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30 Commits

Author SHA1 Message Date
Andrew Kane
2b125a1956 Moved bit functions to separate file 2024-03-27 13:42:24 -07:00
Andrew Kane
fcd655d2a3 Improved test [skip ci] 2024-03-26 19:26:52 -07:00
Andrew Kane
97fe28940d Updated readme [skip ci] 2024-03-25 23:33:59 -07:00
Andrew Kane
23c5bf6ef6 Fixed CI [skip ci] 2024-03-25 23:22:03 -07:00
Andrew Kane
9ed4303a5e Fixed test 2024-03-25 23:16:38 -07:00
Andrew Kane
acd066463a Added Jaccard distance to test 2024-03-25 23:15:14 -07:00
Andrew Kane
be936075eb Improved test [skip ci] 2024-03-25 23:13:30 -07:00
Andrew Kane
a9959fede2 Improved code [skip ci] 2024-03-25 23:03:12 -07:00
Andrew Kane
02c4f4884c Added support for indexing Jaccard distance 2024-03-25 22:44:51 -07:00
Andrew Kane
791fc2436f Added jaccard_distance function 2024-03-25 22:35:53 -07:00
Andrew Kane
e7a7936bb2 Improved code [skip ci] 2024-03-25 19:23:30 -07:00
Andrew Kane
ce2ba65906 Fixed CI 2024-03-25 19:07:09 -07:00
Andrew Kane
023633a274 Added test for build recall 2024-03-25 19:02:37 -07:00
Andrew Kane
9baa051b5b Fixed CI 2024-03-25 17:20:35 -07:00
Andrew Kane
ac94ac7cf1 Updated changelog [skip ci] 2024-03-25 17:18:09 -07:00
Andrew Kane
8b819dfdc2 Moved bit code to separate files 2024-03-25 17:10:01 -07:00
Andrew Kane
d9ca850faf Updated max dimensions [skip ci] 2024-03-25 16:56:32 -07:00
Andrew Kane
131782999b Updated changelog [skip ci] 2024-03-25 16:47:25 -07:00
Andrew Kane
d57ef873c2 Improved test [skip ci] 2024-03-25 16:43:15 -07:00
Andrew Kane
30c86fb05a Improved test [skip ci] 2024-03-25 16:41:40 -07:00
Andrew Kane
833f379ebe Added quantize_binary function 2024-03-25 16:39:55 -07:00
Andrew Kane
709fc75ce0 Updated changelog [skip ci] 2024-03-25 16:11:52 -07:00
Andrew Kane
2bc959b3eb Updated readme [skip ci] 2024-03-25 15:53:44 -07:00
Andrew Kane
ec9e13b5fb Improved test [skip ci] 2024-03-25 15:50:38 -07:00
Andrew Kane
95e476d570 Fixed CI 2024-03-25 15:49:18 -07:00
Andrew Kane
6bc0c47a0a Updated comments [skip ci] 2024-03-25 15:43:05 -07:00
Andrew Kane
58eeefeef4 Handle nulls 2024-03-25 15:40:15 -07:00
Andrew Kane
263e684824 Started indexing 2024-03-25 15:25:04 -07:00
Andrew Kane
21dfed5719 Fixed CI 2024-03-25 14:24:19 -07:00
Andrew Kane
f3aec9fd03 Added hamming_distance function 2024-03-25 14:22:23 -07:00
152 changed files with 2207 additions and 15299 deletions

View File

@@ -8,18 +8,18 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
include: include:
# - postgres: 18
# os: ubuntu-24.04
- postgres: 17 - postgres: 17
os: ubuntu-24.04 os: ubuntu-22.04
- postgres: 16 - postgres: 16
os: ubuntu-22.04 os: ubuntu-22.04
- postgres: 15 - postgres: 15
os: ubuntu-22.04 os: ubuntu-22.04
- postgres: 14 - postgres: 14
os: ubuntu-20.04 os: ubuntu-22.04
- postgres: 13 - postgres: 13
os: ubuntu-20.04 os: ubuntu-20.04
- postgres: 12
os: ubuntu-20.04
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1 - uses: ankane/setup-postgres@v1
@@ -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:
@@ -87,14 +73,13 @@ jobs:
postgres-version: 14 postgres-version: 14
- run: | - run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^ call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
cd %TEMP% && ^
nmake /NOLOGO /F Makefile.win && ^ nmake /NOLOGO /F Makefile.win && ^
nmake /NOLOGO /F Makefile.win install && ^ nmake /NOLOGO /F Makefile.win install && ^
nmake /NOLOGO /F Makefile.win installcheck && ^ nmake /NOLOGO /F Makefile.win installcheck && ^
nmake /NOLOGO /F Makefile.win clean && ^ nmake /NOLOGO /F Makefile.win clean && ^
nmake /NOLOGO /F Makefile.win uninstall nmake /NOLOGO /F Makefile.win uninstall
shell: cmd shell: cmd
- if: ${{ failure() }}
run: cat regression.diffs
i386: i386:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }} if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest runs-on: ubuntu-latest
@@ -116,8 +101,6 @@ jobs:
sudo -u postgres make prove_installcheck sudo -u postgres make prove_installcheck
env: env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
- if: ${{ failure() }}
run: cat pgvector/regression.diffs
valgrind: valgrind:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }} if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest runs-on: ubuntu-latest
@@ -126,7 +109,6 @@ jobs:
- uses: ankane/setup-postgres-valgrind@v1 - uses: ankane/setup-postgres-valgrind@v1
with: with:
postgres-version: 16 postgres-version: 16
check-ub: yes - run: make
- run: make OPTFLAGS=""
- run: sudo --preserve-env=PG_CONFIG make install - run: sudo --preserve-env=PG_CONFIG make install
- run: make installcheck - run: make installcheck

View File

@@ -1,45 +1,9 @@
## 0.8.0 (unreleased) ## 0.7.0 (unreleased)
- Added casts for arrays to `sparsevec` - Added support for binary vectors to HNSW
- Reduced memory usage for HNSW index scans
- Dropped support for Postgres 12
## 0.7.4 (2024-08-05)
- Fixed locking for parallel HNSW index builds
- Fixed compilation error with GCC 14 on i386 when SSE2 is not enabled
## 0.7.3 (2024-07-22)
- Fixed `failed to add index item` error with `sparsevec`
- Fixed compilation error with FreeBSD ARM
- Fixed compilation warning with MSVC and Postgres 16
## 0.7.2 (2024-06-11)
- Fixed initialization fork for indexes on unlogged tables
## 0.7.1 (2024-06-03)
- Improved performance of on-disk HNSW index builds
- Fixed `undefined symbol` error with GCC 8
- Fixed compilation error with universal binaries on Mac
- Fixed compilation warning with Clang < 14
## 0.7.0 (2024-04-29)
- Added `halfvec` type
- Added `sparsevec` type
- Added support for indexing `bit` type
- Added support for indexing L1 distance with HNSW
- Added `binary_quantize` function
- Added `hamming_distance` function - Added `hamming_distance` function
- Added `jaccard_distance` function - Added `jaccard_distance` function
- Added `l2_normalize` function - Added `quantize_binary` function
- Added `subvector` function
- Added concatenate operator for vectors
- 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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@@ -2,7 +2,7 @@
"name": "vector", "name": "vector",
"abstract": "Open-source vector similarity search for Postgres", "abstract": "Open-source vector similarity search for Postgres",
"description": "Supports L2 distance, inner product, and cosine distance", "description": "Supports L2 distance, inner product, and cosine distance",
"version": "0.7.4", "version": "0.6.2",
"maintainer": [ "maintainer": [
"Andrew Kane <andrew@ankane.org>" "Andrew Kane <andrew@ankane.org>"
], ],
@@ -20,7 +20,7 @@
"vector": { "vector": {
"file": "sql/vector.sql", "file": "sql/vector.sql",
"docfile": "README.md", "docfile": "README.md",
"version": "0.7.4", "version": "0.6.2",
"abstract": "Open-source vector similarity search for Postgres" "abstract": "Open-source vector similarity search for Postgres"
} }
}, },

View File

@@ -1,20 +1,18 @@
EXTENSION = vector EXTENSION = vector
EXTVERSION = 0.7.4 EXTVERSION = 0.6.2
MODULE_big = vector MODULE_big = vector
DATA = $(wildcard sql/*--*--*.sql) DATA = $(wildcard sql/*--*.sql)
DATA_built = sql/$(EXTENSION)--$(EXTVERSION).sql OBJS = src/bitvector.o src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
OBJS = src/bitutils.o src/bitvec.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/minivec.o src/ivfvacuum.o src/sparsevec.o src/vector.o HEADERS = src/vector.h
HEADERS = src/halfvec.h src/minivec.h src/sparsevec.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))
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION) REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
# To compile for portability, run: make OPTFLAGS=""
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
@@ -43,6 +41,8 @@ all: sql/$(EXTENSION)--$(EXTVERSION).sql
sql/$(EXTENSION)--$(EXTVERSION).sql: sql/$(EXTENSION).sql sql/$(EXTENSION)--$(EXTVERSION).sql: sql/$(EXTENSION).sql
cp $< $@ cp $< $@
EXTRA_CLEAN = sql/$(EXTENSION)--$(EXTVERSION).sql
PG_CONFIG ?= pg_config PG_CONFIG ?= pg_config
PGXS := $(shell $(PG_CONFIG) --pgxs) PGXS := $(shell $(PG_CONFIG) --pgxs)
include $(PGXS) include $(PGXS)
@@ -52,7 +52,7 @@ ifeq ($(PROVE),)
PROVE = prove PROVE = prove
endif endif
# for Postgres < 15 # for Postgres 15
PROVE_FLAGS += -I ./test/perl PROVE_FLAGS += -I ./test/perl
prove_installcheck: prove_installcheck:

View File

@@ -1,11 +1,10 @@
EXTENSION = vector EXTENSION = vector
EXTVERSION = 0.7.4 EXTVERSION = 0.6.2
DATA_built = sql\$(EXTENSION)--$(EXTVERSION).sql OBJS = src\bitvector.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
OBJS = src\bitutils.obj src\bitvec.obj src\halfutils.obj src\halfvec.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\minivec.obj src\sparsevec.obj src\vector.obj HEADERS = src\vector.h
HEADERS = src\halfvec.h src\minivec.h src\sparsevec.h src\vector.h
REGRESS = bit btree cast copy halfvec hnsw_bit hnsw_halfvec hnsw_sparsevec hnsw_vector ivfflat_bit ivfflat_halfvec ivfflat_vector minivec sparsevec vector_type REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION) REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
# For /arch flags # For /arch flags
@@ -20,6 +19,11 @@ PG_CFLAGS = $(PG_CFLAGS) $(OPTFLAGS) /O2 /fp:fast
# https://learn.microsoft.com/en-us/cpp/error-messages/tool-errors/vectorizer-and-parallelizer-messages # https://learn.microsoft.com/en-us/cpp/error-messages/tool-errors/vectorizer-and-parallelizer-messages
# PG_CFLAGS = $(PG_CFLAGS) /Qvec-report:2 # PG_CFLAGS = $(PG_CFLAGS) /Qvec-report:2
all: sql\$(EXTENSION)--$(EXTVERSION).sql
sql\$(EXTENSION)--$(EXTVERSION).sql: sql\$(EXTENSION).sql
copy sql\$(EXTENSION).sql $@
# TODO use pg_config # TODO use pg_config
!ifndef PGROOT !ifndef PGROOT
!error PGROOT is not set !error PGROOT is not set
@@ -39,18 +43,15 @@ SHLIB = $(EXTENSION).dll
LIBS = "$(LIBDIR)\postgres.lib" LIBS = "$(LIBDIR)\postgres.lib"
all: $(SHLIB) $(DATA_built)
.c.obj: .c.obj:
$(CC) $(CFLAGS) /c $< /Fo$@ $(CC) $(CFLAGS) /c $< /Fo$@
$(SHLIB): $(OBJS) $(SHLIB): $(OBJS)
$(CC) $(CFLAGS) $(OBJS) $(LIBS) /link /DLL /OUT:$(SHLIB) $(CC) $(CFLAGS) $(OBJS) $(LIBS) /link /DLL /OUT:$(SHLIB)
sql\$(EXTENSION)--$(EXTVERSION).sql: sql\$(EXTENSION).sql all: $(SHLIB)
copy sql\$(EXTENSION).sql $@
install: all install:
copy $(SHLIB) "$(PKGLIBDIR)" copy $(SHLIB) "$(PKGLIBDIR)"
copy $(EXTENSION).control "$(SHAREDIR)\extension" copy $(EXTENSION).control "$(SHAREDIR)\extension"
copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension" copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
@@ -69,6 +70,6 @@ uninstall:
clean: clean:
del /f $(SHLIB) $(EXTENSION).lib $(EXTENSION).exp del /f $(SHLIB) $(EXTENSION).lib $(EXTENSION).exp
del /f $(DATA_built)
del /f $(OBJS) del /f $(OBJS)
del /f sql\$(EXTENSION)--$(EXTVERSION).sql
del /f /s /q results regression.diffs regression.out tmp_check tmp_check_iso log output_iso del /f /s /q results regression.diffs regression.out tmp_check tmp_check_iso log output_iso

330
README.md
View File

@@ -5,8 +5,7 @@ Open-source vector similarity search for Postgres
Store your vectors with the rest of your data. Supports: Store your vectors with the rest of your data. Supports:
- exact and approximate nearest neighbor search - exact and approximate nearest neighbor search
- single-precision, half-precision, binary, and sparse vectors - L2 distance, inner product, cosine distance, and more
- L2 distance, inner product, cosine distance, L1 distance, Hamming distance, and Jaccard distance
- any [language](#languages) with a Postgres client - any [language](#languages) with a Postgres client
Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recovery, JOINs, and all of the other [great features](https://www.postgresql.org/about/) of Postgres Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recovery, JOINs, and all of the other [great features](https://www.postgresql.org/about/) of Postgres
@@ -21,7 +20,7 @@ Compile and install the extension (supports Postgres 12+)
```sh ```sh
cd /tmp cd /tmp
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector cd pgvector
make make
make install # may need sudo make install # may need sudo
@@ -46,7 +45,7 @@ Then use `nmake` to build:
```cmd ```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16" set "PGROOT=C:\Program Files\PostgreSQL\16"
cd %TEMP% cd %TEMP%
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector cd pgvector
nmake /F Makefile.win nmake /F Makefile.win
nmake /F Makefile.win install nmake /F Makefile.win install
@@ -82,7 +81,7 @@ Get the nearest neighbors by L2 distance
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5; SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
``` ```
Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`, added in 0.7.0) Also supports inner product (`<#>`) and cosine distance (`<=>`)
Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators
@@ -106,7 +105,7 @@ Insert vectors
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]'); INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
``` ```
Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py)) Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py))
```sql ```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY); COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
@@ -139,13 +138,6 @@ Get the nearest neighbors to a vector
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5; SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
``` ```
Supported distance functions are:
- `<->` - L2 distance
- `<#>` - (negative) inner product
- `<=>` - cosine distance
- `<+>` - L1 distance (added in 0.7.0)
Get the nearest neighbors to a row Get the nearest neighbors to a row
```sql ```sql
@@ -202,7 +194,7 @@ You can add an index to use approximate nearest neighbor search, which trades so
Supported index types are: Supported index types are:
- [HNSW](#hnsw) - [HNSW](#hnsw) - added in 0.5.0
- [IVFFlat](#ivfflat) - [IVFFlat](#ivfflat)
## HNSW ## HNSW
@@ -217,8 +209,6 @@ L2 distance
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops); CREATE INDEX ON items USING hnsw (embedding vector_l2_ops);
``` ```
Note: Use `halfvec_l2_ops` for `halfvec` and `sparsevec_l2_ops` for `sparsevec` (and similar with the other distance functions)
Inner product Inner product
```sql ```sql
@@ -231,12 +221,6 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops); CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
``` ```
L1 distance - added in 0.7.0
```sql
CREATE INDEX ON items USING hnsw (embedding vector_l1_ops);
```
Hamming distance - added in 0.7.0 Hamming distance - added in 0.7.0
```sql ```sql
@@ -249,12 +233,7 @@ Jaccard distance - added in 0.7.0
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops); CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
``` ```
Supported types are: Vectors with up to 2,000 dimensions can be indexed, or bit vectors with up to 64,000 dimensions.
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
- `sparsevec` - up to 1,000 non-zero elements (added in 0.7.0)
### Index Options ### Index Options
@@ -347,8 +326,6 @@ L2 distance
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100); CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100);
``` ```
Note: Use `halfvec_l2_ops` for `halfvec` (and similar with the other distance functions)
Inner product Inner product
```sql ```sql
@@ -361,17 +338,7 @@ 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);
``` ```
Hamming distance - added in 0.7.0 Vectors with up to 2,000 dimensions can be indexed.
```sql
CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100);
```
Supported types are:
- `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
### Query Options ### Query Options
@@ -445,103 +412,6 @@ 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-Precision Vectors
*Added in 0.7.0*
Use the `halfvec` type to store half-precision vectors
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));
```
## Half-Precision Indexing
*Added in 0.7.0*
Index vectors at half precision for smaller indexes
```sql
CREATE INDEX ON items USING hnsw ((embedding::halfvec(3)) halfvec_l2_ops);
```
Get the nearest neighbors
```sql
SELECT * 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/imagehash/example.py))
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES ('000'), ('111');
```
Get the nearest neighbors by Hamming distance (added in 0.7.0)
```sql
SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
```
Or (before 0.7.0)
```sql
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Also supports Jaccard distance (`<%>`)
## Binary Quantization
*Added in 0.7.0*
Use expression indexing for binary quantization
```sql
CREATE INDEX ON items USING hnsw ((binary_quantize(embedding)::bit(3)) bit_hamming_ops);
```
Get the nearest neighbors by Hamming distance
```sql
SELECT * FROM items ORDER BY binary_quantize(embedding)::bit(3) <~> binary_quantize('[1,-2,3]') LIMIT 5;
```
Re-rank by the original vectors for better recall
```sql
SELECT * FROM (
SELECT * FROM items ORDER BY binary_quantize(embedding)::bit(3) <~> binary_quantize('[1,-2,3]') LIMIT 20
) ORDER BY embedding <=> '[1,-2,3]' LIMIT 5;
```
## Sparse Vectors
*Added in 0.7.0*
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');
```
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
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search. Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search.
@@ -551,53 +421,17 @@ SELECT id, content FROM items, plainto_tsquery('hello search') query
WHERE textsearch @@ query ORDER BY ts_rank_cd(textsearch, query) DESC LIMIT 5; WHERE textsearch @@ query ORDER BY ts_rank_cd(textsearch, query) DESC LIMIT 5;
``` ```
You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search/rrf.py) or a [cross-encoder](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search/cross_encoder.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.
## Indexing Subvectors
*Added in 0.7.0*
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
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py)). Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py)).
```sql ```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY); COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
@@ -687,7 +521,7 @@ Scale pgvector the same way you scale Postgres.
Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring). Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus/example.py)). Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus.py)).
## Languages ## Languages
@@ -731,7 +565,7 @@ Yes, pgvector uses the write-ahead log (WAL), which allows for replication and p
#### What if I want to index vectors with more than 2,000 dimensions? #### What if I want to index vectors with more than 2,000 dimensions?
You can use [half-precision indexing](#half-precision-indexing) to index up to 4,000 dimensions or [binary quantization](#binary-quantization) to index up to 64,000 dimensions. Another option is [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction). Youll need to use [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction) at the moment.
#### Can I store vectors with different dimensions in the same column? #### Can I store vectors with different dimensions in the same column?
@@ -782,6 +616,18 @@ and query with:
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5; SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
``` ```
#### Are binary vectors supported?
You can store binary vectors and perform exact nearest neighbor search by Hamming distance in Postgres without an extension ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py)).
```tsql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES (B'000'), (B'111');
SELECT * FROM items ORDER BY bit_count(embedding # B'101') LIMIT 5;
```
Indexing is not currently supported.
#### Do indexes need to fit into memory? #### Do indexes need to fit into memory?
No, but like other index types, youll likely see better performance if they do. You can get the size of an index with: No, but like other index types, youll likely see better performance if they do. You can get the size of an index with:
@@ -794,7 +640,7 @@ SELECT pg_size_pretty(pg_relation_size('index_name'));
#### Why isnt a query using an index? #### Why isnt a query using an index?
The query needs to have an `ORDER BY` and `LIMIT`, and the `ORDER BY` must be the result of a distance operator (not an expression) in ascending order. The query needs to have an `ORDER BY` and `LIMIT`, and the `ORDER BY` must be the result of a distance operator, not an expression.
```sql ```sql
-- index -- index
@@ -837,8 +683,6 @@ ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;
Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead. Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead.
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
#### Why are there less results for a query after adding an IVFFlat index? #### Why are there less results for a query after adding an IVFFlat index?
The index was likely created with too little data for the number of lists. Drop the index until the table has more data. The index was likely created with too little data for the number of lists. Drop the index until the table has more data.
@@ -849,18 +693,11 @@ DROP INDEX index_name;
Results can also be limited by the number of probes (`ivfflat.probes`). Results can also be limited by the number of probes (`ivfflat.probes`).
Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).
## Reference ## 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
@@ -869,106 +706,29 @@ Operator | Description | Added
\+ | element-wise addition | \+ | element-wise addition |
\- | element-wise subtraction | \- | element-wise subtraction |
\* | element-wise multiplication | 0.5.0 \* | element-wise multiplication | 0.5.0
\|\| | concatenate | 0.7.0
<-> | Euclidean distance | <-> | Euclidean distance |
<#> | negative inner product | <#> | negative inner product |
<=> | cosine distance | <=> | cosine distance |
<+> | taxicab distance | 0.7.0
### Vector Functions ### Vector Functions
Function | Description | Added Function | Description | Added
--- | --- | --- --- | --- | ---
binary_quantize(vector) → bit | binary quantize | 0.7.0
cosine_distance(vector, vector) → double precision | cosine distance | cosine_distance(vector, vector) → double precision | cosine distance |
inner_product(vector, vector) → double precision | inner product | inner_product(vector, vector) → double precision | inner product |
l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
l2_distance(vector, vector) → double precision | Euclidean distance | l2_distance(vector, vector) → double precision | Euclidean distance |
l2_normalize(vector) → vector | Normalize with Euclidean norm | 0.7.0 l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
subvector(vector, integer, integer) → vector | subvector | 0.7.0 quantize_binary(vector) → bit | quantize | 0.7.0
vector_dims(vector) → integer | number of dimensions | vector_dims(vector) → integer | number of dimensions |
vector_norm(vector) → double precision | Euclidean norm | vector_norm(vector) → double precision | Euclidean norm |
### Vector Aggregate Functions ### Aggregate Functions
Function | Description | Added Function | Description | Added
--- | --- | --- --- | --- | ---
avg(vector) → vector | average | avg(vector) → vector | average |
sum(vector) → vector | sum | 0.5.0 sum(vector) → vector | sum | 0.5.0
### Halfvec Type
Each half vector takes `2 * dimensions + 8` bytes of storage. Each element is a half-precision floating-point number, and all elements must be finite (no `NaN`, `Infinity` or `-Infinity`). Half vectors can have up to 16,000 dimensions.
### Halfvec Operators
Operator | Description | Added
--- | --- | ---
\+ | element-wise addition | 0.7.0
\- | element-wise subtraction | 0.7.0
\* | element-wise multiplication | 0.7.0
\|\| | concatenate | 0.7.0
<-> | Euclidean distance | 0.7.0
<#> | negative inner product | 0.7.0
<=> | cosine distance | 0.7.0
<+> | taxicab distance | 0.7.0
### Halfvec Functions
Function | Description | Added
--- | --- | ---
binary_quantize(halfvec) → bit | binary quantize | 0.7.0
cosine_distance(halfvec, halfvec) → double precision | cosine distance | 0.7.0
inner_product(halfvec, halfvec) → double precision | inner product | 0.7.0
l1_distance(halfvec, halfvec) → double precision | taxicab distance | 0.7.0
l2_distance(halfvec, halfvec) → double precision | Euclidean distance | 0.7.0
l2_norm(halfvec) → double precision | Euclidean norm | 0.7.0
l2_normalize(halfvec) → halfvec | Normalize with Euclidean norm | 0.7.0
subvector(halfvec, integer, integer) → halfvec | subvector | 0.7.0
vector_dims(halfvec) → integer | number of dimensions | 0.7.0
### Halfvec Aggregate Functions
Function | Description | Added
--- | --- | ---
avg(halfvec) → halfvec | average | 0.7.0
sum(halfvec) → halfvec | sum | 0.7.0
### Minivec Type
Each mini vector takes `dimensions + 8` bytes of storage. Each element is a E4M3 8-bit floating-point number, and all elements must be finite (no `NaN`). Mini vectors can have up to 16,000 dimensions.
### Minivec Operators
Operator | Description | Added
--- | --- | ---
\+ | element-wise addition | 0.8.0
\- | element-wise subtraction | 0.8.0
\* | element-wise multiplication | 0.8.0
\|\| | concatenate | 0.8.0
<-> | Euclidean distance | 0.8.0
<#> | negative inner product | 0.8.0
<=> | cosine distance | 0.8.0
<+> | taxicab distance | 0.8.0
### Minivec Functions
Function | Description | Added
--- | --- | ---
binary_quantize(minivec) → bit | binary quantize | 0.8.0
cosine_distance(minivec, minivec) → double precision | cosine distance | 0.8.0
inner_product(minivec, minivec) → double precision | inner product | 0.8.0
l1_distance(minivec, minivec) → double precision | taxicab distance | 0.8.0
l2_distance(minivec, minivec) → double precision | Euclidean distance | 0.8.0
l2_norm(minivec) → double precision | Euclidean norm | 0.8.0
l2_normalize(minivec) → minivec | Normalize with Euclidean norm | 0.8.0
subvector(minivec, integer, integer) → minivec | subvector | 0.8.0
vector_dims(minivec) → integer | number of dimensions | 0.8.0
### 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 ### Bit Operators
Operator | Description | Added Operator | Description | Added
@@ -983,30 +743,6 @@ Function | Description | Added
hamming_distance(bit, bit) → double precision | Hamming distance | 0.7.0 hamming_distance(bit, bit) → double precision | Hamming distance | 0.7.0
jaccard_distance(bit, bit) → double precision | Jaccard distance | 0.7.0 jaccard_distance(bit, bit) → double precision | Jaccard distance | 0.7.0
### 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 | 0.7.0
<#> | negative inner product | 0.7.0
<=> | cosine distance | 0.7.0
<+> | taxicab distance | 0.7.0
### Sparsevec Functions
Function | Description | Added
--- | --- | ---
cosine_distance(sparsevec, sparsevec) → double precision | cosine distance | 0.7.0
inner_product(sparsevec, sparsevec) → double precision | inner product | 0.7.0
l1_distance(sparsevec, sparsevec) → double precision | taxicab distance | 0.7.0
l2_distance(sparsevec, sparsevec) → double precision | Euclidean distance | 0.7.0
l2_norm(sparsevec) → double precision | Euclidean norm | 0.7.0
l2_normalize(sparsevec) → sparsevec | Normalize with Euclidean norm | 0.7.0
## Installation Notes - Linux and Mac ## Installation Notes - Linux and Mac
### Postgres Location ### Postgres Location
@@ -1082,9 +818,9 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
You can also build the image manually: You can also build the image manually:
```sh ```sh
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git git clone --branch v0.6.2 https://github.com/pgvector/pgvector.git
cd pgvector cd pgvector
docker build --pull --build-arg PG_MAJOR=16 -t myuser/pgvector . docker build --build-arg PG_MAJOR=16 -t myuser/pgvector .
``` ```
### Homebrew ### Homebrew
@@ -1132,7 +868,7 @@ Note: Replace `16` with your Postgres server version
Install the FreeBSD package with: Install the FreeBSD package with:
```sh ```sh
pkg install postgresql15-pgvector pkg install postgresql15-pg_vector
``` ```
or the port with: or the port with:

