Fixed Windows build [skip ci]

CHANGELOG.md

@@ -1,7 +1,7 @@
-## 0.5.1 (2023-10-10)
+## 0.5.1 (unreleased)
 
-- Improved performance of HNSW index builds
-- Added check for MVCC-compliant snapshot for index scans
+- Added check for MVCC-compliant snapshot for HNSW index scans
+- Improved performance of index scans for IVFFlat after updates and deletes
 
 ## 0.5.0 (2023-08-28)
 

META.json

@@ -2,7 +2,7 @@
 	"name": "vector",
 	"abstract": "Open-source vector similarity search for Postgres",
 	"description": "Supports L2 distance, inner product, and cosine distance",
-	"version": "0.5.1",
+	"version": "0.5.0",
 	"maintainer": [
 		"Andrew Kane <andrew@ankane.org>"
 	],
@@ -20,7 +20,7 @@
 		"vector": {
 			"file": "sql/vector.sql",
 			"docfile": "README.md",
-			"version": "0.5.1",
+			"version": "0.5.0",
 			"abstract": "Open-source vector similarity search for Postgres"
 		}
 	},

Makefile

@@ -1,10 +1,10 @@
 EXTENSION = vector
-EXTVERSION = 0.5.1
+EXTVERSION = 0.5.0
 
 MODULE_big = vector
 DATA = $(wildcard sql/*--*.sql)
-OBJS = src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/vector.o
-HEADERS = src/vector.h
+OBJS = src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/tinyint.o src/vector.o
+HEADERS = src/tinyint.h src/vector.h
 
 TESTS = $(wildcard test/sql/*.sql)
 REGRESS = $(patsubst test/sql/%.sql,%,$(TESTS))

Makefile.win

@@ -1,8 +1,8 @@
 EXTENSION = vector
-EXTVERSION = 0.5.1
+EXTVERSION = 0.5.0
 
-OBJS = 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\vector.obj
-HEADERS = src\vector.h
+OBJS = 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\tinyint.obj src\vector.obj
+HEADERS = src\tinyint.h src\vector.h
 
 REGRESS = btree cast copy functions input ivfflat_cosine ivfflat_ip ivfflat_l2 ivfflat_options ivfflat_unlogged
 REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
@@ -56,7 +56,7 @@ install:
 	copy $(EXTENSION).control "$(SHAREDIR)\extension"
 	copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
 	mkdir "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
-	copy $(HEADERS) "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
+	for %f in ($(HEADERS)) do copy %f "$(INCLUDEDIR_SERVER)\extension\$(EXTENSION)"
 
 installcheck:
 	"$(BINDIR)\pg_regress" --bindir="$(BINDIR)" $(REGRESS_OPTS) $(REGRESS)

README.md

@@ -18,7 +18,7 @@ Compile and install the extension (supports Postgres 11+)
 
 ```sh
 cd /tmp
-git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
+git clone --branch v0.5.0 https://github.com/pgvector/pgvector.git
 cd pgvector
 make
 make install # may need sudo
@@ -509,7 +509,7 @@ Then use `nmake` to build:
 
 ```cmd
 set "PGROOT=C:\Program Files\PostgreSQL\15"
-git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
+git clone --branch v0.5.0 https://github.com/pgvector/pgvector.git
 cd pgvector
 nmake /F Makefile.win
 nmake /F Makefile.win install
@@ -530,7 +530,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
 You can also build the image manually:
 
 ```sh
-git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
+git clone --branch v0.5.0 https://github.com/pgvector/pgvector.git
 cd pgvector
 docker build --build-arg PG_MAJOR=15 -t myuser/pgvector .
 ```

sql/vector--0.5.0--0.5.1.sql

@@ -1,2 +1,67 @@
 -- complain if script is sourced in psql, rather than via CREATE EXTENSION
 \echo Use "ALTER EXTENSION vector UPDATE TO '0.5.1'" to load this file. \quit
+
+-- tinyint
+
+CREATE TYPE tinyint;
+
+CREATE FUNCTION tinyint_in(cstring, oid, integer) RETURNS tinyint
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION tinyint_out(tinyint) RETURNS cstring
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION tinyint_recv(internal, oid, integer) RETURNS tinyint
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION tinyint_send(tinyint) RETURNS bytea
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE TYPE tinyint (
+	INPUT     = tinyint_in,
+	OUTPUT    = tinyint_out,
+	RECEIVE   = tinyint_recv,
+	SEND      = tinyint_send,
+	INTERNALLENGTH = 1,
+	PASSEDBYVALUE,
+	ALIGNMENT = char
+);
+
+CREATE FUNCTION integer_to_tinyint(integer, integer, boolean) RETURNS tinyint
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION numeric_to_tinyint(numeric, integer, boolean) RETURNS tinyint
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE CAST (integer AS tinyint)
+	WITH FUNCTION integer_to_tinyint(integer, integer, boolean) AS IMPLICIT;
+
+CREATE CAST (numeric AS tinyint)
+	WITH FUNCTION numeric_to_tinyint(numeric, integer, boolean) AS IMPLICIT;
+
+CREATE FUNCTION l2_distance(tinyint[], tinyint[]) RETURNS float8
+	AS 'MODULE_PATHNAME', 'tinyint_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION inner_product(tinyint[], tinyint[]) RETURNS float8
+	AS 'MODULE_PATHNAME', 'tinyint_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION cosine_distance(tinyint[], tinyint[]) RETURNS float8
+	AS 'MODULE_PATHNAME', 'tinyint_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION tinyint_negative_inner_product(tinyint[], tinyint[]) RETURNS float8
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE OPERATOR <-> (
+	LEFTARG = tinyint[], RIGHTARG = tinyint[], PROCEDURE = l2_distance,
+	COMMUTATOR = '<->'
+);
+
+CREATE OPERATOR <#> (
+	LEFTARG = tinyint[], RIGHTARG = tinyint[], PROCEDURE = tinyint_negative_inner_product,
+	COMMUTATOR = '<#>'
+);
+
+CREATE OPERATOR <=> (
+	LEFTARG = tinyint[], RIGHTARG = tinyint[], PROCEDURE = cosine_distance,
+	COMMUTATOR = '<=>'
+);

