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Author SHA1 Message Date
Andrew Kane
42c930231a Test with ARM on CI 2025-01-19 01:29:28 -08:00
11 changed files with 71 additions and 202 deletions

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@@ -8,18 +8,10 @@ jobs:
fail-fast: false fail-fast: false
matrix: matrix:
include: include:
- postgres: 18
os: ubuntu-24.04
- postgres: 17
os: ubuntu-24.04
- postgres: 16 - postgres: 16
os: ubuntu-24.04-arm os: ubuntu-24.04-arm
- postgres: 15
os: ubuntu-22.04
- postgres: 14 - postgres: 14
os: ubuntu-22.04-arm os: ubuntu-22.04-arm
- postgres: 13
os: ubuntu-22.04
steps: steps:
- uses: actions/checkout@v4 - uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1 - uses: ankane/setup-postgres@v1
@@ -28,7 +20,7 @@ jobs:
dev-files: true dev-files: true
- run: make - run: make
env: env:
PG_CFLAGS: ${{ matrix.postgres == 18 && '-Wno-missing-field-initializers' || '' }} -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
- run: | - run: |
export PG_CONFIG=`which pg_config` export PG_CONFIG=`which pg_config`
sudo --preserve-env=PG_CONFIG make install sudo --preserve-env=PG_CONFIG make install
@@ -39,95 +31,3 @@ jobs:
sudo apt-get update sudo apt-get update
sudo apt-get install libipc-run-perl sudo apt-get install libipc-run-perl
- run: make prove_installcheck - run: make prove_installcheck
mac:
runs-on: ${{ matrix.os }}
if: ${{ !startsWith(github.ref_name, 'windows') }}
strategy:
fail-fast: false
matrix:
include:
- postgres: 17
os: macos-15
- postgres: 14
os: macos-13
steps:
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: ${{ matrix.postgres }}
- run: make
env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter
- run: make install
- run: make installcheck
- if: ${{ failure() }}
run: cat regression.diffs
# Homebrew Postgres does not enable TAP tests, so need to download
- run: |
brew install cpanm
cpanm --notest IPC::Run
wget -q https://github.com/postgres/postgres/archive/refs/tags/$TAG.tar.gz
tar xf $TAG.tar.gz
mv postgres-$TAG postgres
env:
TAG: ${{ matrix.postgres == 17 && 'REL_17_2' || 'REL_14_15' }}
- run: make prove_installcheck PROVE_FLAGS="-I ./postgres/src/test/perl -I ./test/perl"
env:
PERL5LIB: /Users/runner/perl5/lib/perl5
- run: make clean && $(brew --prefix llvm@$LLVM_VERSION)/bin/scan-build --status-bugs make
env:
LLVM_VERSION: ${{ matrix.os == 'macos-15' && 18 || 15 }}
PG_CFLAGS: -DUSE_ASSERT_CHECKING
windows:
runs-on: windows-latest
if: ${{ !startsWith(github.ref_name, 'mac') }}
steps:
- uses: actions/checkout@v4
- uses: ankane/setup-postgres@v1
with:
postgres-version: 14
- run: |
call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
nmake /NOLOGO /F Makefile.win && ^
nmake /NOLOGO /F Makefile.win install && ^
nmake /NOLOGO /F Makefile.win installcheck && ^
nmake /NOLOGO /F Makefile.win clean && ^
nmake /NOLOGO /F Makefile.win uninstall
shell: cmd
- if: ${{ failure() }}
run: cat regression.diffs
i386:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest
container:
image: debian:12
options: --platform linux/386
steps:
- run: apt-get update && apt-get install -y build-essential git libipc-run-perl postgresql-15 postgresql-server-dev-15 sudo
- run: service postgresql start
- run: |
git clone https://github.com/${{ github.repository }}.git pgvector
cd pgvector
git fetch origin ${{ github.ref }}
git reset --hard FETCH_HEAD
make
make install
chown -R postgres .
