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98 Commits

Author SHA1 Message Date
Andrew Kane
c01e76f2fa Added strict ordering [skip ci] 2024-09-28 11:31:03 -07:00
Andrew Kane
ab57217f48 Added todo [skip ci] 2024-09-28 10:07:09 -07:00
Andrew Kane
5f6e031ccc Updated changelog [skip ci] 2024-09-28 09:57:05 -07:00
Andrew Kane
1a1221f905 Merge branch 'master' into hnsw-streaming 2024-09-26 08:34:07 -07:00
Andrew Kane
54fa16e3e3 Added safety check [skip ci] 2024-09-26 08:32:44 -07:00
Andrew Kane
40c3e402c7 Removed todo [skip ci] 2024-09-25 17:29:20 -07:00
Andrew Kane
058248fdcc Improved cost code [skip ci] 2024-09-25 17:23:29 -07:00
Andrew Kane
73c5145b77 Use int for ef [skip ci] 2024-09-25 16:52:41 -07:00
Andrew Kane
ec4a23fe49 Added cost estimation [skip ci] 2024-09-25 16:45:04 -07:00
Andrew Kane
38207f5640 Merge branch 'master' into hnsw-streaming 2024-09-25 16:09:09 -07:00
Andrew Kane
46de265a24 Updated changelog [skip ci] 2024-09-25 16:03:58 -07:00
Andrew Kane
b8c27914d4 Improved test [skip ci] 2024-09-25 15:58:41 -07:00
Andrew Kane
2d85af51a8 Added test for IVFFlat costs [skip ci] 2024-09-25 15:53:34 -07:00
Andrew Kane
e0ad441306 Added test for costs [skip ci] 2024-09-25 15:49:03 -07:00
Andrew Kane
5776a4d937 Only adjust for TOAST [skip ci] 2024-09-25 15:39:56 -07:00
Andrew Kane
242a12b7d5 Added same cost adjustment to HNSW as IVFFlat since TOAST not included in seq scan cost - #682 [skip ci] 2024-09-25 15:33:57 -07:00
Andrew Kane
1370dd6e86 Removed unneeded floor and fixed comment formatting [skip ci] 2024-09-25 14:13:02 -07:00
Andrew Kane
a100dc67e5 Ran pgindent [skip ci] 2024-09-25 14:03:51 -07:00
Jonathan S. Katz
2df9f24aad Update HNSW cost estimatation to utilize search and index info (#682)
Previously, the cost estimation formula for a HNSW index scan utilized
a methodology that only factored in the entry level for an HNSW scan
and the "m" index parameter, which reflects the number of tuples (or
vectors) to scan at each step of a HNSW graph traversal. While this
would bias the PostgreSQL query planner to choose an HNSW index scan
over other available paths, this could lead to potential suboptimal
index selection, for example, choosing to use a HNSW index instead of
an available B-tree index that has better selectivity.

The number of tuples scanned during HNSW graph traversal is principally
influenced by these factors:

 * The number of tuples stored in the index
 * `m` - the number of tuples that are scanned in each step of the graph
   traversal
 * `hnsw.ef_search` - which influences the total number of steps it
   takes for the scan to converge on the approximated nearest neighbors

Through testing different source models for vectors, we also observed
that the correlation of vectors in mdoels would impact this convergence.
For this first iteration, we've opted to hardcode a constant scaling
factor and set it to `0.55`, though a future commit may turn this into
a configurable parameter.

The high-level formula for estimating the cost of a HNSW index scan is
as such:

```
(entryLevel * m) + (layer0TuplesMax * layer0Selectivity)
```

where

- `(entryLevel * m)` is the lower bound of tuples to scan, as it
accounts for the graph traversal to layer 0 (L0). (L1 and above has an ef=1)
- `layer0TuplesMax` is an estimate of the maximum number of tuples to
scan at L0. This accounts for tuples that may end up being discarded due
to them already being visited. Testing shows that the number of steps
until converge is similar to the value of `hnsw.ef_search`, thus we can
estimate tuples max at `hnsw.ef_search * m * 2`
- `layer0Selectivity` - estimates the percentage of tuples that will
actually be scanned during the index traversal, multipled by the scaling
factor

In addition to the `m` build parameter and `hsnw.ef_search`, costs
estimates can be influenced by standard PostgreSQL costing parameters,
though adjusting those (e.g. `random_page_cost`) should be done with
care.

Co-authored-by: @ankane
2024-09-25 14:01:33 -07:00
Andrew Kane
8e979ed377 Do not adjust index selectivity based on probes [skip ci] 2024-09-25 13:48:24 -07:00
Andrew Kane
4e35c6abe3 Updated readme [skip ci] 2024-09-24 23:24:48 -07:00
Andrew Kane
77b3d1f2a8 Added test for join with attribute filtering [skip ci] 2024-09-24 23:21:34 -07:00
Andrew Kane
ecd0738728 Improved test [skip ci] 2024-09-24 23:13:30 -07:00
Andrew Kane
62ffc3641c Added test for join [skip ci] 2024-09-24 23:12:27 -07:00
Andrew Kane
11e4d040d9 Fixed test [skip ci] 2024-09-24 19:38:06 -07:00
Andrew Kane
87ac108bf7 Removed code for Postgres 12 [skip ci] 2024-09-23 15:26:31 -07:00
Andrew Kane
b2fa625255 Fixed crash with empty index [skip ci] 2024-09-23 09:42:31 -07:00
Andrew Kane
a8e699c927 Improved message [skip ci] 2024-09-22 22:31:48 -07:00
Andrew Kane
91541fece6 Fixed example [skip ci] 2024-09-22 22:28:39 -07:00
Andrew Kane
f3de487da2 Started readme updates [skip ci] 2024-09-22 22:26:27 -07:00
Andrew Kane
721d4b7e3f Improved test for ef_stream [skip ci] 2024-09-22 18:51:38 -07:00
Andrew Kane
28066d8fe4 Added test for ef_stream [skip ci] 2024-09-22 18:35:35 -07:00
Andrew Kane
495041e43b Added option to limit tuples [skip ci] 2024-09-22 18:10:19 -07:00
Andrew Kane
52c385c03a Only pass discarded when streaming [skip ci] 2024-09-22 17:47:10 -07:00
Andrew Kane
80cbd32dab Added streaming option for HNSW 2024-09-22 12:02:48 -07:00
Andrew Kane
97cf990e0f Free TupleDesc [skip ci] 2024-09-21 19:15:34 -07:00
Andrew Kane
55dc735e1a Moved allocations out of GetScanItems [skip ci] 2024-09-21 19:10:25 -07:00
Andrew Kane
be4e9a9df2 Added macros for IvfflatScanList [skip ci] 2024-09-21 18:10:37 -07:00
Andrew Kane
d5e8fc96a5 Changed HnswPairingHeapNode to HnswSearchCandidate to reduce allocations and improve code 2024-09-21 12:07:44 -07:00
Andrew Kane
6d2af6d3f9 Improved code [skip ci] 2024-09-20 15:21:57 -07:00
Andrew Kane
a6ab5d07c0 Fixed CI 2024-09-19 20:50:51 -07:00
Andrew Kane
aa77346103 Improved code [skip ci] 2024-09-19 19:57:16 -07:00
Andrew Kane
b0da2d95d9 Fixed array_to_sparsevec on Windows [skip ci] 2024-09-19 19:52:16 -07:00
Andrew Kane
3fb05eb847 Added casts for arrays to sparsevec - #604
Co-authored-by: Narek Galstyan <narekg@berkeley.edu>
Co-authored-by: Di Qi <di@lantern.dev>
2024-09-19 19:17:05 -07:00
Andrew Kane
b738ffecc1 Dropped support for Postgres 12 2024-09-19 18:13:54 -07:00
Heikki Linnakangas
7117513532 Add error codes to a few errors (#657)
With elog(), you get XX000 "internal_error", which sounds scary.

It's not self-evident what the right error codes for some of these
errors are, but I tried to use my best judgment.
2024-09-19 18:04:23 -07:00
Andrew Kane
85d877d540 Updated changelog [skip ci] 2024-09-19 18:03:20 -07:00
Jonathan S. Katz
05fb382031 Swap max costing values to align with upstream guidance (#658)
A feature targeted for PostgreSQL 18 (postgres/postgres@e2225346)
that makes optimizations around disabled path nodes impacted pgvector
such that PostgreSQL would choose to perform an index scan when it
should have used a different scan (e.g. `SELECT count(*) FROM table`).
Per upstream guidance[1], the recommendation is to switch to using
`get_float8_infinity()`, which achieves the same behavior in backbranches,
and can be adapated to work with the new behavior introduced in PostgreSQL 18.

[1] https://www.postgresql.org/message-id/2281822.1724441531%40sss.pgh.pa.us
2024-09-19 18:01:59 -07:00
Andrew Kane
8e1853fbf3 Improved variable name [skip ci] 2024-09-19 15:09:40 -07:00
Andrew Kane
f9d68a061a Simplified HnswLoadUnvisitedFromMemory [skip ci] 2024-09-19 04:39:46 -07:00
Andrew Kane
4f8ab574c9 Simplified CountElement [skip ci] 2024-09-19 04:32:38 -07:00
Andrew Kane
a15806196e Keep scan-build happy 2024-09-19 04:02:09 -07:00
Andrew Kane
5c9429a0f8 Reduced memory usage for HNSW index scans 2024-09-19 03:27:35 -07:00
Andrew Kane
4b44d6e745 Updated changelog [skip ci] 2024-09-19 02:42:33 -07:00
Andrew Kane
16ca608f42 Updated AddToVisited to use HnswElementPtr 2024-09-19 02:41:20 -07:00
Andrew Kane
8dde14a736 Reduced memory usage for HNSW index scans
Co-authored-by: Heikki Linnakangas <heikki.linnakangas@iki.fi>
2024-09-19 02:17:51 -07:00
Andrew Kane
d74d3065bc Reduced allocations for pairing heap 2024-09-19 01:59:46 -07:00
Andrew Kane
a1b80faa67 Updated readme 2024-09-05 23:13:12 -07:00
Andrew Kane
4af5a127e0 Revert "Improved cleanup for IVFFlat index scans [skip ci]"
This reverts commit da7d3959a3.
2024-09-02 01:52:28 -07:00
Andrew Kane
d02d71a398 Fixed CI 2024-09-02 01:44:03 -07:00
Andrew Kane
2aca04b8de Updated links [skip ci] 2024-08-28 13:39:03 -07:00
Andrew Kane
e47984e616 Reset tuple sort for Postgres 12 [skip ci] 2024-08-24 22:10:26 -07:00
Andrew Kane
da7d3959a3 Improved cleanup for IVFFlat index scans [skip ci] 2024-08-24 21:59:44 -07:00
Andrew Kane
dadbbc3758 Renamed InitSortState to InitScanSortState [skip ci] 2024-08-24 21:53:15 -07:00
Andrew Kane
6af0a43d62 Added InitBuildSortState function [skip ci] 2024-08-24 21:50:31 -07:00
Andrew Kane
ffcb90d094 Added InitSortState function [skip ci] 2024-08-24 21:42:18 -07:00
Andrew Kane
8a312c3c8e Added memory usage for IVFFlat index scans [skip ci] 2024-08-24 21:30:40 -07:00
Andrew Kane
5d86b177ab Fixed -DIVFFLAT_MEMORY [skip ci] 2024-08-24 20:56:33 -07:00
Andrew Kane
ea99957fae Added fields to IndexAmRoutine 2024-08-22 20:39:16 -07:00
Samuel Marks
4cede1a9c9 [src/hnswutils.c] Resolve 1 -Wmaybe-uninitialized (#654) 2024-08-22 19:51:16 -07:00
Andrew Kane
d0dbc8b4d1 Added Postgres 18 to CI [skip ci] 2024-08-13 02:24:42 -07:00
Andrew Kane
bb855e6cb4 Updated comment [skip ci] 2024-08-06 10:35:26 -07:00
Andrew Kane
103ac50f1a Version bump to 0.7.4 [skip ci] 2024-08-05 10:44:01 -07:00
Andrew Kane
57fb706242 Fixed locking for parallel HNSW index builds - fixes #635 2024-08-04 11:27:51 -07:00
Andrew Kane
020d3edaa9 Changed warnings to errors for TAP tests [skip ci] 2024-07-27 12:28:03 -07:00
Andrew Kane
1e9e355175 Updated TAP tests to use PostgreSQL::Test packages [skip ci] 2024-07-27 12:24:15 -07:00
Andrew Kane
f1d283f565 Updated comment [skip ci] 2024-07-27 11:36:48 -07:00
Andrew Kane
8684c2ba62 Updated formatting [skip ci] 2024-07-27 08:25:09 -07:00
Andrew Kane
6c692ef23f Fixed compilation error with GCC 14 on i386 when SSE2 is not enabled 2024-07-27 06:20:27 -07:00
Andrew Kane
bb424e96e7 Revert "Simplified makefile"
This reverts commit 30911edb7a.
2024-07-24 20:50:14 -07:00
Andrew Kane
30911edb7a Simplified makefile 2024-07-24 20:39:52 -07:00
Andrew Kane
5ae2bd9efb Improved Windows makefile [skip ci] 2024-07-24 20:37:28 -07:00
Andrew Kane
19215317a4 Fixed installation when make is not run before make install on Windows [skip ci] 2024-07-24 02:09:32 -07:00
Andrew Kane
c7ca7f05de Fixed installation when make is not run before make install - closes #631 2024-07-24 01:30:22 -07:00
Andrew Kane
4733cf253b Version bump to 0.7.3 [skip ci] 2024-07-22 09:16:59 -07:00
Andrew Kane
06d1fa1402 Added alignment check to ensure consistency with PageIndexTupleOverwrite 2024-07-19 15:50:24 -07:00
Andrew Kane
8c5a4bfb6c Fixed failed to add index item error with sparsevec - fixes #625 2024-07-19 13:54:36 -07:00
Andrew Kane
8772c8de68 Fixed compilation error with FreeBSD ARM 2024-06-30 11:23:39 -07:00
Andrew Kane
d1694a93af Added ubuntu-24.04 to CI [skip ci] 2024-06-17 10:45:58 -07:00
Andrew Kane
61870a0244 Fixed compilation warning with MSVC and Postgres 16 - fixes #598
Co-authored-by: Xing Guo <higuoxing@gmail.com>
2024-06-16 12:09:01 -07:00
Andrew Kane
9b89bed701 Version bump to 0.7.2 [skip ci] 2024-06-11 17:26:51 -07:00
Andrew Kane
ad7cad5ecd Improved HnswSearchLayer code 2024-06-11 16:29:14 -07:00
Andrew Kane
2a8b9d689e Moved check 2024-06-11 15:45:03 -07:00
Andrew Kane
18cd8a60c3 Updated comment [skip ci] 2024-06-10 22:02:40 -07:00
Andrew Kane
8c91a9f56a Fixed initialization fork for IVFFlat indexes on unlogged tables - #591 2024-06-10 21:55:17 -07:00
Andrew Kane
9249e7e2de Updated changelog [skip ci] 2024-06-10 21:33:49 -07:00
Andrew Kane
9e91af5989 Added checks for invalid indexes - #591 2024-06-10 21:20:54 -07:00
Narek Galstyan
9dcf1bdc80 Fix init_fork WAL-logging on unlogged indexes (#591)
Currently pgvector does not create any WAL records for unlogged tables

Postgres assumes INIT_FORK of unlogged tables is persistent and uses it
to reset the table index to its default empty state after a server
crash.

