Compare commits

...

107 Commits

Author SHA1 Message Date
Andrew Kane
f90d52d562 Added test for explicit zeros [skip ci] 2023-11-06 14:29:52 -08:00
Andrew Kane
22a1b06924 Added todo [skip ci] 2023-11-05 21:26:28 -08:00
Andrew Kane
b17b9c1ca2 Updated version [skip ci] 2023-11-05 18:21:09 -08:00
Andrew Kane
492ae1225c Added support for sparse vectors 2023-11-05 18:12:19 -08:00
Andrew Kane
a01a72d812 Updated comment [skip ci] 2023-11-05 08:42:06 -08:00
Andrew Kane
0c2fc18a80 Updated comment [skip ci] 2023-11-05 08:40:21 -08:00
Andrew Kane
e860042d3c Improved variable name [skip ci] 2023-11-05 08:35:54 -08:00
Andrew Kane
5986862bd2 Added note about check constraint [skip ci] 2023-11-04 15:01:37 -07:00
Andrew Kane
5d24f5d09a Improved header installation on Windows 2023-11-04 11:16:40 -07:00
Andrew Kane
7c43b0d8ee Updated example [skip ci] 2023-11-03 23:54:50 -07:00
Andrew Kane
7be40036f4 Updated readme [skip ci] 2023-11-03 23:46:23 -07:00
Andrew Kane
9b5a1a69db Updated readme [skip ci] 2023-11-03 23:43:47 -07:00
Andrew Kane
04b96506f5 Added info on storing vectors with more precision [skip ci] 2023-11-03 20:14:28 -07:00
Andrew Kane
35cd7b63cb Updated readme [skip ci] 2023-11-03 17:02:30 -07:00
Andrew Kane
b5416d6f10 Updated readme [skip ci] 2023-11-03 16:48:57 -07:00
Andrew Kane
f361bf2704 Improved docs on indexing vectors with different dimensions [skip ci] 2023-11-03 16:42:14 -07:00
Andrew Kane
3d8c1921aa Improved upgrading docs - #339 [skip ci] 2023-11-03 16:15:06 -07:00
Andrew Kane
154207bc17 Added info on columns with different dimensions [skip ci] 2023-11-03 16:02:00 -07:00
Andrew Kane
8e507f3bf5 Free remaining allocation from deconstruct_array - #332 2023-11-02 21:20:21 -07:00
Andrew Kane
e115773a55 Removed unneeded allocation 2023-11-02 21:16:06 -07:00
Andrew Kane
9333bef046 Added link to setup-pgvector [skip ci] 2023-11-02 13:22:19 -07:00
Andrew Kane
4851e47d9f Added Reciprocal Rank Fusion example to readme [skip ci] 2023-11-01 13:20:49 -07:00
Andrew Kane
12aecfb4f5 Added Nim and Zig to readme [skip ci] 2023-10-31 02:26:18 -07:00
Andrew Kane
800697fb14 Updated column alias [skip ci] 2023-10-29 16:47:55 -07:00
Andrew Kane
de1f2b09dd Improved indexing progress queries [skip ci] 2023-10-29 16:41:39 -07:00
Andrew Kane
bcccb7f5a5 Improved docs for indexing progress - closes #320 and closes #321 [skip ci] 2023-10-29 16:13:12 -07:00
Andrew Kane
bec3d30d68 Added TypeScript to readme [skip ci] 2023-10-29 12:49:01 -07:00
Andrew Kane
588de60445 Added Groovy to readme [skip ci] 2023-10-29 12:39:53 -07:00
Andrew Kane
c599f92b52 Updated readme [skip ci] 2023-10-27 13:22:37 -07:00
Andrew Kane
2a17b335da Added Kotlin to readme [skip ci] 2023-10-26 12:25:58 -07:00
Andrew Kane
6ede6ac301 Added link to pgvector-c [skip ci] 2023-10-26 00:30:06 -07:00
Andrew Kane
3f49b95f01 Added Postgres 17 to CI [skip ci] 2023-10-19 00:37:24 -07:00
Andrew Kane
ef1bea7163 Updated checkout action [skip ci] 2023-10-19 00:36:53 -07:00
Andrew Kane
e630efd195 Version bump to 0.5.1 [skip ci] 2023-10-10 17:40:57 -07:00
Andrew Kane
b5b912906b Added check for MVCC-compliant snapshot and removed marking tuples as dead for IVFFlat index scans - closes #260 2023-10-10 17:28:48 -07:00
Andrew Kane
4b5db94307 Disable closer caching for new elements for now 2023-10-06 14:27:09 -07:00
Andrew Kane
65e70326b8 Updated comment [skip ci] 2023-10-06 14:07:35 -07:00
Andrew Kane
71641ed84e Updated comment [skip ci] 2023-10-06 13:58:07 -07:00
Andrew Kane
f3dba25036 Added comment [skip ci] 2023-10-06 13:56:25 -07:00
Andrew Kane
5588ba6410 Improved variable name [skip ci] 2023-10-06 13:46:19 -07:00
Andrew Kane
ec9fac5456 Improved closerSet logic 2023-10-06 13:39:55 -07:00
Andrew Kane
8085d3e538 Moved sorting logic into SelectNeighbors 2023-10-06 12:56:15 -07:00
Andrew Kane
cae162ffc6 Ensure order is deterministic for SelectNeighbors closer caching 2023-10-06 12:26:53 -07:00
Andrew Kane
62482e3760 Use e for consistency 2023-10-05 16:15:13 -07:00
Heikki Linnakangas
c81302b835 Improve HNSW index build performance more (#295)
This takes the approach from commit a713e2acaa further. Once we have
remove a candidate from the "closer" set, we still don't need to
recalculate everything that follows. Any candidates that were in the
closer set before still only need to be compared with any new
candidates that we have added.
2023-10-05 16:04:50 -07:00
Andrew Kane
a713e2acaa Improved performance of HNSW index builds - closes #292
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2023-10-05 13:21:26 -07:00
Andrew Kane
6e1312ddbe DRY max size 2023-10-04 21:43:34 -07:00
Andrew Kane
4ef5bca275 Use BLCKSZ for consistency 2023-10-04 21:37:55 -07:00
Xiaoran Wang
1ecf6ada76 Include ItemIdData when computing the maxSize for the data in a page (#274)
As the data is aligned, for hnsw, the combined size won't be in the range
(8156 (maxSize exlucding `ItemIdData`), 8160]. So even if the
ItemIdData is not included in the maxSize, it works well now, but I
think it's better to make it correct.
2023-10-04 21:26:46 -07:00
Andrew Kane
564a3d45fc Added check for MVCC-compliant snapshot for HNSW index scans - closes #281 2023-10-04 20:14:50 -07:00
Andrew Kane
8d7abb6590 Revert "Fixed locking for index scans for HNSW - #256"
This reverts commit d032726976.
2023-09-26 23:00:14 -07:00
jeff-davis
b247b688a8 No need to MarkBufferDirty(); GenericXLogFinish() does that. (#265) 2023-09-15 13:14:10 -07:00
Andrew Kane
9672446a4c Updated order [skip ci] 2023-09-12 19:53:12 -07:00
Andrew Kane
334614b7f7 Added HnswFreeNeighbors function [skip ci] 2023-09-12 19:49:31 -07:00
Andrew Kane
643eacd9dc Improved variable name [skip ci] 2023-09-12 19:37:42 -07:00
Andrew Kane
bca50a03fa Use consistent variable name 2023-09-12 19:24:31 -07:00
Andrew Kane
d87833cacc Improved variable scoping [skip ci] 2023-09-12 19:16:55 -07:00
Andrew Kane
4c01073ac1 Improved variable scoping [skip ci] 2023-09-12 18:43:43 -07:00
Andrew Kane
6fed8f1e78 Improved types and scoping for k-means [skip ci] 2023-09-12 18:37:56 -07:00
Andrew Kane
611f5b1047 Improved variable scoping [skip ci] 2023-09-12 18:35:53 -07:00
Andrew Kane
e367155732 Improved types and scoping for k-means 2023-09-12 18:33:31 -07:00
Andrew Kane
466c556b1a Improved variable scoping [skip ci] 2023-09-12 18:24:46 -07:00
Andrew Kane
75e09265d6 Improved variable scoping [skip ci] 2023-09-12 18:14:20 -07:00
Andrew Kane
77c5070fb6 Improved variable scoping [skip ci] 2023-09-12 16:50:51 -07:00
Andrew Kane
1006fdf3f2 Improved variable scoping [skip ci] 2023-09-12 16:44:09 -07:00
Andrew Kane
4209c9b3af Improved variable scoping 2023-09-12 16:13:10 -07:00
Andrew Kane
ec0bb4e4ff Improved code 2023-09-12 15:43:28 -07:00
Andrew Kane
b164833933 Removed pinning for HNSW index scan 2023-09-11 12:12:28 -07:00
Andrew Kane
30fb4dd602 Updated comments [skip ci] 2023-09-07 15:29:54 -07:00
Andrew Kane
d032726976 Fixed locking for index scans for HNSW - #256 2023-09-07 15:27:26 -07:00
Andrew Kane
8fa9001474 Improved Makefiles 2023-09-05 16:43:23 -07:00
Andrew Kane
3431acef94 Improved variable names 2023-09-03 16:49:24 -07:00
Andrew Kane
41bdf24cb7 Fixed flaky test 2023-09-03 15:24:40 -07:00
Andrew Kane
3469a0e74c Simplified test [skip ci] 2023-09-03 15:18:23 -07:00
Andrew Kane
0fe43ca675 Added test for marking tuples as dead 2023-09-03 15:15:02 -07:00
Andrew Kane
bbbe1db72b Improved performance of index scans for IVFFlat after updates and deletes 2023-09-03 14:21:57 -07:00
Andrew Kane
bab5fea9e7 Improved variable name [skip ci] 2023-09-03 12:32:59 -07:00
Andrew Kane
b1f9519689 Get info from metapage to determine cost 2023-09-03 12:31:01 -07:00
Andrew Kane
4571fccc60 Fixed previous commit 2023-09-03 10:51:56 -07:00
Andrew Kane
db747e5aa0 Get lists from metapage 2023-09-03 10:34:44 -07:00
Andrew Kane
2179414c05 Updated extension comment [skip ci] 2023-09-03 03:08:35 -07:00
Andrew Kane
8426ee61d2 Improved upgrading instructions [skip ci] 2023-09-03 03:02:10 -07:00
Andrew Kane
c98c4e13aa Added query for checking version to readme [skip ci] 2023-09-03 02:57:56 -07:00
Andrew Kane
04312f6638 Simplified HNSW vacuum logic 2023-09-03 02:25:19 -07:00
Andrew Kane
72ea3c1210 Added GetScanValue function 2023-09-03 01:59:27 -07:00
Andrew Kane
b0801b8833 Fixed vacuum from previous commit 2023-09-03 01:58:45 -07:00
Andrew Kane
d05d6ee83d Get m from metapage 2023-09-03 01:35:21 -07:00
Andrew Kane
4022bb66a0 Improved variable scoping 2023-09-02 21:14:31 -07:00
Andrew Kane
034d4acaea Removed comment [skip ci] 2023-09-02 18:23:08 -07:00
Andrew Kane
01f58e470a Revert "Use int64 for wlen"
This reverts commit dbef8d1ad1.
2023-09-02 18:09:10 -07:00
Andrew Kane
dbef8d1ad1 Use int64 for wlen 2023-09-02 17:55:48 -07:00
Andrew Kane
5c005cf57c Revert "No need to increment wlen when removing"
This reverts commit 6b2e215447.
2023-09-02 17:41:31 -07:00
Andrew Kane
5665a11a05 Updated comment [skip ci] 2023-09-02 15:34:33 -07:00
Andrew Kane
6b2e215447 No need to increment wlen when removing 2023-09-02 15:33:40 -07:00
Andrew Kane
0d86191eaf Improved test for cosine distance [skip ci] 2023-09-01 19:59:21 -07:00
Andrew Kane
cf9f7aeea9 Added another test for cosine distance [skip ci] 2023-09-01 19:57:28 -07:00
Andrew Kane
0b0e542ce6 Fixed auto-vectorization for vector_spherical_distance with MSVC 2023-09-01 18:42:37 -07:00
Andrew Kane
a4590d2d9d Simplified WAL tests [skip ci] 2023-09-01 15:49:52 -07:00
Andrew Kane
9ebec1529b Updated comments [skip ci] 2023-09-01 00:35:06 -07:00
Andrew Kane
77ff4c18f0 Updated comments [skip ci] 2023-09-01 00:32:42 -07:00
Andrew Kane
88dabaa41c Added test for IVFFlat insert recall 2023-09-01 00:30:02 -07:00
Andrew Kane
1809ffa52b Renamed test [skip ci] 2023-09-01 00:15:07 -07:00
Andrew Kane
024f283ee8 Updated header order [skip ci] 2023-09-01 00:14:03 -07:00
Andrew Kane
da3b2fab46 Updated readme [skip ci] 2023-08-31 22:20:13 -07:00
Andrew Kane
884026a23c Updated changelog [skip ci] 2023-08-29 10:13:05 -07:00
Andrew Kane
4d352e6c30 Updated changelog [skip ci] 2023-08-29 10:11:53 -07:00
Andrew Kane
a8e257e1f1 Added comments [skip ci] 2023-08-28 22:02:48 -07:00
38 changed files with 1804 additions and 362 deletions

