 -07:00
Andrew Kane
4f1a379638 Added casting between vector and halfvec 2024-03-28 14:04:59 -07:00
Andrew Kane
45ef8f8a45 Improved code [skip ci] 2024-03-27 17:28:15 -07:00
Andrew Kane
6eedf78c25 Improved HnswNormValue [skip ci] 2024-03-27 17:19:58 -07:00
Andrew Kane
e2978d1365 Updated test [skip ci] 2024-03-27 17:09:38 -07:00
Andrew Kane
ccf44136dd Updated readme [skip ci] 2024-03-27 14:03:59 -07:00
Andrew Kane
daf27d5bd4 Fixed upgrade file [skip ci] 2024-03-27 13:51:12 -07:00
Andrew Kane
868498abec Fixed CI 2024-03-27 13:49:37 -07:00
Andrew Kane
264494b3e2 Added halfvec type 2024-03-27 13:47:19 -07:00
91 changed files with 892 additions and 5371 deletions

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@@ -40,21 +40,13 @@ jobs:
sudo apt-get install libipc-run-perl sudo apt-get install libipc-run-perl
- run: make prove_installcheck - run: make prove_installcheck
mac: mac:
runs-on: ${{ matrix.os }} runs-on: macos-latest
if: ${{ !startsWith(github.ref_name, 'windows') }} if: ${{ !startsWith(github.ref_name, 'windows') }}
strategy:
fail-fast: false
matrix:
include:
- postgres: 16
os: macos-14
- postgres: 14
os: macos-12
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1 - uses: ankane/setup-postgres@v1
with: with:
postgres-version: ${{ matrix.postgres }} postgres-version: 14
- run: make - run: make
env: env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter
@@ -62,19 +54,13 @@ jobs:
- run: make installcheck - run: make installcheck
- if: ${{ failure() }} - if: ${{ failure() }}
run: cat regression.diffs run: cat regression.diffs
# Homebrew Postgres does not enable TAP tests, so need to download
- run: | - run: |
brew install cpanm brew install cpanm
cpanm --notest IPC::Run cpanm --notest IPC::Run
wget -q https://github.com/postgres/postgres/archive/refs/tags/$TAG.tar.gz wget -q https://github.com/postgres/postgres/archive/refs/tags/REL_14_10.tar.gz
tar xf $TAG.tar.gz tar xf REL_14_10.tar.gz
mv postgres-$TAG postgres - run: make prove_installcheck PROVE_FLAGS="-I ./postgres-REL_14_10/src/test/perl" PERL5LIB="/Users/runner/perl5/lib/perl5"
env: - run: make clean && /usr/local/opt/llvm@15/bin/scan-build --status-bugs make
TAG: ${{ matrix.postgres == 16 && 'REL_16_2' || 'REL_14_11' }}
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres/src/test/perl -I ./test/perl"
env:
PERL5LIB: /Users/runner/perl5/lib/perl5
- run: make clean && $(brew --prefix llvm@15)/bin/scan-build --status-bugs make
env: env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING PG_CFLAGS: -DUSE_ASSERT_CHECKING
windows: windows:
@@ -123,6 +109,6 @@ jobs:
- uses: ankane/setup-postgres-valgrind@v1 - uses: ankane/setup-postgres-valgrind@v1
with: with:
postgres-version: 16 postgres-version: 16
- run: make OPTFLAGS="" - run: make
- run: sudo --preserve-env=PG_CONFIG make install - run: sudo --preserve-env=PG_CONFIG make install
- run: make installcheck - run: make installcheck

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@@ -1,14 +1,6 @@
## 0.7.0 (unreleased) ## 0.7.0 (unreleased)
- Added `halfvec` type - Added `halfvec` type
- Added `sparsevec` type
- Added support for `bit` vectors to HNSW
- Added `hamming_distance` function
- Added `jaccard_distance` function
- Added `quantize_binary` function
- Added `subvector` function
- Added CPU dispatching for distance functions on Linux x86-64
- Updated comparison operators to support vectors with different dimensions
## 0.6.2 (2024-03-18) ## 0.6.2 (2024-03-18)

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@@ -3,8 +3,8 @@ EXTVERSION = 0.6.2
MODULE_big = vector MODULE_big = vector
DATA = $(wildcard sql/*--*.sql) DATA = $(wildcard sql/*--*.sql)
OBJS = src/bitvector.o src/halfutils.o src/halfvec.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/sparsevec.o src/vector.o OBJS = src/halfvec.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/halfvec.h src/sparsevec.h src/vector.h HEADERS = src/halfvec.h src/vector.h
TESTS = $(wildcard test/sql/*.sql) TESTS = $(wildcard test/sql/*.sql)
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS)) REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))
@@ -12,7 +12,7 @@ REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
OPTFLAGS = -march=native OPTFLAGS = -march=native
# Mac ARM doesn't always support -march=native # Mac ARM doesn't support -march=native
ifeq ($(shell uname -s), Darwin) ifeq ($(shell uname -s), Darwin)
ifeq ($(shell uname -p), arm) ifeq ($(shell uname -p), arm)
# no difference with -march=armv8.5-a # no difference with -march=armv8.5-a

View File

@@ -1,10 +1,10 @@
EXTENSION = vector EXTENSION = vector
EXTVERSION = 0.6.2 EXTVERSION = 0.6.2
OBJS = src\bitvector.obj src\halfutils.obj src\halfvec.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\sparsevec.obj src\vector.obj OBJS = src\halfvec.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\halfvec.h src\sparsevec.h src\vector.h HEADERS = src\halfvec.h src\vector.h
REGRESS = bit_functions btree cast copy halfvec_functions halfvec_input hnsw_bit_hamming hnsw_bit_jaccard hnsw_halfvec_cosine hnsw_halfvec_ip hnsw_halfvec_l2 hnsw_options hnsw_sparsevec_cosine hnsw_sparsevec_ip hnsw_sparsevec_l2 hnsw_unlogged hnsw_vector_cosine hnsw_vector_ip hnsw_vector_l2 ivfflat_options ivfflat_unlogged ivfflat_vector_cosine ivfflat_vector_ip ivfflat_vector_l2 sparsevec_functions sparsevec_input vector_functions vector_input REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION) REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
# For /arch flags # For /arch flags

232
README.md
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@@ -221,24 +221,7 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops); CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
``` ```
Hamming distance - unreleased Vectors with up to 2,000 dimensions can be indexed.
```sql
CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
```
Jaccard distance - unreleased
```sql
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
```
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (unreleased)
- `bit` - up to 64,000 dimensions (unreleased)
- `sparsevec` - up to 1,000 non-zero elements (unreleased)
### Index Options ### Index Options
@@ -343,10 +326,7 @@ Cosine distance
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100); CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
``` ```
Supported types are: Vectors with up to 2,000 dimensions can be indexed.
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (unreleased)
### Query Options ### Query Options
@@ -420,101 +400,27 @@ Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id); CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
``` ```
## Half Vectors ## Types
*Unreleased* - `vector`
- `halfvec`
Use the `halfvec` type to store half-precision vectors ## Half-Precision
```sql ```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3)); CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));
``` INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
## Half Indexing
*Unreleased*
Index vectors at half precision for smaller indexes and faster build times
```sql
CREATE INDEX ON items USING hnsw ((embedding::halfvec(3)) halfvec_l2_ops); CREATE INDEX ON items USING hnsw ((embedding::halfvec(3)) halfvec_l2_ops);
``` ```
Get the nearest neighbors
```sql ```sql
SELECT * FROM items ORDER BY embedding::halfvec(3) <-> '[1,2,3]' LIMIT 5; SELECT id FROM items ORDER BY embedding::halfvec(3) <-> '[1,2,3]' LIMIT 5;
``` ```
## Binary Vectors
Use the `bit` type to store binary vectors ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py))
```sql ```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3)); SELECT id FROM (
INSERT INTO items (embedding) VALUES ('000'), ('111'); SELECT * FROM items ORDER BY embedding::halfvec(3) <-> '[1,2,3]' LIMIT 20
``` ) ORDER BY embedding <-> '[1,2,3]' LIMIT 5;
Get the nearest neighbors by Hamming distance
```sql
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Or (unreleased)
```sql
SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
```
Also supports Jaccard distance (`<%>`)
## Binary Quantization
*Unreleased*
Use expression indexing for binary quantization
```sql
CREATE INDEX ON items USING hnsw ((quantize_binary(embedding)::bit(3)) bit_hamming_ops);
```
Get the nearest neighbors by Hamming distance
```sql
SELECT * FROM items ORDER BY quantize_binary(embedding)::bit(3) <~> quantize_binary('[1,-2,3]') LIMIT 5;
```
Re-rank by the original vectors for better recall
```sql
SELECT * FROM (
SELECT * FROM items ORDER BY quantize_binary(embedding)::bit(3) <~> quantize_binary('[1,-2,3]') LIMIT 20
) ORDER BY embedding <=> '[1,-2,3]' LIMIT 5;
```
## Sparse Vectors
*Unreleased*
Use the `sparsevec` type to store sparse vectors
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding sparsevec(5));
```
Insert vectors
```sql
INSERT INTO items (embedding) VALUES ('{1:1,3:2,5:3}/5'), ('{1:4,3:5,5:6}/5');
```
Note: The format is `{index1:value1,index2:value2,...}/dimensions` and indices start at 1 like SQL arrays
Get the nearest neighbors by L2 distance
```sql
SELECT * FROM items ORDER BY embedding <-> '{1:3,3:1,5:2}/5' LIMIT 5;
``` ```
## Hybrid Search ## Hybrid Search
@@ -528,47 +434,11 @@ SELECT id, content FROM items, plainto_tsquery('hello search') query
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. 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.
## Subvector Indexing
*Unreleased*
Use expression indexing to index subvectors
```sql
CREATE INDEX ON items USING hnsw ((subvector(embedding, 1, 3)::vector(3)) vector_cosine_ops);
```
Get the nearest neighbors by cosine distance
```sql
SELECT * FROM items ORDER BY subvector(embedding, 1, 3)::vector(3) <=> subvector('[1,2,3,4,5]'::vector, 1, 3) LIMIT 5;
```
Re-rank by the full vectors for better recall
```sql
SELECT * FROM (
SELECT * FROM items ORDER BY subvector(embedding, 1, 3)::vector(3) <=> subvector('[1,2,3,4,5]'::vector, 1, 3) LIMIT 20
) ORDER BY embedding <=> '[1,2,3,4,5]' LIMIT 5;
```
## Performance ## Performance
### Tuning ### Tuning
Use a tool like [PgTune](https://pgtune.leopard.in.ua/) to set initial values for Postgres server parameters. For instance, `shared_buffers` should typically be 25% of the servers memory. You can find the config file with: Use a tool like [PgTune](https://pgtune.leopard.in.ua/) to set initial values for Postgres server parameters.
```sql
SHOW config_file;
```
And check individual settings with:
```sql
SHOW shared_buffers;
```
Be sure to restart Postgres for changes to take effect.
### Loading ### Loading
@@ -757,6 +627,18 @@ and query with:
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5; SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
``` ```
#### Are binary vectors supported?
You can store binary vectors and perform exact nearest neighbor search by Hamming distance in Postgres without an extension ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py)).
```tsql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES (B'000'), (B'111');
SELECT * FROM items ORDER BY bit_count(embedding # B'101') LIMIT 5;
```
Indexing is not currently supported.
#### Do indexes need to fit into memory? #### Do indexes need to fit into memory?
No, but like other index types, youll likely see better performance if they do. You can get the size of an index with: No, but like other index types, youll likely see better performance if they do. You can get the size of an index with:
@@ -828,14 +710,9 @@ Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosi
## Reference ## Reference
- [Vector](#vector-type)
- [Halfvec](#halfvec-type)
- [Bit](#bit-type)
- [Sparsevec](#sparsevec-type)
### Vector Type ### 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 ### Vector Operators
@@ -856,12 +733,10 @@ cosine_distance(vector, vector) → double precision | cosine distance |
inner_product(vector, vector) → double precision | inner product | inner_product(vector, vector) → double precision | inner product |
l2_distance(vector, vector) → double precision | Euclidean distance | l2_distance(vector, vector) → double precision | Euclidean distance |
l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0 l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
quantize_binary(vector) → bit | quantize | unreleased
subvector(vector, integer, integer) → vector | subvector | unreleased
vector_dims(vector) → integer | number of dimensions | vector_dims(vector) → integer | number of dimensions |
vector_norm(vector) → double precision | Euclidean norm | vector_norm(vector) → double precision | Euclidean norm |
### Vector Aggregate Functions ### Aggregate Functions
Function | Description | Added Function | Description | Added
--- | --- | --- --- | --- | ---
@@ -876,59 +751,18 @@ Each half vector takes `2 * dimensions + 8` bytes of storage. Each element is a
Operator | Description | Added Operator | Description | Added
--- | --- | --- --- | --- | ---
<-> | Euclidean distance | unreleased <-> | Euclidean distance | 0.7.0
<#> | negative inner product | unreleased <#> | negative inner product | 0.7.0
<=> | cosine distance | unreleased <=> | cosine distance | 0.7.0
### Halfvec Functions ### Halfvec Functions
Function | Description | Added Function | Description | Added
--- | --- | --- --- | --- | ---
cosine_distance(halfvec, halfvec) → double precision | cosine distance | unreleased cosine_distance(halfvec, halfvec) → double precision | cosine distance | 0.7.0
inner_product(halfvec, halfvec) → double precision | inner product | unreleased inner_product(halfvec, halfvec) → double precision | inner product | 0.7.0
l2_distance(halfvec, halfvec) → double precision | Euclidean distance | unreleased l2_distance(halfvec, halfvec) → double precision | Euclidean distance | 0.7.0
l1_distance(halfvec, halfvec) → double precision | taxicab distance | unreleased l1_distance(halfvec, halfvec) → double precision | taxicab distance | 0.7.0
quantize_binary(halfvec) → bit | quantize | unreleased
subvector(halfvec, integer, integer) → halfvec | subvector | unreleased
### Bit Type
Each bit vector takes `dimensions / 8 + 8` bytes of storage. See the [Postgres docs](https://www.postgresql.org/docs/current/datatype-bit.html) for more info.
### Bit Operators
Operator | Description | Added
--- | --- | ---
<~> | Hamming distance | unreleased
<%> | Jaccard distance | unreleased
### Bit Functions
Function | Description | Added
--- | --- | ---
hamming_distance(bit, bit) → double precision | Hamming distance | unreleased
jaccard_distance(bit, bit) → double precision | Jaccard distance | unreleased
### Sparsevec Type
Each sparse vector takes `8 * non-zero elements + 16` bytes of storage. Each element is a single-precision floating-point number, and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Sparse vectors can have up to 16,000 non-zero elements.
### Sparsevec Operators
Operator | Description | Added
--- | --- | ---
<-> | Euclidean distance | unreleased
<#> | negative inner product | unreleased
<=> | cosine distance | unreleased
### Sparsevec Functions
Function | Description | Added
--- | --- | ---
cosine_distance(sparsevec, sparsevec) → double precision | cosine distance | unreleased
inner_product(sparsevec, sparsevec) → double precision | inner product | unreleased
l2_distance(sparsevec, sparsevec) → double precision | Euclidean distance | unreleased
l1_distance(sparsevec, sparsevec) → double precision | taxicab distance | unreleased
## Installation Notes - Linux and Mac ## Installation Notes - Linux and Mac

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@@ -1,38 +1,6 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION -- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.0'" to load this file. \quit \echo Use "ALTER EXTENSION vector UPDATE TO '0.7.0'" to load this file. \quit
CREATE FUNCTION quantize_binary(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(vector, int, int) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
);
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit);
CREATE TYPE halfvec; CREATE TYPE halfvec;
CREATE FUNCTION halfvec_in(cstring, oid, integer) RETURNS halfvec CREATE FUNCTION halfvec_in(cstring, oid, integer) RETURNS halfvec
@@ -74,21 +42,12 @@ CREATE FUNCTION l1_distance(halfvec, halfvec) RETURNS float8
CREATE FUNCTION halfvec_norm(halfvec) RETURNS float8 CREATE FUNCTION halfvec_norm(halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION quantize_binary(halfvec) RETURNS bit
AS 'MODULE_PATHNAME', 'halfvec_quantize_binary' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(halfvec, int, int) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8 CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8 CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_spherical_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -140,27 +99,6 @@ CREATE OPERATOR <=> (
COMMUTATOR = '<=>' COMMUTATOR = '<=>'
); );
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec),
FUNCTION 3 l2_distance(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 halfvec_norm(halfvec);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 halfvec_norm(halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 halfvec_norm(halfvec);
CREATE OPERATOR CLASS halfvec_l2_ops CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING hnsw AS FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops, OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
@@ -184,100 +122,7 @@ CREATE FUNCTION vector_to_halfvec(vector, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (halfvec AS vector) CREATE CAST (halfvec AS vector)
WITH FUNCTION halfvec_to_vector(halfvec, integer, boolean) AS IMPLICIT; WITH FUNCTION halfvec_to_vector(halfvec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (vector AS halfvec) CREATE CAST (vector AS halfvec)
WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT; WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS ASSIGNMENT;
CREATE TYPE sparsevec;
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE sparsevec (
INPUT = sparsevec_in,
OUTPUT = sparsevec_out,
TYPMOD_IN = sparsevec_typmod_in,
RECEIVE = sparsevec_recv,
SEND = sparsevec_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_norm(sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (sparsevec AS sparsevec)
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS vector)
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS sparsevec)
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
CREATE OPERATOR <-> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR CLASS sparsevec_l2_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_ip_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_cosine_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 2 sparsevec_norm(sparsevec);

View File

@@ -1,7 +1,7 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION -- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "CREATE EXTENSION vector" to load this file. \quit \echo Use "CREATE EXTENSION vector" to load this file. \quit
-- vector type -- type
CREATE TYPE vector; CREATE TYPE vector;
@@ -29,7 +29,7 @@ CREATE TYPE vector (
STORAGE = external STORAGE = external
); );
-- vector functions -- functions
CREATE FUNCTION l2_distance(vector, vector) RETURNS float8 CREATE FUNCTION l2_distance(vector, vector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -58,13 +58,7 @@ CREATE FUNCTION vector_sub(vector, vector) RETURNS vector
CREATE FUNCTION vector_mul(vector, vector) RETURNS vector CREATE FUNCTION vector_mul(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION quantize_binary(vector) RETURNS bit -- private functions
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(vector, int, int) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- vector private functions
CREATE FUNCTION vector_lt(vector, vector) RETURNS bool CREATE FUNCTION vector_lt(vector, vector) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -105,7 +99,7 @@ CREATE FUNCTION vector_avg(double precision[]) RETURNS vector
CREATE FUNCTION vector_combine(double precision[], double precision[]) RETURNS double precision[] CREATE FUNCTION vector_combine(double precision[], double precision[]) RETURNS double precision[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- vector aggregates -- aggregates
CREATE AGGREGATE avg(vector) ( CREATE AGGREGATE avg(vector) (
SFUNC = vector_accum, SFUNC = vector_accum,
@@ -123,7 +117,7 @@ CREATE AGGREGATE sum(vector) (
PARALLEL = SAFE PARALLEL = SAFE
); );
-- vector cast functions -- cast functions
CREATE FUNCTION vector(vector, integer, boolean) RETURNS vector CREATE FUNCTION vector(vector, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -143,7 +137,7 @@ CREATE FUNCTION array_to_vector(numeric[], integer, boolean) RETURNS vector
CREATE FUNCTION vector_to_float4(vector, integer, boolean) RETURNS real[] CREATE FUNCTION vector_to_float4(vector, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- vector casts -- casts
CREATE CAST (vector AS vector) CREATE CAST (vector AS vector)
WITH FUNCTION vector(vector, integer, boolean) AS IMPLICIT; WITH FUNCTION vector(vector, integer, boolean) AS IMPLICIT;
@@ -163,7 +157,7 @@ CREATE CAST (double precision[] AS vector)
CREATE CAST (numeric[] AS vector) CREATE CAST (numeric[] AS vector)
WITH FUNCTION array_to_vector(numeric[], integer, boolean) AS ASSIGNMENT; WITH FUNCTION array_to_vector(numeric[], integer, boolean) AS ASSIGNMENT;
-- vector operators -- operators
CREATE OPERATOR <-> ( CREATE OPERATOR <-> (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l2_distance, LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l2_distance,
@@ -246,7 +240,7 @@ CREATE ACCESS METHOD hnsw TYPE INDEX HANDLER hnswhandler;
COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method'; COMMENT ON ACCESS METHOD hnsw IS 'hnsw index access method';
-- vector opclasses -- opclasses
CREATE OPERATOR CLASS vector_ops CREATE OPERATOR CLASS vector_ops
DEFAULT FOR TYPE vector USING btree AS DEFAULT FOR TYPE vector USING btree AS
@@ -294,34 +288,6 @@ CREATE OPERATOR CLASS vector_cosine_ops
FUNCTION 1 vector_negative_inner_product(vector, vector), FUNCTION 1 vector_negative_inner_product(vector, vector),
FUNCTION 2 vector_norm(vector); FUNCTION 2 vector_norm(vector);
-- bit functions
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <~> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = hamming_distance,
COMMUTATOR = '<~>'
);
CREATE OPERATOR <%> (
LEFTARG = bit, RIGHTARG = bit, PROCEDURE = jaccard_distance,
COMMUTATOR = '<%>'
);
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit);
CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit);
-- halfvec type -- halfvec type
CREATE TYPE halfvec; CREATE TYPE halfvec;
@@ -367,12 +333,6 @@ CREATE FUNCTION l1_distance(halfvec, halfvec) RETURNS float8
CREATE FUNCTION halfvec_norm(halfvec) RETURNS float8 CREATE FUNCTION halfvec_norm(halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION quantize_binary(halfvec) RETURNS bit
AS 'MODULE_PATHNAME', 'halfvec_quantize_binary' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION subvector(halfvec, int, int) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_subvector' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec private functions -- halfvec private functions
CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8 CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
@@ -381,9 +341,6 @@ CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8 CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_spherical_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- halfvec cast functions -- halfvec cast functions
CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec
@@ -443,27 +400,6 @@ CREATE OPERATOR <=> (
-- halfvec opclasses -- halfvec opclasses
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec),
FUNCTION 3 l2_distance(halfvec, halfvec);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 halfvec_norm(halfvec);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING ivfflat AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 halfvec_norm(halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 halfvec_norm(halfvec);
CREATE OPERATOR CLASS halfvec_l2_ops CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING hnsw AS FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops, OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
@@ -493,110 +429,3 @@ CREATE CAST (halfvec AS vector)
CREATE CAST (vector AS halfvec) CREATE CAST (vector AS halfvec)
WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT; WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT;
--- sparsevec type
CREATE TYPE sparsevec;
CREATE FUNCTION sparsevec_in(cstring, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_out(sparsevec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_recv(internal, oid, integer) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_send(sparsevec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE sparsevec (
INPUT = sparsevec_in,
OUTPUT = sparsevec_out,
TYPMOD_IN = sparsevec_typmod_in,
RECEIVE = sparsevec_recv,
SEND = sparsevec_send,
STORAGE = external
);
-- sparsevec functions
CREATE FUNCTION l2_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_norm(sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec private functions
CREATE FUNCTION sparsevec_l2_squared_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_negative_inner_product(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec cast functions
CREATE FUNCTION sparsevec(sparsevec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_sparsevec(vector, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec casts
CREATE CAST (sparsevec AS sparsevec)
WITH FUNCTION sparsevec(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS vector)
WITH FUNCTION sparsevec_to_vector(sparsevec, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS sparsevec)
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
-- sparsevec operators
CREATE OPERATOR <-> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
-- sparsevec opclasses
CREATE OPERATOR CLASS sparsevec_l2_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <-> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_l2_squared_distance(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_ip_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <#> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec);
CREATE OPERATOR CLASS sparsevec_cosine_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <=> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 sparsevec_negative_inner_product(sparsevec, sparsevec),
FUNCTION 2 sparsevec_norm(sparsevec);