View File

@@ -1,347 +1,9 @@
-- 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 l2_normalize(vector) RETURNS vector CREATE FUNCTION quantize_binary(vector) RETURNS bit
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION binary_quantize(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 vector_concat(vector, vector) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE OPERATOR <+> (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = l1_distance,
COMMUTATOR = '<+>'
);
CREATE OPERATOR || (
LEFTARG = vector, RIGHTARG = vector, PROCEDURE = vector_concat
);
CREATE FUNCTION ivfflat_halfvec_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION ivfflat_bit_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION hnsw_halfvec_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION hnsw_bit_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE FUNCTION hnsw_sparsevec_support(internal) RETURNS internal
AS 'MODULE_PATHNAME' LANGUAGE C;
CREATE OPERATOR CLASS vector_l1_ops
FOR TYPE vector USING hnsw AS
OPERATOR 1 <+> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(vector, vector);
CREATE TYPE halfvec;
CREATE FUNCTION halfvec_in(cstring, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_out(halfvec) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_recv(internal, oid, integer) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_send(halfvec) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE halfvec (
INPUT = halfvec_in,
OUTPUT = halfvec_out,
TYPMOD_IN = halfvec_typmod_in,
RECEIVE = halfvec_recv,
SEND = halfvec_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l1_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_dims(halfvec) RETURNS integer
AS 'MODULE_PATHNAME', 'halfvec_vector_dims' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_norm(halfvec) RETURNS float8
AS 'MODULE_PATHNAME', 'halfvec_l2_norm' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_normalize(halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME', 'halfvec_l2_normalize' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION binary_quantize(halfvec) RETURNS bit
AS 'MODULE_PATHNAME', 'halfvec_binary_quantize' 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_add(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_sub(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_mul(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_concat(halfvec, halfvec) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_lt(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_le(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_eq(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_ne(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_ge(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_gt(halfvec, halfvec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_cmp(halfvec, halfvec) RETURNS int4
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_l2_squared_distance(halfvec, halfvec) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_negative_inner_product(halfvec, halfvec) RETURNS float8
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_accum(double precision[], halfvec) RETURNS double precision[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_avg(double precision[]) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_combine(double precision[], double precision[]) RETURNS double precision[]
AS 'MODULE_PATHNAME', 'vector_combine' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE AGGREGATE avg(halfvec) (
SFUNC = halfvec_accum,
STYPE = double precision[],
FINALFUNC = halfvec_avg,
COMBINEFUNC = halfvec_combine,
INITCOND = '{0}',
PARALLEL = SAFE
);
CREATE AGGREGATE sum(halfvec) (
SFUNC = halfvec_add,
STYPE = halfvec,
COMBINEFUNC = halfvec_add,
PARALLEL = SAFE
);
CREATE FUNCTION halfvec(halfvec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_vector(halfvec, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_halfvec(vector, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(integer[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(real[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(double precision[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_halfvec(numeric[], integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION halfvec_to_float4(halfvec, integer, boolean) RETURNS real[]
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (halfvec AS halfvec)
WITH FUNCTION halfvec(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS vector)
WITH FUNCTION halfvec_to_vector(halfvec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (vector AS halfvec)
WITH FUNCTION vector_to_halfvec(vector, integer, boolean) AS IMPLICIT;
CREATE CAST (halfvec AS real[])
WITH FUNCTION halfvec_to_float4(halfvec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (integer[] AS halfvec)
WITH FUNCTION array_to_halfvec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS halfvec)
WITH FUNCTION array_to_halfvec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS halfvec)
WITH FUNCTION array_to_halfvec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS halfvec)
WITH FUNCTION array_to_halfvec(numeric[], integer, boolean) AS ASSIGNMENT;
CREATE OPERATOR <-> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);
CREATE OPERATOR <+> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = l1_distance,
COMMUTATOR = '<+>'
);
CREATE OPERATOR + (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_add,
COMMUTATOR = +
);
CREATE OPERATOR - (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_sub
);
CREATE OPERATOR * (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_mul,
COMMUTATOR = *
);
CREATE OPERATOR || (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_concat
);
CREATE OPERATOR < (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_lt,
COMMUTATOR = > , NEGATOR = >= ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
);
CREATE OPERATOR <= (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_le,
COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
CREATE OPERATOR = (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_eq,
COMMUTATOR = = , NEGATOR = <> ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR <> (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_ne,
COMMUTATOR = <> , NEGATOR = = ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR >= (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_ge,
COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargesel, JOIN = scalargejoinsel
);
CREATE OPERATOR > (
LEFTARG = halfvec, RIGHTARG = halfvec, PROCEDURE = halfvec_gt,
COMMUTATOR = < , NEGATOR = <= ,
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
);
CREATE OPERATOR CLASS halfvec_ops
DEFAULT FOR TYPE halfvec USING btree AS
OPERATOR 1 < ,
OPERATOR 2 <= ,
OPERATOR 3 = ,
OPERATOR 4 >= ,
OPERATOR 5 > ,
FUNCTION 1 halfvec_cmp(halfvec, halfvec);
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),
FUNCTION 5 ivfflat_halfvec_support(internal);
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 l2_norm(halfvec),
FUNCTION 5 ivfflat_halfvec_support(internal);
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 l2_norm(halfvec),
FUNCTION 3 halfvec_spherical_distance(halfvec, halfvec),
FUNCTION 4 l2_norm(halfvec),
FUNCTION 5 ivfflat_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_l2_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <-> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_l2_squared_distance(halfvec, halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_ip_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <#> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_cosine_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <=> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 halfvec_negative_inner_product(halfvec, halfvec),
FUNCTION 2 l2_norm(halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE OPERATOR CLASS halfvec_l1_ops
FOR TYPE halfvec USING hnsw AS
OPERATOR 1 <+> (halfvec, halfvec) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(halfvec, halfvec),
FUNCTION 3 hnsw_halfvec_support(internal);
CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8 CREATE FUNCTION hamming_distance(bit, bit) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE; AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
@@ -358,212 +20,12 @@ CREATE OPERATOR <%> (
COMMUTATOR = '<%>' COMMUTATOR = '<%>'
); );
CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING ivfflat AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit),
FUNCTION 3 hamming_distance(bit, bit),
FUNCTION 5 ivfflat_bit_support(internal);
CREATE OPERATOR CLASS bit_hamming_ops CREATE OPERATOR CLASS bit_hamming_ops
FOR TYPE bit USING hnsw AS FOR TYPE bit USING hnsw AS
OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops, OPERATOR 1 <~> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 hamming_distance(bit, bit), FUNCTION 1 hamming_distance(bit, bit);
FUNCTION 3 hnsw_bit_support(internal);
CREATE OPERATOR CLASS bit_jaccard_ops CREATE OPERATOR CLASS bit_jaccard_ops
FOR TYPE bit USING hnsw AS FOR TYPE bit USING hnsw AS
OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops, OPERATOR 1 <%> (bit, bit) FOR ORDER BY float_ops,
FUNCTION 1 jaccard_distance(bit, bit), FUNCTION 1 jaccard_distance(bit, bit);
FUNCTION 3 hnsw_bit_support(internal);
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 l1_distance(sparsevec, sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l1_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_norm(sparsevec) RETURNS float8
AS 'MODULE_PATHNAME', 'sparsevec_l2_norm' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION l2_normalize(sparsevec) RETURNS sparsevec
AS 'MODULE_PATHNAME', 'sparsevec_l2_normalize' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_lt(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_le(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_eq(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_ne(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_ge(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_gt(sparsevec, sparsevec) RETURNS bool
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_cmp(sparsevec, sparsevec) RETURNS int4
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 FUNCTION halfvec_to_sparsevec(halfvec, integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION sparsevec_to_halfvec(sparsevec, integer, boolean) RETURNS halfvec
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 ASSIGNMENT;
CREATE CAST (vector AS sparsevec)
WITH FUNCTION vector_to_sparsevec(vector, integer, boolean) AS IMPLICIT;
CREATE CAST (sparsevec AS halfvec)
WITH FUNCTION sparsevec_to_halfvec(sparsevec, integer, boolean) AS ASSIGNMENT;
CREATE CAST (halfvec AS sparsevec)
WITH FUNCTION halfvec_to_sparsevec(halfvec, 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 <+> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = l1_distance,
COMMUTATOR = '<+>'
);
CREATE OPERATOR < (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_lt,
COMMUTATOR = > , NEGATOR = >= ,
RESTRICT = scalarltsel, JOIN = scalarltjoinsel
);
CREATE OPERATOR <= (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_le,
COMMUTATOR = >= , NEGATOR = > ,
RESTRICT = scalarlesel, JOIN = scalarlejoinsel
);
CREATE OPERATOR = (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_eq,
COMMUTATOR = = , NEGATOR = <> ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR <> (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_ne,
COMMUTATOR = <> , NEGATOR = = ,
RESTRICT = eqsel, JOIN = eqjoinsel
);
CREATE OPERATOR >= (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_ge,
COMMUTATOR = <= , NEGATOR = < ,
RESTRICT = scalargesel, JOIN = scalargejoinsel
);
CREATE OPERATOR > (
LEFTARG = sparsevec, RIGHTARG = sparsevec, PROCEDURE = sparsevec_gt,
COMMUTATOR = < , NEGATOR = <= ,
RESTRICT = scalargtsel, JOIN = scalargtjoinsel
);
CREATE OPERATOR CLASS sparsevec_ops
DEFAULT FOR TYPE sparsevec USING btree AS
OPERATOR 1 < ,
OPERATOR 2 <= ,
OPERATOR 3 = ,
OPERATOR 4 >= ,
OPERATOR 5 > ,
FUNCTION 1 sparsevec_cmp(sparsevec, sparsevec);
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),
FUNCTION 3 hnsw_sparsevec_support(internal);
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),
FUNCTION 3 hnsw_sparsevec_support(internal);
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 l2_norm(sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);
CREATE OPERATOR CLASS sparsevec_l1_ops
FOR TYPE sparsevec USING hnsw AS
OPERATOR 1 <+> (sparsevec, sparsevec) FOR ORDER BY float_ops,
FUNCTION 1 l1_distance(sparsevec, sparsevec),
FUNCTION 3 hnsw_sparsevec_support(internal);

View File

@@ -1,2 +0,0 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.1'" to load this file. \quit

View File

@@ -1,2 +0,0 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.2'" to load this file. \quit

View File

@@ -1,2 +0,0 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.3'" to load this file. \quit

View File

@@ -1,2 +0,0 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.4'" to load this file. \quit

View File

@@ -1,28 +0,0 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.8.0'" to load this file. \quit
-- TODO minivec functions
CREATE FUNCTION array_to_sparsevec(integer[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(real[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(double precision[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(numeric[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (integer[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(numeric[], integer, boolean) AS ASSIGNMENT;

File diff suppressed because it is too large Load Diff

View File

@@ -1,222 +0,0 @@
#include "postgres.h"
#include "bitutils.h"
#include "halfvec.h" /* for USE_DISPATCH and USE_TARGET_CLONES */
#include "port/pg_bitutils.h"
#if defined(USE_DISPATCH)
#define BIT_DISPATCH
#endif
#ifdef BIT_DISPATCH
#include <immintrin.h>
#if defined(USE__GET_CPUID)
#include <cpuid.h>
#else
#include <intrin.h>
#endif
#ifdef _MSC_VER
#define TARGET_AVX512_POPCOUNT
#else
#define TARGET_AVX512_POPCOUNT __attribute__((target("avx512f,avx512vpopcntdq")))
#endif
#endif
/* Disable for LLVM due to crash with bitcode generation */
#if defined(USE_TARGET_CLONES) && !defined(__POPCNT__) && !defined(__llvm__)
#define BIT_TARGET_CLONES __attribute__((target_clones("default", "popcnt")))
#else
#define BIT_TARGET_CLONES
#endif
/* Use built-ins when possible for inlining */
#if defined(HAVE__BUILTIN_POPCOUNT) && defined(HAVE_LONG_INT_64)
#define popcount64(x) __builtin_popcountl(x)
#elif defined(HAVE__BUILTIN_POPCOUNT) && defined(HAVE_LONG_LONG_INT_64)
#define popcount64(x) __builtin_popcountll(x)
#elif !defined(_MSC_VER)
/* Fails to resolve with MSVC */
#define popcount64(x) pg_popcount64(x)
#endif
uint64 (*BitHammingDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance);
double (*BitJaccardDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 ab, uint64 aa, uint64 bb);
BIT_TARGET_CLONES static uint64
BitHammingDistanceDefault(uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance)
{
#ifdef popcount64
for (; bytes >= sizeof(uint64); bytes -= sizeof(uint64))
{
uint64 axs;
uint64 bxs;
/* Ensure aligned */
memcpy(&axs, ax, sizeof(uint64));
memcpy(&bxs, bx, sizeof(uint64));
distance += popcount64(axs ^ bxs);
ax += sizeof(uint64);
bx += sizeof(uint64);
}
#endif
for (uint32 i = 0; i < bytes; i++)
distance += pg_number_of_ones[ax[i] ^ bx[i]];
return distance;
}
#ifdef BIT_DISPATCH
TARGET_AVX512_POPCOUNT static uint64
BitHammingDistanceAvx512Popcount(uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance)
{
__m512i dist = _mm512_setzero_si512();
for (; bytes >= sizeof(__m512i); bytes -= sizeof(__m512i))
{
__m512i axs = _mm512_loadu_si512((const __m512i *) ax);
__m512i bxs = _mm512_loadu_si512((const __m512i *) bx);
dist = _mm512_add_epi64(dist, _mm512_popcnt_epi64(_mm512_xor_si512(axs, bxs)));
ax += sizeof(__m512i);
bx += sizeof(__m512i);
}
distance += _mm512_reduce_add_epi64(dist);
return BitHammingDistanceDefault(bytes, ax, bx, distance);
}
#endif
BIT_TARGET_CLONES static double
BitJaccardDistanceDefault(uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 ab, uint64 aa, uint64 bb)
{
#ifdef popcount64
for (; bytes >= sizeof(uint64); bytes -= sizeof(uint64))
{
uint64 axs;
uint64 bxs;
/* Ensure aligned */
memcpy(&axs, ax, sizeof(uint64));
memcpy(&bxs, bx, sizeof(uint64));
ab += popcount64(axs & bxs);
aa += popcount64(axs);
bb += popcount64(bxs);
ax += sizeof(uint64);
bx += sizeof(uint64);
}
#endif
for (uint32 i = 0; i < bytes; i++)
{
ab += pg_number_of_ones[ax[i] & bx[i]];
aa += pg_number_of_ones[ax[i]];
bb += pg_number_of_ones[bx[i]];
}
if (ab == 0)
return 1;
else
return 1 - (ab / ((double) (aa + bb - ab)));
}
#ifdef BIT_DISPATCH
TARGET_AVX512_POPCOUNT static double
BitJaccardDistanceAvx512Popcount(uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 ab, uint64 aa, uint64 bb)
{
__m512i abx = _mm512_setzero_si512();
__m512i aax = _mm512_setzero_si512();
__m512i bbx = _mm512_setzero_si512();
for (; bytes >= sizeof(__m512i); bytes -= sizeof(__m512i))
{
__m512i axs = _mm512_loadu_si512((const __m512i *) ax);
__m512i bxs = _mm512_loadu_si512((const __m512i *) bx);
abx = _mm512_add_epi64(abx, _mm512_popcnt_epi64(_mm512_and_si512(axs, bxs)));
aax = _mm512_add_epi64(aax, _mm512_popcnt_epi64(axs));
bbx = _mm512_add_epi64(bbx, _mm512_popcnt_epi64(bxs));
ax += sizeof(__m512i);
bx += sizeof(__m512i);
}
ab += _mm512_reduce_add_epi64(abx);
aa += _mm512_reduce_add_epi64(aax);
bb += _mm512_reduce_add_epi64(bbx);
return BitJaccardDistanceDefault(bytes, ax, bx, ab, aa, bb);
}
#endif
#ifdef BIT_DISPATCH
#define CPU_FEATURE_OSXSAVE (1 << 27) /* F1 ECX */
#define CPU_FEATURE_AVX512F (1 << 16) /* F7,0 EBX */
#define CPU_FEATURE_AVX512VPOPCNTDQ (1 << 14) /* F7,0 ECX */
#ifdef _MSC_VER
#define TARGET_XSAVE
#else
#define TARGET_XSAVE __attribute__((target("xsave")))
#endif
TARGET_XSAVE static bool
SupportsAvx512Popcount()
{
unsigned int exx[4] = {0, 0, 0, 0};
#if defined(USE__GET_CPUID)
__get_cpuid(1, &exx[0], &exx[1], &exx[2], &exx[3]);
#else
__cpuid(exx, 1);
#endif
/* Check OS supports XSAVE */
if ((exx[2] & CPU_FEATURE_OSXSAVE) != CPU_FEATURE_OSXSAVE)
return false;
/* Check XMM, YMM, and ZMM registers are enabled */
if ((_xgetbv(0) & 0xe6) != 0xe6)
return false;
#if defined(USE__GET_CPUID)
__get_cpuid_count(7, 0, &exx[0], &exx[1], &exx[2], &exx[3]);
#else
__cpuidex(exx, 7, 0);
#endif
/* Check AVX512F */
if ((exx[1] & CPU_FEATURE_AVX512F) != CPU_FEATURE_AVX512F)
return false;
/* Check AVX512VPOPCNTDQ */
return (exx[2] & CPU_FEATURE_AVX512VPOPCNTDQ) == CPU_FEATURE_AVX512VPOPCNTDQ;
}
#endif
void
BitvecInit(void)
{
/*
* Could skip pointer when single function, but no difference in
* performance
*/
BitHammingDistance = BitHammingDistanceDefault;
BitJaccardDistance = BitJaccardDistanceDefault;
#ifdef BIT_DISPATCH
if (SupportsAvx512Popcount())
{
BitHammingDistance = BitHammingDistanceAvx512Popcount;
BitJaccardDistance = BitJaccardDistanceAvx512Popcount;
}
#endif
}

View File

@@ -1,16 +0,0 @@
#ifndef BITUTILS_H
#define BITUTILS_H
#include "postgres.h"
/* Check version in first header */
#if PG_VERSION_NUM < 130000
#error "Requires PostgreSQL 13+"
#endif
extern uint64 (*BitHammingDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance);
extern double (*BitJaccardDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 ab, uint64 aa, uint64 bb);
void BitvecInit(void);
#endif

View File

@@ -1,69 +0,0 @@
#include "postgres.h"
#include "bitutils.h"
#include "bitvec.h"
#include "utils/varbit.h"
#include "vector.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
*/
FUNCTION_PREFIX 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);
CheckDims(a, b);
PG_RETURN_FLOAT8((double) BitHammingDistance(VARBITBYTES(a), VARBITS(a), VARBITS(b), 0));
}
/*
* Get the Jaccard distance between two bit vectors
*/
FUNCTION_PREFIX 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);
CheckDims(a, b);
PG_RETURN_FLOAT8(BitJaccardDistance(VARBITBYTES(a), VARBITS(a), VARBITS(b), 0, 0, 0));
}

90
src/bitvector.c Normal file
View File

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

View File

@@ -1,5 +1,5 @@
#ifndef BITVEC_H #ifndef BITVECTOR_H
#define BITVEC_H #define BITVECTOR_H
#include "utils/varbit.h" #include "utils/varbit.h"

View File

@@ -1,298 +0,0 @@
#include "postgres.h"
#include "halfutils.h"
#include "halfvec.h"
#ifdef HALFVEC_DISPATCH
#include <immintrin.h>
#if defined(USE__GET_CPUID)
#include <cpuid.h>
#else
#include <intrin.h>
#endif
#ifdef _MSC_VER
#define TARGET_F16C
#else
#define TARGET_F16C __attribute__((target("avx,f16c,fma")))
#endif
#endif
float (*HalfvecL2SquaredDistance) (int dim, half * ax, half * bx);
float (*HalfvecInnerProduct) (int dim, half * ax, half * bx);
double (*HalfvecCosineSimilarity) (int dim, half * ax, half * bx);
float (*HalfvecL1Distance) (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 static float
HalfvecL2SquaredDistanceF16c(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 static float
HalfvecInnerProductF16c(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
static double
HalfvecCosineSimilarityDefault(int dim, half * ax, half * bx)
{
float similarity = 0.0;
float norma = 0.0;
float normb = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
{
float axi = HalfToFloat4(ax[i]);
float bxi = HalfToFloat4(bx[i]);
similarity += axi * bxi;
norma += axi * axi;
normb += bxi * bxi;
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
return (double) similarity / sqrt((double) norma * (double) normb);
}
#ifdef HALFVEC_DISPATCH
TARGET_F16C static double
HalfvecCosineSimilarityF16c(int dim, half * ax, half * bx)
{
float similarity;
float norma;
float normb;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 sim = _mm256_setzero_ps();
__m256 na = _mm256_setzero_ps();
__m256 nb = _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);
sim = _mm256_fmadd_ps(axs, bxs, sim);
na = _mm256_fmadd_ps(axs, axs, na);
nb = _mm256_fmadd_ps(bxs, bxs, nb);
}
_mm256_storeu_ps(s, sim);
similarity = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
_mm256_storeu_ps(s, na);
norma = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
_mm256_storeu_ps(s, nb);
normb = s[0] + s[1] + s[2] + s[3] + s[4] + s[5] + s[6] + s[7];
/* Auto-vectorized */
for (; i < dim; i++)
{
float axi = HalfToFloat4(ax[i]);
float bxi = HalfToFloat4(bx[i]);
similarity += axi * bxi;
norma += axi * axi;
normb += bxi * bxi;
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
return (double) similarity / sqrt((double) norma * (double) normb);
}
#endif
static float
HalfvecL1DistanceDefault(int dim, half * ax, half * bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += fabsf(HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]));
return distance;
}
#ifdef HALFVEC_DISPATCH
/* Does not require FMA, but keep logic simple */
TARGET_F16C static float
HalfvecL1DistanceF16c(int dim, half * ax, half * bx)
{
float distance;
int i;
float s[8];
int count = (dim / 8) * 8;
__m256 dist = _mm256_setzero_ps();
__m256 sign = _mm256_set1_ps(-0.0);
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_add_ps(dist, _mm256_andnot_ps(sign, _mm256_sub_ps(axs, bxs)));
}
_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 += fabsf(HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]));
return distance;
}
#endif
#ifdef HALFVEC_DISPATCH
#define CPU_FEATURE_FMA (1 << 12)
#define CPU_FEATURE_OSXSAVE (1 << 27)
#define CPU_FEATURE_AVX (1 << 28)
#define CPU_FEATURE_F16C (1 << 29)
#ifdef _MSC_VER
#define TARGET_XSAVE
#else
#define TARGET_XSAVE __attribute__((target("xsave")))
#endif
TARGET_XSAVE static bool
SupportsCpuFeature(unsigned int feature)
{
unsigned int exx[4] = {0, 0, 0, 0};
#if defined(USE__GET_CPUID)
__get_cpuid(1, &exx[0], &exx[1], &exx[2], &exx[3]);
#else
__cpuid(exx, 1);
#endif
/* Check OS supports XSAVE */
if ((exx[2] & CPU_FEATURE_OSXSAVE) != CPU_FEATURE_OSXSAVE)
return false;
/* Check XMM and YMM registers are enabled */
if ((_xgetbv(0) & 6) != 6)
return false;
/* Now check features */
return (exx[2] & feature) == feature;
}
#endif
void
HalfvecInit(void)
{
/*
* Could skip pointer when single function, but no difference in
* performance
*/
HalfvecL2SquaredDistance = HalfvecL2SquaredDistanceDefault;
HalfvecInnerProduct = HalfvecInnerProductDefault;
HalfvecCosineSimilarity = HalfvecCosineSimilarityDefault;
HalfvecL1Distance = HalfvecL1DistanceDefault;
#ifdef HALFVEC_DISPATCH
if (SupportsCpuFeature(CPU_FEATURE_AVX | CPU_FEATURE_F16C | CPU_FEATURE_FMA))
{
HalfvecL2SquaredDistance = HalfvecL2SquaredDistanceF16c;
HalfvecInnerProduct = HalfvecInnerProductF16c;
HalfvecCosineSimilarity = HalfvecCosineSimilarityF16c;
/* Does not require FMA, but keep logic simple */
HalfvecL1Distance = HalfvecL1DistanceF16c;
}
#endif
}

View File

@@ -1,263 +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);
extern double (*HalfvecCosineSimilarity) (int dim, half * ax, half * bx);
extern float (*HalfvecL1Distance) (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
}
/*
* Check if half is zero
*/
static inline bool
HalfIsZero(half num)
{
#ifdef FLT16_SUPPORT
return num == 0;
#else
return (num & 0x7FFF) == 0x0000;
#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
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
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

File diff suppressed because it is too large Load Diff

View File

@@ -1,70 +0,0 @@
#ifndef HALFVEC_H
#define HALFVEC_H
#define __STDC_WANT_IEC_60559_TYPES_EXT__
#include <float.h>
/* We use two types of dispatching: intrinsics and target_clones */
/* TODO Move to better place */
#ifndef DISABLE_DISPATCH
/* Only enable for more recent compilers to keep build process simple */
#if defined(__x86_64__) && defined(__GNUC__) && __GNUC__ >= 9
#define USE_DISPATCH
#elif defined(__x86_64__) && defined(__clang_major__) && __clang_major__ >= 7
#define USE_DISPATCH
#elif defined(_M_AMD64) && defined(_MSC_VER) && _MSC_VER >= 1920
#define USE_DISPATCH
#endif
#endif
/* target_clones requires glibc */
#if defined(USE_DISPATCH) && defined(__gnu_linux__) && defined(__has_attribute)
/* Use separate line for portability */
#if __has_attribute(target_clones)
#define USE_TARGET_CLONES
#endif
#endif
/* Apple clang check needed for universal binaries on Mac */
#if defined(USE_DISPATCH) && (defined(HAVE__GET_CPUID) || defined(__apple_build_version__))
#define USE__GET_CPUID
#endif
#if defined(USE_DISPATCH)
#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) && !defined(__FreeBSD__) && (!defined(__i386__) || defined(__SSE2__))
#define FLT16_SUPPORT
#endif
#ifdef FLT16_SUPPORT
#define half _Float16
#define HALF_MAX FLT16_MAX
#else
#define half uint16
#define HALF_MAX 65504
#endif
#define HALFVEC_MAX_DIM 16000
#define HALFVEC_SIZE(_dim) (offsetof(HalfVector, x) + sizeof(half)*(_dim))
#define DatumGetHalfVector(x) ((HalfVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_HALFVEC_P(x) DatumGetHalfVector(PG_GETARG_DATUM(x))
#define PG_RETURN_HALFVEC_P(x) PG_RETURN_POINTER(x)
typedef struct HalfVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int16 dim; /* number of dimensions */
int16 unused; /* reserved for future use, always zero */
half x[FLEXIBLE_ARRAY_MEMBER];
} HalfVector;
HalfVector *InitHalfVector(int dim);
#endif

View File

@@ -9,7 +9,6 @@
#include "commands/vacuum.h" #include "commands/vacuum.h"
#include "hnsw.h" #include "hnsw.h"
#include "miscadmin.h" #include "miscadmin.h"
#include "utils/float.h"
#include "utils/guc.h" #include "utils/guc.h"
#include "utils/selfuncs.h" #include "utils/selfuncs.h"
@@ -60,9 +59,17 @@ HnswInit(void)
hnsw_relopt_kind = add_reloption_kind(); hnsw_relopt_kind = add_reloption_kind();
add_int_reloption(hnsw_relopt_kind, "m", "Max number of connections", add_int_reloption(hnsw_relopt_kind, "m", "Max number of connections",
HNSW_DEFAULT_M, HNSW_MIN_M, HNSW_MAX_M, AccessExclusiveLock); HNSW_DEFAULT_M, HNSW_MIN_M, HNSW_MAX_M
#if PG_VERSION_NUM >= 130000
,AccessExclusiveLock
#endif
);
add_int_reloption(hnsw_relopt_kind, "ef_construction", "Size of the dynamic candidate list for construction", add_int_reloption(hnsw_relopt_kind, "ef_construction", "Size of the dynamic candidate list for construction",
HNSW_DEFAULT_EF_CONSTRUCTION, HNSW_MIN_EF_CONSTRUCTION, HNSW_MAX_EF_CONSTRUCTION, AccessExclusiveLock); HNSW_DEFAULT_EF_CONSTRUCTION, HNSW_MIN_EF_CONSTRUCTION, HNSW_MAX_EF_CONSTRUCTION
#if PG_VERSION_NUM >= 130000
,AccessExclusiveLock
#endif
);
DefineCustomIntVariable("hnsw.ef_search", "Sets the size of the dynamic candidate list for search", DefineCustomIntVariable("hnsw.ef_search", "Sets the size of the dynamic candidate list for search",
"Valid range is 1..1000.", &hnsw_ef_search, "Valid range is 1..1000.", &hnsw_ef_search,
@@ -105,8 +112,8 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
/* Never use index without order */ /* Never use index without order */
if (path->indexorderbys == NULL) if (path->indexorderbys == NULL)
{ {
*indexStartupCost = get_float8_infinity(); *indexStartupCost = DBL_MAX;
*indexTotalCost = get_float8_infinity(); *indexTotalCost = DBL_MAX;
*indexSelectivity = 0; *indexSelectivity = 0;
*indexCorrelation = 0; *indexCorrelation = 0;
*indexPages = 0; *indexPages = 0;
@@ -147,10 +154,23 @@ hnswoptions(Datum reloptions, bool validate)
{"ef_construction", RELOPT_TYPE_INT, offsetof(HnswOptions, efConstruction)}, {"ef_construction", RELOPT_TYPE_INT, offsetof(HnswOptions, efConstruction)},
}; };
#if PG_VERSION_NUM >= 130000
return (bytea *) build_reloptions(reloptions, validate, return (bytea *) build_reloptions(reloptions, validate,
hnsw_relopt_kind, hnsw_relopt_kind,
sizeof(HnswOptions), sizeof(HnswOptions),
tab, lengthof(tab)); tab, lengthof(tab));
#else
relopt_value *options;
int numoptions;
HnswOptions *rdopts;
options = parseRelOptions(reloptions, validate, hnsw_relopt_kind, &numoptions);
rdopts = allocateReloptStruct(sizeof(HnswOptions), options, numoptions);
fillRelOptions((void *) rdopts, sizeof(HnswOptions), options, numoptions,
validate, tab, lengthof(tab));
return (bytea *) rdopts;
#endif
} }
/* /*
@@ -167,15 +187,17 @@ hnswvalidate(Oid opclassoid)
* *
* See https://www.postgresql.org/docs/current/index-api.html * See https://www.postgresql.org/docs/current/index-api.html
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnswhandler); PGDLLEXPORT PG_FUNCTION_INFO_V1(hnswhandler);
Datum Datum
hnswhandler(PG_FUNCTION_ARGS) hnswhandler(PG_FUNCTION_ARGS)
{ {
IndexAmRoutine *amroutine = makeNode(IndexAmRoutine); IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0; amroutine->amstrategies = 0;
amroutine->amsupport = 3; amroutine->amsupport = 2;
#if PG_VERSION_NUM >= 130000
amroutine->amoptsprocnum = 0; amroutine->amoptsprocnum = 0;
#endif
amroutine->amcanorder = false; amroutine->amcanorder = false;
amroutine->amcanorderbyop = true; amroutine->amcanorderbyop = true;
amroutine->amcanbackward = false; /* can change direction mid-scan */ amroutine->amcanbackward = false; /* can change direction mid-scan */
@@ -188,24 +210,17 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amclusterable = false; amroutine->amclusterable = false;
amroutine->ampredlocks = false; amroutine->ampredlocks = false;
amroutine->amcanparallel = false; amroutine->amcanparallel = false;
#if PG_VERSION_NUM >= 170000
amroutine->amcanbuildparallel = true;
#endif
amroutine->amcaninclude = false; amroutine->amcaninclude = false;
#if PG_VERSION_NUM >= 130000
amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */ amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */
#if PG_VERSION_NUM >= 160000
amroutine->amsummarizing = false;
#endif
amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL; amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL;
#endif
amroutine->amkeytype = InvalidOid; amroutine->amkeytype = InvalidOid;
/* Interface functions */ /* Interface functions */
amroutine->ambuild = hnswbuild; amroutine->ambuild = hnswbuild;
amroutine->ambuildempty = hnswbuildempty; amroutine->ambuildempty = hnswbuildempty;
amroutine->aminsert = hnswinsert; amroutine->aminsert = hnswinsert;
#if PG_VERSION_NUM >= 170000
amroutine->aminsertcleanup = NULL;
#endif
amroutine->ambulkdelete = hnswbulkdelete; amroutine->ambulkdelete = hnswbulkdelete;
amroutine->amvacuumcleanup = hnswvacuumcleanup; amroutine->amvacuumcleanup = hnswvacuumcleanup;
amroutine->amcanreturn = NULL; amroutine->amcanreturn = NULL;

View File

@@ -12,13 +12,15 @@
#include "utils/sampling.h" #include "utils/sampling.h"
#include "vector.h" #include "vector.h"
#if PG_VERSION_NUM < 120000
#error "Requires PostgreSQL 12+"
#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
#define HNSW_NORM_PROC 2 #define HNSW_NORM_PROC 2
#define HNSW_TYPE_INFO_PROC 3
#define HNSW_VERSION 1 #define HNSW_VERSION 1
#define HNSW_MAGIC_NUMBER 0xA953A953 #define HNSW_MAGIC_NUMBER 0xA953A953
@@ -76,6 +78,11 @@
#define SeedRandom(seed) srandom(seed) #define SeedRandom(seed) srandom(seed)
#endif #endif
#if PG_VERSION_NUM < 130000
#define list_delete_last(list) list_truncate(list, list_length(list) - 1)
#define list_sort(list, cmp) ((list) = list_qsort(list, cmp))
#endif
#define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE) #define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
#define HnswIsNeighborTuple(tup) ((tup)->type == HNSW_NEIGHBOR_TUPLE_TYPE) #define HnswIsNeighborTuple(tup) ((tup)->type == HNSW_NEIGHBOR_TUPLE_TYPE)
@@ -155,13 +162,11 @@ struct HnswNeighborArray
HnswCandidate items[FLEXIBLE_ARRAY_MEMBER]; HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
}; };
typedef struct HnswSearchCandidate typedef struct HnswPairingHeapNode
{ {
pairingheap_node c_node; pairingheap_node ph_node;
pairingheap_node w_node; HnswCandidate *inner;
HnswElementPtr element; } HnswPairingHeapNode;
float distance;
} HnswSearchCandidate;
/* HNSW index options */ /* HNSW index options */
typedef struct HnswOptions typedef struct HnswOptions
@@ -230,13 +235,6 @@ typedef struct HnswAllocator
void *state; void *state;
} HnswAllocator; } HnswAllocator;
typedef struct HnswTypeInfo
{
int maxDimensions;
Datum (*normalize) (PG_FUNCTION_ARGS);
void (*checkValue) (Pointer v);
} HnswTypeInfo;
typedef struct HnswBuildState typedef struct HnswBuildState
{ {
/* Info */ /* Info */
@@ -244,7 +242,6 @@ typedef struct HnswBuildState
Relation index; Relation index;
IndexInfo *indexInfo; IndexInfo *indexInfo;
ForkNumber forkNum; ForkNumber forkNum;
const HnswTypeInfo *typeInfo;
/* Settings */ /* Settings */
int dimensions; int dimensions;
@@ -265,6 +262,7 @@ typedef struct HnswBuildState
HnswGraph *graph; HnswGraph *graph;
double ml; double ml;
int maxLevel; int maxLevel;
Vector *normvec;
/* Memory */ /* Memory */
MemoryContext graphCtx; MemoryContext graphCtx;
@@ -327,7 +325,6 @@ typedef HnswNeighborTupleData * HnswNeighborTuple;
typedef struct HnswScanOpaqueData typedef struct HnswScanOpaqueData
{ {
const HnswTypeInfo *typeInfo;
bool first; bool first;
List *w; List *w;
MemoryContext tmpCtx; MemoryContext tmpCtx;
@@ -370,8 +367,7 @@ 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);
Datum HnswNormValue(const HnswTypeInfo * typeInfo, Oid collation, Datum value); bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
bool HnswCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value);
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);
@@ -382,7 +378,7 @@ void *HnswAlloc(HnswAllocator * allocator, Size size);
HnswElement HnswInitElement(char *base, ItemPointer tid, int m, double ml, int maxLevel, HnswAllocator * alloc); HnswElement HnswInitElement(char *base, ItemPointer tid, int m, double ml, int maxLevel, HnswAllocator * alloc);
HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno); HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno);
void HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing); void HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing);
HnswSearchCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec); HnswCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum, bool building); void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum, bool building);
void HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m); void HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m);
void HnswAddHeapTid(HnswElement element, ItemPointer heaptid); void HnswAddHeapTid(HnswElement element, ItemPointer heaptid);
@@ -390,12 +386,11 @@ void HnswInitNeighbors(char *base, HnswElement element, int m, HnswAllocator *
bool HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building); bool HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building);
void HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building); void HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building);
void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec); void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec);
void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance); void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element); void HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element);
void HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation); void HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
void HnswLoadNeighbors(HnswElement element, Relation index, int m); void HnswLoadNeighbors(HnswElement element, Relation index, int m);
void HnswInitLockTranche(void); void HnswInitLockTranche(void);
const HnswTypeInfo *HnswGetTypeInfo(Relation index);
PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc); PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);
/* Index access methods */ /* Index access methods */

