No need to set heap id [skip ci]

.github/workflows/build.yml

@@ -8,6 +8,8 @@ jobs:
       fail-fast: false
       matrix:
         include:
+          - postgres: 17
+            os: ubuntu-22.04
           - postgres: 16
             os: ubuntu-22.04
           - postgres: 15
@@ -21,7 +23,7 @@ jobs:
           - postgres: 11
             os: ubuntu-20.04
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - uses: ankane/setup-postgres@v1
         with:
           postgres-version: ${{ matrix.postgres }}
@@ -43,7 +45,7 @@ jobs:
     runs-on: macos-latest
     if: ${{ !startsWith(github.ref_name, 'windows') }}
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - uses: ankane/setup-postgres@v1
         with:
           postgres-version: 14
@@ -65,7 +67,7 @@ jobs:
     runs-on: windows-latest
     if: ${{ !startsWith(github.ref_name, 'mac') }}
     steps:
-      - uses: actions/checkout@v3
+      - uses: actions/checkout@v4
       - uses: ankane/setup-postgres@v1
         with:
           postgres-version: 14

src/hnsw.c

@@ -155,6 +155,15 @@ hnswvalidate(Oid opclassoid)
 	return true;
 }
 
+/*
+ * Checks if index-only scan is supported
+ */
+static bool
+hnswcanreturn(Relation indexRelation, int attno)
+{
+	return attno == 1 && !OidIsValid(index_getprocid(indexRelation, 1, HNSW_NORM_PROC));
+}
+
 /*
  * Define index handler
  *
@@ -196,7 +205,7 @@ hnswhandler(PG_FUNCTION_ARGS)
 	amroutine->aminsert = hnswinsert;
 	amroutine->ambulkdelete = hnswbulkdelete;
 	amroutine->amvacuumcleanup = hnswvacuumcleanup;
-	amroutine->amcanreturn = NULL;
+	amroutine->amcanreturn = hnswcanreturn;
 	amroutine->amcostestimate = hnswcostestimate;
 	amroutine->amoptions = hnswoptions;
 	amroutine->amproperty = NULL;	/* TODO AMPROP_DISTANCE_ORDERABLE */

src/hnsw.h

@@ -269,7 +269,7 @@ Buffer		HnswNewBuffer(Relation index, ForkNumber forkNum);
 void		HnswInitPage(Buffer buf, Page page);
 void		HnswInitRegisterPage(Relation index, Buffer *buf, Page *page, GenericXLogState **state);
 void		HnswInit(void);
-List	   *HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement);
+List	   *HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool loadVec, HnswElement skipElement);
 HnswElement HnswGetEntryPoint(Relation index);
 void		HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint);
 HnswElement HnswInitElement(ItemPointer tid, int m, double ml, int maxLevel);

src/hnswscan.c

@@ -17,6 +17,7 @@ GetScanItems(IndexScanDesc scan, Datum q)
 	Relation	index = scan->indexRelation;
 	FmgrInfo   *procinfo = so->procinfo;
 	Oid			collation = so->collation;
+	bool		loadVec = scan->xs_want_itup;
 	List	   *ep;
 	List	   *w;
 	int			m;
@@ -28,15 +29,15 @@ GetScanItems(IndexScanDesc scan, Datum q)
 	if (entryPoint == NULL)
 		return NIL;
 
-	ep = list_make1(HnswEntryCandidate(entryPoint, q, index, procinfo, collation, false));
+	ep = list_make1(HnswEntryCandidate(entryPoint, q, index, procinfo, collation, loadVec));
 
 	for (int lc = entryPoint->level; lc >= 1; lc--)
 	{
-		w = HnswSearchLayer(q, ep, 1, lc, index, procinfo, collation, m, false, NULL);
+		w = HnswSearchLayer(q, ep, 1, lc, index, procinfo, collation, m, loadVec, NULL);
 		ep = w;
 	}
 
-	return HnswSearchLayer(q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
+	return HnswSearchLayer(q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, loadVec, NULL);
 }
 
