Updated SparsevecInnerProduct [skip ci]

.github/workflows/build.yml

@@ -8,12 +8,10 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          - postgres: 20
-            os: ubuntu-26.04
           - postgres: 19
-            os: ubuntu-26.04
+            os: ubuntu-24.04
           - postgres: 18
-            os: ubuntu-26.04-arm
+            os: ubuntu-24.04
           - postgres: 17
             os: ubuntu-24.04
           - postgres: 16
@@ -25,7 +23,7 @@ jobs:
           - postgres: 13
             os: ubuntu-22.04
     steps:
-      - uses: actions/checkout@v7
+      - uses: actions/checkout@v6
       - uses: ankane/setup-postgres@v1
         with:
           postgres-version: ${{ matrix.postgres }}
@@ -55,7 +53,7 @@ jobs:
           - postgres: 14
             os: macos-15-intel
     steps:
-      - uses: actions/checkout@v7
+      - uses: actions/checkout@v6
       - uses: ankane/setup-postgres@v1
         with:
           postgres-version: ${{ matrix.postgres }}
@@ -94,12 +92,12 @@ jobs:
           - postgres: 14
             os: windows-2022
     steps:
-      - uses: actions/checkout@v7
+      - uses: actions/checkout@v6
       - uses: ankane/setup-postgres@v1
         with:
           postgres-version: ${{ matrix.postgres }}
       - run: |
-          call "C:\Program Files\Microsoft Visual Studio\${{ matrix.os == 'windows-2025' && 18 || 2022 }}\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
+          call "C:\Program Files\Microsoft Visual Studio\2022\Enterprise\VC\Auxiliary\Build\vcvars64.bat" && ^
           nmake /NOLOGO /F Makefile.win && ^
           nmake /NOLOGO /F Makefile.win install && ^
           nmake /NOLOGO /F Makefile.win installcheck ${{ matrix.postgres != 17 && 'PG_REGRESS=$(PGROOT)\bin\pg_regress' || '' }} && ^
@@ -135,7 +133,7 @@ jobs:
     if: ${{ !startsWith(github.ref_name, 'mac') && !startsWith(github.ref_name, 'windows') }}
     runs-on: ubuntu-latest
     steps:
-      - uses: actions/checkout@v7
+      - uses: actions/checkout@v6
       - uses: ankane/setup-postgres-valgrind@v1
         with:
           postgres-version: 18

CHANGELOG.md

@@ -1,18 +1,3 @@
-## 0.8.5 (2026-07-08)
-
-- Reduced memory usage for small tables for IVFFlat index builds
-
-## 0.8.4 (2026-06-30)
-
-- Fixed `hnsw graph not repaired` error with HNSW vacuuming
-- Fixed possible error with inserts during HNSW vacuuming
-- Fixed memory exceeding `maintenance_work_mem` with IVFFlat index builds
-
-## 0.8.3 (2026-06-17)
-
-- Fixed possible index corruption with HNSW vacuuming
-- Fixed performance regression with Hamming distance and Jaccard distance with Postgres 18
-
 ## 0.8.2 (2026-02-25)
 
 - Fixed buffer overflow with parallel HNSW index build - [more info](https://github.com/pgvector/pgvector/issues/959)

Dockerfile

@@ -5,7 +5,7 @@ ARG DEBIAN_CODENAME=bookworm
 FROM postgres:$PG_MAJOR-$DEBIAN_CODENAME
 ARG PG_MAJOR
 
-ADD https://github.com/pgvector/pgvector.git#v0.8.5 /tmp/pgvector
+ADD https://github.com/pgvector/pgvector.git#v0.8.2 /tmp/pgvector
 
 RUN apt-get update && \
 		apt-mark hold locales && \

META.json

@@ -2,12 +2,12 @@
 	"name": "vector",
 	"abstract": "Open-source vector similarity search for Postgres",
 	"description": "Supports L2 distance, inner product, and cosine distance",
-	"version": "0.8.5",
+	"version": "0.8.2",
 	"maintainer": [
 		"Andrew Kane <andrew@ankane.org>"
 	],
 	"license": {
-		"PostgreSQL": "https://www.postgresql.org/about/licence"
+		"PostgreSQL": "http://www.postgresql.org/about/licence"
 	},
 	"prereqs": {
 		"runtime": {
@@ -20,7 +20,7 @@
 		"vector": {
 			"file": "sql/vector.sql",
 			"docfile": "README.md",
-			"version": "0.8.5",
+			"version": "0.8.2",
 			"abstract": "Open-source vector similarity search for Postgres"
 		}
 	},
@@ -38,7 +38,7 @@
 	"generated_by": "Andrew Kane",
 	"meta-spec": {
 		"version": "1.0.0",
-		"url": "https://pgxn.org/meta/spec.txt"
+		"url": "http://pgxn.org/meta/spec.txt"
 	},
 	"tags": [
 		"vectors",

Makefile

@@ -1,5 +1,5 @@
 EXTENSION = vector
-EXTVERSION = 0.8.5
+EXTVERSION = 0.8.2
 
 MODULE_big = vector
 DATA = $(wildcard sql/*--*--*.sql)

Makefile.win

@@ -1,5 +1,5 @@
 EXTENSION = vector
-EXTVERSION = 0.8.5
+EXTVERSION = 0.8.2
 
 DATA_built = sql\$(EXTENSION)--$(EXTVERSION).sql
 OBJS = src\bitutils.obj src\bitvec.obj src\halfutils.obj src\halfvec.obj 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\sparsevec.obj src\vector.obj

README.md

@@ -11,8 +11,6 @@ Store your vectors with the rest of your data. Supports:
 
 Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recovery, JOINs, and all of the other [great features](https://www.postgresql.org/about/) of Postgres
 
-Have a lot of vectors? Use [quantization](#scaling) to scale
-
 [![Build Status](https://github.com/pgvector/pgvector/actions/workflows/build.yml/badge.svg)](https://github.com/pgvector/pgvector/actions)
 