sql/vector.sql

@@ -290,3 +290,68 @@ CREATE OPERATOR CLASS vector_cosine_ops
 	OPERATOR 1 <=> (vector, vector) FOR ORDER BY float_ops,
 	FUNCTION 1 vector_negative_inner_product(vector, vector),
 	FUNCTION 2 vector_norm(vector);
+
+-- tinyint
+
+CREATE TYPE tinyint;
+
+CREATE FUNCTION tinyint_in(cstring, oid, integer) RETURNS tinyint
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION tinyint_out(tinyint) RETURNS cstring
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION tinyint_recv(internal, oid, integer) RETURNS tinyint
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION tinyint_send(tinyint) RETURNS bytea
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE TYPE tinyint (
+	INPUT     = tinyint_in,
+	OUTPUT    = tinyint_out,
+	RECEIVE   = tinyint_recv,
+	SEND      = tinyint_send,
+	INTERNALLENGTH = 1,
+	PASSEDBYVALUE,
+	ALIGNMENT = char
+);
+
+CREATE FUNCTION integer_to_tinyint(integer, integer, boolean) RETURNS tinyint
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION numeric_to_tinyint(numeric, integer, boolean) RETURNS tinyint
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE CAST (integer AS tinyint)
+	WITH FUNCTION integer_to_tinyint(integer, integer, boolean) AS IMPLICIT;
+
+CREATE CAST (numeric AS tinyint)
+	WITH FUNCTION numeric_to_tinyint(numeric, integer, boolean) AS IMPLICIT;
+
+CREATE FUNCTION l2_distance(tinyint[], tinyint[]) RETURNS float8
+	AS 'MODULE_PATHNAME', 'tinyint_l2_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION inner_product(tinyint[], tinyint[]) RETURNS float8
+	AS 'MODULE_PATHNAME', 'tinyint_inner_product' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION cosine_distance(tinyint[], tinyint[]) RETURNS float8
+	AS 'MODULE_PATHNAME', 'tinyint_cosine_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE FUNCTION tinyint_negative_inner_product(tinyint[], tinyint[]) RETURNS float8
+	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
+
+CREATE OPERATOR <-> (
+	LEFTARG = tinyint[], RIGHTARG = tinyint[], PROCEDURE = l2_distance,
+	COMMUTATOR = '<->'
+);
+
+CREATE OPERATOR <#> (
+	LEFTARG = tinyint[], RIGHTARG = tinyint[], PROCEDURE = tinyint_negative_inner_product,
+	COMMUTATOR = '<#>'
+);
+
+CREATE OPERATOR <=> (
+	LEFTARG = tinyint[], RIGHTARG = tinyint[], PROCEDURE = cosine_distance,
+	COMMUTATOR = '<=>'
+);

src/hnsw.h

@@ -112,13 +112,11 @@ typedef struct HnswCandidate
 {
 	HnswElement element;
 	float		distance;
-	bool		closer;
 }			HnswCandidate;
 
 typedef struct HnswNeighborArray
 {
 	int			length;
-	bool		closerSet;
 	HnswCandidate *items;
 }			HnswNeighborArray;
 

src/hnswutils.c

@@ -139,7 +139,6 @@ HnswInitNeighbors(HnswElement element, int m)
 		a = &element->neighbors[lc];
 		a->length = 0;
 		a->items = palloc(sizeof(HnswCandidate) * lm);
-		a->closerSet = false;
 	}
 }
 
@@ -693,34 +692,6 @@ HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *pro
 	return w;
 }
 
-/*
- * Compare candidate distances
- */
-static int
-#if PG_VERSION_NUM >= 130000
-CompareCandidateDistances(const ListCell *a, const ListCell *b)
-#else
-CompareCandidateDistances(const void *a, const void *b)
-#endif
-{
-	HnswCandidate *hca = lfirst((ListCell *) a);
-	HnswCandidate *hcb = lfirst((ListCell *) b);
-
-	if (hca->distance < hcb->distance)
-		return 1;
-
-	if (hca->distance > hcb->distance)
-		return -1;
-
-	if (hca->element < hcb->element)
-		return 1;
-
-	if (hca->element > hcb->element)
-		return -1;
-
-	return 0;
-}
-
 /*
  * Calculate the distance between elements
  */
@@ -777,77 +748,33 @@ CheckElementCloser(HnswCandidate * e, List *r, int lc, FmgrInfo *procinfo, Oid c
  * Algorithm 4 from paper
  */
 static List *
-SelectNeighbors(List *c, int m, int lc, FmgrInfo *procinfo, Oid collation, HnswElement e2, HnswCandidate * newCandidate, HnswCandidate * *pruned, bool sortCandidates)
+SelectNeighbors(List *c, int m, int lc, FmgrInfo *procinfo, Oid collation, HnswCandidate * *pruned)
 {
 	List	   *r = NIL;
 	List	   *w = list_copy(c);
 	pairingheap *wd;
-	bool		mustCalculate = !e2->neighbors[lc].closerSet;
-	List	   *added = NIL;
-	bool		removedAny = false;
 
 	if (list_length(w) <= m)
 		return w;
 
 	wd = pairingheap_allocate(CompareNearestCandidates, NULL);
 