View File

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

View File

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

View File

@@ -1,156 +0,0 @@
#include "postgres.h"
#include "halfutils.h"
#include "halfvec.h"
#ifdef HALFVEC_DISPATCH
#include <immintrin.h>
#if defined(HAVE__GET_CPUID)
#include <cpuid.h>
#elif defined(HAVE__CPUID)
#include <intrin.h>
#endif
#ifdef _MSC_VER
#define TARGET_F16C_FMA
#else
#define TARGET_F16C_FMA __attribute__((target("f16c,fma")))
#endif
#endif
float (*HalfvecL2SquaredDistance) (int dim, half * ax, half * bx);
float (*HalfvecInnerProduct) (int dim, half * ax, half * bx);
static float
HalfvecL2SquaredDistanceDefault(int dim, half * ax, half * bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
return distance;
}
#ifdef HALFVEC_DISPATCH
TARGET_F16C_FMA static float
HalfvecL2SquaredDistanceF16cFma(int dim, half * ax, half * bx)
{
float distance;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 dist = _mm256_setzero_ps();
for (i = 0; i < count; i += 8)
{
__m128i axi = _mm_loadu_si128((__m128i *) (ax + i));
__m128i bxi = _mm_loadu_si128((__m128i *) (bx + i));
__m256 axs = _mm256_cvtph_ps(axi);
__m256 bxs = _mm256_cvtph_ps(bxi);
__m256 diff = _mm256_sub_ps(axs, bxs);
dist = _mm256_fmadd_ps(diff, diff, dist);
}
_mm256_storeu_ps(s, dist);
distance = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
for (; i < dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
return distance;
}
#endif
static float
HalfvecInnerProductDefault(int dim, half * ax, half * bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
return distance;
}
#ifdef HALFVEC_DISPATCH
TARGET_F16C_FMA static float
HalfvecInnerProductF16cFma(int dim, half * ax, half * bx)
{
float distance;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 dist = _mm256_setzero_ps();
for (i = 0; i < count; i += 8)
{
__m128i axi = _mm_loadu_si128((__m128i *) (ax + i));
__m128i bxi = _mm_loadu_si128((__m128i *) (bx + i));
__m256 axs = _mm256_cvtph_ps(axi);
__m256 bxs = _mm256_cvtph_ps(bxi);
dist = _mm256_fmadd_ps(axs, bxs, dist);
}
_mm256_storeu_ps(s, dist);
distance = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
for (; i < dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
return distance;
}
#endif
#ifdef HALFVEC_DISPATCH
#define CPU_FEATURE_FMA (1 << 12)
#define CPU_FEATURE_F16C (1 << 29)
static bool
SupportsCpuFeature(unsigned int feature)
{
unsigned int exx[4] = {0, 0, 0, 0};
#if defined(HAVE__GET_CPUID)
__get_cpuid(1, &exx[0], &exx[1], &exx[2], &exx[3]);
#elif defined(HAVE__CPUID)
__cpuid(exx, 1);
#endif
return (exx[2] & feature) == feature;
}
#endif
void
HalfvecInit(void)
{
/*
* Could skip pointer when single function, but no difference in
* performance
*/
HalfvecL2SquaredDistance = HalfvecL2SquaredDistanceDefault;
HalfvecInnerProduct = HalfvecInnerProductDefault;
#ifdef HALFVEC_DISPATCH
if (SupportsCpuFeature(CPU_FEATURE_FMA | CPU_FEATURE_F16C))
{
HalfvecL2SquaredDistance = HalfvecL2SquaredDistanceF16cFma;
HalfvecInnerProduct = HalfvecInnerProductF16cFma;
}
#endif
}

View File

@@ -1,254 +0,0 @@
#ifndef HALFUTILS_H
#define HALFUTILS_H
#include <math.h>
#include "common/shortest_dec.h"
#include "halfvec.h"
#ifdef F16C_SUPPORT
#include <immintrin.h>
#endif
extern float (*HalfvecL2SquaredDistance) (int dim, half * ax, half * bx);
extern float (*HalfvecInnerProduct) (int dim, half * ax, half * bx);
void HalfvecInit(void);
/*
* Check if half is NaN
*/
static inline bool
HalfIsNan(half num)
{
#ifdef FLT16_SUPPORT
return isnan(num);
#else
return (num & 0x7C00) == 0x7C00 && (num & 0x7FFF) != 0x7C00;
#endif
}
/*
* Check if half is infinite
*/
static inline bool
HalfIsInf(half num)
{
#ifdef FLT16_SUPPORT
return isinf(num);
#else
return (num & 0x7FFF) == 0x7C00;
#endif
}
/*
* Convert a half to a float4
*/
static inline float
HalfToFloat4(half num)
{
#if defined(F16C_SUPPORT)
return _cvtsh_ss(num);
#elif defined(FLT16_SUPPORT)
return (float) num;
#else
/* TODO Improve performance */
/* Assumes same endianness for floats and integers */
union
{
float f;
uint32 i;
} swapfloat;
union
{
half h;
uint16 i;
} swaphalf;
uint16 bin;
uint32 exponent;
uint32 mantissa;
uint32 result;
swaphalf.h = num;
bin = swaphalf.i;
exponent = (bin & 0x7C00) >> 10;
mantissa = bin & 0x03FF;
/* Sign */
result = (bin & 0x8000) << 16;
if (unlikely(exponent == 31))
{
if (mantissa == 0)
{
/* Infinite */
result |= 0x7F800000;
}
else
{
/* NaN */
result |= 0x7FC00000;
}
}
else if (unlikely(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;
}
}
else
{
/* Normal */
result |= (exponent - 15 + 127) << 23;
}
result |= mantissa << 13;
swapfloat.i = result;
return swapfloat.f;
#endif
}
/*
* Convert a float4 to a half
*/
static inline half
Float4ToHalfUnchecked(float num)
{
#if defined(F16C_SUPPORT)
return _cvtss_sh(num, 0);
#elif defined(FLT16_SUPPORT)
return (_Float16) num;
#else
/* TODO Improve performance */
/* Assumes same endianness for floats and integers */
union
{
float f;
uint32 i;
} swapfloat;
union
{
half h;
uint16 i;
} swaphalf;
uint32 bin;
int exponent;
int mantissa;
uint16 result;
swapfloat.f = num;
bin = swapfloat.i;
exponent = (bin & 0x7F800000) >> 23;
mantissa = bin & 0x007FFFFF;
/* Sign */
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;
}
}
swaphalf.i = result;
return swaphalf.h;
#endif
}
/*
* Convert a float4 to a half
*/
static inline half
Float4ToHalf(float num)
{
half result = Float4ToHalfUnchecked(num);
if (unlikely(HalfIsInf(result)) && !isinf(num))
{
char *buf = palloc(FLOAT_SHORTEST_DECIMAL_LEN);
float_to_shortest_decimal_buf(num, buf);
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type halfvec", buf)));
}
return result;
}
#endif

View File

@@ -2,11 +2,9 @@
#include <math.h> #include <math.h>
#include "bitvector.h"
#include "catalog/pg_type.h" #include "catalog/pg_type.h"
#include "common/shortest_dec.h" #include "common/shortest_dec.h"
#include "fmgr.h" #include "fmgr.h"
#include "halfutils.h"
#include "halfvec.h" #include "halfvec.h"
#include "lib/stringinfo.h" #include "lib/stringinfo.h"
#include "libpq/pqformat.h" #include "libpq/pqformat.h"
@@ -23,6 +21,45 @@
#define TYPALIGN_INT 'i' #define TYPALIGN_INT 'i'
#endif #endif
/*
* Check if half is NaN
*/
static inline bool
HalfIsNan(half num)
{
#ifdef FLT16_SUPPORT
return isnan(num);
#else
return (num & 0x7C00) == 0x7C00 && (num & 0x7FFF) != 0x7C00;
#endif
}
/*
* Check if half is infinite
*/
static inline bool
HalfIsInf(half num)
{
#ifdef FLT16_SUPPORT
return isinf(num);
#else
return (num & 0x7FFF) == 0x7C00;
#endif
}
/*
* Check if half is zero
*/
static inline bool
HalfIsZero(half num)
{
#ifdef FLT16_SUPPORT
return num == 0;
#else
return (num & 0x7FFF) == 0x0000;
#endif
}
/* /*
* Get a half from a message buffer * Get a half from a message buffer
*/ */
@@ -55,6 +92,207 @@ pq_sendhalf(StringInfo buf, half h)
pq_sendint16(buf, swap.i); pq_sendint16(buf, swap.i);
} }
/*
* Convert a half to a float4
*/
float
HalfToFloat4(half num)
{
#ifdef FLT16_SUPPORT
return (float) num;
#else
/* TODO Improve performance */
/* Assumes same endianness for floats and integers */
union
{
float f;
uint32 i;
} swapfloat;
union
{
half h;
uint16 i;
} swaphalf;
uint16 bin;
uint32 exponent;
uint32 mantissa;
uint32 result;
swaphalf.h = num;
bin = swaphalf.i;
exponent = (bin & 0x7C00) >> 10;
mantissa = bin & 0x03FF;
/* Sign */
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;
}
swapfloat.i = result;
return swapfloat.f;
#endif
}
/*
* Convert a float4 to a half
*/
half
Float4ToHalfUnchecked(float num)
{
#ifdef FLT16_SUPPORT
return (_Float16) num;
#else
/* TODO Improve performance */
/* Assumes same endianness for floats and integers */
union
{
float f;
uint32 i;
} swapfloat;
union
{
half h;
uint16 i;
} swaphalf;
uint32 bin;
int exponent;
int mantissa;
uint16 result;
swapfloat.f = num;
bin = swapfloat.i;
exponent = (bin & 0x7F800000) >> 23;
mantissa = bin & 0x007FFFFF;
/* Sign */
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;
}
}
swaphalf.i = result;
return swaphalf.h;
#endif
}
/*
* Convert a float4 to a half
*/
half
Float4ToHalf(float num)
{
half result = Float4ToHalfUnchecked(num);
if (unlikely(HalfIsInf(result)) && !isinf(num))
float_overflow_error();
if (unlikely(HalfIsZero(result)) && num != 0.0)
float_underflow_error();
return result;
}
/* /*
* Ensure same dimensions * Ensure same dimensions
*/ */
@@ -146,6 +384,24 @@ halfvec_isspace(char ch)
return false; return false;
} }
#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
/* /*
* Convert textual representation to internal representation * Convert textual representation to internal representation
*/ */
@@ -157,33 +413,27 @@ halfvec_in(PG_FUNCTION_ARGS)
int32 typmod = PG_GETARG_INT32(2); int32 typmod = PG_GETARG_INT32(2);
half x[HALFVEC_MAX_DIM]; half x[HALFVEC_MAX_DIM];
int dim = 0; int dim = 0;
char *pt = lit; char *pt;
char *stringEnd;
HalfVector *result; HalfVector *result;
char *litcopy = pstrdup(lit);
char *str = litcopy;
while (halfvec_isspace(*pt)) while (halfvec_isspace(*str))
pt++; str++;
if (*pt != '[') if (*str != '[')
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type halfvec: \"%s\"", lit), errmsg("malformed halfvec literal: \"%s\"", lit),
errdetail("Vector contents must start with \"[\"."))); errdetail("Vector contents must start with \"[\".")));
pt++; str++;
pt = strtok(str, ",");
stringEnd = pt;
while (halfvec_isspace(*pt)) while (pt != NULL && *stringEnd != ']')
pt++;
if (*pt == ']')
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("halfvec must have at least 1 dimension")));
for (;;)
{ {
float val;
char *stringEnd;
if (dim == HALFVEC_MAX_DIM) if (dim == HALFVEC_MAX_DIM)
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED), (errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
@@ -198,56 +448,61 @@ halfvec_in(PG_FUNCTION_ARGS)
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type halfvec: \"%s\"", lit))); errmsg("invalid input syntax for type halfvec: \"%s\"", lit)));
errno = 0; /* Use strtof like float4in to avoid a double-rounding problem */
x[dim] = Float4ToHalf(strtof(pt, &stringEnd));
/* Postgres sets LC_NUMERIC to C on startup */ CheckElement(x[dim]);
val = strtof(pt, &stringEnd); dim++;
if (stringEnd == pt) if (stringEnd == pt)
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type halfvec: \"%s\"", lit))); errmsg("invalid input syntax for type halfvec: \"%s\"", lit)));
x[dim] = Float4ToHalfUnchecked(val); while (halfvec_isspace(*stringEnd))
stringEnd++;
/* Check for range error like float4in */ if (*stringEnd != '\0' && *stringEnd != ']')
if ((errno == ERANGE && isinf(val)) || (HalfIsInf(x[dim]) && !isinf(val)))
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type halfvec", pnstrdup(pt, stringEnd - pt))));
CheckElement(x[dim]);
dim++;
pt = stringEnd;
while (halfvec_isspace(*pt))
pt++;
if (*pt == ',')
pt++;
else if (*pt == ']')
{
pt++;
break;
}
else
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type halfvec: \"%s\"", lit))); errmsg("invalid input syntax for type halfvec: \"%s\"", lit)));
pt = strtok(NULL, ",");
} }
/* Only whitespace is allowed after the closing brace */ if (stringEnd == NULL || *stringEnd != ']')
while (halfvec_isspace(*pt))
pt++;
if (*pt != '\0')
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type halfvec: \"%s\"", lit), errmsg("malformed halfvec literal: \"%s\"", lit),
errdetail("Unexpected end of input.")));
stringEnd++;
/* Only whitespace is allowed after the closing brace */
while (halfvec_isspace(*stringEnd))
stringEnd++;
if (*stringEnd != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed halfvec literal: \"%s\"", lit),
errdetail("Junk after closing right brace."))); errdetail("Junk after closing right brace.")));
CheckDim(dim); /* Ensure no consecutive delimiters since strtok skips */
for (pt = lit + 1; *pt != '\0'; pt++)
{
if (pt[-1] == ',' && *pt == ',')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed halfvec literal: \"%s\"", lit)));
}
if (dim < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("halfvec must have at least 1 dimension")));
pfree(litcopy);
CheckExpectedDim(typmod, dim); CheckExpectedDim(typmod, dim);
result = InitHalfVector(dim); result = InitHalfVector(dim);
@@ -517,7 +772,11 @@ vector_to_halfvec(PG_FUNCTION_ARGS)
result = InitHalfVector(vec->dim); result = InitHalfVector(vec->dim);
for (int i = 0; i < vec->dim; i++) for (int i = 0; i < vec->dim; i++)
result->x[i] = Float4ToHalf(vec->x[i]); {
result->x[i] = Float4ToHalfUnchecked(vec->x[i]);
/* TODO Better error for overflow */
CheckElement(result->x[i]);
}
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
@@ -531,10 +790,21 @@ halfvec_l2_distance(PG_FUNCTION_ARGS)
{ {
HalfVector *a = PG_GETARG_HALFVEC_P(0); HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1); HalfVector *b = PG_GETARG_HALFVEC_P(1);
half *ax = a->x;
half *bx = b->x;
float distance = 0.0;
CheckDims(a, b); CheckDims(a, b);
PG_RETURN_FLOAT8(sqrt((double) HalfvecL2SquaredDistance(a->dim, a->x, b->x))); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
PG_RETURN_FLOAT8(sqrt((double) distance));
} }
/* /*
@@ -546,10 +816,21 @@ halfvec_l2_squared_distance(PG_FUNCTION_ARGS)
{ {
HalfVector *a = PG_GETARG_HALFVEC_P(0); HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1); HalfVector *b = PG_GETARG_HALFVEC_P(1);
half *ax = a->x;
half *bx = b->x;
float distance = 0.0;
CheckDims(a, b); CheckDims(a, b);
PG_RETURN_FLOAT8((double) HalfvecL2SquaredDistance(a->dim, a->x, b->x)); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
float diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
distance += diff * diff;
}
PG_RETURN_FLOAT8((double) distance);
} }
/* /*
@@ -561,10 +842,17 @@ halfvec_inner_product(PG_FUNCTION_ARGS)
{ {
HalfVector *a = PG_GETARG_HALFVEC_P(0); HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1); HalfVector *b = PG_GETARG_HALFVEC_P(1);
half *ax = a->x;
half *bx = b->x;
float distance = 0.0;
CheckDims(a, b); CheckDims(a, b);
PG_RETURN_FLOAT8((double) HalfvecInnerProduct(a->dim, a->x, b->x)); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
PG_RETURN_FLOAT8((double) distance);
} }
/* /*
@@ -576,10 +864,17 @@ halfvec_negative_inner_product(PG_FUNCTION_ARGS)
{ {
HalfVector *a = PG_GETARG_HALFVEC_P(0); HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1); HalfVector *b = PG_GETARG_HALFVEC_P(1);
half *ax = a->x;
half *bx = b->x;
float distance = 0.0;
CheckDims(a, b); CheckDims(a, b);
PG_RETURN_FLOAT8((double) -HalfvecInnerProduct(a->dim, a->x, b->x)); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += HalfToFloat4(ax[i]) * HalfToFloat4(bx[i]);
PG_RETURN_FLOAT8((double) distance * -1);
} }
/* /*
@@ -629,32 +924,6 @@ halfvec_cosine_distance(PG_FUNCTION_ARGS)
PG_RETURN_FLOAT8(1 - similarity); PG_RETURN_FLOAT8(1 - similarity);
} }
/*
* Get the distance for spherical k-means
* Currently uses angular distance since needs to satisfy triangle inequality
* Assumes inputs are unit vectors (skips norm)
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_spherical_distance);
Datum
halfvec_spherical_distance(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
HalfVector *b = PG_GETARG_HALFVEC_P(1);
double distance;
CheckDims(a, b);
distance = (double) HalfvecInnerProduct(a->dim, a->x, b->x);
/* Prevent NaN with acos with loss of precision */
if (distance > 1)
distance = 1;
else if (distance < -1)
distance = -1;
PG_RETURN_FLOAT8(acos(distance) / M_PI);
}
/* /*
* Get the L1 distance between two half vectors * Get the L1 distance between two half vectors
*/ */
@@ -698,80 +967,3 @@ halfvec_norm(PG_FUNCTION_ARGS)
PG_RETURN_FLOAT8(sqrt(norm)); PG_RETURN_FLOAT8(sqrt(norm));
} }
/*
* Quantize a half vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_quantize_binary);
Datum
halfvec_quantize_binary(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
half *ax = a->x;
VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result);
for (int i = 0; i < a->dim; i++)
rx[i / 8] |= (HalfToFloat4(ax[i]) > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result);
}
/*
* Get a subvector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_subvector);
Datum
halfvec_subvector(PG_FUNCTION_ARGS)
{
HalfVector *a = PG_GETARG_HALFVEC_P(0);
int32 start = PG_GETARG_INT32(1);
int32 count = PG_GETARG_INT32(2);
int32 end = start + count;
half *ax = a->x;
HalfVector *result;
int dim;
/* Indexing starts at 1, like substring */
if (start < 1)
start = 1;
if (end > a->dim)
end = a->dim + 1;
dim = end - start;
CheckDim(dim);
result = InitHalfVector(dim);
for (int i = 0; i < dim; i++)
result->x[i] = ax[start - 1 + i];
PG_RETURN_POINTER(result);
}
/*
* Internal helper to compare half vectors
*/
int
halfvec_cmp_internal(HalfVector * a, HalfVector * b)
{
int dim = Min(a->dim, b->dim);
/* Check values before dimensions to be consistent with Postgres arrays */
for (int i = 0; i < dim; i++)
{
if (HalfToFloat4(a->x[i]) < HalfToFloat4(b->x[i]))
return -1;
if (HalfToFloat4(a->x[i]) > HalfToFloat4(b->x[i]))
return 1;
}
if (a->dim < b->dim)
return -1;
if (a->dim > b->dim)
return 1;
return 0;
}

View File

@@ -5,16 +5,7 @@
#include <float.h> #include <float.h>
#include "vector.h" #ifdef __FLT16_MAX__
#if defined(__x86_64__) || defined(_M_AMD64)
#define HALFVEC_DISPATCH
#endif
/* F16C has better performance than _Float16 (on x86-64) */
#if defined(__F16C__)
#define F16C_SUPPORT
#elif defined(__FLT16_MAX__) && !defined(HALFVEC_DISPATCH)
#define FLT16_SUPPORT #define FLT16_SUPPORT
#endif #endif
@@ -22,11 +13,12 @@
#define half _Float16 #define half _Float16
#define HALF_MAX FLT16_MAX #define HALF_MAX FLT16_MAX
#else #else
/* TODO #pragma message("")? */
#define half uint16 #define half uint16
#define HALF_MAX 65504 #define HALF_MAX 65504
#endif #endif
#define HALFVEC_MAX_DIM VECTOR_MAX_DIM #define HALFVEC_MAX_DIM 16000
#define HALFVEC_SIZE(_dim) (offsetof(HalfVector, x) + sizeof(half)*(_dim)) #define HALFVEC_SIZE(_dim) (offsetof(HalfVector, x) + sizeof(half)*(_dim))
#define DatumGetHalfVector(x) ((HalfVector *) PG_DETOAST_DATUM(x)) #define DatumGetHalfVector(x) ((HalfVector *) PG_DETOAST_DATUM(x))
@@ -42,6 +34,8 @@ typedef struct HalfVector
} HalfVector; } HalfVector;
HalfVector *InitHalfVector(int dim); HalfVector *InitHalfVector(int dim);
int halfvec_cmp_internal(HalfVector * a, HalfVector * b); float HalfToFloat4(half num);
half Float4ToHalf(float num);
half Float4ToHalfUnchecked(float num);
#endif #endif

View File

@@ -17,7 +17,6 @@
#endif #endif
#define HNSW_MAX_DIM 2000 #define HNSW_MAX_DIM 2000
#define HNSW_MAX_NNZ 1000
/* Support functions */ /* Support functions */
#define HNSW_DISTANCE_PROC 1 #define HNSW_DISTANCE_PROC 1
@@ -56,13 +55,9 @@
#define HNSW_UPDATE_ENTRY_GREATER 1 #define HNSW_UPDATE_ENTRY_GREATER 1
#define HNSW_UPDATE_ENTRY_ALWAYS 2 #define HNSW_UPDATE_ENTRY_ALWAYS 2
typedef enum HnswType /* Data types */
{ #define HNSW_TYPE_VECTOR 1
HNSW_TYPE_VECTOR, #define HNSW_TYPE_HALFVEC 2
HNSW_TYPE_HALFVEC,
HNSW_TYPE_BIT,
HNSW_TYPE_SPARSEVEC
} HnswType;
/* Build phases */ /* Build phases */
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */ /* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
@@ -251,7 +246,7 @@ typedef struct HnswBuildState
Relation index; Relation index;
IndexInfo *indexInfo; IndexInfo *indexInfo;
ForkNumber forkNum; ForkNumber forkNum;
HnswType type; int type;
/* Settings */ /* Settings */
int dimensions; int dimensions;
@@ -376,9 +371,8 @@ typedef struct HnswVacuumState
int HnswGetM(Relation index); int HnswGetM(Relation index);
int HnswGetEfConstruction(Relation index); int HnswGetEfConstruction(Relation index);
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum); FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
HnswType HnswGetType(Relation index); int HnswGetType(Relation index);
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type); bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, int type);
void HnswCheckValue(Datum value, HnswType type);
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum); Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
void HnswInitPage(Buffer buf, Page page); void HnswInitPage(Buffer buf, Page page);
void HnswInit(void); void HnswInit(void);

