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17 Commits

Author SHA1 Message Date
Andrew Kane
2a7b954beb Fixed version check for palloc variants, take 2 2026-07-27 22:30:23 -07:00
Andrew Kane
0b2d92bc4f Fixed version check for palloc variants 2026-07-27 22:25:21 -07:00
Andrew Kane
e6bd4c8acf Improved CreateStateDatums [skip ci] 2026-07-27 22:09:33 -07:00
Andrew Kane
1be6148eca Switched to palloc_array and palloc0_array where possible 2026-07-27 21:51:15 -07:00
Andrew Kane
bc4e6a13a2 Updated changelog [skip ci] 2026-07-27 21:47:57 -07:00
Andrew Kane
c267348f21 Updated changelog [skip ci] 2026-07-27 21:39:46 -07:00
zthhhhh
93a5b4a16d Fix memory leak in ivfrescan 2026-07-27 21:22:17 -07:00
Andrew Kane
c0919bc26a Added nnz check for vector/halfvec to sparsevec casts (in case limits change in future) [skip ci]
Co-authored-by: 0xJi3F
2026-07-27 20:38:17 -07:00
Andrew Kane
3566276bd4 Fixed array to sparsevec cast not limiting to 16,000 non-zero elements [skip ci]
Co-authored-by: 0xJi3F
2026-07-27 20:33:15 -07:00
Andrew Kane
3e523434f4 Added test for array to halfvec cast [skip ci] 2026-07-27 20:30:04 -07:00
Andrew Kane
d2e2aa0e63 Switched to palloc_object and palloc0_object when possible 2026-07-27 19:26:50 -07:00
Andrew Kane
573040d3a2 Hardened VectorArrayGet [skip ci] 2026-07-27 16:14:25 -07:00
Andrew Kane
a6420355c5 Updated FreeBSD package name in readme [skip ci] 2026-07-10 22:17:27 -07:00
Andrew Kane
73356ecfa7 Improved check for VectorArrayInit [skip ci] 2026-07-10 16:30:35 -07:00
Andrew Kane
0e557b1d18 Updated readme [skip ci] 2026-07-10 15:16:36 -07:00
Andrew Kane
769a60884c Updated readme [skip ci] 2026-07-10 14:20:26 -07:00
Andrew Kane
8711840058 Added section on multitenancy [skip ci] 2026-07-10 14:13:13 -07:00
18 changed files with 91 additions and 35 deletions

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@@ -1,3 +1,8 @@
## 0.8.6 (unreleased)
- Fixed array to `sparsevec` cast not limiting non-zero elements
- Fixed memory usage for IVFFlat index scans with nested loop joins
## 0.8.5 (2026-07-08) ## 0.8.5 (2026-07-08)
- Reduced memory usage for small tables for IVFFlat index builds - Reduced memory usage for small tables for IVFFlat index builds

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@@ -465,6 +465,16 @@ If filtering by many different values, consider [partitioning](https://www.postg
CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id); CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
``` ```
## Multitenancy
For applications with multiple tenants, sharing an approximate index between tenants means vectors from one tenant can affect recall (and speed) for other tenants.
For tenant isolation, use [list partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html) or separate tables.
```sql
CREATE TABLE items (customer_id int, embedding vector(3)) PARTITION BY LIST(customer_id);
```
## Iterative Index Scans ## Iterative Index Scans
With approximate indexes, queries with filtering can return less results since filtering is applied *after* the index is scanned. Starting with 0.8.0, you can enable iterative index scans, which will automatically scan more of the index until enough results are found (or it reaches `hnsw.max_scan_tuples` or `ivfflat.max_probes`). With approximate indexes, queries with filtering can return less results since filtering is applied *after* the index is scanned. Starting with 0.8.0, you can enable iterative index scans, which will automatically scan more of the index until enough results are found (or it reaches `hnsw.max_scan_tuples` or `ivfflat.max_probes`).