-	/* Ensure order of candidates is deterministic for closer caching */
-	if (sortCandidates)
-		list_sort(w, CompareCandidateDistances);
-
 	while (list_length(w) > 0 && list_length(r) < m)
 	{
 		/* Assumes w is already ordered desc */
 		HnswCandidate *e = llast(w);
+		bool		closer;
 
 		w = list_delete_last(w);
 
-		/* Use previous state of r and wd to skip work when possible */
-		if (mustCalculate)
-			e->closer = CheckElementCloser(e, r, lc, procinfo, collation);
-		else if (list_length(added) > 0)
-		{
-			/*
-			 * If the current candidate was closer, we only need to compare it
-			 * with the other candidates that we have added.
-			 */
-			if (e->closer)
-			{
-				e->closer = CheckElementCloser(e, added, lc, procinfo, collation);
+		closer = CheckElementCloser(e, r, lc, procinfo, collation);
 
-				if (!e->closer)
-					removedAny = true;
-			}
-			else
-			{
-				/*
-				 * If we have removed any candidates from closer, a candidate
-				 * that was not closer earlier might now be.
-				 */
-				if (removedAny)
-				{
-					e->closer = CheckElementCloser(e, r, lc, procinfo, collation);
-					if (e->closer)
-						added = lappend(added, e);
-				}
-			}
-		}
-		else if (e == newCandidate)
-		{
-			e->closer = CheckElementCloser(e, r, lc, procinfo, collation);
-			if (e->closer)
-				added = lappend(added, e);
-		}
-
-		if (e->closer)
+		if (closer)
 			r = lappend(r, e);
 		else
 			pairingheap_add(wd, &(CreatePairingHeapNode(e)->ph_node));
 	}
 
-	/* Cached value can only be used in future if sorted deterministically */
-	e2->neighbors[lc].closerSet = sortCandidates;
-
 	/* Keep pruned connections */
 	while (!pairingheap_is_empty(wd) && list_length(r) < m)
 		r = lappend(r, ((HnswPairingHeapNode *) pairingheap_remove_first(wd))->inner);
@@ -901,6 +828,28 @@ AddConnections(HnswElement element, List *neighbors, int m, int lc)
 		a->items[a->length++] = *((HnswCandidate *) lfirst(lc2));
 }
 
+/*
+ * Compare candidate distances
+ */
+static int
+#if PG_VERSION_NUM >= 130000
+CompareCandidateDistances(const ListCell *a, const ListCell *b)
+#else
+CompareCandidateDistances(const void *a, const void *b)
+#endif
+{
+	HnswCandidate *hca = lfirst((ListCell *) a);
+	HnswCandidate *hcb = lfirst((ListCell *) b);
+
+	if (hca->distance < hcb->distance)
+		return 1;
+
+	if (hca->distance > hcb->distance)
+		return -1;
+
+	return 0;
+}
+
 /*
  * Update connections
  */
@@ -954,12 +903,13 @@ HnswUpdateConnection(HnswElement element, HnswCandidate * hc, int m, int lc, int
 		{
 			List	   *c = NIL;
 
-			/* Add candidates */
+			/* Add and sort candidates */
 			for (int i = 0; i < currentNeighbors->length; i++)
 				c = lappend(c, &currentNeighbors->items[i]);
 			c = lappend(c, &hc2);
+			list_sort(c, CompareCandidateDistances);
 
-			SelectNeighbors(c, m, lc, procinfo, collation, hc->element, &hc2, &pruned, true);
+			SelectNeighbors(c, m, lc, procinfo, collation, &pruned);
 
 			/* Should not happen */
 			if (pruned == NULL)
@@ -1058,12 +1008,7 @@ HnswInsertElement(HnswElement element, HnswElement entryPoint, Relation index, F
 		else
 			lw = w;
 
-		/*
-		 * Candidates are sorted, but not deterministically. Could set
-		 * sortCandidates to true for in-memory builds to enable closer
-		 * caching, but there does not seem to be a difference in performance.
-		 */
-		neighbors = SelectNeighbors(lw, lm, lc, procinfo, collation, element, NULL, NULL, false);
+		neighbors = SelectNeighbors(lw, lm, lc, procinfo, collation, NULL);
 
 		AddConnections(element, neighbors, lm, lc);
 

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;
-	Datum		value;
-	int			targsamples = buildstate->targsamples;
-
-	/* Use memory context since detoast can allocate */
-	oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
+	VectorArray samples = buildstate->samples;
+	int			targsamples = samples->maxlen;
 
 	/* Detoast once for all calls */
-	value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
-
-	/* Restore memory context */
-	MemoryContextSwitchTo(oldCtx);
+	Datum		value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
 
 	/*
 	 * Normalize with KMEANS_NORM_PROC since spherical distance function
@@ -89,23 +81,18 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
 			return;
 	}
 
-	/* Copy datum */
-	value = datumCopy(value, false, -1);
-
-	/* Reset memory context */
-	MemoryContextReset(buildstate->tmpCtx);
-
-	if (list_length(buildstate->samples) < targsamples)
-		buildstate->samples = lappend(buildstate->samples, DatumGetVector(value));
+	if (samples->length < targsamples)
+	{
+		VectorArraySet(samples, samples->length, DatumGetVector(value));
+		samples->length++;
+	}
 	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);
-			lfirst(lc) = DatumGetVector(value);
+			VectorArraySet(samples, k, 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->targsamples = numSamples;
+	buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions);
 	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;
-	int			targsamples;
+	VectorArray samples;
 	VectorArray centers;
 	ListInfo   *listInfo;
 	Vector	   *normvec;
@@ -251,6 +246,8 @@ typedef struct IvfflatScanOpaqueData
 	int			probes;
 	int			dimensions;
 	bool		first;
+	Buffer		buf;
+	ItemPointerData heaptid;
 