This patch makes INIT_FORK of unlogged table WAL-tracked, which ensures
an unlogged table is usable after a crash-restart
2024-06-10 21:16:32 -07:00
81 changed files with 1737 additions and 692 deletions

View File

@@ -8,17 +8,17 @@ jobs:
fail-fast: false
matrix:
include:
# - postgres: 18
# os: ubuntu-24.04
- postgres: 17
os: ubuntu-22.04
os: ubuntu-24.04
- postgres: 16
os: ubuntu-22.04
- postgres: 15
os: ubuntu-22.04
- postgres: 14
os: ubuntu-22.04
- postgres: 13
os: ubuntu-20.04
- postgres: 12
- postgres: 13
os: ubuntu-20.04
steps:
- uses: actions/checkout@v4

View File

@@ -1,3 +1,26 @@
## 0.8.0 (unreleased)
- Added support for iterative index scans
- Added casts for arrays to `sparsevec`
- Improved cost estimation
- Reduced memory usage for HNSW index scans
- Dropped support for Postgres 12
## 0.7.4 (2024-08-05)
- Fixed locking for parallel HNSW index builds
- Fixed compilation error with GCC 14 on i386 when SSE2 is not enabled
## 0.7.3 (2024-07-22)
- Fixed `failed to add index item` error with `sparsevec`
- Fixed compilation error with FreeBSD ARM
- Fixed compilation warning with MSVC and Postgres 16
## 0.7.2 (2024-06-11)
- Fixed initialization fork for indexes on unlogged tables
## 0.7.1 (2024-06-03)
- Improved performance of on-disk HNSW index builds

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": "0.7.1",
"version": "0.7.4",
"maintainer": [
"Andrew Kane <andrew@ankane.org>"
],
@@ -20,7 +20,7 @@
"vector": {
"file": "sql/vector.sql",
"docfile": "README.md",
"version": "0.7.1",
"version": "0.7.4",
"abstract": "Open-source vector similarity search for Postgres"
}
},

View File

@@ -1,8 +1,9 @@
EXTENSION = vector
EXTVERSION = 0.7.1
EXTVERSION = 0.7.4
MODULE_big = vector
DATA = $(wildcard sql/*--*.sql)
DATA = $(wildcard sql/*--*--*.sql)
DATA_built = sql/$(EXTENSION)--$(EXTVERSION).sql
OBJS = src/bitutils.o src/bitvec.o src/halfutils.o src/halfvec.o src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/sparsevec.o src/vector.o
HEADERS = src/halfvec.h src/sparsevec.h src/vector.h
@@ -42,8 +43,6 @@ all: sql/$(EXTENSION)--$(EXTVERSION).sql
sql/$(EXTENSION)--$(EXTVERSION).sql: sql/$(EXTENSION).sql
cp $< $@
EXTRA_CLEAN = sql/$(EXTENSION)--$(EXTVERSION).sql
PG_CONFIG ?= pg_config
PGXS := $(shell $(PG_CONFIG) --pgxs)
include $(PGXS)
@@ -53,7 +52,7 @@ ifeq ($(PROVE),)
PROVE = prove
endif
# for Postgres 15
# for Postgres < 15
PROVE_FLAGS += -I ./test/perl
prove_installcheck:

View File

@@ -1,6 +1,7 @@
EXTENSION = vector
EXTVERSION = 0.7.1
EXTVERSION = 0.7.4
DATA_built = sql\$(EXTENSION)--$(EXTVERSION).sql
OBJS = src\bitutils.obj src\bitvec.obj src\halfutils.obj src\halfvec.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\sparsevec.obj src\vector.obj
HEADERS = src\halfvec.h src\sparsevec.h src\vector.h
@@ -19,11 +20,6 @@ PG_CFLAGS = $(PG_CFLAGS) $(OPTFLAGS) /O2 /fp:fast
# https://learn.microsoft.com/en-us/cpp/error-messages/tool-errors/vectorizer-and-parallelizer-messages
# PG_CFLAGS = $(PG_CFLAGS) /Qvec-report:2
all: sql\$(EXTENSION)--$(EXTVERSION).sql
sql\$(EXTENSION)--$(EXTVERSION).sql: sql\$(EXTENSION).sql
copy sql\$(EXTENSION).sql $@
# TODO use pg_config
!ifndef PGROOT
!error PGROOT is not set
@@ -43,15 +39,18 @@ SHLIB = $(EXTENSION).dll
LIBS = "$(LIBDIR)\postgres.lib"
all: $(SHLIB) $(DATA_built)
.c.obj:
$(CC) $(CFLAGS) /c $< /Fo$@
$(SHLIB): $(OBJS)
$(CC) $(CFLAGS) $(OBJS) $(LIBS) /link /DLL /OUT:$(SHLIB)
all: $(SHLIB)
sql\$(EXTENSION)--$(EXTVERSION).sql: sql\$(EXTENSION).sql
copy sql\$(EXTENSION).sql $@
install:
install: all
copy $(SHLIB) "$(PKGLIBDIR)"
copy $(EXTENSION).control "$(SHAREDIR)\extension"
copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
@@ -70,6 +69,6 @@ uninstall:
clean:
del /f $(SHLIB) $(EXTENSION).lib $(EXTENSION).exp
del /f $(DATA_built)
del /f $(OBJS)
del /f sql\$(EXTENSION)--$(EXTVERSION).sql
del /f /s /q results regression.diffs regression.out tmp_check tmp_check_iso log output_iso