View File

@@ -60,6 +60,12 @@
#include "pgstat.h" #include "pgstat.h"
#endif #endif
#if PG_VERSION_NUM >= 130000
#define CALLBACK_ITEM_POINTER ItemPointer tid
#else
#define CALLBACK_ITEM_POINTER HeapTuple hup
#endif
#if PG_VERSION_NUM >= 140000 #if PG_VERSION_NUM >= 140000
#include "utils/backend_status.h" #include "utils/backend_status.h"
#include "utils/wait_event.h" #include "utils/wait_event.h"
@@ -69,6 +75,10 @@
#define PARALLEL_KEY_HNSW_AREA UINT64CONST(0xA000000000000002) #define PARALLEL_KEY_HNSW_AREA UINT64CONST(0xA000000000000002)
#define PARALLEL_KEY_QUERY_TEXT UINT64CONST(0xA000000000000003) #define PARALLEL_KEY_QUERY_TEXT UINT64CONST(0xA000000000000003)
#if PG_VERSION_NUM < 130000
#define GENERATIONCHUNK_RAWSIZE (SIZEOF_SIZE_T + SIZEOF_VOID_P * 2)
#endif
/* /*
* Create the metapage * Create the metapage
*/ */
@@ -182,9 +192,7 @@ CreateGraphPages(HnswBuildState * buildstate)
/* Initial size check */ /* Initial size check */
if (etupSize > HNSW_TUPLE_ALLOC_SIZE) if (etupSize > HNSW_TUPLE_ALLOC_SIZE)
ereport(ERROR, elog(ERROR, "index tuple too large");
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("index tuple too large")));
HnswSetElementTuple(base, etup, element); HnswSetElementTuple(base, etup, element);
@@ -371,13 +379,7 @@ UpdateNeighborsInMemory(char *base, FmgrInfo *procinfo, Oid collation, HnswEleme
for (int lc = e->level; lc >= 0; lc--) for (int lc = e->level; lc >= 0; lc--)
{ {
int lm = HnswGetLayerM(m, lc); int lm = HnswGetLayerM(m, lc);
Size neighborsSize = HNSW_NEIGHBOR_ARRAY_SIZE(lm); HnswNeighborArray *neighbors = HnswGetNeighbors(base, e, lc);
HnswNeighborArray *neighbors = palloc(neighborsSize);
/* Copy neighbors to local memory */
LWLockAcquire(&e->lock, LW_SHARED);
memcpy(neighbors, HnswGetNeighbors(base, e, lc), neighborsSize);
LWLockRelease(&e->lock);
for (int i = 0; i < neighbors->length; i++) for (int i = 0; i < neighbors->length; i++)
{ {
@@ -387,6 +389,7 @@ UpdateNeighborsInMemory(char *base, FmgrInfo *procinfo, Oid collation, HnswEleme
/* Keep scan-build happy on Mac x86-64 */ /* Keep scan-build happy on Mac x86-64 */
Assert(neighborElement); Assert(neighborElement);
/* Use element for lock instead of hc since hc can be replaced */
LWLockAcquire(&neighborElement->lock, LW_EXCLUSIVE); LWLockAcquire(&neighborElement->lock, LW_EXCLUSIVE);
HnswUpdateConnection(base, e, hc, lm, lc, NULL, NULL, procinfo, collation); HnswUpdateConnection(base, e, hc, lm, lc, NULL, NULL, procinfo, collation);
LWLockRelease(&neighborElement->lock); LWLockRelease(&neighborElement->lock);
@@ -473,7 +476,6 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
static bool static bool
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, HnswBuildState * buildstate) InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, HnswBuildState * buildstate)
{ {
const HnswTypeInfo *typeInfo = buildstate->typeInfo;
HnswGraph *graph = buildstate->graph; HnswGraph *graph = buildstate->graph;
HnswElement element; HnswElement element;
HnswAllocator *allocator = &buildstate->allocator; HnswAllocator *allocator = &buildstate->allocator;
@@ -485,17 +487,11 @@ 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 */
if (typeInfo->checkValue != NULL)
typeInfo->checkValue(DatumGetPointer(value));
/* Normalize if needed */ /* Normalize if needed */
if (buildstate->normprocinfo != NULL) if (buildstate->normprocinfo != NULL)
{ {
if (!HnswCheckNorm(buildstate->normprocinfo, buildstate->collation, value)) if (!HnswNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
return false; return false;
value = HnswNormValue(typeInfo, buildstate->collation, value);
} }
/* Get datum size */ /* Get datum size */
@@ -575,13 +571,17 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
* Callback for table_index_build_scan * Callback for table_index_build_scan
*/ */
static void static void
BuildCallback(Relation index, ItemPointer tid, Datum *values, BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
bool *isnull, bool tupleIsAlive, void *state) bool *isnull, bool tupleIsAlive, void *state)
{ {
HnswBuildState *buildstate = (HnswBuildState *) state; HnswBuildState *buildstate = (HnswBuildState *) state;
HnswGraph *graph = buildstate->graph; HnswGraph *graph = buildstate->graph;
MemoryContext oldCtx; MemoryContext oldCtx;
#if PG_VERSION_NUM < 130000
ItemPointer tid = &hup->t_self;
#endif
/* Skip nulls */ /* Skip nulls */
if (isnull[0]) if (isnull[0])
return; return;
@@ -644,7 +644,11 @@ HnswMemoryContextAlloc(Size size, void *state)
HnswBuildState *buildstate = (HnswBuildState *) state; HnswBuildState *buildstate = (HnswBuildState *) state;
void *chunk = MemoryContextAlloc(buildstate->graphCtx, size); void *chunk = MemoryContextAlloc(buildstate->graphCtx, size);
#if PG_VERSION_NUM >= 130000
buildstate->graphData.memoryUsed = MemoryContextMemAllocated(buildstate->graphCtx, false); buildstate->graphData.memoryUsed = MemoryContextMemAllocated(buildstate->graphCtx, false);
#else
buildstate->graphData.memoryUsed += MAXALIGN(size);
#endif
return chunk; return chunk;
} }
@@ -668,37 +672,30 @@ HnswSharedMemoryAlloc(Size size, void *state)
static void static void
InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum) InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, IndexInfo *indexInfo, ForkNumber forkNum)
{ {
int maxDimensions = HNSW_MAX_DIM;
Oid typid = TupleDescAttr(index->rd_att, 0)->atttypid;
if (typid == BITOID || typid == VARBITOID)
maxDimensions *= 32;
buildstate->heap = heap; buildstate->heap = heap;
buildstate->index = index; buildstate->index = index;
buildstate->indexInfo = indexInfo; buildstate->indexInfo = indexInfo;
buildstate->forkNum = forkNum; buildstate->forkNum = forkNum;
buildstate->typeInfo = HnswGetTypeInfo(index);
buildstate->m = HnswGetM(index); buildstate->m = HnswGetM(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;
/* Disallow varbit since require fixed dimensions */
if (TupleDescAttr(index->rd_att, 0)->atttypid == VARBITOID)
ereport(ERROR,
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
errmsg("type not supported for hnsw index")));
/* Require column to have dimensions to be indexed */ /* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0) if (buildstate->dimensions < 0)
ereport(ERROR, elog(ERROR, "column does not have dimensions");
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("column does not have dimensions")));
if (buildstate->dimensions > buildstate->typeInfo->maxDimensions) if (buildstate->dimensions > maxDimensions)
ereport(ERROR, elog(ERROR, "column cannot have more than %d dimensions for hnsw index", maxDimensions);
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("column cannot have more than %d dimensions for hnsw index", buildstate->typeInfo->maxDimensions)));
if (buildstate->efConstruction < 2 * buildstate->m) if (buildstate->efConstruction < 2 * buildstate->m)
ereport(ERROR, elog(ERROR, "ef_construction must be greater than or equal to 2 * m");
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("ef_construction must be greater than or equal to 2 * m")));
buildstate->reltuples = 0; buildstate->reltuples = 0;
buildstate->indtuples = 0; buildstate->indtuples = 0;
@@ -713,6 +710,9 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
buildstate->ml = HnswGetMl(buildstate->m); buildstate->ml = HnswGetMl(buildstate->m);
buildstate->maxLevel = HnswGetMaxLevel(buildstate->m); buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
/* Reuse for each tuple */
buildstate->normvec = InitVector(buildstate->dimensions);
buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext, buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext,
"Hnsw build graph context", "Hnsw build graph context",
#if PG_VERSION_NUM >= 150000 #if PG_VERSION_NUM >= 150000
@@ -736,6 +736,7 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
static void static void
FreeBuildState(HnswBuildState * buildstate) FreeBuildState(HnswBuildState * buildstate)
{ {
pfree(buildstate->normvec);
MemoryContextDelete(buildstate->graphCtx); MemoryContextDelete(buildstate->graphCtx);
MemoryContextDelete(buildstate->tmpCtx); MemoryContextDelete(buildstate->tmpCtx);
} }
@@ -1118,8 +1119,8 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
BuildGraph(buildstate, forkNum); BuildGraph(buildstate, forkNum);
if (RelationNeedsWAL(index) || forkNum == INIT_FORKNUM) if (RelationNeedsWAL(index))
log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true); log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocks(index), true);
FreeBuildState(buildstate); FreeBuildState(buildstate);
} }

View File

@@ -36,15 +36,14 @@ GetInsertPage(Relation index)
* Check for a free offset * Check for a free offset
*/ */
static bool static bool
HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size etupSize, Size ntupSize, Buffer *nbuf, Page *npage, OffsetNumber *freeOffno, OffsetNumber *freeNeighborOffno, BlockNumber *newInsertPage) HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size ntupSize, Buffer *nbuf, Page *npage, OffsetNumber *freeOffno, OffsetNumber *freeNeighborOffno, BlockNumber *newInsertPage)
{ {
OffsetNumber offno; OffsetNumber offno;
OffsetNumber maxoffno = PageGetMaxOffsetNumber(page); OffsetNumber maxoffno = PageGetMaxOffsetNumber(page);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno)) for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{ {
ItemId eitemid = PageGetItemId(page, offno); HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, eitemid);
/* Skip neighbor tuples */ /* Skip neighbor tuples */
if (!HnswIsElementTuple(etup)) if (!HnswIsElementTuple(etup))
@@ -55,9 +54,7 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
BlockNumber elementPage = BufferGetBlockNumber(buf); BlockNumber elementPage = BufferGetBlockNumber(buf);
BlockNumber neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid); BlockNumber neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
OffsetNumber neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid); OffsetNumber neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
ItemId nitemid; ItemId itemid;
Size pageFree;
Size npageFree;
if (!BlockNumberIsValid(*newInsertPage)) if (!BlockNumberIsValid(*newInsertPage))
*newInsertPage = elementPage; *newInsertPage = elementPage;
@@ -76,25 +73,10 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
*npage = BufferGetPage(*nbuf); *npage = BufferGetPage(*nbuf);
} }
nitemid = PageGetItemId(*npage, neighborOffno); itemid = PageGetItemId(*npage, neighborOffno);
/* Ensure aligned for space check */ /* Check for space on neighbor tuple page */
Assert(etupSize == MAXALIGN(etupSize)); if (PageGetFreeSpace(*npage) + ItemIdGetLength(itemid) - sizeof(ItemIdData) >= ntupSize)
Assert(ntupSize == MAXALIGN(ntupSize));
/*
* Calculate free space individually since tuples are overwritten
* individually (in separate calls to PageIndexTupleOverwrite)
*/
pageFree = ItemIdGetLength(eitemid) + PageGetExactFreeSpace(page);
npageFree = ItemIdGetLength(nitemid);
if (neighborPage != elementPage)
npageFree += PageGetExactFreeSpace(*npage);
else if (pageFree >= etupSize)
npageFree += pageFree - etupSize;
/* Check for space */
if (pageFree >= etupSize && npageFree >= ntupSize)
{ {
*freeOffno = offno; *freeOffno = offno;
*freeNeighborOffno = neighborOffno; *freeNeighborOffno = neighborOffno;
@@ -202,7 +184,7 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
} }
/* Next, try space from a deleted element */ /* Next, try space from a deleted element */
if (HnswFreeOffset(index, buf, page, e, etupSize, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage)) if (HnswFreeOffset(index, buf, page, e, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage))
{ {
if (nbuf != buf) if (nbuf != buf)
{ {
@@ -379,12 +361,8 @@ HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, Hns
HnswElement neighborElement = HnswPtrAccess(base, hc->element); HnswElement neighborElement = HnswPtrAccess(base, hc->element);
OffsetNumber offno = neighborElement->neighborOffno; OffsetNumber offno = neighborElement->neighborOffno;
/* /* Get latest neighbors since they may have changed */
* Get latest neighbors since they may have changed. Do not lock /* Do not lock yet since selecting neighbors can take time */
* yet since selecting neighbors can take time. Could use
* optimistic locking to retry if another update occurs before
* getting exclusive lock.
*/
HnswLoadNeighbors(neighborElement, index, m); HnswLoadNeighbors(neighborElement, index, m);
/* /*
@@ -634,25 +612,18 @@ static void
HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid) HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid)
{ {
Datum value; Datum value;
const HnswTypeInfo *typeInfo = HnswGetTypeInfo(index);
FmgrInfo *normprocinfo; FmgrInfo *normprocinfo;
Oid collation = index->rd_indcollation[0]; Oid collation = index->rd_indcollation[0];
/* 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 */
if (typeInfo->checkValue != NULL)
typeInfo->checkValue(DatumGetPointer(value));
/* 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 (!HnswCheckNorm(normprocinfo, collation, value)) if (!HnswNormValue(normprocinfo, collation, &value, NULL))
return; return;
value = HnswNormValue(typeInfo, collation, value);
} }
HnswInsertTupleOnDisk(index, value, values, isnull, heap_tid, false); HnswInsertTupleOnDisk(index, value, values, isnull, heap_tid, false);

View File

@@ -1,6 +1,8 @@
#include "postgres.h" #include "postgres.h"
#include "access/relscan.h" #include "access/relscan.h"
#include "bitvector.h"
#include "catalog/pg_type_d.h"
#include "hnsw.h" #include "hnsw.h"
#include "pgstat.h" #include "pgstat.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
@@ -40,6 +42,29 @@ 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 +75,15 @@ GetScanValue(IndexScanDesc scan)
Datum value; Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL) if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(NULL); {
Oid typid = TupleDescAttr(scan->indexRelation->rd_att, 0)->atttypid;
int dimensions = GetDimensions(scan->indexRelation);
if (typid == BITOID || typid == VARBITOID)
value = PointerGetDatum(InitBitVector(dimensions));
else
value = PointerGetDatum(InitVector(dimensions));
}
else else
{ {
value = scan->orderByData->sk_argument; value = scan->orderByData->sk_argument;
@@ -59,9 +92,9 @@ GetScanValue(IndexScanDesc scan)
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value))); Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value))); Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Normalize if needed */ /* Fine if normalization fails */
if (so->normprocinfo != NULL) if (so->normprocinfo != NULL)
value = HnswNormValue(so->typeInfo, so->collation, value); HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
} }
return value; return value;
@@ -79,7 +112,6 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
scan = RelationGetIndexScan(index, nkeys, norderbys); scan = RelationGetIndexScan(index, nkeys, norderbys);
so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData)); so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData));
so->typeInfo = HnswGetTypeInfo(index);
so->first = true; so->first = true;
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext, so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw scan temporary context", "Hnsw scan temporary context",
@@ -159,16 +191,12 @@ 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)
elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(so->tmpCtx, false) / 1024);
#endif
} }
while (list_length(so->w) > 0) while (list_length(so->w) > 0)
{ {
char *base = NULL; char *base = NULL;
HnswSearchCandidate *hc = llast(so->w); HnswCandidate *hc = llast(so->w);
HnswElement element = HnswPtrAccess(base, hc->element); HnswElement element = HnswPtrAccess(base, hc->element);
ItemPointer heaptid; ItemPointer heaptid;

View File

@@ -3,17 +3,19 @@
#include <math.h> #include <math.h>
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "catalog/pg_type.h"
#include "catalog/pg_type_d.h"
#include "common/hashfn.h"
#include "fmgr.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"
#include "utils/rel.h" #include "utils/rel.h"
#include "vector.h"
#if PG_VERSION_NUM >= 130000
#include "common/hashfn.h"
#else
#include "utils/hashutils.h"
#endif
#if PG_VERSION_NUM < 170000 #if PG_VERSION_NUM < 170000
static inline uint64 static inline uint64
@@ -107,12 +109,6 @@ typedef union
tidhash_hash *tids; tidhash_hash *tids;
} visited_hash; } visited_hash;
typedef union
{
HnswElement element;
ItemPointerData indextid;
} HnswUnvisited;
/* /*
* Get the max number of connections in an upper layer for each element in the index * Get the max number of connections in an upper layer for each element in the index
*/ */
@@ -154,24 +150,34 @@ HnswOptionalProcInfo(Relation index, uint16 procnum)
} }
/* /*
* Normalize value * Divide by the norm
*/ *
Datum * Returns false if value should not be indexed
HnswNormValue(const HnswTypeInfo * typeInfo, Oid collation, Datum value) *
{ * The caller needs to free the pointer stored in value
if (!typeInfo->normalize) * if it's different than the original value
return value;
return DirectFunctionCall1Coll(typeInfo->normalize, collation, value);
}
/*
* Check if non-zero norm
*/ */
bool bool
HnswCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value) HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
{ {
return DatumGetFloat8(FunctionCall1Coll(procinfo, collation, value)) > 0; double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0)
{
Vector *v = DatumGetVector(*value);
if (result == NULL)
result = InitVector(v->dim);
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
*value = PointerGetDatum(result);
return true;
}
return false;
} }
/* /*
@@ -304,9 +310,6 @@ HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint)
page = BufferGetPage(buf); page = BufferGetPage(buf);
metap = HnswPageGetMeta(page); metap = HnswPageGetMeta(page);
if (unlikely(metap->magicNumber != HNSW_MAGIC_NUMBER))
elog(ERROR, "hnsw index is not valid");
if (m != NULL) if (m != NULL)
*m = metap->m; *m = metap->m;
@@ -551,59 +554,40 @@ HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHe
/* /*
* Load an element and optionally get its distance from q * Load an element and optionally get its distance from q
*/ */
static void void
HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance, HnswElement * element) HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec)
{ {
Buffer buf; Buffer buf;
Page page; Page page;
HnswElementTuple etup; HnswElementTuple etup;
/* Read vector */ /* Read vector */
buf = ReadBuffer(index, blkno); buf = ReadBuffer(index, element->blkno);
LockBuffer(buf, BUFFER_LOCK_SHARE); LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf); page = BufferGetPage(buf);
etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno)); etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, element->offno));
Assert(HnswIsElementTuple(etup)); Assert(HnswIsElementTuple(etup));
/* Load element */
HnswLoadElementFromTuple(element, etup, true, loadVec);
/* 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)));
}
/* Load element */
if (distance == NULL || maxDistance == NULL || *distance < *maxDistance)
{
if (*element == NULL)
*element = HnswInitElementFromBlock(blkno, offno);
HnswLoadElementFromTuple(*element, etup, true, loadVec);
}
UnlockReleaseBuffer(buf); UnlockReleaseBuffer(buf);
} }
/* /*
* Load an element and optionally get its distance from q * Get the distance for a candidate
*/
void
HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance)
{
HnswLoadElementImpl(element->blkno, element->offno, distance, q, index, procinfo, collation, loadVec, maxDistance, &element);
}
/*
* Get the distance for an element
*/ */
static float static float
GetElementDistance(char *base, HnswElement element, Datum q, FmgrInfo *procinfo, Oid collation) GetCandidateDistance(char *base, HnswCandidate * hc, Datum q, FmgrInfo *procinfo, Oid collation)
{ {
Datum value = HnswGetValue(base, element); HnswElement hce = HnswPtrAccess(base, hc->element);
Datum value = HnswGetValue(base, hce);
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, q, value)); return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, q, value));
} }
@@ -611,32 +595,29 @@ GetElementDistance(char *base, HnswElement element, Datum q, FmgrInfo *procinfo,
/* /*
* Create a candidate for the entry point * Create a candidate for the entry point
*/ */
HnswSearchCandidate * HnswCandidate *
HnswEntryCandidate(char *base, HnswElement entryPoint, Datum q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec) HnswEntryCandidate(char *base, HnswElement entryPoint, Datum q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec)
{ {
HnswSearchCandidate *hc = palloc(sizeof(HnswSearchCandidate)); HnswCandidate *hc = palloc(sizeof(HnswCandidate));
HnswPtrStore(base, hc->element, entryPoint); HnswPtrStore(base, hc->element, entryPoint);
if (index == NULL) if (index == NULL)
hc->distance = GetElementDistance(base, entryPoint, q, procinfo, collation); hc->distance = GetCandidateDistance(base, hc, q, procinfo, collation);
else else
HnswLoadElement(entryPoint, &hc->distance, &q, index, procinfo, collation, loadVec, NULL); HnswLoadElement(entryPoint, &hc->distance, &q, index, procinfo, collation, loadVec);
return hc; return hc;
} }
#define HnswGetSearchCandidate(membername, ptr) pairingheap_container(HnswSearchCandidate, membername, ptr)
#define HnswGetSearchCandidateConst(membername, ptr) pairingheap_const_container(HnswSearchCandidate, membername, ptr)
/* /*
* Compare candidate distances * Compare candidate distances
*/ */
static int static int
CompareNearestCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg) CompareNearestCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg)
{ {
if (HnswGetSearchCandidateConst(c_node, a)->distance < HnswGetSearchCandidateConst(c_node, b)->distance) if (((const HnswPairingHeapNode *) a)->inner->distance < ((const HnswPairingHeapNode *) b)->inner->distance)
return 1; return 1;
if (HnswGetSearchCandidateConst(c_node, a)->distance > HnswGetSearchCandidateConst(c_node, b)->distance) if (((const HnswPairingHeapNode *) a)->inner->distance > ((const HnswPairingHeapNode *) b)->inner->distance)
return -1; return -1;
return 0; return 0;
@@ -648,15 +629,27 @@ CompareNearestCandidates(const pairingheap_node *a, const pairingheap_node *b, v
static int static int
CompareFurthestCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg) CompareFurthestCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg)
{ {
if (HnswGetSearchCandidateConst(w_node, a)->distance < HnswGetSearchCandidateConst(w_node, b)->distance) if (((const HnswPairingHeapNode *) a)->inner->distance < ((const HnswPairingHeapNode *) b)->inner->distance)
return -1; return -1;
if (HnswGetSearchCandidateConst(w_node, a)->distance > HnswGetSearchCandidateConst(w_node, b)->distance) if (((const HnswPairingHeapNode *) a)->inner->distance > ((const HnswPairingHeapNode *) b)->inner->distance)
return 1; return 1;
return 0; return 0;
} }
/*
* Create a pairing heap node for a candidate
*/
static HnswPairingHeapNode *
CreatePairingHeapNode(HnswCandidate * c)
{
HnswPairingHeapNode *node = palloc(sizeof(HnswPairingHeapNode));
node->inner = c;
return node;
}
/* /*
* Init visited * Init visited
*/ */
@@ -675,11 +668,11 @@ InitVisited(char *base, visited_hash * v, Relation index, int ef, int m)
* Add to visited * Add to visited
*/ */
static inline void static inline void
AddToVisited(char *base, visited_hash * v, HnswElementPtr elementPtr, Relation index, bool *found) AddToVisited(char *base, visited_hash * v, HnswCandidate * hc, Relation index, bool *found)
{ {
if (index != NULL) if (index != NULL)
{ {
HnswElement element = HnswPtrAccess(base, elementPtr); HnswElement element = HnswPtrAccess(base, hc->element);
ItemPointerData indextid; ItemPointerData indextid;
ItemPointerSet(&indextid, element->blkno, element->offno); ItemPointerSet(&indextid, element->blkno, element->offno);
@@ -687,15 +680,23 @@ AddToVisited(char *base, visited_hash * v, HnswElementPtr elementPtr, Relation i
} }
else if (base != NULL) else if (base != NULL)
{ {
HnswElement element = HnswPtrAccess(base, elementPtr); #if PG_VERSION_NUM >= 130000
HnswElement element = HnswPtrAccess(base, hc->element);
offsethash_insert_hash(v->offsets, HnswPtrOffset(elementPtr), element->hash, found); offsethash_insert_hash(v->offsets, HnswPtrOffset(hc->element), element->hash, found);
#else
offsethash_insert(v->offsets, HnswPtrOffset(hc->element), found);
#endif
} }
else else
{ {
HnswElement element = HnswPtrAccess(base, elementPtr); #if PG_VERSION_NUM >= 130000
HnswElement element = HnswPtrAccess(base, hc->element);
pointerhash_insert_hash(v->pointers, (uintptr_t) HnswPtrPointer(elementPtr), element->hash, found); pointerhash_insert_hash(v->pointers, (uintptr_t) HnswPtrPointer(hc->element), element->hash, found);
#else
pointerhash_insert(v->pointers, (uintptr_t) HnswPtrPointer(hc->element), found);
#endif
} }
} }
@@ -703,89 +704,20 @@ AddToVisited(char *base, visited_hash * v, HnswElementPtr elementPtr, Relation i
* Count element towards ef * Count element towards ef
*/ */
static inline bool static inline bool
CountElement(HnswElement skipElement, HnswElement e) CountElement(char *base, HnswElement skipElement, HnswCandidate * hc)
{ {
HnswElement e;
if (skipElement == NULL) if (skipElement == NULL)
return true; return true;
/* Ensure does not access heaptidsLength during in-memory build */ /* Ensure does not access heaptidsLength during in-memory build */
pg_memory_barrier(); pg_memory_barrier();
/* Keep scan-build happy on Mac x86-64 */ e = HnswPtrAccess(base, hc->element);
Assert(e);
return e->heaptidsLength != 0; return e->heaptidsLength != 0;
} }
/*
* Load unvisited neighbors from memory
*/
static void
HnswLoadUnvisitedFromMemory(char *base, HnswElement element, HnswUnvisited * unvisited, int *unvisitedLength, visited_hash * v, int lc, HnswNeighborArray * localNeighborhood, Size neighborhoodSize)
{
/* Get the neighborhood at layer lc */
HnswNeighborArray *neighborhood = HnswGetNeighbors(base, element, lc);
/* Copy neighborhood to local memory */
LWLockAcquire(&element->lock, LW_SHARED);
memcpy(localNeighborhood, neighborhood, neighborhoodSize);
LWLockRelease(&element->lock);
*unvisitedLength = 0;
for (int i = 0; i < localNeighborhood->length; i++)
{
HnswCandidate *hc = &localNeighborhood->items[i];
bool found;
AddToVisited(base, v, hc->element, NULL, &found);
if (!found)
unvisited[(*unvisitedLength)++].element = HnswPtrAccess(base, hc->element);
}
}
/*
* Load unvisited neighbors from disk
*/
static void
HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *unvisitedLength, visited_hash * v, Relation index, int m, int lm, int lc)
{
Buffer buf;
Page page;
HnswNeighborTuple ntup;
int start;
ItemPointerData indextids[HNSW_MAX_M * 2];
buf = ReadBuffer(index, element->neighborPage);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, element->neighborOffno));
start = (element->level - lc) * m;
/* Copy to minimize lock time */
memcpy(&indextids, ntup->indextids + start, lm * sizeof(ItemPointerData));
UnlockReleaseBuffer(buf);
*unvisitedLength = 0;
for (int i = 0; i < lm; i++)
{
ItemPointer indextid = &indextids[i];
bool found;
if (!ItemPointerIsValid(indextid))
break;
tidhash_insert(v->tids, *indextid, &found);
if (!found)
unvisited[(*unvisitedLength)++].indextid = *indextid;
}
}
/* /*
* Algorithm 2 from paper * Algorithm 2 from paper
*/ */
@@ -798,45 +730,43 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
int wlen = 0; int wlen = 0;
visited_hash v; visited_hash v;
ListCell *lc2; ListCell *lc2;
HnswNeighborArray *localNeighborhood = NULL; HnswNeighborArray *neighborhoodData = NULL;
Size neighborhoodSize = 0; Size neighborhoodSize;
int lm = HnswGetLayerM(m, lc);
HnswUnvisited *unvisited = palloc(lm * sizeof(HnswUnvisited));
int unvisitedLength;
InitVisited(base, &v, index, ef, m); InitVisited(base, &v, index, ef, m);
/* Create local memory for neighborhood if needed */ /* Create local memory for neighborhood if needed */
if (index == NULL) if (index == NULL)
{ {
neighborhoodSize = HNSW_NEIGHBOR_ARRAY_SIZE(lm); neighborhoodSize = HNSW_NEIGHBOR_ARRAY_SIZE(HnswGetLayerM(m, lc));
localNeighborhood = palloc(neighborhoodSize); neighborhoodData = palloc(neighborhoodSize);
} }
/* Add entry points to v, C, and W */ /* Add entry points to v, C, and W */
foreach(lc2, ep) foreach(lc2, ep)
{ {
HnswSearchCandidate *hc = (HnswSearchCandidate *) lfirst(lc2); HnswCandidate *hc = (HnswCandidate *) lfirst(lc2);
bool found; bool found;
AddToVisited(base, &v, hc->element, index, &found); AddToVisited(base, &v, hc, index, &found);
pairingheap_add(C, &hc->c_node); pairingheap_add(C, &(CreatePairingHeapNode(hc)->ph_node));
pairingheap_add(W, &hc->w_node); pairingheap_add(W, &(CreatePairingHeapNode(hc)->ph_node));
/* /*
* Do not count elements being deleted towards ef when vacuuming. It * Do not count elements being deleted towards ef when vacuuming. It
* would be ideal to do this for inserts as well, but this could * would be ideal to do this for inserts as well, but this could
* affect insert performance. * affect insert performance.
*/ */
if (CountElement(skipElement, HnswPtrAccess(base, hc->element))) if (CountElement(base, skipElement, hc))
wlen++; wlen++;
} }
while (!pairingheap_is_empty(C)) while (!pairingheap_is_empty(C))
{ {
HnswSearchCandidate *c = HnswGetSearchCandidate(c_node, pairingheap_remove_first(C)); HnswNeighborArray *neighborhood;
HnswSearchCandidate *f = HnswGetSearchCandidate(w_node, pairingheap_first(W)); HnswCandidate *c = ((HnswPairingHeapNode *) pairingheap_remove_first(C))->inner;
HnswCandidate *f = ((HnswPairingHeapNode *) pairingheap_first(W))->inner;
HnswElement cElement; HnswElement cElement;
if (c->distance > f->distance) if (c->distance > f->distance)
@@ -844,67 +774,71 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
cElement = HnswPtrAccess(base, c->element); cElement = HnswPtrAccess(base, c->element);
if (HnswPtrIsNull(base, cElement->neighbors))
HnswLoadNeighbors(cElement, index, m);
/* Get the neighborhood at layer lc */
neighborhood = HnswGetNeighbors(base, cElement, lc);
/* Copy neighborhood to local memory if needed */
if (index == NULL) if (index == NULL)
HnswLoadUnvisitedFromMemory(base, cElement, unvisited, &unvisitedLength, &v, lc, localNeighborhood, neighborhoodSize);
else
HnswLoadUnvisitedFromDisk(cElement, unvisited, &unvisitedLength, &v, index, m, lm, lc);
for (int i = 0; i < unvisitedLength; i++)
{ {
HnswElement eElement; LWLockAcquire(&cElement->lock, LW_SHARED);
HnswSearchCandidate *e; memcpy(neighborhoodData, neighborhood, neighborhoodSize);
float eDistance; LWLockRelease(&cElement->lock);
bool alwaysAdd = wlen < ef; neighborhood = neighborhoodData;
}
f = HnswGetSearchCandidate(w_node, pairingheap_first(W)); for (int i = 0; i < neighborhood->length; i++)
{
HnswCandidate *e = &neighborhood->items[i];
bool visited;
if (index == NULL) AddToVisited(base, &v, e, index, &visited);
if (!visited)
{ {
eElement = unvisited[i].element; float eDistance;
eDistance = GetElementDistance(base, eElement, q, procinfo, collation); HnswElement eElement = HnswPtrAccess(base, e->element);
}
else
{
ItemPointer indextid = &unvisited[i].indextid;
BlockNumber blkno = ItemPointerGetBlockNumber(indextid);
OffsetNumber offno = ItemPointerGetOffsetNumber(indextid);
/* Avoid any allocations if not adding */ f = ((HnswPairingHeapNode *) pairingheap_first(W))->inner;
eElement = NULL;
HnswLoadElementImpl(blkno, offno, &eDistance, &q, index, procinfo, collation, inserting, alwaysAdd ? NULL : &f->distance, &eElement);
if (eElement == NULL) if (index == NULL)
eDistance = GetCandidateDistance(base, e, q, procinfo, collation);
else
HnswLoadElement(eElement, &eDistance, &q, index, procinfo, collation, inserting);
Assert(!eElement->deleted);
/* Make robust to issues */
if (eElement->level < lc)
continue; continue;
}
if (!(eDistance < f->distance || alwaysAdd)) if (eDistance < f->distance || wlen < ef)
continue; {
/* Copy e */
HnswCandidate *ec = palloc(sizeof(HnswCandidate));
Assert(!eElement->deleted); HnswPtrStore(base, ec->element, eElement);
ec->distance = eDistance;
/* Make robust to issues */ pairingheap_add(C, &(CreatePairingHeapNode(ec)->ph_node));
if (eElement->level < lc) pairingheap_add(W, &(CreatePairingHeapNode(ec)->ph_node));
continue;
/* Create a new candidate */ /*
e = palloc(sizeof(HnswSearchCandidate)); * Do not count elements being deleted towards ef when
HnswPtrStore(base, e->element, eElement); * vacuuming. It would be ideal to do this for inserts as
e->distance = eDistance; * well, but this could affect insert performance.
pairingheap_add(C, &e->c_node); */
pairingheap_add(W, &e->w_node); if (CountElement(base, skipElement, e))
{
wlen++;
/* /* No need to decrement wlen */
* Do not count elements being deleted towards ef when vacuuming. if (wlen > ef)
* It would be ideal to do this for inserts as well, but this pairingheap_remove_first(W);
* could affect insert performance. }
*/ }
if (CountElement(skipElement, eElement))
{
wlen++;
/* No need to decrement wlen */
if (wlen > ef)
pairingheap_remove_first(W);
} }
} }
} }
@@ -912,7 +846,7 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
/* Add each element of W to w */ /* Add each element of W to w */
while (!pairingheap_is_empty(W)) while (!pairingheap_is_empty(W))
{ {
HnswSearchCandidate *hc = HnswGetSearchCandidate(w_node, pairingheap_remove_first(W)); HnswCandidate *hc = ((HnswPairingHeapNode *) pairingheap_remove_first(W))->inner;
w = lappend(w, hc); w = lappend(w, hc);
} }
@@ -924,10 +858,17 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
* Compare candidate distances with pointer tie-breaker * Compare candidate distances with pointer tie-breaker
*/ */
static int static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistances(const ListCell *a, const ListCell *b) CompareCandidateDistances(const ListCell *a, const ListCell *b)
{ {
HnswCandidate *hca = lfirst(a); HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b); HnswCandidate *hcb = lfirst(b);
#else
CompareCandidateDistances(const void *a, const void *b)
{
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif
if (hca->distance < hcb->distance) if (hca->distance < hcb->distance)
return 1; return 1;
@@ -948,10 +889,17 @@ CompareCandidateDistances(const ListCell *a, const ListCell *b)
* Compare candidate distances with offset tie-breaker * Compare candidate distances with offset tie-breaker
*/ */
static int static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b) CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b)
{ {
HnswCandidate *hca = lfirst(a); HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b); HnswCandidate *hcb = lfirst(b);
#else
CompareCandidateDistancesOffset(const void *a, const void *b)
{
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif
if (hca->distance < hcb->distance) if (hca->distance < hcb->distance)
return 1; return 1;
@@ -1159,9 +1107,9 @@ HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm
HnswElement hc3Element = HnswPtrAccess(base, hc3->element); HnswElement hc3Element = HnswPtrAccess(base, hc3->element);
if (HnswPtrIsNull(base, hc3Element->value)) if (HnswPtrIsNull(base, hc3Element->value))
HnswLoadElement(hc3Element, &hc3->distance, &q, index, procinfo, collation, true, NULL); HnswLoadElement(hc3Element, &hc3->distance, &q, index, procinfo, collation, true);
else else
hc3->distance = GetElementDistance(base, hc3Element, q, procinfo, collation); hc3->distance = GetCandidateDistance(base, hc3, q, procinfo, collation);
/* Prune element if being deleted */ /* Prune element if being deleted */
if (hc3Element->heaptidsLength == 0) if (hc3Element->heaptidsLength == 0)
@@ -1233,6 +1181,7 @@ RemoveElements(char *base, List *w, HnswElement skipElement)
return w2; return w2;
} }
#if PG_VERSION_NUM >= 130000
/* /*
* Precompute hash * Precompute hash
*/ */
@@ -1248,6 +1197,7 @@ PrecomputeHash(char *base, HnswElement element)
else else
element->hash = hash_offset(HnswPtrOffset(ptr)); element->hash = hash_offset(HnswPtrOffset(ptr));
} }
#endif
/* /*
* Algorithm 1 from paper * Algorithm 1 from paper
@@ -1262,9 +1212,11 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
Datum q = HnswGetValue(base, element); Datum q = HnswGetValue(base, element);
HnswElement skipElement = existing ? element : NULL; HnswElement skipElement = existing ? element : NULL;
#if PG_VERSION_NUM >= 130000
/* Precompute hash */ /* Precompute hash */
if (index == NULL) if (index == NULL)
PrecomputeHash(base, element); PrecomputeHash(base, element);
#endif
/* No neighbors if no entry point */ /* No neighbors if no entry point */
if (entryPoint == NULL) if (entryPoint == NULL)
@@ -1293,27 +1245,16 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
{ {
int lm = HnswGetLayerM(m, lc); int lm = HnswGetLayerM(m, lc);
List *neighbors; List *neighbors;
List *lw = NIL; List *lw;
ListCell *lc2;
w = HnswSearchLayer(base, q, ep, efConstruction, lc, index, procinfo, collation, m, true, skipElement); w = HnswSearchLayer(base, q, ep, efConstruction, lc, index, procinfo, collation, m, true, skipElement);
/* Convert search candidates to candidates */
foreach(lc2, w)
{
HnswSearchCandidate *sc = lfirst(lc2);
HnswCandidate *hc = palloc(sizeof(HnswCandidate));
hc->element = sc->element;
hc->distance = sc->distance;
lw = lappend(lw, hc);
}
/* Elements being deleted or skipped can help with search */ /* Elements being deleted or skipped can help with search */
/* but should be removed before selecting neighbors */ /* but should be removed before selecting neighbors */
if (index != NULL) if (index != NULL)
lw = RemoveElements(base, lw, skipElement); lw = RemoveElements(base, w, skipElement);
else
lw = w;
/* /*
* Candidates are sorted, but not deterministically. Could set * Candidates are sorted, but not deterministically. Could set
@@ -1327,94 +1268,3 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
ep = w; ep = w;
} }
} }
PGDLLEXPORT Datum l2_normalize(PG_FUNCTION_ARGS);
PGDLLEXPORT Datum halfvec_l2_normalize(PG_FUNCTION_ARGS);
PGDLLEXPORT Datum minivec_l2_normalize(PG_FUNCTION_ARGS);
PGDLLEXPORT Datum sparsevec_l2_normalize(PG_FUNCTION_ARGS);
static void
SparsevecCheckValue(Pointer v)
{
SparseVector *vec = (SparseVector *) v;
if (vec->nnz > HNSW_MAX_NNZ)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ)));
}
/*
* Get type info
*/
const HnswTypeInfo *
HnswGetTypeInfo(Relation index)
{
FmgrInfo *procinfo = HnswOptionalProcInfo(index, HNSW_TYPE_INFO_PROC);
if (procinfo == NULL)
{
static const HnswTypeInfo typeInfo = {
.maxDimensions = HNSW_MAX_DIM,
.normalize = l2_normalize,
.checkValue = NULL
};
return (&typeInfo);
}
else
return (const HnswTypeInfo *) DatumGetPointer(FunctionCall0Coll(procinfo, InvalidOid));
}
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_halfvec_support);
Datum
hnsw_halfvec_support(PG_FUNCTION_ARGS)
{
static const HnswTypeInfo typeInfo = {
.maxDimensions = HNSW_MAX_DIM * 2,
.normalize = halfvec_l2_normalize,
.checkValue = NULL
};
PG_RETURN_POINTER(&typeInfo);
};
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_minivec_support);
Datum
hnsw_minivec_support(PG_FUNCTION_ARGS)
{
static const HnswTypeInfo typeInfo = {
.maxDimensions = HNSW_MAX_DIM * 4,
/* Do not normalize to maximize precision */
.normalize = NULL,
.checkValue = NULL
};
PG_RETURN_POINTER(&typeInfo);
};
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_bit_support);
Datum
hnsw_bit_support(PG_FUNCTION_ARGS)
{
static const HnswTypeInfo typeInfo = {
.maxDimensions = HNSW_MAX_DIM * 32,
.normalize = NULL,
.checkValue = NULL
};
PG_RETURN_POINTER(&typeInfo);
};
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_sparsevec_support);
Datum
hnsw_sparsevec_support(PG_FUNCTION_ARGS)
{
static const HnswTypeInfo typeInfo = {
.maxDimensions = SPARSEVEC_MAX_DIM,
.normalize = sparsevec_l2_normalize,
.checkValue = SparsevecCheckValue
};
PG_RETURN_POINTER(&typeInfo);
};