sudo -u postgres make installcheck
sudo -u postgres make prove_installcheck
env:
PG_CFLAGS: -DUSE_ASSERT_CHECKING -Wall -Wextra -Werror -Wno-unused-parameter -Wno-sign-compare
- if: ${{ failure() }}
run: cat pgvector/regression.diffs
valgrind:
if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
runs-on: ubuntu-latest
steps:
- uses: actions/checkout@v4
- uses: ankane/setup-postgres-valgrind@v1
with:
postgres-version: 17
check-ub: yes
- run: make OPTFLAGS=""
- run: sudo --preserve-env=PG_CONFIG make install
- run: make installcheck

110
README.md
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@@ -52,6 +52,8 @@ nmake /F Makefile.win
nmake /F Makefile.win install nmake /F Makefile.win install
``` ```
Note: Postgres 17 is not supported with MSVC yet due to an [upstream issue](https://www.postgresql.org/message-id/flat/CAOdR5yF0krWrxycA04rgUKCgKugRvGWzzGLAhDZ9bzNv8g0Lag%40mail.gmail.com)
See the [installation notes](#installation-notes---windows) if you run into issues See the [installation notes](#installation-notes---windows) if you run into issues
You can also install it with [Docker](#docker) or [conda-forge](#conda-forge). You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
@@ -82,7 +84,7 @@ Get the nearest neighbors by L2 distance
SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5; SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
``` ```
Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`) Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`, added in 0.7.0)
Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators
@@ -146,9 +148,9 @@ Supported distance functions are:
- `<->` - L2 distance - `<->` - L2 distance
- `<#>` - (negative) inner product - `<#>` - (negative) inner product
- `<=>` - cosine distance - `<=>` - cosine distance
- `<+>` - L1 distance - `<+>` - L1 distance (added in 0.7.0)
- `<~>` - Hamming distance (binary vectors) - `<~>` - Hamming distance (binary vectors, added in 0.7.0)
- `<%>` - Jaccard distance (binary vectors) - `<%>` - Jaccard distance (binary vectors, added in 0.7.0)
Get the nearest neighbors to a row Get the nearest neighbors to a row
@@ -235,19 +237,19 @@ Cosine distance
CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops); CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
``` ```
L1 distance L1 distance - added in 0.7.0
```sql ```sql
CREATE INDEX ON items USING hnsw (embedding vector_l1_ops); CREATE INDEX ON items USING hnsw (embedding vector_l1_ops);
``` ```
Hamming distance Hamming distance - added in 0.7.0
```sql ```sql
CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops); CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
``` ```
Jaccard distance Jaccard distance - added in 0.7.0
```sql ```sql
CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops); CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
@@ -256,9 +258,9 @@ CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
Supported types are: Supported types are:
- `vector` - up to 2,000 dimensions - `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions - `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions - `bit` - up to 64,000 dimensions (added in 0.7.0)
- `sparsevec` - up to 1,000 non-zero elements - `sparsevec` - up to 1,000 non-zero elements (added in 0.7.0)
### Index Options ### Index Options
@@ -312,15 +314,13 @@ Note: Do not set `maintenance_work_mem` so high that it exhausts the memory on t
Like other index types, its faster to create an index after loading your initial data Like other index types, its faster to create an index after loading your initial data
You can also speed up index creation by increasing the number of parallel workers (2 by default) Starting with 0.6.0, you can also speed up index creation by increasing the number of parallel workers (2 by default)
```sql ```sql
SET max_parallel_maintenance_workers = 7; -- plus leader SET max_parallel_maintenance_workers = 7; -- plus leader
``` ```
For a large number of workers, you may need to increase `max_parallel_workers` (8 by default) For a large number of workers, you may also need to increase `max_parallel_workers` (8 by default)
The [index options](#index-options) also have a significant impact on build time (use the defaults unless seeing low recall)
### Indexing Progress ### Indexing Progress
@@ -367,7 +367,7 @@ Cosine distance
CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100); CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
``` ```
Hamming distance Hamming distance - added in 0.7.0
```sql ```sql
CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100); CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100);
@@ -376,8 +376,8 @@ CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 10
Supported types are: Supported types are:
- `vector` - up to 2,000 dimensions - `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions - `halfvec` - up to 4,000 dimensions (added in 0.7.0)
- `bit` - up to 64,000 dimensions - `bit` - up to 64,000 dimensions (added in 0.7.0)
### Query Options ### Query Options
@@ -477,6 +477,8 @@ CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(cate
## Iterative Index Scans ## Iterative Index Scans
*Added in 0.8.0*
With approximate indexes, queries with filtering can return less results since filtering is applied *after* the index is scanned. Starting with 0.8.0, you can enable iterative index scans, which will automatically scan more of the index until enough results are found (or it reaches `hnsw.max_scan_tuples` or `ivfflat.max_probes`). With approximate indexes, queries with filtering can return less results since filtering is applied *after* the index is scanned. Starting with 0.8.0, you can enable iterative index scans, which will automatically scan more of the index until enough results are found (or it reaches `hnsw.max_scan_tuples` or `ivfflat.max_probes`).