 ## Installation
@@ -23,7 +21,7 @@ Compile and install the extension (supports Postgres 13+)
 
 ```sh
 cd /tmp
-git clone --branch v0.8.5 https://github.com/pgvector/pgvector.git
+git clone --branch v0.8.2 https://github.com/pgvector/pgvector.git
 cd pgvector
 make
 make install # may need sudo
@@ -40,7 +38,7 @@ Ensure [C++ support in Visual Studio](https://learn.microsoft.com/en-us/cpp/buil
 ```cmd
 set "PGROOT=C:\Program Files\PostgreSQL\18"
 cd %TEMP%
-git clone --branch v0.8.5 https://github.com/pgvector/pgvector.git
+git clone --branch v0.8.2 https://github.com/pgvector/pgvector.git
 cd pgvector
 nmake /F Makefile.win
 nmake /F Makefile.win install
@@ -316,8 +314,6 @@ For a large number of workers, you may need to increase `max_parallel_workers` (
 
 The [index options](#index-options) also have a significant impact on build time (use the defaults unless seeing low recall)
 
-Use [binary quantization](#binary-quantization) for faster build times at scale
-
 ### Indexing Progress
 
 Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
@@ -447,7 +443,13 @@ Exact indexes work well for conditions that match a low percentage of rows. Othe
 CREATE INDEX ON items USING hnsw (embedding vector_l2_ops);
 ```
 
-With approximate indexes, filtering is applied *after* the index is scanned. If a condition matches 10% of rows, with HNSW and the default `hnsw.ef_search` of 40, only 4 rows will match on average. For more rows, enable [iterative index scans](#iterative-index-scans), which will automatically scan more of the index when needed.
+With approximate indexes, filtering is applied *after* the index is scanned. If a condition matches 10% of rows, with HNSW and the default `hnsw.ef_search` of 40, only 4 rows will match on average. For more rows, increase `hnsw.ef_search`.
+
+```sql
+SET hnsw.ef_search = 200;
+```
+
+Starting with 0.8.0, you can enable [iterative index scans](#iterative-index-scans), which will automatically scan more of the index when needed.
 
 ```sql
 SET hnsw.iterative_scan = strict_order;
@@ -465,16 +467,6 @@ 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);
 ```
 
-## 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
 
 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`).
@@ -681,10 +673,6 @@ SHOW shared_buffers;
 
 Be sure to restart Postgres for changes to take effect.
 
-### Storing
-
-Use the `halfvec` type instead of `vector` for a smaller working set.
-
 ### Loading
 
 Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py)).
@@ -699,8 +687,6 @@ Add any indexes *after* loading the initial data for best performance.
 
 See index build time for [HNSW](#index-build-time) and [IVFFlat](#index-build-time-1).
 
-Use [binary quantization](#binary-quantization) for smaller indexes and faster build times at scale.
-
 In production environments, create indexes concurrently to avoid blocking writes.
 
 ```sql
@@ -731,8 +717,6 @@ SELECT * FROM items ORDER BY embedding <#> '[3,1,2]' LIMIT 5;
 
 #### Approximate Search
 
-Use [binary quantization](#binary-quantization) with re-ranking to keep indexes in-memory at scale.
-
 To speed up queries with an IVFFlat index, increase the number of inverted lists (at the expense of recall).
 
 ```sql
@@ -748,20 +732,21 @@ REINDEX INDEX CONCURRENTLY index_name;
 VACUUM table_name;
 ```
 
-## Scaling
-
-For a smaller working set:
-
-1. Use the `halfvec` type instead of `vector` for tables
-2. Use [binary quantization](#binary-quantization) for indexes (with re-ranking for search)
-
-Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
-
-Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus), [PgDog](https://github.com/pgdogdev/pgdog), or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus/example.py)).
-
 ## Monitoring
 
-Use existing tools like [pg_stat_statements](https://www.postgresql.org/docs/current/pgstatstatements.html) or [PgHero](https://github.com/ankane/pghero) to monitor performance.
+Monitor performance with [pg_stat_statements](https://www.postgresql.org/docs/current/pgstatstatements.html) (be sure to add it to `shared_preload_libraries`).
+
+```sql
+CREATE EXTENSION pg_stat_statements;
+```
+
+Get the most time-consuming queries with:
+
+```sql
+SELECT query, calls, ROUND((total_plan_time + total_exec_time) / calls) AS avg_time_ms,
+    ROUND((total_plan_time + total_exec_time) / 60000) AS total_time_min
+    FROM pg_stat_statements ORDER BY total_plan_time + total_exec_time DESC LIMIT 20;
+```
 
 Monitor recall by comparing results from approximate search with exact search.
 
@@ -772,6 +757,14 @@ SELECT ...
 COMMIT;
 ```
 
+## Scaling
+
+Scale pgvector the same way you scale Postgres.
+
+Scale vertically by increasing memory, CPU, and storage on a single instance. Use existing tools to [tune parameters](#tuning) and [monitor performance](#monitoring).
+
+Scale horizontally with [replicas](https://www.postgresql.org/docs/current/hot-standby.html), or use [Citus](https://github.com/citusdata/citus) or another approach for sharding ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/citus/example.py)).
+
 ## Languages
 
 Use pgvector from any language with a Postgres client. You can even generate and store vectors in one language and query them in another.
@@ -885,8 +878,6 @@ No, but like other index types, you’ll likely see better performance if they d
 SELECT pg_size_pretty(pg_relation_size('index_name'));
 ```
 
-Use [half-precision indexing](#half-precision-indexing) or [binary quantization](#binary-quantization) for smaller indexes.
-
 ## Troubleshooting
 
 #### Why isn’t a query using an index?
@@ -1161,23 +1152,23 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
 
 Supported tags are:
 