@@ -1223,7 +1233,7 @@ Note: Replace `18` with your Postgres server version
Install the FreeBSD package with: Install the FreeBSD package with:
```sh ```sh
pkg install postgresql17-pgvector pkg install postgresql18-pgvector
``` ```
or the port with: or the port with:

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@@ -27,8 +27,12 @@
#include "parser/scansup.h" #include "parser/scansup.h"
#endif #endif
#if PG_VERSION_NUM < 140006
#define palloc_array(type, count) ((type *) palloc(sizeof(type) * (count)))
#endif
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1) #define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1)) #define CreateStateDatums(dim) palloc_array(Datum, (dim) + 1)
/* /*
* Get a half from a message buffer * Get a half from a message buffer
@@ -513,7 +517,7 @@ halfvec_to_float4(PG_FUNCTION_ARGS)
Datum *datums; Datum *datums;
ArrayType *result; ArrayType *result;
datums = (Datum *) palloc(sizeof(Datum) * vec->dim); datums = palloc_array(Datum, vec->dim);
for (int i = 0; i < vec->dim; i++) for (int i = 0; i < vec->dim; i++)
datums[i] = Float4GetDatum(HalfToFloat4(vec->x[i])); datums[i] = Float4GetDatum(HalfToFloat4(vec->x[i]));

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@@ -105,6 +105,12 @@ typedef Pointer Item;
#define SeedRandom(seed) srandom(seed) #define SeedRandom(seed) srandom(seed)
#endif #endif
#if PG_VERSION_NUM < 140006
#define palloc_object(type) ((type *) palloc(sizeof(type)))
#define palloc0_object(type) ((type *) palloc0(sizeof(type)))
#define palloc_array(type, count) ((type *) palloc(sizeof(type) * (count)))
#endif
#define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE) #define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
#define HnswIsNeighborTuple(tup) ((tup)->type == HNSW_NEIGHBOR_TUPLE_TYPE) #define HnswIsNeighborTuple(tup) ((tup)->type == HNSW_NEIGHBOR_TUPLE_TYPE)

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@@ -930,7 +930,7 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
Size estother; Size estother;
HnswShared *hnswshared; HnswShared *hnswshared;
char *hnswarea; char *hnswarea;
HnswLeader *hnswleader = (HnswLeader *) palloc0(sizeof(HnswLeader)); HnswLeader *hnswleader = palloc0_object(HnswLeader);
bool leaderparticipates = true; bool leaderparticipates = true;
int querylen; int querylen;
@@ -1151,7 +1151,7 @@ hnswbuild(Relation heap, Relation index, IndexInfo *indexInfo)
BuildIndex(heap, index, indexInfo, &buildstate, MAIN_FORKNUM); BuildIndex(heap, index, indexInfo, &buildstate, MAIN_FORKNUM);
result = (IndexBuildResult *) palloc(sizeof(IndexBuildResult)); result = palloc_object(IndexBuildResult);
result->heap_tuples = buildstate.reltuples; result->heap_tuples = buildstate.reltuples;
result->index_tuples = buildstate.indtuples; result->index_tuples = buildstate.indtuples;

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@@ -136,7 +136,7 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
scan = RelationGetIndexScan(index, nkeys, norderbys); scan = RelationGetIndexScan(index, nkeys, norderbys);
so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData)); so = palloc_object(HnswScanOpaqueData);
so->typeInfo = HnswGetTypeInfo(index); so->typeInfo = HnswGetTypeInfo(index);
/* Set support functions */ /* Set support functions */

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@@ -282,7 +282,7 @@ HnswAddHeapTid(HnswElement element, ItemPointer heaptid)
HnswElement HnswElement
HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno) HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno)
{ {
HnswElement element = palloc(sizeof(HnswElementData)); HnswElement element = palloc_object(HnswElementData);
char *base = NULL; char *base = NULL;
element->blkno = blkno; element->blkno = blkno;
@@ -596,7 +596,7 @@ GetElementDistance(char *base, HnswElement element, HnswQuery * q, HnswSupport *
static HnswSearchCandidate * static HnswSearchCandidate *
HnswInitSearchCandidate(char *base, HnswElement element, double distance) HnswInitSearchCandidate(char *base, HnswElement element, double distance)
{ {
