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cb108ebfd2 |
@@ -1,6 +1,6 @@
|
||||
root = true
|
||||
|
||||
[*.{c,h}]
|
||||
[*.{c,h,pl}]
|
||||
indent_style = tab
|
||||
indent_size = tab
|
||||
tab_width = 4
|
||||
|
||||
10
CHANGELOG.md
10
CHANGELOG.md
@@ -1,3 +1,13 @@
|
||||
## 0.2.6 (2022-05-22)
|
||||
|
||||
- Improved performance of index creation for Postgres < 12
|
||||
|
||||
## 0.2.5 (2022-02-11)
|
||||
|
||||
- Reduced memory usage during index creation
|
||||
- Fixed index creation exceeding `maintenance_work_mem`
|
||||
- Fixed error with index creation when lists > 1600
|
||||
|
||||
## 0.2.4 (2022-02-06)
|
||||
|
||||
- Added support for parallel vacuum
|
||||
|
||||
@@ -2,7 +2,7 @@
|
||||
"name": "vector",
|
||||
"abstract": "Open-source vector similarity search for Postgres",
|
||||
"description": "Supports L2 distance, inner product, and cosine distance",
|
||||
"version": "0.2.4",
|
||||
"version": "0.2.6",
|
||||
"maintainer": [
|
||||
"Andrew Kane <andrew@ankane.org>"
|
||||
],
|
||||
@@ -20,7 +20,7 @@
|
||||
"vector": {
|
||||
"file": "sql/vector.sql",
|
||||
"docfile": "README.md",
|
||||
"version": "0.2.4",
|
||||
"version": "0.2.6",
|
||||
"abstract": "Open-source vector similarity search for Postgres"
|
||||
}
|
||||
},
|
||||
|
||||
4
Makefile
4
Makefile
@@ -1,5 +1,5 @@
|
||||
EXTENSION = vector
|
||||
EXTVERSION = 0.2.4
|
||||
EXTVERSION = 0.2.6
|
||||
|
||||
MODULE_big = vector
|
||||
DATA = $(wildcard sql/*--*.sql)
|
||||
@@ -21,7 +21,7 @@ endif
|
||||
# For auto-vectorization:
|
||||
# - GCC (needs -ftree-vectorize OR -O3) - https://gcc.gnu.org/projects/tree-ssa/vectorization.html
|
||||
# - Clang (could use pragma instead) - https://llvm.org/docs/Vectorizers.html
|
||||
PG_CFLAGS = $(OPTFLAGS) -ftree-vectorize -fassociative-math -fno-signed-zeros -fno-trapping-math
|
||||
PG_CFLAGS += $(OPTFLAGS) -ftree-vectorize -fassociative-math -fno-signed-zeros -fno-trapping-math
|
||||
|
||||
# Debug GCC auto-vectorization
|
||||
# PG_CFLAGS += -fopt-info-vec
|
||||
|
||||
25
README.md
25
README.md
@@ -17,7 +17,7 @@ Supports L2 distance, inner product, and cosine distance
|
||||
Compile and install the extension (supports Postgres 9.6+)
|
||||
|
||||
```sh
|
||||
git clone --branch v0.2.4 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.2.6 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
make
|
||||
make install # may need sudo
|
||||
@@ -77,19 +77,7 @@ Cosine distance
|
||||
CREATE INDEX ON table USING ivfflat (column vector_cosine_ops);
|
||||
```
|
||||
|
||||
Indexes should be created after the table has data for optimal clustering. If the distribution of data changes significantly, you can reindex without downtime:
|
||||
|
||||
```sql
|
||||
-- Postgres 12+
|
||||
REINDEX INDEX CONCURRENTLY index_name;
|
||||
|
||||
-- Postgres < 12
|
||||
CREATE INDEX CONCURRENTLY temp_name ON table USING ivfflat (column opclass);
|
||||
DROP INDEX CONCURRENTLY index_name;
|
||||
ALTER INDEX temp_name RENAME TO index_name;
|
||||
```
|
||||
|
||||
Also, unlike typical indexes which only affect performance, you may see different results for queries after adding an approximate index.
|
||||
Indexes should be created after the table has some data for optimal clustering. Also, unlike typical indexes which only affect performance, you may see different results for queries after adding an approximate index.
|
||||
|
||||
### Index Options
|
||||
|
||||
@@ -194,6 +182,7 @@ Libraries that use pgvector:
|
||||
|
||||
- [pgvector-python](https://github.com/pgvector/pgvector-python) (Python)
|
||||
- [Neighbor](https://github.com/ankane/neighbor) (Ruby)
|
||||
- [pgvector-ruby](https://github.com/pgvector/pgvector-ruby) (Ruby)
|
||||
- [pgvector-node](https://github.com/pgvector/pgvector-node) (Node.js)
|
||||
- [pgvector-go](https://github.com/pgvector/pgvector-go) (Go)
|
||||
- [pgvector-rust](https://github.com/pgvector/pgvector-rust) (Rust)
|
||||
@@ -231,7 +220,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres).
|
||||
You can also build the image manually
|
||||
|
||||
```sh
|
||||
git clone --branch v0.2.4 https://github.com/pgvector/pgvector.git
|
||||
git clone --branch v0.2.6 https://github.com/pgvector/pgvector.git
|
||||
cd pgvector
|
||||
docker build -t pgvector .
