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https://github.com/pgvector/pgvector.git
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1 Commits
ivfflat-st
...
samples-li
| Author | SHA1 | Date | |
|---|---|---|---|
|
|
64223989cd |
8
.github/workflows/build.yml
vendored
8
.github/workflows/build.yml
vendored
@@ -8,8 +8,6 @@ jobs:
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fail-fast: false
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matrix:
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include:
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- postgres: 17
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os: ubuntu-22.04
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- postgres: 16
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os: ubuntu-22.04
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- postgres: 15
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@@ -23,7 +21,7 @@ jobs:
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- postgres: 11
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os: ubuntu-20.04
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steps:
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- uses: actions/checkout@v4
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- uses: actions/checkout@v3
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- uses: ankane/setup-postgres@v1
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with:
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postgres-version: ${{ matrix.postgres }}
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@@ -45,7 +43,7 @@ jobs:
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runs-on: macos-latest
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if: ${{ !startsWith(github.ref_name, 'windows') }}
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steps:
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- uses: actions/checkout@v4
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- uses: actions/checkout@v3
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- uses: ankane/setup-postgres@v1
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with:
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postgres-version: 14
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@@ -67,7 +65,7 @@ jobs:
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runs-on: windows-latest
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if: ${{ !startsWith(github.ref_name, 'mac') }}
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steps:
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- uses: actions/checkout@v4
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- uses: actions/checkout@v3
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- uses: ankane/setup-postgres@v1
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with:
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postgres-version: 14
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@@ -11,6 +11,7 @@
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#include "miscadmin.h"
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#include "storage/bufmgr.h"
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#include "tcop/tcopprot.h"
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#include "utils/datum.h"
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#include "utils/memutils.h"
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#if PG_VERSION_NUM >= 140000
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@@ -65,11 +66,18 @@
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static void
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AddSample(Datum *values, IvfflatBuildState * buildstate)
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{
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VectorArray samples = buildstate->samples;
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int targsamples = samples->maxlen;
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MemoryContext oldCtx;
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Datum value;
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int targsamples = buildstate->targsamples;
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/* Use memory context since detoast can allocate */
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oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
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/* Detoast once for all calls */
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Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
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value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
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/* Restore memory context */
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MemoryContextSwitchTo(oldCtx);
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/*
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* Normalize with KMEANS_NORM_PROC since spherical distance function
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@@ -81,18 +89,23 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
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return;
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}
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if (samples->length < targsamples)
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{
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VectorArraySet(samples, samples->length, DatumGetVector(value));
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samples->length++;
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}
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/* Copy datum */
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value = datumCopy(value, false, -1);
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/* Reset memory context */
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MemoryContextReset(buildstate->tmpCtx);
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if (list_length(buildstate->samples) < targsamples)
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buildstate->samples = lappend(buildstate->samples, DatumGetVector(value));
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else
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{
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if (buildstate->rowstoskip < 0)
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buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, samples->length, targsamples);
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buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, list_length(buildstate->samples), targsamples);
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if (buildstate->rowstoskip <= 0)
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{
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ListCell *lc;
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#if PG_VERSION_NUM >= 150000
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int k = (int) (targsamples * sampler_random_fract(&buildstate->rstate.randstate));
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#else
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@@ -100,7 +113,8 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
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#endif
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Assert(k >= 0 && k < targsamples);
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VectorArraySet(samples, k, DatumGetVector(value));
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lc = list_nth_cell(buildstate->samples, k);
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lfirst(lc) = DatumGetVector(value);
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}
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buildstate->rowstoskip -= 1;
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@@ -115,21 +129,13 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
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bool *isnull, bool tupleIsAlive, void *state)
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{
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IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
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MemoryContext oldCtx;
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/* Skip nulls */
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if (isnull[0])
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return;
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/* Use memory context since detoast can allocate */
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oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
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/* Add sample */
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AddSample(values, state);
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/* Reset memory context */
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MemoryContextSwitchTo(oldCtx);
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MemoryContextReset(buildstate->tmpCtx);
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AddSample(values, buildstate);
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}
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/*
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@@ -138,7 +144,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
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static void
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SampleRows(IvfflatBuildState * buildstate)
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{
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int targsamples = buildstate->samples->maxlen;