HnswSearchCandidate *sc = palloc(sizeof(HnswSearchCandidate)); HnswSearchCandidate *sc = palloc_object(HnswSearchCandidate);
HnswPtrStore(base, sc->element, element); HnswPtrStore(base, sc->element, element);
sc->distance = distance; sc->distance = distance;
@@ -831,7 +831,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
HnswNeighborArray *localNeighborhood = NULL; HnswNeighborArray *localNeighborhood = NULL;
Size neighborhoodSize = 0; Size neighborhoodSize = 0;
int lm = HnswGetLayerM(m, lc); int lm = HnswGetLayerM(m, lc);
HnswUnvisited *unvisited = palloc(lm * sizeof(HnswUnvisited)); HnswUnvisited *unvisited = palloc_array(HnswUnvisited, lm);
int unvisitedLength; int unvisitedLength;
bool inMemory = index == NULL; bool inMemory = index == NULL;
@@ -1074,7 +1074,7 @@ SelectNeighbors(char *base, List *c, int lm, HnswSupport * support, bool *closer
if (list_length(w) <= lm) if (list_length(w) <= lm)
return w; return w;
wd = palloc(sizeof(HnswCandidate *) * list_length(w)); wd = palloc_array(HnswCandidate *, list_length(w));
/* Ensure order of candidates is deterministic for closer caching */ /* Ensure order of candidates is deterministic for closer caching */
if (sortCandidates) if (sortCandidates)
@@ -1328,7 +1328,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
foreach(lc2, w) foreach(lc2, w)
{ {
HnswSearchCandidate *sc = lfirst(lc2); HnswSearchCandidate *sc = lfirst(lc2);
HnswCandidate *hc = palloc(sizeof(HnswCandidate)); HnswCandidate *hc = palloc_object(HnswCandidate);
hc->element = sc->element; hc->element = sc->element;
hc->distance = sc->distance; hc->distance = sc->distance;

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@@ -737,7 +737,7 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
Relation index = info->index; Relation index = info->index;
if (stats == NULL) if (stats == NULL)
stats = (IndexBulkDeleteResult *) palloc0(sizeof(IndexBulkDeleteResult)); stats = palloc0_object(IndexBulkDeleteResult);
vacuumstate->index = index; vacuumstate->index = index;
vacuumstate->stats = stats; vacuumstate->stats = stats;

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@@ -396,7 +396,7 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, buildstate->itemsize); buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, buildstate->itemsize);
/* TODO Move allocation to page creation */ /* TODO Move allocation to page creation */
buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists); buildstate->listInfo = palloc_array(ListInfo, buildstate->lists);
buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext, buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
"Ivfflat build temporary context", "Ivfflat build temporary context",
@@ -404,8 +404,8 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
#ifdef IVFFLAT_KMEANS_DEBUG #ifdef IVFFLAT_KMEANS_DEBUG
buildstate->inertia = 0; buildstate->inertia = 0;
buildstate->listSums = palloc0(sizeof(double) * buildstate->lists); buildstate->listSums = palloc0_array(double, buildstate->lists);
buildstate->listCounts = palloc0(sizeof(int) * buildstate->lists); buildstate->listCounts = palloc0_array(int, buildstate->lists);
#endif #endif
buildstate->ivfleader = NULL; buildstate->ivfleader = NULL;
@@ -662,7 +662,7 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
IndexInfo *indexInfo; IndexInfo *indexInfo;
/* Initialize local tuplesort coordination state */ /* Initialize local tuplesort coordination state */
coordinate = palloc0(sizeof(SortCoordinateData)); coordinate = palloc0_object(SortCoordinateData);
coordinate->isWorker = true; coordinate->isWorker = true;
coordinate->nParticipants = -1; coordinate->nParticipants = -1;
coordinate->sharedsort = sharedsort; coordinate->sharedsort = sharedsort;
@@ -757,7 +757,7 @@ IvfflatParallelBuildMain(dsm_segment *seg, shm_toc *toc)
indexRel = index_open(ivfshared->indexrelid, indexLockmode); indexRel = index_open(ivfshared->indexrelid, indexLockmode);
/* Initialize worker's own spool */ /* Initialize worker's own spool */
ivfspool = (IvfflatSpool *) palloc0(sizeof(IvfflatSpool)); ivfspool = palloc0_object(IvfflatSpool);