View File

@@ -8,6 +8,8 @@ jobs:
fail-fast: false
matrix:
include:
- postgres: 17
os: ubuntu-22.04
- postgres: 16
os: ubuntu-22.04
- postgres: 15
@@ -21,7 +23,7 @@ jobs:
- postgres: 11
os: ubuntu-20.04
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
@@ -43,7 +45,7 @@ jobs:
runs-on: macos-latest
if: ${{ !startsWith(github.ref_name, 'windows') }}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14
@@ -65,7 +67,7 @@ jobs:
runs-on: windows-latest
if: ${{ !startsWith(github.ref_name, 'mac') }}
steps:
- uses: actions/checkout@v3
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14

View File

@@ -1,13 +1,22 @@
## 0.6.0 (unreleased)
- Added support for sparse vectors
## 0.5.1 (2023-10-10)
- Improved performance of HNSW index builds
- Added check for MVCC-compliant snapshot for index scans
## 0.5.0 (2023-08-28)
- Added HNSW index type
- Added support for parallel index builds
- Added support for parallel index builds for IVFFlat
- Added `l1_distance` function
- Added element-wise multiplication for vectors
- Added `sum` aggregate
- Improved performance of distance functions
- Fixed out of range results for cosine distance
- Fixed results for NULL and NaN distances
- Fixed results for NULL and NaN distances for IVFFlat
## 0.4.4 (2023-06-12)

View File

@@ -2,7 +2,7 @@
"name": "vector",
"abstract": "Open-source vector similarity search for Postgres",
"description": "Supports L2 distance, inner product, and cosine distance",
"version": "0.5.0",
"version": "0.5.1",
"maintainer": [
"Andrew Kane <andrew@ankane.org>"
],
@@ -20,7 +20,7 @@
"vector": {
"file": "sql/vector.sql",
"docfile": "README.md",
"version": "0.5.0",
"version": "0.5.1",
"abstract": "Open-source vector similarity search for Postgres"
}
},

View File

@@ -1,14 +1,14 @@
EXTENSION = vector
EXTVERSION = 0.5.0
EXTVERSION = 0.5.1
MODULE_big = vector
DATA = $(wildcard sql/*--*.sql)
OBJS = src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
HEADERS = src/vector.h
OBJS = src/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/svector.o src/vector.o
HEADERS = src/svector.h src/vector.h
TESTS = $(wildcard test/sql/*.sql)
REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))
REGRESS_OPTS = --inputdir=test --load-extension=vector
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
OPTFLAGS = -march=native

View File

@@ -1,11 +1,11 @@
EXTENSION = vector
EXTVERSION = 0.5.0
EXTVERSION = 0.5.1
OBJS = src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\vector.obj
HEADERS = src\vector.h
OBJS = src\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\svector.obj src\vector.obj
HEADERS = src\svector.h src\vector.h
REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
REGRESS_OPTS = --inputdir=test --load-extension=vector
REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
# For /arch flags
# https://learn.microsoft.com/en-us/cpp/build/reference/arch-minimum-cpu-architecture
@@ -56,7 +56,7 @@ install:
copy $(EXTENSION).control "$(SHAREDIR)\extension"
copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
mkdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
copy $(HEADERS) "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
for %f in ($(HEADERS)) do copy %f "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
installcheck:
"$(BINDIR)\pg_regress" --bindir="$(BINDIR)" $(REGRESS_OPTS) $(REGRESS)