|
||||
```
|
||||
@@ -315,6 +304,12 @@ make installcheck REGRESS=functions # regression test
|
||||
make prove_installcheck PROVE_TESTS=test/t/001_wal.pl # TAP test
|
||||
```
|
||||
|
||||
To enable benchmarking:
|
||||
|
||||
```sh
|
||||
make clean && PG_CFLAGS=-DIVFFLAT_BENCH make && make install
|
||||
```
|
||||
|
||||
Resources for contributors
|
||||
|
||||
- [Extension Building Infrastructure](https://www.postgresql.org/docs/current/extend-pgxs.html)
|
||||
|
||||
2
sql/vector--0.2.4--0.2.5.sql
Normal file
2
sql/vector--0.2.4--0.2.5.sql
Normal file
@@ -0,0 +1,2 @@
|
||||
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
|
||||
\echo Use "ALTER EXTENSION vector UPDATE TO '0.2.5'" to load this file. \quit
|
||||
2
sql/vector--0.2.5--0.2.6.sql
Normal file
2
sql/vector--0.2.5--0.2.6.sql
Normal file
@@ -0,0 +1,2 @@
|
||||
-- complain if script is sourced in psql, rather than via CREATE EXTENSION
|
||||
\echo Use "ALTER EXTENSION vector UPDATE TO '0.2.6'" to load this file. \quit
|
||||
123
src/ivfbuild.c
123
src/ivfbuild.c
@@ -36,16 +36,11 @@
|
||||
#define CALLBACK_ITEM_POINTER HeapTuple hup
|
||||
#endif
|
||||
|
||||
/*
|
||||
* Update build phase progress
|
||||
*/
|
||||
static inline void
|
||||
UpdateProgress(int index, int64 val)
|
||||
{
|
||||
#if PG_VERSION_NUM >= 120000
|
||||
pgstat_progress_update_param(index, val);
|
||||
#define UpdateProgress(index, val) pgstat_progress_update_param(index, val)
|
||||
#else
|
||||
#define UpdateProgress(index, val) ((void)val)
|
||||
#endif
|
||||
}
|
||||
|
||||
/*
|
||||
* Callback for sampling
|
||||
@@ -117,13 +112,13 @@ SampleRows(IvfflatBuildState * buildstate)
|
||||
|
||||
#if PG_VERSION_NUM >= 120000
|
||||
table_index_build_range_scan(buildstate->heap, buildstate->index, buildstate->indexInfo,
|
||||
false, true, true, targblock, 1, SampleCallback, (void *) buildstate, NULL);
|
||||
false, true, false, targblock, 1, SampleCallback, (void *) buildstate, NULL);
|
||||
#elif PG_VERSION_NUM >= 110000
|
||||
IndexBuildHeapRangeScan(buildstate->heap, buildstate->index, buildstate->indexInfo,
|
||||
true, true, targblock, 1, SampleCallback, (void *) buildstate, NULL);
|
||||
false, true, targblock, 1, SampleCallback, (void *) buildstate, NULL);
|
||||
#else
|
||||
IndexBuildHeapRangeScan(buildstate->heap, buildstate->index, buildstate->indexInfo,
|
||||
true, true, targblock, 1, SampleCallback, (void *) buildstate);
|
||||
false, true, targblock, 1, SampleCallback, (void *) buildstate);
|
||||
#endif
|
||||
}
|
||||
}
|
||||
@@ -170,16 +165,20 @@ BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
|
||||
}
|
||||
}
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
buildstate->inertia += minDistance;
|
||||
buildstate->listSums[closestCenter] += minDistance;
|
||||
buildstate->listCounts[closestCenter]++;
|
||||
#endif
|
||||
|
||||
/* Create a virtual tuple */
|
||||
ExecClearTuple(slot);
|
||||
slot->tts_values[0] = Int32GetDatum(closestCenter);
|
||||
slot->tts_isnull[0] = false;
|
||||
slot->tts_values[1] = Int32GetDatum(ItemPointerGetBlockNumberNoCheck(tid));
|
||||
slot->tts_values[1] = PointerGetDatum(tid);
|
||||
slot->tts_isnull[1] = false;
|
||||
slot->tts_values[2] = Int32GetDatum(ItemPointerGetOffsetNumberNoCheck(tid));
|
||||
slot->tts_values[2] = value;
|
||||
slot->tts_isnull[2] = false;
|
||||
slot->tts_values[3] = value;
|
||||
slot->tts_isnull[3] = false;
|
||||
ExecStoreVirtualTuple(slot);
|
||||
|
||||
/*
|
||||
@@ -201,8 +200,6 @@ GetNextTuple(Tuplesortstate *sortstate, TupleDesc tupdesc, TupleTableSlot *slot,
|
||||
{
|
||||
Datum value;
|
||||
bool isnull;
|
||||
int tupblk;
|
||||
int tupoff;
|
||||
|
||||
#if PG_VERSION_NUM >= 100000
|
||||
if (tuplesort_gettupleslot(sortstate, true, false, slot, NULL))
|
||||
@@ -211,13 +208,11 @@ GetNextTuple(Tuplesortstate *sortstate, TupleDesc tupdesc, TupleTableSlot *slot,
|
||||
#endif
|
||||
{
|
||||
*list = DatumGetInt32(slot_getattr(slot, 1, &isnull));
|
||||
tupblk = DatumGetInt32(slot_getattr(slot, 2, &isnull));
|
||||
tupoff = DatumGetInt32(slot_getattr(slot, 3, &isnull));
|
||||
value = slot_getattr(slot, 4, &isnull);
|
||||
value = slot_getattr(slot, 3, &isnull);
|
||||
|
||||
/* Form the index tuple */
|
||||
*itup = index_form_tuple(tupdesc, &value, &isnull);
|
||||
ItemPointerSet(&(*itup)->t_tid, tupblk, tupoff);
|
||||
(*itup)->t_tid = *((ItemPointer) DatumGetPointer(slot_getattr(slot, 2, &isnull)));
|
||||
}
|
||||
else
|
||||
*list = -1;
|
||||
@@ -326,17 +321,16 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
|
||||
|
||||
/* Create tuple description for sorting */
|
||||
#if PG_VERSION_NUM >= 120000
|
||||
buildstate->tupdesc = CreateTemplateTupleDesc(4);
|
||||
buildstate->tupdesc = CreateTemplateTupleDesc(3);
|
||||
#else
|
||||
buildstate->tupdesc = CreateTemplateTupleDesc(4, false);
|
||||
buildstate->tupdesc = CreateTemplateTupleDesc(3, false);
|
||||
#endif
|
||||
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 1, "list", INT4OID, -1, 0);
|
||||
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 2, "blkno", INT4OID, -1, 0);
|
||||
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 3, "offset", INT4OID, -1, 0);
|
||||