View File

@@ -44,7 +44,6 @@
#include "access/xact.h" #include "access/xact.h"
#include "access/xloginsert.h" #include "access/xloginsert.h"
#include "catalog/index.h" #include "catalog/index.h"
#include "catalog/pg_type_d.h"
#include "commands/progress.h" #include "commands/progress.h"
#include "hnsw.h" #include "hnsw.h"
#include "miscadmin.h" #include "miscadmin.h"
@@ -487,9 +486,6 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
/* Detoast once for all calls */ /* Detoast once for all calls */
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0])); Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Check value */
HnswCheckValue(value, buildstate->type);
/* Normalize if needed */ /* Normalize if needed */
if (buildstate->normprocinfo != NULL) if (buildstate->normprocinfo != NULL)
{ {
@@ -669,31 +665,13 @@ HnswSharedMemoryAlloc(Size size, void *state)
return chunk; return chunk;
} }
/*
* Get max dimensions
*/
static int
GetMaxDimensions(HnswType type)
{
int maxDimensions = HNSW_MAX_DIM;
if (type == HNSW_TYPE_HALFVEC)
maxDimensions *= 2;
else if (type == HNSW_TYPE_BIT)
maxDimensions *= 32;
else if (type == HNSW_TYPE_SPARSEVEC)
maxDimensions = INT_MAX;
return maxDimensions;
}
/* /*
* Initialize the build state * Initialize the build state
*/ */
static void static void
InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum) InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum)
{ {
int maxDimensions; int maxDimensions = HNSW_MAX_DIM;
buildstate->heap = heap; buildstate->heap = heap;
buildstate->index = index; buildstate->index = index;
@@ -705,7 +683,8 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->efConstruction = HnswGetEfConstruction(index); buildstate->efConstruction = HnswGetEfConstruction(index);
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod; buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
maxDimensions = GetMaxDimensions(buildstate->type); if (buildstate->type == HNSW_TYPE_HALFVEC)
maxDimensions *= 2;
/* Require column to have dimensions to be indexed */ /* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0) if (buildstate->dimensions < 0)

View File

@@ -614,19 +614,15 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
Datum value; Datum value;
FmgrInfo *normprocinfo; FmgrInfo *normprocinfo;
Oid collation = index->rd_indcollation[0]; Oid collation = index->rd_indcollation[0];
HnswType type = HnswGetType(index);
/* Detoast once for all calls */ /* Detoast once for all calls */
value = PointerGetDatum(PG_DETOAST_DATUM(values[0])); value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Check value */
HnswCheckValue(value, type);
/* Normalize if needed */ /* Normalize if needed */
normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC); normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
if (normprocinfo != NULL) if (normprocinfo != NULL)
{ {
if (!HnswNormValue(normprocinfo, collation, &value, type)) if (!HnswNormValue(normprocinfo, collation, &value, HnswGetType(index)))
return; return;
} }

View File

@@ -1,6 +1,7 @@
#include "postgres.h" #include "postgres.h"
#include "access/relscan.h" #include "access/relscan.h"
#include "halfvec.h"
#include "hnsw.h" #include "hnsw.h"
#include "pgstat.h" #include "pgstat.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
@@ -40,6 +41,29 @@ GetScanItems(IndexScanDesc scan, Datum q)
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL); 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 * Get scan value
*/ */
@@ -50,7 +74,14 @@ GetScanValue(IndexScanDesc scan)
Datum value; Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL) if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(NULL); {
int dimensions = GetDimensions(scan->indexRelation);
if (HnswGetType(scan->indexRelation) == HNSW_TYPE_HALFVEC)
value = PointerGetDatum(InitHalfVector(dimensions));
else
value = PointerGetDatum(InitVector(dimensions));
}
else else
{ {
value = scan->orderByData->sk_argument; value = scan->orderByData->sk_argument;
@@ -158,10 +189,6 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock); UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
so->first = false; so->first = false;
#if defined(HNSW_MEMORY) && PG_VERSION_NUM >= 130000
elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(so->tmpCtx, false) / (1024 * 1024));
#endif
} }
while (list_length(so->w) > 0) while (list_length(so->w) > 0)

View File

@@ -4,12 +4,9 @@
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "catalog/pg_type.h" #include "catalog/pg_type.h"
#include "catalog/pg_type_d.h"
#include "halfutils.h"
#include "halfvec.h" #include "halfvec.h"
#include "hnsw.h" #include "hnsw.h"
#include "lib/pairingheap.h" #include "lib/pairingheap.h"
#include "sparsevec.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "utils/datum.h" #include "utils/datum.h"
#include "utils/memdebug.h" #include "utils/memdebug.h"
@@ -158,33 +155,23 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
/* /*
* Get type * Get type
*/ */
HnswType int
HnswGetType(Relation index) HnswGetType(Relation index)
{ {
Oid typid = TupleDescAttr(index->rd_att, 0)->atttypid; Oid typeOid = TupleDescAttr(index->rd_att, 0)->atttypid;
HeapTuple tuple; HeapTuple tuple;
Form_pg_type type; Form_pg_type type;
HnswType result; int result;
if (typid == BITOID) tuple = SearchSysCache1(TYPEOID, ObjectIdGetDatum(typeOid));
return HNSW_TYPE_BIT;
tuple = SearchSysCache1(TYPEOID, ObjectIdGetDatum(typid));
if (!HeapTupleIsValid(tuple)) if (!HeapTupleIsValid(tuple))
elog(ERROR, "cache lookup failed for type %u", typid); elog(ERROR, "cache lookup failed for type %u", typeOid);
type = (Form_pg_type) GETSTRUCT(tuple); type = (Form_pg_type) GETSTRUCT(tuple);
if (strcmp(NameStr(type->typname), "vector") == 0) if (strcmp(NameStr(type->typname), "halfvec") == 0)
result = HNSW_TYPE_VECTOR;
else if (strcmp(NameStr(type->typname), "halfvec") == 0)
result = HNSW_TYPE_HALFVEC; result = HNSW_TYPE_HALFVEC;
else if (strcmp(NameStr(type->typname), "sparsevec") == 0)
result = HNSW_TYPE_SPARSEVEC;
else else
{ result = HNSW_TYPE_VECTOR;
ReleaseSysCache(tuple);
elog(ERROR, "type not supported for hnsw index");
}
ReleaseSysCache(tuple); ReleaseSysCache(tuple);
@@ -200,14 +187,26 @@ HnswGetType(Relation index)
* if it's different than the original value * if it's different than the original value
*/ */
bool bool
HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type) HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, int type)
{ {
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value)); double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0) if (norm > 0)
{ {
/* TODO Remove vector-specific code */ if (type == HNSW_TYPE_HALFVEC)
if (type == HNSW_TYPE_VECTOR) {
HalfVector *v = DatumGetHalfVector(*value);
HalfVector *result = InitHalfVector(v->dim);
for (int i = 0; i < v->dim; i++)
{
/* TODO Fix */
result->x[i] = Float4ToHalfUnchecked(HalfToFloat4(v->x[i]) / norm);
}
*value = PointerGetDatum(result);
}
else if (type == HNSW_TYPE_VECTOR)
{ {
Vector *v = DatumGetVector(*value); Vector *v = DatumGetVector(*value);
Vector *result = InitVector(v->dim); Vector *result = InitVector(v->dim);
@@ -217,31 +216,6 @@ HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type)
*value = PointerGetDatum(result); *value = PointerGetDatum(result);
} }
else if (type == HNSW_TYPE_HALFVEC)
{
HalfVector *v = DatumGetHalfVector(*value);
HalfVector *result = InitHalfVector(v->dim);
for (int i = 0; i < v->dim; i++)
result->x[i] = Float4ToHalfUnchecked(HalfToFloat4(v->x[i]) / norm);
*value = PointerGetDatum(result);
}
else if (type == HNSW_TYPE_SPARSEVEC)
{
SparseVector *v = DatumGetSparseVector(*value);
SparseVector *result = InitSparseVector(v->dim, v->nnz);
float *vx = SPARSEVEC_VALUES(v);
float *rx = SPARSEVEC_VALUES(result);
for (int i = 0; i < v->nnz; i++)
{
result->indices[i] = v->indices[i];
rx[i] = vx[i] / norm;
}
*value = PointerGetDatum(result);
}
else else
elog(ERROR, "Unsupported type"); elog(ERROR, "Unsupported type");
@@ -251,21 +225,6 @@ HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, HnswType type)
return false; return false;
} }
/*
* Check if a value can be indexed
*/
void
HnswCheckValue(Datum value, HnswType type)
{
if (type == HNSW_TYPE_SPARSEVEC)
{
SparseVector *vec = DatumGetSparseVector(value);
if (vec->nnz > HNSW_MAX_NNZ)
elog(ERROR, "sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ);
}
}
/* /*
* New buffer * New buffer
*/ */
@@ -661,12 +620,7 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
/* Calculate distance */ /* Calculate distance */
if (distance != NULL) if (distance != NULL)
{ *distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
if (DatumGetPointer(*q) == NULL)
*distance = 0;
else
*distance = (float) DatumGetFloat8(FunctionCall2Coll(procinfo, collation, *q, PointerGetDatum(&etup->data)));
}
UnlockReleaseBuffer(buf); UnlockReleaseBuffer(buf);
} }

View File

@@ -10,14 +10,12 @@
#include "catalog/pg_operator_d.h" #include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h" #include "catalog/pg_type_d.h"
#include "commands/progress.h" #include "commands/progress.h"
#include "halfvec.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "miscadmin.h" #include "miscadmin.h"
#include "optimizer/optimizer.h" #include "optimizer/optimizer.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "tcop/tcopprot.h" #include "tcop/tcopprot.h"
#include "utils/memutils.h" #include "utils/memutils.h"
#include "vector.h"
#if PG_VERSION_NUM >= 140000 #if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h" #include "utils/backend_progress.h"
@@ -59,13 +57,13 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
*/ */
if (buildstate->kmeansnormprocinfo != NULL) if (buildstate->kmeansnormprocinfo != NULL)
{ {
if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->type)) if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->normvec))
return; return;
} }
if (samples->length < targsamples) if (samples->length < targsamples)
{ {
VectorArraySet(samples, samples->length, DatumGetPointer(value)); VectorArraySet(samples, samples->length, DatumGetVector(value));
samples->length++; samples->length++;
} }
else else
@@ -82,7 +80,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
#endif #endif
Assert(k >= 0 && k < targsamples); Assert(k >= 0 && k < targsamples);
VectorArraySet(samples, k, DatumGetPointer(value)); VectorArraySet(samples, k, DatumGetVector(value));
} }
buildstate->rowstoskip -= 1; buildstate->rowstoskip -= 1;
@@ -107,7 +105,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx); oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
/* Add sample */ /* Add sample */
AddSample(values, buildstate); AddSample(values, state);
/* Reset memory context */ /* Reset memory context */
MemoryContextSwitchTo(oldCtx); MemoryContextSwitchTo(oldCtx);
@@ -155,7 +153,7 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
/* Normalize if needed */ /* Normalize if needed */
if (buildstate->normprocinfo != NULL) if (buildstate->normprocinfo != NULL)
{ {
if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->type)) if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
return; return;
} }
@@ -314,58 +312,25 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
} }
} }
/*
* Get max dimensions
*/
static int
GetMaxDimensions(IvfflatType type)
{
int maxDimensions = IVFFLAT_MAX_DIM;
if (type == IVFFLAT_TYPE_HALFVEC)
maxDimensions *= 2;
return maxDimensions;
}
/*
* Get item size
*/
static Size
GetItemSize(IvfflatType type, int dimensions)
{
if (type == IVFFLAT_TYPE_VECTOR)
return VECTOR_SIZE(dimensions);
else if (type == IVFFLAT_TYPE_HALFVEC)
return HALFVEC_SIZE(dimensions);
else
elog(ERROR, "Unsupported type");
}
/* /*
* Initialize the build state * Initialize the build state
*/ */
static void static void
InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo) InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo)
{ {
int maxDimensions;
buildstate->heap = heap; buildstate->heap = heap;
buildstate->index = index; buildstate->index = index;
buildstate->indexInfo = indexInfo; buildstate->indexInfo = indexInfo;
buildstate->type = IvfflatGetType(index);
buildstate->lists = IvfflatGetLists(index); buildstate->lists = IvfflatGetLists(index);
buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod; buildstate->dimensions = TupleDescAttr(index->rd_att, 0)->atttypmod;
maxDimensions = GetMaxDimensions(buildstate->type);
/* Require column to have dimensions to be indexed */ /* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0) if (buildstate->dimensions < 0)
elog(ERROR, "column does not have dimensions"); elog(ERROR, "column does not have dimensions");
if (buildstate->dimensions > maxDimensions) if (buildstate->dimensions > IVFFLAT_MAX_DIM)
elog(ERROR, "column cannot have more than %d dimensions for ivfflat index", maxDimensions); elog(ERROR, "column cannot have more than %d dimensions for ivfflat index", IVFFLAT_MAX_DIM);
buildstate->reltuples = 0; buildstate->reltuples = 0;
buildstate->indtuples = 0; buildstate->indtuples = 0;
@@ -388,9 +353,12 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->slot = MakeSingleTupleTableSlot(buildstate->tupdesc, &TTSOpsVirtual); buildstate->slot = MakeSingleTupleTableSlot(buildstate->tupdesc, &TTSOpsVirtual);
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, GetItemSize(buildstate->type, buildstate->dimensions)); buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions);
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists); buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
/* Reuse for each tuple */
buildstate->normvec = InitVector(buildstate->dimensions);
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext, buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat build temporary context", "Ivfflat build temporary context",
ALLOCSET_DEFAULT_SIZES); ALLOCSET_DEFAULT_SIZES);
@@ -412,6 +380,7 @@ FreeBuildState(IvfflatBuildState * buildstate)
{ {
VectorArrayFree(buildstate->centers); VectorArrayFree(buildstate->centers);
pfree(buildstate->listInfo); pfree(buildstate->listInfo);
pfree(buildstate->normvec);
#ifdef IVFFLAT_KMEANS_DEBUG #ifdef IVFFLAT_KMEANS_DEBUG
pfree(buildstate->listSums); pfree(buildstate->listSums);
@@ -443,7 +412,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
/* Sample rows */ /* Sample rows */
/* TODO Ensure within maintenance_work_mem */ /* TODO Ensure within maintenance_work_mem */
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions, buildstate->centers->itemsize); buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions);
if (buildstate->heap != NULL) if (buildstate->heap != NULL)
{ {
SampleRows(buildstate); SampleRows(buildstate);
@@ -458,7 +427,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
} }
/* Calculate centers */ /* Calculate centers */
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers, buildstate->type)); IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers));
/* Free samples before we allocate more memory */ /* Free samples before we allocate more memory */
VectorArrayFree(buildstate->samples); VectorArrayFree(buildstate->samples);
@@ -503,7 +472,7 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
Size listSize; Size listSize;
IvfflatList list; IvfflatList list;
listSize = MAXALIGN(IVFFLAT_LIST_SIZE(centers->itemsize)); listSize = MAXALIGN(IVFFLAT_LIST_SIZE(dimensions));
list = palloc0(listSize); list = palloc0(listSize);
buf = IvfflatNewBuffer(index, forkNum); buf = IvfflatNewBuffer(index, forkNum);
@@ -516,7 +485,7 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
/* Load list */ /* Load list */
list->startPage = InvalidBlockNumber; list->startPage = InvalidBlockNumber;
list->insertPage = InvalidBlockNumber; list->insertPage = InvalidBlockNumber;
memcpy(&list->center, VectorArrayGet(centers, i), centers->itemsize); memcpy(&list->center, VectorArrayGet(centers, i), VECTOR_SIZE(dimensions));
/* Ensure free space */ /* Ensure free space */
if (PageGetFreeSpace(page) < listSize) if (PageGetFreeSpace(page) < listSize)
@@ -621,7 +590,7 @@ ParallelHeapScan(IvfflatBuildState * buildstate)
* Perform a worker's portion of a parallel sort * Perform a worker's portion of a parallel sort
*/ */
static void static void
IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, Sharedsort *sharedsort, char *ivfcenters, int sortmem, bool progress) IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, Sharedsort *sharedsort, Vector * ivfcenters, int sortmem, bool progress)
{ {
SortCoordinate coordinate; SortCoordinate coordinate;
IvfflatBuildState buildstate; IvfflatBuildState buildstate;
@@ -645,7 +614,7 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
indexInfo = BuildIndexInfo(ivfspool->index); indexInfo = BuildIndexInfo(ivfspool->index);
indexInfo->ii_Concurrent = ivfshared->isconcurrent; indexInfo->ii_Concurrent = ivfshared->isconcurrent;
InitBuildState(&buildstate, ivfspool->heap, ivfspool->index, indexInfo); InitBuildState(&buildstate, ivfspool->heap, ivfspool->index, indexInfo);
memcpy(buildstate.centers->items, ivfcenters, buildstate.centers->itemsize * buildstate.centers->maxlen); memcpy(buildstate.centers->items, ivfcenters, VECTOR_SIZE(buildstate.centers->dim) * buildstate.centers->maxlen);
buildstate.centers->length = buildstate.centers->maxlen; buildstate.centers->length = buildstate.centers->maxlen;
ivfspool->sortstate = tuplesort_begin_heap(buildstate.tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, sortmem, coordinate, false); ivfspool->sortstate = tuplesort_begin_heap(buildstate.tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, sortmem, coordinate, false);
buildstate.sortstate = ivfspool->sortstate; buildstate.sortstate = ivfspool->sortstate;
@@ -693,7 +662,7 @@ IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc)
IvfflatSpool *ivfspool; IvfflatSpool *ivfspool;
IvfflatShared *ivfshared; IvfflatShared *ivfshared;
Sharedsort *sharedsort; Sharedsort *sharedsort;
char *ivfcenters; Vector *ivfcenters;
Relation heapRel; Relation heapRel;
Relation indexRel; Relation indexRel;
LOCKMODE heapLockmode; LOCKMODE heapLockmode;
@@ -807,7 +776,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
Size estcenters; Size estcenters;
IvfflatShared *ivfshared; IvfflatShared *ivfshared;
Sharedsort *sharedsort; Sharedsort *sharedsort;
char *ivfcenters; Vector *ivfcenters;
IvfflatLeader *ivfleader = (IvfflatLeader *) palloc0(sizeof(IvfflatLeader)); IvfflatLeader *ivfleader = (IvfflatLeader *) palloc0(sizeof(IvfflatLeader));
bool leaderparticipates = true; bool leaderparticipates = true;
int querylen; int querylen;
@@ -834,7 +803,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
shm_toc_estimate_chunk(&pcxt->estimator, estivfshared); shm_toc_estimate_chunk(&pcxt->estimator, estivfshared);
estsort = tuplesort_estimate_shared(scantuplesortstates); estsort = tuplesort_estimate_shared(scantuplesortstates);
shm_toc_estimate_chunk(&pcxt->estimator, estsort); shm_toc_estimate_chunk(&pcxt->estimator, estsort);
estcenters = buildstate->centers->itemsize * buildstate->centers->maxlen; estcenters = VECTOR_SIZE(buildstate->dimensions) * buildstate->lists;
shm_toc_estimate_chunk(&pcxt->estimator, estcenters); shm_toc_estimate_chunk(&pcxt->estimator, estcenters);
shm_toc_estimate_keys(&pcxt->estimator, 3); shm_toc_estimate_keys(&pcxt->estimator, 3);
@@ -886,7 +855,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
tuplesort_initialize_shared(sharedsort, scantuplesortstates, tuplesort_initialize_shared(sharedsort, scantuplesortstates,
pcxt->seg); pcxt->seg);
ivfcenters = shm_toc_allocate(pcxt->toc, estcenters); ivfcenters = (Vector *) shm_toc_allocate(pcxt->toc, estcenters);
memcpy(ivfcenters, buildstate->centers->items, estcenters); memcpy(ivfcenters, buildstate->centers->items, estcenters);
shm_toc_insert(pcxt->toc, PARALLEL_KEY_IVFFLAT_SHARED, ivfshared); shm_toc_insert(pcxt->toc, PARALLEL_KEY_IVFFLAT_SHARED, ivfshared);

View File

@@ -43,19 +43,13 @@
#define IVFFLAT_MAX_LISTS 32768 #define IVFFLAT_MAX_LISTS 32768
#define IVFFLAT_DEFAULT_PROBES 1 #define IVFFLAT_DEFAULT_PROBES 1
typedef enum IvfflatType
{
IVFFLAT_TYPE_VECTOR,
IVFFLAT_TYPE_HALFVEC
} IvfflatType;
/* Build phases */ /* Build phases */
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */ /* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
#define PROGRESS_IVFFLAT_PHASE_KMEANS 2 #define PROGRESS_IVFFLAT_PHASE_KMEANS 2
#define PROGRESS_IVFFLAT_PHASE_ASSIGN 3 #define PROGRESS_IVFFLAT_PHASE_ASSIGN 3
#define PROGRESS_IVFFLAT_PHASE_LOAD 4 #define PROGRESS_IVFFLAT_PHASE_LOAD 4
#define IVFFLAT_LIST_SIZE(size) (offsetof(IvfflatListData, center) + size) #define IVFFLAT_LIST_SIZE(_dim) (offsetof(IvfflatListData, center) + VECTOR_SIZE(_dim))
#define IvfflatPageGetOpaque(page) ((IvfflatPageOpaque) PageGetSpecialPointer(page)) #define IvfflatPageGetOpaque(page) ((IvfflatPageOpaque) PageGetSpecialPointer(page))
#define IvfflatPageGetMeta(page) ((IvfflatMetaPageData *) PageGetContents(page)) #define IvfflatPageGetMeta(page) ((IvfflatMetaPageData *) PageGetContents(page))
@@ -91,8 +85,7 @@ typedef struct VectorArrayData
int length; int length;
int maxlen; int maxlen;
int dim; int dim;
Size itemsize; Vector *items;
char *items;
} VectorArrayData; } VectorArrayData;
typedef VectorArrayData * VectorArray; typedef VectorArrayData * VectorArray;
@@ -151,7 +144,7 @@ typedef struct IvfflatLeader
IvfflatShared *ivfshared; IvfflatShared *ivfshared;
Sharedsort *sharedsort; Sharedsort *sharedsort;
Snapshot snapshot; Snapshot snapshot;
char *ivfcenters; Vector *ivfcenters;
} IvfflatLeader; } IvfflatLeader;
typedef struct IvfflatBuildState typedef struct IvfflatBuildState
@@ -160,7 +153,6 @@ typedef struct IvfflatBuildState
Relation heap; Relation heap;
Relation index; Relation index;
IndexInfo *indexInfo; IndexInfo *indexInfo;
IvfflatType type;
/* Settings */ /* Settings */
int dimensions; int dimensions;
@@ -180,6 +172,7 @@ typedef struct IvfflatBuildState
VectorArray samples; VectorArray samples;
VectorArray centers; VectorArray centers;
ListInfo *listInfo; ListInfo *listInfo;
Vector *normvec;
#ifdef IVFFLAT_KMEANS_DEBUG #ifdef IVFFLAT_KMEANS_DEBUG
double inertia; double inertia;
@@ -263,18 +256,18 @@ typedef struct IvfflatScanOpaqueData
typedef IvfflatScanOpaqueData * IvfflatScanOpaque; typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
#define VECTOR_ARRAY_SIZE(_length, _size) (sizeof(VectorArrayData) + (_length) * _size) #define VECTOR_ARRAY_SIZE(_length, _dim) (sizeof(VectorArrayData) + (_length) * VECTOR_SIZE(_dim))
#define VECTOR_ARRAY_OFFSET(_arr, _offset) ((char*) (_arr)->items + (_offset) * (_arr)->itemsize) #define VECTOR_ARRAY_OFFSET(_arr, _offset) ((char*) (_arr)->items + (_offset) * VECTOR_SIZE((_arr)->dim))
#define VectorArrayGet(_arr, _offset) VECTOR_ARRAY_OFFSET(_arr, _offset) #define VectorArrayGet(_arr, _offset) ((Vector *) VECTOR_ARRAY_OFFSET(_arr, _offset))
#define VectorArraySet(_arr, _offset, _val) memcpy(VECTOR_ARRAY_OFFSET(_arr, _offset), _val, (_arr)->itemsize) #define VectorArraySet(_arr, _offset, _val) memcpy(VECTOR_ARRAY_OFFSET(_arr, _offset), _val, VECTOR_SIZE((_arr)->dim))
/* Methods */ /* Methods */
VectorArray VectorArrayInit(int maxlen, int dimensions, Size itemsize); VectorArray VectorArrayInit(int maxlen, int dimensions);
void VectorArrayFree(VectorArray arr); void VectorArrayFree(VectorArray arr);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatType type); void PrintVectorArray(char *msg, VectorArray arr);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum); FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
IvfflatType IvfflatGetType(Relation index); bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, IvfflatType type);
int IvfflatGetLists(Relation index); int IvfflatGetLists(Relation index);
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions); void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum); void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);