Iterative scans can use strict or relaxed ordering. Iterative scans can use strict or relaxed ordering.
@@ -547,6 +549,8 @@ Note: If this is lower than `ivfflat.probes`, `ivfflat.probes` will be used
## Half-Precision Vectors ## Half-Precision Vectors
*Added in 0.7.0*
Use the `halfvec` type to store half-precision vectors Use the `halfvec` type to store half-precision vectors
```sql ```sql
@@ -555,6 +559,8 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));
## Half-Precision Indexing ## Half-Precision Indexing
*Added in 0.7.0*
Index vectors at half precision for smaller indexes Index vectors at half precision for smaller indexes
```sql ```sql
@@ -576,16 +582,24 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
INSERT INTO items (embedding) VALUES ('000'), ('111'); INSERT INTO items (embedding) VALUES ('000'), ('111');
``` ```
Get the nearest neighbors by Hamming distance Get the nearest neighbors by Hamming distance (added in 0.7.0)
```sql ```sql
SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5; SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
``` ```
Or (before 0.7.0)
```sql
SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
```
Also supports Jaccard distance (`<%>`) Also supports Jaccard distance (`<%>`)
## Binary Quantization ## Binary Quantization
*Added in 0.7.0*
Use expression indexing for binary quantization Use expression indexing for binary quantization
```sql ```sql
@@ -608,6 +622,8 @@ SELECT * FROM (
## Sparse Vectors ## Sparse Vectors
*Added in 0.7.0*
Use the `sparsevec` type to store sparse vectors Use the `sparsevec` type to store sparse vectors
```sql ```sql
@@ -641,6 +657,8 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python
## Indexing Subvectors ## Indexing Subvectors
*Added in 0.7.0*
Use expression indexing to index subvectors Use expression indexing to index subvectors
```sql ```sql
@@ -754,6 +772,8 @@ SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_t
FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20; FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20;
``` ```
Note: Replace `total_plan_time + total_exec_time` with `total_time` for Postgres < 13
Monitor recall by comparing results from approximate search with exact search. Monitor recall by comparing results from approximate search with exact search.
```sql ```sql
@@ -822,7 +842,7 @@ You can use [half-precision indexing](#half-precision-indexing) to index up to 4
#### Can I store vectors with different dimensions in the same column? #### Can I store vectors with different dimensions in the same column?
You can use `vector` as the type (instead of `vector(n)`). You can use `vector` as the type (instead of `vector(3)`).
```sql ```sql
CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id)); CREATE TABLE embeddings (model_id bigint, item_id bigint, embedding vector, PRIMARY KEY (model_id, item_id));
@@ -1101,13 +1121,7 @@ Note: Replace `17` with your Postgres server version
### Missing SDK ### Missing SDK
If compilation fails and the output includes `warning: no such sysroot directory` on Mac, your Postgres installation points to a path that no longer exists. If compilation fails and the output includes `warning: no such sysroot directory` on Mac, reinstall Xcode Command Line Tools.
```sh
pg_config --cppflags
```
Reinstall Postgres to fix this.
### Portability ### Portability
@@ -1125,14 +1139,6 @@ make OPTFLAGS=""
If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct. If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct.
### Mismatched Architecture
If compilation fails with `error C2196: case value '4' already used`, make sure `vcvars64.bat` was called. Then run `nmake /F Makefile.win clean` and re-run the installation instructions.
### Missing Symbol
If linking fails with `unresolved external symbol float_to_shortest_decimal_bufn` with Postgres 17.0-17.2, upgrade to Postgres 17.3+.
### Permissions ### Permissions
If installation fails with `Access is denied`, re-run the installation instructions as an administrator. If installation fails with `Access is denied`, re-run the installation instructions as an administrator.