View File

@@ -21,7 +21,7 @@ Compile and install the extension (supports Postgres 12+)
```sh
cd /tmp
git clone --branch v0.7.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
cd pgvector
make
make install # may need sudo
@@ -46,7 +46,7 @@ Then use `nmake` to build:
```cmd
set "PGROOT=C:\Program Files\PostgreSQL\16"
cd %TEMP%
git clone --branch v0.7.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
cd pgvector
nmake /F Makefile.win
nmake /F Makefile.win install
@@ -106,7 +106,7 @@ Insert vectors
INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
```
Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py))
Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py))
```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
@@ -202,7 +202,7 @@ You can add an index to use approximate nearest neighbor search, which trades so
Supported index types are:
- [HNSW](#hnsw) - added in 0.5.0
- [HNSW](#hnsw)
- [IVFFlat](#ivfflat)
## HNSW
@@ -445,6 +445,63 @@ Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
```
## Streaming Queries [unreleased]
*Added in 0.8.0*
With approximate indexes, you can end up with less results than expected due to filtering conditions in the query.
Starting with 0.8.0, you can enable streaming queries. If too few results from the initial index scan match the query filters, it will resume scanning until enough results are found. This can significantly improve recall (at the cost of speed).
```tsql
SET hnsw.streaming = on;
-- or
SET ivfflat.streaming = on;
```
### Streaming Options
Since scanning a large portion of the index is expensive, there are options to control when the scan ends.
#### HNSW
Specify the max number of additional tuples visited
```sql
SET hnsw.ef_stream = 10000;
```
The scan will also end if reaches `work_mem`, at which point a notice is shown
```text
NOTICE: hnsw index scan exceeded work_mem after 50000 tuples
HINT: Increase work_mem to scan more tuples.
```
Adjust this with:
```sql
SET work_mem = '8MB';
```
#### IVFFlat
Specify the max number of probes
```sql
SET ivfflat.max_probes = 100;
```
### Streaming Order
With streaming queries, its possible for rows to be slightly out of order by distance. For strict ordering, use:
```sql
WITH approx_order AS MATERIALIZED (
SELECT *, embedding <-> '[1,2,3]' AS distance FROM items WHERE ... ORDER BY distance LIMIT 5
) SELECT * FROM approx_order ORDER BY distance;
```
## Half-Precision Vectors
*Added in 0.7.0*
@@ -473,7 +530,7 @@ SELECT * FROM items ORDER BY embedding::halfvec(3) <-> '[1,2,3]' LIMIT 5;
## Binary Vectors
Use the `bit` type to store binary vectors ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py))
Use the `bit` type to store binary vectors ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/imagehash/example.py))
```sql
CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
@@ -551,7 +608,7 @@ 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.
You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search/rrf.py) or a [cross-encoder](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search/cross_encoder.py) to combine results.
## Indexing Subvectors
@@ -597,7 +654,7 @@ Be sure to restart Postgres for changes to take effect.
### Loading
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py)).
Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py)).
```sql
COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
@@ -687,7 +744,7 @@ Scale pgvector the same way you scale Postgres.
Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus.py)).
Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus/example.py)).
## Languages
@@ -1051,7 +1108,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
You can also build the image manually:
```sh
git clone --branch v0.7.1 https://github.com/pgvector/pgvector.git
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
cd pgvector
docker build --pull --build-arg PG_MAJOR=16 -t myuser/pgvector .
```

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 '0.7.2'" to load this file. \quit

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 '0.7.3'" to load this file. \quit

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 '0.7.4'" to load this file. \quit

View File

@@ -0,0 +1,26 @@
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
\echo Use "ALTER EXTENSION vector UPDATE TO '0.8.0'" to load this file. \quit
CREATE FUNCTION array_to_sparsevec(integer[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(real[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(double precision[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(numeric[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE CAST (integer[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(numeric[], integer, boolean) AS ASSIGNMENT;

View File

@@ -782,6 +782,18 @@ CREATE FUNCTION halfvec_to_sparsevec(halfvec, integer, boolean) RETURNS sparseve
CREATE FUNCTION sparsevec_to_halfvec(sparsevec, integer, boolean) RETURNS halfvec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(integer[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(real[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(double precision[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
CREATE FUNCTION array_to_sparsevec(numeric[], integer, boolean) RETURNS sparsevec
AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-- sparsevec casts
CREATE CAST (sparsevec AS sparsevec)
@@ -799,6 +811,18 @@ CREATE CAST (sparsevec AS halfvec)
CREATE CAST (halfvec AS sparsevec)
WITH FUNCTION halfvec_to_sparsevec(halfvec, integer, boolean) AS IMPLICIT;
CREATE CAST (integer[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(integer[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (real[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(real[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (double precision[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(double precision[], integer, boolean) AS ASSIGNMENT;
CREATE CAST (numeric[] AS sparsevec)
WITH FUNCTION array_to_sparsevec(numeric[], integer, boolean) AS ASSIGNMENT;
-- sparsevec operators
CREATE OPERATOR <-> (

View File

@@ -4,8 +4,8 @@
#include "postgres.h"
/* Check version in first header */
#if PG_VERSION_NUM < 120000
#error "Requires PostgreSQL 12+"
#if PG_VERSION_NUM < 130000
#error "Requires PostgreSQL 13+"
#endif
extern uint64 (*BitHammingDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance);

View File

@@ -3,6 +3,7 @@
#include "bitutils.h"
#include "bitvec.h"
#include "utils/varbit.h"
#include "vector.h"
#if PG_VERSION_NUM >= 160000
#include "varatt.h"
@@ -40,7 +41,7 @@ CheckDims(VarBit *a, VarBit *b)
/*
* Get the Hamming distance between two bit vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(hamming_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hamming_distance);
Datum
hamming_distance(PG_FUNCTION_ARGS)
{
@@ -55,7 +56,7 @@ hamming_distance(PG_FUNCTION_ARGS)
/*
* Get the Jaccard distance between two bit vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(jaccard_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(jaccard_distance);
Datum
jaccard_distance(PG_FUNCTION_ARGS)
{

View File

@@ -19,11 +19,6 @@
#include "utils/numeric.h"
#include "vector.h"
#if PG_VERSION_NUM < 130000
#define TYPALIGN_DOUBLE 'd'
#define TYPALIGN_INT 'i'
#endif
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
@@ -164,28 +159,10 @@ CheckStateArray(ArrayType *statearray, const char *caller)
return (float8 *) ARR_DATA_PTR(statearray);
}
#if PG_VERSION_NUM < 120003
static pg_noinline void
float_overflow_error(void)
{
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("value out of range: overflow")));
}
static pg_noinline void
float_underflow_error(void)
{
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("value out of range: underflow")));
}
#endif
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_in);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_in);
Datum
halfvec_in(PG_FUNCTION_ARGS)
{
@@ -299,7 +276,7 @@ halfvec_in(PG_FUNCTION_ARGS)
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_out);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_out);
Datum
halfvec_out(PG_FUNCTION_ARGS)
{
@@ -345,7 +322,7 @@ halfvec_out(PG_FUNCTION_ARGS)
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_typmod_in);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_typmod_in);
Datum
halfvec_typmod_in(PG_FUNCTION_ARGS)
{
@@ -376,7 +353,7 @@ halfvec_typmod_in(PG_FUNCTION_ARGS)
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_recv);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_recv);
Datum
halfvec_recv(PG_FUNCTION_ARGS)
{
@@ -410,7 +387,7 @@ halfvec_recv(PG_FUNCTION_ARGS)
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_send);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_send);
Datum
halfvec_send(PG_FUNCTION_ARGS)
{
@@ -430,7 +407,7 @@ halfvec_send(PG_FUNCTION_ARGS)
* Convert half vector to half vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec);
Datum
halfvec(PG_FUNCTION_ARGS)
{
@@ -445,7 +422,7 @@ halfvec(PG_FUNCTION_ARGS)
/*
* Convert array to half vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(array_to_halfvec);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(array_to_halfvec);
Datum
array_to_halfvec(PG_FUNCTION_ARGS)
{
@@ -519,7 +496,7 @@ array_to_halfvec(PG_FUNCTION_ARGS)
/*
* Convert half vector to float4[]
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_to_float4);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_to_float4);
Datum
halfvec_to_float4(PG_FUNCTION_ARGS)
{
@@ -543,7 +520,7 @@ halfvec_to_float4(PG_FUNCTION_ARGS)
/*
* Convert vector to half vec
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_halfvec);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_to_halfvec);
Datum
vector_to_halfvec(PG_FUNCTION_ARGS)
{
@@ -565,7 +542,7 @@ vector_to_halfvec(PG_FUNCTION_ARGS)
/*
* Get the L2 distance between half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l2_distance);
Datum
halfvec_l2_distance(PG_FUNCTION_ARGS)
{
@@ -580,7 +557,7 @@ halfvec_l2_distance(PG_FUNCTION_ARGS)
/*
* Get the L2 squared distance between half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_squared_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l2_squared_distance);
Datum
halfvec_l2_squared_distance(PG_FUNCTION_ARGS)
{
@@ -595,7 +572,7 @@ halfvec_l2_squared_distance(PG_FUNCTION_ARGS)
/*
* Get the inner product of two half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_inner_product);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_inner_product);
Datum
halfvec_inner_product(PG_FUNCTION_ARGS)
{
@@ -610,7 +587,7 @@ halfvec_inner_product(PG_FUNCTION_ARGS)
/*
* Get the negative inner product of two half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_negative_inner_product);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_negative_inner_product);
Datum
halfvec_negative_inner_product(PG_FUNCTION_ARGS)
{
@@ -625,7 +602,7 @@ halfvec_negative_inner_product(PG_FUNCTION_ARGS)
/*
* Get the cosine distance between two half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_cosine_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_cosine_distance);
Datum
halfvec_cosine_distance(PG_FUNCTION_ARGS)
{
@@ -657,7 +634,7 @@ halfvec_cosine_distance(PG_FUNCTION_ARGS)
* Currently uses angular distance since needs to satisfy triangle inequality
* Assumes inputs are unit vectors (skips norm)
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_spherical_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_spherical_distance);
Datum
halfvec_spherical_distance(PG_FUNCTION_ARGS)
{
@@ -681,7 +658,7 @@ halfvec_spherical_distance(PG_FUNCTION_ARGS)
/*
* Get the L1 distance between two half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l1_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l1_distance);
Datum
halfvec_l1_distance(PG_FUNCTION_ARGS)
{
@@ -696,7 +673,7 @@ halfvec_l1_distance(PG_FUNCTION_ARGS)
/*
* Get the dimensions of a half vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_vector_dims);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_vector_dims);
Datum
halfvec_vector_dims(PG_FUNCTION_ARGS)
{
@@ -708,7 +685,7 @@ halfvec_vector_dims(PG_FUNCTION_ARGS)
/*
* Get the L2 norm of a half vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_norm);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l2_norm);
Datum
halfvec_l2_norm(PG_FUNCTION_ARGS)
{
@@ -730,7 +707,7 @@ halfvec_l2_norm(PG_FUNCTION_ARGS)
/*
* Normalize a half vector with the L2 norm
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_normalize);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l2_normalize);
Datum
halfvec_l2_normalize(PG_FUNCTION_ARGS)
{
@@ -769,7 +746,7 @@ halfvec_l2_normalize(PG_FUNCTION_ARGS)
/*
* Add half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_add);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_add);
Datum
halfvec_add(PG_FUNCTION_ARGS)
{
@@ -808,7 +785,7 @@ halfvec_add(PG_FUNCTION_ARGS)
/*
* Subtract half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_sub);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_sub);
Datum
halfvec_sub(PG_FUNCTION_ARGS)
{
@@ -847,7 +824,7 @@ halfvec_sub(PG_FUNCTION_ARGS)
/*
* Multiply half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_mul);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_mul);
Datum
halfvec_mul(PG_FUNCTION_ARGS)
{
@@ -889,7 +866,7 @@ halfvec_mul(PG_FUNCTION_ARGS)
/*
* Concatenate half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_concat);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_concat);
Datum
halfvec_concat(PG_FUNCTION_ARGS)
{
@@ -913,7 +890,7 @@ halfvec_concat(PG_FUNCTION_ARGS)
/*
* Quantize a half vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_binary_quantize);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_binary_quantize);
Datum
halfvec_binary_quantize(PG_FUNCTION_ARGS)
{
@@ -931,7 +908,7 @@ halfvec_binary_quantize(PG_FUNCTION_ARGS)
/*
* Get a subvector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_subvector);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_subvector);
Datum
halfvec_subvector(PG_FUNCTION_ARGS)
{
@@ -1005,7 +982,7 @@ halfvec_cmp_internal(HalfVector * a, HalfVector * b)
/*
* Less than
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_lt);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_lt);
Datum
halfvec_lt(PG_FUNCTION_ARGS)
{
@@ -1018,7 +995,7 @@ halfvec_lt(PG_FUNCTION_ARGS)
/*
* Less than or equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_le);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_le);
Datum
halfvec_le(PG_FUNCTION_ARGS)
{
@@ -1031,7 +1008,7 @@ halfvec_le(PG_FUNCTION_ARGS)
/*
* Equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_eq);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_eq);
Datum
halfvec_eq(PG_FUNCTION_ARGS)
{
@@ -1044,7 +1021,7 @@ halfvec_eq(PG_FUNCTION_ARGS)
/*
* Not equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_ne);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_ne);
Datum
halfvec_ne(PG_FUNCTION_ARGS)
{
@@ -1057,7 +1034,7 @@ halfvec_ne(PG_FUNCTION_ARGS)
/*
* Greater than or equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_ge);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_ge);
Datum
halfvec_ge(PG_FUNCTION_ARGS)
{
@@ -1070,7 +1047,7 @@ halfvec_ge(PG_FUNCTION_ARGS)
/*
* Greater than
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_gt);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_gt);
Datum
halfvec_gt(PG_FUNCTION_ARGS)
{
@@ -1083,7 +1060,7 @@ halfvec_gt(PG_FUNCTION_ARGS)
/*
* Compare half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_cmp);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_cmp);
Datum
halfvec_cmp(PG_FUNCTION_ARGS)
{
@@ -1096,7 +1073,7 @@ halfvec_cmp(PG_FUNCTION_ARGS)
/*
* Accumulate half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_accum);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_accum);
Datum
halfvec_accum(PG_FUNCTION_ARGS)
{
@@ -1157,7 +1134,7 @@ halfvec_accum(PG_FUNCTION_ARGS)
/*
* Average half vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_avg);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_avg);
Datum
halfvec_avg(PG_FUNCTION_ARGS)
{
@@ -1191,7 +1168,7 @@ halfvec_avg(PG_FUNCTION_ARGS)
/*
* Convert sparse vector to half vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_to_halfvec);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_to_halfvec);
Datum
sparsevec_to_halfvec(PG_FUNCTION_ARGS)
{

View File

@@ -38,7 +38,7 @@
/* F16C has better performance than _Float16 (on x86-64) */
#if defined(__F16C__)
#define F16C_SUPPORT
#elif defined(__FLT16_MAX__) && !defined(HALFVEC_DISPATCH)
#elif defined(__FLT16_MAX__) && !defined(HALFVEC_DISPATCH) && !defined(__FreeBSD__) && (!defined(__i386__) || defined(__SSE2__))
#define FLT16_SUPPORT
#endif

View File

@@ -9,14 +9,18 @@
#include "commands/vacuum.h"
#include "hnsw.h"
#include "miscadmin.h"
#include "utils/float.h"
#include "utils/guc.h"
#include "utils/selfuncs.h"
#include "utils/spccache.h"
#if PG_VERSION_NUM < 150000
#define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
#endif
int hnsw_ef_search;
int hnsw_ef_stream;
bool hnsw_streaming;
int hnsw_lock_tranche_id;
static relopt_kind hnsw_relopt_kind;
@@ -59,22 +63,25 @@ HnswInit(void)
hnsw_relopt_kind = add_reloption_kind();
add_int_reloption(hnsw_relopt_kind, "m", "Max number of connections",
HNSW_DEFAULT_M, HNSW_MIN_M, HNSW_MAX_M
#if PG_VERSION_NUM >= 130000
,AccessExclusiveLock
#endif
);
HNSW_DEFAULT_M, HNSW_MIN_M, HNSW_MAX_M, AccessExclusiveLock);
add_int_reloption(hnsw_relopt_kind, "ef_construction", "Size of the dynamic candidate list for construction",
HNSW_DEFAULT_EF_CONSTRUCTION, HNSW_MIN_EF_CONSTRUCTION, HNSW_MAX_EF_CONSTRUCTION
#if PG_VERSION_NUM >= 130000
,AccessExclusiveLock
#endif
);
HNSW_DEFAULT_EF_CONSTRUCTION, HNSW_MIN_EF_CONSTRUCTION, HNSW_MAX_EF_CONSTRUCTION, AccessExclusiveLock);
DefineCustomIntVariable("hnsw.ef_search", "Sets the size of the dynamic candidate list for search",
"Valid range is 1..1000.", &hnsw_ef_search,
HNSW_DEFAULT_EF_SEARCH, HNSW_MIN_EF_SEARCH, HNSW_MAX_EF_SEARCH, PGC_USERSET, 0, NULL, NULL, NULL);
/* TODO Figure out name */
DefineCustomBoolVariable("hnsw.streaming", "Use streaming mode",
NULL, &hnsw_streaming,
HNSW_DEFAULT_STREAMING, PGC_USERSET, 0, NULL, NULL, NULL);
/* TODO Figure out name */
/* TODO Use same value as ivfflat.max_probes for "all" */
DefineCustomIntVariable("hnsw.ef_stream", "Sets the max number of additional candidates to visit for streaming search",
"-1 means all", &hnsw_ef_stream,
HNSW_DEFAULT_EF_STREAM, HNSW_MIN_EF_STREAM, HNSW_MAX_EF_STREAM, PGC_USERSET, 0, NULL, NULL, NULL);
MarkGUCPrefixReserved("hnsw");
}
@@ -95,6 +102,33 @@ hnswbuildphasename(int64 phasenum)
}
}
/*
* Estimate ef needed for iterative scans
*/
static int
EstimateEf(PlannerInfo *root, IndexPath *path)
{
double selectivity = 1;
ListCell *lc;
/* Cannot estimate without limit */
/* limit_tuples includes offset */
if (root->limit_tuples < 0)
return 0;
/* Get the selectivity of non-index conditions */
foreach(lc, path->indexinfo->indrestrictinfo)
{
RestrictInfo *rinfo = lfirst(lc);
/* Skip DEFAULT_INEQ_SEL since it may be a distance filter */
if (rinfo->norm_selec >= 0 && rinfo->norm_selec <= 1 && rinfo->norm_selec != (Selectivity) DEFAULT_INEQ_SEL)
selectivity *= rinfo->norm_selec;
}
return root->limit_tuples / Max(selectivity, 0.00001);
