mirror of
https://github.com/pgvector/pgvector.git
synced 2026-07-22 20:15:46 +08:00
Compare commits
50 Commits
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
2627c5ff77 | ||
|
|
34b3cfdc43 | ||
|
|
cd218aae5a | ||
|
|
ba9367f86c | ||
|
|
9c20550a41 | ||
|
|
e3e74fe94e | ||
|
|
96a5a44632 | ||
|
|
67e1392a83 | ||
|
|
e530a1a026 | ||
|
|
6170e2645b | ||
|
|
e6bae175f1 | ||
|
|
52b777e04a | ||
|
|
307271214f | ||
|
|
6e9f74ddce | ||
|
|
258215ad97 | ||
|
|
fb87b6da91 | ||
|
|
a2a0b377f0 | ||
|
|
2f770307b8 | ||
|
|
c04e16ff5b | ||
|
|
bd4d272f26 | ||
|
|
8bb797cc2f | ||
|
|
fe6ec03dac | ||
|
|
c1161f8889 | ||
|
|
c530a3c490 | ||
|
|
d8b9e8ef73 | ||
|
|
00894efed5 | ||
|
|
0aa0f6619b | ||
|
|
38d053001e | ||
|
|
ccb95407e7 | ||
|
|
04d5e934a1 | ||
|
|
b163b5b196 | ||
|
|
6a30c1e824 | ||
|
|
2db1b19644 | ||
|
|
305d62146e | ||
|
|
f9d627c9a9 | ||
|
|
38f42820be | ||
|
|
15c8245b42 | ||
|
|
572a9ab404 | ||
|
|
00492d7e57 | ||
|
|
857d716d9e | ||
|
|
c5dd2af750 | ||
|
|
78b877bdaf | ||
|
|
7043cce893 | ||
|
|
62039d74f6 | ||
|
|
ac6576e53a | ||
|
|
67eff41c44 | ||
|
|
1291b12090 | ||
|
|
24522700b8 | ||
|
|
bfb3a45b31 | ||
|
|
e718eb8da4 |
4
.github/workflows/build.yml
vendored
4
.github/workflows/build.yml
vendored
@@ -8,8 +8,8 @@ jobs:
|
||||
fail-fast: false
|
||||
matrix:
|
||||
include:
|
||||
# - postgres: 18
|
||||
# os: ubuntu-24.04
|
||||
- postgres: 18
|
||||
os: ubuntu-24.04
|
||||
- postgres: 17
|
||||
os: ubuntu-24.04
|
||||
- postgres: 16
|
||||
|
||||
@@ -1,10 +1,10 @@
|
||||
## 0.8.0 (unreleased)
|
||||
## 0.8.0 (2024-10-30)
|
||||
|
||||
- Added support for iterative index scans
|
||||
- Added casts for arrays to `sparsevec`
|
||||
- Improved cost estimation
|
||||
- Improved cost estimation for better index selection when filtering
|
||||
- Improved performance of HNSW index scans
|
||||
- Improved performance of HNSW inserts and on-disk index builds
|
||||
- Reduced memory usage for HNSW index scans
|
||||
- Dropped support for Postgres 12
|
||||
|
||||
## 0.7.4 (2024-08-05)
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
"name": "vector",
|
||||
"abstract": "Open-source vector similarity search for Postgres",
|
||||
"description": "Supports L2 distance, inner product, and cosine distance",
|
||||
"version": "0.7.4",
|
||||
"version": "0.8.0",
|
||||
"maintainer": [
|
||||
"Andrew Kane <andrew@ankane.org>"
|
||||
],
|
||||
@@ -12,7 +12,7 @@
|
||||
"prereqs": {
|
||||
"runtime": {
|
||||
"requires": {
|
||||
"PostgreSQL": "12.0.0"
|
||||
"PostgreSQL": "13.0.0"
|
||||
}
|
||||
}
|
||||
},
|
||||
@@ -20,7 +20,7 @@
|
||||
"vector": {
|
||||
"file": "sql/vector.sql",
|
||||
"docfile": "README.md",
|
||||
"version": "0.7.4",
|
||||
"version": "0.8.0",
|
||||
"abstract": "Open-source vector similarity search for Postgres"
|
||||
}
|
||||
},
|
||||
|
||||
2
Makefile
2
Makefile
@@ -1,5 +1,5 @@
|
||||
EXTENSION = vector
|
||||
EXTVERSION = 0.7.4
|
||||
EXTVERSION = 0.8.0
|
||||
|
||||
MODULE_big = vector
|
||||
DATA = $(wildcard sql/*--*--*.sql)
|
||||
|
||||
@@ -1,5 +1,5 @@
|
||||
EXTENSION = vector
|
||||
EXTVERSION = 0.7.4
|
||||
EXTVERSION = 0.8.0
|
||||
|
||||
DATA_built = sql\$(EXTENSION)--$(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
|
||||
|
||||
116
README.md
116
README.md
@@ -17,11 +17,11 @@ Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recove
|
||||
|
||||
### Linux and Mac
|
||||
|
||||
Compile and install the extension (supports Postgres 12+)
|
||||
Compile and install the extension (supports Postgres 13+)
|
||||
|
||||
```sh
|
||||
cd /tmp
|
||||
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.8.0 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 v0.7.4 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
nmake /F Makefile.win
|
||||
nmake /F Makefile.win install
|
||||
@@ -324,7 +324,7 @@ For a large number of workers, you may also need to increase `max_parallel_worke
|
||||
|
||||
### Indexing Progress
|
||||
|
||||
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
|
||||
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
|
||||
|
||||
```sql
|
||||
SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
|
||||
@@ -410,7 +410,7 @@ For a large number of workers, you may also need to increase `max_parallel_worke
|
||||
|
||||
### Indexing Progress
|
||||
|
||||
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+
|
||||
Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
|
||||
|
||||
```sql
|
||||
SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
|
||||
@@ -427,30 +427,126 @@ Note: `%` is only populated during the `loading tuples` phase
|
||||
|
||||
## Filtering
|
||||
|
||||
There are a few ways to index nearest neighbor queries with a `WHERE` clause
|
||||
There are a few ways to index nearest neighbor queries with a `WHERE` clause.