View File

@@ -256,7 +256,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
LockPage(index, HNSW_UPDATE_LOCK, ShareLock); LockPage(index, HNSW_UPDATE_LOCK, ShareLock);
/* Load element */ /* Load element */
HnswLoadElement(highestPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true, NULL); HnswLoadElement(highestPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true);
/* Repair if needed */ /* Repair if needed */
if (NeedsUpdated(vacuumstate, highestPoint)) if (NeedsUpdated(vacuumstate, highestPoint))
@@ -294,7 +294,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
* is outdated, this can remove connections at higher levels in * is outdated, this can remove connections at higher levels in
* the graph until they are repaired, but this should be fine. * the graph until they are repaired, but this should be fine.
*/ */
HnswLoadElement(entryPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true, NULL); HnswLoadElement(entryPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true);
if (NeedsUpdated(vacuumstate, entryPoint)) if (NeedsUpdated(vacuumstate, entryPoint))
{ {

View File

@@ -6,19 +6,16 @@
#include "access/tableam.h" #include "access/tableam.h"
#include "access/parallel.h" #include "access/parallel.h"
#include "access/xact.h" #include "access/xact.h"
#include "bitvec.h"
#include "catalog/index.h" #include "catalog/index.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 "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"
@@ -26,6 +23,12 @@
#include "pgstat.h" #include "pgstat.h"
#endif #endif
#if PG_VERSION_NUM >= 130000
#define CALLBACK_ITEM_POINTER ItemPointer tid
#else
#define CALLBACK_ITEM_POINTER HeapTuple hup
#endif
#if PG_VERSION_NUM >= 140000 #if PG_VERSION_NUM >= 140000
#include "utils/backend_status.h" #include "utils/backend_status.h"
#include "utils/wait_event.h" #include "utils/wait_event.h"
@@ -54,15 +57,13 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
*/ */
if (buildstate->kmeansnormprocinfo != NULL) if (buildstate->kmeansnormprocinfo != NULL)
{ {
if (!IvfflatCheckNorm(buildstate->kmeansnormprocinfo, buildstate->collation, value)) if (!IvfflatNormValue(buildstate->kmeansnormprocinfo, buildstate->collation, &value, buildstate->normvec))
return; return;
value = IvfflatNormValue(buildstate->typeInfo, buildstate->collation, value);
} }
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
@@ -79,7 +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;
@@ -90,7 +91,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
* Callback for sampling * Callback for sampling
*/ */
static void static void
SampleCallback(Relation index, ItemPointer tid, Datum *values, SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
bool *isnull, bool tupleIsAlive, void *state) bool *isnull, bool tupleIsAlive, void *state)
{ {
IvfflatBuildState *buildstate = (IvfflatBuildState *) state; IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
@@ -104,7 +105,7 @@ SampleCallback(Relation index, ItemPointer tid, 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);
@@ -152,10 +153,8 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
/* Normalize if needed */ /* Normalize if needed */
if (buildstate->normprocinfo != NULL) if (buildstate->normprocinfo != NULL)
{ {
if (!IvfflatCheckNorm(buildstate->normprocinfo, buildstate->collation, value)) if (!IvfflatNormValue(buildstate->normprocinfo, buildstate->collation, &value, buildstate->normvec))
return; return;
value = IvfflatNormValue(buildstate->typeInfo, buildstate->collation, value);
} }
/* Find the list that minimizes the distance */ /* Find the list that minimizes the distance */
@@ -201,12 +200,16 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
* Callback for table_index_build_scan * Callback for table_index_build_scan
*/ */
static void static void
BuildCallback(Relation index, ItemPointer tid, Datum *values, BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
bool *isnull, bool tupleIsAlive, void *state) bool *isnull, bool tupleIsAlive, void *state)
{ {
IvfflatBuildState *buildstate = (IvfflatBuildState *) state; IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
MemoryContext oldCtx; MemoryContext oldCtx;
#if PG_VERSION_NUM < 130000
ItemPointer tid = &hup->t_self;
#endif
/* Skip nulls */ /* Skip nulls */
if (isnull[0]) if (isnull[0])
return; return;
@@ -318,27 +321,16 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->heap = heap; buildstate->heap = heap;
buildstate->index = index; buildstate->index = index;
buildstate->indexInfo = indexInfo; buildstate->indexInfo = indexInfo;
buildstate->typeInfo = IvfflatGetTypeInfo(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;
/* Disallow varbit since require fixed dimensions */
if (TupleDescAttr(index->rd_att, 0)->atttypid == VARBITOID)
ereport(ERROR,
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
errmsg("type not supported for ivfflat index")));
/* Require column to have dimensions to be indexed */ /* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0) if (buildstate->dimensions < 0)
ereport(ERROR, elog(ERROR, "column does not have dimensions");
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("column does not have dimensions")));
if (buildstate->dimensions > buildstate->typeInfo->maxDimensions) if (buildstate->dimensions > IVFFLAT_MAX_DIM)
ereport(ERROR, elog(ERROR, "column cannot have more than %d dimensions for ivfflat index", IVFFLAT_MAX_DIM);
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("column cannot have more than %d dimensions for ivfflat index", buildstate->typeInfo->maxDimensions)));
buildstate->reltuples = 0; buildstate->reltuples = 0;
buildstate->indtuples = 0; buildstate->indtuples = 0;
@@ -351,9 +343,7 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
/* Require more than one dimension for spherical k-means */ /* Require more than one dimension for spherical k-means */
if (buildstate->kmeansnormprocinfo != NULL && buildstate->dimensions == 1) if (buildstate->kmeansnormprocinfo != NULL && buildstate->dimensions == 1)
ereport(ERROR, elog(ERROR, "dimensions must be greater than one for this opclass");
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions must be greater than one for this opclass")));
/* Create tuple description for sorting */ /* Create tuple description for sorting */
buildstate->tupdesc = CreateTemplateTupleDesc(3); buildstate->tupdesc = CreateTemplateTupleDesc(3);
@@ -363,9 +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, buildstate->typeInfo->itemSize(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);
@@ -387,6 +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);
@@ -418,7 +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);
@@ -433,7 +427,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
} }
/* Calculate centers */ /* Calculate centers */
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers, buildstate->typeInfo)); 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);
@@ -478,7 +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);
@@ -488,13 +482,10 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
{ {
OffsetNumber offno; OffsetNumber offno;
/* Zero memory for each list */
MemSet(list, 0, listSize);
/* Load list */ /* Load list */
list->startPage = InvalidBlockNumber; list->startPage = InvalidBlockNumber;
list->insertPage = InvalidBlockNumber; list->insertPage = InvalidBlockNumber;
memcpy(&list->center, VectorArrayGet(centers, i), VARSIZE_ANY(VectorArrayGet(centers, i))); memcpy(&list->center, VectorArrayGet(centers, i), VECTOR_SIZE(dimensions));
/* Ensure free space */ /* Ensure free space */
if (PageGetFreeSpace(page) < listSize) if (PageGetFreeSpace(page) < listSize)
@@ -560,20 +551,6 @@ PrintKmeansMetrics(IvfflatBuildState * buildstate)
} }
#endif #endif
/*
* Initialize build sort state
*/
static Tuplesortstate *
InitBuildSortState(TupleDesc tupdesc, int memory, SortCoordinate coordinate)
{
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Int4LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
return tuplesort_begin_heap(tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, memory, coordinate, false);
}
/* /*
* Within leader, wait for end of heap scan * Within leader, wait for end of heap scan
*/ */
@@ -613,7 +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;
@@ -621,6 +598,12 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
double reltuples; double reltuples;
IndexInfo *indexInfo; IndexInfo *indexInfo;
/* Sort options, which must match AssignTuples */
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Int4LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
/* Initialize local tuplesort coordination state */ /* Initialize local tuplesort coordination state */
coordinate = palloc0(sizeof(SortCoordinateData)); coordinate = palloc0(sizeof(SortCoordinateData));
coordinate->isWorker = true; coordinate->isWorker = true;
@@ -631,9 +614,9 @@ 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 = InitBuildSortState(buildstate.tupdesc, sortmem, coordinate); ivfspool->sortstate = tuplesort_begin_heap(buildstate.tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, sortmem, coordinate, false);
buildstate.sortstate = ivfspool->sortstate; buildstate.sortstate = ivfspool->sortstate;
scan = table_beginscan_parallel(ivfspool->heap, scan = table_beginscan_parallel(ivfspool->heap,
ParallelTableScanFromIvfflatShared(ivfshared)); ParallelTableScanFromIvfflatShared(ivfshared));
@@ -679,7 +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;
@@ -793,7 +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;
@@ -820,7 +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);
@@ -872,7 +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);
@@ -930,6 +913,12 @@ AssignTuples(IvfflatBuildState * buildstate)
int parallel_workers = 0; int parallel_workers = 0;
SortCoordinate coordinate = NULL; SortCoordinate coordinate = NULL;
/* Sort options, which must match IvfflatParallelScanAndSort */
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Int4LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_ASSIGN); pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_ASSIGN);
/* Calculate parallel workers */ /* Calculate parallel workers */
@@ -950,7 +939,7 @@ AssignTuples(IvfflatBuildState * buildstate)
} }
/* Begin serial/leader tuplesort */ /* Begin serial/leader tuplesort */
buildstate->sortstate = InitBuildSortState(buildstate->tupdesc, maintenance_work_mem, coordinate); buildstate->sortstate = tuplesort_begin_heap(buildstate->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, maintenance_work_mem, coordinate, false);
/* Add tuples to sort */ /* Add tuples to sort */
if (buildstate->heap != NULL) if (buildstate->heap != NULL)
@@ -1006,10 +995,6 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo); CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo);
CreateEntryPages(buildstate, forkNum); CreateEntryPages(buildstate, forkNum);
/* Write WAL for initialization fork since GenericXLog functions do not */
if (forkNum == INIT_FORKNUM)
log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true);
FreeBuildState(buildstate); FreeBuildState(buildstate);
} }

View File

@@ -7,7 +7,6 @@
#include "commands/progress.h" #include "commands/progress.h"
#include "commands/vacuum.h" #include "commands/vacuum.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "utils/float.h"
#include "utils/guc.h" #include "utils/guc.h"
#include "utils/selfuncs.h" #include "utils/selfuncs.h"
#include "utils/spccache.h" #include "utils/spccache.h"
@@ -27,7 +26,11 @@ IvfflatInit(void)
{ {
ivfflat_relopt_kind = add_reloption_kind(); ivfflat_relopt_kind = add_reloption_kind();
add_int_reloption(ivfflat_relopt_kind, "lists", "Number of inverted lists", add_int_reloption(ivfflat_relopt_kind, "lists", "Number of inverted lists",
IVFFLAT_DEFAULT_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, AccessExclusiveLock); IVFFLAT_DEFAULT_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS
#if PG_VERSION_NUM >= 130000
,AccessExclusiveLock
#endif
);
DefineCustomIntVariable("ivfflat.probes", "Sets the number of probes", DefineCustomIntVariable("ivfflat.probes", "Sets the number of probes",
"Valid range is 1..lists.", &ivfflat_probes, "Valid range is 1..lists.", &ivfflat_probes,
@@ -75,8 +78,8 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
/* Never use index without order */ /* Never use index without order */
if (path->indexorderbys == NULL) if (path->indexorderbys == NULL)
{ {
*indexStartupCost = get_float8_infinity(); *indexStartupCost = DBL_MAX;
*indexTotalCost = get_float8_infinity(); *indexTotalCost = DBL_MAX;
*indexSelectivity = 0; *indexSelectivity = 0;
*indexCorrelation = 0; *indexCorrelation = 0;
*indexPages = 0; *indexPages = 0;
@@ -145,10 +148,23 @@ ivfflatoptions(Datum reloptions, bool validate)
{"lists", RELOPT_TYPE_INT, offsetof(IvfflatOptions, lists)}, {"lists", RELOPT_TYPE_INT, offsetof(IvfflatOptions, lists)},
}; };
#if PG_VERSION_NUM >= 130000
return (bytea *) build_reloptions(reloptions, validate, return (bytea *) build_reloptions(reloptions, validate,
ivfflat_relopt_kind, ivfflat_relopt_kind,
sizeof(IvfflatOptions), sizeof(IvfflatOptions),
tab, lengthof(tab)); tab, lengthof(tab));
#else
relopt_value *options;
int numoptions;
IvfflatOptions *rdopts;
options = parseRelOptions(reloptions, validate, ivfflat_relopt_kind, &numoptions);
rdopts = allocateReloptStruct(sizeof(IvfflatOptions), options, numoptions);
fillRelOptions((void *) rdopts, sizeof(IvfflatOptions), options, numoptions,
validate, tab, lengthof(tab));
return (bytea *) rdopts;
#endif
} }
/* /*
@@ -165,15 +181,17 @@ ivfflatvalidate(Oid opclassoid)
* *
* See https://www.postgresql.org/docs/current/index-api.html * See https://www.postgresql.org/docs/current/index-api.html
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflathandler); PGDLLEXPORT PG_FUNCTION_INFO_V1(ivfflathandler);
Datum Datum
ivfflathandler(PG_FUNCTION_ARGS) ivfflathandler(PG_FUNCTION_ARGS)
{ {
IndexAmRoutine *amroutine = makeNode(IndexAmRoutine); IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
amroutine->amstrategies = 0; amroutine->amstrategies = 0;
amroutine->amsupport = 5; amroutine->amsupport = 4;
#if PG_VERSION_NUM >= 130000
amroutine->amoptsprocnum = 0; amroutine->amoptsprocnum = 0;
#endif
amroutine->amcanorder = false; amroutine->amcanorder = false;
amroutine->amcanorderbyop = true; amroutine->amcanorderbyop = true;
amroutine->amcanbackward = false; /* can change direction mid-scan */ amroutine->amcanbackward = false; /* can change direction mid-scan */
@@ -186,24 +204,17 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amclusterable = false; amroutine->amclusterable = false;
amroutine->ampredlocks = false; amroutine->ampredlocks = false;
amroutine->amcanparallel = false; amroutine->amcanparallel = false;
#if PG_VERSION_NUM >= 170000
amroutine->amcanbuildparallel = true;
#endif
amroutine->amcaninclude = false; amroutine->amcaninclude = false;
#if PG_VERSION_NUM >= 130000
amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */ amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */
#if PG_VERSION_NUM >= 160000
amroutine->amsummarizing = false;
#endif
amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL; amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL;
#endif
amroutine->amkeytype = InvalidOid; amroutine->amkeytype = InvalidOid;
/* Interface functions */ /* Interface functions */
amroutine->ambuild = ivfflatbuild; amroutine->ambuild = ivfflatbuild;
amroutine->ambuildempty = ivfflatbuildempty; amroutine->ambuildempty = ivfflatbuildempty;
amroutine->aminsert = ivfflatinsert; amroutine->aminsert = ivfflatinsert;
#if PG_VERSION_NUM >= 170000
amroutine->aminsertcleanup = NULL;
#endif
amroutine->ambulkdelete = ivfflatbulkdelete; amroutine->ambulkdelete = ivfflatbulkdelete;
amroutine->amvacuumcleanup = ivfflatvacuumcleanup; amroutine->amvacuumcleanup = ivfflatvacuumcleanup;
amroutine->amcanreturn = NULL; /* tuple not included in heapsort */ amroutine->amcanreturn = NULL; /* tuple not included in heapsort */

View File

@@ -28,7 +28,6 @@
#define IVFFLAT_NORM_PROC 2 #define IVFFLAT_NORM_PROC 2
#define IVFFLAT_KMEANS_DISTANCE_PROC 3 #define IVFFLAT_KMEANS_DISTANCE_PROC 3
#define IVFFLAT_KMEANS_NORM_PROC 4 #define IVFFLAT_KMEANS_NORM_PROC 4
#define IVFFLAT_TYPE_INFO_PROC 5
#define IVFFLAT_VERSION 1 #define IVFFLAT_VERSION 1
#define IVFFLAT_MAGIC_NUMBER 0x14FF1A7 #define IVFFLAT_MAGIC_NUMBER 0x14FF1A7
@@ -50,7 +49,7 @@
#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))
@@ -86,8 +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;
@@ -146,25 +144,15 @@ typedef struct IvfflatLeader
IvfflatShared *ivfshared; IvfflatShared *ivfshared;
Sharedsort *sharedsort; Sharedsort *sharedsort;
Snapshot snapshot; Snapshot snapshot;
char *ivfcenters; Vector *ivfcenters;
} IvfflatLeader; } IvfflatLeader;
typedef struct IvfflatTypeInfo
{
int maxDimensions;
Datum (*normalize) (PG_FUNCTION_ARGS);
Size (*itemSize) (int dimensions);
void (*updateCenter) (Pointer v, int dimensions, float *x);
void (*sumCenter) (Pointer v, float *x);
} IvfflatTypeInfo;
typedef struct IvfflatBuildState typedef struct IvfflatBuildState
{ {
/* Info */ /* Info */
Relation heap; Relation heap;
Relation index; Relation index;
IndexInfo *indexInfo; IndexInfo *indexInfo;
const IvfflatTypeInfo *typeInfo;
/* Settings */ /* Settings */
int dimensions; int dimensions;
@@ -184,6 +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;
@@ -245,7 +234,6 @@ typedef struct IvfflatScanList
typedef struct IvfflatScanOpaqueData typedef struct IvfflatScanOpaqueData
{ {
const IvfflatTypeInfo *typeInfo;
int probes; int probes;
int dimensions; int dimensions;
bool first; bool first;
@@ -253,15 +241,13 @@ typedef struct IvfflatScanOpaqueData
/* Sorting */ /* Sorting */
Tuplesortstate *sortstate; Tuplesortstate *sortstate;
TupleDesc tupdesc; TupleDesc tupdesc;
TupleTableSlot *vslot; TupleTableSlot *slot;
TupleTableSlot *mslot; bool isnull;
BufferAccessStrategy bas;
/* Support functions */ /* Support functions */
FmgrInfo *procinfo; FmgrInfo *procinfo;
FmgrInfo *normprocinfo; FmgrInfo *normprocinfo;
Oid collation; Oid collation;
Datum (*distfunc) (FmgrInfo *flinfo, Oid collation, Datum arg1, Datum arg2);
/* Lists */ /* Lists */
pairingheap *listQueue; pairingheap *listQueue;
@@ -270,29 +256,18 @@ typedef struct IvfflatScanOpaqueData
typedef IvfflatScanOpaqueData * IvfflatScanOpaque; typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
#define VECTOR_ARRAY_SIZE(_length, _size) (sizeof(VectorArrayData) + (_length) * MAXALIGN(_size)) #define VECTOR_ARRAY_SIZE(_length, _dim) (sizeof(VectorArrayData) + (_length) * VECTOR_SIZE(_dim))
#define VECTOR_ARRAY_OFFSET(_arr, _offset) ((char*) (_arr)->items + (_offset) * VECTOR_SIZE((_arr)->dim))
/* Use functions instead of macros to avoid double evaluation */ #define VectorArrayGet(_arr, _offset) ((Vector *) VECTOR_ARRAY_OFFSET(_arr, _offset))
#define VectorArraySet(_arr, _offset, _val) memcpy(VECTOR_ARRAY_OFFSET(_arr, _offset), _val, VECTOR_SIZE((_arr)->dim))
static inline Pointer
VectorArrayGet(VectorArray arr, int offset)
{
return ((char *) arr->items) + (offset * arr->itemsize);
}
static inline void
VectorArraySet(VectorArray arr, int offset, Pointer val)
{
memcpy(VectorArrayGet(arr, offset), val, VARSIZE_ANY(val));
}
/* 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, const IvfflatTypeInfo * typeInfo); 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);
Datum IvfflatNormValue(const IvfflatTypeInfo * typeInfo, Oid collation, Datum value); bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
bool IvfflatCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value);
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);
@@ -302,7 +277,6 @@ Buffer IvfflatNewBuffer(Relation index, ForkNumber forkNum);
void IvfflatInitPage(Buffer buf, Page page); void IvfflatInitPage(Buffer buf, Page page);
void IvfflatInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state); void IvfflatInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state);
void IvfflatInit(void); void IvfflatInit(void);
const IvfflatTypeInfo *IvfflatGetTypeInfo(Relation index);
PGDLLEXPORT void IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc); PGDLLEXPORT void IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc);
/* Index access methods */ /* Index access methods */

View File

@@ -67,7 +67,6 @@ FindInsertPage(Relation index, Datum *values, BlockNumber *insertPage, ListInfo
static void static void
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel) InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
{ {
const IvfflatTypeInfo *typeInfo = IvfflatGetTypeInfo(index);
IndexTuple itup; IndexTuple itup;
Datum value; Datum value;
FmgrInfo *normprocinfo; FmgrInfo *normprocinfo;
@@ -86,17 +85,10 @@ 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)
{ {
Oid collation = index->rd_indcollation[0]; if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
if (!IvfflatCheckNorm(normprocinfo, collation, value))
return; return;
value = IvfflatNormValue(typeInfo, collation, value);
} }
/* Ensure index is valid */
IvfflatGetMetaPageInfo(index, NULL, NULL);
/* Find the insert page - sets the page and list info */ /* Find the insert page - sets the page and list info */
FindInsertPage(index, values, &insertPage, &listInfo); FindInsertPage(index, values, &insertPage, &listInfo);
Assert(BlockNumberIsValid(insertPage)); Assert(BlockNumberIsValid(insertPage));