 	/* Sorting */
 	Tuplesortstate *sortstate;
@@ -279,7 +276,7 @@ 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);
-		for (int i = 0; i < list_length(samples); i++)
+		qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
+		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);

src/ivfscan.c

@@ -143,6 +143,10 @@ GetScanItems(IndexScanDesc scan, Datum value)
 				bool		isnull;
 				ItemId		itemid = PageGetItemId(page, offno);
 
+				/* Skip dead tuples */
+				if (scan->ignore_killed_tuples && ItemIdIsDead(itemid))
+					continue;
+
 				itup = (IndexTuple) PageGetItem(page, itemid);
 				datum = index_getattr(itup, 1, tupdesc, &isnull);
 
@@ -157,6 +161,8 @@ GetScanItems(IndexScanDesc scan, Datum value)
 				slot->tts_isnull[0] = false;
 				slot->tts_values[1] = PointerGetDatum(&itup->t_tid);
 				slot->tts_isnull[1] = false;
+				slot->tts_values[2] = Int32GetDatum((int) searchPage);
+				slot->tts_isnull[2] = false;
 				ExecStoreVirtualTuple(slot);
 
 				tuplesort_puttupleslot(so->sortstate, slot);
@@ -181,6 +187,55 @@ GetScanItems(IndexScanDesc scan, Datum value)
 	tuplesort_performsort(so->sortstate);
 }
 
+/*
+ * Mark prior tuple as dead
+ */
+static void
+MarkPriorTupleDead(IndexScanDesc scan)
+{
+	IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
+	Buffer		buf = so->buf;
+	Page		page;
+	OffsetNumber maxoffno;
+
+	/* Safety check */
+	if (!BufferIsValid(so->buf) || !ItemPointerIsValid(&so->heaptid))
+		return;
+
+	/* Only a shared locked is needed for ItemIdMarkDead */
+	LockBuffer(buf, BUFFER_LOCK_SHARE);
+	page = BufferGetPage(buf);
+	maxoffno = PageGetMaxOffsetNumber(page);
+
+	for (OffsetNumber offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
+	{
+		ItemId		itemid = PageGetItemId(page, offno);
+		IndexTuple	itup = (IndexTuple) PageGetItem(page, itemid);
+
+		/*
+		 * Find tuple. Since buffer has been pinned, tuple cannot have been
+		 * vacuumed (and heap TID reused).
+		 */
+		if (ItemPointerEquals(&itup->t_tid, &so->heaptid))
+		{
+			/*
+			 * Make sure tuple has not already been marked dead to avoid extra
+			 * WAL if wal_log_hints or data checksums enabled
+			 */
+			if (!ItemIdIsDead(itemid))
+			{
+				ItemIdMarkDead(itemid);
+				MarkBufferDirtyHint(buf, true);
+			}
+
+			break;
+		}
+	}
+
+	/* Unlock buffer */
+	LockBuffer(buf, BUFFER_LOCK_UNLOCK);
+}
+
 /*
  * Prepare for an index scan
  */
@@ -206,7 +261,9 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
 		probes = lists;
 
 	so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
+	so->buf = InvalidBuffer;
 	so->first = true;
+	ItemPointerSetInvalid(&so->heaptid);
 	so->probes = probes;
 	so->dimensions = dimensions;
 
@@ -217,12 +274,13 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
 
 	/* Create tuple description for sorting */
 #if PG_VERSION_NUM >= 120000
-	so->tupdesc = CreateTemplateTupleDesc(2);
+	so->tupdesc = CreateTemplateTupleDesc(3);
 #else
-	so->tupdesc = CreateTemplateTupleDesc(2, false);
+	so->tupdesc = CreateTemplateTupleDesc(3, false);
 #endif
 	TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
 	TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
+	TupleDescInitEntry(so->tupdesc, (AttrNumber) 3, "indexblkno", INT4OID, -1, 0);
 
 	/* Prep sort */
 	so->sortstate = tuplesort_begin_heap(so->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
@@ -254,6 +312,7 @@ ivfflatrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int
 #endif
 
 	so->first = true;
+	ItemPointerSetInvalid(&so->heaptid);
 	pairingheap_reset(so->listQueue);
 
 	if (keys && scan->numberOfKeys > 0)
@@ -288,11 +347,6 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
 		if (scan->orderByData == NULL)
 			elog(ERROR, "cannot scan ivfflat index without order");
 
-		/* Requires MVCC-compliant snapshot as not able to pin during sorting */
-		/* https://www.postgresql.org/docs/current/index-locking.html */
-		if (!IsMVCCSnapshot(scan->xs_snapshot))
-			elog(ERROR, "non-MVCC snapshots are not supported with ivfflat");
-
 		if (scan->orderByData->sk_flags & SK_ISNULL)
 			value = PointerGetDatum(InitVector(so->dimensions));
 		else
@@ -316,10 +370,17 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
 		if (value != scan->orderByData->sk_argument)
 			pfree(DatumGetPointer(value));
 	}
+	else
+	{
+		/* Mark prior tuple as dead */
+		if (scan->kill_prior_tuple)
+			MarkPriorTupleDead(scan);
+	}
 
 	if (tuplesort_gettupleslot(so->sortstate, true, false, so->slot, NULL))
 	{
 		ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
+		BlockNumber indexblkno = DatumGetInt32(slot_getattr(so->slot, 3, &so->isnull));
 
 #if PG_VERSION_NUM >= 120000
 		scan->xs_heaptid = *heaptid;
@@ -327,6 +388,21 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
 		scan->xs_ctup.t_self = *heaptid;
 #endif
 