|
||||
|
||||
```sql
|
||||
SELECT * FROM items WHERE category_id = 123 ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
|
||||
```
|
||||
|
||||
Create an index on one [or more](https://www.postgresql.org/docs/current/indexes-multicolumn.html) of the `WHERE` columns for exact search
|
||||
A good place to start is creating an index on the filter column. This can provide fast, exact nearest neighbor search in many cases. Postgres has a number of [index types](https://www.postgresql.org/docs/current/indexes-types.html) for this: B-tree (default), hash, GiST, SP-GiST, GIN, and BRIN.
|
||||
|
||||
```sql
|
||||
CREATE INDEX ON items (category_id);
|
||||
```
|
||||
|
||||
Or a [partial index](https://www.postgresql.org/docs/current/indexes-partial.html) on the vector column for approximate search
|
||||
For multiple columns, consider a [multicolumn index](https://www.postgresql.org/docs/current/indexes-multicolumn.html).
|
||||
|
||||
```sql
|
||||
CREATE INDEX ON items (location_id, category_id);
|
||||
```
|
||||
|
||||
Exact indexes work well for conditions that match a low percentage of rows. Otherwise, [approximate indexes](#indexing) can work better.
|
||||
|
||||
```sql
|
||||
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops);
|
||||
```
|
||||
|
||||
With approximate indexes, filtering is applied *after* the index is scanned. If a condition matches 10% of rows, with HNSW and the default `hnsw.ef_search` of 40, only 4 rows will match on average. For more rows, increase `hnsw.ef_search`.
|
||||
|
||||
```sql
|
||||
SET hnsw.ef_search = 200;
|
||||
```
|
||||
|
||||
Starting with 0.8.0, you can enable [iterative index scans](#iterative-index-scans), which will automatically scan more of the index when needed.
|
||||
|
||||
```sql
|
||||
SET hnsw.iterative_scan = strict_order;
|
||||
```
|
||||
|
||||
If filtering by only a few distinct values, consider [partial indexing](https://www.postgresql.org/docs/current/indexes-partial.html).
|
||||
|
||||
```sql
|
||||
CREATE INDEX ON items USING hnsw (embedding vector_l2_ops) WHERE (category_id = 123);
|
||||
```
|
||||
|
||||
Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html) for approximate search on many different values of the `WHERE` columns
|
||||
If filtering by many different values, consider [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html).
|
||||
|
||||
```sql
|
||||
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
|
||||
```
|
||||
|
||||
## 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`).
|
||||
|
||||
Iterative scans can use strict or relaxed ordering.
|
||||
|
||||
Strict ensures results are in the exact order by distance
|
||||
|
||||
```sql
|
||||
SET hnsw.iterative_scan = strict_order;
|
||||
```
|
||||
|
||||
Relaxed allows results to be slightly out of order by distance, but provides better recall
|
||||
|
||||
```sql
|
||||
SET hnsw.iterative_scan = relaxed_order;
|
||||
# or
|
||||
SET ivfflat.iterative_scan = relaxed_order;
|
||||
```
|
||||
|
||||
With relaxed ordering, you can use a [materialized CTE](https://www.postgresql.org/docs/current/queries-with.html#QUERIES-WITH-CTE-MATERIALIZATION) to get strict ordering
|
||||
|
||||
```sql
|
||||
WITH relaxed_results AS MATERIALIZED (
|
||||
SELECT id, embedding <-> '[1,2,3]' AS distance FROM items WHERE category_id = 123 ORDER BY distance LIMIT 5
|
||||
) SELECT * FROM relaxed_results ORDER BY distance;
|
||||
```
|
||||
|
||||
For queries that filter by distance, use a materialized CTE and place the distance filter outside of it for best performance (due to the [current behavior](https://www.postgresql.org/message-id/flat/CAOdR5yGUoMQ6j7M5hNUXrySzaqZVGf_Ne%2B8fwZMRKTFxU1nbJg%40mail.gmail.com) of the Postgres executor)
|
||||
|
||||
```sql
|
||||
WITH nearest_results AS MATERIALIZED (
|
||||
SELECT id, embedding <-> '[1,2,3]' AS distance FROM items ORDER BY distance LIMIT 5
|
||||
) SELECT * FROM nearest_results WHERE distance < 5 ORDER BY distance;
|
||||
```
|
||||
|
||||
Note: Place any other filters inside the CTE
|
||||
|
||||
### Iterative Scan Options
|
||||
|
||||
Since scanning a large portion of an approximate index is expensive, there are options to control when a scan ends.