View File

@@ -3,15 +3,12 @@
#include <float.h> #include <float.h>
#include <math.h> #include <math.h>
#include "bitvec.h"
#include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "miscadmin.h" #include "miscadmin.h"
#include "utils/builtins.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++
@@ -49,12 +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;
@@ -89,59 +86,73 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
} }
/* /*
* Norm centers * Apply norm to vector
*/ */
static void static inline void
NormCenters(const IvfflatTypeInfo * typeInfo, Oid collation, VectorArray centers) ApplyNorm(FmgrInfo *normprocinfo, Oid collation, Vector * vec)
{ {
MemoryContext normCtx = AllocSetContextCreate(CurrentMemoryContext, double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(vec)));
"Ivfflat norm temporary context",
ALLOCSET_DEFAULT_SIZES);
MemoryContext oldCtx = MemoryContextSwitchTo(normCtx);
for (int j = 0; j < centers->length; j++) /* TODO Handle zero norm */
if (norm > 0)
{ {
Datum center = PointerGetDatum(VectorArrayGet(centers, j)); for (int i = 0; i < vec->dim; i++)
Datum newCenter = IvfflatNormValue(typeInfo, collation, center); vec->x[i] /= norm;
Size size = VARSIZE_ANY(DatumGetPointer(newCenter));
if (size > centers->itemsize)
elog(ERROR, "safety check failed");
memcpy(DatumGetPointer(center), DatumGetPointer(newCenter), size);
MemoryContextReset(normCtx);
} }
MemoryContextSwitchTo(oldCtx);
MemoryContextDelete(normCtx);
} }
/* /*
* Quick approach if we have no data * Compare vectors
*/
static int
CompareVectors(const void *a, const void *b)
{
return vector_cmp_internal((Vector *) a, (Vector *) b);
}
/*
* Quick approach if we have little data
*/ */
static void static void
RandomCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeInfo) QuickCenters(Relation index, VectorArray samples, VectorArray centers)
{ {
int dimensions = centers->dim; int dimensions = centers->dim;
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
Oid collation = index->rd_indcollation[0]; Oid collation = index->rd_indcollation[0];
float *x = (float *) palloc(sizeof(float) * dimensions); FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
/* Fill with random data */ /* Copy existing vectors while avoiding duplicates */
if (samples->length > 0)
{
qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
for (int i = 0; i < samples->length; i++)
{
Vector *vec = VectorArrayGet(samples, i);
if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
{
VectorArraySet(centers, centers->length, vec);
centers->length++;
}
}
}
/* Fill remaining with random data */
while (centers->length < centers->maxlen) while (centers->length < centers->maxlen)
{ {
Pointer center = VectorArrayGet(centers, centers->length); Vector *vec = VectorArrayGet(centers, centers->length);
for (int i = 0; i < dimensions; i++) SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
x[i] = (float) RandomDouble(); vec->dim = dimensions;
typeInfo->updateCenter(center, dimensions, x); for (int j = 0; j < dimensions; j++)
vec->x[j] = RandomDouble();
/* Normalize if needed (only needed for random centers) */
if (normprocinfo != NULL)
ApplyNorm(normprocinfo, collation, vec);
centers->length++; centers->length++;
} }
if (normprocinfo != NULL)
NormCenters(typeInfo, collation, centers);
} }
#ifdef IVFFLAT_MEMORY #ifdef IVFFLAT_MEMORY
@@ -149,104 +160,18 @@ RandomCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeI
* Show memory usage * Show memory usage
*/ */
static void static void
ShowMemoryUsage(MemoryContext context, Size estimatedSize) ShowMemoryUsage(Size estimatedSize)
{ {
#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
MemoryContextStats(CurrentMemoryContext);
#endif
elog(INFO, "estimated memory: %zu MB", estimatedSize / (1024 * 1024)); elog(INFO, "estimated memory: %zu MB", estimatedSize / (1024 * 1024));
} }
#endif #endif
/*
* Sum centers
*/
static void
SumCenters(VectorArray samples, float *agg, int *closestCenters, const IvfflatTypeInfo * typeInfo)
{
for (int j = 0; j < samples->length; j++)
{
float *x = agg + ((int64) closestCenters[j] * samples->dim);
typeInfo->sumCenter(VectorArrayGet(samples, j), x);
}
}
/*
* Update centers
*/
static void
UpdateCenters(float *agg, VectorArray centers, const IvfflatTypeInfo * typeInfo)
{
for (int j = 0; j < centers->length; j++)
{
float *x = agg + ((int64) j * centers->dim);
typeInfo->updateCenter(VectorArrayGet(centers, j), centers->dim, x);
}
}
/*
* Compute new centers
*/
static void
ComputeNewCenters(VectorArray samples, float *agg, VectorArray newCenters, int *centerCounts, int *closestCenters, FmgrInfo *normprocinfo, Oid collation, const IvfflatTypeInfo * typeInfo)
{
int dimensions = newCenters->dim;
int numCenters = newCenters->length;
int numSamples = samples->length;
/* Reset sum and count */
for (int j = 0; j < numCenters; j++)
{
float *x = agg + ((int64) j * dimensions);
for (int k = 0; k < dimensions; k++)
x[k] = 0.0;
centerCounts[j] = 0;
}
/* Increment sum of closest center */
SumCenters(samples, agg, closestCenters, typeInfo);
/* 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++)
{
float *x = agg + ((int64) j * dimensions);
if (centerCounts[j] > 0)
{
/* Double avoids overflow, but requires more memory */
/* TODO Update bounds */
for (int k = 0; k < dimensions; k++)
{
if (isinf(x[k]))
x[k] = x[k] > 0 ? FLT_MAX : -FLT_MAX;
}
for (int k = 0; k < dimensions; k++)
x[k] /= centerCounts[j];
}
else
{
/* TODO Handle empty centers properly */
for (int k = 0; k < dimensions; k++)
x[k] = RandomDouble();
}
}
/* Set new centers */
UpdateCenters(agg, newCenters, typeInfo);
/* Normalize if needed */
if (normprocinfo != NULL)
NormCenters(typeInfo, collation, newCenters);
}
/* /*
* Use Elkan for performance. This requires distance function to satisfy triangle inequality. * Use Elkan for performance. This requires distance function to satisfy triangle inequality.
* *
@@ -256,16 +181,19 @@ ComputeNewCenters(VectorArray samples, float *agg, VectorArray newCenters, int *
* 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, const IvfflatTypeInfo * typeInfo) 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;
float *agg;
int *centerCounts; int *centerCounts;
int *closestCenters; int *closestCenters;
float *lowerBound; float *lowerBound;
@@ -275,10 +203,9 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
float *newcdist; float *newcdist;
/* 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 aggSize = sizeof(float) * (int64) numCenters * 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;
@@ -288,7 +215,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
Size newcdistSize = sizeof(float) * numCenters; Size newcdistSize = sizeof(float) * numCenters;
/* Calculate total size */ /* Calculate total size */
Size totalSize = samplesSize + centersSize + newCentersSize + aggSize + 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 */
@@ -309,7 +236,6 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
/* Allocate space */ /* Allocate space */
/* Use float instead of double to save memory */ /* Use float instead of double to save memory */
agg = palloc(aggSize);
centerCounts = palloc(centerCountsSize); centerCounts = palloc(centerCountsSize);
closestCenters = palloc(closestCentersSize); closestCenters = palloc(closestCentersSize);
lowerBound = palloc_extended(lowerBoundSize, MCXT_ALLOC_HUGE); lowerBound = palloc_extended(lowerBoundSize, MCXT_ALLOC_HUGE);
@@ -318,25 +244,29 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
halfcdist = palloc_extended(halfcdistSize, MCXT_ALLOC_HUGE); halfcdist = palloc_extended(halfcdistSize, MCXT_ALLOC_HUGE);
newcdist = palloc(newcdistSize); newcdist = palloc(newcdistSize);
/* Initialize new centers */ newCenters = VectorArrayInit(numCenters, dimensions);
newCenters = VectorArrayInit(numCenters, dimensions, centers->itemsize); for (j = 0; j < numCenters; j++)
newCenters->length = numCenters; {
vec = VectorArrayGet(newCenters, j);
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
}
#ifdef IVFFLAT_MEMORY #ifdef IVFFLAT_MEMORY
ShowMemoryUsage(MemoryContextGetParent(CurrentMemoryContext), 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];
@@ -362,13 +292,13 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
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;
@@ -376,11 +306,11 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
} }
/* 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;
@@ -397,7 +327,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
rjreset = iteration != 0; rjreset = iteration != 0;
for (int64 j = 0; j < numSamples; j++) for (j = 0; j < numSamples; j++)
{ {
bool rj; bool rj;
@@ -407,9 +337,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
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 */
@@ -422,12 +351,12 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
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;
@@ -441,7 +370,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
/* 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;
@@ -460,15 +389,66 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
} }
/* 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, agg, newCenters, centerCounts, closestCenters, normprocinfo, collation, typeInfo); 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];
@@ -481,78 +461,77 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
/* 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;
} }
}
/* VectorArrayFree(newCenters);
* Ensure no NaN or infinite values pfree(centerCounts);
*/ pfree(closestCenters);
static void pfree(lowerBound);
CheckElements(VectorArray centers, const IvfflatTypeInfo * typeInfo) pfree(upperBound);
{ pfree(s);
float *scratch = palloc(sizeof(float) * centers->dim); pfree(halfcdist);
pfree(newcdist);
for (int i = 0; i < centers->length; i++)
{
for (int j = 0; j < centers->dim; j++)
scratch[j] = 0;
/* /fp:fast may not propagate NaN with MSVC, but that's alright */
typeInfo->sumCenter(VectorArrayGet(centers, i), scratch);
for (int j = 0; j < centers->dim; j++)
{
if (isnan(scratch[j]))
elog(ERROR, "NaN detected. Please report a bug.");
if (isinf(scratch[j]))
elog(ERROR, "Infinite value detected. Please report a bug.");
}
}
}
/*
* Ensure no zero vectors for cosine distance
*/
static void
CheckNorms(VectorArray centers, Relation index)
{
/* Check NORM_PROC instead of KMEANS_NORM_PROC */
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
Oid collation = index->rd_indcollation[0];
if (normprocinfo == NULL)
return;
for (int i = 0; i < centers->length; i++)
{
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(VectorArrayGet(centers, i))));
if (norm == 0)
elog(ERROR, "Zero norm detected. Please report a bug.");
}
} }
/* /*
* Detect issues with centers * Detect issues with centers
*/ */
static void static void
CheckCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeInfo) CheckCenters(Relation index, VectorArray centers)
{ {
FmgrInfo *normprocinfo;
if (centers->length != centers->maxlen) if (centers->length != centers->maxlen)
elog(ERROR, "Not enough centers. Please report a bug."); elog(ERROR, "Not enough centers. Please report a bug.");
CheckElements(centers, typeInfo); /* Ensure no NaN or infinite values */
CheckNorms(centers, index); for (int i = 0; i < centers->length; i++)
{
Vector *vec = VectorArrayGet(centers, i);
for (int j = 0; j < vec->dim; j++)
{
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.");
}
}
/* Ensure no duplicate centers */
/* Fine to sort in-place */
qsort(centers->items, centers->length, VECTOR_SIZE(centers->dim), CompareVectors);
for (int i = 1; i < centers->length; i++)
{
if (CompareVectors(VectorArrayGet(centers, i), VectorArrayGet(centers, i - 1)) == 0)
elog(ERROR, "Duplicate centers detected. Please report a bug.");
}
/* Ensure no zero vectors for cosine distance */
/* Check NORM_PROC instead of KMEANS_NORM_PROC */
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL)
{
Oid collation = index->rd_indcollation[0];
for (int i = 0; i < centers->length; i++)
{
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(VectorArrayGet(centers, i))));
if (norm == 0)
elog(ERROR, "Zero norm detected. Please report a bug.");
}
}
} }
/* /*
@@ -560,20 +539,12 @@ CheckCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeIn
* 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, const IvfflatTypeInfo * typeInfo) IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers)
{ {
MemoryContext kmeansCtx = AllocSetContextCreate(CurrentMemoryContext, if (samples->length <= centers->maxlen)
"Ivfflat kmeans temporary context", QuickCenters(index, samples, centers);
ALLOCSET_DEFAULT_SIZES);
MemoryContext oldCtx = MemoryContextSwitchTo(kmeansCtx);
if (samples->length == 0)
RandomCenters(index, centers, typeInfo);
else else
ElkanKmeans(index, samples, centers, typeInfo); ElkanKmeans(index, samples, centers);
CheckCenters(index, centers, typeInfo); CheckCenters(index, centers);
MemoryContextSwitchTo(oldCtx);
MemoryContextDelete(kmeansCtx);
} }

View File

@@ -11,23 +11,16 @@
#include "pgstat.h" #include "pgstat.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#ifdef IVFFLAT_MEMORY
#include "utils/memutils.h"
#endif
#define GetScanList(ptr) pairingheap_container(IvfflatScanList, ph_node, ptr)
#define GetScanListConst(ptr) pairingheap_const_container(IvfflatScanList, ph_node, ptr)
/* /*
* Compare list distances * Compare list distances
*/ */
static int static int
CompareLists(const pairingheap_node *a, const pairingheap_node *b, void *arg) CompareLists(const pairingheap_node *a, const pairingheap_node *b, void *arg)
{ {
if (GetScanListConst(a)->distance > GetScanListConst(b)->distance) if (((const IvfflatScanList *) a)->distance > ((const IvfflatScanList *) b)->distance)
return 1; return 1;
if (GetScanListConst(a)->distance < GetScanListConst(b)->distance) if (((const IvfflatScanList *) a)->distance < ((const IvfflatScanList *) b)->distance)
return -1; return -1;
return 0; return 0;
@@ -63,7 +56,7 @@ GetScanLists(IndexScanDesc scan, Datum value)
double distance; double distance;
/* Use procinfo from the index instead of scan key for performance */ /* Use procinfo from the index instead of scan key for performance */
distance = DatumGetFloat8(so->distfunc(so->procinfo, so->collation, PointerGetDatum(&list->center), value)); distance = DatumGetFloat8(FunctionCall2Coll(so->procinfo, so->collation, PointerGetDatum(&list->center), value));
if (listCount < so->probes) if (listCount < so->probes)
{ {
@@ -79,14 +72,14 @@ GetScanLists(IndexScanDesc scan, Datum value)
/* Calculate max distance */ /* Calculate max distance */
if (listCount == so->probes) if (listCount == so->probes)
maxDistance = GetScanList(pairingheap_first(so->listQueue))->distance; maxDistance = ((IvfflatScanList *) pairingheap_first(so->listQueue))->distance;
} }
else if (distance < maxDistance) else if (distance < maxDistance)
{ {
IvfflatScanList *scanlist; IvfflatScanList *scanlist;
/* Remove */ /* Remove */
scanlist = GetScanList(pairingheap_remove_first(so->listQueue)); scanlist = (IvfflatScanList *) pairingheap_remove_first(so->listQueue);
/* Reuse */ /* Reuse */
scanlist->startPage = list->startPage; scanlist->startPage = list->startPage;
@@ -94,7 +87,7 @@ GetScanLists(IndexScanDesc scan, Datum value)
pairingheap_add(so->listQueue, &scanlist->ph_node); pairingheap_add(so->listQueue, &scanlist->ph_node);
/* Update max distance */ /* Update max distance */
maxDistance = GetScanList(pairingheap_first(so->listQueue))->distance; maxDistance = ((IvfflatScanList *) pairingheap_first(so->listQueue))->distance;
} }
} }
@@ -113,12 +106,19 @@ GetScanItems(IndexScanDesc scan, Datum value)
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque; IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
TupleDesc tupdesc = RelationGetDescr(scan->indexRelation); TupleDesc tupdesc = RelationGetDescr(scan->indexRelation);
double tuples = 0; double tuples = 0;
TupleTableSlot *slot = so->vslot; TupleTableSlot *slot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsVirtual);
/*
* Reuse same set of shared buffers for scan
*
* See postgres/src/backend/storage/buffer/README for description
*/
BufferAccessStrategy bas = GetAccessStrategy(BAS_BULKREAD);
/* Search closest probes lists */ /* Search closest probes lists */
while (!pairingheap_is_empty(so->listQueue)) while (!pairingheap_is_empty(so->listQueue))
{ {
BlockNumber searchPage = GetScanList(pairingheap_remove_first(so->listQueue))->startPage; BlockNumber searchPage = ((IvfflatScanList *) pairingheap_remove_first(so->listQueue))->startPage;
/* Search all entry pages for list */ /* Search all entry pages for list */
while (BlockNumberIsValid(searchPage)) while (BlockNumberIsValid(searchPage))
@@ -127,7 +127,7 @@ GetScanItems(IndexScanDesc scan, Datum value)
Page page; Page page;
OffsetNumber maxoffno; OffsetNumber maxoffno;
buf = ReadBufferExtended(scan->indexRelation, MAIN_FORKNUM, searchPage, RBM_NORMAL, so->bas); buf = ReadBufferExtended(scan->indexRelation, MAIN_FORKNUM, searchPage, RBM_NORMAL, bas);
LockBuffer(buf, BUFFER_LOCK_SHARE); LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf); page = BufferGetPage(buf);
maxoffno = PageGetMaxOffsetNumber(page); maxoffno = PageGetMaxOffsetNumber(page);
@@ -149,7 +149,7 @@ GetScanItems(IndexScanDesc scan, Datum value)
* performance * performance
*/ */
ExecClearTuple(slot); ExecClearTuple(slot);
slot->tts_values[0] = so->distfunc(so->procinfo, so->collation, datum, value); slot->tts_values[0] = FunctionCall2Coll(so->procinfo, so->collation, datum, value);
slot->tts_isnull[0] = false; slot->tts_isnull[0] = false;
slot->tts_values[1] = PointerGetDatum(&itup->t_tid); slot->tts_values[1] = PointerGetDatum(&itup->t_tid);
slot->tts_isnull[1] = false; slot->tts_isnull[1] = false;
@@ -166,6 +166,8 @@ GetScanItems(IndexScanDesc scan, Datum value)
} }
} }
FreeAccessStrategy(bas);
if (tuples < 100) if (tuples < 100)
ereport(DEBUG1, ereport(DEBUG1,
(errmsg("index scan found few tuples"), (errmsg("index scan found few tuples"),
@@ -175,60 +177,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
tuplesort_performsort(so->sortstate); tuplesort_performsort(so->sortstate);
} }
/*
* Zero distance
*/
static Datum
ZeroDistance(FmgrInfo *flinfo, Oid collation, Datum arg1, Datum arg2)
{
return Float8GetDatum(0.0);
}
/*
* Get scan value
*/
static Datum
GetScanValue(IndexScanDesc scan)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL)
{
value = PointerGetDatum(NULL);
so->distfunc = ZeroDistance;
}
else
{
value = scan->orderByData->sk_argument;
so->distfunc = FunctionCall2Coll;
/* Value should not be compressed or toasted */
Assert(!VARATT_IS_COMPRESSED(DatumGetPointer(value)));
Assert(!VARATT_IS_EXTENDED(DatumGetPointer(value)));
/* Normalize if needed */
if (so->normprocinfo != NULL)
value = IvfflatNormValue(so->typeInfo, so->collation, value);
}
return value;
}
/*
* Initialize scan sort state
*/
static Tuplesortstate *
InitScanSortState(TupleDesc tupdesc)
{
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Float8LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
return tuplesort_begin_heap(tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
}
/* /*
* Prepare for an index scan * Prepare for an index scan
*/ */
@@ -239,6 +187,10 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
IvfflatScanOpaque so; IvfflatScanOpaque so;
int lists; int lists;
int dimensions; int dimensions;
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Float8LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
int probes = ivfflat_probes; int probes = ivfflat_probes;
scan = RelationGetIndexScan(index, nkeys, norderbys); scan = RelationGetIndexScan(index, nkeys, norderbys);
@@ -250,7 +202,6 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
probes = lists; probes = lists;
so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList)); so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
so->typeInfo = IvfflatGetTypeInfo(index);
so->first = true; so->first = true;
so->probes = probes; so->probes = probes;
so->dimensions = dimensions; so->dimensions = dimensions;
@@ -266,18 +217,9 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0); TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
/* Prep sort */ /* Prep sort */
so->sortstate = InitScanSortState(so->tupdesc); so->sortstate = tuplesort_begin_heap(so->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
/* Need separate slots for puttuple and gettuple */ so->slot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsMinimalTuple);
so->vslot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsVirtual);
so->mslot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsMinimalTuple);
/*
* Reuse same set of shared buffers for scan
*
* See postgres/src/backend/storage/buffer/README for description
*/
so->bas = GetAccessStrategy(BAS_BULKREAD);
so->listQueue = pairingheap_allocate(CompareLists, scan); so->listQueue = pairingheap_allocate(CompareLists, scan);
@@ -294,8 +236,10 @@ ivfflatrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int
{ {
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque; IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
#if PG_VERSION_NUM >= 130000
if (!so->first) if (!so->first)
tuplesort_reset(so->sortstate); tuplesort_reset(so->sortstate);
#endif
so->first = true; so->first = true;
pairingheap_reset(so->listQueue); pairingheap_reset(so->listQueue);
@@ -337,24 +281,33 @@ 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;
#if defined(IVFFLAT_MEMORY)
elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(CurrentMemoryContext, true) / (1024 * 1024));
#endif
/* Clean up if we allocated a new value */ /* Clean up if we allocated a new value */
if (value != scan->orderByData->sk_argument) if (value != scan->orderByData->sk_argument)
pfree(DatumGetPointer(value)); pfree(DatumGetPointer(value));
} }
if (tuplesort_gettupleslot(so->sortstate, true, false, so->mslot, NULL)) if (tuplesort_gettupleslot(so->sortstate, true, false, so->slot, NULL))
{ {
bool isnull; ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->mslot, 2, &isnull));
scan->xs_heaptid = *heaptid; scan->xs_heaptid = *heaptid;
scan->xs_recheck = false; scan->xs_recheck = false;
@@ -375,10 +328,6 @@ ivfflatendscan(IndexScanDesc scan)
pairingheap_free(so->listQueue); pairingheap_free(so->listQueue);
tuplesort_end(so->sortstate); tuplesort_end(so->sortstate);
FreeAccessStrategy(so->bas);
FreeTupleDesc(so->tupdesc);
/* TODO Free vslot and mslot without freeing TupleDesc */
pfree(so); pfree(so);
scan->opaque = NULL; scan->opaque = NULL;

View File

@@ -1,31 +1,22 @@
#include "postgres.h" #include "postgres.h"
#include "access/generic_xlog.h" #include "access/generic_xlog.h"
#include "bitvec.h"
#include "catalog/pg_type.h"
#include "fmgr.h"
#include "halfutils.h"
#include "halfvec.h"
#include "ivfflat.h" #include "ivfflat.h"
#include "minivec.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#include "vector.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));
/* Ensure items are aligned to prevent UB */
itemsize = MAXALIGN(itemsize);
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;
} }
@@ -39,6 +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
*/ */
@@ -66,24 +67,34 @@ IvfflatOptionalProcInfo(Relation index, uint16 procnum)
} }
/* /*
* Normalize value * Divide by the norm
*/ *
Datum * Returns false if value should not be indexed
IvfflatNormValue(const IvfflatTypeInfo * typeInfo, Oid collation, Datum value) *
{ * The caller needs to free the pointer stored in value
if (!typeInfo->normalize) * if it's different than the original value
return value;
return DirectFunctionCall1Coll(typeInfo->normalize, collation, value);
}
/*
* Check if non-zero norm
*/ */
bool bool
IvfflatCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value) IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result)
{ {
return DatumGetFloat8(FunctionCall1Coll(procinfo, collation, value)) > 0; double norm = DatumGetFloat8(FunctionCall1Coll(procinfo, collation, *value));
if (norm > 0)
{
Vector *v = DatumGetVector(*value);
if (result == NULL)
result = InitVector(v->dim);
for (int i = 0; i < v->dim; i++)
result->x[i] = v->x[i] / norm;
*value = PointerGetDatum(result);
return true;
}
return false;
} }
/* /*
@@ -174,11 +185,7 @@ IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions)
page = BufferGetPage(buf); page = BufferGetPage(buf);
metap = IvfflatPageGetMeta(page); metap = IvfflatPageGetMeta(page);
if (unlikely(metap->magicNumber != IVFFLAT_MAGIC_NUMBER)) *lists = metap->lists;
elog(ERROR, "ivfflat index is not valid");
if (lists != NULL)
*lists = metap->lists;
if (dimensions != NULL) if (dimensions != NULL)
*dimensions = metap->dimensions; *dimensions = metap->dimensions;
@@ -232,190 +239,3 @@ IvfflatUpdateList(Relation index, ListInfo listInfo,
UnlockReleaseBuffer(buf); UnlockReleaseBuffer(buf);
} }
} }
PGDLLEXPORT Datum l2_normalize(PG_FUNCTION_ARGS);
PGDLLEXPORT Datum halfvec_l2_normalize(PG_FUNCTION_ARGS);
PGDLLEXPORT Datum minivec_l2_normalize(PG_FUNCTION_ARGS);
PGDLLEXPORT Datum sparsevec_l2_normalize(PG_FUNCTION_ARGS);
static Size
VectorItemSize(int dimensions)
{
return VECTOR_SIZE(dimensions);
}
static Size
HalfvecItemSize(int dimensions)
{
return HALFVEC_SIZE(dimensions);
}
static Size
MinivecItemSize(int dimensions)
{
return MINIVEC_SIZE(dimensions);
}
static Size
BitItemSize(int dimensions)
{
return VARBITTOTALLEN(dimensions);
}
static void
VectorUpdateCenter(Pointer v, int dimensions, float *x)
{
Vector *vec = (Vector *) v;
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
for (int k = 0; k < dimensions; k++)
vec->x[k] = x[k];
}
static void
HalfvecUpdateCenter(Pointer v, int dimensions, float *x)
{
HalfVector *vec = (HalfVector *) v;
SET_VARSIZE(vec, HALFVEC_SIZE(dimensions));
vec->dim = dimensions;
for (int k = 0; k < dimensions; k++)
vec->x[k] = Float4ToHalfUnchecked(x[k]);
}
static void
MinivecUpdateCenter(Pointer v, int dimensions, float *x)
{
MiniVector *vec = (MiniVector *) v;
SET_VARSIZE(vec, MINIVEC_SIZE(dimensions));
vec->dim = dimensions;
for (int k = 0; k < dimensions; k++)
vec->x[k] = Float4ToFp8Unchecked(x[k]);
}
static void
BitUpdateCenter(Pointer v, int dimensions, float *x)
{
VarBit *vec = (VarBit *) v;
unsigned char *nx = VARBITS(vec);
SET_VARSIZE(vec, VARBITTOTALLEN(dimensions));
VARBITLEN(vec) = dimensions;
for (uint32 k = 0; k < VARBITBYTES(vec); k++)
nx[k] = 0;
for (int k = 0; k < dimensions; k++)
nx[k / 8] |= (x[k] > 0.5 ? 1 : 0) << (7 - (k % 8));
}
static void
VectorSumCenter(Pointer v, float *x)
{
Vector *vec = (Vector *) v;
for (int k = 0; k < vec->dim; k++)
x[k] += vec->x[k];
}
static void
HalfvecSumCenter(Pointer v, float *x)
{
HalfVector *vec = (HalfVector *) v;
for (int k = 0; k < vec->dim; k++)
x[k] += HalfToFloat4(vec->x[k]);
}
static void
MinivecSumCenter(Pointer v, float *x)
{
MiniVector *vec = (MiniVector *) v;
for (int k = 0; k < vec->dim; k++)
x[k] += Fp8ToFloat4(vec->x[k]);
}
static void
BitSumCenter(Pointer v, float *x)
{
VarBit *vec = (VarBit *) v;
for (int k = 0; k < VARBITLEN(vec); k++)
x[k] += (float) (((VARBITS(vec)[k / 8]) >> (7 - (k % 8))) & 0x01);
}
/*
* Get type info
*/
const IvfflatTypeInfo *
IvfflatGetTypeInfo(Relation index)
{
FmgrInfo *procinfo = IvfflatOptionalProcInfo(index, IVFFLAT_TYPE_INFO_PROC);
if (procinfo == NULL)
{
static const IvfflatTypeInfo typeInfo = {
.maxDimensions = IVFFLAT_MAX_DIM,
.normalize = l2_normalize,
.itemSize = VectorItemSize,
.updateCenter = VectorUpdateCenter,
.sumCenter = VectorSumCenter
};
return (&typeInfo);
}
else
return (const IvfflatTypeInfo *) DatumGetPointer(FunctionCall0Coll(procinfo, InvalidOid));
}
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_halfvec_support);
Datum
ivfflat_halfvec_support(PG_FUNCTION_ARGS)
{
static const IvfflatTypeInfo typeInfo = {
.maxDimensions = IVFFLAT_MAX_DIM * 2,
.normalize = halfvec_l2_normalize,
.itemSize = HalfvecItemSize,
.updateCenter = HalfvecUpdateCenter,
.sumCenter = HalfvecSumCenter
};
PG_RETURN_POINTER(&typeInfo);
};
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_minivec_support);
Datum
ivfflat_minivec_support(PG_FUNCTION_ARGS)
{
static const IvfflatTypeInfo typeInfo = {
.maxDimensions = IVFFLAT_MAX_DIM * 4,
/* Do not normalize to maximize precision */
.normalize = NULL,
.itemSize = MinivecItemSize,
.updateCenter = MinivecUpdateCenter,
.sumCenter = MinivecSumCenter
};
PG_RETURN_POINTER(&typeInfo);
};
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_bit_support);
Datum
ivfflat_bit_support(PG_FUNCTION_ARGS)
{
static const IvfflatTypeInfo typeInfo = {
.maxDimensions = IVFFLAT_MAX_DIM * 32,
.normalize = NULL,
.itemSize = BitItemSize,
.updateCenter = BitUpdateCenter,
.sumCenter = BitSumCenter
};
PG_RETURN_POINTER(&typeInfo);
};

File diff suppressed because it is too large Load Diff

View File

@@ -1,163 +0,0 @@
#ifndef MINIVEC_H
#define MINIVEC_H
#define MINIVEC_MAX_DIM 16000
#define fp8 uint8
#define MINIVEC_SIZE(_dim) (offsetof(MiniVector, x) + sizeof(fp8)*(_dim))
#define DatumGetMiniVector(x) ((MiniVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_MINIVEC_P(x) DatumGetMiniVector(PG_GETARG_DATUM(x))
#define PG_RETURN_MINIVEC_P(x) PG_RETURN_POINTER(x)
typedef struct MiniVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int16 dim; /* number of dimensions */
int16 unused; /* reserved for future use, always zero */
fp8 x[FLEXIBLE_ARRAY_MEMBER];
} MiniVector;
MiniVector *InitMiniVector(int dim);
/*
* Check if fp8 is NaN
*/
static inline bool
Fp8IsNan(fp8 num)
{
return (num & 0x7F) == 0x7F;
}
/*
* Check if fp8 is zero
*/
static inline bool
Fp8IsZero(fp8 num)
{
return num == 0;
}
/*
* Convert a fp8 to a float4
*/
static inline float
Fp8ToFloat4(fp8 num)
{
/* Lookup table for non-sign bits */
/* Uses uint32 for correctness */
uint32 lookup[128] = {0, 989855744, 998244352, 1002438656, 1006632960, 1008730112, 1010827264, 1012924416, 1015021568, 1016070144, 1017118720, 1018167296, 1019215872, 1020264448, 1021313024, 1022361600, 1023410176, 1024458752, 1025507328, 1026555904, 1027604480, 1028653056, 1029701632, 1030750208, 1031798784, 1032847360, 1033895936, 1034944512, 1035993088, 1037041664, 1038090240, 1039138816, 1040187392, 1041235968, 1042284544, 1043333120, 1044381696, 1045430272, 1046478848, 1047527424, 1048576000, 1049624576, 1050673152, 1051721728, 1052770304, 1053818880, 1054867456, 1055916032, 1056964608, 1058013184, 1059061760, 1060110336, 1061158912, 1062207488, 1063256064, 1064304640, 1065353216, 1066401792, 1067450368, 1068498944, 1069547520, 1070596096, 1071644672, 1072693248, 1073741824, 1074790400, 1075838976, 1076887552, 1077936128, 1078984704, 1080033280, 1081081856, 1082130432, 1083179008, 1084227584, 1085276160, 1086324736, 1087373312, 1088421888, 1089470464, 1090519040, 1091567616, 1092616192, 1093664768, 1094713344, 1095761920, 1096810496, 1097859072, 1098907648, 1099956224, 1101004800, 1102053376, 1103101952, 1104150528, 1105199104, 1106247680, 1107296256, 1108344832, 1109393408, 1110441984, 1111490560, 1112539136, 1113587712, 1114636288, 1115684864, 1116733440, 1117782016, 1118830592, 1119879168, 1120927744, 1121976320, 1123024896, 1124073472, 1125122048, 1126170624, 1127219200, 1128267776, 1129316352, 1130364928, 1131413504, 1132462080, 1133510656, 1134559232, 1135607808, 1136656384, 1137704960, 1138753536, 2146435072};
union
{
float f;
uint32 i;
} swap;
swap.i = lookup[num & 0x7F];
return (num & 0x80) == 0x80 ? -swap.f : swap.f;
}
/*
* Convert a float4 to a fp8
*/
static inline fp8
Float4ToFp8Unchecked(float num)
{
union
{
float f;
uint32 i;
} swap;
uint32 bin;
int exponent;
int mantissa;
uint8 result;
swap.f = num;
bin = swap.i;
exponent = (bin & 0x7F800000) >> 23;
mantissa = bin & 0x007FFFFF;
/* Sign */
result = (bin & 0x80000000) >> 24;
if (isinf(num) || isnan(num))
{
/* NaN */
result |= 0x7F;
}
else if (exponent > 114)
{
int m;
int gr;
int s;
exponent -= 127;
s = mantissa & 0x0007FFFF;
/* Subnormal */
if (exponent < -6)
{
int diff = -exponent - 6;
mantissa >>= diff;
mantissa += 1 << (23 - diff);
s |= mantissa & 0x0007FFFF;
}
m = mantissa >> 20;
/* Round */
gr = (mantissa >> 19) % 4;
if (gr == 3 || (gr == 1 && s != 0))
m += 1;
if (m == 8)
{
m = 0;
exponent += 1;
}
if (exponent > 8)
{
/* Infinite, which is NaN */
result |= 0x7F;
}
else
{
if (exponent >= -6)
result |= (exponent + 7) << 3;
result |= m;
}
}
return result;
}
/*
* Convert a float4 to a fp8
*/
static inline fp8
Float4ToFp8(float num)
{
fp8 result = Float4ToFp8Unchecked(num);
if (unlikely(Fp8IsNan(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 minivec", buf)));
}
return result;
}
#endif