ivfspool->heap = heapRel; ivfspool->heap = heapRel;
ivfspool->index = indexRel; ivfspool->index = indexRel;
@@ -812,7 +812,7 @@ IvfflatLeaderParticipateAsWorker(IvfflatBuildState * buildstate)
int sortmem; int sortmem;
/* Allocate memory and initialize private spool */ /* Allocate memory and initialize private spool */
leaderworker = (IvfflatSpool *) palloc0(sizeof(IvfflatSpool)); leaderworker = palloc0_object(IvfflatSpool);
leaderworker->heap = buildstate->heap; leaderworker->heap = buildstate->heap;
leaderworker->index = buildstate->index; leaderworker->index = buildstate->index;
@@ -838,7 +838,7 @@ IvfflatBeginParallel(IvfflatBuildState * buildstate, bool isconcurrent, int requ
IvfflatShared *ivfshared; IvfflatShared *ivfshared;
Sharedsort *sharedsort; Sharedsort *sharedsort;
char *ivfcenters; char *ivfcenters;
IvfflatLeader *ivfleader = (IvfflatLeader *) palloc0(sizeof(IvfflatLeader)); IvfflatLeader *ivfleader = palloc0_object(IvfflatLeader);
bool leaderparticipates = true; bool leaderparticipates = true;
int querylen; int querylen;
@@ -987,7 +987,7 @@ AssignTuples(IvfflatBuildState * buildstate)
/* Set up coordination state if at least one worker launched */ /* Set up coordination state if at least one worker launched */
if (buildstate->ivfleader) if (buildstate->ivfleader)
{ {
coordinate = (SortCoordinate) palloc0(sizeof(SortCoordinateData)); coordinate = palloc0_object(SortCoordinateData);
coordinate->isWorker = false; coordinate->isWorker = false;
coordinate->nParticipants = buildstate->ivfleader->nparticipanttuplesorts; coordinate->nParticipants = buildstate->ivfleader->nparticipanttuplesorts;
coordinate->sharedsort = buildstate->ivfleader->sharedsort; coordinate->sharedsort = buildstate->ivfleader->sharedsort;
@@ -1072,7 +1072,7 @@ ivfflatbuild(Relation heap, Relation index, IndexInfo *indexInfo)
BuildIndex(heap, index, indexInfo, &buildstate, MAIN_FORKNUM); BuildIndex(heap, index, indexInfo, &buildstate, MAIN_FORKNUM);
result = (IndexBuildResult *) palloc(sizeof(IndexBuildResult)); result = palloc_object(IndexBuildResult);
result->heap_tuples = buildstate.reltuples; result->heap_tuples = buildstate.reltuples;
result->index_tuples = buildstate.indtuples; result->index_tuples = buildstate.indtuples;

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@@ -89,6 +89,13 @@ typedef Pointer Item;
#define SeedRandom(seed) srandom(seed) #define SeedRandom(seed) srandom(seed)
#endif #endif
#if PG_VERSION_NUM < 140006
#define palloc_object(type) ((type *) palloc(sizeof(type)))
#define palloc0_object(type) ((type *) palloc0(sizeof(type)))
#define palloc_array(type, count) ((type *) palloc(sizeof(type) * (count)))
#define palloc0_array(type, count) ((type *) palloc0(sizeof(type) * (count)))
#endif
/* Variables */ /* Variables */
extern int ivfflat_probes; extern int ivfflat_probes;
extern int ivfflat_iterative_scan; extern int ivfflat_iterative_scan;
@@ -305,7 +312,7 @@ typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
static inline Pointer static inline Pointer
VectorArrayGet(VectorArray arr, int offset) VectorArrayGet(VectorArray arr, int offset)
{ {
if (offset >= arr->maxlen) if (offset < 0 || offset >= arr->maxlen)
elog(ERROR, "safety check failed"); elog(ERROR, "safety check failed");
return ((char *) arr->items) + (offset * arr->itemsize); return ((char *) arr->items) + (offset * arr->itemsize);

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@@ -26,7 +26,7 @@ InitCenters(Relation index, VectorArray samples, VectorArray centers, float *low
FmgrInfo *procinfo; FmgrInfo *procinfo;
Oid collation; Oid collation;
int64 j; int64 j;
float *weight = palloc(samples->length * sizeof(float)); float *weight = palloc_array(float, samples->length);
int numCenters = centers->maxlen; int numCenters = centers->maxlen;
int numSamples = samples->length; int numSamples = samples->length;
@@ -113,7 +113,7 @@ RandomCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeI
int dimensions = centers->dim; int dimensions = centers->dim;
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC); FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