View File

@@ -85,7 +85,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC); normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL) if (normprocinfo != NULL)
{ {
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, IvfflatGetType(index))) if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
return; return;
} }

View File

@@ -3,13 +3,12 @@
#include <float.h> #include <float.h>
#include <math.h> #include <math.h>
#include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "miscadmin.h" #include "miscadmin.h"
#include "utils/datum.h"
#ifdef IVFFLAT_MEMORY
#include "utils/memutils.h" #include "utils/memutils.h"
#include "vector.h" #endif
/* /*
* Initialize with kmeans++ * Initialize with kmeans++
@@ -47,12 +46,12 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
for (j = 0; j < numSamples; j++) for (j = 0; j < numSamples; j++)
{ {
Datum vec = PointerGetDatum(VectorArrayGet(samples, j)); Vector *vec = VectorArrayGet(samples, j);
double distance; double distance;
/* Only need to compute distance for new center */ /* Only need to compute distance for new center */
/* TODO Use triangle inequality to reduce distance calculations */ /* TODO Use triangle inequality to reduce distance calculations */
distance = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, i)))); distance = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, i))));
/* Set lower bound */ /* Set lower bound */
lowerBound[j * numCenters + i] = distance; lowerBound[j * numCenters + i] = distance;
@@ -90,29 +89,15 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
* Apply norm to vector * Apply norm to vector
*/ */
static inline void static inline void
ApplyNorm(FmgrInfo *normprocinfo, Oid collation, Datum value, IvfflatType type) ApplyNorm(FmgrInfo *normprocinfo, Oid collation, Vector * vec)
{ {
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, value)); double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(vec)));
/* TODO Handle zero norm */ /* TODO Handle zero norm */
if (norm > 0) if (norm > 0)
{ {
if (type == IVFFLAT_TYPE_VECTOR) for (int i = 0; i < vec->dim; i++)
{ vec->x[i] /= norm;
Vector *vec = DatumGetVector(value);
for (int i = 0; i < vec->dim; i++)
vec->x[i] /= norm;
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
HalfVector *vec = DatumGetHalfVector(value);
for (int i = 0; i < vec->dim; i++)
vec->x[i] = Float4ToHalfUnchecked(HalfToFloat4(vec->x[i]) / norm);
}
else
elog(ERROR, "Unsupported type");
} }
} }
@@ -125,20 +110,11 @@ CompareVectors(const void *a, const void *b)
return vector_cmp_internal((Vector *) a, (Vector *) b); return vector_cmp_internal((Vector *) a, (Vector *) b);
} }
/*
* Compare half vectors
*/
static int
CompareHalfVectors(const void *a, const void *b)
{
return halfvec_cmp_internal((HalfVector *) a, (HalfVector *) b);
}
/* /*
* Quick approach if we have little data * Quick approach if we have little data
*/ */
static void static void
QuickCenters(Relation index, VectorArray samples, VectorArray centers, IvfflatType type) QuickCenters(Relation index, VectorArray samples, VectorArray centers)
{ {
int dimensions = centers->dim; int dimensions = centers->dim;
Oid collation = index->rd_indcollation[0]; Oid collation = index->rd_indcollation[0];
@@ -147,20 +123,14 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers, IvfflatTy
/* Copy existing vectors while avoiding duplicates */ /* Copy existing vectors while avoiding duplicates */
if (samples->length > 0) if (samples->length > 0)
{ {
if (type == IVFFLAT_TYPE_VECTOR) qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
qsort(samples->items, samples->length, samples->itemsize, CompareVectors);
else if (type == IVFFLAT_TYPE_HALFVEC)
qsort(samples->items, samples->length, samples->itemsize, CompareHalfVectors);
else
elog(ERROR, "Unsupported type");
for (int i = 0; i < samples->length; i++) for (int i = 0; i < samples->length; i++)
{ {
Datum vec = PointerGetDatum(VectorArrayGet(samples, i)); Vector *vec = VectorArrayGet(samples, i);
if (i == 0 || !datumIsEqual(vec, PointerGetDatum(VectorArrayGet(samples, i - 1)), false, -1)) if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
{ {
VectorArraySet(centers, centers->length, DatumGetPointer(vec)); VectorArraySet(centers, centers->length, vec);
centers->length++; centers->length++;
} }
} }
@@ -169,34 +139,17 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers, IvfflatTy
/* Fill remaining with random data */ /* Fill remaining with random data */
while (centers->length < centers->maxlen) while (centers->length < centers->maxlen)
{ {
Datum center = PointerGetDatum(VectorArrayGet(centers, centers->length)); Vector *vec = VectorArrayGet(centers, centers->length);
if (type == IVFFLAT_TYPE_VECTOR) SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
{ vec->dim = dimensions;
Vector *vec = DatumGetVector(center);
SET_VARSIZE(vec, VECTOR_SIZE(dimensions)); for (int j = 0; j < dimensions; j++)
vec->dim = dimensions; vec->x[j] = RandomDouble();
for (int j = 0; j < dimensions; j++)
vec->x[j] = RandomDouble();
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
HalfVector *vec = DatumGetHalfVector(center);
SET_VARSIZE(vec, HALFVEC_SIZE(dimensions));
vec->dim = dimensions;
for (int j = 0; j < dimensions; j++)
vec->x[j] = Float4ToHalfUnchecked((float) RandomDouble());
}
else
elog(ERROR, "Unsupported type");
/* Normalize if needed (only needed for random centers) */ /* Normalize if needed (only needed for random centers) */
if (normprocinfo != NULL) if (normprocinfo != NULL)
ApplyNorm(normprocinfo, collation, center, type); ApplyNorm(normprocinfo, collation, vec);
centers->length++; centers->length++;
} }
@@ -207,120 +160,18 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers, IvfflatTy
* Show memory usage * Show memory usage
*/ */
static void static void
ShowMemoryUsage(MemoryContext context, Size estimatedSize) ShowMemoryUsage(Size estimatedSize)
{ {
#if PG_VERSION_NUM >= 130000 #if PG_VERSION_NUM >= 130000
elog(INFO, "total memory: %zu MB", elog(INFO, "total memory: %zu MB",
MemoryContextMemAllocated(context, true) / (1024 * 1024)); MemoryContextMemAllocated(CurrentMemoryContext, true) / (1024 * 1024));
#else #else
MemoryContextStats(context); MemoryContextStats(CurrentMemoryContext);
#endif #endif
elog(INFO, "estimated memory: %zu MB", estimatedSize / (1024 * 1024)); elog(INFO, "estimated memory: %zu MB", estimatedSize / (1024 * 1024));
} }
#endif #endif
/*
* Compute new centers
*/
static void
ComputeNewCenters(VectorArray samples, VectorArray aggCenters, VectorArray newCenters, int *centerCounts, int *closestCenters, FmgrInfo *normprocinfo, Oid collation, IvfflatType type)
{
int dimensions = aggCenters->dim;
int numCenters = aggCenters->maxlen;
int numSamples = samples->length;
/* Reset sum and count */
for (int j = 0; j < numCenters; j++)
{
Vector *vec = (Vector *) VectorArrayGet(aggCenters, j);
for (int k = 0; k < dimensions; k++)
vec->x[k] = 0.0;
centerCounts[j] = 0;
}
/* Increment sum of closest center */
if (type == IVFFLAT_TYPE_VECTOR)
{
for (int j = 0; j < numSamples; j++)
{
Vector *aggCenter = (Vector *) VectorArrayGet(aggCenters, closestCenters[j]);
Vector *vec = (Vector *) VectorArrayGet(samples, j);
for (int k = 0; k < dimensions; k++)
aggCenter->x[k] += vec->x[k];
}
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
for (int j = 0; j < numSamples; j++)
{
Vector *aggCenter = (Vector *) VectorArrayGet(aggCenters, closestCenters[j]);
HalfVector *vec = (HalfVector *) VectorArrayGet(samples, j);
for (int k = 0; k < dimensions; k++)
aggCenter->x[k] += HalfToFloat4(vec->x[k]);
}
}
else
elog(ERROR, "Unsupported type");
/* Increment count of closest center */
for (int j = 0; j < numSamples; j++)
centerCounts[closestCenters[j]] += 1;
/* Divide sum by count */
for (int j = 0; j < numCenters; j++)
{
Vector *vec = (Vector *) VectorArrayGet(aggCenters, j);
if (centerCounts[j] > 0)
{
/* Double avoids overflow, but requires more memory */
/* TODO Update bounds */
for (int k = 0; k < dimensions; k++)
{
if (isinf(vec->x[k]))
vec->x[k] = vec->x[k] > 0 ? FLT_MAX : -FLT_MAX;
}
for (int k = 0; k < dimensions; k++)
vec->x[k] /= centerCounts[j];
}
else
{
/* TODO Handle empty centers properly */
for (int k = 0; k < dimensions; k++)
vec->x[k] = RandomDouble();
}
}
/* Set new centers if different from agg centers */
if (type == IVFFLAT_TYPE_HALFVEC)
{
for (int j = 0; j < numCenters; j++)
{
Vector *aggCenter = (Vector *) VectorArrayGet(aggCenters, j);
HalfVector *newCenter = (HalfVector *) VectorArrayGet(newCenters, j);
for (int k = 0; k < dimensions; k++)
newCenter->x[k] = Float4ToHalfUnchecked(aggCenter->x[k]);
}
}
/* Normalize if needed */
if (normprocinfo != NULL)
{
for (int j = 0; j < numCenters; j++)
{
Datum newCenter = PointerGetDatum(VectorArrayGet(newCenters, j));
ApplyNorm(normprocinfo, collation, newCenter, type);
}
}
}
/* /*
* Use Elkan for performance. This requires distance function to satisfy triangle inequality. * Use Elkan for performance. This requires distance function to satisfy triangle inequality.
* *
@@ -330,16 +181,19 @@ ComputeNewCenters(VectorArray samples, VectorArray aggCenters, VectorArray newCe
* https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf * https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
*/ */
static void static void
ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatType type) ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
{ {
FmgrInfo *procinfo; FmgrInfo *procinfo;
FmgrInfo *normprocinfo; FmgrInfo *normprocinfo;
Oid collation; Oid collation;
Vector *vec;
Vector *newCenter;
int64 j;
int64 k;
int dimensions = centers->dim; int dimensions = centers->dim;
int numCenters = centers->maxlen; int numCenters = centers->maxlen;
int numSamples = samples->length; int numSamples = samples->length;
VectorArray newCenters; VectorArray newCenters;
VectorArray aggCenters;
int *centerCounts; int *centerCounts;
int *closestCenters; int *closestCenters;
float *lowerBound; float *lowerBound;
@@ -347,14 +201,11 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
float *s; float *s;
float *halfcdist; float *halfcdist;
float *newcdist; float *newcdist;
MemoryContext kmeansCtx;
MemoryContext oldCtx;
/* Calculate allocation sizes */ /* Calculate allocation sizes */
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->itemsize); Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->dim);
Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->itemsize); Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->dim);
Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, centers->itemsize); Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, dimensions);
Size aggCentersSize = type == IVFFLAT_TYPE_VECTOR ? 0 : VECTOR_ARRAY_SIZE(numCenters, VECTOR_SIZE(dimensions));
Size centerCountsSize = sizeof(int) * numCenters; Size centerCountsSize = sizeof(int) * numCenters;
Size closestCentersSize = sizeof(int) * numSamples; Size closestCentersSize = sizeof(int) * numSamples;
Size lowerBoundSize = sizeof(float) * numSamples * numCenters; Size lowerBoundSize = sizeof(float) * numSamples * numCenters;
@@ -364,7 +215,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
Size newcdistSize = sizeof(float) * numCenters; Size newcdistSize = sizeof(float) * numCenters;
/* Calculate total size */ /* Calculate total size */
Size totalSize = samplesSize + centersSize + newCentersSize + aggCentersSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize; Size totalSize = samplesSize + centersSize + newCentersSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
/* Check memory requirements */ /* Check memory requirements */
/* Add one to error message to ceil */ /* Add one to error message to ceil */
@@ -383,12 +234,6 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC); normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
collation = index->rd_indcollation[0]; collation = index->rd_indcollation[0];
/* Use memory context */
kmeansCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat kmeans temporary context",
ALLOCSET_DEFAULT_SIZES);
oldCtx = MemoryContextSwitchTo(kmeansCtx);
/* Allocate space */ /* Allocate space */
/* Use float instead of double to save memory */ /* Use float instead of double to save memory */
centerCounts = palloc(centerCountsSize); centerCounts = palloc(centerCountsSize);
@@ -399,50 +244,29 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
halfcdist = palloc_extended(halfcdistSize, MCXT_ALLOC_HUGE); halfcdist = palloc_extended(halfcdistSize, MCXT_ALLOC_HUGE);
newcdist = palloc(newcdistSize); newcdist = palloc(newcdistSize);
aggCenters = VectorArrayInit(numCenters, dimensions, VECTOR_SIZE(dimensions)); newCenters = VectorArrayInit(numCenters, dimensions);
for (int j = 0; j < numCenters; j++) for (j = 0; j < numCenters; j++)
{ {
Vector *vec = (Vector *) VectorArrayGet(aggCenters, j); vec = VectorArrayGet(newCenters, j);
SET_VARSIZE(vec, VECTOR_SIZE(dimensions)); SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions; vec->dim = dimensions;
} }
if (type == IVFFLAT_TYPE_VECTOR)
{
/* Use same centers to save memory */
newCenters = aggCenters;
}
else if (type == IVFFLAT_TYPE_HALFVEC)
{
newCenters = VectorArrayInit(numCenters, dimensions, centers->itemsize);
for (int j = 0; j < numCenters; j++)
{
HalfVector *vec = (HalfVector *) VectorArrayGet(newCenters, j);
SET_VARSIZE(vec, HALFVEC_SIZE(dimensions));
vec->dim = dimensions;
}
}
else
elog(ERROR, "Unsupported type");
#ifdef IVFFLAT_MEMORY #ifdef IVFFLAT_MEMORY
ShowMemoryUsage(oldCtx, totalSize); ShowMemoryUsage(totalSize);
#endif #endif
/* Pick initial centers */ /* Pick initial centers */
InitCenters(index, samples, centers, lowerBound); InitCenters(index, samples, centers, lowerBound);
/* Assign each x to its closest initial center c(x) = argmin d(x,c) */ /* Assign each x to its closest initial center c(x) = argmin d(x,c) */
for (int64 j = 0; j < numSamples; j++) for (j = 0; j < numSamples; j++)
{ {
float minDistance = FLT_MAX; float minDistance = FLT_MAX;
int closestCenter = 0; int closestCenter = 0;
/* Find closest center */ /* Find closest center */
for (int64 k = 0; k < numCenters; k++) for (k = 0; k < numCenters; k++)
{ {
/* TODO Use Lemma 1 in k-means++ initialization */ /* TODO Use Lemma 1 in k-means++ initialization */
float distance = lowerBound[j * numCenters + k]; float distance = lowerBound[j * numCenters + k];
@@ -468,13 +292,13 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
CHECK_FOR_INTERRUPTS(); CHECK_FOR_INTERRUPTS();
/* Step 1: For all centers, compute distance */ /* Step 1: For all centers, compute distance */
for (int64 j = 0; j < numCenters; j++) for (j = 0; j < numCenters; j++)
{ {
Datum vec = PointerGetDatum(VectorArrayGet(centers, j)); vec = VectorArrayGet(centers, j);
for (int64 k = j + 1; k < numCenters; k++) for (k = j + 1; k < numCenters; k++)
{ {
float distance = 0.5 * DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, k)))); float distance = 0.5 * DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
halfcdist[j * numCenters + k] = distance; halfcdist[j * numCenters + k] = distance;
halfcdist[k * numCenters + j] = distance; halfcdist[k * numCenters + j] = distance;
@@ -482,11 +306,11 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
} }
/* For all centers c, compute s(c) */ /* For all centers c, compute s(c) */
for (int64 j = 0; j < numCenters; j++) for (j = 0; j < numCenters; j++)
{ {
float minDistance = FLT_MAX; float minDistance = FLT_MAX;
for (int64 k = 0; k < numCenters; k++) for (k = 0; k < numCenters; k++)
{ {
float distance; float distance;
@@ -503,7 +327,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
rjreset = iteration != 0; rjreset = iteration != 0;
for (int64 j = 0; j < numSamples; j++) for (j = 0; j < numSamples; j++)
{ {
bool rj; bool rj;
@@ -513,9 +337,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
rj = rjreset; rj = rjreset;
for (int64 k = 0; k < numCenters; k++) for (k = 0; k < numCenters; k++)
{ {
Datum vec;
float dxcx; float dxcx;
/* Step 3: For all remaining points x and centers c */ /* Step 3: For all remaining points x and centers c */
@@ -528,12 +351,12 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
if (upperBound[j] <= halfcdist[closestCenters[j] * numCenters + k]) if (upperBound[j] <= halfcdist[closestCenters[j] * numCenters + k])
continue; continue;
vec = PointerGetDatum(VectorArrayGet(samples, j)); vec = VectorArrayGet(samples, j);
/* Step 3a */ /* Step 3a */
if (rj) if (rj)
{ {
dxcx = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, closestCenters[j])))); dxcx = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, closestCenters[j]))));
/* d(x,c(x)) computed, which is a form of d(x,c) */ /* d(x,c(x)) computed, which is a form of d(x,c) */
lowerBound[j * numCenters + closestCenters[j]] = dxcx; lowerBound[j * numCenters + closestCenters[j]] = dxcx;
@@ -547,7 +370,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
/* Step 3b */ /* Step 3b */
if (dxcx > lowerBound[j * numCenters + k] || dxcx > halfcdist[closestCenters[j] * numCenters + k]) if (dxcx > lowerBound[j * numCenters + k] || dxcx > halfcdist[closestCenters[j] * numCenters + k])
{ {
float dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, vec, PointerGetDatum(VectorArrayGet(centers, k)))); float dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
/* d(x,c) calculated */ /* d(x,c) calculated */
lowerBound[j * numCenters + k] = dxc; lowerBound[j * numCenters + k] = dxc;
@@ -566,15 +389,66 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
} }
/* Step 4: For each center c, let m(c) be mean of all points assigned */ /* Step 4: For each center c, let m(c) be mean of all points assigned */
ComputeNewCenters(samples, aggCenters, newCenters, centerCounts, closestCenters, normprocinfo, collation, type); for (j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(newCenters, j);
for (k = 0; k < dimensions; k++)
vec->x[k] = 0.0;
centerCounts[j] = 0;
}
for (j = 0; j < numSamples; j++)
{
int closestCenter;
vec = VectorArrayGet(samples, j);
closestCenter = closestCenters[j];
/* Increment sum and count of closest center */
newCenter = VectorArrayGet(newCenters, closestCenter);
for (k = 0; k < dimensions; k++)
newCenter->x[k] += vec->x[k];
centerCounts[closestCenter] += 1;
}
for (j = 0; j < numCenters; j++)
{
vec = VectorArrayGet(newCenters, j);
if (centerCounts[j] > 0)
{
/* Double avoids overflow, but requires more memory */
/* TODO Update bounds */
for (k = 0; k < dimensions; k++)
{
if (isinf(vec->x[k]))
vec->x[k] = vec->x[k] > 0 ? FLT_MAX : -FLT_MAX;
}
for (k = 0; k < dimensions; k++)
vec->x[k] /= centerCounts[j];
}
else
{
/* TODO Handle empty centers properly */
for (k = 0; k < dimensions; k++)
vec->x[k] = RandomDouble();
}
/* Normalize if needed */
if (normprocinfo != NULL)
ApplyNorm(normprocinfo, collation, vec);
}
/* Step 5 */ /* Step 5 */
for (int j = 0; j < numCenters; j++) for (j = 0; j < numCenters; j++)
newcdist[j] = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(VectorArrayGet(centers, j)), PointerGetDatum(VectorArrayGet(newCenters, j)))); newcdist[j] = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(VectorArrayGet(centers, j)), PointerGetDatum(VectorArrayGet(newCenters, j))));
for (int64 j = 0; j < numSamples; j++) for (j = 0; j < numSamples; j++)
{ {
for (int64 k = 0; k < numCenters; k++) for (k = 0; k < numCenters; k++)
{ {
float distance = lowerBound[j * numCenters + k] - newcdist[k]; float distance = lowerBound[j * numCenters + k] - newcdist[k];
@@ -587,26 +461,32 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatTyp
/* Step 6 */ /* Step 6 */
/* We reset r(x) before Step 3 in the next iteration */ /* We reset r(x) before Step 3 in the next iteration */
for (int j = 0; j < numSamples; j++) for (j = 0; j < numSamples; j++)
upperBound[j] += newcdist[closestCenters[j]]; upperBound[j] += newcdist[closestCenters[j]];
/* Step 7 */ /* Step 7 */
for (int j = 0; j < numCenters; j++) for (j = 0; j < numCenters; j++)
VectorArraySet(centers, j, VectorArrayGet(newCenters, j)); VectorArraySet(centers, j, VectorArrayGet(newCenters, j));
if (changes == 0 && iteration != 0) if (changes == 0 && iteration != 0)
break; break;
} }
MemoryContextSwitchTo(oldCtx); VectorArrayFree(newCenters);
MemoryContextDelete(kmeansCtx); pfree(centerCounts);
pfree(closestCenters);
pfree(lowerBound);
pfree(upperBound);
pfree(s);
pfree(halfcdist);
pfree(newcdist);
} }
/* /*
* Detect issues with centers * Detect issues with centers
*/ */
static void static void
CheckCenters(Relation index, VectorArray centers, IvfflatType type) CheckCenters(Relation index, VectorArray centers)
{ {
FmgrInfo *normprocinfo; FmgrInfo *normprocinfo;
@@ -616,48 +496,24 @@ CheckCenters(Relation index, VectorArray centers, IvfflatType type)
/* Ensure no NaN or infinite values */ /* Ensure no NaN or infinite values */
for (int i = 0; i < centers->length; i++) for (int i = 0; i < centers->length; i++)
{ {
if (type == IVFFLAT_TYPE_VECTOR) Vector *vec = VectorArrayGet(centers, i);
for (int j = 0; j < vec->dim; j++)
{ {
Vector *vec = (Vector *) VectorArrayGet(centers, i); if (isnan(vec->x[j]))
elog(ERROR, "NaN detected. Please report a bug.");
for (int j = 0; j < vec->dim; j++) if (isinf(vec->x[j]))
{ elog(ERROR, "Infinite value detected. Please report a bug.");
if (isnan(vec->x[j]))
elog(ERROR, "NaN detected. Please report a bug.");
if (isinf(vec->x[j]))
elog(ERROR, "Infinite value detected. Please report a bug.");
}
} }
else if (type == IVFFLAT_TYPE_HALFVEC)
{
HalfVector *vec = (HalfVector *) VectorArrayGet(centers, i);
for (int j = 0; j < vec->dim; j++)
{
if (HalfIsNan(vec->x[j]))
elog(ERROR, "NaN detected. Please report a bug.");
if (HalfIsInf(vec->x[j]))
elog(ERROR, "Infinite value detected. Please report a bug.");
}
}
else
elog(ERROR, "Unsupported type");
} }
/* Ensure no duplicate centers */ /* Ensure no duplicate centers */
/* Fine to sort in-place */ /* Fine to sort in-place */
if (type == IVFFLAT_TYPE_VECTOR) qsort(centers->items, centers->length, VECTOR_SIZE(centers->dim), CompareVectors);
qsort(centers->items, centers->length, centers->itemsize, CompareVectors);
else if (type == IVFFLAT_TYPE_HALFVEC)
qsort(centers->items, centers->length, centers->itemsize, CompareHalfVectors);
else
elog(ERROR, "Unsupported type");
for (int i = 1; i < centers->length; i++) for (int i = 1; i < centers->length; i++)
{ {
if (datumIsEqual(PointerGetDatum(VectorArrayGet(centers, i)), PointerGetDatum(VectorArrayGet(centers, i - 1)), false, -1)) if (CompareVectors(VectorArrayGet(centers, i), VectorArrayGet(centers, i - 1)) == 0)
elog(ERROR, "Duplicate centers detected. Please report a bug."); elog(ERROR, "Duplicate centers detected. Please report a bug.");
} }
@@ -683,12 +539,12 @@ CheckCenters(Relation index, VectorArray centers, IvfflatType type)
* We use spherical k-means for inner product and cosine * We use spherical k-means for inner product and cosine
*/ */
void void
IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, IvfflatType type) IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers)
{ {
if (samples->length <= centers->maxlen) if (samples->length <= centers->maxlen)
QuickCenters(index, samples, centers, type); QuickCenters(index, samples, centers);
else else
ElkanKmeans(index, samples, centers, type); ElkanKmeans(index, samples, centers);
CheckCenters(index, centers, type); CheckCenters(index, centers);
} }