-- `pg18-trixie`, `0.8.5-pg18-trixie`
+- `pg18-trixie`, `0.8.2-pg18-trixie`
-- `pg18-bookworm`, `0.8.5-pg18-bookworm`, `pg18`, `0.8.5-pg18`
+- `pg18-bookworm`, `0.8.2-pg18-bookworm`, `pg18`, `0.8.2-pg18`
-- `pg17-trixie`, `0.8.5-pg17-trixie`
+- `pg17-trixie`, `0.8.2-pg17-trixie`
-- `pg17-bookworm`, `0.8.5-pg17-bookworm`, `pg17`, `0.8.5-pg17`
+- `pg17-bookworm`, `0.8.2-pg17-bookworm`, `pg17`, `0.8.2-pg17`
-- `pg16-trixie`, `0.8.5-pg16-trixie`
+- `pg16-trixie`, `0.8.2-pg16-trixie`
-- `pg16-bookworm`, `0.8.5-pg16-bookworm`, `pg16`, `0.8.5-pg16`
+- `pg16-bookworm`, `0.8.2-pg16-bookworm`, `pg16`, `0.8.2-pg16`
-- `pg15-trixie`, `0.8.5-pg15-trixie`
+- `pg15-trixie`, `0.8.2-pg15-trixie`
-- `pg15-bookworm`, `0.8.5-pg15-bookworm`, `pg15`, `0.8.5-pg15`
+- `pg15-bookworm`, `0.8.2-pg15-bookworm`, `pg15`, `0.8.2-pg15`
-- `pg14-trixie`, `0.8.5-pg14-trixie`
+- `pg14-trixie`, `0.8.2-pg14-trixie`
-- `pg14-bookworm`, `0.8.5-pg14-bookworm`, `pg14`, `0.8.5-pg14`
+- `pg14-bookworm`, `0.8.2-pg14-bookworm`, `pg14`, `0.8.2-pg14`
-- `pg13-trixie`, `0.8.5-pg13-trixie`
+- `pg13-trixie`, `0.8.2-pg13-trixie`
-- `pg13-bookworm`, `0.8.5-pg13-bookworm`, `pg13`, `0.8.5-pg13`
+- `pg13-bookworm`, `0.8.2-pg13-bookworm`, `pg13`, `0.8.2-pg13`
 
 You can also build the image manually:
 
 ```sh
-git clone --branch v0.8.5 https://github.com/pgvector/pgvector.git
+git clone --branch v0.8.2 https://github.com/pgvector/pgvector.git
 cd pgvector
 docker build --pull --build-arg PG_MAJOR=18 -t myuser/pgvector .
 ```
@@ -1233,7 +1224,7 @@ Note: Replace `18` with your Postgres server version
 Install the FreeBSD package with:
 
 ```sh
-pkg install postgresql18-pgvector
+pkg install postgresql17-pgvector
 ```
 
 or the port with:
@@ -1339,7 +1330,7 @@ make clean && PG_CFLAGS="-DUSE_ASSERT_CHECKING" make && make install
 To enable benchmarking:
 
 ```sh
-make clean && PG_CFLAGS="-DHNSW_BENCH -DIVFFLAT_BENCH" make && make install
+make clean && PG_CFLAGS="-DIVFFLAT_BENCH" make && make install
 ```
 
 To show memory usage:

sql/vector--0.8.2--0.8.3.sql

@@ -1,2 +0,0 @@
--- complain if script is sourced in psql, rather than via CREATE EXTENSION
-\echo Use "ALTER EXTENSION vector UPDATE TO '0.8.3'" to load this file. \quit

sql/vector--0.8.3--0.8.4.sql

@@ -1,2 +0,0 @@
--- complain if script is sourced in psql, rather than via CREATE EXTENSION
-\echo Use "ALTER EXTENSION vector UPDATE TO '0.8.4'" to load this file. \quit

sql/vector--0.8.4--0.8.5.sql

@@ -1,2 +0,0 @@
--- complain if script is sourced in psql, rather than via CREATE EXTENSION
-\echo Use "ALTER EXTENSION vector UPDATE TO '0.8.5'" to load this file. \quit

src/bitutils.c

@@ -31,12 +31,10 @@
 #define BIT_TARGET_CLONES
 #endif
 
-/* Use built-ins when possible for Postgres < 19 for inlining */
+/* Use built-ins when possible for inlining */
-#if PG_VERSION_NUM >= 190000
+#if defined(HAVE__BUILTIN_POPCOUNT) && defined(HAVE_LONG_INT_64)
-#define popcount64(x) pg_popcount64(x)
-#elif defined(HAVE__BUILTIN_POPCOUNT) && (defined(HAVE_LONG_INT_64) || SIZEOF_LONG == 8)
 #define popcount64(x) __builtin_popcountl(x)
-#elif defined(HAVE__BUILTIN_POPCOUNT) && (defined(HAVE_LONG_LONG_INT_64) || SIZEOF_LONG_LONG == 8)
+#elif defined(HAVE__BUILTIN_POPCOUNT) && defined(HAVE_LONG_LONG_INT_64)
 #define popcount64(x) __builtin_popcountll(x)
 #elif !defined(_MSC_VER)
 /* Fails to resolve with MSVC */
@@ -171,7 +169,7 @@ BitJaccardDistanceAvx512Popcount(uint32 bytes, unsigned char *ax, unsigned char
 #endif
 
 TARGET_XSAVE static bool
-SupportsAvx512Popcount(void)
+SupportsAvx512Popcount()
 {
 	unsigned int exx[4] = {0, 0, 0, 0};
 

src/hnsw.c

@@ -13,7 +13,6 @@
 #include "hnsw.h"
 #include "miscadmin.h"
 #include "nodes/pg_list.h"
-#include "storage/lwlock.h"
 #include "utils/float.h"
 #include "utils/guc.h"
 #include "utils/relcache.h"

src/hnsw.h

@@ -10,18 +10,10 @@
 #include "lib/pairingheap.h"
 #include "nodes/execnodes.h"
 #include "port.h"				/* for random() */
-#include "storage/bufpage.h"
-#include "storage/condition_variable.h"
-#include "storage/lwlock.h"
-#include "storage/s_lock.h"
 #include "utils/relptr.h"
 #include "utils/sampling.h"
 #include "vector.h"
 