}
/*
* Estimate the cost of an index scan
*/
@@ -106,14 +140,19 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
{
GenericCosts costs;
int m;
int ef;
int entryLevel;
int layer0TuplesMax;
double layer0Selectivity;
double scalingFactor = 0.55;
double spc_seq_page_cost;
Relation index;
/* Never use index without order */
if (path->indexorderbys == NULL)
{
*indexStartupCost = DBL_MAX;
*indexTotalCost = DBL_MAX;
*indexStartupCost = get_float8_infinity();
*indexTotalCost = get_float8_infinity();
*indexSelectivity = 0;
*indexCorrelation = 0;
*indexPages = 0;
@@ -126,15 +165,57 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
HnswGetMetaPageInfo(index, &m, NULL);
index_close(index, NoLock);
/* Approximate entry level */
entryLevel = (int) -log(1.0 / path->indexinfo->tuples) * HnswGetMl(m);
ef = hnsw_streaming ? Max(hnsw_ef_search, EstimateEf(root, path)) : hnsw_ef_search;
/* TODO Improve estimate of visited tuples (currently underestimates) */
/* Account for number of tuples (or entry level), m, and ef_search */
costs.numIndexTuples = (entryLevel + 2) * m;
/*
* HNSW cost estimation follows a formula that accounts for the total
* number of tuples indexed combined with the parameters that most
* influence the duration of the index scan, namely: m - the number of
* tuples that are scanned in each step of the HNSW graph traversal
* ef_search - which influences the total number of steps taken at layer 0
*
* The source of the vector data can impact how many steps it takes to
* converge on the set of vectors to return to the executor. Currently, we
* use a hardcoded scaling factor (HNSWScanScalingFactor) to help
* influence that, but this could later become a configurable parameter
* based on the cost estimations.
*
* The tuple estimator formula is below:
*
* numIndexTuples = entryLevel * m + layer0TuplesMax * layer0Selectivity
*
* "entryLevel * m" represents the floor of tuples we need to scan to get
* to layer 0 (L0).
*
* "layer0TuplesMax" is the estimated total number of tuples we'd scan at
* L0 if we weren't discarding already visited tuples as part of the scan.
*
* "layer0Selectivity" estimates the percentage of tuples that are scanned
* at L0, accounting for previously visited tuples, multiplied by the
* "scalingFactor" (currently hardcoded).
*/
entryLevel = (int) (log(path->indexinfo->tuples + 1) * HnswGetMl(m));
layer0TuplesMax = HnswGetLayerM(m, 0) * ef;
layer0Selectivity = (scalingFactor * log(path->indexinfo->tuples + 1)) /
(log(m) * (1 + log(ef)));
costs.numIndexTuples = (entryLevel * m) +
(layer0TuplesMax * layer0Selectivity);
genericcostestimate(root, path, loop_count, &costs);
get_tablespace_page_costs(path->indexinfo->reltablespace, NULL, &spc_seq_page_cost);
/* Adjust cost if needed since TOAST not included in seq scan cost */
if (costs.numIndexPages > path->indexinfo->rel->pages)
{
/* Change all page cost from random to sequential */
costs.indexTotalCost -= costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
/* Remove cost of extra pages */
costs.indexTotalCost -= (costs.numIndexPages - path->indexinfo->rel->pages) * spc_seq_page_cost;
}
/* Use total cost since most work happens before first tuple is returned */
*indexStartupCost = costs.indexTotalCost;
*indexTotalCost = costs.indexTotalCost;
@@ -154,23 +235,10 @@ hnswoptions(Datum reloptions, bool validate)
{"ef_construction", RELOPT_TYPE_INT, offsetof(HnswOptions, efConstruction)},
};
#if PG_VERSION_NUM >= 130000
return (bytea *) build_reloptions(reloptions, validate,
hnsw_relopt_kind,
sizeof(HnswOptions),
tab, lengthof(tab));
#else
relopt_value *options;
int numoptions;
HnswOptions *rdopts;
options = parseRelOptions(reloptions, validate, hnsw_relopt_kind, &numoptions);
rdopts = allocateReloptStruct(sizeof(HnswOptions), options, numoptions);
fillRelOptions((void *) rdopts, sizeof(HnswOptions), options, numoptions,
validate, tab, lengthof(tab));
return (bytea *) rdopts;
#endif
}
/*
@@ -187,7 +255,7 @@ hnswvalidate(Oid opclassoid)
*
* See https://www.postgresql.org/docs/current/index-api.html
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(hnswhandler);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnswhandler);
Datum
hnswhandler(PG_FUNCTION_ARGS)
{
@@ -195,9 +263,7 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amstrategies = 0;
amroutine->amsupport = 3;
#if PG_VERSION_NUM >= 130000
amroutine->amoptsprocnum = 0;
#endif
amroutine->amcanorder = false;
amroutine->amcanorderbyop = true;
amroutine->amcanbackward = false; /* can change direction mid-scan */
@@ -210,17 +276,24 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amclusterable = false;
amroutine->ampredlocks = false;
amroutine->amcanparallel = false;
amroutine->amcaninclude = false;
#if PG_VERSION_NUM >= 130000
amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */
amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL;
#if PG_VERSION_NUM >= 170000
amroutine->amcanbuildparallel = true;
#endif
amroutine->amcaninclude = false;
amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */
#if PG_VERSION_NUM >= 160000
amroutine->amsummarizing = false;
#endif
amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL;
amroutine->amkeytype = InvalidOid;
/* Interface functions */
amroutine->ambuild = hnswbuild;
amroutine->ambuildempty = hnswbuildempty;
amroutine->aminsert = hnswinsert;
#if PG_VERSION_NUM >= 170000
amroutine->aminsertcleanup = NULL;
#endif
amroutine->ambulkdelete = hnswbulkdelete;
amroutine->amvacuumcleanup = hnswvacuumcleanup;
amroutine->amcanreturn = NULL;

View File

@@ -12,6 +12,10 @@
#include "utils/sampling.h"
#include "vector.h"
#ifdef HNSW_BENCH
#include "portability/instr_time.h"
#endif
#define HNSW_MAX_DIM 2000
#define HNSW_MAX_NNZ 1000
@@ -42,6 +46,10 @@
#define HNSW_DEFAULT_EF_SEARCH 40
#define HNSW_MIN_EF_SEARCH 1
#define HNSW_MAX_EF_SEARCH 1000
#define HNSW_DEFAULT_STREAMING false
#define HNSW_DEFAULT_EF_STREAM -1
#define HNSW_MIN_EF_STREAM -1
#define HNSW_MAX_EF_STREAM INT_MAX
/* Tuple types */
#define HNSW_ELEMENT_TUPLE_TYPE 1
@@ -68,6 +76,21 @@
#define HnswPageGetOpaque(page) ((HnswPageOpaque) PageGetSpecialPointer(page))
#define HnswPageGetMeta(page) ((HnswMetaPageData *) PageGetContents(page))
#ifdef HNSW_BENCH
#define HnswBench(name, code) \
do { \
instr_time start; \
instr_time duration; \
INSTR_TIME_SET_CURRENT(start); \
(code); \
INSTR_TIME_SET_CURRENT(duration); \
INSTR_TIME_SUBTRACT(duration, start); \
elog(INFO, "%s: %.3f ms", name, INSTR_TIME_GET_MILLISEC(duration)); \
} while (0)
#else
#define HnswBench(name, code) (code)
#endif
#if PG_VERSION_NUM >= 150000
#define RandomDouble() pg_prng_double(&pg_global_prng_state)
#define SeedRandom(seed) pg_prng_seed(&pg_global_prng_state, seed)
@@ -76,11 +99,6 @@
#define SeedRandom(seed) srandom(seed)
#endif
#if PG_VERSION_NUM < 130000
#define list_delete_last(list) list_truncate(list, list_length(list) - 1)
#define list_sort(list, cmp) ((list) = list_qsort(list, cmp))
#endif
#define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
#define HnswIsNeighborTuple(tup) ((tup)->type == HNSW_NEIGHBOR_TUPLE_TYPE)
@@ -111,6 +129,8 @@
/* Variables */
extern int hnsw_ef_search;
extern int hnsw_ef_stream;
extern bool hnsw_streaming;
extern int hnsw_lock_tranche_id;
typedef struct HnswElementData HnswElementData;
@@ -134,6 +154,7 @@ struct HnswElementData
uint8 heaptidsLength;
uint8 level;
uint8 deleted;
uint8 version;
uint32 hash;
HnswNeighborsPtr neighbors;
BlockNumber blkno;
@@ -160,11 +181,16 @@ struct HnswNeighborArray
HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
};
typedef struct HnswPairingHeapNode
typedef struct HnswSearchCandidate
{
pairingheap_node ph_node;
HnswCandidate *inner;
} HnswPairingHeapNode;
pairingheap_node c_node;
pairingheap_node w_node;
HnswElementPtr element;
float distance;
} HnswSearchCandidate;
#define HnswGetSearchCandidate(membername, ptr) pairingheap_container(HnswSearchCandidate, membername, ptr)
#define HnswGetSearchCandidateConst(membername, ptr) pairingheap_const_container(HnswSearchCandidate, membername, ptr)
/* HNSW index options */
typedef struct HnswOptions
@@ -309,10 +335,10 @@ typedef struct HnswElementTupleData
uint8 type;
uint8 level;
uint8 deleted;
uint8 unused;
uint8 version;
ItemPointerData heaptids[HNSW_HEAPTIDS];
ItemPointerData neighbortid;
uint16 unused2;
uint16 unused;
Vector data;
} HnswElementTupleData;
@@ -321,18 +347,31 @@ typedef HnswElementTupleData * HnswElementTuple;
typedef struct HnswNeighborTupleData
{
uint8 type;
uint8 unused;
uint8 version;
uint16 count;
ItemPointerData indextids[FLEXIBLE_ARRAY_MEMBER];
} HnswNeighborTupleData;
typedef HnswNeighborTupleData * HnswNeighborTuple;
typedef union
{
struct pointerhash_hash *pointers;
struct offsethash_hash *offsets;
struct tidhash_hash *tids;
} visited_hash;
typedef struct HnswScanOpaqueData
{
const HnswTypeInfo *typeInfo;
bool first;
List *w;
visited_hash v;
pairingheap *discarded;
Datum q;
int m;
int64 tuples;
double previousDistance;
MemoryContext tmpCtx;
/* Support functions */
@@ -378,14 +417,14 @@ bool HnswCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value);
Buffer HnswNewBuffer(Relation index, ForkNumber forkNum);
void HnswInitPage(Buffer buf, Page page);
void HnswInit(void);
List *HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement);
List *HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples);
HnswElement HnswGetEntryPoint(Relation index);
void HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint);
void *HnswAlloc(HnswAllocator * allocator, Size size);
HnswElement HnswInitElement(char *base, ItemPointer tid, int m, double ml, int maxLevel, HnswAllocator * alloc);
HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno);
void HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing);
HnswCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec);
HnswSearchCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec);
void HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum, bool building);
void HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m);
void HnswAddHeapTid(HnswElement element, ItemPointer heaptid);

View File

@@ -60,12 +60,6 @@
#include "pgstat.h"
#endif
#if PG_VERSION_NUM >= 130000
#define CALLBACK_ITEM_POINTER ItemPointer tid
#else
#define CALLBACK_ITEM_POINTER HeapTuple hup
#endif
#if PG_VERSION_NUM >= 140000
#include "utils/backend_status.h"
#include "utils/wait_event.h"
@@ -75,10 +69,6 @@
#define PARALLEL_KEY_HNSW_AREA UINT64CONST(0xA000000000000002)
#define PARALLEL_KEY_QUERY_TEXT UINT64CONST(0xA000000000000003)
#if PG_VERSION_NUM < 130000
#define GENERATIONCHUNK_RAWSIZE (SIZEOF_SIZE_T + SIZEOF_VOID_P * 2)
#endif
/*
* Create the metapage
*/
@@ -192,7 +182,9 @@ CreateGraphPages(HnswBuildState * buildstate)
/* Initial size check */
if (etupSize > HNSW_TUPLE_ALLOC_SIZE)
elog(ERROR, "index tuple too large");
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("index tuple too large")));
HnswSetElementTuple(base, etup, element);
@@ -379,7 +371,13 @@ UpdateNeighborsInMemory(char *base, FmgrInfo *procinfo, Oid collation, HnswEleme
for (int lc = e->level; lc >= 0; lc--)
{
int lm = HnswGetLayerM(m, lc);
HnswNeighborArray *neighbors = HnswGetNeighbors(base, e, lc);
Size neighborsSize = HNSW_NEIGHBOR_ARRAY_SIZE(lm);
HnswNeighborArray *neighbors = palloc(neighborsSize);
/* Copy neighbors to local memory */
LWLockAcquire(&e->lock, LW_SHARED);
memcpy(neighbors, HnswGetNeighbors(base, e, lc), neighborsSize);
LWLockRelease(&e->lock);
for (int i = 0; i < neighbors->length; i++)
{
@@ -389,7 +387,6 @@ UpdateNeighborsInMemory(char *base, FmgrInfo *procinfo, Oid collation, HnswEleme
/* Keep scan-build happy on Mac x86-64 */
Assert(neighborElement);
/* Use element for lock instead of hc since hc can be replaced */
LWLockAcquire(&neighborElement->lock, LW_EXCLUSIVE);
HnswUpdateConnection(base, e, hc, lm, lc, NULL, NULL, procinfo, collation);
LWLockRelease(&neighborElement->lock);
@@ -578,17 +575,13 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
* Callback for table_index_build_scan
*/
static void
BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
BuildCallback(Relation index, ItemPointer tid, Datum *values,
bool *isnull, bool tupleIsAlive, void *state)
{
HnswBuildState *buildstate = (HnswBuildState *) state;
HnswGraph *graph = buildstate->graph;
MemoryContext oldCtx;
#if PG_VERSION_NUM < 130000
ItemPointer tid = &hup->t_self;
#endif
/* Skip nulls */
if (isnull[0])
return;
@@ -651,11 +644,7 @@ HnswMemoryContextAlloc(Size size, void *state)
HnswBuildState *buildstate = (HnswBuildState *) state;
void *chunk = MemoryContextAlloc(buildstate->graphCtx, size);
#if PG_VERSION_NUM >= 130000
buildstate->graphData.memoryUsed = MemoryContextMemAllocated(buildstate->graphCtx, false);
#else
buildstate->graphData.memoryUsed += MAXALIGN(size);
#endif
return chunk;
}
@@ -691,17 +680,25 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
/* Disallow varbit since require fixed dimensions */
if (TupleDescAttr(index->rd_att, 0)->atttypid == VARBITOID)
elog(ERROR, "type not supported for hnsw index");
ereport(ERROR,
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
errmsg("type not supported for hnsw index")));
/* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0)
elog(ERROR, "column does not have dimensions");
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("column does not have dimensions")));
if (buildstate->dimensions > buildstate->typeInfo->maxDimensions)
elog(ERROR, "column cannot have more than %d dimensions for hnsw index", buildstate->typeInfo->maxDimensions);
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("column cannot have more than %d dimensions for hnsw index", buildstate->typeInfo->maxDimensions)));
if (buildstate->efConstruction < 2 * buildstate->m)
elog(ERROR, "ef_construction must be greater than or equal to 2 * m");
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("ef_construction must be greater than or equal to 2 * m")));
buildstate->reltuples = 0;
buildstate->indtuples = 0;
@@ -1121,8 +1118,8 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
BuildGraph(buildstate, forkNum);
if (RelationNeedsWAL(index))
log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocks(index), true);
if (RelationNeedsWAL(index) || forkNum == INIT_FORKNUM)
log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true);
FreeBuildState(buildstate);
}

View File

@@ -36,14 +36,15 @@ GetInsertPage(Relation index)
* Check for a free offset
*/
static bool
HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size ntupSize, Buffer *nbuf, Page *npage, OffsetNumber *freeOffno, OffsetNumber *freeNeighborOffno, BlockNumber *newInsertPage)
HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size etupSize, Size ntupSize, Buffer *nbuf, Page *npage, OffsetNumber *freeOffno, OffsetNumber *freeNeighborOffno, BlockNumber *newInsertPage, uint8 *tupleVersion)
{
OffsetNumber offno;
OffsetNumber maxoffno = PageGetMaxOffsetNumber(page);
for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
{
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
ItemId eitemid = PageGetItemId(page, offno);
HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, eitemid);
/* Skip neighbor tuples */
if (!HnswIsElementTuple(etup))
@@ -54,7 +55,9 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
BlockNumber elementPage = BufferGetBlockNumber(buf);
BlockNumber neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
OffsetNumber neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
ItemId itemid;
ItemId nitemid;
Size pageFree;
Size npageFree;
if (!BlockNumberIsValid(*newInsertPage))
*newInsertPage = elementPage;
@@ -73,13 +76,29 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
*npage = BufferGetPage(*nbuf);
}
itemid = PageGetItemId(*npage, neighborOffno);
nitemid = PageGetItemId(*npage, neighborOffno);
/* Check for space on neighbor tuple page */
if (PageGetFreeSpace(*npage) + ItemIdGetLength(itemid) - sizeof(ItemIdData) >= ntupSize)
/* Ensure aligned for space check */
Assert(etupSize == MAXALIGN(etupSize));
Assert(ntupSize == MAXALIGN(ntupSize));
/*
* Calculate free space individually since tuples are overwritten
* individually (in separate calls to PageIndexTupleOverwrite)
*/
pageFree = ItemIdGetLength(eitemid) + PageGetExactFreeSpace(page);
npageFree = ItemIdGetLength(nitemid);
if (neighborPage != elementPage)
npageFree += PageGetExactFreeSpace(*npage);
else if (pageFree >= etupSize)
npageFree += pageFree - etupSize;
/* Check for space */
if (pageFree >= etupSize && npageFree >= ntupSize)
{
*freeOffno = offno;
*freeNeighborOffno = neighborOffno;
*tupleVersion = etup->version;
return true;
}
else if (*nbuf != buf)
@@ -135,6 +154,7 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
OffsetNumber freeOffno = InvalidOffsetNumber;
OffsetNumber freeNeighborOffno = InvalidOffsetNumber;
BlockNumber newInsertPage = InvalidBlockNumber;
uint8 tupleVersion;
char *base = NULL;
/* Calculate sizes */
@@ -184,7 +204,7 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
}
/* Next, try space from a deleted element */
if (HnswFreeOffset(index, buf, page, e, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage))
if (HnswFreeOffset(index, buf, page, e, etupSize, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage, &tupleVersion))
{
if (nbuf != buf)
{
@@ -194,6 +214,10 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
npage = GenericXLogRegisterBuffer(state, nbuf, 0);
}
/* Set tuple version */
etup->version = tupleVersion;
ntup->version = tupleVersion;
break;
}
@@ -361,8 +385,12 @@ HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, Hns
HnswElement neighborElement = HnswPtrAccess(base, hc->element);
OffsetNumber offno = neighborElement->neighborOffno;
/* Get latest neighbors since they may have changed */
/* Do not lock yet since selecting neighbors can take time */
/*
* Get latest neighbors since they may have changed. Do not lock
* yet since selecting neighbors can take time. Could use
* optimistic locking to retry if another update occurs before
* getting exclusive lock.
*/
HnswLoadNeighbors(neighborElement, index, m);
/*

View File

@@ -1,5 +1,7 @@
#include "postgres.h"
#include <float.h>
#include "access/relscan.h"
#include "hnsw.h"
#include "pgstat.h"
@@ -26,6 +28,9 @@ GetScanItems(IndexScanDesc scan, Datum q)
/* Get m and entry point */
HnswGetMetaPageInfo(index, &m, &entryPoint);
so->q = q;
so->m = m;
if (entryPoint == NULL)
return NIL;
@@ -33,11 +38,44 @@ GetScanItems(IndexScanDesc scan, Datum q)
for (int lc = entryPoint->level; lc >= 1; lc--)
{
w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, false, NULL);
w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, false, NULL, NULL, NULL, true, NULL);
ep = w;
}
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL, &so->v, hnsw_streaming ? &so->discarded : NULL, true, &so->tuples);
}
/*
* Resume scan at ground level with discarded candidates
*/
static List *
ResumeScanItems(IndexScanDesc scan)
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
Relation index = scan->indexRelation;
FmgrInfo *procinfo = so->procinfo;
Oid collation = so->collation;
List *ep = NIL;
char *base = NULL;
int batch_size = hnsw_ef_search;
if (pairingheap_is_empty(so->discarded))
return NIL;
/* Get next batch of candidates */
for (int i = 0; i < batch_size; i++)
{
HnswSearchCandidate *hc;