@@ -1157,12 +1163,6 @@ cd pgvector
docker build --pull --build-arg PG_MAJOR=17 -t myuser/pgvector . docker build --pull --build-arg PG_MAJOR=17 -t myuser/pgvector .
``` ```
If you increase `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
```sh
docker run --shm-size=1g ...
```
### Homebrew ### Homebrew
With Homebrew Postgres, you can use: With Homebrew Postgres, you can use:
@@ -1250,6 +1250,36 @@ You can check the version in the current database with:
SELECT extversion FROM pg_extension WHERE extname = 'vector'; SELECT extversion FROM pg_extension WHERE extname = 'vector';
``` ```
## Upgrade Notes
### 0.6.0
#### Postgres 12
If upgrading with Postgres 12, remove this line from `sql/vector--0.5.1--0.6.0.sql`:
```sql
ALTER TYPE vector SET (STORAGE = external);
```
Then run `make install` and `ALTER EXTENSION vector UPDATE;`.
#### Docker
The Docker image is now published in the `pgvector` org, and there are tags for each supported version of Postgres (rather than a `latest` tag).
```sh
docker pull pgvector/pgvector:pg16
# or
docker pull pgvector/pgvector:0.6.0-pg16
```
Also, if youve increased `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
```sh
docker run --shm-size=1g ...
```
## Thanks ## Thanks
Thanks to: Thanks to:

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@@ -259,11 +259,6 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amoptsprocnum = 0; amroutine->amoptsprocnum = 0;
amroutine->amcanorder = false; amroutine->amcanorder = false;
amroutine->amcanorderbyop = true; amroutine->amcanorderbyop = true;
#if PG_VERSION_NUM >= 180000
amroutine->amcanhash = false;
amroutine->amconsistentequality = false;
amroutine->amconsistentordering = false;
#endif
amroutine->amcanbackward = false; /* can change direction mid-scan */ amroutine->amcanbackward = false; /* can change direction mid-scan */
amroutine->amcanunique = false; amroutine->amcanunique = false;
amroutine->amcanmulticol = false; amroutine->amcanmulticol = false;
@@ -296,9 +291,6 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->amvacuumcleanup = hnswvacuumcleanup; amroutine->amvacuumcleanup = hnswvacuumcleanup;
amroutine->amcanreturn = NULL; amroutine->amcanreturn = NULL;
amroutine->amcostestimate = hnswcostestimate; amroutine->amcostestimate = hnswcostestimate;
#if PG_VERSION_NUM >= 180000
amroutine->amgettreeheight = NULL;
#endif
amroutine->amoptions = hnswoptions; amroutine->amoptions = hnswoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */ amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
amroutine->ambuildphasename = hnswbuildphasename; amroutine->ambuildphasename = hnswbuildphasename;
@@ -319,10 +311,5 @@ hnswhandler(PG_FUNCTION_ARGS)
amroutine->aminitparallelscan = NULL; amroutine->aminitparallelscan = NULL;
amroutine->amparallelrescan = NULL; amroutine->amparallelrescan = NULL;
#if PG_VERSION_NUM >= 180000
amroutine->amtranslatestrategy = NULL;
amroutine->amtranslatecmptype = NULL;
#endif
PG_RETURN_POINTER(amroutine); PG_RETURN_POINTER(amroutine);
} }

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@@ -805,12 +805,6 @@ HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *u
if (!found) if (!found)
unvisited[(*unvisitedLength)++].indextid = *indextid; unvisited[(*unvisitedLength)++].indextid = *indextid;
} }
#ifdef USE_PREFETCH
/* TODO limit by get_tablespace_io_concurrency */
for (int i = 0; i < *unvisitedLength; i++)
PrefetchBuffer(index, MAIN_FORKNUM, ItemPointerGetBlockNumber(&unvisited[i].indextid));
#endif
} }
/* /*

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@@ -9,10 +9,6 @@
#include "storage/lmgr.h" #include "storage/lmgr.h"
#include "utils/memutils.h" #include "utils/memutils.h"
#if PG_VERSION_NUM >= 180000
#define vacuum_delay_point() vacuum_delay_point(false)
#endif
/* /*
* Check if deleted list contains an index TID * Check if deleted list contains an index TID
*/ */