-#ifdef HNSW_BENCH
-#include "portability/instr_time.h"
-#endif
-
 #if PG_VERSION_NUM >= 190000
 typedef Pointer Item;
 #endif
@@ -82,21 +74,6 @@ typedef Pointer Item;
 #define HnswPageGetOpaque(page)	((HnswPageOpaque) PageGetSpecialPointer(page))
 #define HnswPageGetMeta(page)	((HnswMetaPageData *) PageGetContents(page))
 
-#ifdef HNSW_BENCH
-#define HnswBench(name, code) \
-	do { \
-		instr_time	start; \
-		instr_time	duration; \
-		INSTR_TIME_SET_CURRENT(start); \
-		(code); \
-		INSTR_TIME_SET_CURRENT(duration); \
-		INSTR_TIME_SUBTRACT(duration, start); \
-		elog(INFO, "%s: %.3f ms", name, INSTR_TIME_GET_MILLISEC(duration)); \
-	} while (0)
-#else
-#define HnswBench(name, code) (code)
-#endif
-
 #if PG_VERSION_NUM >= 150000
 #define RandomDouble() pg_prng_double(&pg_global_prng_state)
 #define SeedRandom(seed) pg_prng_seed(&pg_global_prng_state, seed)
@@ -427,11 +404,10 @@ typedef struct HnswVacuumState
 	HnswSupport support;
 
 	/* Variables */
-	struct tidhash_hash *deleting;
+	struct tidhash_hash *deleted;
 	BufferAccessStrategy bas;
 	HnswNeighborTuple ntup;
 	HnswElementData highestPoint;
-	HnswElementData fallbackPoint;
 
 	/* Memory */
 	MemoryContext tmpCtx;

src/hnswbuild.c

@@ -54,7 +54,6 @@
 #include "nodes/execnodes.h"
 #include "optimizer/optimizer.h"
 #include "storage/bufmgr.h"
-#include "storage/condition_variable.h"
 #include "tcop/tcopprot.h"
 #include "utils/datum.h"
 #include "utils/memutils.h"
@@ -719,7 +718,7 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
 	/* Get support functions */
 	HnswInitSupport(&buildstate->support, index);
 
-	InitGraph(&buildstate->graphData, NULL, maintenance_work_mem * (Size) 1024);
+	InitGraph(&buildstate->graphData, NULL, (Size) maintenance_work_mem * 1024L);
 	buildstate->graph = &buildstate->graphData;
 	buildstate->ml = HnswGetMl(buildstate->m);
 	buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
@@ -803,11 +802,7 @@ HnswParallelScanAndInsert(Relation heapRel, Relation indexRel, HnswShared * hnsw
 	buildstate.hnswarea = hnswarea;
 	InitAllocator(&buildstate.allocator, &HnswSharedMemoryAlloc, &buildstate);
 	scan = table_beginscan_parallel(heapRel,
-									ParallelTableScanFromHnswShared(hnswshared)
+									ParallelTableScanFromHnswShared(hnswshared));
-#if PG_VERSION_NUM >= 190000
-									,SO_NONE
-#endif
-		);
 	reltuples = table_index_build_scan(heapRel, indexRel, indexInfo,
 									   true, progress, BuildCallback,
 									   (void *) &buildstate, scan);
@@ -956,7 +951,7 @@ HnswBeginParallel(HnswBuildState * buildstate, bool isconcurrent, int request)
 	/* Leave space for other objects in shared memory */
 	/* Docker has a default limit of 64 MB for shm_size */
 	/* which happens to be the default value of maintenance_work_mem */
-	esthnswarea = maintenance_work_mem * (Size) 1024;
+	esthnswarea = maintenance_work_mem * 1024L;
 	estother = 3 * 1024 * 1024;
 	if (esthnswarea > estother)
 		esthnswarea -= estother;

src/hnswinsert.c

@@ -6,7 +6,6 @@
 #include "nodes/execnodes.h"
 #include "storage/bufmgr.h"
 #include "storage/lmgr.h"
-#include "storage/lwlock.h"
 #include "utils/datum.h"
 #include "utils/memutils.h"
 #include "utils/rel.h"

src/hnswutils.c

@@ -546,9 +546,6 @@ HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, double *distance, Hns
 
 	Assert(HnswIsElementTuple(etup));
 
-	if (unlikely(etup->deleted))
-		elog(ERROR, "cannot load deleted element");
-
 	/* Calculate distance */
 	if (distance != NULL)
 	{

src/hnswvacuum.c

@@ -19,12 +19,12 @@
 #endif
 
 /*
- * Check if deletion list contains an element
+ * Check if deleted list contains an index TID
  */
 static bool
-DeletingElement(tidhash_hash * deleting, ItemPointer indextid)
+DeletedContains(tidhash_hash * deleted, ItemPointer indextid)
 {
-	return tidhash_lookup(deleting, *indextid) != NULL;
+	return tidhash_lookup(deleted, *indextid) != NULL;
 }
 
 /*
@@ -37,20 +37,17 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
 {
 	BlockNumber blkno = HNSW_HEAD_BLKNO;
 	HnswElement highestPoint = &vacuumstate->highestPoint;
-	HnswElement fallbackPoint = &vacuumstate->fallbackPoint;
 	Relation	index = vacuumstate->index;
 	BufferAccessStrategy bas = vacuumstate->bas;
+	HnswElement entryPoint = HnswGetEntryPoint(vacuumstate->index);
 	IndexBulkDeleteResult *stats = vacuumstate->stats;
 
-	/* Store separately since HnswElement level is uint8 */
+	/* Store separately since highestPoint.level is uint8 */
 	int			highestLevel = -1;
-	int			fallbackLevel = -1;
 