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
|
||||
#if PG_VERSION_NUM >= 110000
|
||||
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 4, "vector", RelationGetDescr(index)->attrs[0].atttypid, -1, 0);
|
||||
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 3, "vector", RelationGetDescr(index)->attrs[0].atttypid, -1, 0);
|
||||
#else
|
||||
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 4, "vector", RelationGetDescr(index)->attrs[0]->atttypid, -1, 0);
|
||||
TupleDescInitEntry(buildstate->tupdesc, (AttrNumber) 3, "vector", RelationGetDescr(index)->attrs[0]->atttypid, -1, 0);
|
||||
#endif
|
||||
|
||||
#if PG_VERSION_NUM >= 120000
|
||||
@@ -350,6 +344,12 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
|
||||
|
||||
/* Reuse for each tuple */
|
||||
buildstate->normvec = InitVector(buildstate->dimensions);
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
buildstate->inertia = 0;
|
||||
buildstate->listSums = palloc0(sizeof(double) * buildstate->lists);
|
||||
buildstate->listCounts = palloc0(sizeof(int) * buildstate->lists);
|
||||
#endif
|
||||
}
|
||||
|
||||
/*
|
||||
@@ -361,6 +361,11 @@ FreeBuildState(IvfflatBuildState * buildstate)
|
||||
pfree(buildstate->centers);
|
||||
pfree(buildstate->listInfo);
|
||||
pfree(buildstate->normvec);
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
pfree(buildstate->listSums);
|
||||
pfree(buildstate->listCounts);
|
||||
#endif
|
||||
}
|
||||
|
||||
/*
|
||||
@@ -377,14 +382,19 @@ ComputeCenters(IvfflatBuildState * buildstate)
|
||||
if (numSamples < 10000)
|
||||
numSamples = 10000;
|
||||
|
||||
/* Sample samples */
|
||||
/* Skip samples for unlogged table */
|
||||
if (buildstate->heap == NULL)
|
||||
numSamples = 1;
|
||||
|
||||
/* Sample rows */
|
||||
/* TODO Ensure within maintenance_work_mem */
|
||||
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions);
|
||||
if (buildstate->heap != NULL)
|
||||
SampleRows(buildstate);
|
||||
|
||||
/* Calculate centers */
|
||||
UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_KMEANS);
|
||||
IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers);
|
||||
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers));
|
||||
|
||||
/* Free samples before we allocate more memory */
|
||||
pfree(buildstate->samples);
|
||||
@@ -463,6 +473,51 @@ CreateListPages(Relation index, VectorArray centers, int dimensions,
|
||||
pfree(list);
|
||||
}
|
||||
|
||||
/*
|
||||
* Print k-means metrics
|
||||
*/
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
static void
|
||||
PrintKmeansMetrics(IvfflatBuildState * buildstate)
|
||||
{
|
||||
elog(INFO, "inertia: %.3e", buildstate->inertia);
|
||||
|
||||
/* Calculate Davies-Bouldin index */
|
||||
if (buildstate->lists > 1)
|
||||
{
|
||||
double db = 0.0;
|
||||
|
||||
/* Calculate average distance */
|
||||
for (int i = 0; i < buildstate->lists; i++)
|
||||
{
|
||||
if (buildstate->listCounts[i] > 0)
|
||||
buildstate->listSums[i] /= buildstate->listCounts[i];
|
||||
}
|
||||
|
||||
for (int i = 0; i < buildstate->lists; i++)
|
||||
{
|
||||
double max = 0.0;
|
||||
double distance;
|
||||
|
||||
for (int j = 0; j < buildstate->lists; j++)
|
||||
{
|
||||
if (j == i)
|
||||
continue;
|
||||
|
||||
distance = DatumGetFloat8(FunctionCall2Coll(buildstate->procinfo, buildstate->collation, PointerGetDatum(VectorArrayGet(buildstate->centers, i)), PointerGetDatum(VectorArrayGet(buildstate->centers, j))));
|
||||
distance = (buildstate->listSums[i] + buildstate->listSums[j]) / distance;
|
||||
|
||||
if (distance > max)
|
||||
max = distance;
|
||||
}
|
||||
db += max;
|
||||
}
|
||||
db /= buildstate->lists;
|
||||
elog(INFO, "davies-bouldin: %.3f", db);
|
||||
}
|
||||
}
|
||||
#endif
|
||||
|
||||
/*
|
||||
* Create entry pages
|
||||
*/
|
||||
@@ -497,8 +552,14 @@ CreateEntryPages(IvfflatBuildState * buildstate, ForkNumber forkNum)
|
||||
#endif
|
||||
}
|
||||
|
||||
/* Sort and insert */
|
||||
/* Sort */
|
||||
tuplesort_performsort(buildstate->sortstate);
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
PrintKmeansMetrics(buildstate);
|
||||
#endif
|
||||
|
||||
/* Insert */
|
||||
InsertTuples(buildstate->index, buildstate, forkNum);
|
||||
tuplesort_end(buildstate->sortstate);
|
||||
}
|
||||
@@ -517,7 +578,7 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
|
||||
/* Create pages */
|
||||
CreateMetaPage(index, buildstate->dimensions, buildstate->lists, forkNum);
|
||||
CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo);
|
||||
CreateEntryPages(buildstate, forkNum);
|
||||
IvfflatBench("CreateEntryPages", CreateEntryPages(buildstate, forkNum));
|
||||
|
||||
FreeBuildState(buildstate);
|
||||
}
|
||||
|
||||
@@ -159,6 +159,11 @@ ivfflatvalidate(Oid opclassoid)
|
||||
return true;
|
||||
}
|
||||
|
||||
/*
|
||||
* Define index handler
|
||||
*
|
||||
* See https://www.postgresql.org/docs/current/index-api.html
|
||||
*/
|
||||
PG_FUNCTION_INFO_V1(ivfflathandler);
|
||||
Datum
|
||||
ivfflathandler(PG_FUNCTION_ARGS)
|
||||
@@ -193,6 +198,7 @@ ivfflathandler(PG_FUNCTION_ARGS)
|
||||
#endif
|
||||
amroutine->amkeytype = InvalidOid;
|
||||
|
||||
/* Interface functions */
|
||||
amroutine->ambuild = ivfflatbuild;
|
||||