if (pairingheap_is_empty(so->discarded))
break;
hc = HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded));
ep = lappend(ep, hc);
}
return HnswSearchLayer(base, so->q, ep, batch_size, 0, index, procinfo, collation, so->m, false, NULL, &so->v, &so->discarded, false, &so->tuples);
}
/*
@@ -81,6 +119,8 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData));
so->typeInfo = HnswGetTypeInfo(index);
so->first = true;
so->v.tids = NULL;
so->discarded = NULL;
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Hnsw scan temporary context",
ALLOCSET_DEFAULT_SIZES);
@@ -103,7 +143,15 @@ hnswrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int no
{
HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
if (so->v.tids != NULL)
tidhash_reset(so->v.tids);
if (so->discarded != NULL)
pairingheap_reset(so->discarded);
so->first = true;
so->tuples = 0;
so->previousDistance = -INFINITY;
MemoryContextReset(so->tmpCtx);
if (keys && scan->numberOfKeys > 0)
@@ -153,34 +201,109 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
*/
LockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
so->w = GetScanItems(scan, value);
HnswBench("scan iteration", so->w = GetScanItems(scan, value));
/* Release shared lock */
UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
so->first = false;
#if defined(HNSW_MEMORY) && PG_VERSION_NUM >= 130000
elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(so->tmpCtx, false) / (1024 * 1024));
#if defined(HNSW_MEMORY)
elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(so->tmpCtx, false) / 1024);
#endif
}
while (list_length(so->w) > 0)
for (;;)
{
char *base = NULL;
HnswCandidate *hc = llast(so->w);
HnswElement element = HnswPtrAccess(base, hc->element);
HnswSearchCandidate *hc;
HnswElement element;
ItemPointer heaptid;
if (list_length(so->w) == 0)
{
if (!hnsw_streaming)
break;
/* Empty index */
if (so->discarded == NULL)
break;
/* Reached max number of additional tuples */
if (hnsw_ef_stream != -1 && so->tuples >= hnsw_ef_search + hnsw_ef_stream)
{
if (pairingheap_is_empty(so->discarded))
break;
/* Return remaining tuples */
so->w = lappend(so->w, HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded)));
}
/* Prevent scans from consuming too much memory */
else if (MemoryContextMemAllocated(so->tmpCtx, false) > (Size) work_mem * 1024L)
{
if (pairingheap_is_empty(so->discarded))
{
ereport(NOTICE,
(errmsg("hnsw index scan exceeded work_mem after " INT64_FORMAT " tuples", so->tuples),
errhint("Increase work_mem to scan more tuples.")));
break;
}
/* Return remaining tuples */
so->w = lappend(so->w, HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded)));
}
else
{
/*
* Locking ensures when neighbors are read, the elements they
* reference will not be deleted (and replaced) during the
* iteration.
*
* Elements loaded into memory on previous iterations may have
* been deleted (and replaced), so when reading neighbors, the
* element version must be checked.
*/
LockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
HnswBench("scan iteration", so->w = ResumeScanItems(scan));
UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
#if defined(HNSW_MEMORY)
elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(so->tmpCtx, false) / 1024);
#endif
}
if (list_length(so->w) == 0)
break;
}
hc = llast(so->w);
element = HnswPtrAccess(base, hc->element);
/* Move to next element if no valid heap TIDs */
if (element->heaptidsLength == 0)
{
so->w = list_delete_last(so->w);
/* Mark memory as free for next iteration */
if (hnsw_streaming)
{
pfree(element);
pfree(hc);
}
continue;
}
heaptid = &element->heaptids[--element->heaptidsLength];
if (hc->distance < so->previousDistance)
continue;
so->previousDistance = hc->distance;
MemoryContextSwitchTo(oldCtx);
scan->xs_heaptid = *heaptid;

View File

@@ -5,6 +5,7 @@
#include "access/generic_xlog.h"
#include "catalog/pg_type.h"
#include "catalog/pg_type_d.h"
#include "common/hashfn.h"
#include "fmgr.h"
#include "hnsw.h"
#include "lib/pairingheap.h"
@@ -14,12 +15,6 @@
#include "utils/memdebug.h"
#include "utils/rel.h"
#if PG_VERSION_NUM >= 130000
#include "common/hashfn.h"
#else
#include "utils/hashutils.h"
#endif
#if PG_VERSION_NUM < 170000
static inline uint64
murmurhash64(uint64 data)
@@ -107,10 +102,9 @@ hash_offset(Size offset)
typedef union
{
pointerhash_hash *pointers;
offsethash_hash *offsets;
tidhash_hash *tids;
} visited_hash;
HnswElement element;
ItemPointerData indextid;
} HnswUnvisited;
/*
* Get the max number of connections in an upper layer for each element in the index
@@ -252,6 +246,8 @@ HnswInitElement(char *base, ItemPointer heaptid, int m, double ml, int maxLevel,
element->level = level;
element->deleted = 0;
/* Start at one to make it easier to find issues */
element->version = 1;
HnswInitNeighbors(base, element, m, allocator);
@@ -300,6 +296,9 @@ HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint)
page = BufferGetPage(buf);
metap = HnswPageGetMeta(page);
if (unlikely(metap->magicNumber != HNSW_MAGIC_NUMBER))
elog(ERROR, "hnsw index is not valid");
if (m != NULL)
*m = metap->m;
@@ -401,6 +400,7 @@ HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element)
etup->type = HNSW_ELEMENT_TUPLE_TYPE;
etup->level = element->level;
etup->deleted = 0;
etup->version = element->version;
for (int i = 0; i < HNSW_HEAPTIDS; i++)
{
if (i < element->heaptidsLength)
@@ -443,6 +443,7 @@ HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m)
}
ntup->count = idx;
ntup->version = e->version;
}
/*
@@ -516,6 +517,7 @@ HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHe
{
element->level = etup->level;
element->deleted = etup->deleted;
element->version = etup->version;
element->neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
element->neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
element->heaptidsLength = 0;
@@ -544,19 +546,19 @@ HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHe
/*
* Load an element and optionally get its distance from q
*/
void
HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance)
static void
HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance, HnswElement * element)
{
Buffer buf;
Page page;
HnswElementTuple etup;
/* Read vector */
buf = ReadBuffer(index, element->blkno);
buf = ReadBuffer(index, blkno);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, element->offno));
etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
Assert(HnswIsElementTuple(etup));
@@ -571,19 +573,32 @@ HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index,
/* Load element */
if (distance == NULL || maxDistance == NULL || *distance < *maxDistance)
HnswLoadElementFromTuple(element, etup, true, loadVec);
{
if (*element == NULL)
*element = HnswInitElementFromBlock(blkno, offno);
HnswLoadElementFromTuple(*element, etup, true, loadVec);
}
UnlockReleaseBuffer(buf);
}
/*
* Get the distance for a candidate
* Load an element and optionally get its distance from q
*/
void
HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance)
{
HnswLoadElementImpl(element->blkno, element->offno, distance, q, index, procinfo, collation, loadVec, maxDistance, &element);
}
/*
* Get the distance for an element
*/
static float
GetCandidateDistance(char *base, HnswCandidate * hc, Datum q, FmgrInfo *procinfo, Oid collation)
GetElementDistance(char *base, HnswElement element, Datum q, FmgrInfo *procinfo, Oid collation)
{
HnswElement hce = HnswPtrAccess(base, hc->element);
Datum value = HnswGetValue(base, hce);
Datum value = HnswGetValue(base, element);
return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, q, value));
}
@@ -591,14 +606,14 @@ GetCandidateDistance(char *base, HnswCandidate * hc, Datum q, FmgrInfo *procinfo
/*
* Create a candidate for the entry point
*/
HnswCandidate *
HnswSearchCandidate *
HnswEntryCandidate(char *base, HnswElement entryPoint, Datum q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec)
{
HnswCandidate *hc = palloc(sizeof(HnswCandidate));
HnswSearchCandidate *hc = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, hc->element, entryPoint);
if (index == NULL)
hc->distance = GetCandidateDistance(base, hc, q, procinfo, collation);
hc->distance = GetElementDistance(base, entryPoint, q, procinfo, collation);
else
HnswLoadElement(entryPoint, &hc->distance, &q, index, procinfo, collation, loadVec, NULL);
return hc;
@@ -610,10 +625,25 @@ HnswEntryCandidate(char *base, HnswElement entryPoint, Datum q, Relation index,
static int
CompareNearestCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg)
{
if (((const HnswPairingHeapNode *) a)->inner->distance < ((const HnswPairingHeapNode *) b)->inner->distance)
if (HnswGetSearchCandidateConst(c_node, a)->distance < HnswGetSearchCandidateConst(c_node, b)->distance)
return 1;
if (((const HnswPairingHeapNode *) a)->inner->distance > ((const HnswPairingHeapNode *) b)->inner->distance)
if (HnswGetSearchCandidateConst(c_node, a)->distance > HnswGetSearchCandidateConst(c_node, b)->distance)
return -1;
return 0;
}
/*
* Compare discarded candidate distances
*/
static int
CompareNearestDiscardedCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg)
{
if (HnswGetSearchCandidateConst(w_node, a)->distance < HnswGetSearchCandidateConst(w_node, b)->distance)
return 1;
if (HnswGetSearchCandidateConst(w_node, a)->distance > HnswGetSearchCandidateConst(w_node, b)->distance)
return -1;
return 0;
@@ -625,27 +655,15 @@ CompareNearestCandidates(const pairingheap_node *a, const pairingheap_node *b, v
static int
CompareFurthestCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg)
{
if (((const HnswPairingHeapNode *) a)->inner->distance < ((const HnswPairingHeapNode *) b)->inner->distance)
if (HnswGetSearchCandidateConst(w_node, a)->distance < HnswGetSearchCandidateConst(w_node, b)->distance)
return -1;
if (((const HnswPairingHeapNode *) a)->inner->distance > ((const HnswPairingHeapNode *) b)->inner->distance)
if (HnswGetSearchCandidateConst(w_node, a)->distance > HnswGetSearchCandidateConst(w_node, b)->distance)
return 1;
return 0;
}
/*
* Create a pairing heap node for a candidate
*/
static HnswPairingHeapNode *
CreatePairingHeapNode(HnswCandidate * c)
{
HnswPairingHeapNode *node = palloc(sizeof(HnswPairingHeapNode));
node->inner = c;
return node;
}
/*
* Init visited
*/
@@ -664,11 +682,11 @@ InitVisited(char *base, visited_hash * v, Relation index, int ef, int m)
* Add to visited
*/
static inline void
AddToVisited(char *base, visited_hash * v, HnswCandidate * hc, Relation index, bool *found)
AddToVisited(char *base, visited_hash * v, HnswElementPtr elementPtr, Relation index, bool *found)
{
if (index != NULL)
{
HnswElement element = HnswPtrAccess(base, hc->element);
HnswElement element = HnswPtrAccess(base, elementPtr);
ItemPointerData indextid;
ItemPointerSet(&indextid, element->blkno, element->offno);
@@ -676,23 +694,15 @@ AddToVisited(char *base, visited_hash * v, HnswCandidate * hc, Relation index, b
}
else if (base != NULL)
{
#if PG_VERSION_NUM >= 130000
HnswElement element = HnswPtrAccess(base, hc->element);
HnswElement element = HnswPtrAccess(base, elementPtr);
offsethash_insert_hash(v->offsets, HnswPtrOffset(hc->element), element->hash, found);
#else
offsethash_insert(v->offsets, HnswPtrOffset(hc->element), found);
#endif
offsethash_insert_hash(v->offsets, HnswPtrOffset(elementPtr), element->hash, found);
}
else
{
#if PG_VERSION_NUM >= 130000
HnswElement element = HnswPtrAccess(base, hc->element);
HnswElement element = HnswPtrAccess(base, elementPtr);
pointerhash_insert_hash(v->pointers, (uintptr_t) HnswPtrPointer(hc->element), element->hash, found);
#else
pointerhash_insert(v->pointers, (uintptr_t) HnswPtrPointer(hc->element), found);
#endif
pointerhash_insert_hash(v->pointers, (uintptr_t) HnswPtrPointer(elementPtr), element->hash, found);
}
}
@@ -700,69 +710,168 @@ AddToVisited(char *base, visited_hash * v, HnswCandidate * hc, Relation index, b
* Count element towards ef
*/
static inline bool
CountElement(char *base, HnswElement skipElement, HnswCandidate * hc)
CountElement(HnswElement skipElement, HnswElement e)
{
HnswElement e;
if (skipElement == NULL)
return true;
/* Ensure does not access heaptidsLength during in-memory build */
pg_memory_barrier();
e = HnswPtrAccess(base, hc->element);
/* Keep scan-build happy on Mac x86-64 */
Assert(e);
return e->heaptidsLength != 0;
}
/*
* Load unvisited neighbors from memory
*/
static void
HnswLoadUnvisitedFromMemory(char *base, HnswElement element, HnswUnvisited * unvisited, int *unvisitedLength, visited_hash * v, int lc, HnswNeighborArray * localNeighborhood, Size neighborhoodSize)
{
/* Get the neighborhood at layer lc */
HnswNeighborArray *neighborhood = HnswGetNeighbors(base, element, lc);
/* Copy neighborhood to local memory */
LWLockAcquire(&element->lock, LW_SHARED);
memcpy(localNeighborhood, neighborhood, neighborhoodSize);
LWLockRelease(&element->lock);
*unvisitedLength = 0;
for (int i = 0; i < localNeighborhood->length; i++)
{
HnswCandidate *hc = &localNeighborhood->items[i];
bool found;
AddToVisited(base, v, hc->element, NULL, &found);
if (!found)
unvisited[(*unvisitedLength)++].element = HnswPtrAccess(base, hc->element);
}
}
/*
* Load unvisited neighbors from disk
*/
static void
HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *unvisitedLength, visited_hash * v, Relation index, int m, int lm, int lc)
{
Buffer buf;
Page page;
HnswNeighborTuple ntup;
int start;
ItemPointerData indextids[HNSW_MAX_M * 2];
*unvisitedLength = 0;
buf = ReadBuffer(index, element->neighborPage);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, element->neighborOffno));
/*
* Ensure the neighbor tuple has not been deleted or replaced between
* index scan iterations
*/
if (ntup->version != element->version || ntup->count != (element->level + 2) * m)
{
UnlockReleaseBuffer(buf);
return;
}
/* Copy to minimize lock time */
start = (element->level - lc) * m;
memcpy(&indextids, ntup->indextids + start, lm * sizeof(ItemPointerData));
UnlockReleaseBuffer(buf);
for (int i = 0; i < lm; i++)
{
ItemPointer indextid = &indextids[i];
bool found;
if (!ItemPointerIsValid(indextid))
break;
tidhash_insert(v->tids, *indextid, &found);
if (!found)
unvisited[(*unvisitedLength)++].indextid = *indextid;
}
}
/*
* Algorithm 2 from paper
*/
List *
HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement)
HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples)
{
List *w = NIL;
pairingheap *C = pairingheap_allocate(CompareNearestCandidates, NULL);
pairingheap *W = pairingheap_allocate(CompareFurthestCandidates, NULL);
int wlen = 0;
visited_hash v;
visited_hash vh;
ListCell *lc2;
HnswNeighborArray *neighborhoodData = NULL;
Size neighborhoodSize;
HnswNeighborArray *localNeighborhood = NULL;
Size neighborhoodSize = 0;
int lm = HnswGetLayerM(m, lc);
HnswUnvisited *unvisited = palloc(lm * sizeof(HnswUnvisited));
int unvisitedLength;
InitVisited(base, &v, index, ef, m);
if (v == NULL)
{
v = &vh;
initVisited = true;
}
if (initVisited)
{
InitVisited(base, v, index, ef, m);
if (discarded != NULL)
*discarded = pairingheap_allocate(CompareNearestDiscardedCandidates, NULL);
}
/* Create local memory for neighborhood if needed */
if (index == NULL)
{
neighborhoodSize = HNSW_NEIGHBOR_ARRAY_SIZE(HnswGetLayerM(m, lc));
neighborhoodData = palloc(neighborhoodSize);
neighborhoodSize = HNSW_NEIGHBOR_ARRAY_SIZE(lm);
localNeighborhood = palloc(neighborhoodSize);
}
/* Add entry points to v, C, and W */
foreach(lc2, ep)
{
HnswCandidate *hc = (HnswCandidate *) lfirst(lc2);
HnswSearchCandidate *hc = (HnswSearchCandidate *) lfirst(lc2);
bool found;
AddToVisited(base, &v, hc, index, &found);
if (initVisited)
{
AddToVisited(base, v, hc->element, index, &found);
pairingheap_add(C, &(CreatePairingHeapNode(hc)->ph_node));
pairingheap_add(W, &(CreatePairingHeapNode(hc)->ph_node));
if (tuples != NULL)
(*tuples)++;
}
pairingheap_add(C, &hc->c_node);
pairingheap_add(W, &hc->w_node);
/*
* Do not count elements being deleted towards ef when vacuuming. It
* would be ideal to do this for inserts as well, but this could
* affect insert performance.
*/
if (CountElement(base, skipElement, hc))
if (CountElement(skipElement, HnswPtrAccess(base, hc->element)))
wlen++;
}
while (!pairingheap_is_empty(C))
{
HnswNeighborArray *neighborhood;
HnswCandidate *c = ((HnswPairingHeapNode *) pairingheap_remove_first(C))->inner;
HnswCandidate *f = ((HnswPairingHeapNode *) pairingheap_first(W))->inner;
HnswSearchCandidate *c = HnswGetSearchCandidate(c_node, pairingheap_remove_first(C));
HnswSearchCandidate *f = HnswGetSearchCandidate(w_node, pairingheap_first(W));
HnswElement cElement;
if (c->distance > f->distance)
@@ -770,71 +879,80 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
cElement = HnswPtrAccess(base, c->element);
if (HnswPtrIsNull(base, cElement->neighbors))
HnswLoadNeighbors(cElement, index, m);
/* Get the neighborhood at layer lc */
neighborhood = HnswGetNeighbors(base, cElement, lc);
/* Copy neighborhood to local memory if needed */
if (index == NULL)
HnswLoadUnvisitedFromMemory(base, cElement, unvisited, &unvisitedLength, v, lc, localNeighborhood, neighborhoodSize);
else
HnswLoadUnvisitedFromDisk(cElement, unvisited, &unvisitedLength, v, index, m, lm, lc);
if (tuples != NULL)
(*tuples) += unvisitedLength;
for (int i = 0; i < unvisitedLength; i++)
{
LWLockAcquire(&cElement->lock, LW_SHARED);
memcpy(neighborhoodData, neighborhood, neighborhoodSize);
LWLockRelease(&cElement->lock);
neighborhood = neighborhoodData;
}
HnswElement eElement;
HnswSearchCandidate *e;
float eDistance;
bool alwaysAdd = wlen < ef;
for (int i = 0; i < neighborhood->length; i++)
{
HnswCandidate *e = &neighborhood->items[i];
bool visited;
f = HnswGetSearchCandidate(w_node, pairingheap_first(W));
AddToVisited(base, &v, e, index, &visited);
if (!visited)
if (index == NULL)
{
float eDistance;
HnswElement eElement = HnswPtrAccess(base, e->element);
eElement = unvisited[i].element;
eDistance = GetElementDistance(base, eElement, q, procinfo, collation);
}
else
{
ItemPointer indextid = &unvisited[i].indextid;
BlockNumber blkno = ItemPointerGetBlockNumber(indextid);
OffsetNumber offno = ItemPointerGetOffsetNumber(indextid);
f = ((HnswPairingHeapNode *) pairingheap_first(W))->inner;
/* Avoid any allocations if not adding */
eElement = NULL;
HnswLoadElementImpl(blkno, offno, &eDistance, &q, index, procinfo, collation, inserting, alwaysAdd || discarded != NULL ? NULL : &f->distance, &eElement);
}
if (index == NULL)
eDistance = GetCandidateDistance(base, e, q, procinfo, collation);
else
HnswLoadElement(eElement, &eDistance, &q, index, procinfo, collation, inserting, wlen >= ef ? &f->distance : NULL);
if (eDistance < f->distance || wlen < ef)
if (eElement == NULL || !(eDistance < f->distance || alwaysAdd))
{
if (discarded != NULL)
{
HnswCandidate *ec;
/* Create a new candidate */
e = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, e->element, eElement);
e->distance = eDistance;
pairingheap_add(*discarded, &e->w_node);
}
Assert(!eElement->deleted);
continue;
}
/* Make robust to issues */
if (eElement->level < lc)
continue;
/* Make robust to issues */
if (eElement->level < lc)
continue;
/* Copy e */
ec = palloc(sizeof(HnswCandidate));
HnswPtrStore(base, ec->element, eElement);
ec->distance = eDistance;
/* Create a new candidate */
e = palloc(sizeof(HnswSearchCandidate));
HnswPtrStore(base, e->element, eElement);
e->distance = eDistance;