-	/* Initialize highest point and fallback point */
+	/* Initialize highest point */
 	highestPoint->blkno = InvalidBlockNumber;
 	highestPoint->offno = InvalidOffsetNumber;
-	fallbackPoint->blkno = InvalidBlockNumber;
-	fallbackPoint->offno = InvalidOffsetNumber;
 
 	while (BlockNumberIsValid(blkno))
 	{
@@ -80,14 +77,6 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
 			if (!HnswIsElementTuple(etup))
 				continue;
 
-			/*
-			 * Skip deleted tuples. It is important they are not added to the
-			 * deletion list to avoid false positives in NeedsUpdated and
-			 * ConfirmRepaired.
-			 */
-			if (etup->deleted)
-				continue;
-
 			if (ItemPointerIsValid(&etup->heaptids[0]))
 			{
 				for (int i = 0; i < HNSW_HEAPTIDS; i++)
@@ -121,40 +110,23 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
 
 			if (!ItemPointerIsValid(&etup->heaptids[0]))
 			{
-				ItemPointerData indextid;
+				ItemPointerData ip;
 				bool		found;
 
-				/* Add to deletion list */
+				/* Add to deleted list */
-				ItemPointerSet(&indextid, blkno, offno);
+				ItemPointerSet(&ip, blkno, offno);
 
-				tidhash_insert(vacuumstate->deleting, indextid, &found);
+				tidhash_insert(vacuumstate->deleted, ip, &found);
 				Assert(!found);
 			}
-			else if (etup->level > highestLevel)
+			else if (etup->level > highestLevel && !(entryPoint != NULL && blkno == entryPoint->blkno && offno == entryPoint->offno))
 			{
-				if (BlockNumberIsValid(highestPoint->blkno))
+				/* Keep track of highest non-entry point */
-				{
-					/* Current highest point becomes fallback */
-					fallbackPoint->blkno = highestPoint->blkno;
-					fallbackPoint->offno = highestPoint->offno;
-					fallbackPoint->level = highestPoint->level;
-					fallbackLevel = highestLevel;
-				}
-
-				/* Keep track of highest point */
 				highestPoint->blkno = blkno;
 				highestPoint->offno = offno;
 				highestPoint->level = etup->level;
 				highestLevel = etup->level;
 			}
-			else if (etup->level > fallbackLevel)
-			{
-				/* Keep track of second highest point */
-				fallbackPoint->blkno = blkno;
-				fallbackPoint->offno = offno;
-				fallbackPoint->level = etup->level;
-				fallbackLevel = etup->level;
-			}
 		}
 
 		blkno = HnswPageGetOpaque(page)->nextblkno;
@@ -166,10 +138,6 @@ RemoveHeapTids(HnswVacuumState * vacuumstate)
 
 		UnlockReleaseBuffer(buf);
 	}
-
-#ifdef HNSW_MEMORY
-	elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(CurrentMemoryContext, true) / 1024);
-#endif
 }
 
 /*
@@ -200,8 +168,8 @@ NeedsUpdated(HnswVacuumState * vacuumstate, HnswElement element)
 		if (!ItemPointerIsValid(indextid))
 			continue;
 
-		/* Check if in deletion list */
+		/* Check if in deleted list */
-		if (DeletingElement(vacuumstate->deleting, indextid))
+		if (DeletedContains(vacuumstate->deleted, indextid))
 		{
 			needsUpdated = true;
 			break;
@@ -210,9 +178,13 @@ NeedsUpdated(HnswVacuumState * vacuumstate, HnswElement element)
 
 	/* Also update if layer 0 is not full */
 	/* This could indicate too many candidates being deleted during insert */
-	/* There should always be more than zero indextids, but check for safety */
+	if (!needsUpdated)
-	if (!needsUpdated && ntup->count > 0)
+	{
+		/* Keep clang-tidy happy */
+		Assert(ntup->count > 0);
+
 		needsUpdated = !ItemPointerIsValid(&ntup->indextids[ntup->count - 1]);
+	}
 
 	UnlockReleaseBuffer(buf);
 
@@ -297,27 +269,12 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
 		/* Get a shared lock */
 		LockPage(index, HNSW_UPDATE_LOCK, ShareLock);
 
-		/* Get latest entry point */
-		entryPoint = HnswGetEntryPoint(index);
-
-		/* Use fallback point if highest point is entry point */
-		if (entryPoint != NULL && entryPoint->blkno == highestPoint->blkno && entryPoint->offno == highestPoint->offno)
-		{
-			highestPoint = &vacuumstate->fallbackPoint;
-
-			if (!BlockNumberIsValid(highestPoint->blkno))
-				highestPoint = NULL;
-		}
-
-		if (highestPoint != NULL)
-		{
 		/* Load element */
 		HnswLoadElement(highestPoint, NULL, NULL, index, support, true, NULL);
 
 		/* Repair if needed */
 		if (NeedsUpdated(vacuumstate, highestPoint))
-				RepairGraphElement(vacuumstate, highestPoint, entryPoint);
+			RepairGraphElement(vacuumstate, highestPoint, HnswGetEntryPoint(index));
-		}
 
 		/* Release lock */
 		UnlockPage(index, HNSW_UPDATE_LOCK, ShareLock);
@@ -335,7 +292,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
 
 		ItemPointerSet(&epData, entryPoint->blkno, entryPoint->offno);
 
-		if (DeletingElement(vacuumstate->deleting, &epData))
+		if (DeletedContains(vacuumstate->deleted, &epData))
 		{
 			/*
 			 * Replace the entry point with the highest point. If highest
@@ -421,10 +378,6 @@ RepairGraph(HnswVacuumState * vacuumstate)
 			if (!HnswIsElementTuple(etup))
 				continue;
 