amroutine->ambuildempty = ivfflatbuildempty;
|
||||
amroutine->aminsert = ivfflatinsert;
|
||||
@@ -206,6 +212,9 @@ ivfflathandler(PG_FUNCTION_ARGS)
|
||||
amroutine->ambuildphasename = ivfflatbuildphasename;
|
||||
#endif
|
||||
amroutine->amvalidate = ivfflatvalidate;
|
||||
#if PG_VERSION_NUM >= 140000
|
||||
amroutine->amadjustmembers = NULL;
|
||||
#endif
|
||||
amroutine->ambeginscan = ivfflatbeginscan;
|
||||
amroutine->amrescan = ivfflatrescan;
|
||||
amroutine->amgettuple = ivfflatgettuple;
|
||||
@@ -213,6 +222,8 @@ ivfflathandler(PG_FUNCTION_ARGS)
|
||||
amroutine->amendscan = ivfflatendscan;
|
||||
amroutine->ammarkpos = NULL;
|
||||
amroutine->amrestrpos = NULL;
|
||||
|
||||
/* Interface functions to support parallel index scans */
|
||||
#if PG_VERSION_NUM >= 100000
|
||||
amroutine->amestimateparallelscan = NULL;
|
||||
amroutine->aminitparallelscan = NULL;
|
||||
|
||||
@@ -10,6 +10,14 @@
|
||||
#include "utils/tuplesort.h"
|
||||
#include "vector.h"
|
||||
|
||||
#ifdef IVFFLAT_BENCH
|
||||
#include "portability/instr_time.h"
|
||||
#endif
|
||||
|
||||
#if PG_VERSION_NUM < 90600
|
||||
#error "Requires PostgreSQL 9.6+"
|
||||
#endif
|
||||
|
||||
/* Support functions */
|
||||
#define IVFFLAT_DISTANCE_PROC 1
|
||||
#define IVFFLAT_NORM_PROC 2
|
||||
@@ -39,9 +47,19 @@
|
||||
#define IvfflatPageGetOpaque(page) ((IvfflatPageOpaque) PageGetSpecialPointer(page))
|
||||
#define IvfflatPageGetMeta(page) ((IvfflatMetaPageData *) PageGetContents(page))
|
||||
|
||||
#if PG_VERSION_NUM < 100000
|
||||
#define ItemPointerGetBlockNumberNoCheck ItemPointerGetBlockNumber
|
||||
#define ItemPointerGetOffsetNumberNoCheck ItemPointerGetOffsetNumber
|
||||
#ifdef IVFFLAT_BENCH
|
||||
#define IvfflatBench(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 IvfflatBench(name, code) (code)
|
||||
#endif
|
||||
|
||||
/* Variables */
|
||||
@@ -97,6 +115,12 @@ typedef struct IvfflatBuildState
|
||||
ListInfo *listInfo;
|
||||
Vector *normvec;
|
||||
|
||||
#ifdef IVFFLAT_KMEANS_DEBUG
|
||||
double inertia;
|
||||
double *listSums;
|
||||
int *listCounts;
|
||||
#endif
|
||||
|
||||
/* Sampling */
|
||||
BlockSamplerData bs;
|
||||
ReservoirStateData rstate;
|
||||
@@ -138,6 +162,7 @@ typedef IvfflatListData * IvfflatList;
|
||||
|
||||
typedef struct IvfflatScanList
|
||||
{
|
||||
pairingheap_node ph_node;
|
||||
BlockNumber startPage;
|
||||
double distance;
|
||||
} IvfflatScanList;
|
||||
@@ -159,6 +184,8 @@ typedef struct IvfflatScanOpaqueData
|
||||
FmgrInfo *normprocinfo;
|
||||
Oid collation;
|
||||
|
||||
/* Lists */
|
||||
pairingheap *listQueue;
|
||||
IvfflatScanList lists[FLEXIBLE_ARRAY_MEMBER]; /* must come last */
|
||||
} IvfflatScanOpaqueData;
|
||||
|
||||
|
||||
@@ -11,7 +11,7 @@
|
||||
* https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf
|
||||
*/
|
||||
static void
|
||||
InitCenters(Relation index, VectorArray samples, VectorArray centers, double *lowerBound)
|
||||
InitCenters(Relation index, VectorArray samples, VectorArray centers, float *lowerBound)
|
||||
{
|
||||
FmgrInfo *procinfo;
|
||||
Oid collation;
|
||||
@@ -21,7 +21,7 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, double *lo
|
||||
double sum;
|
||||
double choice;
|
||||
Vector *vec;
|
||||
double *weight = palloc(samples->length * sizeof(double));
|
||||
float *weight = palloc(samples->length * sizeof(float));
|
||||
int numCenters = centers->maxlen;
|
||||
int numSamples = samples->length;
|
||||
|
||||
@@ -121,15 +121,18 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
|
||||
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
|
||||
|
||||
/* Copy existing vectors while avoiding duplicates */
|
||||
qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
|
||||
for (i = 0; i < samples->length; i++)
|
||||
if (samples->length > 0)
|
||||
{
|
||||
vec = VectorArrayGet(samples, i);
|
||||
|
||||
if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
|
||||
qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
|
||||
for (i = 0; i < samples->length; i++)
|
||||
{
|
||||
VectorArraySet(centers, centers->length, vec);
|
||||
centers->length++;
|
||||
vec = VectorArrayGet(samples, i);
|
||||
|
||||
if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
|
||||
{
|
||||
VectorArraySet(centers, centers->length, vec);
|
||||
centers->length++;
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
@@ -177,11 +180,11 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
|
||||
VectorArray newCenters;
|
||||
int *centerCounts;
|
||||
int *closestCenters;
|
||||
double *lowerBound;
|
||||
double *upperBound;
|
||||
double *s;
|
||||
double *halfcdist;
|
||||
double *newcdist;
|
||||
float *lowerBound;
|
||||
float *upperBound;
|
||||
float *s;
|
||||
float *halfcdist;
|
||||
float *newcdist;
|
||||
int changes;
|
||||
double minDistance;
|
||||
int closestCenter;
|
||||
@@ -191,19 +194,43 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
|
||||
double dxcx;
|
||||
double dxc;
|
||||
|
||||
/* Calculate allocation sizes */
|
||||
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->dim);
|
||||
Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->dim);
|
||||
Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, dimensions);
|
||||
Size centerCountsSize = sizeof(int) * numCenters;
|
||||
Size closestCentersSize = sizeof(int) * numSamples;
|
||||
Size lowerBoundSize = sizeof(float) * numSamples * numCenters;
|
||||
Size upperBoundSize = sizeof(float) * numSamples;
|
||||
Size sSize = sizeof(float) * numCenters;
|
||||
Size halfcdistSize = sizeof(float) * numCenters * numCenters;
|
||||
Size newcdistSize = sizeof(float) * numCenters;
|
||||
|
||||
/* Calculate total size */
|
||||
Size totalSize = samplesSize + centersSize + newCentersSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
|
||||
|
||||
/* Check memory requirements */
|
||||
/* Add one to error message to ceil */
|
||||
if (totalSize / 1024 > maintenance_work_mem)
|
||||
ereport(ERROR,
|
||||
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
|
||||
errmsg("memory required is %zu MB, maintenance_work_mem is %d MB",
|
||||
totalSize / (1024 * 1024) + 1, maintenance_work_mem / 1024)));
|
||||
|
||||
/* Set support functions */
|
||||
procinfo = index_getprocinfo(index, 1, IVFFLAT_KMEANS_DISTANCE_PROC);
|
||||
normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
|
||||
collation = index->rd_indcollation[0];
|
||||
|
||||
/* Allocate space */
|
||||
centerCounts = palloc(sizeof(int) * numCenters);
|
||||
closestCenters = palloc(sizeof(int) * numSamples);
|
||||
lowerBound = palloc(sizeof(double) * numSamples * numCenters);
|
||||
upperBound = palloc(sizeof(double) * numSamples);
|
||||
s = palloc(sizeof(double) * numCenters);
|
||||
halfcdist = palloc(sizeof(double) * numCenters * numCenters);
|
||||
newcdist = palloc(sizeof(double) * numCenters);
|
||||
/* Use float instead of double to save memory */
|
||||
centerCounts = palloc(centerCountsSize);
|
||||
closestCenters = palloc(closestCentersSize);
|
||||
lowerBound = palloc_extended(lowerBoundSize, MCXT_ALLOC_HUGE);
|
||||
upperBound = palloc(upperBoundSize);
|
||||
s = palloc(sSize);
|
||||
halfcdist = palloc(halfcdistSize);
|
||||
newcdist = palloc(newcdistSize);
|
||||
|
||||
newCenters = VectorArrayInit(numCenters, dimensions);
|
||||
for (j = 0; j < numCenters; j++)
|
||||
|
||||
@@ -1,5 +1,7 @@
|
||||
#include "postgres.h"
|
||||
|
||||
#include <float.h>
|
||||
|
||||
#include "access/relscan.h"
|
||||
#include "ivfflat.h"
|
||||
#include "miscadmin.h"
|
||||
@@ -17,14 +19,12 @@
|
||||
* Compare list distances
|
||||
*/
|
||||
static int
|
||||
CompareLists(const void *a, const void *b)
|
||||
CompareLists(const pairingheap_node *a, const pairingheap_node *b, void *arg)
|
||||
{
|
||||
double diff = (((IvfflatScanList *) a)->distance - ((IvfflatScanList *) b)->distance);
|
||||
|
||||
if (diff > 0)
|
||||
if (((const IvfflatScanList *) a)->distance > ((const IvfflatScanList *) b)->distance)
|
||||
return 1;
|
||||
|
||||
if (diff < 0)
|
||||
if (((const IvfflatScanList *) a)->distance < ((const IvfflatScanList *) b)->distance)
|
||||
return -1;
|
||||
|
||||
return 0;
|
||||
@@ -45,6 +45,8 @@ GetScanLists(IndexScanDesc scan, Datum value)
|
||||
int listCount = 0;
|
||||
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
|
||||
double distance;
|
||||
IvfflatScanList *scanlist;
|
||||
double maxDistance = DBL_MAX;
|
||||
|
||||
/* Search all list pages */
|
||||
while (BlockNumberIsValid(nextblkno))
|
||||
@@ -62,21 +64,39 @@ GetScanLists(IndexScanDesc scan, Datum value)
|
||||
/* Use procinfo from the index instead of scan key for performance */
|
||||
distance = DatumGetFloat8(FunctionCall2Coll(so->procinfo, so->collation, PointerGetDatum(&list->center), value));
|
||||
|
||||
so->lists[listCount].startPage = list->startPage;
|
||||
so->lists[listCount].distance = distance;
|
||||
listCount++;
|
||||
if (listCount < so->probes)
|
||||
{
|
||||
scanlist = &so->lists[listCount];
|
||||
scanlist->startPage = list->startPage;
|
||||
scanlist->distance = distance;
|
||||
listCount++;
|
||||
|
||||
/* Add to heap */
|
||||
pairingheap_add(so->listQueue, &scanlist->ph_node);
|
||||
|
||||
/* Calculate max distance */
|
||||
if (listCount == so->probes)
|
||||
maxDistance = ((IvfflatScanList *) pairingheap_first(so->listQueue))->distance;
|
||||
}
|
||||
else if (distance < maxDistance)
|
||||
{
|
||||
/* Remove */
|
||||
scanlist = (IvfflatScanList *) pairingheap_remove_first(so->listQueue);
|
||||
|
||||
/* Reuse */
|
||||
scanlist->startPage = list->startPage;
|
||||
scanlist->distance = distance;
|
||||
pairingheap_add(so->listQueue, &scanlist->ph_node);
|
||||
|
||||
/* Update max distance */
|
||||
maxDistance = ((IvfflatScanList *) pairingheap_first(so->listQueue))->distance;
|
||||
}
|
||||
}
|
||||
|
||||
nextblkno = IvfflatPageGetOpaque(cpage)->nextblkno;
|
||||
|
||||
UnlockReleaseBuffer(cbuf);
|
||||
}
|
||||
|
||||
/* Sort by distance */
|
||||
qsort(so->lists, listCount, sizeof(IvfflatScanList), CompareLists);
|
||||
|
||||
if (so->probes > listCount)
|
||||
so->probes = listCount;
|
||||
}
|
||||
|
||||
/*
|
||||
@@ -94,7 +114,6 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
||||
OffsetNumber maxoffno;
|
||||
Datum datum;
|
||||
bool isnull;
|
||||
int i;
|
||||
TupleDesc tupdesc = RelationGetDescr(scan->indexRelation);
|
||||
|
||||