pairingheap_add(C, &e->c_node);
pairingheap_add(W, &e->w_node);
pairingheap_add(C, &(CreatePairingHeapNode(ec)->ph_node));
pairingheap_add(W, &(CreatePairingHeapNode(ec)->ph_node));
/*
* Do not count elements being deleted towards ef when vacuuming.
* It would be ideal to do this for inserts as well, but this
* could affect insert performance.
*/
if (CountElement(skipElement, eElement))
{
wlen++;
/*
* Do not count elements being deleted towards ef when
* vacuuming. It would be ideal to do this for inserts as
* well, but this could affect insert performance.
*/
if (CountElement(base, skipElement, e))
{
wlen++;
/* No need to decrement wlen */
if (wlen > ef)
{
HnswSearchCandidate *d = HnswGetSearchCandidate(w_node, pairingheap_remove_first(W));
/* No need to decrement wlen */
if (wlen > ef)
pairingheap_remove_first(W);
}
if (discarded != NULL)
pairingheap_add(*discarded, &d->w_node);
}
}
}
@@ -843,7 +961,7 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
/* Add each element of W to w */
while (!pairingheap_is_empty(W))
{
HnswCandidate *hc = ((HnswPairingHeapNode *) pairingheap_remove_first(W))->inner;
HnswSearchCandidate *hc = HnswGetSearchCandidate(w_node, pairingheap_remove_first(W));
w = lappend(w, hc);
}
@@ -855,17 +973,10 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
* Compare candidate distances with pointer tie-breaker
*/
static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistances(const ListCell *a, const ListCell *b)
{
HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b);
#else
CompareCandidateDistances(const void *a, const void *b)
{
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif
if (hca->distance < hcb->distance)
return 1;
@@ -886,17 +997,10 @@ CompareCandidateDistances(const void *a, const void *b)
* Compare candidate distances with offset tie-breaker
*/
static int
#if PG_VERSION_NUM >= 130000
CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b)
{
HnswCandidate *hca = lfirst(a);
HnswCandidate *hcb = lfirst(b);
#else
CompareCandidateDistancesOffset(const void *a, const void *b)
{
HnswCandidate *hca = lfirst(*(ListCell **) a);
HnswCandidate *hcb = lfirst(*(ListCell **) b);
#endif
if (hca->distance < hcb->distance)
return 1;
@@ -1106,7 +1210,7 @@ HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm
if (HnswPtrIsNull(base, hc3Element->value))
HnswLoadElement(hc3Element, &hc3->distance, &q, index, procinfo, collation, true, NULL);
else
hc3->distance = GetCandidateDistance(base, hc3, q, procinfo, collation);
hc3->distance = GetElementDistance(base, hc3Element, q, procinfo, collation);
/* Prune element if being deleted */
if (hc3Element->heaptidsLength == 0)
@@ -1178,7 +1282,6 @@ RemoveElements(char *base, List *w, HnswElement skipElement)
return w2;
}
#if PG_VERSION_NUM >= 130000
/*
* Precompute hash
*/
@@ -1194,7 +1297,6 @@ PrecomputeHash(char *base, HnswElement element)
else
element->hash = hash_offset(HnswPtrOffset(ptr));
}
#endif
/*
* Algorithm 1 from paper
@@ -1209,11 +1311,9 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
Datum q = HnswGetValue(base, element);
HnswElement skipElement = existing ? element : NULL;
#if PG_VERSION_NUM >= 130000
/* Precompute hash */
if (index == NULL)
PrecomputeHash(base, element);
#endif
/* No neighbors if no entry point */
if (entryPoint == NULL)
@@ -1226,7 +1326,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
/* 1st phase: greedy search to insert level */
for (int lc = entryLevel; lc >= level + 1; lc--)
{
w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, true, skipElement);
w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, true, skipElement, NULL, NULL, true, NULL);
ep = w;
}
@@ -1242,16 +1342,27 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
{
int lm = HnswGetLayerM(m, lc);
List *neighbors;
List *lw;
List *lw = NIL;
ListCell *lc2;
w = HnswSearchLayer(base, q, ep, efConstruction, lc, index, procinfo, collation, m, true, skipElement);
w = HnswSearchLayer(base, q, ep, efConstruction, lc, index, procinfo, collation, m, true, skipElement, NULL, NULL, true, NULL);
/* Convert search candidates to candidates */
foreach(lc2, w)
{
HnswSearchCandidate *sc = lfirst(lc2);
HnswCandidate *hc = palloc(sizeof(HnswCandidate));
hc->element = sc->element;
hc->distance = sc->distance;
lw = lappend(lw, hc);
}
/* Elements being deleted or skipped can help with search */
/* but should be removed before selecting neighbors */
if (index != NULL)
lw = RemoveElements(base, w, skipElement);
else
lw = w;
lw = RemoveElements(base, lw, skipElement);
/*
* Candidates are sorted, but not deterministically. Could set
@@ -1276,7 +1387,9 @@ SparsevecCheckValue(Pointer v)
SparseVector *vec = (SparseVector *) v;
if (vec->nnz > HNSW_MAX_NNZ)
elog(ERROR, "sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ);
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ)));
}
/*
@@ -1301,7 +1414,7 @@ HnswGetTypeInfo(Relation index)
return (const HnswTypeInfo *) DatumGetPointer(FunctionCall0Coll(procinfo, InvalidOid));
}
PGDLLEXPORT PG_FUNCTION_INFO_V1(hnsw_halfvec_support);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_halfvec_support);
Datum
hnsw_halfvec_support(PG_FUNCTION_ARGS)
{
@@ -1314,7 +1427,7 @@ hnsw_halfvec_support(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(&typeInfo);
};
PGDLLEXPORT PG_FUNCTION_INFO_V1(hnsw_bit_support);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_bit_support);
Datum
hnsw_bit_support(PG_FUNCTION_ARGS)
{
@@ -1327,7 +1440,7 @@ hnsw_bit_support(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(&typeInfo);
};
PGDLLEXPORT PG_FUNCTION_INFO_V1(hnsw_sparsevec_support);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_sparsevec_support);
Datum
hnsw_sparsevec_support(PG_FUNCTION_ARGS)
{

View File

@@ -527,6 +527,14 @@ MarkDeleted(HnswVacuumState * vacuumstate)
for (int i = 0; i < ntup->count; i++)
ItemPointerSetInvalid(&ntup->indextids[i]);
/* Increment version */
/* This is used to avoid incorrect reads for iterative scans */
/* Reserve some bits for future use */
etup->version++;
if (etup->version > 15)
etup->version = 1;
ntup->version = etup->version;
/*
* We modified the tuples in place, no need to call
* PageIndexTupleOverwrite

View File

@@ -26,12 +26,6 @@
#include "pgstat.h"
#endif
#if PG_VERSION_NUM >= 130000
#define CALLBACK_ITEM_POINTER ItemPointer tid
#else
#define CALLBACK_ITEM_POINTER HeapTuple hup
#endif
#if PG_VERSION_NUM >= 140000
#include "utils/backend_status.h"
#include "utils/wait_event.h"
@@ -96,7 +90,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
* Callback for sampling
*/
static void
SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
SampleCallback(Relation index, ItemPointer tid, Datum *values,
bool *isnull, bool tupleIsAlive, void *state)
{
IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
@@ -207,16 +201,12 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
* Callback for table_index_build_scan
*/
static void
BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
BuildCallback(Relation index, ItemPointer tid, Datum *values,
bool *isnull, bool tupleIsAlive, void *state)
{
IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
MemoryContext oldCtx;
#if PG_VERSION_NUM < 130000
ItemPointer tid = &hup->t_self;
#endif
/* Skip nulls */
if (isnull[0])
return;
@@ -335,14 +325,20 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
/* Disallow varbit since require fixed dimensions */
if (TupleDescAttr(index->rd_att, 0)->atttypid == VARBITOID)
elog(ERROR, "type not supported for ivfflat index");
ereport(ERROR,
(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
errmsg("type not supported for ivfflat index")));
/* Require column to have dimensions to be indexed */
if (buildstate->dimensions < 0)
elog(ERROR, "column does not have dimensions");
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("column does not have dimensions")));
if (buildstate->dimensions > buildstate->typeInfo->maxDimensions)
elog(ERROR, "column cannot have more than %d dimensions for ivfflat index", buildstate->typeInfo->maxDimensions);
ereport(ERROR,
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("column cannot have more than %d dimensions for ivfflat index", buildstate->typeInfo->maxDimensions)));
buildstate->reltuples = 0;
buildstate->indtuples = 0;
@@ -355,7 +351,9 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
/* Require more than one dimension for spherical k-means */
if (buildstate->kmeansnormprocinfo != NULL && buildstate->dimensions == 1)
elog(ERROR, "dimensions must be greater than one for this opclass");
ereport(ERROR,
(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
errmsg("dimensions must be greater than one for this opclass")));
/* Create tuple description for sorting */
buildstate->tupdesc = CreateTemplateTupleDesc(3);
@@ -562,6 +560,20 @@ PrintKmeansMetrics(IvfflatBuildState * buildstate)
}
#endif
/*
* Initialize build sort state
*/
static Tuplesortstate *
InitBuildSortState(TupleDesc tupdesc, int memory, SortCoordinate coordinate)
{
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Int4LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
return tuplesort_begin_heap(tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, memory, coordinate, false);
}
/*
* Within leader, wait for end of heap scan
*/
@@ -609,12 +621,6 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
double reltuples;
IndexInfo *indexInfo;
/* Sort options, which must match AssignTuples */
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Int4LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
/* Initialize local tuplesort coordination state */
coordinate = palloc0(sizeof(SortCoordinateData));
coordinate->isWorker = true;
@@ -627,7 +633,7 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
InitBuildState(&buildstate, ivfspool->heap, ivfspool->index, indexInfo);
memcpy(buildstate.centers->items, ivfcenters, buildstate.centers->itemsize * buildstate.centers->maxlen);
buildstate.centers->length = buildstate.centers->maxlen;
ivfspool->sortstate = tuplesort_begin_heap(buildstate.tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, sortmem, coordinate, false);
ivfspool->sortstate = InitBuildSortState(buildstate.tupdesc, sortmem, coordinate);
buildstate.sortstate = ivfspool->sortstate;
scan = table_beginscan_parallel(ivfspool->heap,
ParallelTableScanFromIvfflatShared(ivfshared));
@@ -924,12 +930,6 @@ AssignTuples(IvfflatBuildState * buildstate)
int parallel_workers = 0;
SortCoordinate coordinate = NULL;
/* Sort options, which must match IvfflatParallelScanAndSort */
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Int4LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_ASSIGN);
/* Calculate parallel workers */
@@ -950,7 +950,7 @@ AssignTuples(IvfflatBuildState * buildstate)
}
/* Begin serial/leader tuplesort */
buildstate->sortstate = tuplesort_begin_heap(buildstate->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, maintenance_work_mem, coordinate, false);
buildstate->sortstate = InitBuildSortState(buildstate->tupdesc, maintenance_work_mem, coordinate);
/* Add tuples to sort */
if (buildstate->heap != NULL)
@@ -1006,6 +1006,10 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo);
CreateEntryPages(buildstate, forkNum);
/* Write WAL for initialization fork since GenericXLog functions do not */
if (forkNum == INIT_FORKNUM)
log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true);
FreeBuildState(buildstate);
}

View File

@@ -7,6 +7,7 @@
#include "commands/progress.h"
#include "commands/vacuum.h"
#include "ivfflat.h"
#include "utils/float.h"
#include "utils/guc.h"
#include "utils/selfuncs.h"
#include "utils/spccache.h"
@@ -26,11 +27,7 @@ IvfflatInit(void)
{
ivfflat_relopt_kind = add_reloption_kind();
add_int_reloption(ivfflat_relopt_kind, "lists", "Number of inverted lists",
IVFFLAT_DEFAULT_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS
#if PG_VERSION_NUM >= 130000
,AccessExclusiveLock
#endif
);
IVFFLAT_DEFAULT_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, AccessExclusiveLock);
DefineCustomIntVariable("ivfflat.probes", "Sets the number of probes",
"Valid range is 1..lists.", &ivfflat_probes,
@@ -78,8 +75,8 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
/* Never use index without order */
if (path->indexorderbys == NULL)
{
*indexStartupCost = DBL_MAX;
*indexTotalCost = DBL_MAX;
*indexStartupCost = get_float8_infinity();
*indexTotalCost = get_float8_infinity();
*indexSelectivity = 0;
*indexCorrelation = 0;
*indexPages = 0;
@@ -123,13 +120,6 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
costs.indexTotalCost -= 0.5 * costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
}
/*
* If the list selectivity is lower than what is returned from the generic
* cost estimator, use that.
*/
if (ratio < costs.indexSelectivity)
costs.indexSelectivity = ratio;
/* Use total cost since most work happens before first tuple is returned */
*indexStartupCost = costs.indexTotalCost;
*indexTotalCost = costs.indexTotalCost;
@@ -148,23 +138,10 @@ ivfflatoptions(Datum reloptions, bool validate)
{"lists", RELOPT_TYPE_INT, offsetof(IvfflatOptions, lists)},
};
#if PG_VERSION_NUM >= 130000
return (bytea *) build_reloptions(reloptions, validate,
ivfflat_relopt_kind,
sizeof(IvfflatOptions),
tab, lengthof(tab));
#else
relopt_value *options;
int numoptions;
IvfflatOptions *rdopts;
options = parseRelOptions(reloptions, validate, ivfflat_relopt_kind, &numoptions);
rdopts = allocateReloptStruct(sizeof(IvfflatOptions), options, numoptions);
fillRelOptions((void *) rdopts, sizeof(IvfflatOptions), options, numoptions,
validate, tab, lengthof(tab));
return (bytea *) rdopts;
#endif
}
/*
@@ -181,7 +158,7 @@ ivfflatvalidate(Oid opclassoid)
*
* See https://www.postgresql.org/docs/current/index-api.html
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(ivfflathandler);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflathandler);
Datum
ivfflathandler(PG_FUNCTION_ARGS)
{
@@ -189,9 +166,7 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amstrategies = 0;
amroutine->amsupport = 5;
#if PG_VERSION_NUM >= 130000
amroutine->amoptsprocnum = 0;
#endif
amroutine->amcanorder = false;
amroutine->amcanorderbyop = true;
amroutine->amcanbackward = false; /* can change direction mid-scan */
@@ -204,17 +179,24 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amclusterable = false;
amroutine->ampredlocks = false;
amroutine->amcanparallel = false;
amroutine->amcaninclude = false;
#if PG_VERSION_NUM >= 130000
amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */
amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL;
#if PG_VERSION_NUM >= 170000
amroutine->amcanbuildparallel = true;
#endif
amroutine->amcaninclude = false;
amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */
#if PG_VERSION_NUM >= 160000
amroutine->amsummarizing = false;
#endif
amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL;
amroutine->amkeytype = InvalidOid;
/* Interface functions */
amroutine->ambuild = ivfflatbuild;
amroutine->ambuildempty = ivfflatbuildempty;
amroutine->aminsert = ivfflatinsert;
#if PG_VERSION_NUM >= 170000
amroutine->aminsertcleanup = NULL;
#endif
amroutine->ambulkdelete = ivfflatbulkdelete;
amroutine->amvacuumcleanup = ivfflatvacuumcleanup;
amroutine->amcanreturn = NULL; /* tuple not included in heapsort */

View File

@@ -253,8 +253,9 @@ typedef struct IvfflatScanOpaqueData
/* Sorting */
Tuplesortstate *sortstate;
TupleDesc tupdesc;
TupleTableSlot *slot;
bool isnull;
TupleTableSlot *vslot;
TupleTableSlot *mslot;
BufferAccessStrategy bas;
/* Support functions */
FmgrInfo *procinfo;

View File

@@ -94,6 +94,9 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
value = IvfflatNormValue(typeInfo, collation, value);
}
/* Ensure index is valid */
IvfflatGetMetaPageInfo(index, NULL, NULL);
/* Find the insert page - sets the page and list info */
FindInsertPage(index, values, &insertPage, &listInfo);
Assert(BlockNumberIsValid(insertPage));

View File

@@ -151,12 +151,8 @@ RandomCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeI
static void
ShowMemoryUsage(MemoryContext context, Size estimatedSize)
{
#if PG_VERSION_NUM >= 130000
elog(INFO, "total memory: %zu MB",
MemoryContextMemAllocated(context, true) / (1024 * 1024));
#else
MemoryContextStats(context);
#endif
elog(INFO, "estimated memory: %zu MB", estimatedSize / (1024 * 1024));
}
#endif
@@ -327,7 +323,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
newCenters->length = numCenters;
#ifdef IVFFLAT_MEMORY
ShowMemoryUsage(MemoryContextGetParent(CurrentMemoryContext));
ShowMemoryUsage(MemoryContextGetParent(CurrentMemoryContext), totalSize);
#endif
/* Pick initial centers */

View File

@@ -11,16 +11,23 @@
#include "pgstat.h"
#include "storage/bufmgr.h"
#ifdef IVFFLAT_MEMORY
#include "utils/memutils.h"
#endif
#define GetScanList(ptr) pairingheap_container(IvfflatScanList, ph_node, ptr)
#define GetScanListConst(ptr) pairingheap_const_container(IvfflatScanList, ph_node, ptr)
/*
* Compare list distances
*/
static int
CompareLists(const pairingheap_node *a, const pairingheap_node *b, void *arg)
{
if (((const IvfflatScanList *) a)->distance > ((const IvfflatScanList *) b)->distance)
if (GetScanListConst(a)->distance > GetScanListConst(b)->distance)
return 1;
if (((const IvfflatScanList *) a)->distance < ((const IvfflatScanList *) b)->distance)
if (GetScanListConst(a)->distance < GetScanListConst(b)->distance)
return -1;
return 0;
@@ -72,14 +79,14 @@ GetScanLists(IndexScanDesc scan, Datum value)
/* Calculate max distance */
if (listCount == so->probes)
maxDistance = ((IvfflatScanList *) pairingheap_first(so->listQueue))->distance;
maxDistance = GetScanList(pairingheap_first(so->listQueue))->distance;
}
else if (distance < maxDistance)
{
IvfflatScanList *scanlist;
/* Remove */
scanlist = (IvfflatScanList *) pairingheap_remove_first(so->listQueue);
scanlist = GetScanList(pairingheap_remove_first(so->listQueue));
/* Reuse */
scanlist->startPage = list->startPage;
@@ -87,7 +94,7 @@ GetScanLists(IndexScanDesc scan, Datum value)
pairingheap_add(so->listQueue, &scanlist->ph_node);
/* Update max distance */
maxDistance = ((IvfflatScanList *) pairingheap_first(so->listQueue))->distance;
maxDistance = GetScanList(pairingheap_first(so->listQueue))->distance;
}
}
@@ -106,19 +113,12 @@ GetScanItems(IndexScanDesc scan, Datum value)
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
TupleDesc tupdesc = RelationGetDescr(scan->indexRelation);
double tuples = 0;
TupleTableSlot *slot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsVirtual);
/*
* Reuse same set of shared buffers for scan
*
* See postgres/src/backend/storage/buffer/README for description
*/
BufferAccessStrategy bas = GetAccessStrategy(BAS_BULKREAD);
TupleTableSlot *slot = so->vslot;
/* Search closest probes lists */
while (!pairingheap_is_empty(so->listQueue))
{
BlockNumber searchPage = ((IvfflatScanList *) pairingheap_remove_first(so->listQueue))->startPage;
BlockNumber searchPage = GetScanList(pairingheap_remove_first(so->listQueue))->startPage;
/* Search all entry pages for list */
while (BlockNumberIsValid(searchPage))
@@ -127,7 +127,7 @@ GetScanItems(IndexScanDesc scan, Datum value)
Page page;
OffsetNumber maxoffno;
buf = ReadBufferExtended(scan->indexRelation, MAIN_FORKNUM, searchPage, RBM_NORMAL, bas);
buf = ReadBufferExtended(scan->indexRelation, MAIN_FORKNUM, searchPage, RBM_NORMAL, so->bas);