129
README.md
View File

@@ -18,7 +18,7 @@ Compile and install the extension (supports Postgres 11+)
```sh
cd /tmp
git clone --branch v0.5.0 https://github.com/pgvector/pgvector.git
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo
@@ -26,7 +26,7 @@ make install # may need sudo
See the [installation notes](#installation-notes) if you run into issues
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres)
You can also install it with [Docker](#docker), [Homebrew](#homebrew), [PGXN](#pgxn), [APT](#apt), [Yum](#yum), or [conda-forge](#conda-forge), and it comes preinstalled with [Postgres.app](#postgresapp) and many [hosted providers](#hosted-postgres). There are also instructions for [GitHub Actions](https://github.com/pgvector/setup-pgvector).
## Getting Started
@@ -162,7 +162,7 @@ You can add an index to use approximate nearest neighbor search, which trades so
Supported index types are:
- [IVFFlat](#ivfflat)
- [HNSW](#hnsw) - *added in 0.5.0*
- [HNSW](#hnsw) - added in 0.5.0
## IVFFlat
@@ -215,6 +215,23 @@ SELECT ...
COMMIT;
```
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases for IVFFlat are:
1. `initializing`
2. `performing k-means`
3. `assigning tuples`
4. `loading tuples`
Note: `%` is only populated during the `loading tuples` phase
## HNSW
An HNSW index creates a multilayer graph. It has slower build times and uses more memory than IVFFlat, but has better query performance (in terms of speed-recall tradeoff). Theres no training step like IVFFlat, so the index can be created without any data in the table.
@@ -271,22 +288,18 @@ SELECT ...
COMMIT;
```
## Indexing Progress
### Indexing Progress
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
```sql
SELECT phase, tuples_done, tuples_total FROM pg_stat_progress_create_index;
SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
```
The phases are:
The phases for HNSW are:
1. `initializing`
2. `performing k-means` (IVFFlat only)
3. `assigning tuples` (IVFFlat only)
4. `loading tuples`
Note: `tuples_done` and `tuples_total` are only populated during the `loading tuples` phase
2. `loading tuples`
## Filtering
@@ -317,13 +330,15 @@ CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(cate
## Hybrid Search
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search ([Python example](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search.py)).
Use together with Postgres [full-text search](https://www.postgresql.org/docs/current/textsearch-intro.html) for hybrid search.
```sql
SELECT id, content FROM items, plainto_tsquery('hello search') query
WHERE textsearch @@ query ORDER BY ts_rank_cd(textsearch, query) DESC LIMIT 5;
```
You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search_rrf.py) or a [cross-encoder](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search.py) to combine results.
## Performance
Use `EXPLAIN ANALYZE` to debug performance.
@@ -354,12 +369,33 @@ To speed up queries with an IVFFlat index, increase the number of inverted lists
CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 1000);
```
## Sparse Vectors
Create a sparse vector column with 10 dimensions
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding svector(10));
```
Insert vectors
```sql
INSERT INTO items (embedding) VALUES ('(0,1),(1,2),(2,3)|10|'), ('(0,4),(1,5),(4,6)|10|');
```
Get the nearest neighbors by L2 distance
```sql
SELECT * FROM items ORDER BY embedding <-> '(0,3),(1,1),(2,2)|10|' LIMIT 5;
```
## Languages
Use pgvector from any language with a Postgres client. You can even generate and store vectors in one language and query them in another.
Language | Libraries / Examples
--- | ---
C | [pgvector-c](https://github.com/pgvector/pgvector-c)
C++ | [pgvector-cpp](https://github.com/pgvector/pgvector-cpp)
C# | [pgvector-dotnet](https://github.com/pgvector/pgvector-dotnet)
Crystal | [pgvector-crystal](https://github.com/pgvector/pgvector-crystal)
@@ -367,10 +403,11 @@ Dart | [pgvector-dart](https://github.com/pgvector/pgvector-dart)
Elixir | [pgvector-elixir](https://github.com/pgvector/pgvector-elixir)
Go | [pgvector-go](https://github.com/pgvector/pgvector-go)
Haskell | [pgvector-haskell](https://github.com/pgvector/pgvector-haskell)
Java, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
Java, Kotlin, Groovy, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
JavaScript, TypeScript | [pgvector-node](https://github.com/pgvector/pgvector-node)
Julia | [pgvector-julia](https://github.com/pgvector/pgvector-julia)
Lua | [pgvector-lua](https://github.com/pgvector/pgvector-lua)
Node.js | [pgvector-node](https://github.com/pgvector/pgvector-node)
Nim | [pgvector-nim](https://github.com/pgvector/pgvector-nim)
Perl | [pgvector-perl](https://github.com/pgvector/pgvector-perl)
PHP | [pgvector-php](https://github.com/pgvector/pgvector-php)
Python | [pgvector-python](https://github.com/pgvector/pgvector-python)
@@ -378,6 +415,7 @@ R | [pgvector-r](https://github.com/pgvector/pgvector-r)
Ruby | [pgvector-ruby](https://github.com/pgvector/pgvector-ruby), [Neighbor](https://github.com/ankane/neighbor)
Rust | [pgvector-rust](https://github.com/pgvector/pgvector-rust)
Swift | [pgvector-swift](https://github.com/pgvector/pgvector-swift)
Zig | [pgvector-zig](https://github.com/pgvector/pgvector-zig)
## Frequently Asked Questions
@@ -393,6 +431,55 @@ Yes, pgvector uses the write-ahead log (WAL), which allows for replication and p
Youll need to use [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction) at the moment.
#### Can I store vectors with different dimensions in the same column?
You can use `vector` as the type (instead of `vector(3)`).
```sql
CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id));
```
However, you can only create indexes on rows with the same number of dimensions (using [expression](https://www.postgresql.org/docs/current/indexes-expressional.html) and [partial](https://www.postgresql.org/docs/current/indexes-partial.html) indexing):
```sql
CREATE INDEX ON embeddings USING hnsw ((embedding::vector(3)) vector_l2_ops) WHERE (model_id = 123);
```
and query with:
```sql
SELECT * FROM embeddings WHERE model_id = 123 ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
```
#### Can I store vectors with more precision?
You can use the `double precision[]` or `numeric[]` type to store vectors with more precision.
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding double precision[]);
-- use {} instead of [] for Postgres arrays
INSERT INTO items (embedding) VALUES ('{1,2,3}'), ('{4,5,6}');
```
Optionally, add a [check constraint](https://www.postgresql.org/docs/current/ddl-constraints.html) to ensure data can be converted to the `vector` type and has the expected dimensions.
```sql
ALTER TABLE items ADD CHECK (vector_dims(embedding::vector) = 3);
```
Use [expression indexing](https://www.postgresql.org/docs/current/indexes-expressional.html) to index (at a lower precision):
```sql
CREATE INDEX ON items USING hnsw ((embedding::vector(3)) vector_l2_ops);
```
and query with:
```sql
SELECT * FROM items ORDER BY embedding::vector(3) <-> '[3,1,2]' LIMIT 5;
```
## Troubleshooting
#### Why isnt a query using an index?
@@ -406,6 +493,8 @@ SELECT ...
COMMIT;
```
Also, if the table is small, a table scan may be faster.
#### Why isnt a query using a parallel table scan?
The planner doesnt consider [out-of-line storage](https://www.postgresql.org/docs/current/storage-toast.html) in cost estimates, which can make a serial scan look cheaper. You can reduce the cost of a parallel scan for a query with:
@@ -509,7 +598,7 @@ Then use `nmake` to build:
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\15"
git clone --branch v0.5.0 https://github.com/pgvector/pgvector.git
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
@@ -530,7 +619,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
You can also build the image manually:
```sh
git clone --branch v0.5.0 https://github.com/pgvector/pgvector.git
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
cd pgvector
docker build --build-arg PG_MAJOR=15 -t myuser/pgvector .
```
@@ -595,12 +684,18 @@ pgvector is available on [these providers](https://github.com/pgvector/pgvector/
## Upgrading
Install the latest version and run:
[Install](#installation) the latest version (use the same method as the original installation). Then in each database you want to upgrade, run:
```sql
ALTER EXTENSION vector UPDATE;
```
You can check the version in the current database with:
```sql
SELECT extversion FROM pg_extension WHERE extname = 'vector';
```
## Upgrade Notes
### 0.4.0

View File

@@ -0,0 +1,2 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.5.1'" to load this file. \quit

View File

@@ -0,0 +1,79 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.6.0'" to load this file. \quit
CREATE TYPE svector;
CREATE FUNCTION svector_in(cstring, oid, integer) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_out(svector) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_recv(internal, oid, integer) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_send(svector) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE svector (
INPUT = svector_in,
OUTPUT = svector_out,
TYPMOD_IN = svector_typmod_in,
RECEIVE = svector_recv,
SEND = svector_send,
STORAGE = external
);
CREATE FUNCTION l2_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_jaccard_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_l2_squared_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_negative_inner_product(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector(svector, integer, boolean) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_svector(vector, integer, boolean) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_to_vector(svector, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (svector AS svector)
WITH FUNCTION svector(svector, integer, boolean) AS IMPLICIT;
CREATE CAST (svector AS vector)
WITH FUNCTION svector_to_vector(svector, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS svector)
WITH FUNCTION vector_to_svector(vector, integer, boolean) AS IMPLICIT;
CREATE OPERATOR <-> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = svector_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);

View File

@@ -290,3 +290,92 @@ CREATE OPERATOR CLASS vector_cosine_ops
OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops,
FUNCTION 1 vector_negative_inner_product(vector, vector),
FUNCTION 2 vector_norm(vector);
--- svector type
CREATE TYPE svector;
CREATE FUNCTION svector_in(cstring, oid, integer) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_out(svector) RETURNS cstring
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_typmod_in(cstring[]) RETURNS integer
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_recv(internal, oid, integer) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_send(svector) RETURNS bytea
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE TYPE svector (
INPUT = svector_in,
OUTPUT = svector_out,
TYPMOD_IN = svector_typmod_in,
RECEIVE = svector_recv,
SEND = svector_send,
STORAGE = external
);
-- svector functions
CREATE FUNCTION l2_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION inner_product(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION cosine_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION jaccard_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME', 'svector_jaccard_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- svector private functions
CREATE FUNCTION svector_l2_squared_distance(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_negative_inner_product(svector, svector) RETURNS float8
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- svector cast functions
CREATE FUNCTION svector(svector, integer, boolean) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION vector_to_svector(vector, integer, boolean) RETURNS svector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION svector_to_vector(svector, integer, boolean) RETURNS vector
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- svector casts
CREATE CAST (svector AS svector)
WITH FUNCTION svector(svector, integer, boolean) AS IMPLICIT;
CREATE CAST (svector AS vector)
WITH FUNCTION svector_to_vector(svector, integer, boolean) AS IMPLICIT;
CREATE CAST (vector AS svector)
WITH FUNCTION vector_to_svector(vector, integer, boolean) AS IMPLICIT;
-- svector operators
CREATE OPERATOR <-> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = l2_distance,
COMMUTATOR = '<->'
);
CREATE OPERATOR <#> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = svector_negative_inner_product,
COMMUTATOR = '<#>'
);
CREATE OPERATOR <=> (
LEFTARG = svector, RIGHTARG = svector, PROCEDURE = cosine_distance,
COMMUTATOR = '<=>'
);

View File

@@ -91,7 +91,7 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
MemSet(&costs, 0, sizeof(costs));
index = index_open(path->indexinfo->indexoid, NoLock);
m = HnswGetM(index);
HnswGetMetaPageInfo(index, &m, NULL);
index_close(index, NoLock);
/* Approximate entry level */
@@ -196,7 +196,7 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->aminsert = hnswinsert;
amroutine->ambulkdelete = hnswbulkdelete;
amroutine->amvacuumcleanup = hnswvacuumcleanup;
amroutine->amcanreturn = NULL; /* tuple not included in heapsort */
amroutine->amcanreturn = NULL;
amroutine->amcostestimate = hnswcostestimate;
amroutine->amoptions = hnswoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */

View File

@@ -57,6 +57,8 @@
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
#define PROGRESS_HNSW_PHASE_LOAD 2
#define HNSW_MAX_SIZE (BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - sizeof(ItemIdData))
#define HNSW_ELEMENT_TUPLE_SIZE(_dim) MAXALIGN(offsetof(HnswElementTupleData, vec) + VECTOR_SIZE(_dim))
#define HNSW_NEIGHBOR_TUPLE_SIZE(level, m) MAXALIGN(offsetof(HnswNeighborTupleData, indextids) + ((level) + 2) * (m) * sizeof(ItemPointerData))
@@ -110,11 +112,13 @@ typedef struct HnswCandidate
{
HnswElement element;
float distance;
bool closer;
} HnswCandidate;
typedef struct HnswNeighborArray
{
int length;
bool closerSet;
HnswCandidate *items;
} HnswNeighborArray;
@@ -218,7 +222,6 @@ typedef HnswNeighborTupleData * HnswNeighborTuple;