View File

@@ -5,7 +5,6 @@
#include "access/relscan.h" #include "access/relscan.h"
#include "catalog/pg_operator_d.h" #include "catalog/pg_operator_d.h"
#include "catalog/pg_type_d.h" #include "catalog/pg_type_d.h"
#include "halfvec.h"
#include "lib/pairingheap.h" #include "lib/pairingheap.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "miscadmin.h" #include "miscadmin.h"
@@ -178,42 +177,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
tuplesort_performsort(so->sortstate); tuplesort_performsort(so->sortstate);
} }
/*
* Get scan value
*/
static Datum
GetScanValue(IndexScanDesc scan)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL)
{
IvfflatType type = IvfflatGetType(scan->indexRelation);
if (type == IVFFLAT_TYPE_VECTOR)
value = PointerGetDatum(InitVector(so->dimensions));
else if (type == IVFFLAT_TYPE_HALFVEC)
value = PointerGetDatum(InitHalfVector(so->dimensions));
else
elog(ERROR, "Unsupported type");
}
else
{
value = scan->orderByData->sk_argument;
/* Value should not be compressed or toasted */
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Fine if normalization fails */
if (so->normprocinfo != NULL)
IvfflatNormValue(so->normprocinfo, so->collation, &value, IvfflatGetType(scan->indexRelation));
}
return value;
}
/* /*
* Prepare for an index scan * Prepare for an index scan
*/ */
@@ -318,7 +281,21 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
if (!IsMVCCSnapshot(scan->xs_snapshot)) if (!IsMVCCSnapshot(scan->xs_snapshot))
elog(ERROR, "non-MVCC snapshots are not supported with ivfflat"); elog(ERROR, "non-MVCC snapshots are not supported with ivfflat");
value = GetScanValue(scan); if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(so->dimensions));
else
{
value = scan->orderByData->sk_argument;
/* Value should not be compressed or toasted */
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Fine if normalization fails */
if (so->normprocinfo != NULL)
IvfflatNormValue(so->normprocinfo, so->collation, &value, NULL);
}
IvfflatBench("GetScanLists", GetScanLists(scan, value)); IvfflatBench("GetScanLists", GetScanLists(scan, value));
IvfflatBench("GetScanItems", GetScanItems(scan, value)); IvfflatBench("GetScanItems", GetScanItems(scan, value));
so->first = false; so->first = false;

View File

@@ -1,27 +1,22 @@
#include "postgres.h" #include "postgres.h"
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "catalog/pg_type.h"
#include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "vector.h" #include "vector.h"
#include "utils/syscache.h"
/* /*
* Allocate a vector array * Allocate a vector array
*/ */
VectorArray VectorArray
VectorArrayInit(int maxlen, int dimensions, Size itemsize) VectorArrayInit(int maxlen, int dimensions)
{ {
VectorArray res = palloc(sizeof(VectorArrayData)); VectorArray res = palloc(sizeof(VectorArrayData));
res->length = 0; res->length = 0;
res->maxlen = maxlen; res->maxlen = maxlen;
res->dim = dimensions; res->dim = dimensions;
res->itemsize = itemsize; res->items = palloc_extended(maxlen * VECTOR_SIZE(dimensions), MCXT_ALLOC_ZERO | MCXT_ALLOC_HUGE);
res->items = palloc_extended(maxlen * itemsize, MCXT_ALLOC_ZERO | MCXT_ALLOC_HUGE);
return res; return res;
} }
@@ -35,6 +30,16 @@ VectorArrayFree(VectorArray arr)
pfree(arr); pfree(arr);
} }
/*
* Print vector array - useful for debugging
*/
void
PrintVectorArray(char *msg, VectorArray arr)
{
for (int i = 0; i < arr->length; i++)
PrintVector(msg, VectorArrayGet(arr, i));
}
/* /*
* Get the number of lists in the index * Get the number of lists in the index
*/ */
@@ -61,37 +66,6 @@ IvfflatOptionalProcInfo(Relation index, uint16 procnum)
return index_getprocinfo(index, 1, procnum); return index_getprocinfo(index, 1, procnum);
} }
/*
* Get type
*/
IvfflatType
IvfflatGetType(Relation index)
{
Oid typid = TupleDescAttr(index->rd_att, 0)->atttypid;
HeapTuple tuple;
Form_pg_type type;
IvfflatType result;
tuple = SearchSysCache1(TYPEOID, ObjectIdGetDatum(typid));
if (!HeapTupleIsValid(tuple))
elog(ERROR, "cache lookup failed for type %u", typid);
type = (Form_pg_type) GETSTRUCT(tuple);
if (strcmp(NameStr(type->typname), "vector") == 0)
result = IVFFLAT_TYPE_VECTOR;
else if (strcmp(NameStr(type->typname), "halfvec") == 0)
result = IVFFLAT_TYPE_HALFVEC;
else
{
ReleaseSysCache(tuple);
elog(ERROR, "type not supported for ivfflat index");
}
ReleaseSysCache(tuple);
return result;
}
/* /*
* Divide by the norm * Divide by the norm
* *
@@ -101,34 +75,21 @@ IvfflatGetType(Relation index)
* if it's different than the original value * if it's different than the original value
*/ */
bool bool
IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, IvfflatType type) IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
{ {
double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value)); double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0) if (norm > 0)
{ {
if (type == IVFFLAT_TYPE_VECTOR) Vector *v = DatumGetVector(*value);
{
Vector *v = DatumGetVector(*value);
Vector *result = InitVector(v->dim);
for (int i = 0; i < v->dim; i++) if (result == NULL)
result->x[i] = v->x[i] / norm; result = InitVector(v->dim);
*value = PointerGetDatum(result); for (int i = 0; i < v->dim; i++)
} result->x[i] = v->x[i] / norm;
else if (type == IVFFLAT_TYPE_HALFVEC)
{
HalfVector *v = DatumGetHalfVector(*value);
HalfVector *result = InitHalfVector(v->dim);
for (int i = 0; i < v->dim; i++) *value = PointerGetDatum(result);
result->x[i] = Float4ToHalfUnchecked(HalfToFloat4(v->x[i]) / norm);
*value = PointerGetDatum(result);
}
else
elog(ERROR, "Unsupported type");
return true; return true;
} }

View File

@@ -1,800 +0,0 @@
#include "postgres.h"
#include <limits.h>
#include <math.h>
#include "fmgr.h"
#include "libpq/pqformat.h"
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "vector.h"
#if PG_VERSION_NUM >= 120000
#include "common/shortest_dec.h"
#include "utils/float.h"
#else
#include <float.h>
#include "utils/builtins.h"
#endif
/*
* Ensure same dimensions
*/
static inline void
CheckDims(SparseVector * a, SparseVector * b)
{
if (a->dim != b->dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different sparsevec dimensions %d and %d", a->dim, b->dim)));
}
/*
* Ensure expected dimensions
*/
static inline void
CheckExpectedDim(int32 typmod, int dim)
{
if (typmod != -1 && typmod != dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected %d dimensions, not %d", typmod, dim)));
}
/*
* Ensure valid dimensions
*/
static inline void
CheckDim(int dim)
{
if (dim < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("sparsevec must have at least 1 dimension")));
if (dim > SPARSEVEC_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d dimensions", SPARSEVEC_MAX_DIM)));
}
/*
* Ensure valid nnz
*/
static inline void
CheckNnz(int nnz, int dim)
{
if (nnz < 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("sparsevec cannot have negative number of elements")));
if (nnz > SPARSEVEC_MAX_NNZ)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d non-zero elements", SPARSEVEC_MAX_NNZ)));
if (nnz > dim)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more elements than dimensions")));
}
/*
* Ensure valid index
*/
static inline void
CheckIndex(int32 *indices, int i, int dim)
{
int32 index = indices[i];
if (index < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("index must be greater than zero")));
if (index > dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("index must be less than or equal to dimensions")));
if (i > 0)
{
if (index < indices[i - 1])
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("indexes must be in ascending order")));
if (index == indices[i - 1])
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("indexes must not contain duplicates")));
}
}
/*
* Ensure finite element
*/
static inline void
CheckElement(float value)
{
if (isnan(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("NaN not allowed in sparsevec")));
if (isinf(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("infinite value not allowed in sparsevec")));
}
/*
* Allocate and initialize a new sparse vector
*/
SparseVector *
InitSparseVector(int dim, int nnz)
{
SparseVector *result;
int size;
size = SPARSEVEC_SIZE(nnz);
result = (SparseVector *) palloc0(size);
SET_VARSIZE(result, size);
result->dim = dim;
result->nnz = nnz;
return result;
}
/*
* Check for whitespace, since array_isspace() is static
*/
static inline bool
sparsevec_isspace(char ch)
{
if (ch == ' ' ||
ch == '\t' ||
ch == '\n' ||
ch == '\r' ||
ch == '\v' ||
ch == '\f')
return true;
return false;
}
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_in);
Datum
sparsevec_in(PG_FUNCTION_ARGS)
{
char *lit = PG_GETARG_CSTRING(0);
int32 typmod = PG_GETARG_INT32(2);
int dim;
char *pt = lit;
char *stringEnd;
SparseVector *result;
float *rvalues;
int32 *indices;
float *values;
int maxNnz;
int nnz = 0;
maxNnz = 1;
while (*pt != '\0')
{
if (*pt == ',')
maxNnz++;
pt++;
}
if (maxNnz > SPARSEVEC_MAX_NNZ)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d non-zero elements", SPARSEVEC_MAX_NNZ)));
indices = palloc(maxNnz * sizeof(int32));
values = palloc(maxNnz * sizeof(float));
pt = lit;
while (sparsevec_isspace(*pt))
pt++;
if (*pt != '{')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit),
errdetail("Vector contents must start with \"{\".")));
pt++;
while (sparsevec_isspace(*pt))
pt++;
if (*pt == '}')
pt++;
else
{
for (;;)
{
long index;
float value;
/* TODO Better error */
if (nnz == maxNnz)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("ran out of buffer: \"%s\"", lit)));
while (sparsevec_isspace(*pt))
pt++;
/* Check for empty string like float4in */
if (*pt == '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
/* Use similar logic as int2vectorin */
errno = 0;
index = strtol(pt, &stringEnd, 10);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
if (errno == ERANGE || index < 1 || index > INT_MAX)
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("index \"%ld\" is out of range for type sparsevec", index)));
pt = stringEnd;
while (sparsevec_isspace(*pt))
pt++;
if (*pt != ':')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
pt++;
while (sparsevec_isspace(*pt))
pt++;
errno = 0;
/* Use strtof like float4in to avoid a double-rounding problem */
/* Postgres sets LC_NUMERIC to C on startup */
value = strtof(pt, &stringEnd);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
/* Check for range error like float4in */
if (errno == ERANGE && (value == 0 || isinf(value)))
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type sparsevec", pnstrdup(pt, stringEnd - pt))));
CheckElement(value);
/* Do not store zero values */
if (value != 0)
{
indices[nnz] = index;
values[nnz] = value;
nnz++;
}
pt = stringEnd;
while (sparsevec_isspace(*pt))
pt++;
if (*pt == ',')
pt++;
else if (*pt == '}')
{
pt++;
break;
}
else
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
}
}
while (sparsevec_isspace(*pt))
pt++;
if (*pt != '/')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit),
errdetail("Unexpected end of input.")));
pt++;
while (sparsevec_isspace(*pt))
pt++;
/* Use similar logic as int2vectorin */
errno = 0;
dim = strtol(pt, &stringEnd, 10);
if (stringEnd == pt)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit)));
pt = stringEnd;
/* Only whitespace is allowed after the closing brace */
while (sparsevec_isspace(*pt))
pt++;
if (*pt != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type sparsevec: \"%s\"", lit),
errdetail("Junk after closing.")));
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitSparseVector(dim, nnz);
rvalues = SPARSEVEC_VALUES(result);
for (int i = 0; i < nnz; i++)
{
result->indices[i] = indices[i];
rvalues[i] = values[i];
CheckIndex(result->indices, i, dim);
}
PG_RETURN_POINTER(result);
}
#define AppendChar(ptr, c) (*(ptr)++ = (c))
#define AppendFloat(ptr, f) ((ptr) += float_to_shortest_decimal_bufn((f), (ptr)))
#if PG_VERSION_NUM >= 140000
#define AppendInt(ptr, i) ((ptr) += pg_ltoa((i), (ptr)))
#else
#define AppendInt(ptr, i) \
do { \
pg_ltoa(i, ptr); \
while (*ptr != '\0') \
ptr++; \
} while (0)
#endif
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_out);
Datum
sparsevec_out(PG_FUNCTION_ARGS)
{
SparseVector *sparsevec = PG_GETARG_SPARSEVEC_P(0);
float *values = SPARSEVEC_VALUES(sparsevec);
char *buf;
char *ptr;
/*
* Need:
*
* nnz * 10 bytes for index (positive integer)
*
* nnz bytes for :
*
* nnz * (FLOAT_SHORTEST_DECIMAL_LEN - 1) bytes for
* float_to_shortest_decimal_bufn
*
* nnz - 1 bytes for ,
*
* 10 bytes for dimensions
*
* 4 bytes for {, }, /, and \0
*/
buf = (char *) palloc((11 + FLOAT_SHORTEST_DECIMAL_LEN) * sparsevec->nnz + 13);
ptr = buf;
AppendChar(ptr, '{');
for (int i = 0; i < sparsevec->nnz; i++)
{
if (i > 0)
AppendChar(ptr, ',');
AppendInt(ptr, sparsevec->indices[i]);
AppendChar(ptr, ':');
AppendFloat(ptr, values[i]);
}
AppendChar(ptr, '}');
AppendChar(ptr, '/');
AppendInt(ptr, sparsevec->dim);
*ptr = '\0';
PG_FREE_IF_COPY(sparsevec, 0);
PG_RETURN_CSTRING(buf);
}
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_typmod_in);
Datum
sparsevec_typmod_in(PG_FUNCTION_ARGS)
{
ArrayType *ta = PG_GETARG_ARRAYTYPE_P(0);
int32 *tl;
int n;
tl = ArrayGetIntegerTypmods(ta, &n);
if (n != 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("invalid type modifier")));
if (*tl < 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type sparsevec must be at least 1")));
if (*tl > SPARSEVEC_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type sparsevec cannot exceed %d", SPARSEVEC_MAX_DIM)));
PG_RETURN_INT32(*tl);
}
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_recv);
Datum
sparsevec_recv(PG_FUNCTION_ARGS)
{
StringInfo buf = (StringInfo) PG_GETARG_POINTER(0);
int32 typmod = PG_GETARG_INT32(2);
SparseVector *result;
int32 dim;
int32 nnz;
int32 unused;
float *values;
dim = pq_getmsgint(buf, sizeof(int32));
nnz = pq_getmsgint(buf, sizeof(int32));
unused = pq_getmsgint(buf, sizeof(int32));
CheckDim(dim);
CheckNnz(nnz, dim);
CheckExpectedDim(typmod, dim);
if (unused != 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected unused to be 0, not %d", unused)));
result = InitSparseVector(dim, nnz);
values = SPARSEVEC_VALUES(result);
for (int i = 0; i < nnz; i++)
{
result->indices[i] = pq_getmsgint(buf, sizeof(int32));
CheckIndex(result->indices, i, dim);
}
for (int i = 0; i < nnz; i++)
{
values[i] = pq_getmsgfloat4(buf);
CheckElement(values[i]);
}
PG_RETURN_POINTER(result);
}
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_send);
Datum
sparsevec_send(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
float *values = SPARSEVEC_VALUES(svec);
StringInfoData buf;
pq_begintypsend(&buf);
pq_sendint(&buf, svec->dim, sizeof(int32));
pq_sendint(&buf, svec->nnz, sizeof(int32));
pq_sendint(&buf, svec->unused, sizeof(int32));
for (int i = 0; i < svec->nnz; i++)
pq_sendint(&buf, svec->indices[i], sizeof(int32));
for (int i = 0; i < svec->nnz; i++)
pq_sendfloat4(&buf, values[i]);
PG_RETURN_BYTEA_P(pq_endtypsend(&buf));
}
/*
* Convert sparse vector to sparse vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec);
Datum
sparsevec(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
CheckExpectedDim(typmod, svec->dim);
PG_RETURN_POINTER(svec);
}
/*
* Convert dense vector to sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_sparsevec);
Datum
vector_to_sparsevec(PG_FUNCTION_ARGS)
{
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
SparseVector *result;
int dim = vec->dim;
int nnz = 0;
float *values;
int j = 0;
CheckDim(dim);
CheckExpectedDim(typmod, dim);
for (int i = 0; i < dim; i++)
{
if (vec->x[i] != 0)
nnz++;
}
result = InitSparseVector(dim, nnz);
values = SPARSEVEC_VALUES(result);
for (int i = 0; i < dim; i++)
{
if (vec->x[i] != 0)
{
/* Safety check */
if (j == nnz)
elog(ERROR, "safety check failed");
result->indices[j] = i + 1;
values[j] = vec->x[i];
j++;
}
}
PG_RETURN_POINTER(result);
}
/*
* Get the L2 squared distance between sparse vectors
*/
static double
SparsevecL2SquaredDistance(SparseVector * a, SparseVector * b)
{
float *ax = SPARSEVEC_VALUES(a);
float *bx = SPARSEVEC_VALUES(b);
double distance = 0.0;
int bpos = 0;
for (int i = 0; i < a->nnz; i++)
{
int ai = a->indices[i];
int bi = -1;
for (int j = bpos; j < b->nnz; j++)
{
bi = b->indices[j];
if (ai == bi)
{
double diff = ax[i] - bx[j];
distance += diff * diff;
}
else if (ai > bi)
distance += bx[j] * bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
if (ai != bi)
distance += ax[i] * ax[i];
}
for (int j = bpos; j < b->nnz; j++)
distance += bx[j] * bx[j];
return distance;
}
/*
* Get the L2 distance between sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_distance);
Datum
sparsevec_l2_distance(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(sqrt(SparsevecL2SquaredDistance(a, b)));
}
/*
* Get the L2 squared distance between sparse vectors
* This saves a sqrt calculation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_squared_distance);
Datum
sparsevec_l2_squared_distance(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(SparsevecL2SquaredDistance(a, b));
}
/*
* Get the inner product of two sparse vectors
*/
static double
SparsevecInnerProduct(SparseVector * a, SparseVector * b)
{
float *ax = SPARSEVEC_VALUES(a);
float *bx = SPARSEVEC_VALUES(b);
double distance = 0.0;
int bpos = 0;
for (int i = 0; i < a->nnz; i++)
{
int ai = a->indices[i];
for (int j = bpos; j < b->nnz; j++)
{
int bi = b->indices[j];
/* Only update when the same index */
if (ai == bi)
distance += ax[i] * bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
}
return distance;
}
/*
* Get the inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_inner_product);
Datum
sparsevec_inner_product(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(SparsevecInnerProduct(a, b));
}
/*
* Get the negative inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_negative_inner_product);
Datum
sparsevec_negative_inner_product(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(-SparsevecInnerProduct(a, b));
}
/*
* Get the cosine distance between two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_cosine_distance);
Datum
sparsevec_cosine_distance(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
SparseVector *b = PG_GETARG_SPARSEVEC_P(1);
float *ax = SPARSEVEC_VALUES(a);
float *bx = SPARSEVEC_VALUES(b);
float norma = 0.0;
float normb = 0.0;
double similarity;
CheckDims(a, b);
similarity = SparsevecInnerProduct(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->nnz; i++)
norma += ax[i] * ax[i];
/* Auto-vectorized */
for (int i = 0; i < b->nnz; i++)
normb += bx[i] * bx[i];
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
similarity /= sqrt((double) norma * (double) normb);
#ifdef _MSC_VER
/* /fp:fast may not propagate NaN */
if (isnan(similarity))
PG_RETURN_FLOAT8(NAN);
#endif
/* Keep in range */
if (similarity > 1)
similarity = 1.0;
else if (similarity < -1)
similarity = -1.0;
PG_RETURN_FLOAT8(1.0 - similarity);
}
/*
* Get the L2 norm of a sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_norm);
Datum
sparsevec_norm(PG_FUNCTION_ARGS)
{
SparseVector *a = PG_GETARG_SPARSEVEC_P(0);
float *ax = SPARSEVEC_VALUES(a);
double norm = 0.0;
/* Auto-vectorized */
for (int i = 0; i < a->nnz; i++)
norm += (double) ax[i] * (double) ax[i];
PG_RETURN_FLOAT8(sqrt(norm));
}

View File

@@ -1,25 +0,0 @@
#ifndef SPARSEVEC_H
#define SPARSEVEC_H
#define SPARSEVEC_MAX_DIM 100000
#define SPARSEVEC_MAX_NNZ 16000
/* Ensure values are aligned */
#define SPARSEVEC_SIZE(_nnz) (offsetof(SparseVector, indices) + MAXALIGN((_nnz) * sizeof(int32)) + (_nnz * sizeof(float)))
#define SPARSEVEC_VALUES(x) ((float *) (((char *) (x)) + offsetof(SparseVector, indices) + MAXALIGN((x)->nnz * sizeof(int32))))
#define DatumGetSparseVector(x) ((SparseVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_SPARSEVEC_P(x) DatumGetSparseVector(PG_GETARG_DATUM(x))
#define PG_RETURN_SPARSEVEC_P(x) PG_RETURN_POINTER(x)
typedef struct SparseVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int32 dim; /* number of dimensions */
int32 nnz;
int32 unused;
int32 indices[FLEXIBLE_ARRAY_MEMBER];
} SparseVector;
SparseVector *InitSparseVector(int dim, int nnz);
#endif