|
||||
|
||||
#### HNSW
|
||||
|
||||
Specify the max number of tuples to visit (20,000 by default)
|
||||
|
||||
```sql
|
||||
SET hnsw.max_scan_tuples = 20000;
|
||||
```
|
||||
|
||||
Note: This is approximate and does not affect the initial scan
|
||||
|
||||
Specify the max amount of memory to use, as a multiple of `work_mem` (1 by default)
|
||||
|
||||
```sql
|
||||
SET hnsw.scan_mem_multiplier = 2;
|
||||
```
|
||||
|
||||
Note: Try increasing this if increasing `hnsw.max_scan_tuples` does not improve recall
|
||||
|
||||
#### IVFFlat
|
||||
|
||||
Specify the max number of probes
|
||||
|
||||
```sql
|
||||
SET ivfflat.max_probes = 100;
|
||||
```
|
||||
|
||||
Note: If this is lower than `ivfflat.probes`, `ivfflat.probes` will be used
|
||||
|
||||
## Half-Precision Vectors
|
||||
|
||||
*Added in 0.7.0*
|
||||
@@ -1057,7 +1153,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
|
||||
You can also build the image manually:
|
||||
|
||||
```sh
|
||||
git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
docker build --pull --build-arg PG_MAJOR=17 -t myuser/pgvector .
|
||||
```
|
||||
|
||||
36
src/hnsw.c
36
src/hnsw.c
@@ -18,16 +18,17 @@
|
||||
#define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
|
||||
#endif
|
||||
|
||||
static const struct config_enum_entry hnsw_iterative_search_options[] = {
|
||||
{"off", HNSW_ITERATIVE_SEARCH_OFF, false},
|
||||
{"relaxed_order", HNSW_ITERATIVE_SEARCH_RELAXED, false},
|
||||
{"strict_order", HNSW_ITERATIVE_SEARCH_STRICT, false},
|
||||
static const struct config_enum_entry hnsw_iterative_scan_options[] = {
|
||||
{"off", HNSW_ITERATIVE_SCAN_OFF, false},
|
||||
{"relaxed_order", HNSW_ITERATIVE_SCAN_RELAXED, false},
|
||||
{"strict_order", HNSW_ITERATIVE_SCAN_STRICT, false},
|
||||
{NULL, 0, false}
|
||||
};
|
||||
|
||||
int hnsw_ef_search;
|
||||
int hnsw_max_search_tuples;
|
||||
int hnsw_iterative_search;
|
||||
int hnsw_iterative_scan;
|
||||
int hnsw_max_scan_tuples;
|
||||
double hnsw_scan_mem_multiplier;
|
||||
int hnsw_lock_tranche_id;
|
||||
static relopt_kind hnsw_relopt_kind;
|
||||
|
||||
@@ -78,14 +79,19 @@ HnswInit(void)
|
||||
"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);
|
||||
|
||||
DefineCustomEnumVariable("hnsw.iterative_search", "Sets the iterative search mode",
|
||||
NULL, &hnsw_iterative_search,
|
||||
HNSW_ITERATIVE_SEARCH_OFF, hnsw_iterative_search_options, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
DefineCustomEnumVariable("hnsw.iterative_scan", "Sets the mode for iterative scans",
|
||||
NULL, &hnsw_iterative_scan,
|
||||
HNSW_ITERATIVE_SCAN_OFF, hnsw_iterative_scan_options, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
|
||||
/* This is approximate and does not apply to the initial scan */
|
||||
DefineCustomIntVariable("hnsw.max_search_tuples", "Sets the max number of candidates to visit for iterative search",
|
||||
"-1 means no limit", &hnsw_max_search_tuples,
|
||||
-1, -1, INT_MAX, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
/* This is approximate and does not affect the initial scan */
|
||||
DefineCustomIntVariable("hnsw.max_scan_tuples", "Sets the max number of tuples to visit for iterative scans",
|
||||
NULL, &hnsw_max_scan_tuples,
|
||||
20000, 1, INT_MAX, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
|
||||
/* Same range as hash_mem_multiplier */
|
||||
DefineCustomRealVariable("hnsw.scan_mem_multiplier", "Sets the multiple of work_mem to use for iterative scans",
|
||||
NULL, &hnsw_scan_mem_multiplier,
|
||||
1, 1, 1000, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
|
||||
MarkGUCPrefixReserved("hnsw");
|
||||
}
|
||||
@@ -131,6 +137,10 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
|
||||
*indexSelectivity = 0;
|
||||
*indexCorrelation = 0;
|
||||
*indexPages = 0;
|
||||
#if PG_VERSION_NUM >= 180000
|
||||
/* See "On disable_cost" thread on pgsql-hackers */
|
||||
path->path.disabled_nodes = 2;
|
||||
#endif
|
||||
return;
|
||||
}
|
||||
|
||||
|
||||
16
src/hnsw.h
16
src/hnsw.h
@@ -109,16 +109,17 @@
|
||||
|
||||
/* Variables */