File diff suppressed because it is too large Load Diff

View File

@@ -1,40 +0,0 @@
#ifndef SPARSEVEC_H
#define SPARSEVEC_H
#define SPARSEVEC_MAX_DIM 1000000000
#define SPARSEVEC_MAX_NNZ 16000
#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)
/*
* Indices use 0-based numbering for the on-disk (and binary) format (consistent with C)
* and are always sorted. Values come after indices.
*/
typedef struct SparseVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int32 dim; /* number of dimensions */
int32 nnz; /* number of non-zero elements */
int32 unused; /* reserved for future use, always zero */
int32 indices[FLEXIBLE_ARRAY_MEMBER];
} SparseVector;
/* Use functions instead of macros to avoid double evaluation */
static inline Size
SPARSEVEC_SIZE(int nnz)
{
return offsetof(SparseVector, indices) + (nnz * sizeof(int32)) + (nnz * sizeof(float));
}
static inline float *
SPARSEVEC_VALUES(SparseVector * x)
{
return (float *) (((char *) x) + offsetof(SparseVector, indices) + (x->nnz * sizeof(int32)));
}
SparseVector *InitSparseVector(int dim, int nnz);
#endif

View File

@@ -2,20 +2,15 @@
#include <math.h> #include <math.h>
#include "bitutils.h" #include "bitvector.h"
#include "bitvec.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 "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 "minivec.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"
@@ -27,15 +22,14 @@
#include "varatt.h" #include "varatt.h"
#endif #endif
#if PG_VERSION_NUM < 130000
#define TYPALIGN_DOUBLE 'd'
#define TYPALIGN_INT 'i'
#endif
#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))
#if defined(USE_TARGET_CLONES) && !defined(__FMA__)
#define VECTOR_TARGET_CLONES __attribute__((target_clones("default", "fma")))
#else
#define VECTOR_TARGET_CLONES
#endif
PG_MODULE_MAGIC; PG_MODULE_MAGIC;
/* /*
@@ -45,8 +39,6 @@ PGDLLEXPORT void _PG_init(void);
void void
_PG_init(void) _PG_init(void)
{ {
BitvecInit();
HalfvecInit();
HnswInit(); HnswInit();
IvfflatInit(); IvfflatInit();
} }
@@ -156,10 +148,28 @@ CheckStateArray(ArrayType *statearray, const char *caller)
return (float8 *) ARR_DATA_PTR(statearray); return (float8 *) ARR_DATA_PTR(statearray);
} }
#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
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_in); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_in);
Datum Datum
vector_in(PG_FUNCTION_ARGS) vector_in(PG_FUNCTION_ARGS)
{ {
@@ -167,33 +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),
@@ -208,55 +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);
@@ -266,13 +276,10 @@ 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
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_out); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_out);
Datum Datum
vector_out(PG_FUNCTION_ARGS) vector_out(PG_FUNCTION_ARGS)
{ {
@@ -280,6 +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:
@@ -294,17 +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);
@@ -326,7 +338,7 @@ PrintVector(char *msg, Vector * vector)
/* /*
* Convert type modifier * Convert type modifier
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_typmod_in); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_typmod_in);
Datum Datum
vector_typmod_in(PG_FUNCTION_ARGS) vector_typmod_in(PG_FUNCTION_ARGS)
{ {
@@ -357,7 +369,7 @@ vector_typmod_in(PG_FUNCTION_ARGS)
/* /*
* Convert external binary representation to internal representation * Convert external binary representation to internal representation
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_recv); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_recv);
Datum Datum
vector_recv(PG_FUNCTION_ARGS) vector_recv(PG_FUNCTION_ARGS)
{ {
@@ -391,7 +403,7 @@ vector_recv(PG_FUNCTION_ARGS)
/* /*
* Convert internal representation to the external binary representation * Convert internal representation to the external binary representation
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_send); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_send);
Datum Datum
vector_send(PG_FUNCTION_ARGS) vector_send(PG_FUNCTION_ARGS)
{ {
@@ -411,7 +423,7 @@ vector_send(PG_FUNCTION_ARGS)
* Convert vector to vector * Convert vector to vector
* This is needed to check the type modifier * This is needed to check the type modifier
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector);
Datum Datum
vector(PG_FUNCTION_ARGS) vector(PG_FUNCTION_ARGS)
{ {
@@ -426,7 +438,7 @@ vector(PG_FUNCTION_ARGS)
/* /*
* Convert array to vector * Convert array to vector
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(array_to_vector); PGDLLEXPORT PG_FUNCTION_INFO_V1(array_to_vector);
Datum Datum
array_to_vector(PG_FUNCTION_ARGS) array_to_vector(PG_FUNCTION_ARGS)
{ {
@@ -500,7 +512,7 @@ array_to_vector(PG_FUNCTION_ARGS)
/* /*
* Convert vector to float4[] * Convert vector to float4[]
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_to_float4); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_float4);
Datum Datum
vector_to_float4(PG_FUNCTION_ARGS) vector_to_float4(PG_FUNCTION_ARGS)
{ {
@@ -521,172 +533,131 @@ vector_to_float4(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
/*
* Convert half vector to vector
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_to_vector);
Datum
halfvec_to_vector(PG_FUNCTION_ARGS)
{
HalfVector *vec = PG_GETARG_HALFVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
CheckDim(vec->dim);
CheckExpectedDim(typmod, vec->dim);
result = InitVector(vec->dim);
for (int i = 0; i < vec->dim; i++)
result->x[i] = HalfToFloat4(vec->x[i]);
PG_RETURN_POINTER(result);
}
/*
* Convert fp8 vector to vector
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(minivec_to_vector);
Datum
minivec_to_vector(PG_FUNCTION_ARGS)
{
MiniVector *vec = PG_GETARG_MINIVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
CheckDim(vec->dim);
CheckExpectedDim(typmod, vec->dim);
result = InitVector(vec->dim);
for (int i = 0; i < vec->dim; i++)
result->x[i] = Fp8ToFloat4(vec->x[i]);
PG_RETURN_POINTER(result);
}
VECTOR_TARGET_CLONES 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
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l2_distance); PGDLLEXPORT PG_FUNCTION_INFO_V1(l2_distance);
Datum Datum
l2_distance(PG_FUNCTION_ARGS) 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));
} }
/* /*
* Get the L2 squared distance between vectors * Get the L2 squared distance between vectors
* This saves a sqrt calculation * This saves a sqrt calculation
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_l2_squared_distance); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_l2_squared_distance);
Datum Datum
vector_l2_squared_distance(PG_FUNCTION_ARGS) 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_TARGET_CLONES 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);
} }
/* /*
* Get the inner product of two vectors * Get the inner product of two vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(inner_product); PGDLLEXPORT PG_FUNCTION_INFO_V1(inner_product);
Datum Datum
inner_product(PG_FUNCTION_ARGS) 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);
} }
/* /*
* Get the negative inner product of two vectors * Get the negative inner product of two vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_negative_inner_product); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_negative_inner_product);
Datum Datum
vector_negative_inner_product(PG_FUNCTION_ARGS) 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));
}
VECTOR_TARGET_CLONES static double
VectorCosineSimilarity(int dim, float *ax, float *bx)
{
float similarity = 0.0;
float norma = 0.0;
float normb = 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];
similarity += ax[i] * bx[i];
norma += ax[i] * ax[i];
normb += bx[i] * bx[i];
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */ PG_RETURN_FLOAT8((double) distance * -1);
return (double) similarity / sqrt((double) norma * (double) normb);
} }
/* /*
* Get the cosine distance between two vectors * Get the cosine distance between two vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(cosine_distance); PGDLLEXPORT PG_FUNCTION_INFO_V1(cosine_distance);
Datum Datum
cosine_distance(PG_FUNCTION_ARGS) cosine_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 norma = 0.0;
float normb = 0.0;
double similarity; double similarity;
CheckDims(a, b); CheckDims(a, b);
similarity = VectorCosineSimilarity(a->dim, a->x, b->x); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
{
distance += ax[i] * bx[i];
norma += ax[i] * ax[i];
normb += bx[i] * bx[i];
}
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
similarity = (double) distance / sqrt((double) norma * (double) normb);
#ifdef _MSC_VER #ifdef _MSC_VER
/* /fp:fast may not propagate NaN */ /* /fp:fast may not propagate NaN */
@@ -708,17 +679,24 @@ cosine_distance(PG_FUNCTION_ARGS)
* Currently uses angular distance since needs to satisfy triangle inequality * Currently uses angular distance since needs to satisfy triangle inequality
* Assumes inputs are unit vectors (skips norm) * Assumes inputs are unit vectors (skips norm)
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_spherical_distance); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_spherical_distance);
Datum Datum
vector_spherical_distance(PG_FUNCTION_ARGS) 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)
@@ -729,38 +707,32 @@ vector_spherical_distance(PG_FUNCTION_ARGS)
PG_RETURN_FLOAT8(acos(distance) / M_PI); PG_RETURN_FLOAT8(acos(distance) / M_PI);
} }
/* Does not require FMA, but keep logic simple */
VECTOR_TARGET_CLONES static float
VectorL1Distance(int dim, float *ax, float *bx)
{
float distance = 0.0;
/* Auto-vectorized */
for (int i = 0; i < dim; i++)
distance += fabsf(ax[i] - bx[i]);
return distance;
}
/* /*
* Get the L1 distance between two vectors * Get the L1 distance between two vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l1_distance); PGDLLEXPORT PG_FUNCTION_INFO_V1(l1_distance);
Datum Datum
l1_distance(PG_FUNCTION_ARGS) l1_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;
CheckDims(a, b); CheckDims(a, b);
PG_RETURN_FLOAT8((double) VectorL1Distance(a->dim, a->x, b->x)); /* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
distance += fabsf(ax[i] - bx[i]);
PG_RETURN_FLOAT8((double) distance);
} }
/* /*
* Get the dimensions of a vector * Get the dimensions of a vector
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_dims); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_dims);
Datum Datum
vector_dims(PG_FUNCTION_ARGS) vector_dims(PG_FUNCTION_ARGS)
{ {
@@ -772,7 +744,7 @@ vector_dims(PG_FUNCTION_ARGS)
/* /*
* Get the L2 norm of a vector * Get the L2 norm of a vector
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_norm); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_norm);
Datum Datum
vector_norm(PG_FUNCTION_ARGS) vector_norm(PG_FUNCTION_ARGS)
{ {
@@ -787,49 +759,10 @@ vector_norm(PG_FUNCTION_ARGS)
PG_RETURN_FLOAT8(sqrt(norm)); PG_RETURN_FLOAT8(sqrt(norm));
} }
/*
* Normalize a vector with the L2 norm
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l2_normalize);
Datum
l2_normalize(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
float *ax = a->x;
double norm = 0;
Vector *result;
float *rx;
result = InitVector(a->dim);
rx = result->x;
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
norm += (double) ax[i] * (double) ax[i];
norm = sqrt(norm);
/* Return zero vector for zero norm */
if (norm > 0)
{
for (int i = 0; i < a->dim; i++)
rx[i] = ax[i] / norm;
/* Check for overflow */
for (int i = 0; i < a->dim; i++)
{
if (isinf(rx[i]))
float_overflow_error();
}
}
PG_RETURN_POINTER(result);
}
/* /*
* Add vectors * Add vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_add); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_add);
Datum Datum
vector_add(PG_FUNCTION_ARGS) vector_add(PG_FUNCTION_ARGS)
{ {
@@ -862,7 +795,7 @@ vector_add(PG_FUNCTION_ARGS)
/* /*
* Subtract vectors * Subtract vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_sub); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_sub);
Datum Datum
vector_sub(PG_FUNCTION_ARGS) vector_sub(PG_FUNCTION_ARGS)
{ {
@@ -895,7 +828,7 @@ vector_sub(PG_FUNCTION_ARGS)
/* /*
* Multiply vectors * Multiply vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_mul); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_mul);
Datum Datum
vector_mul(PG_FUNCTION_ARGS) vector_mul(PG_FUNCTION_ARGS)
{ {
@@ -928,94 +861,25 @@ vector_mul(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
/*
* Concatenate vectors
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_concat);
Datum
vector_concat(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
Vector *result;
int dim = a->dim + b->dim;
CheckDim(dim);
result = InitVector(dim);
for (int i = 0; i < a->dim; i++)
result->x[i] = a->x[i];
for (int i = 0; i < b->dim; i++)
result->x[i + a->dim] = b->x[i];
PG_RETURN_POINTER(result);
}
/* /*
* Quantize a vector * Quantize a vector
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(binary_quantize); PGDLLEXPORT PG_FUNCTION_INFO_V1(quantize_binary);
Datum Datum
binary_quantize(PG_FUNCTION_ARGS) quantize_binary(PG_FUNCTION_ARGS)
{ {
Vector *a = PG_GETARG_VECTOR_P(0); Vector *a = PG_GETARG_VECTOR_P(0);
float *ax = a->x; float *ax = a->x;
VarBit *result = InitBitVector(a->dim); VarBit *result = InitBitVector(a->dim);
unsigned char *rx = VARBITS(result); unsigned char *rx = VARBITS(result);
/* TODO Improve */
for (int i = 0; i < a->dim; i++) for (int i = 0; i < a->dim; i++)
rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8)); rx[i / 8] |= (ax[i] > 0) << (7 - (i % 8));
PG_RETURN_VARBIT_P(result); PG_RETURN_VARBIT_P(result);
} }
/*
* Get a subvector
*/
FUNCTION_PREFIX 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;
float *ax = a->x;
Vector *result;
int dim;
if (count < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
/*
* Check if (start + count > a->dim), avoiding integer overflow. a->dim
* and count are both positive, so a->dim - count won't overflow.
*/
if (start > a->dim - count)
end = a->dim + 1;
else
end = start + count;
/* Indexing starts at 1, like substring */
if (start < 1)
start = 1;
else if (start > a->dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("vector must have at least 1 dimension")));
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
@@ -1047,85 +911,103 @@ vector_cmp_internal(Vector * a, Vector * b)
/* /*
* Less than * Less than
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_lt); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_lt);
Datum Datum
vector_lt(PG_FUNCTION_ARGS) 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);
} }
/* /*
* Less than or equal * Less than or equal
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_le); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_le);
Datum Datum
vector_le(PG_FUNCTION_ARGS) 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);
} }
/* /*
* Equal * Equal
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_eq); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_eq);
Datum Datum
vector_eq(PG_FUNCTION_ARGS) 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);
} }
/* /*
* Not equal * Not equal
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_ne); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_ne);
Datum Datum
vector_ne(PG_FUNCTION_ARGS) 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);
} }
/* /*
* Greater than or equal * Greater than or equal
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_ge); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_ge);
Datum Datum
vector_ge(PG_FUNCTION_ARGS) 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);
} }
/* /*
* Greater than * Greater than
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_gt); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_gt);
Datum Datum
vector_gt(PG_FUNCTION_ARGS) 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);
} }
/* /*
* Compare vectors * Compare vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_cmp); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_cmp);
Datum Datum
vector_cmp(PG_FUNCTION_ARGS) vector_cmp(PG_FUNCTION_ARGS)
{ {
@@ -1138,7 +1020,7 @@ vector_cmp(PG_FUNCTION_ARGS)
/* /*
* Accumulate vectors * Accumulate vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_accum); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_accum);
Datum Datum
vector_accum(PG_FUNCTION_ARGS) vector_accum(PG_FUNCTION_ARGS)
{ {
@@ -1197,13 +1079,12 @@ vector_accum(PG_FUNCTION_ARGS)
} }
/* /*
* Combine vectors or half vectors (also used for halfvec_combine) * Combine vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_combine); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_combine);
Datum Datum
vector_combine(PG_FUNCTION_ARGS) vector_combine(PG_FUNCTION_ARGS)
{ {
/* Must also update parameters of halfvec_combine if modifying */
ArrayType *statearray1 = PG_GETARG_ARRAYTYPE_P(0); ArrayType *statearray1 = PG_GETARG_ARRAYTYPE_P(0);
ArrayType *statearray2 = PG_GETARG_ARRAYTYPE_P(1); ArrayType *statearray2 = PG_GETARG_ARRAYTYPE_P(1);
float8 *statevalues1; float8 *statevalues1;
@@ -1270,7 +1151,7 @@ vector_combine(PG_FUNCTION_ARGS)
/* /*
* Average vectors * Average vectors
*/ */
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_avg); PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_avg);
Datum Datum
vector_avg(PG_FUNCTION_ARGS) vector_avg(PG_FUNCTION_ARGS)
{ {
@@ -1300,26 +1181,3 @@ vector_avg(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result); PG_RETURN_POINTER(result);
} }
/*
* Convert sparse vector to dense vector
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_to_vector);
Datum
sparsevec_to_vector(PG_FUNCTION_ARGS)
{
SparseVector *svec = PG_GETARG_SPARSEVEC_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
int dim = svec->dim;
float *values = SPARSEVEC_VALUES(svec);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitVector(dim);
for (int i = 0; i < svec->nnz; i++)
result->x[svec->indices[i]] = values[i];
PG_RETURN_POINTER(result);
}

View File

@@ -12,7 +12,7 @@ typedef struct Vector
{ {
int32 vl_len_; /* varlena header (do not touch directly!) */ int32 vl_len_; /* varlena header (do not touch directly!) */
int16 dim; /* number of dimensions */ int16 dim; /* number of dimensions */
int16 unused; /* reserved for future use, always zero */ int16 unused;
float x[FLEXIBLE_ARRAY_MEMBER]; float x[FLEXIBLE_ARRAY_MEMBER];
} Vector; } Vector;
@@ -20,11 +20,4 @@ Vector *InitVector(int dim);
void PrintVector(char *msg, Vector * vector); void PrintVector(char *msg, Vector * vector);
int vector_cmp_internal(Vector * a, Vector * b); int vector_cmp_internal(Vector * a, Vector * b);
/* TODO Move to better place */
#if PG_VERSION_NUM >= 160000
#define FUNCTION_PREFIX
#else
#define FUNCTION_PREFIX PGDLLEXPORT
#endif
#endif #endif

View File

@@ -1,140 +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('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101');
hamming_distance
------------------
0
(1 row)
SELECT hamming_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010');
hamming_distance
------------------
513
(1 row)
SELECT hamming_distance('110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011', '100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001');
hamming_distance
------------------
2
(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('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101');
jaccard_distance
------------------
0
(1 row)
SELECT jaccard_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011', '100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001');
jaccard_distance
------------------
0.5
(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

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

View File

@@ -1,5 +1,4 @@
SET enable_seqscan = off; SET enable_seqscan = off;
-- vector
CREATE TABLE t (val vector(3)); CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL); INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t (val); CREATE INDEX ON t (val);
@@ -9,73 +8,10 @@ SELECT * FROM t WHERE val = '[1,2,3]';
[1,2,3] [1,2,3]
(1 row) (1 row)
SELECT * FROM t ORDER BY val; SELECT * FROM t ORDER BY val LIMIT 1;
val val
--------- ---------
[0,0,0] [0,0,0]
[1,1,1]
[1,2,3]
(4 rows)
DROP TABLE t;
-- halfvec
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 (val);
SELECT * FROM t WHERE val = '[1,2,3]';
val
---------
[1,2,3]
(1 row) (1 row)
SELECT * FROM t ORDER BY val;
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
(4 rows)
DROP TABLE t;
-- minivec
CREATE TABLE t (val minivec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t (val);
SELECT * FROM t WHERE val = '[1,2,3]';
val
---------
[1,2,3]
(1 row)
SELECT * FROM t ORDER BY val;
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
(4 rows)
DROP TABLE t;
-- sparsevec
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 (val);
SELECT * FROM t WHERE val = '{1:1,2:2,3:3}/3';
val
-----------------
{1:1,2:2,3:3}/3
(1 row)
SELECT * FROM t ORDER BY val;
val
-----------------
{}/3
{1:1,2:1,3:1}/3
{1:1,2:2,3:3}/3
(4 rows)
DROP TABLE t; DROP TABLE t;

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;
@@ -60,268 +40,12 @@ 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) (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)
SELECT '[1,2,3]'::vector::halfvec;
halfvec
---------
[1,2,3]
(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;
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{1,2,3}'::real[]::halfvec;
halfvec
---------
[1,2,3]
(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 '[1,2,3]'::vector::minivec;
minivec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::minivec(3);
minivec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector::minivec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[465]'::vector::minivec;
ERROR: "465" is out of range for type minivec
SELECT '[1e-8]'::vector::minivec;
minivec
---------
[0]
(1 row)
SELECT '[1,2,3]'::minivec::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::minivec::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::minivec::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '{1,2,3}'::real[]::minivec;
minivec
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::minivec(3);
minivec
---------
[1,2,3]
(1 row)
SELECT '{1,2,3}'::real[]::minivec(2);
ERROR: expected 2 dimensions, not 3
SELECT '{465,-465}'::real[]::minivec;
ERROR: "465" is out of range for type minivec
SELECT '{1e-8,-1e-8}'::real[]::minivec;
minivec
---------
[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 '[0,1.5,0,3.5,0]'::halfvec::sparsevec;
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec(5);
sparsevec
-----------------
{2:1.5,4:3.5}/5
(1 row)
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec(4);
ERROR: expected 4 dimensions, not 5
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec;
halfvec
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec(5);
halfvec
-----------------
[0,1.5,0,3.5,0]
(1 row)
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec(4);
ERROR: expected 4 dimensions, not 5
SELECT '{}/16001'::sparsevec::halfvec;
ERROR: halfvec cannot have more than 16000 dimensions
SELECT '{1:65520}/1'::sparsevec::halfvec;
ERROR: "65520" is out of range for type halfvec
SELECT '{1:1e-8}/1'::sparsevec::halfvec;
halfvec
---------
[0]
(1 row)
SELECT ARRAY[1,0,2,0,3,0]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT ARRAY[1.0,0.0,2.0,0.0,3.0,0.0]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT ARRAY[1,0,2,0,3,0]::float4[]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT ARRAY[1,0,2,0,3,0]::float8[]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT ARRAY[1,0,2,0,3,0]::numeric[]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec;
sparsevec
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(6);
sparsevec
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(5);
ERROR: expected 5 dimensions, not 6
SELECT '{NULL}'::real[]::sparsevec;
ERROR: array must not contain nulls
SELECT '{NaN}'::real[]::sparsevec;
ERROR: NaN not allowed in sparsevec
SELECT '{Infinity}'::real[]::sparsevec;
ERROR: infinite value not allowed in sparsevec
SELECT '{-Infinity}'::real[]::sparsevec;
ERROR: infinite value not allowed in sparsevec
SELECT '{}'::real[]::sparsevec;
ERROR: sparsevec must have at least 1 dimension
SELECT '{{1}}'::real[]::sparsevec;
ERROR: array must be 1-D
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

@@ -1,9 +1,8 @@
-- vector
CREATE TABLE t (val vector(3)); CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL); INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val vector(3)); CREATE TABLE t2 (val vector(3));
\copy t TO 'results/vector.bin' WITH (FORMAT binary) \copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/vector.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 val
--------- ---------
@@ -15,54 +14,3 @@ SELECT * FROM t2 ORDER BY val;
DROP TABLE t; DROP TABLE t;
DROP TABLE t2; DROP TABLE t2;
-- halfvec
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val halfvec(3));
\copy t TO 'results/halfvec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/halfvec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
(4 rows)
DROP TABLE t;
DROP TABLE t2;
-- minivec
CREATE TABLE t (val minivec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val minivec(3));
\copy t TO 'results/minivec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/minivec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
(4 rows)
DROP TABLE t;
DROP TABLE t2;
-- sparsevec
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 TABLE t2 (val sparsevec(3));
\copy t TO 'results/sparsevec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/sparsevec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
val
-----------------
{}/3
{1:1,2:1,3:1}/3
{1:1,2:2,3:3}/3
(4 rows)
DROP TABLE t;
DROP TABLE t2;

272
test/expected/functions.out Normal file
View File

@@ -0,0 +1,272 @@
SELECT '[1,2,3]'::vector + '[4,5,6]';
?column?
----------
[5,7,9]
(1 row)
SELECT '[3e38]'::vector + '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2,3]'::vector - '[4,5,6]';
?column?
------------
[-3,-3,-3]
(1 row)
SELECT '[-3e38]'::vector - '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2,3]'::vector * '[4,5,6]';
?column?
-----------
[4,10,18]
(1 row)
SELECT '[1e37]'::vector * '[1e37]';
ERROR: value out of range: overflow
SELECT '[1e-37]'::vector * '[1e-37]';
ERROR: value out of range: underflow
SELECT '[1,2,3]'::vector = '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector = '[1,2]';
ERROR: different vector dimensions 3 and 2
SELECT vector_cmp('[1,2,3]', '[1,2,3]');
vector_cmp
------------
0
(1 row)
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
vector_cmp
------------
1
(1 row)
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[1,2]', '[1,2,3]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[1,2,3]', '[1,2]');
vector_cmp
------------
1
(1 row)
SELECT vector_cmp('[1,2]', '[2,3,4]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[2,3]', '[1,2,3]');
vector_cmp
------------
1
(1 row)
SELECT vector_dims('[1,2,3]');
vector_dims
-------------
3
(1 row)
SELECT round(vector_norm('[1,1]')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT vector_norm('[3,4]');
vector_norm
-------------
5
(1 row)
SELECT vector_norm('[0,1]');
vector_norm
-------------
1
(1 row)
SELECT vector_norm('[3e37,4e37]')::real;
vector_norm
-------------
5e+37
(1 row)
SELECT l2_distance('[0,0]', '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]', '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l2_distance('[3e38]', '[-3e38]');
l2_distance
-------------
Infinity
(1 row)
SELECT inner_product('[1,2]', '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT inner_product('[3e38]', '[3e38]');
inner_product
---------------
Infinity
(1 row)
SELECT cosine_distance('[1,2]', '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]', '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]', '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]', '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]', '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[3e38]', '[3e38]');
cosine_distance
-----------------
NaN
(1 row)
SELECT l1_distance('[0,0]', '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]', '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]', '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l1_distance('[3e38]', '[-3e38]');
l1_distance
-------------
Infinity
(1 row)
SELECT quantize_binary('[1,0,-1]');
quantize_binary
-----------------
100
(1 row)
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]');
quantize_binary
-----------------
01001110101
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
avg
-----
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: expected 2 dimensions, not 1
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
avg
---------
[3e+38]
(1 row)
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
ERROR: vector cannot have more than 16000 dimensions
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
sum
-----
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: different vector dimensions 2 and 1
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
ERROR: value out of range: overflow