 /*
@@ -113,6 +114,9 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
 
 	scan->opaque = so;
 
+	/* OK to always set since cheap */
+	scan->xs_itupdesc = RelationGetDescr(index);
+
 	return scan;
 }
 
@@ -198,6 +202,15 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
 
 		hc->element->heaptids = list_delete_last(hc->element->heaptids);
 
+		if (scan->xs_want_itup)
+		{
+			Datum		value = PointerGetDatum(hc->element->vec);
+			bool		isnull = false;
+
+			/* Allocate in temporary context, so no need to free */
+			scan->xs_itup = index_form_tuple(scan->xs_itupdesc, &value, &isnull);
+		}
+
 		MemoryContextSwitchTo(oldCtx);
 
 #if PG_VERSION_NUM >= 120000

src/hnswutils.c

@@ -569,7 +569,7 @@ AddToVisited(HTAB *v, HnswCandidate * hc, Relation index, bool *found)
  * Algorithm 2 from paper
  */
 List *
-HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement)
+HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool loadVec, HnswElement skipElement)
 {
 	ListCell   *lc2;
 
@@ -645,7 +645,7 @@ HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *pro
 				if (index == NULL)
 					eDistance = GetCandidateDistance(e, q, procinfo, collation);
 				else
-					HnswLoadElement(e->element, &eDistance, &q, index, procinfo, collation, inserting);
+					HnswLoadElement(e->element, &eDistance, &q, index, procinfo, collation, loadVec);
 
 				Assert(!e->element->deleted);
 

src/ivfbuild.c

@@ -11,7 +11,6 @@
 #include "miscadmin.h"
 #include "storage/bufmgr.h"
 #include "tcop/tcopprot.h"
-#include "utils/datum.h"
 #include "utils/memutils.h"
 
 #if PG_VERSION_NUM >= 140000
@@ -66,18 +65,11 @@
 static void
 AddSample(Datum *values, IvfflatBuildState * buildstate)
 {
-	MemoryContext oldCtx;
+	VectorArray samples = buildstate->samples;
-	Datum		value;
+	int			targsamples = samples->maxlen;
-	int			targsamples = buildstate->targsamples;
-
-	/* Use memory context since detoast can allocate */
-	oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
 
 	/* Detoast once for all calls */
-	value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
+	Datum		value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
-
-	/* Restore memory context */
-	MemoryContextSwitchTo(oldCtx);
 
 	/*
 	 * Normalize with KMEANS_NORM_PROC since spherical distance function
@@ -89,23 +81,18 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
 			return;
 	}
 
-	/* Copy datum */
+	if (samples->length < targsamples)
-	value = datumCopy(value, false, -1);
+	{
-
+		VectorArraySet(samples, samples->length, DatumGetVector(value));
-	/* Reset memory context */
+		samples->length++;
-	MemoryContextReset(buildstate->tmpCtx);
+	}
-
-	if (list_length(buildstate->samples) < targsamples)
-		buildstate->samples = lappend(buildstate->samples, DatumGetVector(value));
 	else
 	{
 		if (buildstate->rowstoskip < 0)
-			buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, list_length(buildstate->samples), targsamples);
+			buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, samples->length, targsamples);
 
 		if (buildstate->rowstoskip <= 0)
 		{
-			ListCell   *lc;
-
 #if PG_VERSION_NUM >= 150000
 			int			k = (int) (targsamples * sampler_random_fract(&buildstate->rstate.randstate));
 #else
@@ -113,8 +100,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
 #endif
 
 			Assert(k >= 0 && k < targsamples);
-			lc = list_nth_cell(buildstate->samples, k);
+			VectorArraySet(samples, k, DatumGetVector(value));
-			lfirst(lc) = DatumGetVector(value);
 		}
 
 		buildstate->rowstoskip -= 1;
@@ -129,13 +115,21 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
 			   bool *isnull, bool tupleIsAlive, void *state)
 {
 	IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
+	MemoryContext oldCtx;
 
 	/* Skip nulls */
 	if (isnull[0])
 		return;
 