|
||||
extern int hnsw_ef_search;
|
||||
extern int hnsw_iterative_search;
|
||||
extern int hnsw_max_search_tuples;
|
||||
extern int hnsw_iterative_scan;
|
||||
extern int hnsw_max_scan_tuples;
|
||||
extern double hnsw_scan_mem_multiplier;
|
||||
extern int hnsw_lock_tranche_id;
|
||||
|
||||
typedef enum HnswIterativeSearchMode
|
||||
typedef enum HnswIterativeScanMode
|
||||
{
|
||||
HNSW_ITERATIVE_SEARCH_OFF,
|
||||
HNSW_ITERATIVE_SEARCH_RELAXED,
|
||||
HNSW_ITERATIVE_SEARCH_STRICT
|
||||
} HnswIterativeSearchMode;
|
||||
HNSW_ITERATIVE_SCAN_OFF,
|
||||
HNSW_ITERATIVE_SCAN_RELAXED,
|
||||
HNSW_ITERATIVE_SCAN_STRICT
|
||||
} HnswIterativeScanMode;
|
||||
|
||||
typedef struct HnswElementData HnswElementData;
|
||||
typedef struct HnswNeighborArray HnswNeighborArray;
|
||||
@@ -372,6 +373,7 @@ typedef struct HnswScanOpaqueData
|
||||
int m;
|
||||
int64 tuples;
|
||||
double previousDistance;
|
||||
Size maxMemory;
|
||||
MemoryContext tmpCtx;
|
||||
|
||||
/* Support functions */
|
||||
|
||||
@@ -41,7 +41,7 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
||||
ep = w;
|
||||
}
|
||||
|
||||
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, support, m, false, NULL, &so->v, hnsw_iterative_search != HNSW_ITERATIVE_SEARCH_OFF ? &so->discarded : NULL, true, &so->tuples);
|
||||
return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, support, m, false, NULL, &so->v, hnsw_iterative_scan != HNSW_ITERATIVE_SCAN_OFF ? &so->discarded : NULL, true, &so->tuples);
|
||||
}
|
||||
|
||||
/*
|
||||
@@ -121,14 +121,15 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
|
||||
{
|
||||
IndexScanDesc scan;
|
||||
HnswScanOpaque so;
|
||||
double maxMemory;
|
||||
|
||||
scan = RelationGetIndexScan(index, nkeys, norderbys);
|
||||
|
||||
so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData));
|
||||
so->typeInfo = HnswGetTypeInfo(index);
|
||||
so->first = true;
|
||||
so->v.tids = NULL;
|
||||
so->discarded = NULL;
|
||||
|
||||
/* Set support functions */
|
||||
HnswInitSupport(&so->support, index);
|
||||
|
||||
/*
|
||||
* Use a lower max allocation size than default to allow scanning more
|
||||
@@ -136,10 +137,12 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
|
||||
*/
|
||||
so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
|
||||
"Hnsw scan temporary context",
|
||||
0, 8 * 1024, 512 * 1024);
|
||||
0, 8 * 1024, 256 * 1024);
|
||||
|
||||
/* Set support functions */
|
||||
HnswInitSupport(&so->support, index);
|
||||
/* Calculate max memory */
|
||||
/* Add 256 extra bytes to fill last block when close */
|
||||
maxMemory = (double) work_mem * hnsw_scan_mem_multiplier * 1024.0 + 256;
|
||||
so->maxMemory = Min(maxMemory, (double) SIZE_MAX);
|
||||
|
||||
scan->opaque = so;
|
||||
|
||||
@@ -154,13 +157,10 @@ 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;
|
||||
/* v and discarded are allocated in tmpCtx */
|
||||
so->v.tids = NULL;
|
||||
so->discarded = NULL;
|
||||
so->tuples = 0;
|
||||
so->previousDistance = -get_float8_infinity();
|
||||
MemoryContextReset(so->tmpCtx);
|
||||
@@ -233,15 +233,15 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
|
||||
if (list_length(so->w) == 0)
|
||||
{
|
||||
if (hnsw_iterative_search == HNSW_ITERATIVE_SEARCH_OFF)
|
||||
if (hnsw_iterative_scan == HNSW_ITERATIVE_SCAN_OFF)
|
||||
break;
|
||||
|
||||
/* Empty index */
|
||||
if (so->discarded == NULL)
|
||||
break;
|
||||
|
||||
/* Reached max number of tuples */
|
||||
if (hnsw_max_search_tuples != -1 && so->tuples >= hnsw_max_search_tuples)
|
||||
/* Reached max number of tuples or memory limit */
|
||||
if (so->tuples >= hnsw_max_scan_tuples || MemoryContextMemAllocated(so->tmpCtx, false) > so->maxMemory)
|
||||
{
|
||||
if (pairingheap_is_empty(so->discarded))
|
||||
break;
|
||||
@@ -249,21 +249,6 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
/* 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(DEBUG1,
|
||||
(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
|
||||
{
|
||||
/*
|
||||
@@ -299,7 +284,7 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