View File

@@ -1,636 +0,0 @@
SELECT '[1,2,3]'::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[-1,-2,-3]'::halfvec;
halfvec
------------
[-1,-2,-3]
(1 row)
SELECT '[1.,2.,3.]'::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT ' [ 1, 2 , 3 ] '::halfvec;
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1.23456]'::halfvec;
halfvec
------------
[1.234375]
(1 row)
SELECT '[hello,1]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[hello,1]"
LINE 1: SELECT '[hello,1]'::halfvec;
^
SELECT '[NaN,1]'::halfvec;
ERROR: NaN not allowed in halfvec
LINE 1: SELECT '[NaN,1]'::halfvec;
^
SELECT '[Infinity,1]'::halfvec;
ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[Infinity,1]'::halfvec;
^
SELECT '[-Infinity,1]'::halfvec;
ERROR: infinite value not allowed in halfvec
LINE 1: SELECT '[-Infinity,1]'::halfvec;
^
SELECT '[65519,-65519]'::halfvec;
halfvec
----------------
[65504,-65504]
(1 row)
SELECT '[65520,-65520]'::halfvec;
ERROR: "65520" is out of range for type halfvec
LINE 1: SELECT '[65520,-65520]'::halfvec;
^
SELECT '[1e-8,-1e-8]'::halfvec;
halfvec
---------
[0,-0]
(1 row)
SELECT '[4e38,1]'::halfvec;
ERROR: "4e38" is out of range for type halfvec
LINE 1: SELECT '[4e38,1]'::halfvec;
^
SELECT '[1e-46,1]'::halfvec;
halfvec
---------
[0,1]
(1 row)
SELECT '[1,2,3'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,2,3"
LINE 1: SELECT '[1,2,3'::halfvec;
^
SELECT '[1,2,3]9'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::halfvec;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::halfvec;
ERROR: invalid input syntax for type halfvec: "1,2,3"
LINE 1: SELECT '1,2,3'::halfvec;
^
DETAIL: Vector contents must start with "[".
SELECT ''::halfvec;
ERROR: invalid input syntax for type halfvec: ""
LINE 1: SELECT ''::halfvec;
^
DETAIL: Vector contents must start with "[".
SELECT '['::halfvec;
ERROR: invalid input syntax for type halfvec: "["
LINE 1: SELECT '['::halfvec;
^
SELECT '[ '::halfvec;
ERROR: invalid input syntax for type halfvec: "[ "
LINE 1: SELECT '[ '::halfvec;
^
SELECT '[,'::halfvec;
ERROR: invalid input syntax for type halfvec: "[,"
LINE 1: SELECT '[,'::halfvec;
^
SELECT '[]'::halfvec;
ERROR: halfvec must have at least 1 dimension
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;
ERROR: invalid input syntax for type halfvec: "[1,]"
LINE 1: SELECT '[1,]'::halfvec;
^
SELECT '[1a]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1a]"
LINE 1: SELECT '[1a]'::halfvec;
^
SELECT '[1,,3]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1,,3]"
LINE 1: SELECT '[1,,3]'::halfvec;
^
SELECT '[1, ,3]'::halfvec;
ERROR: invalid input syntax for type halfvec: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::halfvec;
^
SELECT '[1,2,3]'::halfvec(3);
halfvec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::halfvec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::halfvec(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::halfvec(3, 2);
^
SELECT '[1,2,3]'::halfvec('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::halfvec('a');
^
SELECT '[1,2,3]'::halfvec(0);
ERROR: dimensions for type halfvec must be at least 1
LINE 1: SELECT '[1,2,3]'::halfvec(0);
^
SELECT '[1,2,3]'::halfvec(16001);
ERROR: dimensions for type halfvec cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::halfvec(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::halfvec[]);
unnest
---------
[1,2,3]
[4,5,6]
(2 rows)
SELECT '{"[1,2,3]"}'::halfvec(2)[];
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::halfvec + '[4,5,6]';
?column?
----------
[5,7,9]
(1 row)
SELECT '[65519]'::halfvec + '[65519]';
ERROR: value out of range: overflow
SELECT '[1,2]'::halfvec + '[3]';
ERROR: different halfvec dimensions 2 and 1
SELECT '[1,2,3]'::halfvec - '[4,5,6]';
?column?
------------
[-3,-3,-3]
(1 row)
SELECT '[-65519]'::halfvec - '[65519]';
ERROR: value out of range: overflow
SELECT '[1,2]'::halfvec - '[3]';
ERROR: different halfvec dimensions 2 and 1
SELECT '[1,2,3]'::halfvec * '[4,5,6]';
?column?
-----------
[4,10,18]
(1 row)
SELECT '[65519]'::halfvec * '[65519]';
ERROR: value out of range: overflow
SELECT '[1e-7]'::halfvec * '[1e-7]';
ERROR: value out of range: underflow
SELECT '[1,2]'::halfvec * '[3]';
ERROR: different halfvec dimensions 2 and 1
SELECT '[1,2,3]'::halfvec || '[4,5]';
?column?
-------------
[1,2,3,4,5]
(1 row)
SELECT array_fill(0, ARRAY[16000])::halfvec || '[1]';
ERROR: halfvec cannot have more than 16000 dimensions
SELECT '[1,2,3]'::halfvec < '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec < '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec <= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec <= '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec = '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec = '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec != '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec != '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec >= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec >= '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::halfvec > '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::halfvec > '[1,2]';
?column?
----------
t
(1 row)
SELECT halfvec_cmp('[1,2,3]', '[1,2,3]');
halfvec_cmp
-------------
0
(1 row)
SELECT halfvec_cmp('[1,2,3]', '[0,0,0]');
halfvec_cmp
-------------
1
(1 row)
SELECT halfvec_cmp('[0,0,0]', '[1,2,3]');
halfvec_cmp
-------------
-1
(1 row)
SELECT halfvec_cmp('[1,2]', '[1,2,3]');
halfvec_cmp
-------------
-1
(1 row)
SELECT halfvec_cmp('[1,2,3]', '[1,2]');
halfvec_cmp
-------------
1
(1 row)
SELECT halfvec_cmp('[1,2]', '[2,3,4]');
halfvec_cmp
-------------
-1
(1 row)
SELECT halfvec_cmp('[2,3]', '[1,2,3]');
halfvec_cmp
-------------
1
(1 row)
SELECT vector_dims('[1,2,3]'::halfvec);
vector_dims
-------------
3
(1 row)
SELECT round(l2_norm('[1,1]'::halfvec)::numeric, 5);
round
---------
1.41421
(1 row)
SELECT l2_norm('[3,4]'::halfvec);
l2_norm
---------
5
(1 row)
SELECT l2_norm('[0,1]'::halfvec);
l2_norm
---------
1
(1 row)
SELECT l2_norm('[0,0]'::halfvec);
l2_norm
---------
0
(1 row)
SELECT l2_norm('[2]'::halfvec);
l2_norm
---------
2
(1 row)
SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]'::halfvec, '[3]');
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]';
?column?
----------
5
(1 row)
SELECT inner_product('[1,2]'::halfvec, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT inner_product('[65504]'::halfvec, '[65504]');
inner_product
---------------
4290774016
(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]';
?column?
----------
-11
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]'::halfvec, '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT cosine_distance('[1,1]'::halfvec, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]'::halfvec, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[-1,-2,-3,-4,-5,-6,-7,-8,-9]');
cosine_distance
-----------------
2
(1 row)
SELECT '[1,2]'::halfvec <=> '[2,4]';
?column?
----------
0
(1 row)
SELECT l1_distance('[0,0]'::halfvec, '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]'::halfvec, '[3]');
ERROR: different halfvec dimensions 2 and 1
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
l1_distance
-------------
0
(1 row)
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[0,3,2,5,4,7,6,9,8]');
l1_distance
-------------
9
(1 row)
SELECT '[0,0]'::halfvec <+> '[3,4]';
?column?
----------
7
(1 row)
SELECT l2_normalize('[3,4]'::halfvec);
l2_normalize
------------------------
[0.60009766,0.7998047]
(1 row)
SELECT l2_normalize('[3,0]'::halfvec);
l2_normalize
--------------
[1,0]
(1 row)
SELECT l2_normalize('[0,0.1]'::halfvec);
l2_normalize
--------------
[0,1]
(1 row)
SELECT l2_normalize('[0,0]'::halfvec);
l2_normalize
--------------
[0,0]
(1 row)
SELECT l2_normalize('[65504]'::halfvec);
l2_normalize
--------------
[1]
(1 row)
SELECT binary_quantize('[1,0,-1]'::halfvec);
binary_quantize
-----------------
100
(1 row)
SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::halfvec);
binary_quantize
-----------------
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
SELECT subvector('[1,2,3,4,5]'::halfvec, 2147483647, 10);
ERROR: halfvec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2147483647);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::halfvec, -2147483644, 2147483647);
subvector
-----------
[1,2]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]']) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]', NULL]) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY[]::halfvec[]) v;
avg
-----
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::halfvec, '[3]']) v;
ERROR: expected 2 dimensions, not 1
SELECT avg(v) FROM unnest(ARRAY['[65504]'::halfvec, '[65504]']) v;
avg
---------
[65504]
(1 row)
SELECT halfvec_avg(array_agg(n)) FROM generate_series(1, 16002) n;
ERROR: halfvec cannot have more than 16000 dimensions
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]']) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]', NULL]) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY[]::halfvec[]) v;
sum
-----
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::halfvec, '[3]']) v;
ERROR: different halfvec dimensions 2 and 1
SELECT sum(v) FROM unnest(ARRAY['[65504]'::halfvec, '[65504]']) v;
ERROR: value out of range: overflow

View File

@@ -1,51 +0,0 @@
SET enable_seqscan = off;
-- hamming
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;
-- jaccard
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;
-- varbit
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

@@ -0,0 +1,26 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_cosine_ops);
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::vector)) t2;
count
-------
3
(1 row)
DROP TABLE t;

View File

@@ -1,102 +0,0 @@
SET enable_seqscan = off;
-- L2
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 hnsw (val halfvec_l2_ops);
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;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;
-- inner product
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 hnsw (val halfvec_ip_ops);
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;
-- cosine
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 hnsw (val halfvec_cosine_ops);
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;
-- L1
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 hnsw (val halfvec_l1_ops);
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)
DROP TABLE t;

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

21
test/expected/hnsw_ip.out Normal file
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@@ -0,0 +1,21 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_ip_ops);
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::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;

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

36
test/expected/hnsw_l2.out Normal file
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@@ -0,0 +1,36 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,2,4]
[1,1,1]
[0,0,0]
(4 rows)
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;

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@@ -0,0 +1,26 @@
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 1);
ERROR: value 1 out of bounds for option "m"
DETAIL: Valid values are between "2" and "100".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
ERROR: value 101 out of bounds for option "m"
DETAIL: Valid values are between "2" and "100".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
ERROR: value 3 out of bounds for option "ef_construction"
DETAIL: Valid values are between "4" and "1000".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
ERROR: value 1001 out of bounds for option "ef_construction"
DETAIL: Valid values are between "4" and "1000".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
ERROR: ef_construction must be greater than or equal to 2 * m
SHOW hnsw.ef_search;
hnsw.ef_search
----------------
40
(1 row)
SET hnsw.ef_search = 0;
ERROR: 0 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
SET hnsw.ef_search = 1001;
ERROR: 1001 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
DROP TABLE t;

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@@ -1,112 +0,0 @@
SET enable_seqscan = off;
-- L2
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;
-- inner product
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;
-- cosine
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;
-- L1
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_l1_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)
DROP TABLE t;
-- non-zero elements
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;

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@@ -0,0 +1,13 @@
SET enable_seqscan = off;
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
DROP TABLE t;

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@@ -1,142 +0,0 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
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::vector)) t2;
count
-------
4
(1 row)
SELECT COUNT(*) FROM t;
count
-------
5
(1 row)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
DROP TABLE t;
-- inner product
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_ip_ops);
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::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- cosine
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_cosine_ops);
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::vector)) t2;
count
-------
3
(1 row)
DROP TABLE t;
-- L1
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l1_ops);
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::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
DROP TABLE t;
-- options
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 1);
ERROR: value 1 out of bounds for option "m"
DETAIL: Valid values are between "2" and "100".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
ERROR: value 101 out of bounds for option "m"
DETAIL: Valid values are between "2" and "100".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
ERROR: value 3 out of bounds for option "ef_construction"
DETAIL: Valid values are between "4" and "1000".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
ERROR: value 1001 out of bounds for option "ef_construction"
DETAIL: Valid values are between "4" and "1000".
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
ERROR: ef_construction must be greater than or equal to 2 * m
SHOW hnsw.ef_search;
hnsw.ef_search
----------------
40
(1 row)
SET hnsw.ef_search = 0;
ERROR: 0 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
SET hnsw.ef_search = 1001;
ERROR: 1001 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
DROP TABLE t;

151
test/expected/input.out Normal file
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@@ -0,0 +1,151 @@
SELECT '[1,2,3]'::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[-1,-2,-3]'::vector;
vector
------------
[-1,-2,-3]
(1 row)
SELECT '[1.,2.,3.]'::vector;
vector
---------
[1,2,3]
(1 row)
SELECT ' [ 1, 2 , 3 ] '::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[1.23456]'::vector;
vector
-----------
[1.23456]
(1 row)
SELECT '[hello,1]'::vector;
ERROR: invalid input syntax for type vector: "[hello,1]"
LINE 1: SELECT '[hello,1]'::vector;
^
SELECT '[NaN,1]'::vector;
ERROR: NaN not allowed in vector
LINE 1: SELECT '[NaN,1]'::vector;
^
SELECT '[Infinity,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[Infinity,1]'::vector;
^
SELECT '[-Infinity,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[-Infinity,1]'::vector;
^
SELECT '[1.5e38,-1.5e38]'::vector;
vector
--------------------
[1.5e+38,-1.5e+38]
(1 row)
SELECT '[1.5e+38,-1.5e+38]'::vector;
vector
--------------------
[1.5e+38,-1.5e+38]
(1 row)
SELECT '[1.5e-38,-1.5e-38]'::vector;
vector
--------------------
[1.5e-38,-1.5e-38]
(1 row)
SELECT '[4e38,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[4e38,1]'::vector;
^
SELECT '[1,2,3'::vector;
ERROR: malformed vector literal: "[1,2,3"
LINE 1: SELECT '[1,2,3'::vector;
^
DETAIL: Unexpected end of input.
SELECT '[1,2,3]9'::vector;
ERROR: malformed vector literal: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::vector;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::vector;
ERROR: malformed vector literal: "1,2,3"
LINE 1: SELECT '1,2,3'::vector;
^
DETAIL: Vector contents must start with "[".
SELECT ''::vector;
ERROR: malformed vector literal: ""
LINE 1: SELECT ''::vector;
^
DETAIL: Vector contents must start with "[".
SELECT '['::vector;
ERROR: malformed vector literal: "["
LINE 1: SELECT '['::vector;
^
DETAIL: Unexpected end of input.
SELECT '[,'::vector;
ERROR: malformed vector literal: "[,"
LINE 1: SELECT '[,'::vector;
^
DETAIL: Unexpected end of input.
SELECT '[]'::vector;
ERROR: vector must have at least 1 dimension
LINE 1: SELECT '[]'::vector;
^
SELECT '[1,]'::vector;
ERROR: invalid input syntax for type vector: "[1,]"
LINE 1: SELECT '[1,]'::vector;
^
SELECT '[1a]'::vector;
ERROR: invalid input syntax for type vector: "[1a]"
LINE 1: SELECT '[1a]'::vector;
^
SELECT '[1,,3]'::vector;
ERROR: malformed vector literal: "[1,,3]"
LINE 1: SELECT '[1,,3]'::vector;
^
SELECT '[1, ,3]'::vector;
ERROR: invalid input syntax for type vector: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::vector;
^
SELECT '[1,2,3]'::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::vector(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::vector(3, 2);
^
SELECT '[1,2,3]'::vector('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::vector('a');
^
SELECT '[1,2,3]'::vector(0);
ERROR: dimensions for type vector must be at least 1
LINE 1: SELECT '[1,2,3]'::vector(0);
^
SELECT '[1,2,3]'::vector(16001);
ERROR: dimensions for type vector cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::vector(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
unnest
---------
[1,2,3]
[4,5,6]
(2 rows)
SELECT '{"[1,2,3]"}'::vector(2)[];
ERROR: expected 2 dimensions, not 3

View File

@@ -1,37 +0,0 @@
SET enable_seqscan = off;
-- hamming
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops) WITH (lists = 1);
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;
-- varbit
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops) WITH (lists = 1);
ERROR: type not supported for ivfflat index
CREATE INDEX ON t USING ivfflat ((val::bit(3)) bit_hamming_ops) WITH (lists = 1);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
CREATE INDEX ON t USING ivfflat ((val::bit(64001)) bit_hamming_ops) WITH (lists = 1);
ERROR: column cannot have more than 64000 dimensions for ivfflat index
CREATE INDEX ON t USING ivfflat ((val::bit(2)) bit_hamming_ops) WITH (lists = 5);
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
DROP TABLE t;

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@@ -0,0 +1,26 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_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::vector)) t2;
count
-------
3
(1 row)
DROP TABLE t;

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@@ -1,84 +0,0 @@
SET enable_seqscan = off;
-- L2
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;
-- inner product
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;
-- cosine
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;

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@@ -0,0 +1,21 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_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::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;

View File

@@ -0,0 +1,39 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_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 * FROM t ORDER BY val <-> (SELECT NULL::vector);
val
---------
[0,0,0]
[1,1,1]
[1,2,3]
[1,2,4]
(4 rows)
SELECT COUNT(*) FROM t;
count
-------
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

@@ -1,84 +0,0 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val minivec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val minivec_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::minivec)) 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;
-- inner product
CREATE TABLE t (val minivec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val minivec_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::minivec)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- cosine
CREATE TABLE t (val minivec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val minivec_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::minivec)) t2;
count
-------
3
(1 row)
DROP TABLE t;

View File

@@ -0,0 +1,14 @@
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 0);
ERROR: value 0 out of bounds for option "lists"
DETAIL: Valid values are between "1" and "32768".
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
ERROR: value 32769 out of bounds for option "lists"
DETAIL: Valid values are between "1" and "32768".
SHOW ivfflat.probes;
ivfflat.probes
----------------
1
(1 row)
DROP TABLE t;

View File

@@ -0,0 +1,13 @@
SET enable_seqscan = off;
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
DROP TABLE t;

View File

@@ -1,112 +0,0 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_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::vector)) 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;
-- inner product
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_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::vector)) t2;
count
-------
4
(1 row)
DROP TABLE t;
-- cosine
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_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::vector)) t2;
count
-------
3
(1 row)
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 1);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
---------
[1,2,3]
[1,1,1]
[0,0,0]
(3 rows)
DROP TABLE t;
-- options
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 0);
ERROR: value 0 out of bounds for option "lists"
DETAIL: Valid values are between "1" and "32768".
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
ERROR: value 32769 out of bounds for option "lists"
DETAIL: Valid values are between "1" and "32768".
SHOW ivfflat.probes;
ivfflat.probes
----------------
1
(1 row)
DROP TABLE t;

View File

@@ -1,588 +0,0 @@
SELECT '[1,2,3]'::minivec;
minivec
---------
[1,2,3]
(1 row)
SELECT '[-1,-2,-3]'::minivec;
minivec
------------
[-1,-2,-3]
(1 row)
SELECT '[1.,2.,3.]'::minivec;
minivec
---------
[1,2,3]
(1 row)
SELECT ' [ 1, 2 , 3 ] '::minivec;
minivec
---------
[1,2,3]
(1 row)
SELECT '[1.23456]'::minivec;
minivec
---------
[1.25]
(1 row)
SELECT '[hello,1]'::minivec;
ERROR: invalid input syntax for type minivec: "[hello,1]"
LINE 1: SELECT '[hello,1]'::minivec;
^
SELECT '[NaN,1]'::minivec;
ERROR: NaN not allowed in minivec
LINE 1: SELECT '[NaN,1]'::minivec;
^
SELECT '[Infinity,1]'::minivec;
ERROR: "Infinity" is out of range for type minivec
LINE 1: SELECT '[Infinity,1]'::minivec;
^
SELECT '[-Infinity,1]'::minivec;
ERROR: "-Infinity" is out of range for type minivec
LINE 1: SELECT '[-Infinity,1]'::minivec;
^
SELECT '[65519,-65519]'::minivec;
ERROR: "65519" is out of range for type minivec
LINE 1: SELECT '[65519,-65519]'::minivec;
^
SELECT '[65520,-65520]'::minivec;
ERROR: "65520" is out of range for type minivec
LINE 1: SELECT '[65520,-65520]'::minivec;
^
SELECT '[1e-8,-1e-8]'::minivec;
minivec
---------
[0,-0]
(1 row)
SELECT '[4e38,1]'::minivec;
ERROR: "4e38" is out of range for type minivec
LINE 1: SELECT '[4e38,1]'::minivec;
^
SELECT '[1e-46,1]'::minivec;
minivec
---------
[0,1]
(1 row)
SELECT '[1,2,3'::minivec;
ERROR: invalid input syntax for type minivec: "[1,2,3"
LINE 1: SELECT '[1,2,3'::minivec;
^
SELECT '[1,2,3]9'::minivec;
ERROR: invalid input syntax for type minivec: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::minivec;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::minivec;
ERROR: invalid input syntax for type minivec: "1,2,3"
LINE 1: SELECT '1,2,3'::minivec;
^
DETAIL: Vector contents must start with "[".
SELECT ''::minivec;
ERROR: invalid input syntax for type minivec: ""
LINE 1: SELECT ''::minivec;
^
DETAIL: Vector contents must start with "[".
SELECT '['::minivec;
ERROR: invalid input syntax for type minivec: "["
LINE 1: SELECT '['::minivec;
^
SELECT '[ '::minivec;
ERROR: invalid input syntax for type minivec: "[ "
LINE 1: SELECT '[ '::minivec;
^
SELECT '[,'::minivec;
ERROR: invalid input syntax for type minivec: "[,"
LINE 1: SELECT '[,'::minivec;
^
SELECT '[]'::minivec;
ERROR: minivec must have at least 1 dimension
LINE 1: SELECT '[]'::minivec;
^
SELECT '[ ]'::minivec;
ERROR: minivec must have at least 1 dimension
LINE 1: SELECT '[ ]'::minivec;
^
SELECT '[,]'::minivec;
ERROR: invalid input syntax for type minivec: "[,]"
LINE 1: SELECT '[,]'::minivec;
^
SELECT '[1,]'::minivec;
ERROR: invalid input syntax for type minivec: "[1,]"
LINE 1: SELECT '[1,]'::minivec;
^
SELECT '[1a]'::minivec;
ERROR: invalid input syntax for type minivec: "[1a]"
LINE 1: SELECT '[1a]'::minivec;
^
SELECT '[1,,3]'::minivec;
ERROR: invalid input syntax for type minivec: "[1,,3]"
LINE 1: SELECT '[1,,3]'::minivec;
^
SELECT '[1, ,3]'::minivec;
ERROR: invalid input syntax for type minivec: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::minivec;
^
SELECT '[1,2,3]'::minivec(3);
minivec
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::minivec(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::minivec(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::minivec(3, 2);
^
SELECT '[1,2,3]'::minivec('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::minivec('a');
^
SELECT '[1,2,3]'::minivec(0);
ERROR: dimensions for type minivec must be at least 1
LINE 1: SELECT '[1,2,3]'::minivec(0);
^
SELECT '[1,2,3]'::minivec(16001);
ERROR: dimensions for type minivec cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::minivec(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::minivec[]);
unnest
---------
[1,2,3]
[4,5,6]
(2 rows)
SELECT '{"[1,2,3]"}'::minivec(2)[];
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::minivec + '[4,5,6]';
?column?
----------
[5,7,9]
(1 row)
SELECT '[448]'::minivec + '[448]';
ERROR: value out of range: overflow
SELECT '[1,2]'::minivec + '[3]';
ERROR: different minivec dimensions 2 and 1
SELECT '[1,2,3]'::minivec - '[4,5,6]';
?column?
------------
[-3,-3,-3]
(1 row)
SELECT '[-448]'::minivec - '[448]';
ERROR: value out of range: overflow
SELECT '[1,2]'::minivec - '[3]';
ERROR: different minivec dimensions 2 and 1
SELECT '[1,2,3]'::minivec * '[4,5,6]';
?column?
-----------
[4,10,18]
(1 row)
SELECT '[448]'::minivec * '[448]';
ERROR: value out of range: overflow
SELECT '[1e-7]'::minivec * '[1e-7]';
?column?
----------
[0]
(1 row)
SELECT '[1,2]'::minivec * '[3]';
ERROR: different minivec dimensions 2 and 1
SELECT '[1,2,3]'::minivec || '[4,5]';
?column?
-------------
[1,2,3,4,5]
(1 row)
SELECT array_fill(0, ARRAY[16000])::minivec || '[1]';
ERROR: minivec cannot have more than 16000 dimensions
SELECT '[1,2,3]'::minivec < '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::minivec < '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::minivec <= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::minivec <= '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::minivec = '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::minivec = '[1,2]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::minivec != '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::minivec != '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::minivec >= '[1,2,3]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::minivec >= '[1,2]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::minivec > '[1,2,3]';
?column?
----------
f
(1 row)
SELECT '[1,2,3]'::minivec > '[1,2]';
?column?
----------
t
(1 row)
SELECT minivec_cmp('[1,2,3]', '[1,2,3]');
minivec_cmp
-------------
0
(1 row)
SELECT minivec_cmp('[1,2,3]', '[0,0,0]');
minivec_cmp
-------------
1
(1 row)
SELECT minivec_cmp('[0,0,0]', '[1,2,3]');
minivec_cmp
-------------
-1
(1 row)
SELECT minivec_cmp('[1,2]', '[1,2,3]');
minivec_cmp
-------------
-1
(1 row)
SELECT minivec_cmp('[1,2,3]', '[1,2]');
minivec_cmp
-------------
1
(1 row)
SELECT minivec_cmp('[1,2]', '[2,3,4]');
minivec_cmp
-------------
-1
(1 row)
SELECT minivec_cmp('[2,3]', '[1,2,3]');
minivec_cmp
-------------
1
(1 row)
SELECT vector_dims('[1,2,3]'::minivec);
vector_dims
-------------
3
(1 row)
SELECT round(l2_norm('[1,1]'::minivec)::numeric, 5);
round
---------
1.41421
(1 row)
SELECT l2_norm('[3,4]'::minivec);
l2_norm
---------
5
(1 row)
SELECT l2_norm('[0,1]'::minivec);
l2_norm
---------
1
(1 row)
SELECT l2_norm('[0,0]'::minivec);
l2_norm
---------
0
(1 row)
SELECT l2_norm('[2]'::minivec);
l2_norm
---------
2
(1 row)
SELECT l2_distance('[0,0]'::minivec, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]'::minivec, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]'::minivec, '[3]');
ERROR: different minivec dimensions 2 and 1
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::minivec, '[1,1,1,1,1,1,1,4,5]');
l2_distance
-------------
5
(1 row)
SELECT '[0,0]'::minivec <-> '[3,4]';
?column?
----------
5
(1 row)
SELECT inner_product('[1,2]'::minivec, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]'::minivec, '[3]');
ERROR: different minivec dimensions 2 and 1
SELECT inner_product('[448]'::minivec, '[448]');
inner_product
---------------
200704
(1 row)
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::minivec, '[1,2,3,4,5,6,7,8,9]');
inner_product
---------------
45
(1 row)
SELECT '[1,2]'::minivec <#> '[3,4]';
?column?
----------
-11
(1 row)
SELECT cosine_distance('[1,2]'::minivec, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]'::minivec, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]'::minivec, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]'::minivec, '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]'::minivec, '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]'::minivec, '[3]');
ERROR: different minivec dimensions 2 and 1
SELECT cosine_distance('[1,1]'::minivec, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]'::minivec, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::minivec, '[1,2,3,4,5,6,7,8,9]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::minivec, '[-1,-2,-3,-4,-5,-6,-7,-8,-9]');
cosine_distance
-----------------
2
(1 row)
SELECT '[1,2]'::minivec <=> '[2,4]';
?column?
----------
0
(1 row)
SELECT l1_distance('[0,0]'::minivec, '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]'::minivec, '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]'::minivec, '[3]');
ERROR: different minivec dimensions 2 and 1
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::minivec, '[1,2,3,4,5,6,7,8,9]');
l1_distance
-------------
0
(1 row)
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::minivec, '[0,3,2,5,4,7,6,9,8]');
l1_distance
-------------
9
(1 row)
SELECT '[0,0]'::minivec <+> '[3,4]';
?column?
----------
7
(1 row)
SELECT l2_normalize('[3,4]'::minivec);
l2_normalize
----------------
[0.625,0.8125]
(1 row)
SELECT l2_normalize('[3,0]'::minivec);
l2_normalize
--------------
[1,0]
(1 row)
SELECT l2_normalize('[0,0.1]'::minivec);
l2_normalize
--------------
[0,1]
(1 row)
SELECT l2_normalize('[0,0]'::minivec);
l2_normalize
--------------
[0,0]
(1 row)
SELECT l2_normalize('[448]'::minivec);
l2_normalize
--------------
[1]
(1 row)
SELECT binary_quantize('[1,0,-1]'::minivec);
binary_quantize
-----------------
100
(1 row)
SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::minivec);
binary_quantize
-----------------
01001110101
(1 row)
SELECT subvector('[1,2,3,4,5]'::minivec, 1, 3);
subvector
-----------
[1,2,3]
(1 row)
SELECT subvector('[1,2,3,4,5]'::minivec, 3, 2);
subvector
-----------
[3,4]
(1 row)
SELECT subvector('[1,2,3,4,5]'::minivec, -1, 3);
subvector
-----------
[1]
(1 row)
SELECT subvector('[1,2,3,4,5]'::minivec, 3, 9);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::minivec, 1, 0);
ERROR: minivec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::minivec, 3, -1);
ERROR: minivec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::minivec, -1, 2);
ERROR: minivec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::minivec, 2147483647, 10);
ERROR: minivec must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::minivec, 3, 2147483647);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::minivec, -2147483644, 2147483647);
subvector
-----------
[1,2]
(1 row)

View File

@@ -1,653 +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;
sparsevec
-------------
{1:1,2:1}/2
(1 row)
SELECT '{1:1,1:1}/2'::sparsevec;
ERROR: sparsevec indices must not contain duplicates
LINE 1: SELECT '{1:1,1:1}/2'::sparsevec;
^
SELECT '{1:1,2:1,1:1}/2'::sparsevec;
ERROR: sparsevec indices must not contain duplicates
LINE 1: SELECT '{1:1,2:1,1:1}/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 '{}/1000000001'::sparsevec;
ERROR: sparsevec cannot have more than 1000000000 dimensions
LINE 1: SELECT '{}/1000000001'::sparsevec;
^
SELECT '{}/2147483648'::sparsevec;
ERROR: sparsevec cannot have more than 1000000000 dimensions
LINE 1: SELECT '{}/2147483648'::sparsevec;
^
SELECT '{}/-2147483649'::sparsevec;
ERROR: sparsevec must have at least 1 dimension
LINE 1: SELECT '{}/-2147483649'::sparsevec;
^
SELECT '{}/9223372036854775808'::sparsevec;
ERROR: sparsevec cannot have more than 1000000000 dimensions
LINE 1: SELECT '{}/9223372036854775808'::sparsevec;
^
SELECT '{}/-9223372036854775809'::sparsevec;
ERROR: sparsevec must have at least 1 dimension
LINE 1: SELECT '{}/-9223372036854775809'::sparsevec;
^
SELECT '{2147483647:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{2147483647:1}/1'::sparsevec;
^
SELECT '{2147483648:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{2147483648:1}/1'::sparsevec;
^
SELECT '{-2147483648:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{-2147483648:1}/1'::sparsevec;
^
SELECT '{-2147483649:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{-2147483649:1}/1'::sparsevec;
^
SELECT '{0:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
LINE 1: SELECT '{0:1}/1'::sparsevec;
^
SELECT '{2:1}/1'::sparsevec;
ERROR: sparsevec index out of bounds
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(1000000001);
ERROR: dimensions for type sparsevec cannot exceed 1000000000
LINE 1: SELECT '{}/3'::sparsevec(1000000001);
^
SELECT '{1:1,2:2,3:3}/3'::sparsevec < '{1:1,2:2,3:3}/3';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec < '{1:1,2:2}/2';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec <= '{1:1,2:2,3:3}/3';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec <= '{1:1,2:2}/2';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec = '{1:1,2:2,3:3}/3';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec = '{1:1,2:2}/2';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec != '{1:1,2:2,3:3}/3';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec != '{1:1,2:2}/2';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec >= '{1:1,2:2,3:3}/3';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec >= '{1:1,2:2}/2';
?column?
----------
t
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec > '{1:1,2:2,3:3}/3';
?column?
----------
f
(1 row)
SELECT '{1:1,2:2,3:3}/3'::sparsevec > '{1:1,2:2}/2';
?column?
----------
t
(1 row)
SELECT sparsevec_cmp('{1:1,2:2,3:3}/3', '{1:1,2:2,3:3}/3');
sparsevec_cmp
---------------
0
(1 row)
SELECT sparsevec_cmp('{1:1,2:2,3:3}/3', '{}/3');
sparsevec_cmp
---------------
1
(1 row)
SELECT sparsevec_cmp('{}/3', '{1:1,2:2,3:3}/3');
sparsevec_cmp
---------------
-1
(1 row)
SELECT sparsevec_cmp('{1:1,2:2}/2', '{1:1,2:2,3:3}/3');
sparsevec_cmp
---------------
-1
(1 row)
SELECT sparsevec_cmp('{1:1,2:2,3:3}/3', '{1:1,2:2}/2');
sparsevec_cmp
---------------
1
(1 row)
SELECT sparsevec_cmp('{1:1,2:2}/2', '{1:2,2:3,3:4}/3');
sparsevec_cmp
---------------
-1
(1 row)
SELECT sparsevec_cmp('{1:2,2:3}/2', '{1:1,2:2,3:3}/3');
sparsevec_cmp
---------------
1
(1 row)
SELECT round(l2_norm('{1:1,2:1}/2'::sparsevec)::numeric, 5);
round
---------
1.41421
(1 row)
SELECT l2_norm('{1:3,2:4}/2'::sparsevec);
l2_norm
---------
5
(1 row)
SELECT l2_norm('{2:1}/2'::sparsevec);
l2_norm
---------
1
(1 row)
SELECT l2_norm('{1:3e37,2:4e37}/2'::sparsevec)::real;
l2_norm
---------
5e+37
(1 row)
SELECT l2_norm('{}/2'::sparsevec);
l2_norm
---------
0
(1 row)
SELECT l2_norm('{1:2}/1'::sparsevec);
l2_norm
---------
2
(1 row)
SELECT l2_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{1:3}/2'::sparsevec, '{2:4}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{2:4}/2'::sparsevec, '{1:3}/2');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('{1:3,2:4}/2'::sparsevec, '{}/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 inner_product('{1:1,2:2}/2'::sparsevec, '{1:3}/1');
ERROR: different sparsevec dimensions 2 and 1
SELECT inner_product('{1:1,3:3}/4'::sparsevec, '{2:2,4:4}/4');
inner_product
---------------
0
(1 row)
SELECT inner_product('{2:2,4:4}/4'::sparsevec, '{1:1,3:3}/4');
inner_product
---------------
0
(1 row)
SELECT inner_product('{1:1,3:3,5:5}/5'::sparsevec, '{2:4,3:6,4:8}/5');
inner_product
---------------
18
(1 row)
SELECT inner_product('{1:1}/2'::sparsevec, '{}/2');
inner_product
---------------
0
(1 row)
SELECT inner_product('{}/2'::sparsevec, '{1:1}/2');
inner_product
---------------
0
(1 row)
SELECT inner_product('{1:3e38}/1'::sparsevec, '{1:3e38}/1');
inner_product
---------------
Infinity
(1 row)
SELECT inner_product('{1:1,3:3,5:5}/5'::sparsevec, '{2:4,3:6,4:8}/5');
inner_product
---------------
18
(1 row)
SELECT '{1:1,2:2}/2'::sparsevec <#> '{1:3,2:4}/2';
?column?
----------
-11
(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
-----------------
0
(1 row)
SELECT cosine_distance('{1:1}/2'::sparsevec, '{2:2}/2');
cosine_distance
-----------------
1
(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('{2:2}/2'::sparsevec, '{1:2}/2');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('{1:1,2:2}/2'::sparsevec, '{1:3}/1');
ERROR: different sparsevec dimensions 2 and 1
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:1.1,2:1.1}/2');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('{1:1,2:1}/2'::sparsevec, '{1:-1.1,2:-1.1}/2');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('{1:3e38}/1'::sparsevec, '{1:3e38}/1');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('{}/1'::sparsevec, '{}/1');
cosine_distance
-----------------
NaN
(1 row)
SELECT '{1:1,2:2}/2'::sparsevec <=> '{1:2,2:4}/2';
?column?
----------
0
(1 row)
SELECT l1_distance('{}/2'::sparsevec, '{1:3,2:4}/2');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('{}/2'::sparsevec, '{2:1}/2');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('{1:1,2:2}/2'::sparsevec, '{1:3}/1');
ERROR: different sparsevec dimensions 2 and 1
SELECT l1_distance('{1:3e38}/1'::sparsevec, '{1:-3e38}/1');
l1_distance
-------------
Infinity
(1 row)
SELECT l1_distance('{1:1,3:3,5:5,7:7}/8'::sparsevec, '{2:2,4:4,6:6,8:8}/8');
l1_distance
-------------
36
(1 row)
SELECT l1_distance('{1:1,3:3,5:5,7:7,9:9}/9'::sparsevec, '{2:2,4:4,6:6,8:8}/9');
l1_distance
-------------
45
(1 row)
SELECT '{}/2'::sparsevec <+> '{1:3,2:4}/2';
?column?
----------
7
(1 row)
SELECT l2_normalize('{1:3,2:4}/2'::sparsevec);
l2_normalize
-----------------
{1:0.6,2:0.8}/2
(1 row)
SELECT l2_normalize('{1:3}/2'::sparsevec);
l2_normalize
--------------
{1:1}/2
(1 row)
SELECT l2_normalize('{2:0.1}/2'::sparsevec);
l2_normalize
--------------
{2:1}/2
(1 row)
SELECT l2_normalize('{}/2'::sparsevec);
l2_normalize
--------------
{}/2
(1 row)
SELECT l2_normalize('{1:3e38}/1'::sparsevec);
l2_normalize
--------------
{1:1}/1
(1 row)
SELECT l2_normalize('{1:3e38,2:1e-37}/2'::sparsevec);
l2_normalize
--------------
{1:1}/2
(1 row)
SELECT l2_normalize('{2:3e37,4:3e-37,6:4e37,8:4e-37}/9'::sparsevec);
l2_normalize
-----------------
{2:0.6,6:0.8}/9
(1 row)