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int targsamples = buildstate->targsamples;
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BlockNumber totalblocks = RelationGetNumberOfBlocks(buildstate->heap);
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buildstate->rowstoskip = -1;
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@@ -287,7 +293,7 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
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#else
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TupleTableSlot *slot = MakeSingleTupleTableSlot(buildstate->tupdesc);
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#endif
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TupleDesc tupdesc = IvfflatTupleDesc(index);
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TupleDesc tupdesc = RelationGetDescr(index);
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UpdateProgress(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_LOAD);
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@@ -339,8 +345,6 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
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/* Set the start and insert pages */
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IvfflatUpdateList(index, buildstate->listInfo[i], insertPage, InvalidBlockNumber, startPage, forkNum);
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}
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FreeTupleDesc(tupdesc);
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}
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/*
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@@ -451,12 +455,13 @@ ComputeCenters(IvfflatBuildState * buildstate)
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/* Sample rows */
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/* TODO Ensure within maintenance_work_mem */
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buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions);
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buildstate->samples = NIL;
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buildstate->targsamples = numSamples;
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if (buildstate->heap != NULL)
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{
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SampleRows(buildstate);
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if (buildstate->samples->length < buildstate->lists)
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if (list_length(buildstate->samples) < buildstate->lists)
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{
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ereport(NOTICE,
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(errmsg("ivfflat index created with little data"),
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@@ -469,7 +474,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
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IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers));
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/* Free samples before we allocate more memory */
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VectorArrayFree(buildstate->samples);
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list_free_deep(buildstate->samples);
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}
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/*
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@@ -80,6 +80,10 @@
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#define RandomInt() random()
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#endif
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#if PG_VERSION_NUM < 130000
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#define list_sort(list, cmp) list_qsort(list, cmp)
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#endif
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/* Variables */
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extern int ivfflat_probes;
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@@ -178,7 +182,8 @@ typedef struct IvfflatBuildState
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Oid collation;
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/* Variables */
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VectorArray samples;
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List *samples;
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int targsamples;
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VectorArray centers;
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ListInfo *listInfo;
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Vector *normvec;
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@@ -274,7 +279,7 @@ typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
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VectorArray VectorArrayInit(int maxlen, int dimensions);
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void VectorArrayFree(VectorArray arr);
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void PrintVectorArray(char *msg, VectorArray arr);
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void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
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void IvfflatKmeans(Relation index, List *samples, VectorArray centers);
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FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
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bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
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int IvfflatGetLists(Relation index);
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@@ -287,7 +292,6 @@ void IvfflatInitPage(Buffer buf, Page page);
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void IvfflatInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state);
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void IvfflatInit(void);
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PGDLLEXPORT void IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc);
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TupleDesc IvfflatTupleDesc(Relation index);
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/* Index access methods */
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IndexBuildResult *ivfflatbuild(Relation heap, Relation index, IndexInfo *indexInfo);
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@@ -94,7 +94,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
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originalInsertPage = insertPage;
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/* Form tuple */
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itup = index_form_tuple(IvfflatTupleDesc(index), &value, isnull);
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itup = index_form_tuple(RelationGetDescr(index), &value, isnull);
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itup->t_tid = *heap_tid;
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/* Get tuple size */
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@@ -12,20 +12,20 @@
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* https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf
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*/
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static void
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InitCenters(Relation index, VectorArray samples, VectorArray centers, float *lowerBound)
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InitCenters(Relation index, List *samples, VectorArray centers, float *lowerBound)
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{
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FmgrInfo *procinfo;
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Oid collation;
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int64 j;
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float *weight = palloc(samples->length * sizeof(float));
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float *weight = palloc(list_length(samples) * sizeof(float));
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int numCenters = centers->maxlen;
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int numSamples = samples->length;
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int numSamples = list_length(samples);
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procinfo = index_getprocinfo(index, 1, IVFFLAT_KMEANS_DISTANCE_PROC);
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collation = index->rd_indcollation[0];
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/* Choose an initial center uniformly at random */
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VectorArraySet(centers, 0, VectorArrayGet(samples, RandomInt() % samples->length));
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VectorArraySet(centers, 0, list_nth(samples, RandomInt() % list_length(samples)));
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centers->length++;
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for (j = 0; j < numSamples; j++)
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@@ -42,7 +42,7 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
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for (j = 0; j < numSamples; j++)
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{
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Vector *vec = VectorArrayGet(samples, j);
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Vector *vec = list_nth(samples, j);
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double distance;
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/* Only need to compute distance for new center */