+		/* Keep track of info needed to mark tuple as dead */
+		so->heaptid = *heaptid;
+
+		/* Unpin buffer */
+		if (BufferIsValid(so->buf))
+			ReleaseBuffer(so->buf);
+
+		/*
+		 * An index scan must maintain a pin on the index page holding the
+		 * item last returned by amgettuple
+		 *
+		 * https://www.postgresql.org/docs/current/index-locking.html
+		 */
+		so->buf = ReadBuffer(scan->indexRelation, indexblkno);
+
 		scan->xs_recheckorderby = false;
 		return true;
 	}
@@ -342,6 +418,10 @@ ivfflatendscan(IndexScanDesc scan)
 {
 	IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
 
+	/* Release pin */
+	if (BufferIsValid(so->buf))
+		ReleaseBuffer(so->buf);
+
 	pairingheap_free(so->listQueue);
 	tuplesort_end(so->sortstate);
 

src/tinyint.c

@@ -0,0 +1,294 @@
+#include "postgres.h"
+
+#include <math.h>
+#include <stdint.h>
+
+#include "fmgr.h"
+#include "lib/stringinfo.h"
+#include "libpq/pqformat.h"
+#include "tinyint.h"
+#include "utils/array.h"
+#include "utils/builtins.h"
+#include "utils/numeric.h"
+
+/*
+ * Check if array is a vector
+ */
+static bool
+ArrayIsVector(ArrayType *a)
+{
+	return ARR_NDIM(a) == 1 && !array_contains_nulls(a);
+}
+
+/*
+ * Check if dimensions are the same
+ */
+static int
+CheckDims(ArrayType *a, ArrayType *b)
+{
+	int			dima;
+	int			dimb;
+
+	if (!ArrayIsVector(a) || !ArrayIsVector(b))
+		return 0;
+
+	dima = ARR_DIMS(a)[0];
+	dimb = ARR_DIMS(b)[0];
+
+	if (dima != dimb)
+		return 0;
+
+	return dima;
+}
+
+/*
+ * Check range
+ */
+static void
+CheckRange(long i)
+{
+	if (i < INT8_MIN || i > INT8_MAX)
+		ereport(ERROR,
+				(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
+				 errmsg("value \"%ld\" is out of range for type tinyint", i)));
+}
+
+/*
+ * Convert textual representation to internal representation
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(tinyint_in);
+Datum
+tinyint_in(PG_FUNCTION_ARGS)
+{
+	char	   *s = PG_GETARG_CSTRING(0);
+	const char *ptr = s;
+	long		i;
+	char	   *end;
+
+	/* skip leading spaces */
+	while (*ptr != '\0' && isspace((unsigned char) *ptr))
+		ptr++;
+
+	if (*ptr == '\0')
+		ereport(ERROR,
+				(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
+				 errmsg("invalid input syntax for type tinyint: \"%s\"", s)));
+
+	i = strtol(ptr, &end, 10);
+	ptr = end;
+
+	if (i < INT8_MIN || i > INT8_MAX)
+		ereport(ERROR,
+				(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
+				 errmsg("value \"%s\" is out of range for type tinyint", s)));
+
+	/* allow trailing whitespace, but not other trailing chars */
+	while (*ptr != '\0' && isspace((unsigned char) *ptr))
+		ptr++;
+
+	if (*ptr != '\0')
+		ereport(ERROR,
+				(errcode(ERRCODE_INVALID_TEXT_REPRESENTATION),
+				 errmsg("invalid input syntax for type tinyint: \"%s\"", s)));
+
+	PG_RETURN_INT8(i);
+}
+
+/*
+ * Convert internal representation to textual representation
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(tinyint_out);
+Datum
+tinyint_out(PG_FUNCTION_ARGS)
+{
+	int8		num = PG_GETARG_INT8(0);
+	char	   *result = (char *) palloc(5);	/* sign, 3 digits, '\0' */
+
+	pg_ltoa((int32) num, result);
+	PG_RETURN_CSTRING(result);
+}
+
+/*
+ * Convert external binary representation to internal representation
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(tinyint_recv);
+Datum
+tinyint_recv(PG_FUNCTION_ARGS)
+{
+	StringInfo	buf = (StringInfo) PG_GETARG_POINTER(0);
+
+	PG_RETURN_INT8((int8) pq_getmsgint(buf, sizeof(int8)));
+}
+
+/*
+ * Convert internal representation to the external binary representation
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(tinyint_send);
+Datum
+tinyint_send(PG_FUNCTION_ARGS)
+{
+	int8		arg1 = PG_GETARG_INT8(0);
+	StringInfoData buf;
+
+	pq_begintypsend(&buf);
+	pq_sendint8(&buf, arg1);
+	PG_RETURN_BYTEA_P(pq_endtypsend(&buf));
+}
+
+/*
+ * Convert integer to tinyint
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(integer_to_tinyint);
+Datum
+integer_to_tinyint(PG_FUNCTION_ARGS)
+{
+	int32		i = PG_GETARG_INT32(0);
+
+	CheckRange(i);
+
+	PG_RETURN_INT8(i);
+}
+
+/*
+ * Convert numeric to tinyint
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(numeric_to_tinyint);
+Datum
+numeric_to_tinyint(PG_FUNCTION_ARGS)
+{
+	Numeric		num = PG_GETARG_NUMERIC(0);
+	int32		i = numeric_int4_opt_error(num, NULL);
+
+	CheckRange(i);
+
+	PG_RETURN_INT8(i);
+}
+
+/*
+ * Get the L2 distance between tinyint arrays
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(tinyint_l2_distance);
+Datum
+tinyint_l2_distance(PG_FUNCTION_ARGS)
+{
+	ArrayType  *a = PG_GETARG_ARRAYTYPE_P(0);
+	ArrayType  *b = PG_GETARG_ARRAYTYPE_P(1);
+	int8    *ax = (int8 *) ARR_DATA_PTR(a);
+	int8    *bx = (int8 *) ARR_DATA_PTR(b);
+	double		distance = 0.0;
+	int			dim = CheckDims(a, b);
+
+	/* TODO Decide on error or NULL */
+	if (!dim)
+		PG_RETURN_NULL();
+
+	/* Auto-vectorized */
+	for (int i = 0; i < dim; i++)
+	{
+		double		diff = ax[i] - bx[i];
+
+		distance += diff * diff;
+	}
+
+	PG_RETURN_FLOAT8(sqrt(distance));
+}
+
+/*
+ * Get the inner product of two tinyint arrays
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(tinyint_inner_product);
+Datum
+tinyint_inner_product(PG_FUNCTION_ARGS)
+{
+	ArrayType  *a = PG_GETARG_ARRAYTYPE_P(0);
+	ArrayType  *b = PG_GETARG_ARRAYTYPE_P(1);
+	int8	   *ax = (int8 *) ARR_DATA_PTR(a);
+	int8	   *bx = (int8 *) ARR_DATA_PTR(b);
+	double		distance = 0.0;
+	int			dim = CheckDims(a, b);
+
+	/* TODO Decide on error or NULL */
+	if (!dim)
+		PG_RETURN_NULL();
+
+	/* Auto-vectorized */
+	for (int i = 0; i < dim; i++)
+		distance += ax[i] * bx[i];
+
+	PG_RETURN_FLOAT8(distance);
+}
+
+/*
+ * Get the negative inner product of two tinyint arrays
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(tinyint_negative_inner_product);
+Datum
+tinyint_negative_inner_product(PG_FUNCTION_ARGS)
+{
+	ArrayType  *a = PG_GETARG_ARRAYTYPE_P(0);
+	ArrayType  *b = PG_GETARG_ARRAYTYPE_P(1);
+	int8	   *ax = (int8 *) ARR_DATA_PTR(a);
+	int8	   *bx = (int8 *) ARR_DATA_PTR(b);
+	double		distance = 0.0;
+	int			dim = CheckDims(a, b);
+
+	/* TODO Decide on error or NULL */
+	if (!dim)
+		PG_RETURN_NULL();
+
+	/* Auto-vectorized */
+	for (int i = 0; i < dim; i++)
+		distance += ax[i] * bx[i];
+
+	PG_RETURN_FLOAT8(distance * -1);
+}
+
+/*
+ * Get the cosine distance between two float2 arrays
+ */
+PGDLLEXPORT PG_FUNCTION_INFO_V1(tinyint_cosine_distance);
+Datum
+tinyint_cosine_distance(PG_FUNCTION_ARGS)
+{
+	ArrayType  *a = PG_GETARG_ARRAYTYPE_P(0);
+	ArrayType  *b = PG_GETARG_ARRAYTYPE_P(1);
+	int8   *ax = (int8 *) ARR_DATA_PTR(a);
+	int8   *bx = (int8 *) ARR_DATA_PTR(b);
+	double		distance = 0.0;
+	double		norma = 0.0;
+	double		normb = 0.0;
+	double		similarity;
+	int			dim = CheckDims(a, b);
+
+	/* TODO Decide on error or NULL */
+	if (!dim)
+		PG_RETURN_NULL();
+
+	/* Auto-vectorized */
+	for (int i = 0; i < dim; i++)
+	{
+		float		axi = ax[i];
+		float		bxi = bx[i];
+
+		distance += axi * bxi;
+		norma += axi * axi;
+		normb += bxi * bxi;
+	}
+
+	/* Use sqrt(a * b) over sqrt(a) * sqrt(b) */
+	similarity = distance / sqrt(norma * normb);
+
+#ifdef _MSC_VER
+	/* /fp:fast may not propagate NaN */
+	if (isnan(similarity))
+		PG_RETURN_FLOAT8(NAN);
+#endif
+
+	/* Keep in range */
+	if (similarity > 1)
+		similarity = 1;
+	else if (similarity < -1)
+		similarity = -1;
+
+	PG_RETURN_FLOAT8(1 - similarity);
+}