View File

@@ -1,672 +0,0 @@
SELECT '[1,2,3]'::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[-1,-2,-3]'::vector;
vector
------------
[-1,-2,-3]
(1 row)
SELECT '[1.,2.,3.]'::vector;
vector
---------
[1,2,3]
(1 row)
SELECT ' [ 1, 2 , 3 ] '::vector;
vector
---------
[1,2,3]
(1 row)
SELECT '[1.23456]'::vector;
vector
-----------
[1.23456]
(1 row)
SELECT '[hello,1]'::vector;
ERROR: invalid input syntax for type vector: "[hello,1]"
LINE 1: SELECT '[hello,1]'::vector;
^
SELECT '[NaN,1]'::vector;
ERROR: NaN not allowed in vector
LINE 1: SELECT '[NaN,1]'::vector;
^
SELECT '[Infinity,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[Infinity,1]'::vector;
^
SELECT '[-Infinity,1]'::vector;
ERROR: infinite value not allowed in vector
LINE 1: SELECT '[-Infinity,1]'::vector;
^
SELECT '[1.5e38,-1.5e38]'::vector;
vector
--------------------
[1.5e+38,-1.5e+38]
(1 row)
SELECT '[1.5e+38,-1.5e+38]'::vector;
vector
--------------------
[1.5e+38,-1.5e+38]
(1 row)
SELECT '[1.5e-38,-1.5e-38]'::vector;
vector
--------------------
[1.5e-38,-1.5e-38]
(1 row)
SELECT '[4e38,1]'::vector;
ERROR: "4e38" is out of range for type 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;
ERROR: invalid input syntax for type vector: "[1,2,3"
LINE 1: SELECT '[1,2,3'::vector;
^
SELECT '[1,2,3]9'::vector;
ERROR: invalid input syntax for type vector: "[1,2,3]9"
LINE 1: SELECT '[1,2,3]9'::vector;
^
DETAIL: Junk after closing right brace.
SELECT '1,2,3'::vector;
ERROR: invalid input syntax for type vector: "1,2,3"
LINE 1: SELECT '1,2,3'::vector;
^
DETAIL: Vector contents must start with "[".
SELECT ''::vector;
ERROR: invalid input syntax for type vector: ""
LINE 1: SELECT ''::vector;
^
DETAIL: Vector contents must start with "[".
SELECT '['::vector;
ERROR: invalid input syntax for type vector: "["
LINE 1: SELECT '['::vector;
^
SELECT '[ '::vector;
ERROR: invalid input syntax for type vector: "[ "
LINE 1: SELECT '[ '::vector;
^
SELECT '[,'::vector;
ERROR: invalid input syntax for type vector: "[,"
LINE 1: SELECT '[,'::vector;
^
SELECT '[]'::vector;
ERROR: vector must have at least 1 dimension
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;
ERROR: invalid input syntax for type vector: "[1,]"
LINE 1: SELECT '[1,]'::vector;
^
SELECT '[1a]'::vector;
ERROR: invalid input syntax for type vector: "[1a]"
LINE 1: SELECT '[1a]'::vector;
^
SELECT '[1,,3]'::vector;
ERROR: invalid input syntax for type vector: "[1,,3]"
LINE 1: SELECT '[1,,3]'::vector;
^
SELECT '[1, ,3]'::vector;
ERROR: invalid input syntax for type vector: "[1, ,3]"
LINE 1: SELECT '[1, ,3]'::vector;
^
SELECT '[1,2,3]'::vector(3);
vector
---------
[1,2,3]
(1 row)
SELECT '[1,2,3]'::vector(2);
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::vector(3, 2);
ERROR: invalid type modifier
LINE 1: SELECT '[1,2,3]'::vector(3, 2);
^
SELECT '[1,2,3]'::vector('a');
ERROR: invalid input syntax for type integer: "a"
LINE 1: SELECT '[1,2,3]'::vector('a');
^
SELECT '[1,2,3]'::vector(0);
ERROR: dimensions for type vector must be at least 1
LINE 1: SELECT '[1,2,3]'::vector(0);
^
SELECT '[1,2,3]'::vector(16001);
ERROR: dimensions for type vector cannot exceed 16000
LINE 1: SELECT '[1,2,3]'::vector(16001);
^
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
unnest
---------
[1,2,3]
[4,5,6]
(2 rows)
SELECT '{"[1,2,3]"}'::vector(2)[];
ERROR: expected 2 dimensions, not 3
SELECT '[1,2,3]'::vector + '[4,5,6]';
?column?
----------
[5,7,9]
(1 row)
SELECT '[3e38]'::vector + '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2]'::vector + '[3]';
ERROR: different vector dimensions 2 and 1
SELECT '[1,2,3]'::vector - '[4,5,6]';
?column?
------------
[-3,-3,-3]
(1 row)
SELECT '[-3e38]'::vector - '[3e38]';
ERROR: value out of range: overflow
SELECT '[1,2]'::vector - '[3]';
ERROR: different vector dimensions 2 and 1
SELECT '[1,2,3]'::vector * '[4,5,6]';
?column?
-----------
[4,10,18]
(1 row)
SELECT '[1e37]'::vector * '[1e37]';
ERROR: value out of range: overflow
SELECT '[1e-37]'::vector * '[1e-37]';
ERROR: value out of range: underflow
SELECT '[1,2]'::vector * '[3]';
ERROR: different vector dimensions 2 and 1
SELECT '[1,2,3]'::vector || '[4,5]';
?column?
-------------
[1,2,3,4,5]
(1 row)
SELECT array_fill(0, ARRAY[16000])::vector || '[1]';
ERROR: vector cannot have more than 16000 dimensions
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]';
?column?
----------
t
(1 row)
SELECT '[1,2,3]'::vector = '[1,2]';
?column?
----------
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]');
vector_cmp
------------
0
(1 row)
SELECT vector_cmp('[1,2,3]', '[0,0,0]');
vector_cmp
------------
1
(1 row)
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[1,2]', '[1,2,3]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[1,2,3]', '[1,2]');
vector_cmp
------------
1
(1 row)
SELECT vector_cmp('[1,2]', '[2,3,4]');
vector_cmp
------------
-1
(1 row)
SELECT vector_cmp('[2,3]', '[1,2,3]');
vector_cmp
------------
1
(1 row)
SELECT vector_dims('[1,2,3]'::vector);
vector_dims
-------------
3
(1 row)
SELECT round(vector_norm('[1,1]')::numeric, 5);
round
---------
1.41421
(1 row)
SELECT vector_norm('[3,4]');
vector_norm
-------------
5
(1 row)
SELECT vector_norm('[0,1]');
vector_norm
-------------
1
(1 row)
SELECT vector_norm('[3e37,4e37]')::real;
vector_norm
-------------
5e+37
(1 row)
SELECT vector_norm('[0,0]');
vector_norm
-------------
0
(1 row)
SELECT vector_norm('[2]');
vector_norm
-------------
2
(1 row)
SELECT l2_distance('[0,0]'::vector, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]'::vector, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
l2_distance
-------------
Infinity
(1 row)
SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::vector, '[1,1,1,1,1,1,1,4,5]');
l2_distance
-------------
5
(1 row)
SELECT '[0,0]'::vector <-> '[3,4]';
?column?
----------
5
(1 row)
SELECT inner_product('[1,2]'::vector, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT inner_product('[3e38]'::vector, '[3e38]');
inner_product
---------------
Infinity
(1 row)
SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::vector, '[1,2,3,4,5,6,7,8,9]');
inner_product
---------------
45
(1 row)
SELECT '[1,2]'::vector <#> '[3,4]';
?column?
----------
-11
(1 row)
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[1,2,3,4,5,6,7,8,9]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[-1,-2,-3,-4,-5,-6,-7,-8,-9]');
cosine_distance
-----------------
2
(1 row)
SELECT '[1,2]'::vector <=> '[2,4]';
?column?
----------
0
(1 row)
SELECT l1_distance('[0,0]'::vector, '[3,4]');
l1_distance
-------------
7
(1 row)
SELECT l1_distance('[0,0]'::vector, '[0,1]');
l1_distance
-------------
1
(1 row)
SELECT l1_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l1_distance('[3e38]'::vector, '[-3e38]');
l1_distance
-------------
Infinity
(1 row)
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[1,2,3,4,5,6,7,8,9]');
l1_distance
-------------
0
(1 row)
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[0,3,2,5,4,7,6,9,8]');
l1_distance
-------------
9
(1 row)
SELECT '[0,0]'::vector <+> '[3,4]';
?column?
----------
7
(1 row)
SELECT l2_normalize('[3,4]'::vector);
l2_normalize
--------------
[0.6,0.8]
(1 row)
SELECT l2_normalize('[3,0]'::vector);
l2_normalize
--------------
[1,0]
(1 row)
SELECT l2_normalize('[0,0.1]'::vector);
l2_normalize
--------------
[0,1]
(1 row)
SELECT l2_normalize('[0,0]'::vector);
l2_normalize
--------------
[0,0]
(1 row)
SELECT l2_normalize('[3e38]'::vector);
l2_normalize
--------------
[1]
(1 row)
SELECT binary_quantize('[1,0,-1]'::vector);
binary_quantize
-----------------
100
(1 row)
SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
binary_quantize
-----------------
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 subvector('[1,2,3,4,5]'::vector, 2147483647, 10);
ERROR: vector must have at least 1 dimension
SELECT subvector('[1,2,3,4,5]'::vector, 3, 2147483647);
subvector
-----------
[3,4,5]
(1 row)
SELECT subvector('[1,2,3,4,5]'::vector, -2147483644, 2147483647);
subvector
-----------
[1,2]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
avg
-----------
[2,3.5,5]
(1 row)
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
avg
-----
(1 row)
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: expected 2 dimensions, not 1
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
avg
---------
[3e+38]
(1 row)
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
ERROR: vector cannot have more than 16000 dimensions
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
sum
----------
[4,7,10]
(1 row)
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
sum
-----
(1 row)
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
ERROR: different vector dimensions 2 and 1
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
ERROR: value out of range: overflow

View File

@@ -1,11 +0,0 @@
package PostgreSQL::Test::Cluster;
use PostgresNode;
sub new
{
my ($class, $name) = @_;
return get_new_node($name);
}
1;

View File

@@ -1,5 +0,0 @@
package PostgreSQL::Test::Utils;
use TestLib;
1;

View File

@@ -0,0 +1,8 @@
use PostgreSQL::Test::Cluster;
sub get_new_node
{
return PostgreSQL::Test::Cluster->new(@_);
}
1;

3
test/perl/TestLib.pm Normal file
View File

@@ -0,0 +1,3 @@
use PostgreSQL::Test::Utils;
1;

View File

@@ -1,27 +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('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101');
SELECT hamming_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010');
SELECT hamming_distance('110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011', '100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001');
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('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101');
SELECT jaccard_distance('101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101', '010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010101010');
SELECT jaccard_distance('110000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000011', '100000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000000001');
SELECT jaccard_distance('', '');
SELECT jaccard_distance('1111', '000');
SELECT jaccard_distance('1111', '0000'::varbit(5));
SELECT jaccard_distance('1111', '00000'::varbit(5));

View File

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

View File

@@ -1,45 +1,10 @@
SET enable_seqscan = off; SET enable_seqscan = off;
-- vector
CREATE TABLE t (val vector(3)); CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL); INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t (val); CREATE INDEX ON t (val);
SELECT * FROM t WHERE val = '[1,2,3]'; SELECT * FROM t WHERE val = '[1,2,3]';
SELECT * FROM t ORDER BY val; SELECT * FROM t ORDER BY val LIMIT 1;
DROP TABLE t;
-- halfvec
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 (val);
SELECT * FROM t WHERE val = '[1,2,3]';
SELECT * FROM t ORDER BY val;
DROP TABLE t;
-- minivec
CREATE TABLE t (val minivec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t (val);
SELECT * FROM t WHERE val = '[1,2,3]';
SELECT * FROM t ORDER BY val;
DROP TABLE t;
-- sparsevec
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 (val);
SELECT * FROM t WHERE val = '{1:1,2:2,3:3}/3';
SELECT * FROM t ORDER BY val;
DROP TABLE t; DROP TABLE t;

View File

@@ -3,93 +3,13 @@ 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(3);
SELECT '[1,2,3]'::vector::halfvec(2);
SELECT '[65520]'::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 '[1,2,3]'::vector::minivec;
SELECT '[1,2,3]'::vector::minivec(3);
SELECT '[1,2,3]'::vector::minivec(2);
SELECT '[465]'::vector::minivec;
SELECT '[1e-8]'::vector::minivec;
SELECT '[1,2,3]'::minivec::vector;
SELECT '[1,2,3]'::minivec::vector(3);
SELECT '[1,2,3]'::minivec::vector(2);
SELECT '{1,2,3}'::real[]::minivec;
SELECT '{1,2,3}'::real[]::minivec(3);
SELECT '{1,2,3}'::real[]::minivec(2);
SELECT '{465,-465}'::real[]::minivec;
SELECT '{1e-8,-1e-8}'::real[]::minivec;
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 '[0,1.5,0,3.5,0]'::halfvec::sparsevec;
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec(5);
SELECT '[0,1.5,0,3.5,0]'::halfvec::sparsevec(4);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec;
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec(5);
SELECT '{2:1.5,4:3.5}/5'::sparsevec::halfvec(4);
SELECT '{}/16001'::sparsevec::halfvec;
SELECT '{1:65520}/1'::sparsevec::halfvec;
SELECT '{1:1e-8}/1'::sparsevec::halfvec;
SELECT ARRAY[1,0,2,0,3,0]::sparsevec;
SELECT ARRAY[1.0,0.0,2.0,0.0,3.0,0.0]::sparsevec;
SELECT ARRAY[1,0,2,0,3,0]::float4[]::sparsevec;
SELECT ARRAY[1,0,2,0,3,0]::float8[]::sparsevec;
SELECT ARRAY[1,0,2,0,3,0]::numeric[]::sparsevec;
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec;
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(6);
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(5);
SELECT '{NULL}'::real[]::sparsevec;
SELECT '{NaN}'::real[]::sparsevec;
SELECT '{Infinity}'::real[]::sparsevec;
SELECT '{-Infinity}'::real[]::sparsevec;
SELECT '{}'::real[]::sparsevec;
SELECT '{{1}}'::real[]::sparsevec;
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

@@ -1,57 +1,10 @@
-- vector
CREATE TABLE t (val vector(3)); CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL); INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val vector(3)); CREATE TABLE t2 (val vector(3));
\copy t TO 'results/vector.bin' WITH (FORMAT binary) \copy t TO 'results/data.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/vector.bin' WITH (FORMAT binary) \copy t2 FROM 'results/data.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
DROP TABLE t;
DROP TABLE t2;
-- halfvec
CREATE TABLE t (val halfvec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val halfvec(3));
\copy t TO 'results/halfvec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/halfvec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
DROP TABLE t;
DROP TABLE t2;
-- minivec
CREATE TABLE t (val minivec(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE TABLE t2 (val minivec(3));
\copy t TO 'results/minivec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/minivec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val;
DROP TABLE t;
DROP TABLE t2;
-- sparsevec
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 TABLE t2 (val sparsevec(3));
\copy t TO 'results/sparsevec.bin' WITH (FORMAT binary)
\copy t2 FROM 'results/sparsevec.bin' WITH (FORMAT binary)
SELECT * FROM t2 ORDER BY val; SELECT * FROM t2 ORDER BY val;

65
test/sql/functions.sql Normal file
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@@ -0,0 +1,65 @@
SELECT '[1,2,3]'::vector + '[4,5,6]';
SELECT '[3e38]'::vector + '[3e38]';
SELECT '[1,2,3]'::vector - '[4,5,6]';
SELECT '[-3e38]'::vector - '[3e38]';
SELECT '[1,2,3]'::vector * '[4,5,6]';
SELECT '[1e37]'::vector * '[1e37]';
SELECT '[1e-37]'::vector * '[1e-37]';
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]', '[0,0,0]');
SELECT vector_cmp('[0,0,0]', '[1,2,3]');
SELECT vector_cmp('[1,2]', '[1,2,3]');
SELECT vector_cmp('[1,2,3]', '[1,2]');
SELECT vector_cmp('[1,2]', '[2,3,4]');
SELECT vector_cmp('[2,3]', '[1,2,3]');
SELECT vector_dims('[1,2,3]');
SELECT round(vector_norm('[1,1]')::numeric, 5);
SELECT vector_norm('[3,4]');
SELECT vector_norm('[0,1]');
SELECT vector_norm('[3e37,4e37]')::real;
SELECT l2_distance('[0,0]', '[3,4]');
SELECT l2_distance('[0,0]', '[0,1]');
SELECT l2_distance('[1,2]', '[3]');
SELECT l2_distance('[3e38]', '[-3e38]');
SELECT inner_product('[1,2]', '[3,4]');
SELECT inner_product('[1,2]', '[3]');
SELECT inner_product('[3e38]', '[3e38]');
SELECT cosine_distance('[1,2]', '[2,4]');
SELECT cosine_distance('[1,2]', '[0,0]');
SELECT cosine_distance('[1,1]', '[1,1]');
SELECT cosine_distance('[1,0]', '[0,2]');
SELECT cosine_distance('[1,1]', '[-1,-1]');
SELECT cosine_distance('[1,2]', '[3]');
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
SELECT cosine_distance('[3e38]', '[3e38]');
SELECT l1_distance('[0,0]', '[3,4]');
SELECT l1_distance('[0,0]', '[0,1]');
SELECT l1_distance('[1,2]', '[3]');
SELECT l1_distance('[3e38]', '[-3e38]');
SELECT quantize_binary('[1,0,-1]');
SELECT quantize_binary('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]');
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;

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@@ -1,147 +0,0 @@
SELECT '[1,2,3]'::halfvec;
SELECT '[-1,-2,-3]'::halfvec;
SELECT '[1.,2.,3.]'::halfvec;
SELECT ' [ 1, 2 , 3 ] '::halfvec;
SELECT '[1.23456]'::halfvec;
SELECT '[hello,1]'::halfvec;
SELECT '[NaN,1]'::halfvec;
SELECT '[Infinity,1]'::halfvec;
SELECT '[-Infinity,1]'::halfvec;
SELECT '[65519,-65519]'::halfvec;
SELECT '[65520,-65520]'::halfvec;
SELECT '[1e-8,-1e-8]'::halfvec;
SELECT '[4e38,1]'::halfvec;
SELECT '[1e-46,1]'::halfvec;
SELECT '[1,2,3'::halfvec;
SELECT '[1,2,3]9'::halfvec;
SELECT '1,2,3'::halfvec;
SELECT ''::halfvec;
SELECT '['::halfvec;
SELECT '[ '::halfvec;
SELECT '[,'::halfvec;
SELECT '[]'::halfvec;
SELECT '[ ]'::halfvec;
SELECT '[,]'::halfvec;
SELECT '[1,]'::halfvec;
SELECT '[1a]'::halfvec;
SELECT '[1,,3]'::halfvec;
SELECT '[1, ,3]'::halfvec;
SELECT '[1,2,3]'::halfvec(3);
SELECT '[1,2,3]'::halfvec(2);
SELECT '[1,2,3]'::halfvec(3, 2);
SELECT '[1,2,3]'::halfvec('a');
SELECT '[1,2,3]'::halfvec(0);
SELECT '[1,2,3]'::halfvec(16001);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::halfvec[]);
SELECT '{"[1,2,3]"}'::halfvec(2)[];
SELECT '[1,2,3]'::halfvec + '[4,5,6]';
SELECT '[65519]'::halfvec + '[65519]';
SELECT '[1,2]'::halfvec + '[3]';
SELECT '[1,2,3]'::halfvec - '[4,5,6]';
SELECT '[-65519]'::halfvec - '[65519]';
SELECT '[1,2]'::halfvec - '[3]';
SELECT '[1,2,3]'::halfvec * '[4,5,6]';
SELECT '[65519]'::halfvec * '[65519]';
SELECT '[1e-7]'::halfvec * '[1e-7]';
SELECT '[1,2]'::halfvec * '[3]';
SELECT '[1,2,3]'::halfvec || '[4,5]';
SELECT array_fill(0, ARRAY[16000])::halfvec || '[1]';
SELECT '[1,2,3]'::halfvec < '[1,2,3]';
SELECT '[1,2,3]'::halfvec < '[1,2]';
SELECT '[1,2,3]'::halfvec <= '[1,2,3]';
SELECT '[1,2,3]'::halfvec <= '[1,2]';
SELECT '[1,2,3]'::halfvec = '[1,2,3]';
SELECT '[1,2,3]'::halfvec = '[1,2]';
SELECT '[1,2,3]'::halfvec != '[1,2,3]';
SELECT '[1,2,3]'::halfvec != '[1,2]';
SELECT '[1,2,3]'::halfvec >= '[1,2,3]';
SELECT '[1,2,3]'::halfvec >= '[1,2]';
SELECT '[1,2,3]'::halfvec > '[1,2,3]';
SELECT '[1,2,3]'::halfvec > '[1,2]';
SELECT halfvec_cmp('[1,2,3]', '[1,2,3]');
SELECT halfvec_cmp('[1,2,3]', '[0,0,0]');
SELECT halfvec_cmp('[0,0,0]', '[1,2,3]');
SELECT halfvec_cmp('[1,2]', '[1,2,3]');
SELECT halfvec_cmp('[1,2,3]', '[1,2]');
SELECT halfvec_cmp('[1,2]', '[2,3,4]');
SELECT halfvec_cmp('[2,3]', '[1,2,3]');
SELECT vector_dims('[1,2,3]'::halfvec);
SELECT round(l2_norm('[1,1]'::halfvec)::numeric, 5);
SELECT l2_norm('[3,4]'::halfvec);
SELECT l2_norm('[0,1]'::halfvec);
SELECT l2_norm('[0,0]'::halfvec);
SELECT l2_norm('[2]'::halfvec);
SELECT l2_distance('[0,0]'::halfvec, '[3,4]');
SELECT l2_distance('[0,0]'::halfvec, '[0,1]');
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 inner_product('[1,2]'::halfvec, '[3,4]');
SELECT inner_product('[1,2]'::halfvec, '[3]');
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 cosine_distance('[1,2]'::halfvec, '[2,4]');
SELECT cosine_distance('[1,2]'::halfvec, '[0,0]');
SELECT cosine_distance('[1,1]'::halfvec, '[1,1]');
SELECT cosine_distance('[1,0]'::halfvec, '[0,2]');
SELECT cosine_distance('[1,1]'::halfvec, '[-1,-1]');
SELECT cosine_distance('[1,2]'::halfvec, '[3]');
SELECT cosine_distance('[1,1]'::halfvec, '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::halfvec, '[-1.1,-1.1]');
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[-1,-2,-3,-4,-5,-6,-7,-8,-9]');
SELECT '[1,2]'::halfvec <=> '[2,4]';
SELECT l1_distance('[0,0]'::halfvec, '[3,4]');
SELECT l1_distance('[0,0]'::halfvec, '[0,1]');
SELECT l1_distance('[1,2]'::halfvec, '[3]');
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[1,2,3,4,5,6,7,8,9]');
SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::halfvec, '[0,3,2,5,4,7,6,9,8]');
SELECT '[0,0]'::halfvec <+> '[3,4]';
SELECT l2_normalize('[3,4]'::halfvec);
SELECT l2_normalize('[3,0]'::halfvec);
SELECT l2_normalize('[0,0.1]'::halfvec);
SELECT l2_normalize('[0,0]'::halfvec);
SELECT l2_normalize('[65504]'::halfvec);
SELECT binary_quantize('[1,0,-1]'::halfvec);
SELECT binary_quantize('[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);
SELECT subvector('[1,2,3,4,5]'::halfvec, 2147483647, 10);
SELECT subvector('[1,2,3,4,5]'::halfvec, 3, 2147483647);
SELECT subvector('[1,2,3,4,5]'::halfvec, -2147483644, 2147483647);
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]']) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]', NULL]) v;
SELECT avg(v) FROM unnest(ARRAY[]::halfvec[]) v;
SELECT avg(v) FROM unnest(ARRAY['[1,2]'::halfvec, '[3]']) v;
SELECT avg(v) FROM unnest(ARRAY['[65504]'::halfvec, '[65504]']) v;
SELECT halfvec_avg(array_agg(n)) FROM generate_series(1, 16002) n;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]']) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::halfvec, '[3,5,7]', NULL]) v;
SELECT sum(v) FROM unnest(ARRAY[]::halfvec[]) v;
SELECT sum(v) FROM unnest(ARRAY['[1,2]'::halfvec, '[3]']) v;
SELECT sum(v) FROM unnest(ARRAY['[65504]'::halfvec, '[65504]']) v;

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@@ -1,35 +0,0 @@
SET enable_seqscan = off;
-- hamming
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;
-- jaccard
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;
-- varbit
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;

13
test/sql/hnsw_cosine.sql Normal file
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@@ -0,0 +1,13 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_cosine_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
DROP TABLE t;

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@@ -1,58 +0,0 @@
SET enable_seqscan = off;
-- L2
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 hnsw (val halfvec_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::halfvec)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;
-- inner product
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 hnsw (val halfvec_ip_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::halfvec)) t2;
DROP TABLE t;
-- cosine
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 hnsw (val halfvec_cosine_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t2;
DROP TABLE t;
-- L1
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 hnsw (val halfvec_l1_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <+> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::halfvec)) t2;
DROP TABLE t;

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

12
test/sql/hnsw_ip.sql Normal file
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@@ -0,0 +1,12 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_ip_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
DROP TABLE t;

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

16
test/sql/hnsw_l2.sql Normal file
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@@ -0,0 +1,16 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector);
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;

13
test/sql/hnsw_options.sql Normal file
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@@ -0,0 +1,13 @@
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 1);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
SHOW hnsw.ef_search;
SET hnsw.ef_search = 0;
SET hnsw.ef_search = 1001;
DROP TABLE t;

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@@ -1,68 +0,0 @@
SET enable_seqscan = off;
-- L2
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;
-- inner product
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;
-- cosine
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;
-- L1
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_l1_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;
-- non-zero elements
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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@@ -0,0 +1,9 @@
SET enable_seqscan = off;
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;

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@@ -1,84 +0,0 @@
SET enable_seqscan = off;
-- L2
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <-> (SELECT NULL::vector)) t2;
SELECT COUNT(*) FROM t;
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;
-- inner product
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_ip_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <#> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <#> (SELECT NULL::vector)) t2;
DROP TABLE t;
-- cosine
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_cosine_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <=> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2;
DROP TABLE t;
-- L1
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l1_ops);
INSERT INTO t (val) VALUES ('[1,2,4]');
SELECT * FROM t ORDER BY val <+> '[3,3,3]';
SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::vector)) t2;
DROP TABLE t;
-- unlogged
CREATE UNLOGGED TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
DROP TABLE t;
-- options
CREATE TABLE t (val vector(3));
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 1);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
SHOW hnsw.ef_search;
SET hnsw.ef_search = 0;
SET hnsw.ef_search = 1001;
DROP TABLE t;

34
test/sql/input.sql Normal file
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@@ -0,0 +1,34 @@
SELECT '[1,2,3]'::vector;
SELECT '[-1,-2,-3]'::vector;
SELECT '[1.,2.,3.]'::vector;
SELECT ' [ 1, 2 , 3 ] '::vector;
SELECT '[1.23456]'::vector;
SELECT '[hello,1]'::vector;
SELECT '[NaN,1]'::vector;
SELECT '[Infinity,1]'::vector;
SELECT '[-Infinity,1]'::vector;
SELECT '[1.5e38,-1.5e38]'::vector;
SELECT '[1.5e+38,-1.5e+38]'::vector;
SELECT '[1.5e-38,-1.5e-38]'::vector;
SELECT '[4e38,1]'::vector;
SELECT '[1,2,3'::vector;
SELECT '[1,2,3]9'::vector;
SELECT '1,2,3'::vector;
SELECT ''::vector;
SELECT '['::vector;
SELECT '[,'::vector;
SELECT '[]'::vector;
SELECT '[1,]'::vector;
SELECT '[1a]'::vector;
SELECT '[1,,3]'::vector;
SELECT '[1, ,3]'::vector;
SELECT '[1,2,3]'::vector(3);
SELECT '[1,2,3]'::vector(2);
SELECT '[1,2,3]'::vector(3, 2);
SELECT '[1,2,3]'::vector('a');
SELECT '[1,2,3]'::vector(0);
SELECT '[1,2,3]'::vector(16001);
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
SELECT '{"[1,2,3]"}'::vector(2)[];

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@@ -1,23 +0,0 @@
SET enable_seqscan = off;
-- hamming
CREATE TABLE t (val bit(3));
INSERT INTO t (val) VALUES (B'000'), (B'100'), (B'111'), (NULL);
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops) WITH (lists = 1);
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;
-- varbit
CREATE TABLE t (val varbit(3));
CREATE INDEX ON t USING ivfflat (val bit_hamming_ops) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat ((val::bit(3)) bit_hamming_ops) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat ((val::bit(64001)) bit_hamming_ops) WITH (lists = 1);
CREATE INDEX ON t USING ivfflat ((val::bit(2)) bit_hamming_ops) WITH (lists = 5);
DROP TABLE t;

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@@ -0,0 +1,13 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_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::vector)) t2;
DROP TABLE t;

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@@ -1,45 +0,0 @@
SET enable_seqscan = off;
-- L2
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;
-- inner product
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;
-- cosine
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;

12
test/sql/ivfflat_ip.sql Normal file
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@@ -0,0 +1,12 @@
SET enable_seqscan = off;
CREATE TABLE t (val vector(3));
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
CREATE INDEX ON t USING ivfflat (val vector_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::vector)) t2;
DROP TABLE t;

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