LockBuffer(buf, BUFFER_LOCK_SHARE);
page = BufferGetPage(buf);
maxoffno = PageGetMaxOffsetNumber(page);
@@ -166,8 +166,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
}
}
FreeAccessStrategy(bas);
if (tuples < 100)
ereport(DEBUG1,
(errmsg("index scan found few tuples"),
@@ -217,6 +215,20 @@ GetScanValue(IndexScanDesc scan)
return value;
}
/*
* Initialize scan sort state
*/
static Tuplesortstate *
InitScanSortState(TupleDesc tupdesc)
{
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Float8LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
return tuplesort_begin_heap(tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
}
/*
* Prepare for an index scan
*/
@@ -227,10 +239,6 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
IvfflatScanOpaque so;
int lists;
int dimensions;
AttrNumber attNums[] = {1};
Oid sortOperators[] = {Float8LessOperator};
Oid sortCollations[] = {InvalidOid};
bool nullsFirstFlags[] = {false};
int probes = ivfflat_probes;
scan = RelationGetIndexScan(index, nkeys, norderbys);
@@ -258,9 +266,18 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
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);
so->sortstate = InitScanSortState(so->tupdesc);
so->slot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsMinimalTuple);
/* Need separate slots for puttuple and gettuple */
so->vslot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsVirtual);
so->mslot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsMinimalTuple);
/*
* Reuse same set of shared buffers for scan
*
* See postgres/src/backend/storage/buffer/README for description
*/
so->bas = GetAccessStrategy(BAS_BULKREAD);
so->listQueue = pairingheap_allocate(CompareLists, scan);
@@ -277,10 +294,8 @@ ivfflatrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int
{
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
#if PG_VERSION_NUM >= 130000
if (!so->first)
tuplesort_reset(so->sortstate);
#endif
so->first = true;
pairingheap_reset(so->listQueue);
@@ -327,14 +342,19 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
IvfflatBench("GetScanItems", GetScanItems(scan, value));
so->first = false;
#if defined(IVFFLAT_MEMORY)
elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(CurrentMemoryContext, true) / (1024 * 1024));
#endif
/* Clean up if we allocated a new value */
if (value != scan->orderByData->sk_argument)
pfree(DatumGetPointer(value));
}
if (tuplesort_gettupleslot(so->sortstate, true, false, so->slot, NULL))
if (tuplesort_gettupleslot(so->sortstate, true, false, so->mslot, NULL))
{
ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
bool isnull;
ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->mslot, 2, &isnull));
scan->xs_heaptid = *heaptid;
scan->xs_recheck = false;
@@ -355,6 +375,10 @@ ivfflatendscan(IndexScanDesc scan)
pairingheap_free(so->listQueue);
tuplesort_end(so->sortstate);
FreeAccessStrategy(so->bas);
FreeTupleDesc(so->tupdesc);
/* TODO Free vslot and mslot without freeing TupleDesc */
pfree(so);
scan->opaque = NULL;

View File

@@ -170,7 +170,11 @@ IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions)
page = BufferGetPage(buf);
metap = IvfflatPageGetMeta(page);
*lists = metap->lists;
if (unlikely(metap->magicNumber != IVFFLAT_MAGIC_NUMBER))
elog(ERROR, "ivfflat index is not valid");
if (lists != NULL)
*lists = metap->lists;
if (dimensions != NULL)
*dimensions = metap->dimensions;
@@ -338,7 +342,7 @@ IvfflatGetTypeInfo(Relation index)
return (const IvfflatTypeInfo *) DatumGetPointer(FunctionCall0Coll(procinfo, InvalidOid));
}
PGDLLEXPORT PG_FUNCTION_INFO_V1(ivfflat_halfvec_support);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_halfvec_support);
Datum
ivfflat_halfvec_support(PG_FUNCTION_ARGS)
{
@@ -353,7 +357,7 @@ ivfflat_halfvec_support(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(&typeInfo);
};
PGDLLEXPORT PG_FUNCTION_INFO_V1(ivfflat_bit_support);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_bit_support);
Datum
ivfflat_bit_support(PG_FUNCTION_ARGS)
{

View File

@@ -3,6 +3,7 @@
#include <limits.h>
#include <math.h>
#include "catalog/pg_type.h"
#include "common/string.h"
#include "fmgr.h"
#include "halfutils.h"
@@ -11,6 +12,7 @@
#include "sparsevec.h"
#include "utils/array.h"
#include "utils/builtins.h"
#include "utils/lsyscache.h"
#include "vector.h"
#if PG_VERSION_NUM >= 120000
@@ -188,7 +190,7 @@ CompareIndices(const void *a, const void *b)
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_in);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_in);
Datum
sparsevec_in(PG_FUNCTION_ARGS)
{
@@ -409,7 +411,7 @@ sparsevec_in(PG_FUNCTION_ARGS)
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_out);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_out);
Datum
sparsevec_out(PG_FUNCTION_ARGS)
{
@@ -462,7 +464,7 @@ sparsevec_out(PG_FUNCTION_ARGS)
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_typmod_in);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_typmod_in);
Datum
sparsevec_typmod_in(PG_FUNCTION_ARGS)
{
@@ -493,7 +495,7 @@ sparsevec_typmod_in(PG_FUNCTION_ARGS)
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_recv);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_recv);
Datum
sparsevec_recv(PG_FUNCTION_ARGS)
{
@@ -545,7 +547,7 @@ sparsevec_recv(PG_FUNCTION_ARGS)
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_send);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_send);
Datum
sparsevec_send(PG_FUNCTION_ARGS)
{
@@ -572,7 +574,7 @@ sparsevec_send(PG_FUNCTION_ARGS)
* Convert sparse vector to sparse vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec);
Datum
sparsevec(PG_FUNCTION_ARGS)
{
@@ -587,7 +589,7 @@ sparsevec(PG_FUNCTION_ARGS)
/*
* Convert dense vector to sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_sparsevec);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_to_sparsevec);
Datum
vector_to_sparsevec(PG_FUNCTION_ARGS)
{
@@ -630,7 +632,7 @@ vector_to_sparsevec(PG_FUNCTION_ARGS)
/*
* Convert half vector to sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_to_sparsevec);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_to_sparsevec);
Datum
halfvec_to_sparsevec(PG_FUNCTION_ARGS)
{
@@ -670,6 +672,137 @@ halfvec_to_sparsevec(PG_FUNCTION_ARGS)
PG_RETURN_POINTER(result);
}
/*
* Convert array to sparse vector
*/
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(array_to_sparsevec);
Datum
array_to_sparsevec(PG_FUNCTION_ARGS)
{
ArrayType *array = PG_GETARG_ARRAYTYPE_P(0);
int32 typmod = PG_GETARG_INT32(1);
SparseVector *result;
int16 typlen;
bool typbyval;
char typalign;
Datum *elemsp;
int nelemsp;
int nnz = 0;
float *values;
int j = 0;
if (ARR_NDIM(array) > 1)
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("array must be 1-D")));
if (ARR_HASNULL(array) && array_contains_nulls(array))
ereport(ERROR,
(errcode(ERRCODE_NULL_VALUE_NOT_ALLOWED),
errmsg("array must not contain nulls")));
get_typlenbyvalalign(ARR_ELEMTYPE(array), &typlen, &typbyval, &typalign);
deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, NULL, &nelemsp);
CheckDim(nelemsp);
CheckExpectedDim(typmod, nelemsp);
#ifdef _MSC_VER
/* /fp:fast may not propagate +/-Infinity or NaN */
#define IS_NOT_ZERO(v) (isnan((float) (v)) || isinf((float) (v)) || ((float) (v)) != 0)
#else
#define IS_NOT_ZERO(v) (((float) (v)) != 0)
#endif
if (ARR_ELEMTYPE(array) == INT4OID)
{
for (int i = 0; i < nelemsp; i++)
nnz += IS_NOT_ZERO(DatumGetInt32(elemsp[i]));
}
else if (ARR_ELEMTYPE(array) == FLOAT8OID)
{
for (int i = 0; i < nelemsp; i++)
nnz += IS_NOT_ZERO(DatumGetFloat8(elemsp[i]));
}
else if (ARR_ELEMTYPE(array) == FLOAT4OID)
{
for (int i = 0; i < nelemsp; i++)
nnz += IS_NOT_ZERO(DatumGetFloat4(elemsp[i]));
}
else if (ARR_ELEMTYPE(array) == NUMERICOID)
{
for (int i = 0; i < nelemsp; i++)
nnz += IS_NOT_ZERO(DirectFunctionCall1(numeric_float4, elemsp[i]));
}
else
{
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("unsupported array type")));
}
result = InitSparseVector(nelemsp, nnz);
values = SPARSEVEC_VALUES(result);
#define PROCESS_ARRAY_ELEM(elem) \
do { \
float v = (float) (elem); \
if (IS_NOT_ZERO(v)) { \
/* Safety check */ \
if (j >= result->nnz) \
elog(ERROR, "safety check failed"); \
result->indices[j] = i; \
values[j] = v; \
j++; \
} \
} while (0)
if (ARR_ELEMTYPE(array) == INT4OID)
{
for (int i = 0; i < nelemsp; i++)
PROCESS_ARRAY_ELEM(DatumGetInt32(elemsp[i]));
}
else if (ARR_ELEMTYPE(array) == FLOAT8OID)
{
for (int i = 0; i < nelemsp; i++)
PROCESS_ARRAY_ELEM(DatumGetFloat8(elemsp[i]));
}
else if (ARR_ELEMTYPE(array) == FLOAT4OID)
{
for (int i = 0; i < nelemsp; i++)
PROCESS_ARRAY_ELEM(DatumGetFloat4(elemsp[i]));
}
else if (ARR_ELEMTYPE(array) == NUMERICOID)
{
for (int i = 0; i < nelemsp; i++)
PROCESS_ARRAY_ELEM(DatumGetFloat4(DirectFunctionCall1(numeric_float4, elemsp[i])));
}
else
{
ereport(ERROR,
(errcode(ERRCODE_DATA_EXCEPTION),
errmsg("unsupported array type")));
}
#undef PROCESS_ARRAY_ELEM
#undef IS_NOT_ZERO
/*
* Free allocation from deconstruct_array. Do not free individual elements
* when pass-by-reference since they point to original array.
*/
pfree(elemsp);
if (j != result->nnz)
elog(ERROR, "correctness check failed");
/* Check elements */
for (int i = 0; i < result->nnz; i++)
CheckElement(values[i]);
PG_RETURN_POINTER(result);
}
/*
* Get the L2 squared distance between sparse vectors
*/
@@ -721,7 +854,7 @@ SparsevecL2SquaredDistance(SparseVector * a, SparseVector * b)
/*
* Get the L2 distance between sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l2_distance);
Datum
sparsevec_l2_distance(PG_FUNCTION_ARGS)
{
@@ -737,7 +870,7 @@ sparsevec_l2_distance(PG_FUNCTION_ARGS)
* Get the L2 squared distance between sparse vectors
* This saves a sqrt calculation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_squared_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l2_squared_distance);
Datum
sparsevec_l2_squared_distance(PG_FUNCTION_ARGS)
{
@@ -788,7 +921,7 @@ SparsevecInnerProduct(SparseVector * a, SparseVector * b)
/*
* Get the inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_inner_product);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_inner_product);
Datum
sparsevec_inner_product(PG_FUNCTION_ARGS)
{
@@ -803,7 +936,7 @@ sparsevec_inner_product(PG_FUNCTION_ARGS)
/*
* Get the negative inner product of two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_negative_inner_product);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_negative_inner_product);
Datum
sparsevec_negative_inner_product(PG_FUNCTION_ARGS)
{
@@ -818,7 +951,7 @@ sparsevec_negative_inner_product(PG_FUNCTION_ARGS)
/*
* Get the cosine distance between two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_cosine_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_cosine_distance);
Datum
sparsevec_cosine_distance(PG_FUNCTION_ARGS)
{
@@ -863,7 +996,7 @@ sparsevec_cosine_distance(PG_FUNCTION_ARGS)
/*
* Get the L1 distance between two sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l1_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l1_distance);
Datum
sparsevec_l1_distance(PG_FUNCTION_ARGS)
{
@@ -912,7 +1045,7 @@ sparsevec_l1_distance(PG_FUNCTION_ARGS)
/*
* Get the L2 norm of a sparse vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_norm);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l2_norm);
Datum
sparsevec_l2_norm(PG_FUNCTION_ARGS)
{
@@ -930,7 +1063,7 @@ sparsevec_l2_norm(PG_FUNCTION_ARGS)
/*
* Normalize a sparse vector with the L2 norm
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_normalize);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l2_normalize);
Datum
sparsevec_l2_normalize(PG_FUNCTION_ARGS)
{
@@ -1040,7 +1173,7 @@ sparsevec_cmp_internal(SparseVector * a, SparseVector * b)
/*
* Less than
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_lt);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_lt);
Datum
sparsevec_lt(PG_FUNCTION_ARGS)
{
@@ -1053,7 +1186,7 @@ sparsevec_lt(PG_FUNCTION_ARGS)
/*
* Less than or equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_le);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_le);
Datum
sparsevec_le(PG_FUNCTION_ARGS)
{
@@ -1066,7 +1199,7 @@ sparsevec_le(PG_FUNCTION_ARGS)
/*
* Equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_eq);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_eq);
Datum
sparsevec_eq(PG_FUNCTION_ARGS)
{
@@ -1079,7 +1212,7 @@ sparsevec_eq(PG_FUNCTION_ARGS)
/*
* Not equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_ne);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_ne);
Datum
sparsevec_ne(PG_FUNCTION_ARGS)
{
@@ -1092,7 +1225,7 @@ sparsevec_ne(PG_FUNCTION_ARGS)
/*
* Greater than or equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_ge);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_ge);
Datum
sparsevec_ge(PG_FUNCTION_ARGS)
{
@@ -1105,7 +1238,7 @@ sparsevec_ge(PG_FUNCTION_ARGS)
/*
* Greater than
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_gt);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_gt);
Datum
sparsevec_gt(PG_FUNCTION_ARGS)
{
@@ -1118,7 +1251,7 @@ sparsevec_gt(PG_FUNCTION_ARGS)
/*
* Compare sparse vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_cmp);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_cmp);
Datum
sparsevec_cmp(PG_FUNCTION_ARGS)
{

View File

@@ -26,11 +26,6 @@
#include "varatt.h"
#endif
#if PG_VERSION_NUM < 130000
#define TYPALIGN_DOUBLE 'd'
#define TYPALIGN_INT 'i'
#endif
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
@@ -160,28 +155,10 @@ CheckStateArray(ArrayType *statearray, const char *caller)
return (float8 *) ARR_DATA_PTR(statearray);
}
#if PG_VERSION_NUM < 120003
static pg_noinline void
float_overflow_error(void)
{
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("value out of range: overflow")));
}
static pg_noinline void
float_underflow_error(void)
{
ereport(ERROR,
(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
errmsg("value out of range: underflow")));
}
#endif
/*
* Convert textual representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_in);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_in);
Datum
vector_in(PG_FUNCTION_ARGS)
{
@@ -294,7 +271,7 @@ vector_in(PG_FUNCTION_ARGS)
/*
* Convert internal representation to textual representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_out);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_out);
Datum
vector_out(PG_FUNCTION_ARGS)
{
@@ -348,7 +325,7 @@ PrintVector(char *msg, Vector * vector)
/*
* Convert type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_typmod_in);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_typmod_in);
Datum
vector_typmod_in(PG_FUNCTION_ARGS)
{
@@ -379,7 +356,7 @@ vector_typmod_in(PG_FUNCTION_ARGS)
/*
* Convert external binary representation to internal representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_recv);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_recv);
Datum
vector_recv(PG_FUNCTION_ARGS)
{
@@ -413,7 +390,7 @@ vector_recv(PG_FUNCTION_ARGS)
/*
* Convert internal representation to the external binary representation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_send);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_send);
Datum
vector_send(PG_FUNCTION_ARGS)
{
@@ -433,7 +410,7 @@ vector_send(PG_FUNCTION_ARGS)
* Convert vector to vector
* This is needed to check the type modifier
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector);
Datum
vector(PG_FUNCTION_ARGS)
{
@@ -448,7 +425,7 @@ vector(PG_FUNCTION_ARGS)
/*
* Convert array to vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(array_to_vector);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(array_to_vector);
Datum
array_to_vector(PG_FUNCTION_ARGS)
{
@@ -522,7 +499,7 @@ array_to_vector(PG_FUNCTION_ARGS)
/*
* Convert vector to float4[]
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_float4);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_to_float4);
Datum
vector_to_float4(PG_FUNCTION_ARGS)
{
@@ -546,7 +523,7 @@ vector_to_float4(PG_FUNCTION_ARGS)
/*
* Convert half vector to vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_to_vector);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_to_vector);
Datum
halfvec_to_vector(PG_FUNCTION_ARGS)
{
@@ -584,7 +561,7 @@ VectorL2SquaredDistance(int dim, float *ax, float *bx)
/*
* Get the L2 distance between vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(l2_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l2_distance);
Datum
l2_distance(PG_FUNCTION_ARGS)
{
@@ -600,7 +577,7 @@ l2_distance(PG_FUNCTION_ARGS)
* Get the L2 squared distance between vectors
* This saves a sqrt calculation
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_l2_squared_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_l2_squared_distance);
Datum
vector_l2_squared_distance(PG_FUNCTION_ARGS)
{
@@ -627,7 +604,7 @@ VectorInnerProduct(int dim, float *ax, float *bx)
/*
* Get the inner product of two vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(inner_product);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(inner_product);
Datum
inner_product(PG_FUNCTION_ARGS)
{
@@ -642,7 +619,7 @@ inner_product(PG_FUNCTION_ARGS)
/*
* Get the negative inner product of two vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_negative_inner_product);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_negative_inner_product);
Datum
vector_negative_inner_product(PG_FUNCTION_ARGS)
{
@@ -676,7 +653,7 @@ VectorCosineSimilarity(int dim, float *ax, float *bx)
/*
* Get the cosine distance between two vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(cosine_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(cosine_distance);
Datum
cosine_distance(PG_FUNCTION_ARGS)
{
@@ -708,7 +685,7 @@ cosine_distance(PG_FUNCTION_ARGS)
* Currently uses angular distance since needs to satisfy triangle inequality
* Assumes inputs are unit vectors (skips norm)
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_spherical_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_spherical_distance);
Datum
vector_spherical_distance(PG_FUNCTION_ARGS)
{
@@ -745,7 +722,7 @@ VectorL1Distance(int dim, float *ax, float *bx)
/*
* Get the L1 distance between two vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(l1_distance);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l1_distance);
Datum
l1_distance(PG_FUNCTION_ARGS)
{
@@ -760,7 +737,7 @@ l1_distance(PG_FUNCTION_ARGS)
/*
* Get the dimensions of a vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_dims);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_dims);
Datum
vector_dims(PG_FUNCTION_ARGS)
{
@@ -772,7 +749,7 @@ vector_dims(PG_FUNCTION_ARGS)
/*
* Get the L2 norm of a vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_norm);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_norm);
Datum
vector_norm(PG_FUNCTION_ARGS)
{
@@ -790,7 +767,7 @@ vector_norm(PG_FUNCTION_ARGS)
/*
* Normalize a vector with the L2 norm
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(l2_normalize);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l2_normalize);
Datum
l2_normalize(PG_FUNCTION_ARGS)
{
@@ -829,7 +806,7 @@ l2_normalize(PG_FUNCTION_ARGS)
/*
* Add vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_add);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_add);
Datum
vector_add(PG_FUNCTION_ARGS)
{
@@ -862,7 +839,7 @@ vector_add(PG_FUNCTION_ARGS)
/*