so->w = list_delete_last(so->w);
|
||||
|
||||
/* Mark memory as free for next iteration */
|
||||
if (hnsw_iterative_search != HNSW_ITERATIVE_SEARCH_OFF)
|
||||
if (hnsw_iterative_scan != HNSW_ITERATIVE_SCAN_OFF)
|
||||
{
|
||||
pfree(element);
|
||||
pfree(sc);
|
||||
@@ -310,7 +295,7 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
|
||||
heaptid = &element->heaptids[--element->heaptidsLength];
|
||||
|
||||
if (hnsw_iterative_search == HNSW_ITERATIVE_SEARCH_STRICT)
|
||||
if (hnsw_iterative_scan == HNSW_ITERATIVE_SCAN_STRICT)
|
||||
{
|
||||
if (sc->distance < so->previousDistance)
|
||||
continue;
|
||||
|
||||
@@ -857,6 +857,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
|
||||
{
|
||||
AddToVisited(base, v, sc->element, inMemory, &found);
|
||||
|
||||
/* OK to count elements instead of tuples */
|
||||
if (tuples != NULL)
|
||||
(*tuples)++;
|
||||
}
|
||||
@@ -889,6 +890,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
|
||||
else
|
||||
HnswLoadUnvisitedFromDisk(cElement, unvisited, &unvisitedLength, v, index, m, lm, lc);
|
||||
|
||||
/* OK to count elements instead of tuples */
|
||||
if (tuples != NULL)
|
||||
(*tuples) += unvisitedLength;
|
||||
|
||||
|
||||
@@ -17,13 +17,13 @@
|
||||
#endif
|
||||
|
||||
int ivfflat_probes;
|
||||
int ivfflat_iterative_search;
|
||||
int ivfflat_iterative_scan;
|
||||
int ivfflat_max_probes;
|
||||
static relopt_kind ivfflat_relopt_kind;
|
||||
|
||||
static const struct config_enum_entry ivfflat_iterative_search_options[] = {
|
||||
{"off", IVFFLAT_ITERATIVE_SEARCH_OFF, false},
|
||||
{"relaxed_order", IVFFLAT_ITERATIVE_SEARCH_RELAXED, false},
|
||||
static const struct config_enum_entry ivfflat_iterative_scan_options[] = {
|
||||
{"off", IVFFLAT_ITERATIVE_SCAN_OFF, false},
|
||||
{"relaxed_order", IVFFLAT_ITERATIVE_SCAN_RELAXED, false},
|
||||
{NULL, 0, false}
|
||||
};
|
||||
|
||||
@@ -41,14 +41,14 @@ IvfflatInit(void)
|
||||
"Valid range is 1..lists.", &ivfflat_probes,
|
||||
IVFFLAT_DEFAULT_PROBES, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
|
||||
DefineCustomEnumVariable("ivfflat.iterative_search", "Sets the iterative search mode",
|
||||
NULL, &ivfflat_iterative_search,
|
||||
IVFFLAT_ITERATIVE_SEARCH_OFF, ivfflat_iterative_search_options, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
DefineCustomEnumVariable("ivfflat.iterative_scan", "Sets the mode for iterative scans",
|
||||
NULL, &ivfflat_iterative_scan,
|
||||
IVFFLAT_ITERATIVE_SCAN_OFF, ivfflat_iterative_scan_options, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
|
||||
/* If this is less than probes, probes is used */
|
||||
DefineCustomIntVariable("ivfflat.max_probes", "Sets the max number of probes for iterative search",
|
||||
"-1 means no limit", &ivfflat_max_probes,
|
||||
-1, -1, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
DefineCustomIntVariable("ivfflat.max_probes", "Sets the max number of probes for iterative scans",
|
||||
NULL, &ivfflat_max_probes,
|
||||
IVFFLAT_MAX_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
|
||||
|
||||
MarkGUCPrefixReserved("ivfflat");
|
||||
}
|
||||
@@ -99,6 +99,10 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
|
||||
*indexSelectivity = 0;
|
||||
*indexCorrelation = 0;
|
||||
*indexPages = 0;
|
||||
#if PG_VERSION_NUM >= 180000
|
||||
/* See "On disable_cost" thread on pgsql-hackers */
|
||||
path->path.disabled_nodes = 2;
|
||||
#endif
|
||||
return;
|
||||
}
|
||||
|
||||
|
||||
@@ -80,14 +80,14 @@
|
||||
|
||||
/* Variables */
|
||||
extern int ivfflat_probes;
|
||||
extern int ivfflat_iterative_search;
|
||||
extern int ivfflat_iterative_scan;
|
||||
extern int ivfflat_max_probes;
|
||||
|
||||
typedef enum IvfflatIterativeSearchMode
|
||||
typedef enum IvfflatIterativeScanMode
|
||||
{
|
||||
IVFFLAT_ITERATIVE_SEARCH_OFF,
|
||||
IVFFLAT_ITERATIVE_SEARCH_RELAXED
|
||||
} IvfflatIterativeSearchMode;
|
||||
IVFFLAT_ITERATIVE_SCAN_OFF,
|
||||
IVFFLAT_ITERATIVE_SCAN_RELAXED
|
||||
} IvfflatIterativeScanMode;
|
||||
|
||||
typedef struct VectorArrayData