View File

@@ -2,18 +2,15 @@
#include <math.h> #include <math.h>
#include "bitvector.h"
#include "catalog/pg_type.h" #include "catalog/pg_type.h"
#include "common/shortest_dec.h" #include "common/shortest_dec.h"
#include "fmgr.h" #include "fmgr.h"
#include "halfutils.h"
#include "halfvec.h" #include "halfvec.h"
#include "hnsw.h" #include "hnsw.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "lib/stringinfo.h" #include "lib/stringinfo.h"
#include "libpq/pqformat.h" #include "libpq/pqformat.h"
#include "port.h" /* for strtof() */ #include "port.h" /* for strtof() */
#include "sparsevec.h"
#include "utils/array.h" #include "utils/array.h"
#include "utils/builtins.h" #include "utils/builtins.h"
#include "utils/float.h" #include "utils/float.h"
@@ -33,13 +30,6 @@
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1) #define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1)) #define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
/* target_clones requires glibc */
#if defined(__x86_64__) && defined(__gnu_linux__) && defined(__has_attribute) && __has_attribute(target_clones) && !defined(__FMA__)
#define VECTOR_DISPATCH __attribute__((target_clones("default", "fma")))
#else
#define VECTOR_DISPATCH
#endif
PG_MODULE_MAGIC; PG_MODULE_MAGIC;
/* /*
@@ -49,7 +39,6 @@ PGDLLEXPORT void _PG_init(void);
void void
_PG_init(void) _PG_init(void)
{ {
HalfvecInit();
HnswInit(); HnswInit();
IvfflatInit(); IvfflatInit();
} }
@@ -188,33 +177,27 @@ vector_in(PG_FUNCTION_ARGS)
int32 typmod = PG_GETARG_INT32(2); int32 typmod = PG_GETARG_INT32(2);
float x[VECTOR_MAX_DIM]; float x[VECTOR_MAX_DIM];
int dim = 0; int dim = 0;
char *pt = lit; char *pt;
char *stringEnd;
Vector *result; Vector *result;
char *litcopy = pstrdup(lit);
char *str = litcopy;
while (vector_isspace(*pt)) while (vector_isspace(*str))
pt++; str++;
if (*pt != '[') if (*str != '[')
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit), errmsg("malformed vector literal: \"%s\"", lit),
errdetail("Vector contents must start with \"[\"."))); errdetail("Vector contents must start with \"[\".")));
pt++; str++;
pt = strtok(str, ",");
stringEnd = pt;
while (vector_isspace(*pt)) while (pt != NULL && *stringEnd != ']')
pt++;
if (*pt == ']')
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
for (;;)
{ {
float val;
char *stringEnd;
if (dim == VECTOR_MAX_DIM) if (dim == VECTOR_MAX_DIM)
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED), (errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
@@ -229,55 +212,61 @@ vector_in(PG_FUNCTION_ARGS)
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit))); errmsg("invalid input syntax for type vector: \"%s\"", lit)));
errno = 0;
/* Use strtof like float4in to avoid a double-rounding problem */ /* Use strtof like float4in to avoid a double-rounding problem */
/* Postgres sets LC_NUMERIC to C on startup */ x[dim] = strtof(pt, &stringEnd);
val = strtof(pt, &stringEnd); CheckElement(x[dim]);
dim++;
if (stringEnd == pt) if (stringEnd == pt)
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit))); errmsg("invalid input syntax for type vector: \"%s\"", lit)));
/* Check for range error like float4in */ while (vector_isspace(*stringEnd))
if (errno == ERANGE && isinf(val)) stringEnd++;
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("\"%s\" is out of range for type vector", pnstrdup(pt, stringEnd - pt))));
CheckElement(val); if (*stringEnd != '\0' && *stringEnd != ']')
x[dim++] = val;
pt = stringEnd;
while (vector_isspace(*pt))
pt++;
if (*pt == ',')
pt++;
else if (*pt == ']')
{
pt++;
break;
}
else
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit))); errmsg("invalid input syntax for type vector: \"%s\"", lit)));
pt = strtok(NULL, ",");
} }
/* Only whitespace is allowed after the closing brace */ if (stringEnd == NULL || *stringEnd != ']')
while (vector_isspace(*pt))
pt++;
if (*pt != '\0')
ereport(ERROR, ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION), (errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("invalid input syntax for type vector: \"%s\"", lit), errmsg("malformed vector literal: \"%s\"", lit),
errdetail("Unexpected end of input.")));
stringEnd++;
/* Only whitespace is allowed after the closing brace */
while (vector_isspace(*stringEnd))
stringEnd++;
if (*stringEnd != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit),
errdetail("Junk after closing right brace."))); errdetail("Junk after closing right brace.")));
CheckDim(dim); /* Ensure no consecutive delimiters since strtok skips */
for (pt = lit + 1; *pt != '\0'; pt++)
{
if (pt[-1] == ',' && *pt == ',')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed vector literal: \"%s\"", lit)));
}
if (dim < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
pfree(litcopy);
CheckExpectedDim(typmod, dim); CheckExpectedDim(typmod, dim);
result = InitVector(dim); result = InitVector(dim);
@@ -287,9 +276,6 @@ vector_in(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
#define AppendChar(ptr, c) (*(ptr)++ = (c))
#define AppendFloat(ptr, f) ((ptr) += float_to_shortest_decimal_bufn((f), (ptr)))
/* /*
* Convert internal representation to textual representation * Convert internal representation to textual representation
*/ */
@@ -301,6 +287,7 @@ vector_out(PG_FUNCTION_ARGS)
int dim = vector->dim; int dim = vector->dim;
char *buf; char *buf;
char *ptr; char *ptr;
int n;
/* /*
* Need: * Need:
@@ -315,17 +302,21 @@ vector_out(PG_FUNCTION_ARGS)
buf = (char *) palloc(FLOAT_SHORTEST_DECIMAL_LEN * dim + 2); buf = (char *) palloc(FLOAT_SHORTEST_DECIMAL_LEN * dim + 2);
ptr = buf; ptr = buf;
AppendChar(ptr, '['); *ptr = '[';
ptr++;
for (int i = 0; i < dim; i++) for (int i = 0; i < dim; i++)
{ {
if (i > 0) if (i > 0)
AppendChar(ptr, ','); {
*ptr = ',';
ptr++;
}
AppendFloat(ptr, vector->x[i]); n = float_to_shortest_decimal_bufn(vector->x[i], ptr);
ptr += n;
} }
*ptr = ']';
AppendChar(ptr, ']'); ptr++;
*ptr = '\0'; *ptr = '\0';
PG_FREE_IF_COPY(vector, 0); PG_FREE_IF_COPY(vector, 0);
@@ -564,22 +555,6 @@ halfvec_to_vector(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
VECTOR_DISPATCH static float
VectorL2SquaredDistance(int dim, float *ax, float *bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float diff = ax[i] - bx[i];
distance += diff * diff;
}
return distance;
}
/* /*
* Get the L2 distance between vectors * Get the L2 distance between vectors
*/ */
@@ -589,10 +564,21 @@ l2_distance(PG_FUNCTION_ARGS)
{ {
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
float diff;
CheckDims(a, b); CheckDims(a, b);
PG_RETURN_FLOAT8(sqrt((double) VectorL2SquaredDistance(a->dim, a->x, b->x))); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
diff = ax[i] - bx[i];
distance += diff * diff;
}
PG_RETURN_FLOAT8(sqrt((double) distance));
} }
/* /*
@@ -605,22 +591,21 @@ vector_l2_squared_distance(PG_FUNCTION_ARGS)
{ {
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
float diff;
CheckDims(a, b); CheckDims(a, b);
PG_RETURN_FLOAT8((double) VectorL2SquaredDistance(a->dim, a->x, b->x));
}
VECTOR_DISPATCH static float
VectorInnerProduct(int dim, float *ax, float *bx)
{
float distance = 0.0;
/* Auto-vectorized */ /* Auto-vectorized */
for (int i = 0; i < dim; i++) for (int i = 0; i < a->dim; i++)
distance += ax[i] * bx[i]; {
diff = ax[i] - bx[i];
distance += diff * diff;
}
return distance; PG_RETURN_FLOAT8((double) distance);
} }
/* /*
@@ -632,10 +617,17 @@ inner_product(PG_FUNCTION_ARGS)
{ {
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
CheckDims(a, b); CheckDims(a, b);
PG_RETURN_FLOAT8((double) VectorInnerProduct(a->dim, a->x, b->x)); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += ax[i] * bx[i];
PG_RETURN_FLOAT8((double) distance);
} }
/* /*
@@ -647,10 +639,17 @@ vector_negative_inner_product(PG_FUNCTION_ARGS)
{ {
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float distance = 0.0;
CheckDims(a, b); CheckDims(a, b);
PG_RETURN_FLOAT8((double) -VectorInnerProduct(a->dim, a->x, b->x)); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += ax[i] * bx[i];
PG_RETURN_FLOAT8((double) distance * -1);
} }
/* /*
@@ -708,11 +707,18 @@ vector_spherical_distance(PG_FUNCTION_ARGS)
{ {
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float dp = 0.0;
double distance; double distance;
CheckDims(a, b); CheckDims(a, b);
distance = (double) VectorInnerProduct(a->dim, a->x, b->x); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
dp += ax[i] * bx[i];
distance = (double) dp;
/* Prevent NaN with acos with loss of precision */ /* Prevent NaN with acos with loss of precision */
if (distance > 1) if (distance > 1)
@@ -877,56 +883,6 @@ vector_mul(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
/*
* Quantize a vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(quantize_binary);
Datum
quantize_binary(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
float *ax = a->x;
VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result);
for (int i = 0; i < a->dim; i++)
rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result);
}
/*
* Get a subvector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(subvector);
Datum
subvector(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
int32 start = PG_GETARG_INT32(1);
int32 count = PG_GETARG_INT32(2);
int32 end = start + count;
float *ax = a->x;
Vector *result;
int dim;
/* Indexing starts at 1, like substring */
if (start < 1)
start = 1;
if (end > a->dim)
end = a->dim + 1;
dim = end - start;
CheckDim(dim);
result = InitVector(dim);
for (int i = 0; i < dim; i++)
result->x[i] = ax[start - 1 + i];
PG_RETURN_POINTER(result);
}
/* /*
* Internal helper to compare vectors * Internal helper to compare vectors
*/ */
@@ -964,6 +920,9 @@ vector_lt(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) < 0); PG_RETURN_BOOL(vector_cmp_internal(a, b) < 0);
} }
@@ -977,6 +936,9 @@ vector_le(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) <= 0); PG_RETURN_BOOL(vector_cmp_internal(a, b) <= 0);
} }
@@ -990,6 +952,9 @@ vector_eq(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) == 0); PG_RETURN_BOOL(vector_cmp_internal(a, b) == 0);
} }
@@ -1003,6 +968,9 @@ vector_ne(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) != 0); PG_RETURN_BOOL(vector_cmp_internal(a, b) != 0);
} }
@@ -1016,6 +984,9 @@ vector_ge(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) >= 0); PG_RETURN_BOOL(vector_cmp_internal(a, b) >= 0);
} }
@@ -1029,6 +1000,9 @@ vector_gt(PG_FUNCTION_ARGS)
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1); Vector *b = PG_GETARG_VECTOR_P(1);
/* TODO Remove in 0.7.0 */
CheckDims(a, b);
PG_RETURN_BOOL(vector_cmp_internal(a, b) > 0); PG_RETURN_BOOL(vector_cmp_internal(a, b) > 0);
} }
@@ -1209,26 +1183,3 @@ vector_avg(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
/*
* Convert sparse vector to dense vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_to_vector);
Datum
sparsevec_to_vector(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
int dim = svec->dim;
float *values = SPARSEVEC_VALUES(svec);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitVector(dim);
for (int i = 0; i < svec->nnz; i++)
result->x[svec->indices[i] - 1] = values[i];
PG_RETURN_POINTER(result);
}

View File

@@ -1,104 +0,0 @@
SELECT hamming_distance('111', '111');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance('111', '110');
hamming_distance
------------------
1
(1 row)
SELECT hamming_distance('111', '100');
hamming_distance
------------------
2
(1 row)
SELECT hamming_distance('111', '000');
hamming_distance
------------------
3
(1 row)
SELECT hamming_distance('10101010101010101010', '01010101010101010101');
hamming_distance
------------------
20
(1 row)
SELECT hamming_distance('', '');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance('111', '00');
ERROR: different bit lengths 3 and 2
SELECT hamming_distance('111', '000'::varbit(4));
hamming_distance
------------------
3
(1 row)
SELECT hamming_distance('111', '0000'::varbit(4));
ERROR: different bit lengths 3 and 4
SELECT jaccard_distance('1111', '1111');
jaccard_distance
------------------
0
(1 row)
SELECT jaccard_distance('1111', '1110');
jaccard_distance
------------------
0.25
(1 row)
SELECT jaccard_distance('1111', '1100');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance('1111', '1000');
jaccard_distance
------------------
0.75
(1 row)
SELECT jaccard_distance('1111', '0000');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('1100', '1000');
jaccard_distance
------------------
0.5
(1 row)
SELECT jaccard_distance('10101010101010101010', '01010101010101010101');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('', '');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('1111', '000');
ERROR: different bit lengths 4 and 3
SELECT jaccard_distance('1111', '0000'::varbit(5));
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('1111', '00000'::varbit(5));
ERROR: different bit lengths 4 and 5

View File

@@ -28,26 +28,6 @@ SELECT ARRAY[1,2,3]::numeric[]::vector;
[1,2,3] [1,2,3]
(1 row) (1 row)
SELECT '[1,2,3]'::vector::real[];
float4
---------
{1,2,3}
(1 row)
SELECT '{1,2,3}'::real[]::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{NULL}'::real[]::vector; SELECT '{NULL}'::real[]::vector;
ERROR: array must not contain nulls ERROR: array must not contain nulls
SELECT '{NaN}'::real[]::vector; SELECT '{NaN}'::real[]::vector;
@@ -60,26 +40,10 @@ SELECT '{}'::real[]::vector;
ERROR: vector must have at least 1 dimension ERROR: vector must have at least 1 dimension
SELECT '{{1}}'::real[]::vector; SELECT '{{1}}'::real[]::vector;
ERROR: array must be 1-D ERROR: array must be 1-D
SELECT '{1,2,3}'::double precision[]::vector; SELECT '[1,2,3]'::vector::real[];
vector float4
--------- ---------
[1,2,3] {1,2,3}
(1 row)
SELECT '{1,2,3}'::double precision[]::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::double precision[]::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{4e38,-4e38}'::double precision[]::vector;
ERROR: infinite value not allowed in vector
SELECT '{1e-46,-1e-46}'::double precision[]::vector;
vector
--------
[0,-0]
(1 row) (1 row)
SELECT '[1,2,3]'::vector::halfvec; SELECT '[1,2,3]'::vector::halfvec;
@@ -88,88 +52,24 @@ SELECT '[1,2,3]'::vector::halfvec;
[1,2,3] [1,2,3]
(1 row) (1 row)
SELECT '[1,2,3]'::vector::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[65520]'::vector::halfvec;
ERROR: "65520" is out of range for type halfvec
SELECT '[1e-8]'::vector::halfvec;
halfvec
---------
[0]
(1 row)
SELECT '[1,2,3]'::halfvec::vector; SELECT '[1,2,3]'::halfvec::vector;
vector vector
--------- ---------
[1,2,3] [1,2,3]
(1 row) (1 row)
SELECT '[1,2,3]'::halfvec::vector(3); SELECT '[1,2,3]'::vector::halfvec(2);
vector ERROR: expected 2 dimensions, not 3
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec::vector(2); SELECT '[1,2,3]'::halfvec::vector(2);
ERROR: expected 2 dimensions, not 3 ERROR: expected 2 dimensions, not 3
SELECT '{1,2,3}'::real[]::halfvec; SELECT '[65520]'::vector::halfvec;
ERROR: infinite value not allowed in halfvec
SELECT '[1e-8]'::vector::halfvec;
halfvec halfvec
--------- ---------
[1,2,3] [0]
(1 row) (1 row)
SELECT '{1,2,3}'::real[]::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '{65520,-65520}'::real[]::halfvec;
ERROR: "65520" is out of range for type halfvec
SELECT '{1e-8,-1e-8}'::real[]::halfvec;
halfvec
---------
[0,-0]
(1 row)
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(5);
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(4);
ERROR: expected 4 dimensions, not 5
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector;
vector
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(5);
vector
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(4);
ERROR: expected 4 dimensions, not 5
SELECT '{}/16001'::sparsevec::vector;
ERROR: vector cannot have more than 16000 dimensions
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n; SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
ERROR: vector cannot have more than 16000 dimensions ERROR: vector cannot have more than 16000 dimensions
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n; SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;

View File

@@ -1,15 +1,15 @@
CREATE TABLE t (val vector(3), val2 halfvec(3), val3 sparsevec(3)); CREATE TABLE t (val vector(3), val2 halfvec(3));
INSERT INTO t (val, val2, val3) VALUES ('[0,0,0]', '[0,0,0]', '{}/3'), ('[1,2,3]', '[1,2,3]', '{1:1,2:2,3:3}/3'), ('[1,1,1]', '[1,1,1]', '{1:1,2:1,3:1}/3'), (NULL, NULL, NULL); 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 halfvec(3), val3 sparsevec(3)); CREATE TABLE t2 (val vector(3), val2 halfvec(3));
\copy t TO 'results/data.bin' WITH (FORMAT binary) \copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/data.bin' WITH (FORMAT binary) \copy t2 FROM 'results/data.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val; SELECT * FROM t2 ORDER BY val;
val | val2 | val3 val | val2
---------+---------+----------------- ---------+---------
[0,0,0] | [0,0,0] | {}/3 [0,0,0] | [0,0,0]
[1,1,1] | [1,1,1] | {1:1,2:1,3:1}/3 [1,1,1] | [1,1,1]
[1,2,3] | [1,2,3] | {1:1,2:2,3:3}/3 [1,2,3] | [1,2,3]
| | |
(4 rows) (4 rows)
DROP TABLE t; DROP TABLE t;

View File

@@ -24,30 +24,6 @@ SELECT '[1e37]'::vector * '[1e37]';
ERROR: value out of range: overflow ERROR: value out of range: overflow
SELECT '[1e-37]'::vector * '[1e-37]'; SELECT '[1e-37]'::vector * '[1e-37]';
ERROR: value out of range: underflow ERROR: value out of range: underflow
SELECT '[1,2,3]'::vector < '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector < '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector <= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector <= '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector = '[1,2,3]'; SELECT '[1,2,3]'::vector = '[1,2,3]';
?column? ?column?
---------- ----------
@@ -55,47 +31,7 @@ SELECT '[1,2,3]'::vector = '[1,2,3]';
(1 row) (1 row)
SELECT '[1,2,3]'::vector = '[1,2]'; SELECT '[1,2,3]'::vector = '[1,2]';
?column? ERROR: different vector dimensions 3 and 2
----------
f
(1 row)
SELECT '[1,2,3]'::vector != '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector != '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector >= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector >= '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector > '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::vector > '[1,2]';
?column?
----------
t
(1 row)
SELECT vector_cmp('[1,2,3]', '[1,2,3]'); SELECT vector_cmp('[1,2,3]', '[1,2,3]');
vector_cmp vector_cmp
------------ ------------
@@ -272,48 +208,6 @@ SELECT l1_distance('[3e38]'::vector, '[-3e38]');
Infinity Infinity
(1 row) (1 row)
SELECT quantize_binary('[1,0,-1]'::vector);
quantize_binary
-----------------
100
(1 row)
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
quantize_binary
-----------------
01001110101
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
subvector
-----------
[1,2,3]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);
subvector
-----------
[3,4]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, -1, 3);
subvector
-----------
[1]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 3, 9);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, 1, 0);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, 3, -1);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, -1, 2);
ERROR: vector must have at least 1 dimension
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v; SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
avg avg
----------- -----------

View File

@@ -1,21 +1,3 @@
SELECT round(halfvec_norm('[1,1]')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT halfvec_norm('[3,4]');
halfvec_norm
--------------
5
(1 row)
SELECT halfvec_norm('[0,1]');
halfvec_norm
--------------
1
(1 row)
SELECT l2_distance('[0,0]'::halfvec, '[3,4]'); SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
l2_distance l2_distance
------------- -------------
@@ -30,12 +12,6 @@ SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
SELECT l2_distance('[1,2]'::halfvec, '[3]'); SELECT l2_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1 ERROR: different halfvec dimensions 2 and 1
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,1,1,1,1,1,1,4,5]');
l2_distance
-------------
5
(1 row)
SELECT '[0,0]'::halfvec <-> '[3,4]'; SELECT '[0,0]'::halfvec <-> '[3,4]';
?column? ?column?
---------- ----------
@@ -56,12 +32,6 @@ SELECT inner_product('[65504]'::halfvec, '[65504]');
4290774016 4290774016
(1 row) (1 row)
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
inner_product
---------------
45
(1 row)
SELECT '[1,2]'::halfvec <#> '[3,4]'; SELECT '[1,2]'::halfvec <#> '[3,4]';
?column? ?column?
---------- ----------
@@ -132,45 +102,3 @@ SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
SELECT l1_distance('[1,2]'::halfvec, '[3]'); SELECT l1_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1 ERROR: different halfvec dimensions 2 and 1
SELECT quantize_binary('[1,0,-1]'::halfvec);
quantize_binary
-----------------
100
(1 row)
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
quantize_binary
-----------------
01001110101
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
subvector
-----------
[1,2,3]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2);
subvector
-----------
[3,4]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 3);
subvector
-----------
[1]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 9);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 0);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, -1);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 2);
ERROR: halfvec must have at least 1 dimension

View File

@@ -51,68 +51,51 @@ SELECT '[65519,-65519]'::halfvec;
(1 row) (1 row)
SELECT '[65520,-65520]'::halfvec; SELECT '[65520,-65520]'::halfvec;
ERROR: "65520" is out of range for type halfvec ERROR: value out of range: overflow
LINE 1: SELECT '[65520,-65520]'::halfvec; LINE 1: SELECT '[65520,-65520]'::halfvec;
^ ^
SELECT '[1e-8,-1e-8]'::halfvec; SELECT '[1e-8,-1e-8]'::halfvec;
halfvec ERROR: value out of range: underflow
--------- LINE 1: SELECT '[1e-8,-1e-8]'::halfvec;
[0,-0] ^
(1 row)
SELECT '[4e38,1]'::halfvec; SELECT '[4e38,1]'::halfvec;
ERROR: "4e38" is out of range for type halfvec ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[4e38,1]'::halfvec; LINE 1: SELECT '[4e38,1]'::halfvec;
^ ^
SELECT '[1e-46,1]'::halfvec;
halfvec
---------
[0,1]
(1 row)
SELECT '[1,2,3'::halfvec; SELECT '[1,2,3'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,2,3" ERROR: malformed halfvec literal: "[1,2,3"
LINE 1: SELECT '[1,2,3'::halfvec; LINE 1: SELECT '[1,2,3'::halfvec;
^ ^
DETAIL: Unexpected end of input.
SELECT '[1,2,3]9'::halfvec; SELECT '[1,2,3]9'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,2,3]9" ERROR: malformed halfvec literal: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::halfvec; LINE 1: SELECT '[1,2,3]9'::halfvec;
^ ^
DETAIL: Junk after closing right brace. DETAIL: Junk after closing right brace.
SELECT '1,2,3'::halfvec; SELECT '1,2,3'::halfvec;
ERROR: invalid input syntax for type halfvec: "1,2,3" ERROR: malformed halfvec literal: "1,2,3"
LINE 1: SELECT '1,2,3'::halfvec; LINE 1: SELECT '1,2,3'::halfvec;
^ ^
DETAIL: Vector contents must start with "[". DETAIL: Vector contents must start with "[".
SELECT ''::halfvec; SELECT ''::halfvec;
ERROR: invalid input syntax for type halfvec: "" ERROR: malformed halfvec literal: ""
LINE 1: SELECT ''::halfvec; LINE 1: SELECT ''::halfvec;
^ ^
DETAIL: Vector contents must start with "[". DETAIL: Vector contents must start with "[".
SELECT '['::halfvec; SELECT '['::halfvec;
ERROR: invalid input syntax for type halfvec: "[" ERROR: malformed halfvec literal: "["
LINE 1: SELECT '['::halfvec; LINE 1: SELECT '['::halfvec;
^ ^
SELECT '[ '::halfvec; DETAIL: Unexpected end of input.
ERROR: invalid input syntax for type halfvec: "[ "
LINE 1: SELECT '[ '::halfvec;
^
SELECT '[,'::halfvec; SELECT '[,'::halfvec;
ERROR: invalid input syntax for type halfvec: "[," ERROR: malformed halfvec literal: "[,"
LINE 1: SELECT '[,'::halfvec; LINE 1: SELECT '[,'::halfvec;
^ ^
DETAIL: Unexpected end of input.
SELECT '[]'::halfvec; SELECT '[]'::halfvec;
ERROR: halfvec must have at least 1 dimension ERROR: halfvec must have at least 1 dimension
LINE 1: SELECT '[]'::halfvec; LINE 1: SELECT '[]'::halfvec;
^ ^
SELECT '[ ]'::halfvec;
ERROR: halfvec must have at least 1 dimension
LINE 1: SELECT '[ ]'::halfvec;
^
SELECT '[,]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[,]"
LINE 1: SELECT '[,]'::halfvec;
^
SELECT '[1,]'::halfvec; SELECT '[1,]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,]" ERROR: invalid input syntax for type halfvec: "[1,]"
LINE 1: SELECT '[1,]'::halfvec; LINE 1: SELECT '[1,]'::halfvec;
@@ -122,7 +105,7 @@ ERROR: invalid input syntax for type halfvec: "[1a]"
LINE 1: SELECT '[1a]'::halfvec; LINE 1: SELECT '[1a]'::halfvec;
^ ^
SELECT '[1,,3]'::halfvec; SELECT '[1,,3]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,,3]" ERROR: malformed halfvec literal: "[1,,3]"
LINE 1: SELECT '[1,,3]'::halfvec; LINE 1: SELECT '[1,,3]'::halfvec;
^ ^
SELECT '[1, ,3]'::halfvec; SELECT '[1, ,3]'::halfvec;