-			/* Skip deleted tuples */
-			if (etup->deleted)
-				continue;
-
 			/* Skip updating neighbors if being deleted */
 			if (!ItemPointerIsValid(&etup->heaptids[0]))
 				continue;
@@ -488,103 +441,6 @@ RepairGraph(HnswVacuumState * vacuumstate)
 		/* Reset memory context */
 		MemoryContextSwitchTo(oldCtx);
 		MemoryContextReset(vacuumstate->tmpCtx);
-
-#ifdef HNSW_VACUUM_PROGRESS
-		if (!BlockNumberIsValid(blkno) || (blkno - HNSW_HEAD_BLKNO) % 1000 == 0)
-		{
-			BlockNumber totalBlocks = RelationGetNumberOfBlocks(index);
-			BlockNumber currentBlocks = BlockNumberIsValid(blkno) ? blkno : totalBlocks;
-
-			elog(INFO, "hnsw vacuum progress: %.1f%%", 100.0 * currentBlocks / totalBlocks);
-		}
-#endif
-	}
-}
-
-/*
- * Confirm graph was repaired
- */
-static void
-ConfirmRepaired(HnswVacuumState * vacuumstate)
-{
-	BlockNumber blkno = HNSW_HEAD_BLKNO;
-	Relation	index = vacuumstate->index;
-	BufferAccessStrategy bas = vacuumstate->bas;
-
-	while (BlockNumberIsValid(blkno))
-	{
-		Buffer		buf;
-		Page		page;
-		OffsetNumber offno;
-		OffsetNumber maxoffno;
-
-		vacuum_delay_point();
-
-		buf = ReadBufferExtended(index, MAIN_FORKNUM, blkno, RBM_NORMAL, bas);
-		LockBuffer(buf, BUFFER_LOCK_SHARE);
-		page = BufferGetPage(buf);
-		maxoffno = PageGetMaxOffsetNumber(page);
-
-		/* Iterate over nodes */
-		for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
-		{
-			HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
-			HnswNeighborTuple ntup;
-			Buffer		nbuf;
-			Page		npage;
-			BlockNumber neighborPage;
-			OffsetNumber neighborOffno;
-
-			/* Skip neighbor tuples */
-			if (!HnswIsElementTuple(etup))
-				continue;
-
-			/* Skip deleted tuples */
-			if (etup->deleted)
-				continue;
-
-			/* Skip if being deleted */
-			if (!ItemPointerIsValid(&etup->heaptids[0]))
-				continue;
-
-			/* Get neighbor page */
-			neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
-			neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
-
-			if (neighborPage == blkno)
-			{
-				nbuf = buf;
-				npage = page;
-			}
-			else
-			{
-				nbuf = ReadBufferExtended(index, MAIN_FORKNUM, neighborPage, RBM_NORMAL, bas);
-				LockBuffer(nbuf, BUFFER_LOCK_SHARE);
-				npage = BufferGetPage(nbuf);
-			}
-
-			ntup = (HnswNeighborTuple) PageGetItem(npage, PageGetItemId(npage, neighborOffno));
-
-			/* Check neighbors */
-			for (int i = 0; i < ntup->count; i++)
-			{
-				ItemPointer indextid = &ntup->indextids[i];
-
-				if (!ItemPointerIsValid(indextid))
-					continue;
-
-				/* Check if in deletion list */
-				if (DeletingElement(vacuumstate->deleting, indextid))
-					elog(ERROR, "hnsw graph not repaired");
-			}
-
-			if (nbuf != buf)
-				UnlockReleaseBuffer(nbuf);
-		}
-
-		blkno = HnswPageGetOpaque(page)->nextblkno;
-
-		UnlockReleaseBuffer(buf);
 	}
 }
 
@@ -600,15 +456,10 @@ MarkDeleted(HnswVacuumState * vacuumstate)
 	BufferAccessStrategy bas = vacuumstate->bas;
 
 	/*
-	 * Wait for inserts and index scans to complete. Inserts and scans before
+	 * Wait for index scans to complete. Scans before this point may contain
-	 * this point may visit tuples about to be deleted. Inserts and scans
+	 * tuples about to be deleted. Scans after this point will not, since the
-	 * after this point will not, since the graph has been repaired.
+	 * graph has been repaired.
 	 */
-	LockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
-	UnlockPage(index, HNSW_UPDATE_LOCK, ExclusiveLock);
-
-	ConfirmRepaired(vacuumstate);
-
 	LockPage(index, HNSW_SCAN_LOCK, ExclusiveLock);
 	UnlockPage(index, HNSW_SCAN_LOCK, ExclusiveLock);
 
@@ -756,7 +607,7 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
 	HnswGetMetaPageInfo(index, &vacuumstate->m, NULL);
 
 	/* Create hash table */
-	vacuumstate->deleting = tidhash_create(CurrentMemoryContext, 256, NULL);
+	vacuumstate->deleted = tidhash_create(CurrentMemoryContext, 256, NULL);
 }
 
 /*
@@ -765,7 +616,7 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
 static void
 FreeVacuumState(HnswVacuumState * vacuumstate)
 {
-	tidhash_destroy(vacuumstate->deleting);
+	tidhash_destroy(vacuumstate->deleted);
 	FreeAccessStrategy(vacuumstate->bas);
 	pfree(vacuumstate->ntup);
 	MemoryContextDelete(vacuumstate->tmpCtx);
@@ -783,13 +634,13 @@ hnswbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
 	InitVacuumState(&vacuumstate, info, stats, callback, callback_state);
 
 	/* Pass 1: Remove heap TIDs */
-	HnswBench("RemoveHeapTids", RemoveHeapTids(&vacuumstate));
+	RemoveHeapTids(&vacuumstate);
 
 	/* Pass 2: Repair graph */
-	HnswBench("RepairGraph", RepairGraph(&vacuumstate));
+	RepairGraph(&vacuumstate);
 
-	/* Passes 3 and 4: Confirm repaired and mark as deleted */
+	/* Pass 3: Mark as deleted */
-	HnswBench("MarkDeleted", MarkDeleted(&vacuumstate));
+	MarkDeleted(&vacuumstate);
 