src/tinyint.h

@@ -0,0 +1,8 @@
+#ifndef TINYINT_H
+#define TINYINT_H
+
+#define DatumGetInt8(X) ((int8) (X))
+#define PG_GETARG_INT8(n)	 DatumGetInt8(PG_GETARG_DATUM(n))
+#define PG_RETURN_INT8(x)	 return Int8GetDatum(x)
+
+#endif

test/expected/functions.out

@@ -54,85 +54,85 @@ SELECT vector_norm('[3e37,4e37]')::real;
        5e+37
 (1 row)
 
-SELECT l2_distance('[0,0]', '[3,4]');
+SELECT l2_distance('[0,0]'::vector, '[3,4]');
  l2_distance 
 -------------
            5
 (1 row)
 
-SELECT l2_distance('[0,0]', '[0,1]');
+SELECT l2_distance('[0,0]'::vector, '[0,1]');
  l2_distance 
 -------------
            1
 (1 row)
 
-SELECT l2_distance('[1,2]', '[3]');
+SELECT l2_distance('[1,2]'::vector, '[3]');
 ERROR:  different vector dimensions 2 and 1
-SELECT l2_distance('[3e38]', '[-3e38]');
+SELECT l2_distance('[3e38]'::vector, '[-3e38]');
  l2_distance 
 -------------
     Infinity
 (1 row)
 
-SELECT inner_product('[1,2]', '[3,4]');
+SELECT inner_product('[1,2]'::vector, '[3,4]');
  inner_product 
 ---------------
             11
 (1 row)
 