#if PG_VERSION_NUM >= 120000
|
||||
@@ -111,9 +130,9 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
||||
BufferAccessStrategy bas = GetAccessStrategy(BAS_BULKREAD);
|
||||
|
||||
/* Search closest probes lists */
|
||||
for (i = 0; i < so->probes; i++)
|
||||
while (!pairingheap_is_empty(so->listQueue))
|
||||
{
|
||||
searchPage = so->lists[i].startPage;
|
||||
searchPage = ((IvfflatScanList *) pairingheap_remove_first(so->listQueue))->startPage;
|
||||
|
||||
/* Search all entry pages for list */
|
||||
while (BlockNumberIsValid(searchPage))
|
||||
@@ -137,12 +156,10 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
||||
ExecClearTuple(slot);
|
||||
slot->tts_values[0] = FunctionCall2Coll(so->procinfo, so->collation, datum, value);
|
||||
slot->tts_isnull[0] = false;
|
||||
slot->tts_values[1] = Int32GetDatum((int) ItemPointerGetBlockNumberNoCheck(&itup->t_tid));
|
||||
slot->tts_values[1] = PointerGetDatum(&itup->t_tid);
|
||||
slot->tts_isnull[1] = false;
|
||||
slot->tts_values[2] = Int32GetDatum((int) ItemPointerGetOffsetNumberNoCheck(&itup->t_tid));
|
||||
slot->tts_values[2] = Int32GetDatum((int) searchPage);
|
||||
slot->tts_isnull[2] = false;
|
||||
slot->tts_values[3] = Int32GetDatum((int) searchPage);
|
||||
slot->tts_isnull[3] = false;
|
||||
ExecStoreVirtualTuple(slot);
|
||||
|
||||
tuplesort_puttupleslot(so->sortstate, slot);
|
||||
@@ -153,6 +170,8 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
||||
UnlockReleaseBuffer(buf);
|
||||
}
|
||||
}
|
||||
|
||||
tuplesort_performsort(so->sortstate);
|
||||
}
|
||||
|
||||
/*
|
||||
@@ -168,13 +187,18 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
|
||||
Oid sortOperators[] = {Float8LessOperator};
|
||||
Oid sortCollations[] = {InvalidOid};
|
||||
bool nullsFirstFlags[] = {false};
|
||||
int probes = ivfflat_probes;
|
||||
|
||||
scan = RelationGetIndexScan(index, nkeys, norderbys);
|
||||
lists = IvfflatGetLists(scan->indexRelation);
|
||||
|
||||
so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + lists * sizeof(IvfflatScanList));
|
||||
if (probes > lists)
|
||||
probes = lists;
|
||||
|
||||
so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
|
||||
so->buf = InvalidBuffer;
|
||||
so->first = true;
|
||||
so->probes = probes;
|
||||
|
||||
/* Set support functions */
|
||||
so->procinfo = index_getprocinfo(index, 1, IVFFLAT_DISTANCE_PROC);
|
||||
@@ -183,14 +207,13 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
|
||||
|
||||
/* Create tuple description for sorting */
|
||||
#if PG_VERSION_NUM >= 120000
|
||||
so->tupdesc = CreateTemplateTupleDesc(4);
|
||||
so->tupdesc = CreateTemplateTupleDesc(3);
|
||||
#else
|
||||
so->tupdesc = CreateTemplateTupleDesc(4, false);
|
||||
so->tupdesc = CreateTemplateTupleDesc(3, false);
|
||||
#endif
|
||||
TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
|
||||
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "blkno", INT4OID, -1, 0);
|
||||
TupleDescInitEntry(so->tupdesc, (AttrNumber) 3, "offset", INT4OID, -1, 0);
|
||||
TupleDescInitEntry(so->tupdesc, (AttrNumber) 4, "indexblkno", INT4OID, -1, 0);
|
||||
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
|
||||
TupleDescInitEntry(so->tupdesc, (AttrNumber) 3, "indexblkno", INT4OID, -1, 0);
|
||||
|
||||
/* Prep sort */
|
||||
#if PG_VERSION_NUM >= 110000
|
||||
@@ -205,6 +228,8 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
|
||||
so->slot = MakeSingleTupleTableSlot(so->tupdesc);
|
||||
#endif
|
||||
|
||||
so->listQueue = pairingheap_allocate(CompareLists, scan);
|
||||
|
||||
scan->opaque = so;
|
||||
|
||||
return scan;
|
||||
@@ -224,7 +249,7 @@ ivfflatrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int
|
||||
#endif
|
||||
|
||||
so->first = true;
|
||||
so->probes = ivfflat_probes;
|
||||
pairingheap_reset(so->listQueue);
|
||||
|
||||
if (keys && scan->numberOfKeys > 0)
|
||||
memmove(scan->keyData, keys, scan->numberOfKeys * sizeof(ScanKeyData));
|
||||
@@ -268,9 +293,8 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
return false;
|
||||
}
|
||||
|
||||
GetScanLists(scan, value);
|
||||
GetScanItems(scan, value);
|
||||
tuplesort_performsort(so->sortstate);
|
||||
IvfflatBench("GetScanLists", GetScanLists(scan, value));
|
||||
IvfflatBench("GetScanItems", GetScanItems(scan, value));
|
||||
so->first = false;
|
||||
|
||||
/* Clean up if we allocated a new value */
|
||||
@@ -284,14 +308,13 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
|
||||
if (tuplesort_gettupleslot(so->sortstate, true, so->slot, NULL))
|
||||
#endif
|
||||
{
|
||||
BlockNumber blkno = DatumGetInt32(slot_getattr(so->slot, 2, &so->isnull));
|
||||
OffsetNumber offset = DatumGetInt32(slot_getattr(so->slot, 3, &so->isnull));
|
||||
BlockNumber indexblkno = DatumGetInt32(slot_getattr(so->slot, 4, &so->isnull));
|
||||
ItemPointer tid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
|
||||
BlockNumber indexblkno = DatumGetInt32(slot_getattr(so->slot, 3, &so->isnull));
|
||||
|
||||
#if PG_VERSION_NUM >= 120000
|
||||
ItemPointerSet(&scan->xs_heaptid, blkno, offset);
|
||||
scan->xs_heaptid = *tid;
|
||||
#else
|
||||
ItemPointerSet(&scan->xs_ctup.t_self, blkno, offset);
|
||||
scan->xs_ctup.t_self = *tid;