typedef struct HnswScanOpaqueData
{
bool first;
Buffer buf;
List *w;
MemoryContext tmpCtx;
@@ -259,15 +262,16 @@ typedef struct HnswVacuumState
/* Methods */
int HnswGetM(Relation index);
int HnswGetEfConstruction(Relation index);
FmgrInfo *HnswOptionalProcInfo(Relation rel, uint16 procnum);
FmgrInfo *HnswOptionalProcInfo(Relation index, uint16 procnum);
bool HnswNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
void HnswCommitBuffer(Buffer buf, GenericXLogState *state);
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
void HnswInitPage(Buffer buf, Page page);
void HnswInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state);
void HnswInit(void);
List *HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, bool inserting, HnswElement skipElement);
List *HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement);
HnswElement HnswGetEntryPoint(Relation index);
void HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint);
HnswElement HnswInitElement(ItemPointer tid, int m, double ml, int maxLevel);
void HnswFreeElement(HnswElement element);
HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno);
@@ -284,7 +288,7 @@ void HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool
void HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswSetElementTuple(HnswElementTuple etup, HnswElement element);
void HnswUpdateConnection(HnswElement element, HnswCandidate * hc, int m, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
void HnswLoadNeighbors(HnswElement element, Relation index);
void HnswLoadNeighbors(HnswElement element, Relation index, int m);
/* Index access methods */
IndexBuildResult *hnswbuild(Relation heap, Relation index, IndexInfo *indexInfo);

View File

@@ -81,7 +81,6 @@ HnswBuildAppendPage(Relation index, Buffer *buf, Page *page, GenericXLogState **
HnswPageGetOpaque(*page)->nextblkno = BufferGetBlockNumber(newbuf);
/* Commit */
MarkBufferDirty(*buf);
GenericXLogFinish(*state);
UnlockReleaseBuffer(*buf);
@@ -118,12 +117,12 @@ CreateElementPages(HnswBuildState * buildstate)
ListCell *lc;
/* Calculate sizes */
maxSize = BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData));
maxSize = HNSW_MAX_SIZE;
etupSize = HNSW_ELEMENT_TUPLE_SIZE(dimensions);
/* Allocate once */
etup = palloc0(etupSize);
ntup = palloc0(maxSize);
ntup = palloc0(BLCKSZ);
/* Prepare first page */
buf = HnswNewBuffer(index, forkNum);
@@ -179,7 +178,6 @@ CreateElementPages(HnswBuildState * buildstate)
insertPage = BufferGetBlockNumber(buf);
/* Commit */
MarkBufferDirty(buf);
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
@@ -227,7 +225,6 @@ CreateNeighborPages(HnswBuildState * buildstate)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Commit */
MarkBufferDirty(buf);
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
}

View File

@@ -135,7 +135,7 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
etupSize = HNSW_ELEMENT_TUPLE_SIZE(dimensions);
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
maxSize = BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData));
maxSize = HNSW_MAX_SIZE;
minCombinedSize = etupSize + HNSW_NEIGHBOR_TUPLE_SIZE(0, m) + sizeof(ItemIdData);
/* Prepare element tuple */
@@ -202,8 +202,6 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
HnswInsertAppendPage(index, &newbuf, &newpage, state, page);
/* Commit */
MarkBufferDirty(newbuf);
MarkBufferDirty(buf);
GenericXLogFinish(state);
/* Unlock previous buffer */
@@ -270,9 +268,6 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
}
/* Commit */
MarkBufferDirty(buf);
if (nbuf != buf)
MarkBufferDirty(nbuf);
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
if (nbuf != buf)
@@ -329,7 +324,7 @@ HnswUpdateNeighborPages(Relation index, FmgrInfo *procinfo, Oid collation, HnswE
/* Get latest neighbors since they may have changed */
/* Do not lock yet since selecting neighbors can take time */
HnswLoadNeighbors(hc->element, index);
HnswLoadNeighbors(hc->element, index, m);
/*
* Could improve performance for vacuuming by checking neighbors
@@ -391,7 +386,6 @@ HnswUpdateNeighborPages(Relation index, FmgrInfo *procinfo, Oid collation, HnswE
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Commit */
MarkBufferDirty(buf);
GenericXLogFinish(state);
}
else
@@ -445,7 +439,6 @@ HnswAddDuplicate(Relation index, HnswElement element, HnswElement dup)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Commit */
MarkBufferDirty(buf);
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
@@ -492,9 +485,8 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
FmgrInfo *normprocinfo;
HnswElement entryPoint;
HnswElement element;
int m = HnswGetM(index);
int m;
int efConstruction = HnswGetEfConstruction(index);
double ml = HnswGetMl(m);
FmgrInfo *procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
Oid collation = index->rd_indcollation[0];
HnswElement dup;
@@ -511,10 +503,6 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
return false;
}
/* Create an element */
element = HnswInitElement(heap_tid, m, ml, HnswGetMaxLevel(m));
element->vec = DatumGetVector(value);
/*
* Get a shared lock. This allows vacuum to ensure no in-flight inserts
* before repairing graph. Use a page lock so it does not interfere with
@@ -522,8 +510,12 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
*/
LockPage(index, HNSW_UPDATE_LOCK, lockmode);
/* Get entry point */
entryPoint = HnswGetEntryPoint(index);
/* Get m and entry point */
HnswGetMetaPageInfo(index, &m, &entryPoint);
/* Create an element */
element = HnswInitElement(heap_tid, m, HnswGetMl(m), HnswGetMaxLevel(m));
element->vec = DatumGetVector(value);
/* Prevent concurrent inserts when likely updating entry point */
if (entryPoint == NULL || element->level > entryPoint->level)

View File

@@ -19,7 +19,11 @@ GetScanItems(IndexScanDesc scan, Datum q)
Oid collation = so->collation;
List *ep;
List *w;
HnswElement entryPoint = HnswGetEntryPoint(index);
int m;
HnswElement entryPoint;
/* Get m and entry point */
HnswGetMetaPageInfo(index, &m, &entryPoint);
if (entryPoint == NULL)
return NIL;
@@ -28,11 +32,11 @@ GetScanItems(IndexScanDesc scan, Datum q)
for (int lc = entryPoint->level; lc >= 1; lc--)
{
w = HnswSearchLayer(q, ep, 1, lc, index, procinfo, collation, false, NULL);
w = HnswSearchLayer(q, ep, 1, lc, index, procinfo, collation, m, false, NULL);
ep = w;
}
return HnswSearchLayer(q, ep, hnsw_ef_search, 0, index, procinfo, collation, false, NULL);
return HnswSearchLayer(q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
}
/*
@@ -58,6 +62,33 @@ GetDimensions(Relation index)
return dimensions;
}
/*
* Get scan value
*/
static Datum
GetScanValue(IndexScanDesc scan)
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
Datum value;
if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
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)
HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
}
return value;
}
/*
* Prepare for an index scan
*/
@@ -70,7 +101,6 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
scan = RelationGetIndexScan(index, nkeys, norderbys);
so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData));
so->buf = InvalidBuffer;
so->first = true;
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw scan temporary context",
@@ -130,20 +160,13 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
if (scan->orderByData == NULL)
elog(ERROR, "cannot scan hnsw index without order");
if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
else
{
value = scan->orderByData->sk_argument;
/* Requires MVCC-compliant snapshot as not able to maintain a pin */
/* https://www.postgresql.org/docs/current/index-locking.html */
if (!IsMVCCSnapshot(scan->xs_snapshot))
elog(ERROR, "non-MVCC snapshots are not supported with hnsw");
/* 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)
HnswNormValue(so->normprocinfo, so->collation, &value, NULL);
}
/* Get scan value */
value = GetScanValue(scan);
/*
* Get a shared lock. This allows vacuum to ensure no in-flight scans
@@ -162,40 +185,27 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
while (list_length(so->w) > 0)
{
HnswCandidate *hc = llast(so->w);
ItemPointer tid;
BlockNumber indexblkno;
ItemPointer heaptid;
/* Move to next element if no valid heap tids */
/* Move to next element if no valid heap TIDs */
if (list_length(hc->element->heaptids) == 0)
{
so->w = list_delete_last(so->w);
continue;
}
tid = llast(hc->element->heaptids);
indexblkno = hc->element->blkno;
heaptid = llast(hc->element->heaptids);
hc->element->heaptids = list_delete_last(hc->element->heaptids);
MemoryContextSwitchTo(oldCtx);
#if PG_VERSION_NUM >= 120000
scan->xs_heaptid = *tid;
scan->xs_heaptid = *heaptid;
#else
scan->xs_ctup.t_self = *tid;
scan->xs_ctup.t_self = *heaptid;
#endif
if (BufferIsValid(so->buf))
ReleaseBuffer(so->buf);
/*
* An index scan must maintain a pin on the index page holding the
* item last returned by amgettuple
*
* https://www.postgresql.org/docs/current/index-locking.html
*/
so->buf = ReadBuffer(scan->indexRelation, indexblkno);
scan->xs_recheckorderby = false;
return true;
}
@@ -212,10 +222,6 @@ hnswendscan(IndexScanDesc scan)
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
/* Release pin */
if (BufferIsValid(so->buf))
ReleaseBuffer(so->buf);
MemoryContextDelete(so->tmpCtx);
pfree(so);

View File

@@ -38,12 +38,12 @@ HnswGetEfConstruction(Relation index)
* Get proc
*/
FmgrInfo *
HnswOptionalProcInfo(Relation rel, uint16 procnum)
HnswOptionalProcInfo(Relation index, uint16 procnum)
{
if (!OidIsValid(index_getprocid(rel, 1, procnum)))
if (!OidIsValid(index_getprocid(index, 1, procnum)))
return NULL;
return index_getprocinfo(rel, 1, procnum);
return index_getprocinfo(index, 1, procnum);
}
/*
@@ -117,7 +117,6 @@ HnswInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogState *
void
HnswCommitBuffer(Buffer buf, GenericXLogState *state)
{
MarkBufferDirty(buf);
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
}
@@ -140,9 +139,21 @@ HnswInitNeighbors(HnswElement element, int m)
a = &element->neighbors[lc];
a->length = 0;
a->items = palloc(sizeof(HnswCandidate) * lm);
a->closerSet = false;
}
}
/*
* Free neighbors
*/
static void
HnswFreeNeighbors(HnswElement element)
{
for (int lc = 0; lc <= element->level; lc++)
pfree(element->neighbors[lc].items);
pfree(element->neighbors);
}
/*
* Allocate an element
*/
@@ -174,10 +185,8 @@ HnswInitElement(ItemPointer heaptid, int m, double ml, int maxLevel)
void
HnswFreeElement(HnswElement element)
{
HnswFreeNeighbors(element);
list_free_deep(element->heaptids);
for (int lc = 0; lc <= element->level; lc++)
pfree(element->neighbors[lc].items);
pfree(element->neighbors);
pfree(element->vec);
pfree(element);
}
@@ -210,25 +219,43 @@ HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno)
}
/*
* Get the entry point
* Get the metapage info
*/
HnswElement
HnswGetEntryPoint(Relation index)
void
HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint)
{
Buffer buf;
Page page;
HnswMetaPage metap;
HnswElement entryPoint = NULL;
buf = ReadBuffer(index, HNSW_METAPAGE_BLKNO);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
metap = HnswPageGetMeta(page);
if (BlockNumberIsValid(metap->entryBlkno))
entryPoint = HnswInitElementFromBlock(metap->entryBlkno, metap->entryOffno);
if (m != NULL)
*m = metap->m;
if (entryPoint != NULL)
{
if (BlockNumberIsValid(metap->entryBlkno))
*entryPoint = HnswInitElementFromBlock(metap->entryBlkno, metap->entryOffno);
else
*entryPoint = NULL;
}
UnlockReleaseBuffer(buf);
}
/*
* Get the entry point
*/
HnswElement
HnswGetEntryPoint(Relation index)
{
HnswElement entryPoint;
HnswGetMetaPageInfo(index, NULL, &entryPoint);
return entryPoint;
}
@@ -337,10 +364,9 @@ HnswSetNeighborTuple(HnswNeighborTuple ntup, HnswElement e, int m)
* Load neighbors from page
*/
static void
LoadNeighborsFromPage(HnswElement element, Relation index, Page page)
LoadNeighborsFromPage(HnswElement element, Relation index, Page page, int m)
{
HnswNeighborTuple ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, element->neighborOffno));
int m = HnswGetM(index);
int neighborCount = (element->level + 2) * m;
Assert(HnswIsNeighborTuple(ntup));
@@ -381,7 +407,7 @@ LoadNeighborsFromPage(HnswElement element, Relation index, Page page)
* Load neighbors
*/
void
HnswLoadNeighbors(HnswElement element, Relation index)
HnswLoadNeighbors(HnswElement element, Relation index, int m)
{
Buffer buf;
Page page;
@@ -390,7 +416,7 @@ HnswLoadNeighbors(HnswElement element, Relation index)
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
LoadNeighborsFromPage(element, index, page);
LoadNeighborsFromPage(element, index, page, m);
UnlockReleaseBuffer(buf);
}
@@ -543,7 +569,7 @@ AddToVisited(HTAB *v, HnswCandidate * hc, Relation index, bool *found)
* Algorithm 2 from paper
*/
List *
HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, bool inserting, HnswElement skipElement)
HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement)
{
ListCell *lc2;
@@ -598,7 +624,7 @@ HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *pro
break;
if (c->element->neighbors == NULL)
HnswLoadNeighbors(c->element, index);
HnswLoadNeighbors(c->element, index, m);
/* Get the neighborhood at layer lc */
neighborhood = &c->element->neighbors[lc];
@@ -667,6 +693,34 @@ HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *pro
return w;
}
/*
* Compare candidate distances
*/
static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistances(const ListCell *a, const ListCell *b)
#else
CompareCandidateDistances(const void *a, const void *b)
#endif
{
HnswCandidate *hca = lfirst((ListCell *) a);
HnswCandidate *hcb = lfirst((ListCell *) b);
if (hca->distance < hcb->distance)
return 1;
if (hca->distance > hcb->distance)
return -1;
if (hca->element < hcb->element)
return 1;
if (hca->element > hcb->element)
return -1;
return 0;
}
/*
* Calculate the distance between elements
*/
@@ -723,33 +777,77 @@ CheckElementCloser(HnswCandidate * e, List *r, int lc, FmgrInfo *procinfo, Oid c
* Algorithm 4 from paper
*/
static List *
SelectNeighbors(List *c, int m, int lc, FmgrInfo *procinfo, Oid collation, HnswCandidate * *pruned)