View File

@@ -1,29 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
val
-----
111
110
100
000
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- TODO move
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
ERROR: type not supported for hnsw index
CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
ERROR: column cannot have more than 64000 dimensions for hnsw index
DROP TABLE t;

View File

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

View File

@@ -12,11 +12,14 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
[0,0,0] [0,0,0]
(4 rows) (4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2; SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec);
count val
------- ---------
4 [0,0,0]
(1 row) [1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM t; SELECT COUNT(*) FROM t;
count count

View File

@@ -12,11 +12,14 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
[0,0,0] [0,0,0]
(4 rows) (4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2; SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
count val
------- ---------
4 [0,0,0]
(1 row) [1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM t; SELECT COUNT(*) FROM t;
count count

View File

@@ -1,26 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_cosine_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <=> '{1:3,2:3,3:3}/3';
val
-----------------
{1:1,2:1,3:1}/3
{1:1,2:2,3:3}/3
{1:1,2:2,3:4}/3
(3 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '{}/3') t2;
count
-------
3
(1 row)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::sparsevec)) t2;
count
-------
3
(1 row)
DROP TABLE t;

View File

@@ -1,21 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_ip_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <#> '{1:3,2:3,3:3}/3';
val
-----------------
{1:1,2:2,3:4}/3
{1:1,2:2,3:3}/3
{1:1,2:1,3:1}/3
{}/3
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::sparsevec)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

@@ -1,43 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
val
-----------------
{1:1,2:2,3:3}/3
{1:1,2:2,3:4}/3
{1:1,2:1,3:1}/3
{}/3
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
val
-----
(0 rows)
DROP TABLE t;
-- TODO move
CREATE TABLE t (val sparsevec(1001));
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
TRUNCATE t;
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
ERROR: sparsevec cannot have more than 1000 non-zero elements for hnsw index
DROP TABLE t;

View File

@@ -63,68 +63,43 @@ SELECT '[1.5e-38,-1.5e-38]'::vector;
(1 row) (1 row)
SELECT '[4e38,1]'::vector; 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; 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;
vector
--------
[0,1]
(1 row)
SELECT '[-1e-46,1]'::vector;
vector
--------
[-0,1]
(1 row)
SELECT '[1,2,3'::vector; SELECT '[1,2,3'::vector;
ERROR: invalid input syntax for type vector: "[1,2,3" ERROR: malformed vector literal: "[1,2,3"
LINE 1: SELECT '[1,2,3'::vector; LINE 1: SELECT '[1,2,3'::vector;
^ ^
DETAIL: Unexpected end of input.
SELECT '[1,2,3]9'::vector; SELECT '[1,2,3]9'::vector;
ERROR: invalid input syntax for type vector: "[1,2,3]9" ERROR: malformed vector literal: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::vector; LINE 1: SELECT '[1,2,3]9'::vector;
^ ^
DETAIL: Junk after closing right brace. DETAIL: Junk after closing right brace.
SELECT '1,2,3'::vector; SELECT '1,2,3'::vector;
ERROR: invalid input syntax for type vector: "1,2,3" ERROR: malformed vector literal: "1,2,3"
LINE 1: SELECT '1,2,3'::vector; LINE 1: SELECT '1,2,3'::vector;
^ ^
DETAIL: Vector contents must start with "[". DETAIL: Vector contents must start with "[".
SELECT ''::vector; SELECT ''::vector;
ERROR: invalid input syntax for type vector: "" ERROR: malformed vector literal: ""
LINE 1: SELECT ''::vector; LINE 1: SELECT ''::vector;
^ ^
DETAIL: Vector contents must start with "[". DETAIL: Vector contents must start with "[".
SELECT '['::vector; SELECT '['::vector;
ERROR: invalid input syntax for type vector: "[" ERROR: malformed vector literal: "["
LINE 1: SELECT '['::vector; LINE 1: SELECT '['::vector;
^ ^
SELECT '[ '::vector; DETAIL: Unexpected end of input.
ERROR: invalid input syntax for type vector: "[ "
LINE 1: SELECT '[ '::vector;
^
SELECT '[,'::vector; SELECT '[,'::vector;
ERROR: invalid input syntax for type vector: "[," ERROR: malformed vector literal: "[,"
LINE 1: SELECT '[,'::vector; LINE 1: SELECT '[,'::vector;
^ ^
DETAIL: Unexpected end of input.
SELECT '[]'::vector; SELECT '[]'::vector;
ERROR: vector must have at least 1 dimension ERROR: vector must have at least 1 dimension
LINE 1: SELECT '[]'::vector; LINE 1: SELECT '[]'::vector;
^ ^
SELECT '[ ]'::vector;
ERROR: vector must have at least 1 dimension
LINE 1: SELECT '[ ]'::vector;
^
SELECT '[,]'::vector;
ERROR: invalid input syntax for type vector: "[,]"
LINE 1: SELECT '[,]'::vector;
^
SELECT '[1,]'::vector; SELECT '[1,]'::vector;
ERROR: invalid input syntax for type vector: "[1,]" ERROR: invalid input syntax for type vector: "[1,]"
LINE 1: SELECT '[1,]'::vector; LINE 1: SELECT '[1,]'::vector;
@@ -134,7 +109,7 @@ ERROR: invalid input syntax for type vector: "[1a]"
LINE 1: SELECT '[1a]'::vector; LINE 1: SELECT '[1a]'::vector;
^ ^
SELECT '[1,,3]'::vector; SELECT '[1,,3]'::vector;
ERROR: invalid input syntax for type vector: "[1,,3]" ERROR: malformed vector literal: "[1,,3]"
LINE 1: SELECT '[1,,3]'::vector; LINE 1: SELECT '[1,,3]'::vector;
^ ^
SELECT '[1, ,3]'::vector; SELECT '[1, ,3]'::vector;

View File

@@ -1,26 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_cosine_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
val
---------
[1,1,1]
[1,2,3]
[1,2,4]
(3 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
count
-------
3
(1 row)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t2;
count
-------
3
(1 row)
DROP TABLE t;

View File

@@ -1,21 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_ip_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
val
---------
[1,2,4]
[1,2,3]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::halfvec)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

@@ -1,36 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;

View File

@@ -12,11 +12,14 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
[0,0,0] [0,0,0]
(4 rows) (4 rows)
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2; SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
count val
------- ---------
4 [0,0,0]
(1 row) [1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM t; SELECT COUNT(*) FROM t;
count count

View File

@@ -1,86 +0,0 @@
SELECT round(sparsevec_norm('{1:1,2:1}/2')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT sparsevec_norm('{1:3,2:4}/2');
sparsevec_norm
----------------
5
(1 row)
SELECT sparsevec_norm('{2:1}/2');
sparsevec_norm
----------------
1
(1 row)
SELECT sparsevec_norm('{1:3e37,2:4e37}/2')::real;
sparsevec_norm
----------------
5e+37
(1 row)
SELECT l2_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{}/2'::sparsevec, '{2:1}/2');
l2_distance
-------------
1
(1 row)
SELECT '{}/2'::sparsevec <-> '{1:3,2:4}/2';
?column?
----------
5
(1 row)
SELECT inner_product('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
inner_product
---------------
10
(1 row)
SELECT sparsevec_negative_inner_product('{1:1,2:2}/2', '{1:2,2:4}/2');
sparsevec_negative_inner_product
----------------------------------
-10
(1 row)
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{}/2');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:-1,2:-1}/2');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('{1:2}/2'::sparsevec, '{2:2}/2');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{1:2}/2'::sparsevec, '{1:1}/3');
ERROR: different sparsevec dimensions 2 and 3

View File

@@ -1,215 +0,0 @@
SELECT '{1:1.5,3:3.5}/5'::sparsevec;
sparsevec
-----------------
{1:1.5,3:3.5}/5
(1 row)
SELECT '{1:-2,3:-4}/5'::sparsevec;
sparsevec
---------------
{1:-2,3:-4}/5
(1 row)
SELECT '{1:2.,3:4.}/5'::sparsevec;
sparsevec
-------------
{1:2,3:4}/5
(1 row)
SELECT ' { 1 : 1.5 , 3 : 3.5 } / 5 '::sparsevec;
sparsevec
-----------------
{1:1.5,3:3.5}/5
(1 row)
SELECT '{1:1.23456}/1'::sparsevec;
sparsevec
---------------
{1:1.23456}/1
(1 row)
SELECT '{1:hello,2:1}/2'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:hello,2:1}/2"
LINE 1: SELECT '{1:hello,2:1}/2'::sparsevec;
^
SELECT '{1:NaN,2:1}/2'::sparsevec;
ERROR: NaN not allowed in sparsevec
LINE 1: SELECT '{1:NaN,2:1}/2'::sparsevec;
^
SELECT '{1:Infinity,2:1}/2'::sparsevec;
ERROR: infinite value not allowed in sparsevec
LINE 1: SELECT '{1:Infinity,2:1}/2'::sparsevec;
^
SELECT '{1:-Infinity,2:1}/2'::sparsevec;
ERROR: infinite value not allowed in sparsevec
LINE 1: SELECT '{1:-Infinity,2:1}/2'::sparsevec;
^
SELECT '{1:1.5e38,2:-1.5e38}/2'::sparsevec;
sparsevec
--------------------------
{1:1.5e+38,2:-1.5e+38}/2
(1 row)
SELECT '{1:1.5e+38,2:-1.5e+38}/2'::sparsevec;
sparsevec
--------------------------
{1:1.5e+38,2:-1.5e+38}/2
(1 row)
SELECT '{1:1.5e-38,2:-1.5e-38}/2'::sparsevec;
sparsevec
--------------------------
{1:1.5e-38,2:-1.5e-38}/2
(1 row)
SELECT '{1:4e38,2:1}/2'::sparsevec;
ERROR: "4e38" is out of range for type sparsevec
LINE 1: SELECT '{1:4e38,2:1}/2'::sparsevec;
^
SELECT '{1:-4e38,2:1}/2'::sparsevec;
ERROR: "-4e38" is out of range for type sparsevec
LINE 1: SELECT '{1:-4e38,2:1}/2'::sparsevec;
^
SELECT '{1:1e-46,2:1}/2'::sparsevec;
ERROR: "1e-46" is out of range for type sparsevec
LINE 1: SELECT '{1:1e-46,2:1}/2'::sparsevec;
^
SELECT '{1:-1e-46,2:1}/2'::sparsevec;
ERROR: "-1e-46" is out of range for type sparsevec
LINE 1: SELECT '{1:-1e-46,2:1}/2'::sparsevec;
^
SELECT ''::sparsevec;
ERROR: invalid input syntax for type sparsevec: ""
LINE 1: SELECT ''::sparsevec;
^
DETAIL: Vector contents must start with "{".
SELECT '{'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{"
LINE 1: SELECT '{'::sparsevec;
^
SELECT '{ '::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{ "
LINE 1: SELECT '{ '::sparsevec;
^
SELECT '{:'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{:"
LINE 1: SELECT '{:'::sparsevec;
^
SELECT '{,'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{,"
LINE 1: SELECT '{,'::sparsevec;
^
SELECT '{}'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{}"
LINE 1: SELECT '{}'::sparsevec;
^
DETAIL: Unexpected end of input.
SELECT '{}/'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{}/"
LINE 1: SELECT '{}/'::sparsevec;
^
SELECT '{}/1'::sparsevec;
sparsevec
-----------
{}/1
(1 row)
SELECT '{}/1a'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{}/1a"
LINE 1: SELECT '{}/1a'::sparsevec;
^
DETAIL: Junk after closing.
SELECT '{ }/1'::sparsevec;
sparsevec
-----------
{}/1
(1 row)
SELECT '{:}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{:}/1"
LINE 1: SELECT '{:}/1'::sparsevec;
^
SELECT '{,}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{,}/1"
LINE 1: SELECT '{,}/1'::sparsevec;
^
SELECT '{1,}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1,}/1"
LINE 1: SELECT '{1,}/1'::sparsevec;
^
SELECT '{:1}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{:1}/1"
LINE 1: SELECT '{:1}/1'::sparsevec;
^
SELECT '{1:}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:}/1"
LINE 1: SELECT '{1:}/1'::sparsevec;
^
SELECT '{1a:1}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1a:1}/1"
LINE 1: SELECT '{1a:1}/1'::sparsevec;
^
SELECT '{1:1a}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:1a}/1"
LINE 1: SELECT '{1:1a}/1'::sparsevec;
^
SELECT '{1:1,}/1'::sparsevec;
ERROR: invalid input syntax for type sparsevec: "{1:1,}/1"
LINE 1: SELECT '{1:1,}/1'::sparsevec;
^
SELECT '{1:0,2:1,3:0}/3'::sparsevec;
sparsevec
-----------
{2:1}/3
(1 row)
SELECT '{2:1,1:1}/2'::sparsevec;
ERROR: indexes must be in ascending order
LINE 1: SELECT '{2:1,1:1}/2'::sparsevec;
^
SELECT '{}/5'::sparsevec;
sparsevec
-----------
{}/5
(1 row)
SELECT '{}/-1'::sparsevec;
ERROR: sparsevec must have at least 1 dimension
LINE 1: SELECT '{}/-1'::sparsevec;
^
SELECT '{}/100001'::sparsevec;
ERROR: sparsevec cannot have more than 100000 dimensions
LINE 1: SELECT '{}/100001'::sparsevec;
^
SELECT '{0:1}/1'::sparsevec;
ERROR: index "0" is out of range for type sparsevec
LINE 1: SELECT '{0:1}/1'::sparsevec;
^
SELECT '{2:1}/1'::sparsevec;
ERROR: index must be less than or equal to dimensions
LINE 1: SELECT '{2:1}/1'::sparsevec;
^
SELECT '{}/3'::sparsevec(3);
sparsevec
-----------
{}/3
(1 row)
SELECT '{}/3'::sparsevec(2);
ERROR: expected 2 dimensions, not 3
SELECT '{}/3'::sparsevec(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '{}/3'::sparsevec(3, 2);
^
SELECT '{}/3'::sparsevec('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '{}/3'::sparsevec('a');
^
SELECT '{}/3'::sparsevec(0);
ERROR: dimensions for type sparsevec must be at least 1
LINE 1: SELECT '{}/3'::sparsevec(0);
^
SELECT '{}/3'::sparsevec(100001);
ERROR: dimensions for type sparsevec cannot exceed 100000
LINE 1: SELECT '{}/3'::sparsevec(100001);
^

View File

@@ -1,21 +0,0 @@
SELECT hamming_distance('111', '111');
SELECT hamming_distance('111', '110');
SELECT hamming_distance('111', '100');
SELECT hamming_distance('111', '000');
SELECT hamming_distance('10101010101010101010', '01010101010101010101');
SELECT hamming_distance('', '');
SELECT hamming_distance('111', '00');
SELECT hamming_distance('111', '000'::varbit(4));
SELECT hamming_distance('111', '0000'::varbit(4));
SELECT jaccard_distance('1111', '1111');
SELECT jaccard_distance('1111', '1110');
SELECT jaccard_distance('1111', '1100');
SELECT jaccard_distance('1111', '1000');
SELECT jaccard_distance('1111', '0000');
SELECT jaccard_distance('1100', '1000');
SELECT jaccard_distance('10101010101010101010', '01010101010101010101');
SELECT jaccard_distance('', '');
SELECT jaccard_distance('1111', '000');
SELECT jaccard_distance('1111', '0000'::varbit(5));
SELECT jaccard_distance('1111', '00000'::varbit(5));

View File

@@ -3,50 +3,19 @@ SELECT ARRAY[1.0,2.0,3.0]::vector;
SELECT ARRAY[1,2,3]::float4[]::vector; SELECT ARRAY[1,2,3]::float4[]::vector;
SELECT ARRAY[1,2,3]::float8[]::vector; SELECT ARRAY[1,2,3]::float8[]::vector;
SELECT ARRAY[1,2,3]::numeric[]::vector; SELECT ARRAY[1,2,3]::numeric[]::vector;
SELECT '[1,2,3]'::vector::real[];
SELECT '{1,2,3}'::real[]::vector;
SELECT '{1,2,3}'::real[]::vector(3);
SELECT '{1,2,3}'::real[]::vector(2);
SELECT '{NULL}'::real[]::vector; SELECT '{NULL}'::real[]::vector;
SELECT '{NaN}'::real[]::vector; SELECT '{NaN}'::real[]::vector;
SELECT '{Infinity}'::real[]::vector; SELECT '{Infinity}'::real[]::vector;
SELECT '{-Infinity}'::real[]::vector; SELECT '{-Infinity}'::real[]::vector;
SELECT '{}'::real[]::vector; SELECT '{}'::real[]::vector;
SELECT '{{1}}'::real[]::vector; SELECT '{{1}}'::real[]::vector;
SELECT '[1,2,3]'::vector::real[];
SELECT '{1,2,3}'::double precision[]::vector;
SELECT '{1,2,3}'::double precision[]::vector(3);
SELECT '{1,2,3}'::double precision[]::vector(2);
SELECT '{4e38,-4e38}'::double precision[]::vector;
SELECT '{1e-46,-1e-46}'::double precision[]::vector;
SELECT '[1,2,3]'::vector::halfvec; SELECT '[1,2,3]'::vector::halfvec;
SELECT '[1,2,3]'::vector::halfvec(3); SELECT '[1,2,3]'::halfvec::vector;
SELECT '[1,2,3]'::vector::halfvec(2); SELECT '[1,2,3]'::vector::halfvec(2);
SELECT '[1,2,3]'::halfvec::vector(2);
SELECT '[65520]'::vector::halfvec; SELECT '[65520]'::vector::halfvec;
SELECT '[1e-8]'::vector::halfvec; SELECT '[1e-8]'::vector::halfvec;
SELECT '[1,2,3]'::halfvec::vector;
SELECT '[1,2,3]'::halfvec::vector(3);
SELECT '[1,2,3]'::halfvec::vector(2);
SELECT '{1,2,3}'::real[]::halfvec;
SELECT '{1,2,3}'::real[]::halfvec(3);
SELECT '{1,2,3}'::real[]::halfvec(2);
SELECT '{65520,-65520}'::real[]::halfvec;
SELECT '{1e-8,-1e-8}'::real[]::halfvec;
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec;
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(5);
SELECT '[0,1.5,0,3.5,0]'::vector::sparsevec(4);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector;
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(5);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::vector(4);
SELECT '{}/16001'::sparsevec::vector;
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n; SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n; SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;

View File

@@ -1,7 +1,7 @@
CREATE TABLE t (val vector(3), val2 halfvec(3), val3 sparsevec(3)); CREATE TABLE t (val vector(3), val2 halfvec(3));
INSERT INTO t (val, val2, val3) VALUES ('[0,0,0]', '[0,0,0]', '{}/3'), ('[1,2,3]', '[1,2,3]', '{1:1,2:2,3:3}/3'), ('[1,1,1]', '[1,1,1]', '{1:1,2:1,3:1}/3'), (NULL, NULL, NULL); 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 halfvec(3), val3 sparsevec(3)); CREATE TABLE t2 (val vector(3), val2 halfvec(3));
\copy t TO 'results/data.bin' WITH (FORMAT binary) \copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/data.bin' WITH (FORMAT binary) \copy t2 FROM 'results/data.bin' WITH (FORMAT binary)

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@@ -6,18 +6,8 @@ SELECT '[1,2,3]'::vector * '[4,5,6]';
SELECT '[1e37]'::vector * '[1e37]'; SELECT '[1e37]'::vector * '[1e37]';
SELECT '[1e-37]'::vector * '[1e-37]'; SELECT '[1e-37]'::vector * '[1e-37]';
SELECT '[1,2,3]'::vector < '[1,2,3]';
SELECT '[1,2,3]'::vector < '[1,2]';
SELECT '[1,2,3]'::vector <= '[1,2,3]';
SELECT '[1,2,3]'::vector <= '[1,2]';
SELECT '[1,2,3]'::vector = '[1,2,3]'; SELECT '[1,2,3]'::vector = '[1,2,3]';
SELECT '[1,2,3]'::vector = '[1,2]'; SELECT '[1,2,3]'::vector = '[1,2]';
SELECT '[1,2,3]'::vector != '[1,2,3]';
SELECT '[1,2,3]'::vector != '[1,2]';
SELECT '[1,2,3]'::vector >= '[1,2,3]';
SELECT '[1,2,3]'::vector >= '[1,2]';
SELECT '[1,2,3]'::vector > '[1,2,3]';
SELECT '[1,2,3]'::vector > '[1,2]';
SELECT vector_cmp('[1,2,3]', '[1,2,3]'); SELECT vector_cmp('[1,2,3]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[0,0,0]'); SELECT vector_cmp('[1,2,3]', '[0,0,0]');
@@ -58,17 +48,6 @@ SELECT l1_distance('[0,0]'::vector, '[0,1]');
SELECT l1_distance('[1,2]'::vector, '[3]'); SELECT l1_distance('[1,2]'::vector, '[3]');
SELECT l1_distance('[3e38]'::vector, '[-3e38]'); SELECT l1_distance('[3e38]'::vector, '[-3e38]');
SELECT quantize_binary('[1,0,-1]'::vector);
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);
SELECT subvector('[1,2,3,4,5]'::vector, -1, 3);
SELECT subvector('[1,2,3,4,5]'::vector, 3, 9);
SELECT subvector('[1,2,3,4,5]'::vector, 1, 0);
SELECT subvector('[1,2,3,4,5]'::vector, 3, -1);
SELECT subvector('[1,2,3,4,5]'::vector, -1, 2);
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v; SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v; SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v; SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;

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@@ -1,17 +1,11 @@
SELECT round(halfvec_norm('[1,1]')::numeric, 5);
SELECT halfvec_norm('[3,4]');
SELECT halfvec_norm('[0,1]');
SELECT l2_distance('[0,0]'::halfvec, '[3,4]'); SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
SELECT l2_distance('[0,0]'::halfvec, '[0,1]'); SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
SELECT l2_distance('[1,2]'::halfvec, '[3]'); SELECT l2_distance('[1,2]'::halfvec, '[3]');
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,1,1,1,1,1,1,4,5]');
SELECT '[0,0]'::halfvec <-> '[3,4]'; SELECT '[0,0]'::halfvec <-> '[3,4]';
SELECT inner_product('[1,2]'::halfvec, '[3,4]'); SELECT inner_product('[1,2]'::halfvec, '[3,4]');
SELECT inner_product('[1,2]'::halfvec, '[3]'); SELECT inner_product('[1,2]'::halfvec, '[3]');
SELECT inner_product('[65504]'::halfvec, '[65504]'); SELECT inner_product('[65504]'::halfvec, '[65504]');
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
SELECT '[1,2]'::halfvec <#> '[3,4]'; SELECT '[1,2]'::halfvec <#> '[3,4]';
SELECT cosine_distance('[1,2]'::halfvec, '[2,4]'); SELECT cosine_distance('[1,2]'::halfvec, '[2,4]');
@@ -27,14 +21,3 @@ SELECT '[1,2]'::halfvec <=> '[2,4]';
SELECT l1_distance('[0,0]'::halfvec, '[3,4]'); SELECT l1_distance('[0,0]'::halfvec, '[3,4]');
SELECT l1_distance('[0,0]'::halfvec, '[0,1]'); SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
SELECT l1_distance('[1,2]'::halfvec, '[3]'); SELECT l1_distance('[1,2]'::halfvec, '[3]');
SELECT quantize_binary('[1,0,-1]'::halfvec);
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 3);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2);
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 3);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 9);
SELECT subvector('[1,2,3,4,5]'::halfvec, 1, 0);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, -1);
SELECT subvector('[1,2,3,4,5]'::halfvec, -1, 2);