+	/* Use memory context since detoast can allocate */
+	oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
+
 	/* Add sample */
-	AddSample(values, buildstate);
+	AddSample(values, state);
+
+	/* Reset memory context */
+	MemoryContextSwitchTo(oldCtx);
+	MemoryContextReset(buildstate->tmpCtx);
 }
 
 /*
@@ -144,7 +138,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
 static void
 SampleRows(IvfflatBuildState * buildstate)
 {
-	int			targsamples = buildstate->targsamples;
+	int			targsamples = buildstate->samples->maxlen;
 	BlockNumber totalblocks = RelationGetNumberOfBlocks(buildstate->heap);
 
 	buildstate->rowstoskip = -1;
@@ -455,13 +449,12 @@ ComputeCenters(IvfflatBuildState * buildstate)
 
 	/* Sample rows */
 	/* TODO Ensure within maintenance_work_mem */
-	buildstate->samples = NIL;
+	buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions);
-	buildstate->targsamples = numSamples;
 	if (buildstate->heap != NULL)
 	{
 		SampleRows(buildstate);
 
-		if (list_length(buildstate->samples) < buildstate->lists)
+		if (buildstate->samples->length < buildstate->lists)
 		{
 			ereport(NOTICE,
 					(errmsg("ivfflat index created with little data"),
@@ -474,7 +467,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
 	IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers));
 
 	/* Free samples before we allocate more memory */
-	list_free_deep(buildstate->samples);
+	VectorArrayFree(buildstate->samples);
 }
 
 /*

src/ivfflat.h

@@ -80,10 +80,6 @@
 #define RandomInt() random()
 #endif
 
-#if PG_VERSION_NUM < 130000
-#define list_sort(list, cmp) list_qsort(list, cmp)
-#endif
-
 /* Variables */
 extern int	ivfflat_probes;
 
@@ -182,8 +178,7 @@ typedef struct IvfflatBuildState
 	Oid			collation;
 
 	/* Variables */
-	List	   *samples;
+	VectorArray samples;
-	int			targsamples;
 	VectorArray centers;
 	ListInfo   *listInfo;
 	Vector	   *normvec;
@@ -279,7 +274,7 @@ typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
 VectorArray VectorArrayInit(int maxlen, int dimensions);
 void		VectorArrayFree(VectorArray arr);
 void		PrintVectorArray(char *msg, VectorArray arr);
-void		IvfflatKmeans(Relation index, List *samples, VectorArray centers);
+void		IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
 FmgrInfo   *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
 bool		IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
 int			IvfflatGetLists(Relation index);

src/ivfkmeans.c

@@ -12,20 +12,20 @@
  * https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf
  */
 static void
-InitCenters(Relation index, List *samples, VectorArray centers, float *lowerBound)
+InitCenters(Relation index, VectorArray samples, VectorArray centers, float *lowerBound)
 {
 	FmgrInfo   *procinfo;
 	Oid			collation;
 	int64		j;
-	float	   *weight = palloc(list_length(samples) * sizeof(float));
+	float	   *weight = palloc(samples->length * sizeof(float));
 	int			numCenters = centers->maxlen;
-	int			numSamples = list_length(samples);
+	int			numSamples = samples->length;
 
 	procinfo = index_getprocinfo(index, 1, IVFFLAT_KMEANS_DISTANCE_PROC);
 	collation = index->rd_indcollation[0];
 
 	/* Choose an initial center uniformly at random */
-	VectorArraySet(centers, 0, list_nth(samples, RandomInt() % list_length(samples)));
+	VectorArraySet(centers, 0, VectorArrayGet(samples, RandomInt() % samples->length));
 	centers->length++;
 
 	for (j = 0; j < numSamples; j++)
@@ -42,7 +42,7 @@ InitCenters(Relation index, List *samples, VectorArray centers, float *lowerBoun
 
 		for (j = 0; j < numSamples; j++)
 		{
-			Vector	   *vec = list_nth(samples, j);
+			Vector	   *vec = VectorArrayGet(samples, j);
 			double		distance;
 