-SELECT inner_product('[1,2]', '[3]');
+SELECT inner_product('[1,2]'::vector, '[3]');
 ERROR:  different vector dimensions 2 and 1
-SELECT inner_product('[3e38]', '[3e38]');
+SELECT inner_product('[3e38]'::vector, '[3e38]');
  inner_product 
 ---------------
       Infinity
 (1 row)
 
-SELECT cosine_distance('[1,2]', '[2,4]');
+SELECT cosine_distance('[1,2]'::vector, '[2,4]');
  cosine_distance 
 -----------------
                0
 (1 row)
 
-SELECT cosine_distance('[1,2]', '[0,0]');
+SELECT cosine_distance('[1,2]'::vector, '[0,0]');
  cosine_distance 
 -----------------
              NaN
 (1 row)
 
-SELECT cosine_distance('[1,1]', '[1,1]');
+SELECT cosine_distance('[1,1]'::vector, '[1,1]');
  cosine_distance 
 -----------------
                0
 (1 row)
 
-SELECT cosine_distance('[1,0]', '[0,2]');
+SELECT cosine_distance('[1,0]'::vector, '[0,2]');
  cosine_distance 
 -----------------
                1
 (1 row)
 
-SELECT cosine_distance('[1,1]', '[-1,-1]');
+SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
  cosine_distance 
 -----------------
                2
 (1 row)
 
-SELECT cosine_distance('[1,2]', '[3]');
+SELECT cosine_distance('[1,2]'::vector, '[3]');
 ERROR:  different vector dimensions 2 and 1
-SELECT cosine_distance('[1,1]', '[1.1,1.1]');
+SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
  cosine_distance 
 -----------------
                0
 (1 row)
 
-SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
+SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
  cosine_distance 
 -----------------
                2
 (1 row)
 
-SELECT cosine_distance('[3e38]', '[3e38]');
+SELECT cosine_distance('[3e38]'::vector, '[3e38]');
  cosine_distance 
 -----------------
              NaN

test/expected/tinyint.out

@@ -0,0 +1,148 @@
+SELECT '127'::tinyint;
+ tinyint 
+---------
+ 127
+(1 row)
+
+SELECT '128'::tinyint;
+ERROR:  value "128" is out of range for type tinyint
+LINE 1: SELECT '128'::tinyint;
+               ^
+SELECT '-128'::tinyint;
+ tinyint 
+---------
+ -128
+(1 row)
+
+SELECT '-129'::tinyint;
+ERROR:  value "-129" is out of range for type tinyint
+LINE 1: SELECT '-129'::tinyint;
+               ^
+SELECT ''::tinyint;
+ERROR:  invalid input syntax for type tinyint: ""
+LINE 1: SELECT ''::tinyint;
+               ^
+SELECT ' 1'::tinyint;
+ tinyint 
+---------
+ 1
+(1 row)
+
+SELECT '1 '::tinyint;
+ tinyint 
+---------
+ 1
+(1 row)
+
+SELECT '1a'::tinyint;
+ERROR:  invalid input syntax for type tinyint: "1a"
+LINE 1: SELECT '1a'::tinyint;
+               ^
+SELECT '{1,2,3}'::tinyint[];
+ tinyint 
+---------
+ {1,2,3}
+(1 row)
+
+SELECT '128'::numeric::tinyint;
+ERROR:  value "128" is out of range for type tinyint
+SELECT 'NaN'::numeric::tinyint;
+ERROR:  cannot convert NaN to integer
+SELECT l2_distance('{0,0}'::tinyint[], '{3,4}'::tinyint[]);
+ l2_distance 
+-------------
+           5
+(1 row)
+
+SELECT l2_distance('{0,0}'::tinyint[], '{0,1}'::tinyint[]);
+ l2_distance 
+-------------
+           1
+(1 row)
+
+SELECT l2_distance('{1,2}'::tinyint[], '{3}'::tinyint[]);
+ l2_distance 
+-------------
+            
+(1 row)
+
+SELECT l2_distance('{3e38}'::tinyint[], '{-3e38}'::tinyint[]);
+ERROR:  invalid input syntax for type tinyint: "3e38"
+LINE 1: SELECT l2_distance('{3e38}'::tinyint[], '{-3e38}'::tinyint[]...
+                           ^
+SELECT '{0,0}'::tinyint[] <-> '{3,4}'::tinyint[];
+ ?column? 
+----------
+        5
+(1 row)
+
+SELECT inner_product('{1,2}'::tinyint[], '{3,4}'::tinyint[]);
+ inner_product 
+---------------
+            11
+(1 row)
+
+SELECT inner_product('{1,2}'::tinyint[], '{3}'::tinyint[]);
+ inner_product 
+---------------
+              
+(1 row)
+
+SELECT inner_product('{127}'::tinyint[], '{127}'::tinyint[]);
+ inner_product 
+---------------
+         16129
+(1 row)
+
+SELECT '{1,2}'::tinyint[] <#> '{3,4}'::tinyint[];
+ ?column? 
+----------
+      -11
+(1 row)
+
+SELECT cosine_distance('{1,2}'::tinyint[], '{2,4}'::tinyint[]);
+ cosine_distance 
+-----------------
+               0
+(1 row)
+
+SELECT cosine_distance('{1,2}'::tinyint[], '{0,0}'::tinyint[]);
+ cosine_distance 
+-----------------
+             NaN
+(1 row)
+
+SELECT cosine_distance('{1,1}'::tinyint[], '{1,1}'::tinyint[]);
+ cosine_distance 
+-----------------
+               0
+(1 row)
+
+SELECT cosine_distance('{1,0}'::tinyint[], '{0,2}'::tinyint[]);
+ cosine_distance 
+-----------------
+               1
+(1 row)
+
+SELECT cosine_distance('{1,1}'::tinyint[], '{-1,-1}'::tinyint[]);
+ cosine_distance 
+-----------------
+               2
+(1 row)
+
+SELECT cosine_distance('{1,2}'::tinyint[], '{3}'::tinyint[]);
+ cosine_distance 
+-----------------
+                
+(1 row)
+
+SELECT cosine_distance('{3e38}'::tinyint[], '{3e38}'::tinyint[]);
+ERROR:  invalid input syntax for type tinyint: "3e38"
+LINE 1: SELECT cosine_distance('{3e38}'::tinyint[], '{3e38}'::tinyin...
+                               ^
+SELECT '{1,2}'::tinyint[] <=> '{2,4}'::tinyint[];
+ ?column? 
+----------
+        0
+(1 row)
+