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@@ -186,11 +186,6 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amoptsprocnum = 0; amroutine->amoptsprocnum = 0;
amroutine->amcanorder = false; amroutine->amcanorder = false;
amroutine->amcanorderbyop = true; amroutine->amcanorderbyop = true;
#if PG_VERSION_NUM >= 180000
amroutine->amcanhash = false;
amroutine->amconsistentequality = false;
amroutine->amconsistentordering = false;
#endif
amroutine->amcanbackward = false; /* can change direction mid-scan */ amroutine->amcanbackward = false; /* can change direction mid-scan */
amroutine->amcanunique = false; amroutine->amcanunique = false;
amroutine->amcanmulticol = false; amroutine->amcanmulticol = false;
@@ -223,9 +218,6 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->amvacuumcleanup = ivfflatvacuumcleanup; amroutine->amvacuumcleanup = ivfflatvacuumcleanup;
amroutine->amcanreturn = NULL; /* tuple not included in heapsort */ amroutine->amcanreturn = NULL; /* tuple not included in heapsort */
amroutine->amcostestimate = ivfflatcostestimate; amroutine->amcostestimate = ivfflatcostestimate;
#if PG_VERSION_NUM >= 180000
amroutine->amgettreeheight = NULL;
#endif
amroutine->amoptions = ivfflatoptions; amroutine->amoptions = ivfflatoptions;
amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */ amroutine->amproperty = NULL; /* TODO AMPROP_DISTANCE_ORDERABLE */
amroutine->ambuildphasename = ivfflatbuildphasename; amroutine->ambuildphasename = ivfflatbuildphasename;
@@ -246,10 +238,5 @@ ivfflathandler(PG_FUNCTION_ARGS)
amroutine->aminitparallelscan = NULL; amroutine->aminitparallelscan = NULL;
amroutine->amparallelrescan = NULL; amroutine->amparallelrescan = NULL;
#if PG_VERSION_NUM >= 180000
amroutine->amtranslatestrategy = NULL;
amroutine->amtranslatecmptype = NULL;
#endif
PG_RETURN_POINTER(amroutine); PG_RETURN_POINTER(amroutine);
} }

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@@ -5,10 +5,6 @@
#include "ivfflat.h" #include "ivfflat.h"
#include "storage/bufmgr.h" #include "storage/bufmgr.h"
#if PG_VERSION_NUM >= 180000
#define vacuum_delay_point() vacuum_delay_point(false)
#endif
/* /*
* Bulk delete tuples from the index * Bulk delete tuples from the index
*/ */

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@@ -123,12 +123,6 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
[0,0,0] [0,0,0]
(3 rows) (3 rows)
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
RESET hnsw.iterative_scan; RESET hnsw.iterative_scan;
RESET hnsw.ef_search; RESET hnsw.ef_search;
DROP TABLE t; DROP TABLE t;

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@@ -110,15 +110,6 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
[1,1,1] [1,1,1]
(2 rows) (2 rows)
TRUNCATE t;
NOTICE: ivfflat index created with little data
DETAIL: This will cause low recall.
HINT: Drop the index until the table has more data.
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
val
-----
(0 rows)
RESET ivfflat.iterative_scan; RESET ivfflat.iterative_scan;
RESET ivfflat.max_probes; RESET ivfflat.max_probes;
DROP TABLE t; DROP TABLE t;

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@@ -70,9 +70,6 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SET hnsw.iterative_scan = relaxed_order; SET hnsw.iterative_scan = relaxed_order;
SELECT * FROM t ORDER BY val <-> '[3,3,3]'; SELECT * FROM t ORDER BY val <-> '[3,3,3]';
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
RESET hnsw.iterative_scan; RESET hnsw.iterative_scan;
RESET hnsw.ef_search; RESET hnsw.ef_search;
DROP TABLE t; DROP TABLE t;

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@@ -59,9 +59,6 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
SET ivfflat.max_probes = 2; SET ivfflat.max_probes = 2;
SELECT * FROM t ORDER BY val <-> '[3,3,3]'; SELECT * FROM t ORDER BY val <-> '[3,3,3]';
TRUNCATE t;
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
RESET ivfflat.iterative_scan; RESET ivfflat.iterative_scan;
RESET ivfflat.max_probes; RESET ivfflat.max_probes;
DROP TABLE t; DROP TABLE t;