|
||||
{
|
||||
|
||||
@@ -114,7 +114,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
||||
{
|
||||
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
|
||||
TupleDesc tupdesc = RelationGetDescr(scan->indexRelation);
|
||||
double tuples = 0;
|
||||
TupleTableSlot *slot = so->vslot;
|
||||
int batchProbes = 0;
|
||||
|
||||
@@ -161,8 +160,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
||||
ExecStoreVirtualTuple(slot);
|
||||
|
||||
tuplesort_puttupleslot(so->sortstate, slot);
|
||||
|
||||
tuples++;
|
||||
}
|
||||
|
||||
searchPage = IvfflatPageGetOpaque(page)->nextblkno;
|
||||
@@ -171,12 +168,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
||||
}
|
||||
}
|
||||
|
||||
if (tuples < 100 && ivfflat_iterative_search == IVFFLAT_ITERATIVE_SEARCH_OFF)
|
||||
ereport(DEBUG1,
|
||||
(errmsg("index scan found few tuples"),
|
||||
errdetail("Index may have been created with little data."),
|
||||
errhint("Recreate the index and possibly decrease lists.")));
|
||||
|
||||
tuplesort_performsort(so->sortstate);
|
||||
|
||||
#if defined(IVFFLAT_MEMORY)
|
||||
@@ -263,18 +254,8 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
|
||||
/* Get lists and dimensions from metapage */
|
||||
IvfflatGetMetaPageInfo(index, &lists, &dimensions);
|
||||
|
||||
if (ivfflat_iterative_search != IVFFLAT_ITERATIVE_SEARCH_OFF)
|
||||
{
|
||||
maxProbes = ivfflat_max_probes;
|
||||
|
||||
if (maxProbes < 0)
|
||||
maxProbes = lists;
|
||||
else if (maxProbes < probes)
|
||||
{
|
||||
/* TODO Show notice */
|
||||
maxProbes = probes;
|
||||
}
|
||||
}
|
||||
if (ivfflat_iterative_scan != IVFFLAT_ITERATIVE_SCAN_OFF)
|
||||
maxProbes = Max(ivfflat_max_probes, probes);
|
||||
else
|
||||
maxProbes = probes;
|
||||
|
||||
|
||||
@@ -4,6 +4,7 @@
|
||||
#include <math.h>
|
||||
|
||||
#include "catalog/pg_type.h"
|
||||
#include "common/shortest_dec.h"
|
||||
#include "common/string.h"
|
||||
#include "fmgr.h"
|
||||
#include "halfutils.h"
|
||||
@@ -12,17 +13,10 @@
|
||||
#include "sparsevec.h"
|
||||
#include "utils/array.h"
|
||||
#include "utils/builtins.h"
|
||||
#include "utils/float.h"
|
||||
#include "utils/lsyscache.h"
|
||||
#include "vector.h"
|
||||
|
||||
#if PG_VERSION_NUM >= 120000
|
||||
#include "common/shortest_dec.h"
|
||||
#include "utils/float.h"
|
||||
#else
|
||||
#include <float.h>
|
||||
#include "utils/builtins.h"
|
||||
#endif
|
||||
|
||||
typedef struct SparseInputElement
|
||||
{
|
||||
int32 index;
|
||||
|
||||
@@ -104,7 +104,7 @@ DROP TABLE t;
|
||||
CREATE TABLE t (val vector(3));
|
||||
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
|
||||
SET hnsw.iterative_search = strict_order;
|
||||
SET hnsw.iterative_scan = strict_order;
|
||||
SET hnsw.ef_search = 1;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
val
|
||||
@@ -114,7 +114,7 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
[0,0,0]
|
||||
(3 rows)
|
||||
|
||||
SET hnsw.iterative_search = relaxed_order;
|
||||
SET hnsw.iterative_scan = relaxed_order;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
val
|
||||
---------
|
||||
@@ -123,7 +123,7 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
[0,0,0]
|
||||
(3 rows)
|
||||
|
||||
RESET hnsw.iterative_search;
|
||||
RESET hnsw.iterative_scan;
|
||||
RESET hnsw.ef_search;
|
||||
DROP TABLE t;
|
||||
-- unlogged
|
||||
@@ -165,21 +165,31 @@ SET hnsw.ef_search = 0;
|
||||
ERROR: 0 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
|
||||
SET hnsw.ef_search = 1001;
|
||||
ERROR: 1001 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
|
||||
SHOW hnsw.iterative_search;
|
||||
hnsw.iterative_search
|
||||
-----------------------
|
||||
SHOW hnsw.iterative_scan;
|
||||
hnsw.iterative_scan
|
||||
---------------------
|
||||
off
|
||||
(1 row)
|
||||
|
||||
SET hnsw.iterative_search = on;
|
||||
ERROR: invalid value for parameter "hnsw.iterative_search": "on"
|
||||
SET hnsw.iterative_scan = on;
|
||||
ERROR: invalid value for parameter "hnsw.iterative_scan": "on"
|
||||
HINT: Available values: off, relaxed_order, strict_order.