test/sql/functions.sql

@@ -13,24 +13,24 @@ SELECT vector_norm('[3,4]');
 SELECT vector_norm('[0,1]');
 SELECT vector_norm('[3e37,4e37]')::real;
 
-SELECT l2_distance('[0,0]', '[3,4]');
-SELECT l2_distance('[0,0]', '[0,1]');
-SELECT l2_distance('[1,2]', '[3]');
-SELECT l2_distance('[3e38]', '[-3e38]');
+SELECT l2_distance('[0,0]'::vector, '[3,4]');
+SELECT l2_distance('[0,0]'::vector, '[0,1]');
+SELECT l2_distance('[1,2]'::vector, '[3]');
+SELECT l2_distance('[3e38]'::vector, '[-3e38]');
 
-SELECT inner_product('[1,2]', '[3,4]');
-SELECT inner_product('[1,2]', '[3]');
-SELECT inner_product('[3e38]', '[3e38]');
+SELECT inner_product('[1,2]'::vector, '[3,4]');
+SELECT inner_product('[1,2]'::vector, '[3]');
+SELECT inner_product('[3e38]'::vector, '[3e38]');
 
-SELECT cosine_distance('[1,2]', '[2,4]');
-SELECT cosine_distance('[1,2]', '[0,0]');
-SELECT cosine_distance('[1,1]', '[1,1]');
-SELECT cosine_distance('[1,0]', '[0,2]');
-SELECT cosine_distance('[1,1]', '[-1,-1]');
-SELECT cosine_distance('[1,2]', '[3]');
-SELECT cosine_distance('[1,1]', '[1.1,1.1]');
-SELECT cosine_distance('[1,1]', '[-1.1,-1.1]');
-SELECT cosine_distance('[3e38]', '[3e38]');
+SELECT cosine_distance('[1,2]'::vector, '[2,4]');
+SELECT cosine_distance('[1,2]'::vector, '[0,0]');
+SELECT cosine_distance('[1,1]'::vector, '[1,1]');
+SELECT cosine_distance('[1,0]'::vector, '[0,2]');
+SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
+SELECT cosine_distance('[1,2]'::vector, '[3]');
+SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
+SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
+SELECT cosine_distance('[3e38]'::vector, '[3e38]');
 
 SELECT l1_distance('[0,0]', '[3,4]');
 SELECT l1_distance('[0,0]', '[0,1]');

test/sql/tinyint.sql

@@ -0,0 +1,34 @@
+SELECT '127'::tinyint;
+SELECT '128'::tinyint;
+SELECT '-128'::tinyint;
+SELECT '-129'::tinyint;
+
+SELECT ''::tinyint;
+SELECT ' 1'::tinyint;
+SELECT '1 '::tinyint;
+SELECT '1a'::tinyint;
+
+SELECT '{1,2,3}'::tinyint[];
+
+SELECT '128'::numeric::tinyint;
+SELECT 'NaN'::numeric::tinyint;
+
+SELECT l2_distance('{0,0}'::tinyint[], '{3,4}'::tinyint[]);
+SELECT l2_distance('{0,0}'::tinyint[], '{0,1}'::tinyint[]);
+SELECT l2_distance('{1,2}'::tinyint[], '{3}'::tinyint[]);
+SELECT l2_distance('{3e38}'::tinyint[], '{-3e38}'::tinyint[]);
+SELECT '{0,0}'::tinyint[] <-> '{3,4}'::tinyint[];
+
+SELECT inner_product('{1,2}'::tinyint[], '{3,4}'::tinyint[]);
+SELECT inner_product('{1,2}'::tinyint[], '{3}'::tinyint[]);
+SELECT inner_product('{127}'::tinyint[], '{127}'::tinyint[]);
+SELECT '{1,2}'::tinyint[] <#> '{3,4}'::tinyint[];
+
+SELECT cosine_distance('{1,2}'::tinyint[], '{2,4}'::tinyint[]);
+SELECT cosine_distance('{1,2}'::tinyint[], '{0,0}'::tinyint[]);
+SELECT cosine_distance('{1,1}'::tinyint[], '{1,1}'::tinyint[]);
+SELECT cosine_distance('{1,0}'::tinyint[], '{0,2}'::tinyint[]);
+SELECT cosine_distance('{1,1}'::tinyint[], '{-1,-1}'::tinyint[]);
+SELECT cosine_distance('{1,2}'::tinyint[], '{3}'::tinyint[]);
+SELECT cosine_distance('{3e38}'::tinyint[], '{3e38}'::tinyint[]);
+SELECT '{1,2}'::tinyint[] <=> '{2,4}'::tinyint[];

vector.control

@@ -1,4 +1,4 @@
 comment = 'vector data type and ivfflat and hnsw access methods'
-default_version = '0.5.1'
+default_version = '0.5.0'
 module_pathname = '$libdir/vector'
 relocatable = true