 	FreeVacuumState(&vacuumstate);
 

src/ivfbuild.c

@@ -22,7 +22,6 @@
 #include "nodes/execnodes.h"
 #include "optimizer/optimizer.h"
 #include "storage/bufmgr.h"
-#include "storage/condition_variable.h"
 #include "tcop/tcopprot.h"
 #include "utils/memutils.h"
 #include "utils/rel.h"
@@ -63,13 +62,15 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
 	Datum		value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
 
 	/*
-	 * Check with KMEANS_NORM_PROC that the value can be normalized since
+	 * Normalize with KMEANS_NORM_PROC since spherical distance function
-	 * spherical distance function expects unit vectors
+	 * expects unit vectors
 	 */
 	if (buildstate->kmeansnormprocinfo != NULL)
 	{
 		if (!IvfflatCheckNorm(buildstate->kmeansnormprocinfo, buildstate->collation, value))
 			return;
+
+		value = IvfflatNormValue(buildstate->typeInfo, buildstate->collation, value);
 	}
 
 	if (samples->length < targsamples)
@@ -80,7 +81,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
 	else
 	{
 		if (buildstate->rowstoskip < 0)
-			buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, buildstate->samplerows, targsamples);
+			buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, samples->length, targsamples);
 
 		if (buildstate->rowstoskip <= 0)
 		{
@@ -96,9 +97,6 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
 
 		buildstate->rowstoskip -= 1;
 	}
-
-	/* Increment after reservoir_get_next_S */
-	buildstate->samplerows += 1;
 }
 
 /*
@@ -135,7 +133,6 @@ SampleRows(IvfflatBuildState * buildstate)
 	int			targsamples = buildstate->samples->maxlen;
 	BlockNumber totalblocks = RelationGetNumberOfBlocks(buildstate->heap);
 
-	buildstate->samplerows = 0;
 	buildstate->rowstoskip = -1;
 
 	BlockSampler_Init(&buildstate->bs, totalblocks, targsamples, RandomInt());
@@ -145,14 +142,9 @@ SampleRows(IvfflatBuildState * buildstate)
 	{
 		BlockNumber targblock = BlockSampler_Next(&buildstate->bs);
 
-		/* Set anyvisible to false like table_index_build_scan */
 		table_index_build_range_scan(buildstate->heap, buildstate->index, buildstate->indexInfo,
-									 false, false, false, targblock, 1, SampleCallback, (void *) buildstate, NULL);
+									 false, true, false, targblock, 1, SampleCallback, (void *) buildstate, NULL);
 	}
-
-	/* Normalize if needed */
-	if (buildstate->kmeansnormprocinfo != NULL)
-		IvfflatNormVectors(buildstate->typeInfo, buildstate->collation, buildstate->samples, buildstate->tmpCtx);
 }
 
 /*
@@ -382,20 +374,10 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
 	TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 1, "list", INT4OID, -1, 0);
 	TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 2, "tid", TIDOID, -1, 0);
 	TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) 3, "vector", TupleDescAttr(buildstate->tupdesc, 0)->atttypid, -1, 0);
-#if PG_VERSION_NUM >= 190000
-	TupleDescFinalize(buildstate->sortdesc);
-#endif
 
 	buildstate->slot = MakeSingleTupleTableSlot(buildstate->sortdesc, &TTSOpsVirtual);
 
-	buildstate->memoryUsed = 0;
+	buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, buildstate->typeInfo->itemSize(buildstate->dimensions));
-	buildstate->itemsize = buildstate->typeInfo->itemSize(buildstate->dimensions);
-
-	buildstate->memoryUsed += VECTOR_ARRAY_SIZE(buildstate->lists, buildstate->itemsize);
-	IvfflatCheckMemoryUsage(buildstate->memoryUsed);
-	buildstate->centers = VectorArrayInit(buildstate->lists, buildstate->dimensions, buildstate->itemsize);
-
-	/* TODO Move allocation to page creation */
 	buildstate->listInfo = palloc(sizeof(ListInfo) * buildstate->lists);
 
 	buildstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
@@ -438,30 +420,22 @@ ComputeCenters(IvfflatBuildState * buildstate)
 
 	pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_KMEANS);
 
-	/* Skip samples for unlogged table */
-	if (buildstate->heap == NULL)
-		numSamples = 1;
-	else
-	{
-		int64		maxTuples = (int64) RelationGetNumberOfBlocks(buildstate->heap) * MaxHeapTuplesPerPage;
-
 	/* Target 50 samples per list, with at least 10000 samples */
 	/* The number of samples has a large effect on index build time */
 	numSamples = buildstate->lists * 50;
 	if (numSamples < 10000)
 		numSamples = 10000;
 
-		/* Save memory since will not have more than max tuples */
+	/* Skip samples for unlogged table */
-		numSamples = Max(Min(numSamples, maxTuples), 1);
+	if (buildstate->heap == NULL)
-	}
+		numSamples = 1;
 
 	/* Sample rows */
-	buildstate->memoryUsed += VECTOR_ARRAY_SIZE(numSamples, buildstate->itemsize);
+	/* TODO Ensure within maintenance_work_mem */
-	IvfflatCheckMemoryUsage(buildstate->memoryUsed);
+	buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions, buildstate->centers->itemsize);
-	buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions, buildstate->itemsize);
 	if (buildstate->heap != NULL)
 	{
-		IvfflatBench("sample rows", SampleRows(buildstate));
+		SampleRows(buildstate);
 
 		if (buildstate->samples->length < buildstate->lists)
 		{
@@ -473,7 +447,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
 	}
 
 	/* Calculate centers */
-	IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers, buildstate->typeInfo, buildstate->memoryUsed));
+	IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers, buildstate->typeInfo));
 