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@@ -74,7 +74,7 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
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break;
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}
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VectorArraySet(centers, i + 1, VectorArrayGet(samples, j));
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VectorArraySet(centers, i + 1, list_nth(samples, j));
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centers->length++;
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}
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@@ -106,25 +106,41 @@ CompareVectors(const void *a, const void *b)
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return vector_cmp_internal((Vector *) a, (Vector *) b);
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}
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/*
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* Compare list vectors
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*/
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static int
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#if PG_VERSION_NUM >= 130000
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CompareListVectors(const ListCell *a, const ListCell *b)
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#else
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CompareListVectors(const void *a, const void *b)
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#endif
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{
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Vector *va = lfirst((ListCell *) a);
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Vector *vb = lfirst((ListCell *) b);
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return CompareVectors(va, vb);
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}
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/*
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* Quick approach if we have little data
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*/
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static void
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QuickCenters(Relation index, VectorArray samples, VectorArray centers)
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QuickCenters(Relation index, List *samples, VectorArray centers)
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{
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int dimensions = centers->dim;
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Oid collation = index->rd_indcollation[0];
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FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
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/* Copy existing vectors while avoiding duplicates */
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if (samples->length > 0)
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if (list_length(samples) > 0)
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{
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qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
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for (int i = 0; i < samples->length; i++)
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list_sort(samples, CompareListVectors);
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for (int i = 0; i < list_length(samples); i++)
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{
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Vector *vec = VectorArrayGet(samples, i);
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Vector *vec = list_nth(samples, i);
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if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
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if (i == 0 || CompareVectors(vec, list_nth(samples, i - 1)) != 0)
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{
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VectorArraySet(centers, centers->length, vec);
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centers->length++;
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@@ -160,7 +176,7 @@ QuickCenters(Relation index, VectorArray samples, VectorArray centers)
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* https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
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*/
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static void
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ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
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ElkanKmeans(Relation index, List *samples, VectorArray centers)
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{
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FmgrInfo *procinfo;
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FmgrInfo *normprocinfo;
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@@ -171,7 +187,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
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int64 k;
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int dimensions = centers->dim;
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int numCenters = centers->maxlen;
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int numSamples = samples->length;
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int numSamples = list_length(samples);
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VectorArray newCenters;
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int *centerCounts;
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int *closestCenters;
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@@ -182,7 +198,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
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float *newcdist;
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/* Calculate allocation sizes */
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Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->dim);
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Size samplesSize = 0;
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Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->dim);
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Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, dimensions);
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Size centerCountsSize = sizeof(int) * numCenters;
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@@ -326,7 +342,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
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if (upperBound[j] <= halfcdist[closestCenters[j] * numCenters + k])
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continue;
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vec = VectorArrayGet(samples, j);
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vec = list_nth(samples, j);
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/* Step 3a */
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if (rj)
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@@ -377,7 +393,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
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{
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int closestCenter;
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vec = VectorArrayGet(samples, j);
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vec = list_nth(samples, j);
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closestCenter = closestCenters[j];
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/* Increment sum and count of closest center */
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@@ -514,9 +530,9 @@ CheckCenters(Relation index, VectorArray centers)
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* We use spherical k-means for inner product and cosine
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*/
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void
|
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IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers)
|
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IvfflatKmeans(Relation index, List *samples, VectorArray centers)
|
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{
|
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if (samples->length <= centers->maxlen)
|
||||
if (list_length(samples) <= centers->maxlen)
|
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QuickCenters(index, samples, centers);
|
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else
|
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ElkanKmeans(index, samples, centers);
|
||||
|
||||
@@ -4,10 +4,6 @@
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#include "storage/bufmgr.h"
|
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#include "vector.h"
|
||||
|
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#if PG_VERSION_NUM < 130000
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#define TYPSTORAGE_PLAIN 'p'
|
||||
#endif
|
||||
|
||||
/*
|
||||
* Allocate a vector array
|
||||
*/
|
||||
@@ -242,17 +238,3 @@ IvfflatUpdateList(Relation index, ListInfo listInfo,
|
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UnlockReleaseBuffer(buf);
|
||||
}
|
||||
}
|
||||
|
||||
/*
|
||||
* Get the tuple descriptor
|
||||
*/
|
||||
TupleDesc
|
||||
IvfflatTupleDesc(Relation index)
|
||||
{
|
||||
TupleDesc tupdesc = CreateTupleDescCopyConstr(RelationGetDescr(index));
|
||||
|
||||
/* Prevent compression */
|
||||
TupleDescAttr(tupdesc, 0)->attstorage = TYPSTORAGE_PLAIN;
|
||||
|
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return tupdesc;
|
||||
}
|
||||
|
||||
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