Oid collation = index->rd_indcollation[0]; Oid collation = index->rd_indcollation[0];
float *x = (float *) palloc(sizeof(float) * dimensions); float *x = palloc_array(float, dimensions);
/* Fill with random data */ /* Fill with random data */
while (centers->length < centers->maxlen) while (centers->length < centers->maxlen)
@@ -480,7 +480,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
static void static void
CheckElements(VectorArray centers, const IvfflatTypeInfo * typeInfo) CheckElements(VectorArray centers, const IvfflatTypeInfo * typeInfo)
{ {
float *scratch = palloc(sizeof(float) * centers->dim); float *scratch = palloc_array(float, centers->dim);
for (int i = 0; i < centers->length; i++) for (int i = 0; i < centers->length; i++)
{ {

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@@ -276,12 +276,13 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
if (maxProbes > lists) if (maxProbes > lists)
maxProbes = lists; maxProbes = lists;
so = (IvfflatScanOpaque) palloc(sizeof(IvfflatScanOpaqueData)); so = palloc_object(IvfflatScanOpaqueData);
so->typeInfo = IvfflatGetTypeInfo(index); so->typeInfo = IvfflatGetTypeInfo(index);
so->first = true; so->first = true;
so->probes = probes; so->probes = probes;
so->maxProbes = maxProbes; so->maxProbes = maxProbes;
so->dimensions = dimensions; so->dimensions = dimensions;
so->value = PointerGetDatum(NULL);
/* Set support functions */ /* Set support functions */
so->procinfo = index_getprocinfo(index, 1, IVFFLAT_DISTANCE_PROC); so->procinfo = index_getprocinfo(index, 1, IVFFLAT_DISTANCE_PROC);
@@ -317,9 +318,9 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
so->bas = GetAccessStrategy(BAS_BULKREAD); so->bas = GetAccessStrategy(BAS_BULKREAD);
so->listQueue = pairingheap_allocate(CompareLists, scan); so->listQueue = pairingheap_allocate(CompareLists, scan);
so->listPages = palloc(maxProbes * sizeof(BlockNumber)); so->listPages = palloc_array(BlockNumber, maxProbes);
so->listIndex = 0; so->listIndex = 0;
so->lists = palloc(maxProbes * sizeof(IvfflatScanList)); so->lists = palloc_array(IvfflatScanList, maxProbes);
MemoryContextSwitchTo(oldCtx); MemoryContextSwitchTo(oldCtx);
@@ -340,6 +341,12 @@ ivfflatrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int
pairingheap_reset(so->listQueue); pairingheap_reset(so->listQueue);
so->listIndex = 0; so->listIndex = 0;
if (so->normprocinfo != NULL && DatumGetPointer(so->value) != NULL)
{
pfree(DatumGetPointer(so->value));
so->value = PointerGetDatum(NULL);
}
if (keys && scan->numberOfKeys > 0) if (keys && scan->numberOfKeys > 0)
memmove(scan->keyData, keys, scan->numberOfKeys * sizeof(ScanKeyData)); memmove(scan->keyData, keys, scan->numberOfKeys * sizeof(ScanKeyData));

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@@ -25,13 +25,13 @@ VectorArrayInit(int maxlen, int dimensions, Size itemsize)
{ {
VectorArray res; VectorArray res;
if (maxlen < 1 || dimensions < 1) if (maxlen < 1 || dimensions < 1 || itemsize == 0)
elog(ERROR, "safety check failed"); elog(ERROR, "cannot create vector array");
/* Ensure items are aligned to prevent UB */ /* Ensure items are aligned to prevent UB */
itemsize = MAXALIGN(itemsize); itemsize = MAXALIGN(itemsize);
res = palloc(sizeof(VectorArrayData)); res = palloc_object(VectorArrayData);
res->length = 0; res->length = 0;
res->maxlen = maxlen; res->maxlen = maxlen;
res->dim = dimensions; res->dim = dimensions;

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@@ -24,7 +24,7 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
BufferAccessStrategy bas = GetAccessStrategy(BAS_BULKREAD); BufferAccessStrategy bas = GetAccessStrategy(BAS_BULKREAD);
if (stats == NULL) if (stats == NULL)
stats = (IndexBulkDeleteResult *) palloc0(sizeof(IndexBulkDeleteResult)); stats = palloc0_object(IndexBulkDeleteResult);
/* Iterate over list pages */ /* Iterate over list pages */
while (BlockNumberIsValid(blkno)) while (BlockNumberIsValid(blkno))

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@@ -26,6 +26,10 @@
#include "parser/scansup.h" #include "parser/scansup.h"