SelectNeighbors(List *c, int m, int lc, FmgrInfo *procinfo, Oid collation, HnswElement e2, HnswCandidate * newCandidate, HnswCandidate * *pruned, bool sortCandidates)
{
List *r = NIL;
List *w = list_copy(c);
pairingheap *wd;
bool mustCalculate = !e2->neighbors[lc].closerSet;
List *added = NIL;
bool removedAny = false;
if (list_length(w) <= m)
return w;
wd = pairingheap_allocate(CompareNearestCandidates, NULL);
/* Ensure order of candidates is deterministic for closer caching */
if (sortCandidates)
list_sort(w, CompareCandidateDistances);
while (list_length(w) > 0 && list_length(r) < m)
{
/* Assumes w is already ordered desc */
HnswCandidate *e = llast(w);
bool closer;
w = list_delete_last(w);
closer = CheckElementCloser(e, r, lc, procinfo, collation);
/* Use previous state of r and wd to skip work when possible */
if (mustCalculate)
e->closer = CheckElementCloser(e, r, lc, procinfo, collation);
else if (list_length(added) > 0)
{
/*
* If the current candidate was closer, we only need to compare it
* with the other candidates that we have added.
*/
if (e->closer)
{
e->closer = CheckElementCloser(e, added, lc, procinfo, collation);
if (closer)
if (!e->closer)
removedAny = true;
}
else
{
/*
* If we have removed any candidates from closer, a candidate
* that was not closer earlier might now be.
*/
if (removedAny)
{
e->closer = CheckElementCloser(e, r, lc, procinfo, collation);
if (e->closer)
added = lappend(added, e);
}
}
}
else if (e == newCandidate)
{
e->closer = CheckElementCloser(e, r, lc, procinfo, collation);
if (e->closer)
added = lappend(added, e);
}
if (e->closer)
r = lappend(r, e);
else
pairingheap_add(wd, &(CreatePairingHeapNode(e)->ph_node));
}
/* Cached value can only be used in future if sorted deterministically */
e2->neighbors[lc].closerSet = sortCandidates;
/* Keep pruned connections */
while (!pairingheap_is_empty(wd) && list_length(r) < m)
r = lappend(r, ((HnswPairingHeapNode *) pairingheap_remove_first(wd))->inner);
@@ -803,28 +901,6 @@ AddConnections(HnswElement element, List *neighbors, int m, int lc)
a->items[a->length++] = *((HnswCandidate *) lfirst(lc2));
}
/*
* Compare candidate distances
*/
static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistances(const ListCell *a, const ListCell *b)
#else
CompareCandidateDistances(const void *a, const void *b)
#endif
{
HnswCandidate *hca = lfirst((ListCell *) a);
HnswCandidate *hcb = lfirst((ListCell *) b);
if (hca->distance < hcb->distance)
return 1;
if (hca->distance > hcb->distance)
return -1;
return 0;
}
/*
* Update connections
*/
@@ -878,13 +954,12 @@ HnswUpdateConnection(HnswElement element, HnswCandidate * hc, int m, int lc, int
{
List *c = NIL;
/* Add and sort candidates */
/* Add candidates */
for (int i = 0; i < currentNeighbors->length; i++)
c = lappend(c, &currentNeighbors->items[i]);
c = lappend(c, &hc2);
list_sort(c, CompareCandidateDistances);
SelectNeighbors(c, m, lc, procinfo, collation, &pruned);
SelectNeighbors(c, m, lc, procinfo, collation, hc->element, &hc2, &pruned, true);
/* Should not happen */
if (pruned == NULL)
@@ -956,7 +1031,7 @@ HnswInsertElement(HnswElement element, HnswElement entryPoint, Relation index, F
/* 1st phase: greedy search to insert level */
for (int lc = entryLevel; lc >= level + 1; lc--)
{
w = HnswSearchLayer(q, ep, 1, lc, index, procinfo, collation, true, skipElement);
w = HnswSearchLayer(q, ep, 1, lc, index, procinfo, collation, m, true, skipElement);
ep = w;
}
@@ -974,7 +1049,7 @@ HnswInsertElement(HnswElement element, HnswElement entryPoint, Relation index, F
List *neighbors;
List *lw;
w = HnswSearchLayer(q, ep, efConstruction, lc, index, procinfo, collation, true, skipElement);
w = HnswSearchLayer(q, ep, efConstruction, lc, index, procinfo, collation, m, true, skipElement);
/* Elements being deleted or skipped can help with search */
/* but should be removed before selecting neighbors */
@@ -983,7 +1058,12 @@ HnswInsertElement(HnswElement element, HnswElement entryPoint, Relation index, F
else
lw = w;
neighbors = SelectNeighbors(lw, lm, lc, procinfo, collation, NULL);
/*
* Candidates are sorted, but not deterministically. Could set
* sortCandidates to true for in-memory builds to enable closer
* caching, but there does not seem to be a difference in performance.
*/
neighbors = SelectNeighbors(lw, lm, lc, procinfo, collation, element, NULL, NULL, false);
AddConnections(element, neighbors, lm, lc);

View File

@@ -128,10 +128,7 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
blkno = HnswPageGetOpaque(page)->nextblkno;
if (updated)
{
MarkBufferDirty(buf);
GenericXLogFinish(state);
}
else
GenericXLogAbort(state);
@@ -229,7 +226,6 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Commit */
MarkBufferDirty(buf);
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
@@ -330,7 +326,10 @@ RepairGraph(HnswVacuumState * vacuumstate)
BufferAccessStrategy bas = vacuumstate->bas;
BlockNumber blkno = HNSW_HEAD_BLKNO;
/* Wait for inserts to complete */
/*
* Wait for inserts to complete. Inserts before this point may have
* neighbors about to be deleted. Inserts after this point will not.
*/
LockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
UnlockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
@@ -443,7 +442,11 @@ MarkDeleted(HnswVacuumState * vacuumstate)
Relation index = vacuumstate->index;
BufferAccessStrategy bas = vacuumstate->bas;
/* Wait for selects to complete */
/*
* Wait for index scans to complete. Scans before this point may contain
* tuples about to be deleted. Scans after this point will not, since the
* graph has been repaired.
*/
LockPage(index, HNSW_SCAN_LOCK, ExclusiveLock);
UnlockPage(index, HNSW_SCAN_LOCK, ExclusiveLock);
@@ -540,9 +543,6 @@ MarkDeleted(HnswVacuumState * vacuumstate)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
/* Commit */
MarkBufferDirty(buf);
if (nbuf != buf)
MarkBufferDirty(nbuf);
GenericXLogFinish(state);
if (nbuf != buf)
UnlockReleaseBuffer(nbuf);
@@ -582,7 +582,6 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
vacuumstate->stats = stats;
vacuumstate->callback = callback;
vacuumstate->callback_state = callback_state;
vacuumstate->m = HnswGetM(index);
vacuumstate->efConstruction = HnswGetEfConstruction(index);
vacuumstate->bas = GetAccessStrategy(BAS_BULKREAD);
vacuumstate->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
@@ -592,6 +591,9 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
"Hnsw vacuum temporary context",
ALLOCSET_DEFAULT_SIZES);
/* Get m from metapage */
HnswGetMetaPageInfo(index, &vacuumstate->m, NULL);
/* Create hash table */
hash_ctl.keysize = sizeof(ItemPointerData);
hash_ctl.entrysize = sizeof(ItemPointerData);

View File

@@ -10,8 +10,8 @@
#include "ivfflat.h"
#include "miscadmin.h"
#include "storage/bufmgr.h"
#include "utils/memutils.h"
#include "tcop/tcopprot.h"
#include "utils/memutils.h"
#if PG_VERSION_NUM >= 140000
#include "utils/backend_progress.h"
@@ -506,29 +506,30 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
Buffer buf;
Page page;
GenericXLogState *state;
OffsetNumber offno;
Size itemsz;
Size listSize;
IvfflatList list;
itemsz = MAXALIGN(IVFFLAT_LIST_SIZE(dimensions));
list = palloc(itemsz);
listSize = MAXALIGN(IVFFLAT_LIST_SIZE(dimensions));
list = palloc(listSize);
buf = IvfflatNewBuffer(index, forkNum);
IvfflatInitRegisterPage(index, &buf, &page, &state);
for (int i = 0; i < lists; i++)
{
OffsetNumber offno;
/* Load list */
list->startPage = InvalidBlockNumber;
list->insertPage = InvalidBlockNumber;
memcpy(&list->center, VectorArrayGet(centers, i), VECTOR_SIZE(dimensions));
/* Ensure free space */
if (PageGetFreeSpace(page) < itemsz)
if (PageGetFreeSpace(page) < listSize)
IvfflatAppendPage(index, &buf, &page, &state, forkNum);
/* Add the item */
offno = PageAddItem(page, (Item) list, itemsz, InvalidOffsetNumber, false, false);
offno = PageAddItem(page, (Item) list, listSize, InvalidOffsetNumber, false, false);
if (offno == InvalidOffsetNumber)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));

View File

@@ -71,7 +71,7 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
int lists;
double ratio;
double spc_seq_page_cost;
Relation indexRel;
Relation index;
#if PG_VERSION_NUM < 120000
List *qinfos;
#endif
@@ -89,9 +89,9 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
MemSet(&costs, 0, sizeof(costs));
indexRel = index_open(path->indexinfo->indexoid, NoLock);
lists = IvfflatGetLists(indexRel);
index_close(indexRel, NoLock);
index = index_open(path->indexinfo->indexoid, NoLock);
IvfflatGetMetaPageInfo(index, &lists, NULL);
index_close(index, NoLock);
/* Get the ratio of lists that we need to visit */
ratio = ((double) ivfflat_probes) / lists;

View File

@@ -244,8 +244,8 @@ typedef struct IvfflatScanList
typedef struct IvfflatScanOpaqueData
{
int probes;
int dimensions;
bool first;
Buffer buf;
/* Sorting */
Tuplesortstate *sortstate;
@@ -275,9 +275,10 @@ VectorArray VectorArrayInit(int maxlen, int dimensions);
void VectorArrayFree(VectorArray arr);
void PrintVectorArray(char *msg, VectorArray arr);
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
FmgrInfo *IvfflatOptionalProcInfo(Relation rel, uint16 procnum);
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
int IvfflatGetLists(Relation index);
void IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
void IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);
void IvfflatCommitBuffer(Buffer buf, GenericXLogState *state);
void IvfflatAppendPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state, ForkNumber forkNum);

View File

@@ -11,36 +11,37 @@
* Find the list that minimizes the distance function
*/
static void
FindInsertPage(Relation rel, Datum *values, BlockNumber *insertPage, ListInfo * listInfo)
FindInsertPage(Relation index, Datum *values, BlockNumber *insertPage, ListInfo * listInfo)
{
Buffer cbuf;
Page cpage;
IvfflatList list;
double distance;
double minDistance = DBL_MAX;
BlockNumber nextblkno = IVFFLAT_HEAD_BLKNO;
FmgrInfo *procinfo;
Oid collation;
OffsetNumber offno;
OffsetNumber maxoffno;
/* Avoid compiler warning */
listInfo->blkno = nextblkno;
listInfo->offno = FirstOffsetNumber;
procinfo = index_getprocinfo(rel, 1, IVFFLAT_DISTANCE_PROC);
collation = rel->rd_indcollation[0];
procinfo = index_getprocinfo(index, 1, IVFFLAT_DISTANCE_PROC);
collation = index->rd_indcollation[0];
/* Search all list pages */
while (BlockNumberIsValid(nextblkno))
{
cbuf = ReadBuffer(rel, nextblkno);
Buffer cbuf;
Page cpage;
OffsetNumber maxoffno;
cbuf = ReadBuffer(index, nextblkno);
LockBuffer(cbuf, BUFFER_LOCK_SHARE);
cpage = BufferGetPage(cbuf);
maxoffno = PageGetMaxOffsetNumber(cpage);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
for (OffsetNumber offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
IvfflatList list;
double distance;
list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, offno));
distance = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, values[0], PointerGetDatum(&list->center)));
@@ -63,7 +64,7 @@ FindInsertPage(Relation rel, Datum *values, BlockNumber *insertPage, ListInfo *
* Insert a tuple into the index
*/
static void
InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, Relation heapRel)
{
IndexTuple itup;
Datum value;
@@ -80,33 +81,33 @@ InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Rel
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
/* Normalize if needed */
normprocinfo = IvfflatOptionalProcInfo(rel, IVFFLAT_NORM_PROC);
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL)
{
if (!IvfflatNormValue(normprocinfo, rel->rd_indcollation[0], &value, NULL))
if (!IvfflatNormValue(normprocinfo, index->rd_indcollation[0], &value, NULL))
return;
}
/* Find the insert page - sets the page and list info */
FindInsertPage(rel, values, &insertPage, &listInfo);
FindInsertPage(index, values, &insertPage, &listInfo);
Assert(BlockNumberIsValid(insertPage));
originalInsertPage = insertPage;
/* Form tuple */
itup = index_form_tuple(RelationGetDescr(rel), &value, isnull);
itup = index_form_tuple(RelationGetDescr(index), &value, isnull);
itup->t_tid = *heap_tid;
/* Get tuple size */
itemsz = MAXALIGN(IndexTupleSize(itup));
Assert(itemsz <= BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(IvfflatPageOpaqueData)));
Assert(itemsz <= BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(IvfflatPageOpaqueData)) - sizeof(ItemIdData));
/* Find a page to insert the item */
for (;;)
{
buf = ReadBuffer(rel, insertPage);
buf = ReadBuffer(index, insertPage);
LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
state = GenericXLogStart(rel);
state = GenericXLogStart(index);
page = GenericXLogRegisterBuffer(state, buf, 0);
if (PageGetFreeSpace(page) >= itemsz)
@@ -126,9 +127,9 @@ InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Rel
Page newpage;
/* Add a new page */
LockRelationForExtension(rel, ExclusiveLock);
newbuf = IvfflatNewBuffer(rel, MAIN_FORKNUM);
UnlockRelationForExtension(rel, ExclusiveLock);
LockRelationForExtension(index, ExclusiveLock);
newbuf = IvfflatNewBuffer(index, MAIN_FORKNUM);
UnlockRelationForExtension(index, ExclusiveLock);
/* Init new page */
newpage = GenericXLogRegisterBuffer(state, newbuf, GENERIC_XLOG_FULL_IMAGE);
@@ -141,15 +142,13 @@ InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Rel
IvfflatPageGetOpaque(page)->nextblkno = insertPage;
/* Commit */
MarkBufferDirty(newbuf);
MarkBufferDirty(buf);
GenericXLogFinish(state);
/* Unlock previous buffer */
UnlockReleaseBuffer(buf);
/* Prepare new buffer */
state = GenericXLogStart(rel);
state = GenericXLogStart(index);
buf = newbuf;
page = GenericXLogRegisterBuffer(state, buf, 0);
break;
@@ -158,13 +157,13 @@ InsertTuple(Relation rel, Datum *values, bool *isnull, ItemPointer heap_tid, Rel
/* Add to next offset */
if (PageAddItem(page, (Item) itup, itemsz, InvalidOffsetNumber, false, false) == InvalidOffsetNumber)
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(rel));
elog(ERROR, "failed to add index item to \"%s\"", RelationGetRelationName(index));
IvfflatCommitBuffer(buf, state);
/* Update the insert page */
if (insertPage != originalInsertPage)
IvfflatUpdateList(rel, listInfo, insertPage, originalInsertPage, InvalidBlockNumber, MAIN_FORKNUM);
IvfflatUpdateList(index, listInfo, insertPage, originalInsertPage, InvalidBlockNumber, MAIN_FORKNUM);