|
||||
#endif
|
||||
|
||||
if (BufferIsValid(so->buf))
|
||||
@@ -324,6 +347,7 @@ ivfflatendscan(IndexScanDesc scan)
|
||||
if (BufferIsValid(so->buf))
|
||||
ReleaseBuffer(so->buf);
|
||||
|
||||
pairingheap_free(so->listQueue);
|
||||
tuplesort_end(so->sortstate);
|
||||
|
||||
pfree(so);
|
||||
|
||||
@@ -53,3 +53,12 @@ LINE 1: SELECT '[1,]'::vector;
|
||||
^
|
||||
SELECT '[1,2,3]'::vector(2);
|
||||
ERROR: expected 2 dimensions, not 3
|
||||
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
|
||||
unnest
|
||||
---------
|
||||
[1,2,3]
|
||||
[4,5,6]
|
||||
(2 rows)
|
||||
|
||||
SELECT '{"[1,2,3]"}'::vector(2)[];
|
||||
ERROR: expected 2 dimensions, not 3
|
||||
|
||||
@@ -13,3 +13,6 @@ SELECT '1,2,3'::vector;
|
||||
SELECT '[]'::vector;
|
||||
SELECT '[1,]'::vector;
|
||||
SELECT '[1,2,3]'::vector(2);
|
||||
|
||||
SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
|
||||
SELECT '{"[1,2,3]"}'::vector(2)[];
|
||||
|
||||
@@ -34,9 +34,10 @@ sub test_index_replay
|
||||
my $r2 = rand();
|
||||
my $r3 = rand();
|
||||
|
||||
my $queries = qq(SET enable_seqscan=off;
|
||||
SELECT * FROM tst ORDER BY v <-> '[$r1,$r2,$r3]' LIMIT 10;
|
||||
);
|
||||
my $queries = qq(
|
||||
SET enable_seqscan = off;
|
||||
SELECT * FROM tst ORDER BY v <-> '[$r1,$r2,$r3]' LIMIT 10;
|
||||
);
|
||||
|
||||
# Run test queries and compare their result
|
||||
my $primary_result = $node_primary->safe_psql("postgres", $queries);
|
||||
@@ -65,10 +66,9 @@ $node_replica->start;
|
||||
$node_primary->safe_psql("postgres", "CREATE EXTENSION vector;");
|
||||
$node_primary->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector(3));");
|
||||
$node_primary->safe_psql("postgres",
|
||||
"INSERT INTO tst SELECT i%10, ARRAY[random(), random(), random()] FROM generate_series(1,100000) i;"
|
||||
"INSERT INTO tst SELECT i % 10, ARRAY[random(), random(), random()] FROM generate_series(1, 100000) i;"
|
||||
);
|
||||
$node_primary->safe_psql("postgres",
|
||||
"CREATE INDEX ON tst USING ivfflat (v);");
|
||||
$node_primary->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v);");
|
||||
|
||||
# Test that queries give same result
|
||||
test_index_replay('initial');
|
||||
@@ -82,7 +82,7 @@ for my $i (1 .. 10)
|
||||
test_index_replay("vacuum $i");
|
||||
my ($start, $end) = (100001 + ($i - 1) * 10000, 100000 + $i * 10000);
|
||||
$node_primary->safe_psql("postgres",
|
||||
"INSERT INTO tst SELECT i%10, ARRAY[random(), random(), random()] FROM generate_series($start,$end) i;"
|
||||
"INSERT INTO tst SELECT i % 10, ARRAY[random(), random(), random()] FROM generate_series($start, $end) i;"
|
||||
);
|
||||
test_index_replay("insert $i");
|
||||
}
|
||||
|
||||
@@ -13,7 +13,7 @@ $node->start;
|
||||
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
|
||||
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector(3));");
|
||||
$node->safe_psql("postgres",
|
||||
"INSERT INTO tst SELECT i%10, ARRAY[i%1000, i%333, i%55] FROM generate_series(1,100000) i;"
|
||||
"INSERT INTO tst SELECT i % 10, ARRAY[i % 1000, i % 333, i % 55] FROM generate_series(1, 100000) i;"
|
||||
);
|
||||
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v);");
|
||||
|
||||
@@ -24,7 +24,7 @@ my $size = $node->safe_psql("postgres", "SELECT pg_total_relation_size('tst_v_id
|
||||
$node->safe_psql("postgres", "DELETE FROM tst;");
|
||||
$node->safe_psql("postgres", "VACUUM tst;");
|
||||
$node->safe_psql("postgres",
|
||||
"INSERT INTO tst SELECT i%10, ARRAY[i%1000, i%333, i%55] FROM generate_series(1,100000) i;"
|
||||
"INSERT INTO tst SELECT i % 10, ARRAY[i % 1000, i % 333, i % 55] FROM generate_series(1, 100000) i;"
|
||||
);
|
||||
|
||||
# Check size
|
||||
|
||||
88
test/t/003_recall.pl
Normal file
88
test/t/003_recall.pl
Normal file
@@ -0,0 +1,88 @@
|
||||
use strict;
|
||||
use warnings;
|
||||
use PostgresNode;
|
||||
use TestLib;
|
||||
use Test::More tests => 9;
|
||||
|
||||
my $node;
|
||||
my @queries = ();
|
||||
my @expected;
|
||||
my $limit = 20;
|
||||
|
||||
sub test_recall
|
||||
{
|
||||
my ($probes, $min, $operator) = @_;
|
||||
my $correct = 0;
|
||||
my $total = 0;
|
||||
|
||||
for my $i (0 .. $#queries) {
|
||||
my $actual = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SET ivfflat.probes = $probes;
|
||||
SELECT i FROM tst ORDER BY v $operator '$queries[$i]' LIMIT $limit;
|
||||
));
|
||||
my @actual_ids = split("\n", $actual);
|
||||
my %actual_set = map { $_ => 1 } @actual_ids;
|
||||
|
||||
my @expected_ids = split("\n", $expected[$i]);
|
||||
|
||||
foreach (@expected_ids) {
|
||||
if (exists($actual_set{$_})) {
|
||||
$correct++;
|
||||
}
|
||||
$total++;
|
||||
}
|
||||
}
|
||||
|
||||
cmp_ok($correct / $total, ">=", $min, $operator);
|
||||
}
|
||||
|
||||
# Initialize node
|
||||
$node = get_new_node('node');
|
||||
$node->init;
|
||||
$node->start;
|
||||
|
||||
# Create table
|
||||
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
|
||||
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector(3));");
|
||||
$node->safe_psql("postgres",
|
||||
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 100000) i;"
|
||||
);
|
||||
|
||||
# Generate queries
|
||||
for (1..20) {
|
||||
my $r1 = rand();