#endif #endif
#if PG_VERSION_NUM < 140006
#define palloc_array(type, count) ((type *) palloc(sizeof(type) * (count)))
#endif
typedef struct SparseInputElement typedef struct SparseInputElement
{ {
int32 index; int32 index;
@@ -223,7 +227,7 @@ sparsevec_in(PG_FUNCTION_ARGS)
(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED), (errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
errmsg("sparsevec cannot have more than %d non-zero elements", SPARSEVEC_MAX_NNZ))); errmsg("sparsevec cannot have more than %d non-zero elements", SPARSEVEC_MAX_NNZ)));
elements = palloc(maxNnz * sizeof(SparseInputElement)); elements = palloc_array(SparseInputElement, maxNnz);
pt = lit; pt = lit;
@@ -614,6 +618,7 @@ vector_to_sparsevec(PG_FUNCTION_ARGS)
nnz++; nnz++;
} }
CheckNnz(nnz, dim);
result = InitSparseVector(dim, nnz); result = InitSparseVector(dim, nnz);
values = SPARSEVEC_VALUES(result); values = SPARSEVEC_VALUES(result);
for (int i = 0; i < dim; i++) for (int i = 0; i < dim; i++)
@@ -657,6 +662,7 @@ halfvec_to_sparsevec(PG_FUNCTION_ARGS)
nnz++; nnz++;
} }
CheckNnz(nnz, dim);
result = InitSparseVector(dim, nnz); result = InitSparseVector(dim, nnz);
values = SPARSEVEC_VALUES(result); values = SPARSEVEC_VALUES(result);
for (int i = 0; i < dim; i++) for (int i = 0; i < dim; i++)
@@ -745,6 +751,7 @@ array_to_sparsevec(PG_FUNCTION_ARGS)
errmsg("unsupported array type"))); errmsg("unsupported array type")));
} }
CheckNnz(nnz, nelemsp);
result = InitSparseVector(nelemsp, nnz); result = InitSparseVector(nelemsp, nnz);
values = SPARSEVEC_VALUES(result); values = SPARSEVEC_VALUES(result);

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@@ -30,8 +30,12 @@
#include "parser/scansup.h" #include "parser/scansup.h"
#endif #endif
#if PG_VERSION_NUM < 140006
#define palloc_array(type, count) ((type *) palloc(sizeof(type) * (count)))
#endif
#define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1) #define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
#define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1)) #define CreateStateDatums(dim) palloc_array(Datum, (dim) + 1)
#if defined(USE_TARGET_CLONES) && !defined(__FMA__) #if defined(USE_TARGET_CLONES) && !defined(__FMA__)
#define VECTOR_TARGET_CLONES __attribute__((target_clones("default", "fma"))) #define VECTOR_TARGET_CLONES __attribute__((target_clones("default", "fma")))
@@ -516,7 +520,7 @@ vector_to_float4(PG_FUNCTION_ARGS)
Datum *datums; Datum *datums;
ArrayType *result; ArrayType *result;
datums = (Datum *) palloc(sizeof(Datum) * vec->dim); datums = palloc_array(Datum, vec->dim);
for (int i = 0; i < vec->dim; i++) for (int i = 0; i < vec->dim; i++)
datums[i] = Float4GetDatum(vec->x[i]); datums[i] = Float4GetDatum(vec->x[i]);

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@@ -268,6 +268,10 @@ SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
ERROR: vector cannot have more than 16000 dimensions ERROR: vector cannot have more than 16000 dimensions
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n; SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;
ERROR: vector cannot have more than 16000 dimensions ERROR: vector cannot have more than 16000 dimensions
SELECT array_agg(n)::halfvec FROM generate_series(1, 16001) n;
ERROR: halfvec cannot have more than 16000 dimensions
SELECT array_agg(n)::sparsevec FROM generate_series(1, 16001) n;
ERROR: sparsevec cannot have more than 16000 non-zero elements
-- ensure no error -- ensure no error
SELECT ARRAY[1,2,3] = ARRAY[1,2,3]; SELECT ARRAY[1,2,3] = ARRAY[1,2,3];
?column? ?column?

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@@ -76,6 +76,8 @@ SELECT '{{1}}'::real[]::sparsevec;
SELECT array_agg(n)::vector FROM generate_series(1, 16001) n; SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n; SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;
SELECT array_agg(n)::halfvec FROM generate_series(1, 16001) n;
SELECT array_agg(n)::sparsevec FROM generate_series(1, 16001) n;
-- ensure no error -- ensure no error
SELECT ARRAY[1,2,3] = ARRAY[1,2,3]; SELECT ARRAY[1,2,3] = ARRAY[1,2,3];