}
/*

View File

@@ -17,10 +17,6 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
FmgrInfo *procinfo;
Oid collation;
int64 j;
double distance;
double sum;
double choice;
Vector *vec;
float *weight = palloc(samples->length * sizeof(float));
int numCenters = centers->maxlen;
int numSamples = samples->length;
@@ -33,17 +29,21 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
centers->length++;
for (j = 0; j < numSamples; j++)
weight[j] = DBL_MAX;
weight[j] = FLT_MAX;
for (int i = 0; i < numCenters; i++)
{
double sum;
double choice;
CHECK_FOR_INTERRUPTS();
sum = 0.0;
for (j = 0; j < numSamples; j++)
{
vec = VectorArrayGet(samples, j);
Vector *vec = VectorArrayGet(samples, j);
double distance;
/* Only need to compute distance for new center */
/* TODO Use triangle inequality to reduce distance calculations */
@@ -112,7 +112,6 @@ CompareVectors(const void *a, const void *b)
static void
QuickCenters(Relation index, VectorArray samples, VectorArray centers)
{
Vector *vec;
int dimensions = centers->dim;
Oid collation = index->rd_indcollation[0];
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
@@ -123,7 +122,7 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
for (int i = 0; i < samples->length; i++)
{
vec = VectorArrayGet(samples, i);
Vector *vec = VectorArrayGet(samples, i);
if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
{
@@ -136,7 +135,7 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
/* Fill remaining with random data */
while (centers->length < centers->maxlen)
{
vec = VectorArrayGet(centers, centers->length);
Vector *vec = VectorArrayGet(centers, centers->length);
SET_VARSIZE(vec, VECTOR_SIZE(dimensions));
vec->dim = dimensions;
@@ -168,7 +167,6 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
Oid collation;
Vector *vec;
Vector *newCenter;
int iteration;
int64 j;
int64 k;
int dimensions = centers->dim;
@@ -182,14 +180,6 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
float *s;
float *halfcdist;
float *newcdist;
int changes;
double minDistance;
int closestCenter;
double distance;
bool rj;
bool rjreset;
double dxcx;
double dxc;
/* Calculate allocation sizes */
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->dim);
@@ -247,14 +237,14 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Assign each x to its closest initial center c(x) = argmin d(x,c) */
for (j = 0; j < numSamples; j++)
{
minDistance = DBL_MAX;
closestCenter = 0;
float minDistance = FLT_MAX;
int closestCenter = 0;
/* Find closest center */
for (k = 0; k < numCenters; k++)
{
/* TODO Use Lemma 1 in k-means++ initialization */
distance = lowerBound[j * numCenters + k];
float distance = lowerBound[j * numCenters + k];
if (distance < minDistance)
{
@@ -268,13 +258,14 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
}
/* Give 500 iterations to converge */
for (iteration = 0; iteration < 500; iteration++)
for (int iteration = 0; iteration < 500; iteration++)
{
int changes = 0;
bool rjreset;
/* Can take a while, so ensure we can interrupt */
CHECK_FOR_INTERRUPTS();
changes = 0;
/* Step 1: For all centers, compute distance */
for (j = 0; j < numCenters; j++)
{
@@ -282,7 +273,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
for (k = j + 1; k < numCenters; k++)
{
distance = 0.5 * DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(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[k * numCenters + j] = distance;
}
@@ -291,10 +283,12 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* For all centers c, compute s(c) */
for (j = 0; j < numCenters; j++)
{
minDistance = DBL_MAX;
float minDistance = FLT_MAX;
for (k = 0; k < numCenters; k++)
{
float distance;
if (j == k)
continue;
@@ -310,6 +304,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
for (j = 0; j < numSamples; j++)
{
bool rj;
/* Step 2: Identify all points x such that u(x) <= s(c(x)) */
if (upperBound[j] <= s[closestCenters[j]])
continue;
@@ -318,6 +314,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
for (k = 0; k < numCenters; k++)
{
float dxcx;
/* Step 3: For all remaining points x and centers c */
if (k == closestCenters[j])
continue;
@@ -347,7 +345,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Step 3b */
if (dxcx > lowerBound[j * numCenters + k] || dxcx > halfcdist[closestCenters[j] * numCenters + k])
{
dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
float dxc = DatumGetFloat8(FunctionCall2Coll(procinfo, collation, PointerGetDatum(vec), PointerGetDatum(VectorArrayGet(centers, k))));
/* d(x,c) calculated */
lowerBound[j * numCenters + k] = dxc;
@@ -361,7 +359,6 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
changes++;
}
}
}
}
@@ -378,6 +375,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
for (j = 0; j < numSamples; j++)
{
int closestCenter;
vec = VectorArrayGet(samples, j);
closestCenter = closestCenters[j];
@@ -426,7 +425,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
{
for (k = 0; k < numCenters; k++)
{
distance = lowerBound[j * numCenters + k] - newcdist[k];
float distance = lowerBound[j * numCenters + k] - newcdist[k];
if (distance < 0)
distance = 0;
@@ -442,7 +441,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
/* Step 7 */
for (j = 0; j < numCenters; j++)
memcpy(VectorArrayGet(centers, j), VectorArrayGet(newCenters, j), VECTOR_SIZE(dimensions));
VectorArraySet(centers, j, VectorArrayGet(newCenters, j));
if (changes == 0 && iteration != 0)
break;
@@ -465,9 +464,6 @@ static void
CheckCenters(Relation index, VectorArray centers)
{
FmgrInfo *normprocinfo;
Oid collation;
Vector *vec;
double norm;
if (centers->length != centers->maxlen)
elog(ERROR, "Not enough centers. Please report a bug.");
@@ -475,7 +471,7 @@ CheckCenters(Relation index, VectorArray centers)
/* Ensure no NaN or infinite values */
for (int i = 0; i < centers->length; i++)
{
vec = VectorArrayGet(centers, i);
Vector *vec = VectorArrayGet(centers, i);
for (int j = 0; j < vec->dim; j++)
{
@@ -501,11 +497,12 @@ CheckCenters(Relation index, VectorArray centers)
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
if (normprocinfo != NULL)
{
collation = index->rd_indcollation[0];
Oid collation = index->rd_indcollation[0];
for (int i = 0; i < centers->length; i++)
{
norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(VectorArrayGet(centers, i))));
double norm = DatumGetFloat8(FunctionCall1Coll(normprocinfo, collation, PointerGetDatum(VectorArrayGet(centers, i))));
if (norm == 0)
elog(ERROR, "Zero norm detected. Please report a bug.");
}

View File

@@ -31,36 +31,36 @@ CompareLists(const pairingheap_node *a, const pairingheap_node *b, void *arg)
static void
GetScanLists(IndexScanDesc scan, Datum value)
{
Buffer cbuf;
Page cpage;
IvfflatList list;
OffsetNumber offno;
OffsetNumber maxoffno;
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
BlockNumber nextblkno = IVFFLAT_HEAD_BLKNO;
int listCount = 0;
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
double distance;
IvfflatScanList *scanlist;
double maxDistance = DBL_MAX;
/* Search all list pages */
while (BlockNumberIsValid(nextblkno))
{
Buffer cbuf;
Page cpage;
OffsetNumber maxoffno;
cbuf = ReadBuffer(scan->indexRelation, nextblkno);
LockBuffer(cbuf, BUFFER_LOCK_SHARE);
cpage = BufferGetPage(cbuf);
maxoffno = PageGetMaxOffsetNumber(cpage);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
for (OffsetNumber offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, offno));
IvfflatList list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, offno));
double distance;
/* Use procinfo from the index instead of scan key for performance */
distance = DatumGetFloat8(FunctionCall2Coll(so->procinfo, so->collation, PointerGetDatum(&list->center), value));
if (listCount < so->probes)
{
IvfflatScanList *scanlist;
scanlist = &so->lists[listCount];
scanlist->startPage = list->startPage;
scanlist->distance = distance;
@@ -75,6 +75,8 @@ GetScanLists(IndexScanDesc scan, Datum value)
}
else if (distance < maxDistance)
{
IvfflatScanList *scanlist;
/* Remove */
scanlist = (IvfflatScanList *) pairingheap_remove_first(so->listQueue);
@@ -101,14 +103,6 @@ static void
GetScanItems(IndexScanDesc scan, Datum value)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
Buffer buf;
Page page;
IndexTuple itup;
BlockNumber searchPage;
OffsetNumber offno;
OffsetNumber maxoffno;
Datum datum;
bool isnull;
TupleDesc tupdesc = RelationGetDescr(scan->indexRelation);
double tuples = 0;
@@ -128,19 +122,28 @@ GetScanItems(IndexScanDesc scan, Datum value)
/* Search closest probes lists */
while (!pairingheap_is_empty(so->listQueue))
{
searchPage = ((IvfflatScanList *) pairingheap_remove_first(so->listQueue))->startPage;
BlockNumber searchPage = ((IvfflatScanList *) pairingheap_remove_first(so->listQueue))->startPage;
/* Search all entry pages for list */
while (BlockNumberIsValid(searchPage))
{
Buffer buf;
Page page;
OffsetNumber maxoffno;
buf = ReadBufferExtended(scan->indexRelation, MAIN_FORKNUM, searchPage, RBM_NORMAL, bas);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
maxoffno = PageGetMaxOffsetNumber(page);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
for (OffsetNumber offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
itup = (IndexTuple) PageGetItem(page, PageGetItemId(page, offno));
IndexTuple itup;
Datum datum;
bool isnull;
ItemId itemid = PageGetItemId(page, offno);
itup = (IndexTuple) PageGetItem(page, itemid);
datum = index_getattr(itup, 1, tupdesc, &isnull);
/*
@@ -154,8 +157,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
slot->tts_isnull[0] = false;
slot->tts_values[1] = PointerGetDatum(&itup->t_tid);
slot->tts_isnull[1] = false;
slot->tts_values[2] = Int32GetDatum((int) searchPage);
slot->tts_isnull[2] = false;
ExecStoreVirtualTuple(slot);
tuplesort_puttupleslot(so->sortstate, slot);
@@ -180,29 +181,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
tuplesort_performsort(so->sortstate);
}
/*
* Get dimensions from metapage
*/
static int
GetDimensions(Relation index)
{
Buffer buf;
Page page;
IvfflatMetaPage metap;
int dimensions;
buf = ReadBuffer(index, IVFFLAT_METAPAGE_BLKNO);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
metap = IvfflatPageGetMeta(page);
dimensions = metap->dimensions;
UnlockReleaseBuffer(buf);
return dimensions;
}
/*
* Prepare for an index scan
*/
@@ -212,6 +190,7 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
IndexScanDesc scan;
IvfflatScanOpaque so;
int lists;
int dimensions;
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Float8LessOperator};
Oid sortCollations[] = {InvalidOid};
@@ -219,15 +198,17 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
int probes = ivfflat_probes;
scan = RelationGetIndexScan(index, nkeys, norderbys);
lists = IvfflatGetLists(scan->indexRelation);
/* Get lists and dimensions from metapage */
IvfflatGetMetaPageInfo(index, &lists, &dimensions);
if (probes > lists)
probes = lists;
so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
so->buf = InvalidBuffer;
so->first = true;
so->probes = probes;
so->dimensions = dimensions;
/* Set support functions */
so->procinfo = index_getprocinfo(index, 1, IVFFLAT_DISTANCE_PROC);
@@ -236,13 +217,12 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
/* Create tuple description for sorting */
#if PG_VERSION_NUM >= 120000
so->tupdesc = CreateTemplateTupleDesc(3);
so->tupdesc = CreateTemplateTupleDesc(2);
#else
so->tupdesc = CreateTemplateTupleDesc(3, false);
so->tupdesc = CreateTemplateTupleDesc(2, false);
#endif
TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 3, "indexblkno", INT4OID, -1, 0);
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
/* Prep sort */
so->sortstate = tuplesort_begin_heap(so->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
@@ -308,8 +288,13 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
if (scan->orderByData == NULL)
elog(ERROR, "cannot scan ivfflat index without order");
/* Requires MVCC-compliant snapshot as not able to pin during sorting */
/* https://www.postgresql.org/docs/current/index-locking.html */
if (!IsMVCCSnapshot(scan->xs_snapshot))
elog(ERROR, "non-MVCC snapshots are not supported with ivfflat");
if (scan->orderByData->sk_flags & SK_ISNULL)
value = PointerGetDatum(InitVector(GetDimensions(scan->indexRelation)));
value = PointerGetDatum(InitVector(so->dimensions));
else
{
value = scan->orderByData->sk_argument;
@@ -334,26 +319,14 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
if (tuplesort_gettupleslot(so->sortstate, true, false, so->slot, NULL))
{
ItemPointer tid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
BlockNumber indexblkno = DatumGetInt32(slot_getattr(so->slot, 3, &so->isnull));
ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
#if PG_VERSION_NUM >= 120000
scan->xs_heaptid = *tid;
scan->xs_heaptid = *heaptid;
#else
scan->xs_ctup.t_self = *tid;
scan->xs_ctup.t_self = *heaptid;
#endif
if (BufferIsValid(so->buf))
ReleaseBuffer(so->buf);
/*
* An index scan must maintain a pin on the index page holding the
* item last returned by amgettuple
*
* https://www.postgresql.org/docs/current/index-locking.html
*/
so->buf = ReadBuffer(scan->indexRelation, indexblkno);
scan->xs_recheckorderby = false;
return true;
}
@@ -369,10 +342,6 @@ ivfflatendscan(IndexScanDesc scan)
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
/* Release pin */
if (BufferIsValid(so->buf))
ReleaseBuffer(so->buf);
pairingheap_free(so->listQueue);
tuplesort_end(so->sortstate);

View File

@@ -57,12 +57,12 @@ IvfflatGetLists(Relation index)
* Get proc
*/
FmgrInfo *
IvfflatOptionalProcInfo(Relation rel, uint16 procnum)
IvfflatOptionalProcInfo(Relation index, uint16 procnum)
{
if (!OidIsValid(index_getprocid(rel, 1, procnum)))
if (!OidIsValid(index_getprocid(index, 1, procnum)))
return NULL;
return index_getprocinfo(rel, 1, procnum);
return index_getprocinfo(index, 1, procnum);
}
/*
@@ -136,7 +136,6 @@ IvfflatInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogStat
void
IvfflatCommitBuffer(Buffer buf, GenericXLogState *state)
{
MarkBufferDirty(buf);
GenericXLogFinish(state);
UnlockReleaseBuffer(buf);
}
@@ -160,8 +159,6 @@ IvfflatAppendPage(Relation index, Buffer *buf, Page *page, GenericXLogState **st
IvfflatInitPage(newbuf, newpage);