|
||||
SHOW hnsw.max_search_tuples;
|
||||
hnsw.max_search_tuples
|
||||
------------------------
|
||||
-1
|
||||
SHOW hnsw.max_scan_tuples;
|
||||
hnsw.max_scan_tuples
|
||||
----------------------
|
||||
20000
|
||||
(1 row)
|
||||
|
||||
SET hnsw.max_search_tuples = -2;
|
||||
ERROR: -2 is outside the valid range for parameter "hnsw.max_search_tuples" (-1 .. 2147483647)
|
||||
SET hnsw.max_scan_tuples = 0;
|
||||
ERROR: 0 is outside the valid range for parameter "hnsw.max_scan_tuples" (1 .. 2147483647)
|
||||
SHOW hnsw.scan_mem_multiplier;
|
||||
hnsw.scan_mem_multiplier
|
||||
--------------------------
|
||||
1
|
||||
(1 row)
|
||||
|
||||
SET hnsw.scan_mem_multiplier = 0;
|
||||
ERROR: 0 is outside the valid range for parameter "hnsw.scan_mem_multiplier" (1 .. 1000)
|
||||
SET hnsw.scan_mem_multiplier = 1001;
|
||||
ERROR: 1001 is outside the valid range for parameter "hnsw.scan_mem_multiplier" (1 .. 1000)
|
||||
DROP TABLE t;
|
||||
|
||||
@@ -86,7 +86,7 @@ DROP TABLE t;
|
||||
CREATE TABLE t (val vector(3));
|
||||
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
|
||||
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 3);
|
||||
SET ivfflat.iterative_search = relaxed_order;
|
||||
SET ivfflat.iterative_scan = relaxed_order;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
val
|
||||
---------
|
||||
@@ -95,13 +95,6 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
[0,0,0]
|
||||
(3 rows)
|
||||
|
||||
SET ivfflat.max_probes = 0;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
val
|
||||
---------
|
||||
[1,2,3]
|
||||
(1 row)
|
||||
|
||||
SET ivfflat.max_probes = 1;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
val
|
||||
@@ -117,7 +110,7 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
[1,1,1]
|
||||
(2 rows)
|
||||
|
||||
RESET ivfflat.iterative_search;
|
||||
RESET ivfflat.iterative_scan;
|
||||
RESET ivfflat.max_probes;
|
||||
DROP TABLE t;
|
||||
-- unlogged
|
||||
@@ -151,23 +144,23 @@ SET ivfflat.probes = 0;
|
||||
ERROR: 0 is outside the valid range for parameter "ivfflat.probes" (1 .. 32768)
|
||||
SET ivfflat.probes = 32769;
|
||||
ERROR: 32769 is outside the valid range for parameter "ivfflat.probes" (1 .. 32768)
|
||||
SHOW ivfflat.iterative_search;
|
||||
ivfflat.iterative_search
|
||||
--------------------------
|
||||
SHOW ivfflat.iterative_scan;
|
||||
ivfflat.iterative_scan
|
||||
------------------------
|
||||
off
|
||||
(1 row)
|
||||
|
||||
SET ivfflat.iterative_search = on;
|
||||
ERROR: invalid value for parameter "ivfflat.iterative_search": "on"
|
||||
SET ivfflat.iterative_scan = on;
|
||||
ERROR: invalid value for parameter "ivfflat.iterative_scan": "on"
|
||||
HINT: Available values: off, relaxed_order.
|
||||
SHOW ivfflat.max_probes;
|
||||
ivfflat.max_probes
|
||||
--------------------
|
||||
-1
|
||||
32768
|
||||
(1 row)
|
||||
|
||||
SET ivfflat.max_probes = -2;
|
||||
ERROR: -2 is outside the valid range for parameter "ivfflat.max_probes" (-1 .. 32768)
|
||||
SET ivfflat.max_probes = 0;
|
||||
ERROR: 0 is outside the valid range for parameter "ivfflat.max_probes" (1 .. 32768)
|
||||
SET ivfflat.max_probes = 32769;
|
||||
ERROR: 32769 is outside the valid range for parameter "ivfflat.max_probes" (-1 .. 32768)
|
||||
ERROR: 32769 is outside the valid range for parameter "ivfflat.max_probes" (1 .. 32768)
|
||||
DROP TABLE t;
|
||||
|
||||
@@ -63,14 +63,14 @@ CREATE TABLE t (val vector(3));
|
||||
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
|
||||
CREATE INDEX ON t USING hnsw (val vector_l2_ops);
|
||||
|
||||
SET hnsw.iterative_search = strict_order;
|
||||
SET hnsw.iterative_scan = strict_order;
|
||||
SET hnsw.ef_search = 1;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
|
||||
SET hnsw.iterative_search = relaxed_order;
|
||||
SET hnsw.iterative_scan = relaxed_order;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
|
||||
RESET hnsw.iterative_search;
|
||||
RESET hnsw.iterative_scan;
|
||||
RESET hnsw.ef_search;
|
||||
DROP TABLE t;
|
||||
|
||||
@@ -98,12 +98,17 @@ SHOW hnsw.ef_search;
|
||||
SET hnsw.ef_search = 0;
|
||||
SET hnsw.ef_search = 1001;
|
||||
|
||||
SHOW hnsw.iterative_search;
|
||||
SHOW hnsw.iterative_scan;
|
||||
|
||||
SET hnsw.iterative_search = on;
|
||||
SET hnsw.iterative_scan = on;
|
||||
|
||||
SHOW hnsw.max_search_tuples;
|
||||
SHOW hnsw.max_scan_tuples;
|
||||
|
||||
SET hnsw.max_search_tuples = -2;
|
||||
SET hnsw.max_scan_tuples = 0;
|
||||
|
||||
SHOW hnsw.scan_mem_multiplier;
|
||||
|
||||
SET hnsw.scan_mem_multiplier = 0;
|
||||
SET hnsw.scan_mem_multiplier = 1001;
|
||||
|
||||
DROP TABLE t;
|
||||
|
||||
@@ -50,10 +50,7 @@ CREATE TABLE t (val vector(3));
|
||||
INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
|
||||
CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 3);
|
||||
|
||||