* Subtract vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_sub);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_sub);
Datum
vector_sub(PG_FUNCTION_ARGS)
{
@@ -895,7 +872,7 @@ vector_sub(PG_FUNCTION_ARGS)
/*
* Multiply vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_mul);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_mul);
Datum
vector_mul(PG_FUNCTION_ARGS)
{
@@ -931,7 +908,7 @@ vector_mul(PG_FUNCTION_ARGS)
/*
* Concatenate vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_concat);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_concat);
Datum
vector_concat(PG_FUNCTION_ARGS)
{
@@ -955,7 +932,7 @@ vector_concat(PG_FUNCTION_ARGS)
/*
* Quantize a vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(binary_quantize);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(binary_quantize);
Datum
binary_quantize(PG_FUNCTION_ARGS)
{
@@ -973,7 +950,7 @@ binary_quantize(PG_FUNCTION_ARGS)
/*
* Get a subvector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(subvector);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(subvector);
Datum
subvector(PG_FUNCTION_ARGS)
{
@@ -1047,7 +1024,7 @@ vector_cmp_internal(Vector * a, Vector * b)
/*
* Less than
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_lt);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_lt);
Datum
vector_lt(PG_FUNCTION_ARGS)
{
@@ -1060,7 +1037,7 @@ vector_lt(PG_FUNCTION_ARGS)
/*
* Less than or equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_le);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_le);
Datum
vector_le(PG_FUNCTION_ARGS)
{
@@ -1073,7 +1050,7 @@ vector_le(PG_FUNCTION_ARGS)
/*
* Equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_eq);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_eq);
Datum
vector_eq(PG_FUNCTION_ARGS)
{
@@ -1086,7 +1063,7 @@ vector_eq(PG_FUNCTION_ARGS)
/*
* Not equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_ne);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_ne);
Datum
vector_ne(PG_FUNCTION_ARGS)
{
@@ -1099,7 +1076,7 @@ vector_ne(PG_FUNCTION_ARGS)
/*
* Greater than or equal
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_ge);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_ge);
Datum
vector_ge(PG_FUNCTION_ARGS)
{
@@ -1112,7 +1089,7 @@ vector_ge(PG_FUNCTION_ARGS)
/*
* Greater than
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_gt);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_gt);
Datum
vector_gt(PG_FUNCTION_ARGS)
{
@@ -1125,7 +1102,7 @@ vector_gt(PG_FUNCTION_ARGS)
/*
* Compare vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_cmp);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_cmp);
Datum
vector_cmp(PG_FUNCTION_ARGS)
{
@@ -1138,7 +1115,7 @@ vector_cmp(PG_FUNCTION_ARGS)
/*
* Accumulate vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_accum);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_accum);
Datum
vector_accum(PG_FUNCTION_ARGS)
{
@@ -1199,7 +1176,7 @@ vector_accum(PG_FUNCTION_ARGS)
/*
* Combine vectors or half vectors (also used for halfvec_combine)
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_combine);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_combine);
Datum
vector_combine(PG_FUNCTION_ARGS)
{
@@ -1270,7 +1247,7 @@ vector_combine(PG_FUNCTION_ARGS)
/*
* Average vectors
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_avg);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_avg);
Datum
vector_avg(PG_FUNCTION_ARGS)
{
@@ -1304,7 +1281,7 @@ vector_avg(PG_FUNCTION_ARGS)
/*
* Convert sparse vector to dense vector
*/
PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_to_vector);
FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_to_vector);
Datum
sparsevec_to_vector(PG_FUNCTION_ARGS)
{

View File

@@ -20,4 +20,11 @@ Vector *InitVector(int dim);
void PrintVector(char *msg, Vector * vector);
int vector_cmp_internal(Vector * a, Vector * b);
/* TODO Move to better place */
#if PG_VERSION_NUM >= 160000
#define FUNCTION_PREFIX
#else
#define FUNCTION_PREFIX PGDLLEXPORT
#endif
#endif

View File

@@ -208,6 +208,62 @@ SELECT '{1:1e-8}/1'::sparsevec::halfvec;
[0]
(1 row)
SELECT ARRAY[1,0,2,0,3,0]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT ARRAY[1.0,0.0,2.0,0.0,3.0,0.0]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT ARRAY[1,0,2,0,3,0]::float4[]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT ARRAY[1,0,2,0,3,0]::float8[]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT ARRAY[1,0,2,0,3,0]::numeric[]::sparsevec;
array
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec;
sparsevec
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(6);
sparsevec
-----------------
{1:1,3:2,5:3}/6
(1 row)
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(5);
ERROR: expected 5 dimensions, not 6
SELECT '{NULL}'::real[]::sparsevec;
ERROR: array must not contain nulls
SELECT '{NaN}'::real[]::sparsevec;
ERROR: NaN not allowed in sparsevec
SELECT '{Infinity}'::real[]::sparsevec;
ERROR: infinite value not allowed in sparsevec
SELECT '{-Infinity}'::real[]::sparsevec;
ERROR: infinite value not allowed in sparsevec
SELECT '{}'::real[]::sparsevec;
ERROR: sparsevec must have at least 1 dimension
SELECT '{{1}}'::real[]::sparsevec;
ERROR: array must be 1-D
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
ERROR: vector cannot have more than 16000 dimensions
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;

View File

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

View File

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

View File

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

View File

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

View File

@@ -58,6 +58,22 @@ SELECT '{}/16001'::sparsevec::halfvec;
SELECT '{1:65520}/1'::sparsevec::halfvec;
SELECT '{1:1e-8}/1'::sparsevec::halfvec;
SELECT ARRAY[1,0,2,0,3,0]::sparsevec;
SELECT ARRAY[1.0,0.0,2.0,0.0,3.0,0.0]::sparsevec;
SELECT ARRAY[1,0,2,0,3,0]::float4[]::sparsevec;
SELECT ARRAY[1,0,2,0,3,0]::float8[]::sparsevec;
SELECT ARRAY[1,0,2,0,3,0]::numeric[]::sparsevec;
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec;
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(6);
SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(5);
SELECT '{NULL}'::real[]::sparsevec;
SELECT '{NaN}'::real[]::sparsevec;
SELECT '{Infinity}'::real[]::sparsevec;
SELECT '{-Infinity}'::real[]::sparsevec;
SELECT '{}'::real[]::sparsevec;
SELECT '{{1}}'::real[]::sparsevec;
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;

View File

@@ -2,9 +2,9 @@
# Test generic xlog record work for ivfflat index replication.
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 32;
@@ -49,7 +49,7 @@ sub test_index_replay
my $array_sql = join(",", ('random()') x $dim);
# Initialize primary node
$node_primary = get_new_node('primary');
$node_primary = PostgreSQL::Test::Cluster->new('primary');
$node_primary->init(allows_streaming => 1);
if ($dim > 32)
{
@@ -67,7 +67,7 @@ my $backup_name = 'my_backup';
$node_primary->backup($backup_name);
# Create streaming replica linking to primary
$node_replica = get_new_node('replica');
$node_replica = PostgreSQL::Test::Cluster->new('replica');
$node_replica->init_from_backup($node_primary, $backup_name, has_streaming => 1);
$node_replica->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 3;
@@ -15,7 +15,7 @@ for (1 .. $dim)
my $array_sql = join(", ", @r);
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -49,7 +49,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -48,7 +48,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 768;
@@ -9,7 +9,7 @@ my $dim = 768;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 3;
@@ -11,7 +11,7 @@ my $limit = 20;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
@@ -94,8 +94,7 @@ like($explain, qr/Seq Scan/);
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' < 1 ORDER BY v <-> '$query';
));
# TODO Do not use index
like($explain, qr/Index Scan using idx/);
like($explain, qr/Seq Scan/);
# Test attribute index
$node->safe_psql("postgres", "CREATE INDEX attribute_idx ON tst (c);");
@@ -110,7 +109,6 @@ $node->safe_psql("postgres", "CREATE INDEX partial_idx ON tst USING ivfflat (v v
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit;
));
# TODO Use partial index
like($explain, qr/Index Scan using idx/);
like($explain, qr/Index Scan using partial_idx/);
done_testing();

View File

@@ -2,9 +2,9 @@
# Test generic xlog record work for hnsw index replication.
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 32;
@@ -49,7 +49,7 @@ sub test_index_replay
my $array_sql = join(",", ('random()') x $dim);
# Initialize primary node
$node_primary = get_new_node('primary');
$node_primary = PostgreSQL::Test::Cluster->new('primary');
$node_primary->init(allows_streaming => 1);
if ($dim > 32)
{
@@ -67,7 +67,7 @@ my $backup_name = 'my_backup';
$node_primary->backup($backup_name);
# Create streaming replica linking to primary
$node_replica = get_new_node('replica');
$node_replica = PostgreSQL::Test::Cluster->new('replica');
$node_replica->init_from_backup($node_primary, $backup_name, has_streaming => 1);
$node_replica->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 3;
@@ -15,7 +15,7 @@ for (1 .. $dim)
my $array_sql = join(", ", @r);
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -47,7 +47,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -47,7 +47,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -48,7 +48,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Ensures elements and neighbors on both same and different pages
@@ -10,7 +10,7 @@ my $dim = 1900;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 3;
@@ -11,16 +11,20 @@ my $limit = 20;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
# Create table and index
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim), c int4, t text);");
$node->safe_psql("postgres", "CREATE TABLE cat (i int4 PRIMARY KEY, t text, b boolean);");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql], i % $nc, 'test ' || i FROM generate_series(1, 10000) i;"
);
$node->safe_psql("postgres",
"INSERT INTO cat SELECT i, 'cat ' || i, i % 5 = 0 FROM generate_series(1, $nc) i;"
);
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v vector_l2_ops);");
$node->safe_psql("postgres", "ANALYZE tst;");
@@ -96,13 +100,25 @@ $explain = $node->safe_psql("postgres", qq(
));
like($explain, qr/Seq Scan/);
# Test join
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT cat.t FROM cat INNER JOIN tst ON cat.i = tst.c ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
# Test join with attribute filtering
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT cat.t FROM cat INNER JOIN tst ON cat.i = tst.c WHERE cat.b = 't' ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
# Test attribute index
$node->safe_psql("postgres", "CREATE INDEX attribute_idx ON tst (c);");
$explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit;
));
# TODO Use attribute index
like($explain, qr/Index Scan using idx/);
# Use attribute index
like($explain, qr/Bitmap Index Scan on attribute_idx/);
# Test partial index
$node->safe_psql("postgres", "CREATE INDEX partial_idx ON tst USING hnsw (v vector_l2_ops) WHERE (c = $c);");

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
@@ -53,7 +53,7 @@ sub test_aggregate
else
{
# Does not raise overflow error in this instance due to loss of precision
is($res, "[24576,24576,49152]")
is($res, "[24576,24576,49152]");
}
}

View File

@@ -1,13 +1,13 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 1024;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -51,7 +51,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -51,7 +51,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -51,7 +51,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -48,7 +48,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -48,7 +48,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -48,7 +48,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -47,7 +47,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -47,7 +47,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -48,7 +48,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -51,7 +51,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,14 +1,14 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
my $array_sql = join(",", ('floor(random() * 2)::int - 1') x 3);
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -10,7 +10,7 @@ my $dim = 5;
my $array_sql = join(",", ('floor(random() * 4)::int - 2') x $dim);
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,7 +1,7 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
@@ -51,7 +51,7 @@ sub test_recall
}
# Initialize node
$node = get_new_node('node');
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -1,11 +1,11 @@
use strict;
use warnings;
use PostgresNode;
use TestLib;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = get_new_node('node');
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;

View File

@@ -0,0 +1,42 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
# Initialize node
my $node = PostgreSQL::Test::Cluster->new('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 sparsevec(100000));");
$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v sparsevec_l2_ops);");
for (1 .. 3)
{
for (1 .. 100)
{
my @elements;
my %indices;
for (1 .. int(rand() * 100))
{
my $index = int(rand() * (100000 - 1)) + 1;
if (!exists($indices{$index}))
{
my $value = rand();
push(@elements, "$index:$value");
$indices{$index} = 1;
}
}
my $embedding = "{" . join(",", @elements) . "}/100000";
$node->safe_psql("postgres", "INSERT INTO tst (v) VALUES ('$embedding');");
}
$node->safe_psql("postgres", "DELETE FROM tst WHERE i % 2 = 0;");
$node->safe_psql("postgres", "VACUUM tst;");
is(1, 1);
}
done_testing();

46
test/t/039_hnsw_cost.pl Normal file
View File

@@ -0,0 +1,46 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my @dims = (384, 1536);
my $limit = 10;
# Initialize node
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
for my $dim (@dims)
{
my $array_sql = join(",", ('random()') x $dim);
my $n = $dim == 384 ? 2000 : 1000;
# Create table and index
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, $n) i;"
);
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v vector_l2_ops);");
$node->safe_psql("postgres", "ANALYZE tst;");
# Generate query
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
my $query = "[" . join(",", @r) . "]";
my $explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
$node->safe_psql("postgres", "DROP TABLE tst;");
}
done_testing();

View File

@@ -0,0 +1,45 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my @dims = (384, 1536);
my $limit = 10;
# Initialize node
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
for my $dim (@dims)
{
my $array_sql = join(",", ('random()') x $dim);
# Create table and index
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 5000) i;"
);
$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING ivfflat (v vector_l2_ops) WITH (lists = 5);");
$node->safe_psql("postgres", "ANALYZE tst;");
# Generate query
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
my $query = "[" . join(",", @r) . "]";
my $explain = $node->safe_psql("postgres", qq(
EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v <-> '$query' LIMIT $limit;
));
like($explain, qr/Index Scan using idx/);
$node->safe_psql("postgres", "DROP TABLE tst;");
}
done_testing();

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@@ -0,0 +1,66 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $dim = 3;
my $array_sql = join(",", ('random()') x $dim);
# Initialize node
my $node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4 PRIMARY KEY, v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
);
$node->safe_psql("postgres", qq(
SET maintenance_work_mem = '128MB';
SET max_parallel_maintenance_workers = 2;
CREATE INDEX ON tst USING hnsw (v vector_l2_ops)
));
my $count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.streaming = on;
SET work_mem = '8MB';
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
));
is($count, 10);
foreach ((30000, 50000, 70000))
{
my $ef_stream = $_;
my $expected = $ef_stream / 10000;
my $sum = 0;
for my $i (1 .. 20)
{
$count = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.streaming = on;
SET hnsw.ef_stream = $ef_stream;
SET work_mem = '8MB';
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst WHERE i = $i) LIMIT 11) t;
));
$sum += $count;
}
my $avg = $sum / 20;
cmp_ok($avg, '>', $expected - 2);
cmp_ok($avg, '<', $expected + 2);
}
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.streaming = on;
SET work_mem = '2MB';
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
));
like($stderr, qr/hnsw index scan exceeded work_mem after \d+ tuples/);
done_testing();

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@@ -0,0 +1,131 @@
use strict;
use warnings FATAL => 'all';
use PostgreSQL::Test::Cluster;
use PostgreSQL::Test::Utils;
use Test::More;
my $node;
my @queries = ();
my @expected;
my $limit = 20;
my $dim = 3;
my $array_sql = join(",", ('random()') x $dim);
my @cs = (100, 1000);
sub test_recall
{
my ($c, $ef_search, $min, $operator) = @_;
my $correct = 0;
my $total = 0;
my $explain = $node->safe_psql("postgres", qq(
SET enable_seqscan = off;
SET hnsw.ef_search = $ef_search;
SET hnsw.streaming = on;
EXPLAIN ANALYZE SELECT i FROM tst WHERE i % $c = 0 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 hnsw.ef_search = $ef_search;
SET hnsw.streaming = on;
SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[$i]' LIMIT $limit;
));
my @actual_ids = split("\n", $actual);
my @expected_ids = split("\n", $expected[$i]);
my %expected_set = map { $_ => 1 } @expected_ids;
foreach (@actual_ids)
{
if (exists($expected_set{$_}))
{
$correct++;
}
}
$total += $limit;
}
cmp_ok($correct / $total, ">=", $min, $operator);
}
# Initialize node
$node = PostgreSQL::Test::Cluster->new('node');
$node->init;
$node->start;
# Create table
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
$node->safe_psql("postgres",
"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
);
# Generate queries
for (1 .. 20)
{
my @r = ();
for (1 .. $dim)
{
push(@r, rand());
}
push(@queries, "[" . join(",", @r) . "]");
}
# Check each index type
my @operators = ("<->", "<=>");
my @opclasses = ("vector_l2_ops", "vector_cosine_ops");
for my $i (0 .. $#operators)
{
my $operator = $operators[$i];
my $opclass = $opclasses[$i];
$node->safe_psql("postgres", qq(
SET maintenance_work_mem = '128MB';
CREATE INDEX idx ON tst USING hnsw (v $opclass);
));
foreach (@cs)
{
my $c = $_;
# Get exact results
@expected = ();
foreach (@queries)
{
my $res = $node->safe_psql("postgres", qq(
SET enable_indexscan = off;
WITH top AS (
SELECT v $operator '$_' AS distance FROM tst WHERE i % $c = 0 ORDER BY distance LIMIT $limit
)
SELECT i FROM tst WHERE (v $operator '$_') <= (SELECT MAX(distance) FROM top)
));
push(@expected, $res);
}
if ($c == 100)
{
test_recall($c, 40, 0.99, $operator);
}
else
{
if ($operator eq "<->")
{
test_recall($c, 40, 0.99, $operator);
}
else
{
test_recall($c, 40, 0.99, $operator);
}
}
}
$node->safe_psql("postgres", "DROP INDEX idx;");
}
done_testing();

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@@ -1,4 +1,4 @@
comment = 'vector data type and ivfflat and hnsw access methods'
default_version = '0.7.1'
default_version = '0.7.4'
module_pathname = '$libdir/vector'
relocatable = true