/* Commit */
MarkBufferDirty(*buf);
MarkBufferDirty(newbuf);
GenericXLogFinish(*state);
/* Unlock */
@@ -172,6 +169,29 @@ IvfflatAppendPage(Relation index, Buffer *buf, Page *page, GenericXLogState **st
*buf = newbuf;
}
/*
* Get the metapage info
*/
void
IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions)
{
Buffer buf;
Page page;
IvfflatMetaPage metap;
buf = ReadBuffer(index, IVFFLAT_METAPAGE_BLKNO);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
metap = IvfflatPageGetMeta(page);
*lists = metap->lists;
if (dimensions != NULL)
*dimensions = metap->dimensions;
UnlockReleaseBuffer(buf);
}
/*
* Update the start or insert page of a list
*/

View File

@@ -107,7 +107,6 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
{
/* Delete tuples */
PageIndexMultiDelete(page, deletable, ndeletable);
MarkBufferDirty(buf);
GenericXLogFinish(state);
}
else

705
src/svector.c Normal file
View File

@@ -0,0 +1,705 @@
#include "postgres.h"
#include <math.h>
#include "fmgr.h"
#include "libpq/pqformat.h"
#include "svector.h"
#include "utils/array.h"
#include "vector.h"
#if PG_VERSION_NUM >= 120000
#include "common/shortest_dec.h"
#include "utils/float.h"
#else
#include <float.h>
#include "utils/builtins.h"
#endif
/*
* Ensure same dimensions
*/
static inline void
CheckDims(SVector * a, SVector * b)
{
if (a->dim != b->dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("different svector dimensions %d and %d", a->dim, b->dim)));
}
/*
* Ensure expected dimensions
*/
static inline void
CheckExpectedDim(int32 typmod, int dim)
{
if (typmod != -1 && typmod != dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected %d dimensions, not %d", typmod, dim)));
}
/*
* Ensure valid dimensions
*/
static inline void
CheckDim(int dim)
{
if (dim < 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("svector must have at least 1 dimension")));
if (dim > SVECTOR_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("svector cannot have more than %d dimensions", SVECTOR_MAX_DIM)));
}
/*
* Ensure valid nnz
*/
static inline void
CheckNnz(int nnz, int dim)
{
if (nnz < 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("svector must have at least one element")));
if (nnz > dim)
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("svector cannot have more elements than dimensions")));
}
/*
* Ensure valid index
*/
static inline void
CheckIndex(int32 *indices, int i, int dim)
{
int32 index = indices[i];
if (index < 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("index must not be negative")));
if (index >= dim)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("index must be less than dimensions")));
if (i > 0)
{
if (index < indices[i - 1])
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("indexes must be in ascending order")));
if (index == indices[i - 1])
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("indexes must not contain duplicates")));
}
}
/*
* Ensure finite element
*/
static inline void
CheckElement(float value)
{
if (isnan(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("NaN not allowed in svector")));
if (isinf(value))
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("infinite value not allowed in svector")));
}
/*
* Allocate and initialize a new sparse vector
*/
SVector *
InitSVector(int dim, int nnz)
{
SVector *result;
int size;
size = SVECTOR_SIZE(nnz);
result = (SVector *) palloc0(size);
SET_VARSIZE(result, size);
result->dim = dim;
result->nnz = nnz;
return result;
}
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_in);
Datum
svector_in(PG_FUNCTION_ARGS)
{
char *str = PG_GETARG_CSTRING(0);
int32 typmod = PG_GETARG_INT32(2);
int dim;
char *pt;
SVector *result;
float *rvalues;
char *lit = pstrdup(str);
int n;
int32 *indices;
float *values;
int index;
float value;
int maxNnz;
int nnz = 0;
/* TODO Improve code and checks after deciding on format */
maxNnz = 1;
pt = str;
while (*pt != '\0')
{
if (*pt == ',')
maxNnz++;
pt++;
}
maxNnz /= 2;
indices = palloc(maxNnz * sizeof(int32));
values = palloc(maxNnz * sizeof(float));
while (sscanf(str, "(%d,%f)%n", &index, &value, &n) == 2)
{
/* TODO Better error */
if (nnz == maxNnz)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("ran out of buffer: \"%s\"", lit)));
/* TODO Decide whether to store zero values */
indices[nnz] = index;
values[nnz] = value;
nnz++;
str += n;
if (*str == ',')
str++;
else if (*str == '|')
break;
else
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed svector literal: \"%s\"", lit)));
}
if (sscanf(str, "|%d|%n", &dim, &n) != 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed svector literal: \"%s\"", lit)));
str += n;
if (*str != '\0')
ereport(ERROR,
(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
errmsg("malformed svector literal: \"%s\"", lit),
errdetail("Junk after closing pipe.")));
pfree(lit);
CheckDim(dim);
CheckExpectedDim(typmod, dim);
result = InitSVector(dim, nnz);
rvalues = SVECTOR_VALUES(result);
for (int i = 0; i < nnz; i++)
{
result->indices[i] = indices[i];
rvalues[i] = values[i];
CheckIndex(result->indices, i, dim);
CheckElement(rvalues[i]);
}
PG_RETURN_POINTER(result);
}
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_out);
Datum
svector_out(PG_FUNCTION_ARGS)
{
SVector *svector = PG_GETARG_SVECTOR_P(0);
float *values = SVECTOR_VALUES(svector);
char *buf;
char *ptr;
int n;
/* TODO Improve code after deciding on format */
#if PG_VERSION_NUM < 120000
int ndig = FLT_DIG + extra_float_digits;
if (ndig < 1)
ndig = 1;
#define FLOAT_SHORTEST_DECIMAL_LEN (ndig + 10)
#endif
/* TODO Move */
#define APPEND_CHAR(ptr, ch) (*(ptr)++ = (ch))
/* TODO Improve */
buf = (char *) palloc((FLOAT_SHORTEST_DECIMAL_LEN + 20) * svector->nnz + 20);
ptr = buf;
for (int i = 0; i < svector->nnz; i++)
{
if (i > 0)
APPEND_CHAR(ptr, ',');
n = sprintf(ptr, "(%d,", svector->indices[i]);
ptr += n;
#if PG_VERSION_NUM >= 120000
n = float_to_shortest_decimal_bufn(values[i], ptr);
#else
n = sprintf(ptr, "%.*g", ndig, values[i]);
#endif
ptr += n;
APPEND_CHAR(ptr, ')');
}
n = sprintf(ptr, "|%d|", svector->dim);
ptr += n;
APPEND_CHAR(ptr, '\0');
PG_FREE_IF_COPY(svector, 0);
PG_RETURN_CSTRING(buf);
}
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_typmod_in);
Datum
svector_typmod_in(PG_FUNCTION_ARGS)
{
ArrayType *ta = PG_GETARG_ARRAYTYPE_P(0);
int32 *tl;
int n;
tl = ArrayGetIntegerTypmods(ta, &n);
if (n != 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("invalid type modifier")));
if (*tl < 1)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type svector must be at least 1")));
if (*tl > SVECTOR_MAX_DIM)
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions for type svector cannot exceed %d", SVECTOR_MAX_DIM)));
PG_RETURN_INT32(*tl);
}
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_recv);
Datum
svector_recv(PG_FUNCTION_ARGS)
{
StringInfo buf = (StringInfo) PG_GETARG_POINTER(0);
int32 typmod = PG_GETARG_INT32(2);
SVector *result;
int32 dim;
int32 nnz;
int32 unused;
float *values;
dim = pq_getmsgint(buf, sizeof(int32));
nnz = pq_getmsgint(buf, sizeof(int32));
unused = pq_getmsgint(buf, sizeof(int32));
CheckDim(dim);
CheckNnz(nnz, dim);
CheckExpectedDim(typmod, dim);
if (unused != 0)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("expected unused to be 0, not %d", unused)));
result = InitSVector(dim, nnz);
values = SVECTOR_VALUES(result);
for (int i = 0; i < nnz; i++)
{
result->indices[i] = pq_getmsgint(buf, sizeof(int32));
CheckIndex(result->indices, i, dim);
}
for (int i = 0; i < nnz; i++)
{
values[i] = pq_getmsgfloat4(buf);
CheckElement(values[i]);
}
PG_RETURN_POINTER(result);
}
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_send);
Datum
svector_send(PG_FUNCTION_ARGS)
{
SVector *svec = PG_GETARG_SVECTOR_P(0);
float *values = SVECTOR_VALUES(svec);
StringInfoData buf;
pq_begintypsend(&buf);
pq_sendint(&buf, svec->dim, sizeof(int32));
pq_sendint(&buf, svec->nnz, sizeof(int32));
pq_sendint(&buf, svec->unused, sizeof(int32));
for (int i = 0; i < svec->nnz; i++)
pq_sendint(&buf, svec->indices[i], sizeof(int32));
for (int i = 0; i < svec->nnz; i++)
pq_sendfloat4(&buf, values[i]);
PG_RETURN_BYTEA_P(pq_endtypsend(&buf));
}
/*
* Convert sparse vector to sparse vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector);
Datum
svector(PG_FUNCTION_ARGS)
{
SVector *svec = PG_GETARG_SVECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
CheckExpectedDim(typmod, svec->dim);
PG_RETURN_POINTER(svec);
}
/*
* Convert dense vector to sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_svector);
Datum
vector_to_svector(PG_FUNCTION_ARGS)
{
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
SVector *result;
int dim = vec->dim;
int nnz = 0;
float *values;
int j = 0;
CheckDim(dim);
CheckExpectedDim(typmod, dim);
for (int i = 0; i < dim; i++)
{
if (vec->x[i] != 0)
nnz++;
}
result = InitSVector(dim, nnz);
values = SVECTOR_VALUES(result);
for (int i = 0; i < dim; i++)
{
if (vec->x[i] != 0)
{
/* Safety check */
if (j == nnz)
elog(ERROR, "safety check failed");
result->indices[j] = i;
values[j] = vec->x[i];
j++;
}
}
PG_RETURN_POINTER(result);
}
/*
* Get the L2 squared distance between sparse vectors
*/
static double
l2_distance_squared_internal(SVector * a, SVector * b)
{
float *ax = SVECTOR_VALUES(a);
float *bx = SVECTOR_VALUES(b);
double distance = 0.0;
int bpos = 0;
for (int i = 0; i < a->nnz; i++)
{
int ai = a->indices[i];
int bi = -1;
for (int j = bpos; j < b->nnz; j++)
{
bi = b->indices[j];
if (ai == bi)
{
double diff = ax[i] - bx[j];
distance += diff * diff;
}
else if (ai > bi)
distance += bx[j] * bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
if (ai != bi)
distance += ax[i] * ax[i];
}
for (int j = bpos; j < b->nnz; j++)
distance += bx[j] * bx[j];
return distance;
}
/*
* Get the L2 distance between sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_l2_distance);
Datum
svector_l2_distance(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(sqrt(l2_distance_squared_internal(a, b)));
}
/*
* Get the L2 squared distance between sparse vectors
* This saves a sqrt calculation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_l2_squared_distance);
Datum
svector_l2_squared_distance(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(l2_distance_squared_internal(a, b));
}
/*
* Get the inner product of two sparse vectors
*/
static double
inner_product_internal(SVector * a, SVector * b)
{
float *ax = SVECTOR_VALUES(a);
float *bx = SVECTOR_VALUES(b);
double distance = 0.0;
int bpos = 0;
for (int i = 0; i < a->nnz; i++)
{
int ai = a->indices[i];
for (int j = bpos; j < b->nnz; j++)
{
int bi = b->indices[j];
/* Only update when the same index */
if (ai == bi)
distance += ax[i] * bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
}
return distance;
}
/*
* Get the inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_inner_product);
Datum
svector_inner_product(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(inner_product_internal(a, b));
}
/*
* Get the negative inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_negative_inner_product);
Datum
svector_negative_inner_product(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_P(1);
CheckDims(a, b);
PG_RETURN_FLOAT8(-inner_product_internal(a, b));
}
/*
* Get the cosine distance between two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_cosine_distance);
Datum
svector_cosine_distance(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_P(1);
float *ax = SVECTOR_VALUES(a);
float *bx = SVECTOR_VALUES(b);
float norma = 0.0;
float normb = 0.0;
double similarity;
CheckDims(a, b);
similarity = inner_product_internal(a, b);
/* Auto-vectorized */
for (int i = 0; i < a->nnz; i++)
norma += ax[i] * ax[i];
/* Auto-vectorized */
for (int i = 0; i < b->nnz; i++)
normb += bx[i] * bx[i];
/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
similarity /= sqrt((double) norma * (double) normb);
#ifdef _MSC_VER
/* /fp:fast may not propagate NaN */
if (isnan(similarity))
PG_RETURN_FLOAT8(NAN);
#endif
/* Keep in range */
if (similarity > 1)
similarity = 1.0;
else if (similarity < -1)
similarity = -1.0;
PG_RETURN_FLOAT8(1.0 - similarity);
}
/*
* Get the weighted Jaccard distance between two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_jaccard_distance);
Datum
svector_jaccard_distance(PG_FUNCTION_ARGS)
{
SVector *a = PG_GETARG_SVECTOR_P(0);
SVector *b = PG_GETARG_SVECTOR_P(1);
float *ax = SVECTOR_VALUES(a);
float *bx = SVECTOR_VALUES(b);
double num = 0.0;
double denom = 0.0;
int bpos = 0;
CheckDims(a, b);
/*
* Weighted Jaccard distance is not defined for vectors with negative
* values. Could check and return NaN if minimal impact on performance.
*/
for (int i = 0; i < a->nnz; i++)
{
int ai = a->indices[i];
int bi = -1;
for (int j = bpos; j < b->nnz; j++)
{
bi = b->indices[j];
if (ai == bi)
{
num += ax[i] < bx[j] ? ax[i] : bx[j];
denom += ax[i] > bx[j] ? ax[i] : bx[j];
}
else if (ai > bi)
denom += bx[j];
/* Update start for next iteration */
if (ai >= bi)
bpos = j + 1;
/* Found or passed it */
if (bi >= ai)
break;
}
if (ai != bi)
denom += ax[i];
}
for (int j = bpos; j < b->nnz; j++)
denom += bx[j];
if (denom > 0)
PG_RETURN_FLOAT8(1.0 - (num / denom));
else
PG_RETURN_FLOAT8(NAN);
}

23
src/svector.h Normal file
View File

@@ -0,0 +1,23 @@
#ifndef SVECTOR_H
#define SVECTOR_H
#define SVECTOR_MAX_DIM 100000
#define SVECTOR_SIZE(_nnz) (offsetof(SVector, indices) + (_nnz) * sizeof(int32) + (_nnz * sizeof(float)))
#define SVECTOR_VALUES(x) ((float *) (((char *) (x)) + offsetof(SVector, indices) + (x)->nnz * sizeof(int32)))
#define DatumGetSVector(x) ((SVector *) PG_DETOAST_DATUM(x))
#define PG_GETARG_SVECTOR_P(x) DatumGetSVector(PG_GETARG_DATUM(x))
#define PG_RETURN_SVECTOR_P(x) PG_RETURN_POINTER(x)
typedef struct SVector
{
int32 vl_len_; /* varlena header (do not touch directly!) */
int32 dim; /* number of dimensions */
int32 nnz;
int32 unused;
int32 indices[FLEXIBLE_ARRAY_MEMBER];
} SVector;
SVector *InitSVector(int dim, int nnz);
#endif

View File

@@ -9,6 +9,7 @@
#include "lib/stringinfo.h"
#include "libpq/pqformat.h"
#include "port.h" /* for strtof() */
#include "svector.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/lsyscache.h"
@@ -89,7 +90,7 @@ CheckDim(int dim)
}
/*
* Ensure finite elements