 			/* Only need to compute distance for new center */
@@ -74,7 +74,7 @@ InitCenters(Relation index, List *samples, VectorArray centers, float *lowerBoun
 				break;
 		}
 
-		VectorArraySet(centers, i + 1, list_nth(samples, j));
+		VectorArraySet(centers, i + 1, VectorArrayGet(samples, j));
 		centers->length++;
 	}
 
@@ -106,41 +106,25 @@ CompareVectors(const void *a, const void *b)
 	return vector_cmp_internal((Vector *) a, (Vector *) b);
 }
 
-/*
- * Compare list vectors
- */
-static int
-#if PG_VERSION_NUM >= 130000
-CompareListVectors(const ListCell *a, const ListCell *b)
-#else
-CompareListVectors(const void *a, const void *b)
-#endif
-{
-	Vector	   *va = lfirst((ListCell *) a);
-	Vector	   *vb = lfirst((ListCell *) b);
-
-	return CompareVectors(va, vb);
-}
-
 /*
  * Quick approach if we have little data
  */
 static void
-QuickCenters(Relation index, List *samples, VectorArray centers)
+QuickCenters(Relation index, VectorArray samples, VectorArray centers)
 {
 	int			dimensions = centers->dim;
 	Oid			collation = index->rd_indcollation[0];
 	FmgrInfo   *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
 
 	/* Copy existing vectors while avoiding duplicates */
-	if (list_length(samples) > 0)
+	if (samples->length > 0)
 	{
-		list_sort(samples, CompareListVectors);
+		qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
-		for (int i = 0; i < list_length(samples); i++)
+		for (int i = 0; i < samples->length; i++)
 		{
-			Vector	   *vec = list_nth(samples, i);
+			Vector	   *vec = VectorArrayGet(samples, i);
 
-			if (i == 0 || CompareVectors(vec, list_nth(samples, i - 1)) != 0)
+			if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
 			{
 				VectorArraySet(centers, centers->length, vec);
 				centers->length++;
@@ -176,7 +160,7 @@ QuickCenters(Relation index, List *samples, VectorArray centers)
  * https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
  */
 static void
-ElkanKmeans(Relation index, List *samples, VectorArray centers)
+ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
 {
 	FmgrInfo   *procinfo;
 	FmgrInfo   *normprocinfo;
@@ -187,7 +171,7 @@ ElkanKmeans(Relation index, List *samples, VectorArray centers)
 	int64		k;
 	int			dimensions = centers->dim;
 	int			numCenters = centers->maxlen;
-	int			numSamples = list_length(samples);
+	int			numSamples = samples->length;
 	VectorArray newCenters;
 	int		   *centerCounts;
 	int		   *closestCenters;
@@ -198,7 +182,7 @@ ElkanKmeans(Relation index, List *samples, VectorArray centers)
 	float	   *newcdist;
 
 	/* Calculate allocation sizes */
-	Size		samplesSize = 0;
+	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;
@@ -342,7 +326,7 @@ ElkanKmeans(Relation index, List *samples, VectorArray centers)
 				if (upperBound[j] <= halfcdist[closestCenters[j] * numCenters + k])
 					continue;
 
-				vec = list_nth(samples, j);
+				vec = VectorArrayGet(samples, j);
 
 				/* Step 3a */
 				if (rj)
@@ -393,7 +377,7 @@ ElkanKmeans(Relation index, List *samples, VectorArray centers)
 		{
 			int			closestCenter;
 
-			vec = list_nth(samples, j);
+			vec = VectorArrayGet(samples, j);
 			closestCenter = closestCenters[j];
 
 			/* Increment sum and count of closest center */
@@ -530,9 +514,9 @@ CheckCenters(Relation index, VectorArray centers)
  * We use spherical k-means for inner product and cosine
  */
 void
-IvfflatKmeans(Relation index, List *samples, VectorArray centers)
+IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers)
 {
-	if (list_length(samples) <= centers->maxlen)
+	if (samples->length <= centers->maxlen)
 		QuickCenters(index, samples, centers);
 	else
 		ElkanKmeans(index, samples, centers);