|
||||
my $r2 = rand();
|
||||
my $r3 = rand();
|
||||
push(@queries, "[$r1,$r2,$r3]");
|
||||
}
|
||||
|
||||
# Check each index type
|
||||
my @operators = ("<->", "<#>", "<=>");
|
||||
|
||||
foreach (@operators) {
|
||||
my $operator = $_;
|
||||
|
||||
# Get exact results
|
||||
@expected = ();
|
||||
foreach (@queries) {
|
||||
my $res = $node->safe_psql("postgres", "SELECT i FROM tst ORDER BY v $operator '$_' LIMIT $limit;");
|
||||
push(@expected, $res);
|
||||
}
|
||||
|
||||
# Add index
|
||||
my $opclass;
|
||||
if ($operator == "<->") {
|
||||
$opclass = "vector_l2_ops";
|
||||
} elsif ($operator == "<#>") {
|
||||
$opclass = "vector_ip_ops";
|
||||
} else {
|
||||
$opclass = "vector_cosine_ops";
|
||||
}
|
||||
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v $opclass);");
|
||||
|
||||
# Test approximate results
|
||||
test_recall(1, 0.75, $operator);
|
||||
test_recall(10, 0.95, $operator);
|
||||
test_recall(100, 1.0, $operator);
|
||||
}
|
||||
36
test/t/004_centers.pl
Normal file
36
test/t/004_centers.pl
Normal file
@@ -0,0 +1,36 @@
|
||||
use strict;
|
||||
use warnings;
|
||||
use PostgresNode;
|
||||
use TestLib;
|
||||
use Test::More tests => 3;
|
||||
|
||||
# Initialize node
|
||||
my $node = get_new_node('node');
|
||||
$node->init;
|
||||
$node->start;
|
||||
|
||||
# Create table
|
||||
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
|
||||
$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector(3));");
|
||||
$node->safe_psql("postgres",
|
||||
"INSERT INTO tst SELECT i, '[1,2,3]' FROM generate_series(1, 10) i;"
|
||||
);
|
||||
|
||||
sub test_centers
|
||||
{
|
||||
my ($lists, $min) = @_;
|
||||
|
||||
my ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING ivfflat (v) WITH (lists = $lists);");
|
||||
is($ret, 0, $stderr);
|
||||
}
|
||||
|
||||
# Test no error for duplicate centers
|
||||
test_centers(5);
|
||||
test_centers(10);
|
||||
|
||||
$node->safe_psql("postgres",
|
||||
"INSERT INTO tst SELECT i, '[4,5,6]' FROM generate_series(1, 10) i;"
|
||||
);
|
||||
|
||||
# Test no error for duplicate centers
|
||||
test_centers(10);
|
||||
45
test/t/005_query_recall.pl
Normal file
45
test/t/005_query_recall.pl
Normal file
@@ -0,0 +1,45 @@
|
||||
use strict;
|
||||
use warnings;
|
||||
use PostgresNode;
|
||||
use TestLib;
|
||||
use Test::More tests => 60;
|
||||
|
||||
# Initialize node
|
||||
my $node = get_new_node('node');
|
||||
$node->init;
|
||||
$node->start;
|
||||
|
||||
# Create table
|
||||
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
|
||||
$node->safe_psql("postgres", "CREATE TABLE tst (i int4 primary key, v vector(3));");
|
||||
$node->safe_psql("postgres",
|
||||
"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 100000) i;"
|
||||
);
|
||||
|
||||
# Check each index type
|
||||
my @operators = ("<->", "<#>", "<=>");
|
||||
foreach (@operators) {
|
||||
my $operator = $_;
|
||||
|
||||
# Add index
|
||||
my $opclass;
|
||||
if ($operator == "<->") {
|
||||
$opclass = "vector_l2_ops";
|
||||
} elsif ($operator == "<#>") {
|
||||
$opclass = "vector_ip_ops";
|
||||
} else {
|
||||
$opclass = "vector_cosine_ops";
|
||||
}
|
||||
$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v $opclass);");
|
||||
|
||||
# Test 100% recall
|
||||
for (1..20) {
|
||||
my $i = int(rand() * 100000);
|
||||
my $query = $node->safe_psql("postgres", "SELECT v FROM tst WHERE i = $i;");
|
||||
my $res = $node->safe_psql("postgres", qq(
|
||||
SET enable_seqscan = off;
|
||||
SELECT v FROM tst ORDER BY v <-> '$query' LIMIT 1;
|
||||
));
|
||||
is($res, $query);
|
||||
}
|
||||
}
|
||||
31
test/t/006_lists.pl
Normal file
31
test/t/006_lists.pl
Normal file
@@ -0,0 +1,31 @@
|
||||
use strict;
|
||||
use warnings;
|
||||
use PostgresNode;
|
||||
use TestLib;
|
||||
use Test::More tests => 3;
|
||||
|
||||
# Initialize node
|
||||
my $node = get_new_node('node');
|
||||
$node->init;
|
||||
$node->start;
|
||||
|
||||
# Create table
|
||||
$node->safe_psql("postgres", "CREATE EXTENSION vector;");
|
||||
$node->safe_psql("postgres", "CREATE TABLE tst (v vector(3));");
|
||||
$node->safe_psql("postgres",
|
||||
"INSERT INTO tst SELECT ARRAY[random(), random(), random()] FROM generate_series(1, 100000) i;"
|
||||
);
|
||||
|
||||
$node->safe_psql("postgres", "CREATE INDEX lists50 ON tst USING ivfflat (v) WITH (lists = 50);");
|
||||
$node->safe_psql("postgres", "CREATE INDEX lists100 ON tst USING ivfflat (v) WITH (lists = 100);");
|
||||
|
||||
# Test prefers more lists
|
||||
my $res = $node->safe_psql("postgres", "EXPLAIN SELECT v FROM tst ORDER BY v <-> '[0.5,0.5,0.5]' LIMIT 10;");
|
||||
like($res, qr/lists100/);
|
||||
unlike($res, qr/lists50/);
|
||||
|
||||
# Test errors with too much memory
|
||||
my ($ret, $stdout, $stderr) = $node->psql("postgres",
|
||||
"CREATE INDEX lists10000 ON tst USING ivfflat (v) WITH (lists = 10000);"
|
||||
);
|
||||
like($stderr, qr/memory required is/);
|
||||
@@ -1,4 +1,4 @@
|
||||
comment = 'vector data type and ivfflat access method'
|
||||
default_version = '0.2.4'
|
||||
default_version = '0.2.6'
|
||||
module_pathname = '$libdir/vector'
|
||||
relocatable = true
|
||||
|
||||
Reference in New Issue
Block a user