* Ensure finite element
*/
static inline void
CheckElement(float value)
@@ -437,17 +438,18 @@ vector_send(PG_FUNCTION_ARGS)
/*
* Convert vector to vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector);
Datum
vector(PG_FUNCTION_ARGS)
{
Vector *arg = PG_GETARG_VECTOR_P(0);
Vector *vec = PG_GETARG_VECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
CheckExpectedDim(typmod, arg->dim);
CheckExpectedDim(typmod, vec->dim);
PG_RETURN_POINTER(arg);
PG_RETURN_POINTER(vec);
}
/*
@@ -464,7 +466,6 @@ array_to_vector(PG_FUNCTION_ARGS)
bool typbyval;
char typalign;
Datum *elemsp;
bool *nullsp;
int nelemsp;
if (ARR_NDIM(array) > 1)
@@ -478,7 +479,7 @@ array_to_vector(PG_FUNCTION_ARGS)
errmsg("array must not contain nulls")));
get_typlenbyvalalign(ARR_ELEMTYPE(array), &typlen, &typbyval, &typalign);
deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, &nullsp, &nelemsp);
deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, NULL, &nelemsp);
CheckDim(nelemsp);
CheckExpectedDim(typmod, nelemsp);
@@ -512,6 +513,12 @@ array_to_vector(PG_FUNCTION_ARGS)
errmsg("unsupported array type")));
}
/*
* Free allocation from deconstruct_array. Do not free individual elements
* when pass-by-reference since they point to original array.
*/
pfree(elemsp);
/* Check elements */
for (int i = 0; i < result->dim; i++)
CheckElement(result->x[i]);
@@ -695,6 +702,8 @@ vector_spherical_distance(PG_FUNCTION_ARGS)
{
Vector *a = PG_GETARG_VECTOR_P(0);
Vector *b = PG_GETARG_VECTOR_P(1);
float *ax = a->x;
float *bx = b->x;
float dp = 0.0;
double distance;
@@ -702,7 +711,7 @@ vector_spherical_distance(PG_FUNCTION_ARGS)
/* Auto-vectorized */
for (int i = 0; i < a->dim; i++)
dp += a->x[i] * b->x[i];
dp += ax[i] * bx[i];
distance = (double) dp;
@@ -1143,3 +1152,26 @@ vector_avg(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Convert sparse vector to dense vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(svector_to_vector);
Datum
svector_to_vector(PG_FUNCTION_ARGS)
{
SVector *svec = PG_GETARG_SVECTOR_P(0);
int32 typmod = PG_GETARG_INT32(1);
Vector *result;
int dim = svec->dim;
float *values = SVECTOR_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

@@ -54,79 +54,85 @@ SELECT vector_norm('[3e37,4e37]')::real;
5e+37
(1 row)
SELECT l2_distance('[0,0]', '[3,4]');
SELECT l2_distance('[0,0]'::vector, '[3,4]');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('[0,0]', '[0,1]');
SELECT l2_distance('[0,0]'::vector, '[0,1]');
l2_distance
-------------
1
(1 row)
SELECT l2_distance('[1,2]', '[3]');
SELECT l2_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT l2_distance('[3e38]', '[-3e38]');
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
l2_distance
-------------
Infinity
(1 row)
SELECT inner_product('[1,2]', '[3,4]');
SELECT inner_product('[1,2]'::vector, '[3,4]');
inner_product
---------------
11
(1 row)
SELECT inner_product('[1,2]', '[3]');
SELECT inner_product('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT inner_product('[3e38]', '[3e38]');
SELECT inner_product('[3e38]'::vector, '[3e38]');
inner_product
---------------
Infinity
(1 row)
SELECT cosine_distance('[1,2]', '[2,4]');
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,2]', '[0,0]');
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('[1,1]', '[1,1]');
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]', '[-1,-1]');
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]', '[3]');
SELECT cosine_distance('[1,2]'::vector, '[3]');
ERROR: different vector dimensions 2 and 1
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('[3e38]', '[3e38]');
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
cosine_distance
-----------------
NaN

140
test/expected/svector.out Normal file
View File

@@ -0,0 +1,140 @@
SELECT '(0,1.5),(2,3.5)|5|'::svector;
svector
--------------------
(0,1.5),(2,3.5)|5|
(1 row)
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector;
vector
-----------------
[1.5,0,3.5,0,0]
(1 row)
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector(5);
vector
-----------------
[1.5,0,3.5,0,0]
(1 row)
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector(4);
ERROR: expected 4 dimensions, not 5
SELECT '[0,1.5,0,3.5,0]'::vector::svector;
svector
--------------------
(1,1.5),(3,3.5)|5|
(1 row)
SELECT '(0,0),(1,1),(2,0)|3|'::svector;
svector
----------------------
(0,0),(1,1),(2,0)|3|
(1 row)
SELECT '|5|'::svector;
svector
---------
|5|
(1 row)
SELECT '|-1|'::svector;
ERROR: svector must have at least 1 dimension
LINE 1: SELECT '|-1|'::svector;
^
SELECT '|100001|'::svector;
ERROR: svector cannot have more than 100000 dimensions
LINE 1: SELECT '|100001|'::svector;
^
SELECT '|16001|'::svector::vector;
ERROR: vector cannot have more than 16000 dimensions
SELECT '(-1,1)|1|'::svector;
ERROR: index must not be negative
LINE 1: SELECT '(-1,1)|1|'::svector;
^
SELECT '(1,1)|1|'::svector;
ERROR: index must be less than dimensions
LINE 1: SELECT '(1,1)|1|'::svector;
^
SELECT '|1|'::svector(2);
ERROR: expected 2 dimensions, not 1
SELECT l2_distance('|2|'::svector, '(0,3),(1,4)|2|');
l2_distance
-------------
5
(1 row)
SELECT l2_distance('|2|'::svector, '(1,1)|2|');
l2_distance
-------------
1
(1 row)
SELECT '|2|'::svector <-> '(0,3),(1,4)|2|';
?column?
----------
5
(1 row)
SELECT inner_product('(0,1),(1,2)|2|'::svector, '(0,2),(1,4)|2|');
inner_product
---------------
10
(1 row)
SELECT svector_negative_inner_product('(0,1),(1,2)|2|', '(0,2),(1,4)|2|');
svector_negative_inner_product
--------------------------------
-10
(1 row)
SELECT cosine_distance('(0,1),(1,2)|2|'::svector, '(0,2),(1,4)|2|');
cosine_distance
-----------------
0
(1 row)
SELECT cosine_distance('(0,1),(1,2)|2|'::svector, '|2|');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('(0,1),(1,1)|2|'::svector, '(0,-1),(1,-1)|2|');
cosine_distance
-----------------
2
(1 row)
SELECT cosine_distance('(0,1)|2|'::svector, '(1,2)|2|');
cosine_distance
-----------------
1
(1 row)
SELECT cosine_distance('|1|'::svector, '|1|');
cosine_distance
-----------------
NaN
(1 row)
SELECT cosine_distance('(0,1)|2|'::svector, '(0,1)|3|');
ERROR: different svector dimensions 2 and 3
SELECT jaccard_distance('(0,1)|2|', '(0,1)|2|');
jaccard_distance
------------------
0
(1 row)
SELECT jaccard_distance('(0,1)|2|', '(1,1)|2|');
jaccard_distance
------------------
1
(1 row)
SELECT jaccard_distance('|1|', '|1|');
jaccard_distance
------------------
NaN
(1 row)
SELECT jaccard_distance('(0,1)|2|', '(0,1)|3|');
ERROR: different svector dimensions 2 and 3

View File

@@ -13,23 +13,24 @@ SELECT vector_norm('[3,4]');
SELECT vector_norm('[0,1]');
SELECT vector_norm('[3e37,4e37]')::real;
SELECT l2_distance('[0,0]', '[3,4]');
SELECT l2_distance('[0,0]', '[0,1]');
SELECT l2_distance('[1,2]', '[3]');
SELECT l2_distance('[3e38]', '[-3e38]');
SELECT l2_distance('[0,0]'::vector, '[3,4]');
SELECT l2_distance('[0,0]'::vector, '[0,1]');
SELECT l2_distance('[1,2]'::vector, '[3]');
SELECT l2_distance('[3e38]'::vector, '[-3e38]');
SELECT inner_product('[1,2]', '[3,4]');
SELECT inner_product('[1,2]', '[3]');
SELECT inner_product('[3e38]', '[3e38]');
SELECT inner_product('[1,2]'::vector, '[3,4]');
SELECT inner_product('[1,2]'::vector, '[3]');
SELECT inner_product('[3e38]'::vector, '[3e38]');
SELECT cosine_distance('[1,2]', '[2,4]');
SELECT cosine_distance('[1,2]', '[0,0]');
SELECT cosine_distance('[1,1]', '[1,1]');
SELECT cosine_distance('[1,1]', '[-1,-1]');
SELECT cosine_distance('[1,2]', '[3]');
SELECT cosine_distance('[1,1]', '[1.1,1.1]');
SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
SELECT cosine_distance('[3e38]', '[3e38]');
SELECT cosine_distance('[1,2]'::vector, '[2,4]');
SELECT cosine_distance('[1,2]'::vector, '[0,0]');
SELECT cosine_distance('[1,1]'::vector, '[1,1]');
SELECT cosine_distance('[1,0]'::vector, '[0,2]');
SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
SELECT cosine_distance('[1,2]'::vector, '[3]');
SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
SELECT cosine_distance('[3e38]'::vector, '[3e38]');
SELECT l1_distance('[0,0]', '[3,4]');
SELECT l1_distance('[0,0]', '[0,1]');

36
test/sql/svector.sql Normal file
View File

@@ -0,0 +1,36 @@
SELECT '(0,1.5),(2,3.5)|5|'::svector;
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector;
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector(5);
SELECT '(0,1.5),(2,3.5)|5|'::svector::vector(4);
SELECT '[0,1.5,0,3.5,0]'::vector::svector;
SELECT '(0,0),(1,1),(2,0)|3|'::svector;
SELECT '|5|'::svector;
SELECT '|-1|'::svector;
SELECT '|100001|'::svector;
SELECT '|16001|'::svector::vector;
SELECT '(-1,1)|1|'::svector;
SELECT '(1,1)|1|'::svector;
SELECT '|1|'::svector(2);
SELECT l2_distance('|2|'::svector, '(0,3),(1,4)|2|');
SELECT l2_distance('|2|'::svector, '(1,1)|2|');
SELECT '|2|'::svector <-> '(0,3),(1,4)|2|';
SELECT inner_product('(0,1),(1,2)|2|'::svector, '(0,2),(1,4)|2|');
SELECT svector_negative_inner_product('(0,1),(1,2)|2|', '(0,2),(1,4)|2|');
SELECT cosine_distance('(0,1),(1,2)|2|'::svector, '(0,2),(1,4)|2|');
SELECT cosine_distance('(0,1),(1,2)|2|'::svector, '|2|');
SELECT cosine_distance('(0,1),(1,1)|2|'::svector, '(0,-1),(1,-1)|2|');
SELECT cosine_distance('(0,1)|2|'::svector, '(1,2)|2|');
SELECT cosine_distance('|1|'::svector, '|1|');
SELECT cosine_distance('(0,1)|2|'::svector, '(0,1)|3|');
SELECT jaccard_distance('(0,1)|2|', '(0,1)|2|');
SELECT jaccard_distance('(0,1)|2|', '(1,1)|2|');
SELECT jaccard_distance('|1|', '|1|');
SELECT jaccard_distance('(0,1)|2|', '(0,1)|3|');

View File

@@ -19,8 +19,6 @@ sub test_index_replay
# Wait for replica to catch up
my $applname = $node_replica->name;
my $server_version_num = $node_primary->safe_psql("postgres", "SHOW server_version_num");
my $caughtup_query = "SELECT pg_current_wal_lsn() <= replay_lsn FROM pg_stat_replication WHERE application_name = '$applname';";
$node_primary->poll_query_until('postgres', $caughtup_query)
or die "Timed out while waiting for replica 1 to catch up";

View File

@@ -94,7 +94,7 @@ for my $i (0 .. $#operators)
# Test approximate results
if ($operator ne "<#>")
{
# TODO fix test
# TODO Fix test (uniform random vectors all have similar inner product)
test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator);
}
@@ -115,7 +115,7 @@ for my $i (0 .. $#operators)
# Test approximate results
if ($operator ne "<#>")
{
# TODO fix test
# TODO Fix test (uniform random vectors all have similar inner product)
test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator);
}

View File

@@ -19,8 +19,6 @@ sub test_index_replay
# Wait for replica to catch up
my $applname = $node_replica->name;
my $server_version_num = $node_primary->safe_psql("postgres", "SHOW server_version_num");
my $caughtup_query = "SELECT pg_current_wal_lsn() <= replay_lsn FROM pg_stat_replication WHERE application_name = '$applname';";
$node_primary->poll_query_until('postgres', $caughtup_query)
or die "Timed out while waiting for replica 1 to catch up";

View File

@@ -89,7 +89,7 @@ foreach (@queries)
test_recall(0.20, $limit, "before vacuum");
test_recall(0.95, 100, "before vacuum");
# TODO test concurrent inserts with vacuum
# TODO Test concurrent inserts with vacuum
$node->safe_psql("postgres", "VACUUM tst;");
test_recall(0.95, $limit, "after vacuum");

View File

@@ -0,0 +1,117 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
sub test_recall
{
my ($probes, $min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v $operator '$queries[0]' LIMIT $limit;
));
like($explain, qr/Index Scan using idx on tst/);
for my $i (0 .. $#queries)
{
my $actual = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = $probes;
SELECT i FROM tst ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my %actual_set = map { $_ => 1 } @actual_ids;
my @expected_ids = split("\n", $expected[$i]);
foreach (@expected_ids)
{
if (exists($actual_set{$_}))
{
$correct++;
}
$total++;
}
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = get_new_node('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector(3));");
# Generate queries
for (1 .. 20)
{
my $r1 = rand();
my $r2 = rand();
my $r3 = rand();
push(@queries, "[$r1,$r2,$r3]");
}
# Check each index type
my @operators = ("<->", "<#>", "<=>");
my @opclasses = ("vector_l2_ops", "vector_ip_ops", "vector_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
# Add index
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING ivfflat (v $opclass);");
# Use concurrent inserts
$node->pgbench(
"--no-vacuum --client=10 --transactions=1000",
0,
[qr{actually processed}],
[qr{^$}],
"concurrent INSERTs",
{
"017_ivfflat_insert_recall_$opclass" => "INSERT INTO tst (v) SELECT ARRAY[random(), random(), random()] FROM generate_series(1, 10) i;"
}
);
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;
));
push(@expected, $res);
}
# Test approximate results
if ($operator ne "<#>")
{
# TODO Fix test (uniform random vectors all have similar inner product)
test_recall(1, 0.71, $operator);
test_recall(10, 0.95, $operator);
}
# Account for equal distances
test_recall(100, 0.9925, $operator);
$node->safe_psql("postgres", "DROP INDEX idx;");
$node->safe_psql("postgres", "TRUNCATE tst;");
}
done_testing();

View File

@@ -0,0 +1,43 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use Test::More;
my $dim = 3;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = get_new_node('node');
$node->init;
$node->start;
# Create table and index
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst (v) SELECT ARRAY[$array_sql] FROM generate_series(1, 10000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);");
# Delete data
$node->safe_psql("postgres", "DELETE FROM tst WHERE i % 100 != 0;");
my $exp = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
SELECT i FROM tst ORDER BY v <-> '[0,0,0]';
));
# Run twice to make sure correct tuples marked as dead
for (1 .. 2)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET ivfflat.probes = 100;
SELECT i FROM tst ORDER BY v <-> '[0,0,0]';
));
is($res, $exp);
}
done_testing();

View File

@@ -1,4 +1,4 @@
comment = 'vector data type and ivfflat access method'
default_version = '0.5.0'
comment = 'vector data type and ivfflat and hnsw access methods'
default_version = '0.5.1'
module_pathname = '$libdir/vector'
relocatable = true