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@@ -11,17 +11,13 @@ SELECT '[65519,-65519]'::halfvec;
SELECT '[65520,-65520]'::halfvec; SELECT '[65520,-65520]'::halfvec;
SELECT '[1e-8,-1e-8]'::halfvec; SELECT '[1e-8,-1e-8]'::halfvec;
SELECT '[4e38,1]'::halfvec; SELECT '[4e38,1]'::halfvec;
SELECT '[1e-46,1]'::halfvec;
SELECT '[1,2,3'::halfvec; SELECT '[1,2,3'::halfvec;
SELECT '[1,2,3]9'::halfvec; SELECT '[1,2,3]9'::halfvec;
SELECT '1,2,3'::halfvec; SELECT '1,2,3'::halfvec;
SELECT ''::halfvec; SELECT ''::halfvec;
SELECT '['::halfvec; SELECT '['::halfvec;
SELECT '[ '::halfvec;
SELECT '[,'::halfvec; SELECT '[,'::halfvec;
SELECT '[]'::halfvec; SELECT '[]'::halfvec;
SELECT '[ ]'::halfvec;
SELECT '[,]'::halfvec;
SELECT '[1,]'::halfvec; SELECT '[1,]'::halfvec;
SELECT '[1a]'::halfvec; SELECT '[1a]'::halfvec;
SELECT '[1,,3]'::halfvec; SELECT '[1,,3]'::halfvec;

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@@ -1,19 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
INSERT INTO t (val) VALUES (B'110');
SELECT * FROM t ORDER BY val <~> B'111';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <~> (SELECT NULL::bit)) t2;
DROP TABLE t;
-- TODO move
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
DROP TABLE t;

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

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@@ -7,7 +7,7 @@ CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]'); INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]'; SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2; SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec);
SELECT COUNT(*) FROM t; SELECT COUNT(*) FROM t;
TRUNCATE t; TRUNCATE t;

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@@ -7,7 +7,7 @@ CREATE INDEX ON t USING hnsw (val vector_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]'); INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]'; 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; SELECT COUNT(*) FROM t;
TRUNCATE t; TRUNCATE t;

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@@ -1,13 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_cosine_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <=> '{1:3,2:3,3:3}/3';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '{}/3') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::sparsevec)) t2;
DROP TABLE t;

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@@ -1,12 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_ip_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <#> '{1:3,2:3,3:3}/3';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::sparsevec)) t2;
DROP TABLE t;

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@@ -1,25 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val sparsevec(3));
INSERT INTO t (val) VALUES ('{}/3'), ('{1:1,2:2,3:3}/3'), ('{1:1,2:1,3:1}/3'), (NULL);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES ('{1:1,2:2,3:4}/3');
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::sparsevec)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '{1:3,2:3,3:3}/3';
DROP TABLE t;
-- TODO move
CREATE TABLE t (val sparsevec(1001));
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
TRUNCATE t;
CREATE INDEX ON t USING hnsw (val sparsevec_l2_ops);
INSERT INTO t (val) VALUES (array_fill(1, ARRAY[1001])::vector::sparsevec);
DROP TABLE t;

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@@ -11,19 +11,13 @@ SELECT '[1.5e38,-1.5e38]'::vector;
SELECT '[1.5e+38,-1.5e+38]'::vector; SELECT '[1.5e+38,-1.5e+38]'::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 '[-4e38,1]'::vector;
SELECT '[1e-46,1]'::vector;
SELECT '[-1e-46,1]'::vector;
SELECT '[1,2,3'::vector; SELECT '[1,2,3'::vector;
SELECT '[1,2,3]9'::vector; SELECT '[1,2,3]9'::vector;
SELECT '1,2,3'::vector; SELECT '1,2,3'::vector;
SELECT ''::vector; SELECT ''::vector;
SELECT '['::vector; SELECT '['::vector;
SELECT '[ '::vector;
SELECT '[,'::vector; SELECT '[,'::vector;
SELECT '[]'::vector; SELECT '[]'::vector;
SELECT '[ ]'::vector;
SELECT '[,]'::vector;
SELECT '[1,]'::vector; SELECT '[1,]'::vector;
SELECT '[1a]'::vector; SELECT '[1a]'::vector;
SELECT '[1,,3]'::vector; SELECT '[1,,3]'::vector;

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@@ -1,13 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_cosine_ops) WITH (lists = 1);
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 <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t2;
DROP TABLE t;

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@@ -1,12 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_ip_ops) WITH (lists = 1);
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::halfvec)) t2;
DROP TABLE t;

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@@ -1,16 +0,0 @@
SET enable_seqscan = off;
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops) WITH (lists = 1);
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::halfvec)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;

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@@ -7,7 +7,7 @@ CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
INSERT INTO t (val) VALUES ('[1,2,4]'); INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]'; 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; SELECT COUNT(*) FROM t;
TRUNCATE t; TRUNCATE t;

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@@ -1,18 +0,0 @@
SELECT round(sparsevec_norm('{1:1,2:1}/2')::numeric, 5);
SELECT sparsevec_norm('{1:3,2:4}/2');
SELECT sparsevec_norm('{2:1}/2');
SELECT sparsevec_norm('{1:3e37,2:4e37}/2')::real;
SELECT l2_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
SELECT l2_distance('{}/2'::sparsevec, '{2:1}/2');
SELECT '{}/2'::sparsevec <-> '{1:3,2:4}/2';
SELECT inner_product('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
SELECT sparsevec_negative_inner_product('{1:1,2:2}/2', '{1:2,2:4}/2');
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{1:2,2:4}/2');
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{}/2');
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:-1,2:-1}/2');
SELECT cosine_distance('{1:2}/2'::sparsevec, '{2:2}/2');
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
SELECT cosine_distance('{1:2}/2'::sparsevec, '{1:1}/3');

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@@ -1,48 +0,0 @@
SELECT '{1:1.5,3:3.5}/5'::sparsevec;
SELECT '{1:-2,3:-4}/5'::sparsevec;
SELECT '{1:2.,3:4.}/5'::sparsevec;
SELECT ' { 1 : 1.5 , 3 : 3.5 } / 5 '::sparsevec;
SELECT '{1:1.23456}/1'::sparsevec;
SELECT '{1:hello,2:1}/2'::sparsevec;
SELECT '{1:NaN,2:1}/2'::sparsevec;
SELECT '{1:Infinity,2:1}/2'::sparsevec;
SELECT '{1:-Infinity,2:1}/2'::sparsevec;
SELECT '{1:1.5e38,2:-1.5e38}/2'::sparsevec;
SELECT '{1:1.5e+38,2:-1.5e+38}/2'::sparsevec;
SELECT '{1:1.5e-38,2:-1.5e-38}/2'::sparsevec;
SELECT '{1:4e38,2:1}/2'::sparsevec;
SELECT '{1:-4e38,2:1}/2'::sparsevec;
SELECT '{1:1e-46,2:1}/2'::sparsevec;
SELECT '{1:-1e-46,2:1}/2'::sparsevec;
SELECT ''::sparsevec;
SELECT '{'::sparsevec;
SELECT '{ '::sparsevec;
SELECT '{:'::sparsevec;
SELECT '{,'::sparsevec;
SELECT '{}'::sparsevec;
SELECT '{}/'::sparsevec;
SELECT '{}/1'::sparsevec;
SELECT '{}/1a'::sparsevec;
SELECT '{ }/1'::sparsevec;
SELECT '{:}/1'::sparsevec;
SELECT '{,}/1'::sparsevec;
SELECT '{1,}/1'::sparsevec;
SELECT '{:1}/1'::sparsevec;
SELECT '{1:}/1'::sparsevec;
SELECT '{1a:1}/1'::sparsevec;
SELECT '{1:1a}/1'::sparsevec;
SELECT '{1:1,}/1'::sparsevec;
SELECT '{1:0,2:1,3:0}/3'::sparsevec;
SELECT '{2:1,1:1}/2'::sparsevec;
SELECT '{}/5'::sparsevec;
SELECT '{}/-1'::sparsevec;
SELECT '{}/100001'::sparsevec;
SELECT '{0:1}/1'::sparsevec;
SELECT '{2:1}/1'::sparsevec;
SELECT '{}/3'::sparsevec(3);
SELECT '{}/3'::sparsevec(2);
SELECT '{}/3'::sparsevec(3, 2);
SELECT '{}/3'::sparsevec('a');
SELECT '{}/3'::sparsevec(0);
SELECT '{}/3'::sparsevec(100001);

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@@ -30,19 +30,18 @@ sub test_recall
SELECT i FROM tst ORDER BY v $operator '$queries[$i]' LIMIT $limit; SELECT i FROM tst ORDER BY v $operator '$queries[$i]' LIMIT $limit;
)); ));
my @actual_ids = split("\n", $actual); my @actual_ids = split("\n", $actual);
my %actual_set = map { $_ => 1 } @actual_ids;
my @expected_ids = split("\n", $expected[$i]); my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids) foreach (@expected_ids)
{ {
if (exists($expected_set{$_})) if (exists($actual_set{$_}))
{ {
$correct++; $correct++;
} }
$total++;
} }
$total += $limit;
} }
cmp_ok($correct / $total, ">=", $min, $operator); cmp_ok($correct / $total, ">=", $min, $operator);
@@ -82,12 +81,7 @@ for my $i (0 .. $#operators)
@expected = (); @expected = ();
foreach (@queries) foreach (@queries)
{ {
my $res = $node->safe_psql("postgres", qq( my $res = $node->safe_psql("postgres", "SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;");
WITH top AS (
SELECT v $operator '$_' AS distance FROM tst ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator '$_') <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res); push(@expected, $res);
} }
@@ -104,16 +98,8 @@ for my $i (0 .. $#operators)
test_recall(1, 0.71, $operator); test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator); test_recall(10, 0.95, $operator);
} }
# Account for equal distances
# Test probes equals lists test_recall(100, 0.9925, $operator);
if ($operator eq "<=>")
{
test_recall(100, 0.9925, $operator);
}
else
{
test_recall(100, 1.00, $operator);
}
$node->safe_psql("postgres", "DROP INDEX idx;"); $node->safe_psql("postgres", "DROP INDEX idx;");
@@ -133,16 +119,8 @@ for my $i (0 .. $#operators)
test_recall(1, 0.71, $operator); test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator); test_recall(10, 0.95, $operator);
} }
# Account for equal distances
# Test probes equals lists test_recall(100, 0.9925, $operator);
if ($operator eq "<=>")
{
test_recall(100, 0.9925, $operator);
}
else
{
test_recall(100, 1.00, $operator);
}
$node->safe_psql("postgres", "DROP INDEX idx;"); $node->safe_psql("postgres", "DROP INDEX idx;");
} }

View File

@@ -98,7 +98,6 @@ for my $i (0 .. $#operators)
push(@expected, $res); push(@expected, $res);
} }
# Test approximate results
my $min = $operator eq "<#>" ? 0.80 : 0.99; my $min = $operator eq "<#>" ? 0.80 : 0.99;
test_recall($min, $operator); test_recall($min, $operator);

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@@ -86,7 +86,7 @@ foreach (@queries)
push(@expected, $res); push(@expected, $res);
} }
test_recall(0.18, $limit, "before vacuum"); test_recall(0.20, $limit, "before vacuum");
test_recall(0.95, 100, "before vacuum"); test_recall(0.95, 100, "before vacuum");
# TODO Test concurrent inserts with vacuum # TODO Test concurrent inserts with vacuum

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@@ -1,137 +0,0 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 52;
my $max = 2**$dim;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator $queries[0] LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
SELECT i FROM tst ORDER BY v $operator $queries[$i] LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v bit($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, (random() * $max)::bigint::bit($dim) FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1 .. 20)
{
my $r = int(rand() * $max);
push(@queries, "${r}::bigint::bit($dim)");
}
# Check each index type
my @operators = ("<~>", "<\%>");
my @opclasses = ("bit_hamming_ops", "bit_jaccard_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Get exact results
@expected = ();
foreach (@queries)
{
# Handle ties
my $res = $node->safe_psql("postgres", qq(
WITH top AS (
SELECT v $operator $_ AS distance FROM tst ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator $_) <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
# Build index serially
$node->safe_psql("postgres", qq(
SET max_parallel_maintenance_workers = 0;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
# Test approximate results
my $min = $operator eq "<\%>" ? 0.95 : 0.98;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel in memory
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel on disk
# Set parallel_workers on table to use workers with low maintenance_work_mem
($ret, $stdout, $stderr) = $node->psql("postgres", qq(
ALTER TABLE tst SET (parallel_workers = 2);
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '4MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
ALTER TABLE tst RESET (parallel_workers);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem/);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

View File

@@ -94,7 +94,7 @@ for my $i (0 .. $#operators)
)); ));
# Test approximate results # Test approximate results
my $min = $operator eq "<#>" ? 0.93 : 0.98; my $min = $operator eq "<#>" ? 0.95 : 0.99;
test_recall($min, $operator); test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;"); $node->safe_psql("postgres", "DROP INDEX idx;");

View File

@@ -1,128 +0,0 @@
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 sparsevec(3));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()]::vector::sparsevec FROM generate_series(1, 10000) i;"
);
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "{1:$r1,2:$r2,3:$r3}/3");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("sparsevec_l2_ops", "sparsevec_ip_ops", "sparsevec_cosine_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);
}
# 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);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel in memory
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET client_min_messages = DEBUG;
SET min_parallel_table_scan_size = 1;
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
# Build index in parallel on disk
# Set parallel_workers on table to use workers with low maintenance_work_mem
($ret, $stdout, $stderr) = $node->psql("postgres", qq(
ALTER TABLE tst SET (parallel_workers = 2);
SET client_min_messages = DEBUG;
SET maintenance_work_mem = '4MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
ALTER TABLE tst RESET (parallel_workers);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
like($stderr, qr/hnsw graph no longer fits into maintenance_work_mem/);
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

View File

@@ -1,116 +0,0 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 52;
my $max = 2**$dim;
sub test_recall
{
my ($min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator $queries[0] LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 100;
SELECT i FROM tst ORDER BY v $operator $queries[$i] LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v bit($dim));");
# Generate queries
for (1 .. 20)
{
my $r = int(rand() * $max);
push(@queries, "${r}::bigint::bit($dim)");
}
# Check each index type
my @operators = ("<~>", "<\%>");
my @opclasses = ("bit_hamming_ops", "bit_jaccard_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Add index
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v $opclass);");
# Use concurrent inserts
$node->pgbench(
"--no-vacuum --client=10 --transactions=1000",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"023_hnsw_bit_insert_recall_$opclass" => "INSERT INTO tst (v) VALUES ((random() * $max)::bigint::bit($dim));"
}
);
# Get exact results
@expected = ();
foreach (@queries)
{
# Handle ties
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
WITH top AS (
SELECT v $operator $_ AS distance FROM tst ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator $_) <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
# Test approximate results
my $min = $operator eq "<\%>" ? 0.95 : 0.98;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
$node->safe_psql("postgres", "TRUNCATE tst;");
}
done_testing();

View File

@@ -1,113 +0,0 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 10;
my $array_sql = join(",", ('random()') x $dim);
sub test_recall
{
my ($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;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v halfvec($dim));");
# Generate queries
for (1 .. 20)
{
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
push(@queries, "[" . join(",", @r) . "]");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("halfvec_l2_ops", "halfvec_ip_ops", "halfvec_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Add index
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v $opclass);");
# Use concurrent inserts
$node->pgbench(
"--no-vacuum --client=10 --transactions=1000",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"024_hnsw_halfvec_insert_recall_$opclass" => "INSERT INTO tst (v) VALUES (ARRAY[$array_sql]);"
}
);
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;
));
push(@expected, $res);
}
# Test approximate results
my $min = $operator eq "<#>" ? 0.94 : 0.98;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
$node->safe_psql("postgres", "TRUNCATE tst;");
}
done_testing();

View File

@@ -1,109 +0,0 @@
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 serial, v sparsevec(3));");
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "{1:$r1,2:$r2,3:$r3}/3");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("sparsevec_l2_ops", "sparsevec_ip_ops", "sparsevec_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Add index
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v $opclass);");
# Use concurrent inserts
$node->pgbench(
"--no-vacuum --client=10 --transactions=1000",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"025_hnsw_sparsevec_insert_recall_$opclass" => "INSERT INTO tst (v) VALUES (ARRAY[random(), random(), random()]::vector::sparsevec);"
}
);
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;
));
push(@expected, $res);
}
# Test approximate results
my $min = $operator eq "<#>" ? 0.80 : 0.99;
test_recall($min, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
$node->safe_psql("postgres", "TRUNCATE tst;");
}
done_testing();

View File

@@ -1,58 +0,0 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
# Initialize node
my $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 (v bit(3));");
sub insert_vectors
{
for my $i (1 .. 20)
{
$node->safe_psql("postgres", "INSERT INTO tst VALUES ('111');");
}
}
sub test_duplicates
{
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 1;
SELECT COUNT(*) FROM (SELECT * FROM tst ORDER BY v <~> '111') t;
));
is($res, 10);
}
# Test duplicates with build
insert_vectors();
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v bit_hamming_ops);");
test_duplicates();
# Reset
$node->safe_psql("postgres", "TRUNCATE tst;");
# Test duplicates with inserts
insert_vectors();
test_duplicates();
# Test fallback path for inserts
$node->pgbench(
"--no-vacuum --client=5 --transactions=100",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"026_hnsw_bit_duplicates" => "INSERT INTO tst VALUES ('111');"
}
);
done_testing();

View File

@@ -1,58 +0,0 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
# Initialize node
my $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 (v halfvec(3));");
sub insert_vectors
{
for my $i (1 .. 20)
{
$node->safe_psql("postgres", "INSERT INTO tst VALUES ('[1,1,1]');");
}
}
sub test_duplicates
{
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 1;
SELECT COUNT(*) FROM (SELECT * FROM tst ORDER BY v <-> '[1,1,1]') t;
));
is($res, 10);
}
# Test duplicates with build
insert_vectors();
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v halfvec_l2_ops);");
test_duplicates();
# Reset
$node->safe_psql("postgres", "TRUNCATE tst;");
# Test duplicates with inserts
insert_vectors();
test_duplicates();
# Test fallback path for inserts
$node->pgbench(
"--no-vacuum --client=5 --transactions=100",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"027_hnsw_halfvec_duplicates" => "INSERT INTO tst VALUES ('[1,1,1]');"
}
);
done_testing();

View File

@@ -1,58 +0,0 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
# Initialize node
my $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 (v sparsevec(3));");
sub insert_vectors
{
for my $i (1 .. 20)
{
$node->safe_psql("postgres", "INSERT INTO tst VALUES ('{1:1,2:1,3:1}/3');");
}
}
sub test_duplicates
{
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = 1;
SELECT COUNT(*) FROM (SELECT * FROM tst ORDER BY v <-> '{1:1,2:1,3:1}/3') t;
));
is($res, 10);
}
# Test duplicates with build
insert_vectors();
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v sparsevec_l2_ops);");
test_duplicates();
# Reset
$node->safe_psql("postgres", "TRUNCATE tst;");
# Test duplicates with inserts
insert_vectors();
test_duplicates();
# Test fallback path for inserts
$node->pgbench(
"--no-vacuum --client=5 --transactions=100",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"028_hnsw_sparsevec_duplicates" => "INSERT INTO tst VALUES ('{1:1,2:1,3:1}/3');"
}
);
done_testing();

View File

@@ -1,100 +0,0 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 52;
my $max = 2**$dim;
sub test_recall
{
my ($min, $ef_search, $test_name) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v <~> $queries[0] LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
SELECT i FROM tst ORDER BY v <~> $queries[$i] LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $test_name);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v bit($dim));");
$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, (random() * $max)::bigint::bit($dim) FROM generate_series(1, 10000) i;"
);
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v bit_hamming_ops) WITH (m = 4, ef_construction = 8);");
# Delete data
$node->safe_psql("postgres", "DELETE FROM tst WHERE i > 2500;");
# Generate queries
for (1 .. 20)
{
my $r = int(rand() * $max);
push(@queries, "${r}::bigint::bit($dim)");
}
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
WITH top AS (
SELECT v <~> $_ AS distance FROM tst ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v <~> $_) <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
test_recall(0.35, 100, "before vacuum");
# TODO Test concurrent inserts with vacuum
$node->safe_psql("postgres", "VACUUM tst;");
test_recall(0.80, 100, "after vacuum");
done_testing();

View File

@@ -1,97 +0,0 @@
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, $ef_search, $test_name) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v <-> '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
SELECT i FROM tst ORDER BY v <-> '$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, $test_name);
}
# 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 halfvec(3));");
$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 10000) i;"
);
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v halfvec_l2_ops) WITH (m = 4, ef_construction = 8);");
# Delete data
$node->safe_psql("postgres", "DELETE FROM tst WHERE i > 2500;");
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "[$r1,$r2,$r3]");
}
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v <-> '$_' LIMIT $limit;
));
push(@expected, $res);
}
test_recall(0.18, $limit, "before vacuum");
test_recall(0.95, 100, "before vacuum");
# TODO Test concurrent inserts with vacuum
$node->safe_psql("postgres", "VACUUM tst;");
test_recall(0.95, $limit, "after vacuum");
done_testing();

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@@ -1,97 +0,0 @@
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, $ef_search, $test_name) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v <-> '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
SELECT i FROM tst ORDER BY v <-> '$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, $test_name);
}
# 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 sparsevec(3));");
$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()]::vector::sparsevec(3) FROM generate_series(1, 10000) i;"
);
# Add index
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v sparsevec_l2_ops) WITH (m = 4, ef_construction = 8);");
# Delete data
$node->safe_psql("postgres", "DELETE FROM tst WHERE i > 2500;");
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "{1:$r1,2:$r2,3:$r3}/3");
}
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v <-> '$_' LIMIT $limit;
));
push(@expected, $res);
}
test_recall(0.18, $limit, "before vacuum");
test_recall(0.95, 100, "before vacuum");
# TODO Test concurrent inserts with vacuum
$node->safe_psql("postgres", "VACUUM tst;");
test_recall(0.95, $limit, "after vacuum");
done_testing();

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@@ -1,154 +0,0 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 10;
my $array_sql = join(",", ('random()') x $dim);
sub test_recall
{
my ($probes, $min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan using idx on tst/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
SELECT i FROM tst ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v halfvec($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
);
# Generate queries
for (1 .. 20)
{
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
push(@queries, "[" . join(",", @r) . "]");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("halfvec_l2_ops", "halfvec_ip_ops", "halfvec_cosine_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", qq(
WITH top AS (
SELECT v $operator '$_' AS distance FROM tst ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator '$_') <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
# Build index serially
$node->safe_psql("postgres", qq(
SET max_parallel_maintenance_workers = 0;
CREATE INDEX idx ON tst USING ivfflat (v $opclass);
));
# Test approximate results
if ($operator ne "<#>")
{
# TODO Fix test (uniform random vectors all have similar inner product)
test_recall(1, 0.35, $operator);
test_recall(10, 0.95, $operator);
}
# Test probes equals lists
if ($operator eq "<=>")
{
test_recall(100, 0.98, $operator);
}
else
{
test_recall(100, 1.00, $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;
CREATE INDEX idx ON tst USING ivfflat (v $opclass);
));
is($ret, 0, $stderr);
like($stderr, qr/using \d+ parallel workers/);
# Test approximate results
if ($operator ne "<#>")
{
# TODO Fix test (uniform random vectors all have similar inner product)
test_recall(1, 0.35, $operator);
test_recall(10, 0.95, $operator);
}
# Test probes equals lists
if ($operator eq "<=>")
{
test_recall(100, 0.98, $operator);
}
else
{
test_recall(100, 1.00, $operator);
}
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();