SET ivfflat.iterative_search = relaxed_order;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
|
||||
SET ivfflat.max_probes = 0;
|
||||
SET ivfflat.iterative_scan = relaxed_order;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
|
||||
SET ivfflat.max_probes = 1;
|
||||
@@ -62,7 +59,7 @@ SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
SET ivfflat.max_probes = 2;
|
||||
SELECT * FROM t ORDER BY val <-> '[3,3,3]';
|
||||
|
||||
RESET ivfflat.iterative_search;
|
||||
RESET ivfflat.iterative_scan;
|
||||
RESET ivfflat.max_probes;
|
||||
DROP TABLE t;
|
||||
|
||||
@@ -87,13 +84,13 @@ SHOW ivfflat.probes;
|
||||
SET ivfflat.probes = 0;
|
||||
SET ivfflat.probes = 32769;
|
||||
|
||||
SHOW ivfflat.iterative_search;
|
||||
SHOW ivfflat.iterative_scan;
|
||||
|
||||
SET ivfflat.iterative_search = on;
|
||||
SET ivfflat.iterative_scan = on;
|
||||
|
||||
SHOW ivfflat.max_probes;
|
||||
|
||||
SET ivfflat.max_probes = -2;
|
||||
SET ivfflat.max_probes = 0;
|
||||
SET ivfflat.max_probes = 32769;
|
||||
|
||||
DROP TABLE t;
|
||||
|
||||
@@ -23,7 +23,7 @@ $node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops
|
||||
my $count = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET ivfflat.probes = 10;
|
||||
SET ivfflat.iterative_search = relaxed_order;
|
||||
SET ivfflat.iterative_scan = relaxed_order;
|
||||
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
|
||||
));
|
||||
is($count, 10);
|
||||
@@ -39,7 +39,7 @@ foreach ((30, 50, 70))
|
||||
$count = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET ivfflat.probes = 10;
|
||||
SET ivfflat.iterative_search = relaxed_order;
|
||||
SET ivfflat.iterative_scan = relaxed_order;
|
||||
SET ivfflat.max_probes = $max_probes;
|
||||
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst WHERE i = $i) LIMIT 11) t;
|
||||
));
|
||||
@@ -19,7 +19,7 @@ sub test_recall
|
||||
my $explain = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET ivfflat.probes = $probes;
|
||||
SET ivfflat.iterative_search = relaxed_order;
|
||||
SET ivfflat.iterative_scan = relaxed_order;
|
||||
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/);
|
||||
@@ -29,7 +29,7 @@ sub test_recall
|
||||
my $actual = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET ivfflat.probes = $probes;
|
||||
SET ivfflat.iterative_search = relaxed_order;
|
||||
SET ivfflat.iterative_scan = relaxed_order;
|
||||
SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[$i]' LIMIT $limit;
|
||||
));
|
||||
my @actual_ids = split("\n", $actual);
|
||||
@@ -26,8 +26,9 @@ $node->safe_psql("postgres", qq(
|
||||
|
||||
my $count = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET hnsw.iterative_search = relaxed_order;
|
||||
SET work_mem = '8MB';
|
||||
SET hnsw.iterative_scan = relaxed_order;
|
||||
SET hnsw.max_scan_tuples = 100000;
|
||||
SET hnsw.scan_mem_multiplier = 2;
|
||||
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
|
||||
));
|
||||
is($count, 10);
|
||||
@@ -42,9 +43,9 @@ foreach ((30000, 50000, 70000))
|
||||
{
|
||||
$count = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET hnsw.iterative_search = relaxed_order;
|
||||
SET hnsw.max_search_tuples = $max_tuples;
|
||||
SET work_mem = '8MB';
|
||||
SET hnsw.iterative_scan = relaxed_order;
|
||||
SET hnsw.max_scan_tuples = $max_tuples;
|
||||
SET hnsw.scan_mem_multiplier = 2;
|
||||
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 += $count;
|
||||
@@ -55,13 +56,4 @@ foreach ((30000, 50000, 70000))
|
||||
cmp_ok($avg, '<', $expected + 2);
|
||||
}
|
||||
|
||||
my ($ret, $stdout, $stderr) = $node->psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET hnsw.iterative_search = relaxed_order;
|
||||
SET client_min_messages = debug1;
|
||||
SET work_mem = '2MB';
|
||||
SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
|
||||
));
|
||||
like($stderr, qr/hnsw index scan exceeded work_mem after \d+ tuples/);
|
||||
|
||||
done_testing();
|
||||
@@ -21,7 +21,7 @@ sub test_recall
|
||||
my $explain = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET hnsw.ef_search = $ef_search;
|
||||
SET hnsw.iterative_search = $mode;
|
||||
SET hnsw.iterative_scan = $mode;
|
||||
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/);
|
||||
@@ -31,7 +31,7 @@ sub test_recall
|
||||
my $actual = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET hnsw.ef_search = $ef_search;
|
||||
SET hnsw.iterative_search = $mode;
|
||||
SET hnsw.iterative_scan = $mode;
|
||||
SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[$i]' LIMIT $limit;
|
||||
));
|
||||
my @actual_ids = split("\n", $actual);
|
||||
@@ -1,4 +1,4 @@
|
||||
comment = 'vector data type and ivfflat and hnsw access methods'
|
||||
default_version = '0.7.4'
|
||||
default_version = '0.8.0'
|
||||
module_pathname = '$libdir/vector'
|
||||
relocatable = true
|
||||
|
||||
Reference in New Issue
Block a user