 	/* Free samples before we allocate more memory */
 	VectorArrayFree(buildstate->samples);
@@ -676,11 +650,7 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
 	ivfspool->sortstate = InitBuildSortState(buildstate.sortdesc, sortmem, coordinate);
 	buildstate.sortstate = ivfspool->sortstate;
 	scan = table_beginscan_parallel(ivfspool->heap,
-									ParallelTableScanFromIvfflatShared(ivfshared)
+									ParallelTableScanFromIvfflatShared(ivfshared));
-#if PG_VERSION_NUM >= 190000
-									,SO_NONE
-#endif
-		);
 	reltuples = table_index_build_scan(ivfspool->heap, ivfspool->index, indexInfo,
 									   true, progress, BuildCallback,
 									   (void *) &buildstate, scan);

src/ivfflat.h

@@ -9,7 +9,6 @@
 #include "lib/pairingheap.h"
 #include "nodes/execnodes.h"
 #include "port.h"				/* for random() */
-#include "storage/condition_variable.h"
 #include "utils/sampling.h"
 #include "utils/tuplesort.h"
 #include "vector.h"
@@ -204,7 +203,6 @@ typedef struct IvfflatBuildState
 	VectorArray samples;
 	VectorArray centers;
 	ListInfo   *listInfo;
-	Size		itemsize;
 
 #ifdef IVFFLAT_KMEANS_DEBUG
 	double		inertia;
@@ -215,8 +213,7 @@ typedef struct IvfflatBuildState
 	/* Sampling */
 	BlockSamplerData bs;
 	ReservoirStateData rstate;
-	double		samplerows;
+	int			rowstoskip;
-	double		rowstoskip;
 
 	/* Sorting */
 	Tuplesortstate *sortstate;
@@ -224,7 +221,6 @@ typedef struct IvfflatBuildState
 	TupleTableSlot *slot;
 
 	/* Memory */
-	Size		memoryUsed;
 	MemoryContext tmpCtx;
 
 	/* Parallel builds */
@@ -305,32 +301,22 @@ typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
 static inline Pointer
 VectorArrayGet(VectorArray arr, int offset)
 {
-	if (offset >= arr->maxlen)
-		elog(ERROR, "safety check failed");
-
 	return ((char *) arr->items) + (offset * arr->itemsize);
 }
 
 static inline void
 VectorArraySet(VectorArray arr, int offset, Pointer val)
 {
-	Size		size = VARSIZE_ANY(val);
+	memcpy(VectorArrayGet(arr, offset), val, VARSIZE_ANY(val));
-
-	if (size > arr->itemsize)
-		elog(ERROR, "safety check failed");
-
-	memcpy(VectorArrayGet(arr, offset), val, size);
 }
 
 /* Methods */
 VectorArray VectorArrayInit(int maxlen, int dimensions, Size itemsize);
 void		VectorArrayFree(VectorArray arr);
-void		IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo, Size memoryUsed);
+void		IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo);
 FmgrInfo   *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
 Datum		IvfflatNormValue(const IvfflatTypeInfo * typeInfo, Oid collation, Datum value);
 bool		IvfflatCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value);
-void		IvfflatNormVectors(const IvfflatTypeInfo * typeInfo, Oid collation, VectorArray arr, MemoryContext tmpCtx);
-void		IvfflatCheckMemoryUsage(Size totalSize);
 int			IvfflatGetLists(Relation index);
 void		IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions);
 void		IvfflatUpdateList(Relation index, ListInfo listInfo, BlockNumber insertPage, BlockNumber originalInsertPage, BlockNumber startPage, ForkNumber forkNum);

src/ivfkmeans.c

@@ -99,8 +99,22 @@ NormCenters(const IvfflatTypeInfo * typeInfo, Oid collation, VectorArray centers
 	MemoryContext normCtx = AllocSetContextCreate(CurrentMemoryContext,
 												  "Ivfflat norm temporary context",
 												  ALLOCSET_DEFAULT_SIZES);
+	MemoryContext oldCtx = MemoryContextSwitchTo(normCtx);
 
-	IvfflatNormVectors(typeInfo, collation, centers, normCtx);
+	for (int j = 0; j < centers->length; j++)
+	{
+		Datum		center = PointerGetDatum(VectorArrayGet(centers, j));
+		Datum		newCenter = IvfflatNormValue(typeInfo, collation, center);
+		Size		size = VARSIZE_ANY(DatumGetPointer(newCenter));
+
+		if (size > centers->itemsize)
+			elog(ERROR, "safety check failed");
+
+		memcpy(DatumGetPointer(center), DatumGetPointer(newCenter), size);
+		MemoryContextReset(normCtx);
+	}
+
+	MemoryContextSwitchTo(oldCtx);
 	MemoryContextDelete(normCtx);
 }
 
@@ -244,7 +258,7 @@ ComputeNewCenters(VectorArray samples, float *agg, VectorArray newCenters, int *
  * https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
  */
 static void
-ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo, Size memoryUsed)
+ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo)
 {
 	FmgrInfo   *procinfo;
 	FmgrInfo   *normprocinfo;
@@ -263,6 +277,8 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
 	float	   *newcdist;
 
 	/* Calculate allocation sizes */
+	Size		samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->itemsize);
+	Size		centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->itemsize);
 	Size		newCentersSize = VECTOR_ARRAY_SIZE(numCenters, centers->itemsize);
 	Size		aggSize = sizeof(float) * (int64) numCenters * dimensions;
 	Size		centerCountsSize = sizeof(int) * numCenters;
@@ -274,13 +290,18 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
 	Size		newcdistSize = sizeof(float) * numCenters;
 
 	/* Calculate total size */
-	Size		totalSize = memoryUsed + newCentersSize + aggSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
+	Size		totalSize = samplesSize + centersSize + newCentersSize + aggSize + centerCountsSize + closestCentersSize + lowerBoundSize + upperBoundSize + sSize + halfcdistSize + newcdistSize;
 
 	/* Check memory requirements */
-	IvfflatCheckMemoryUsage(totalSize);
+	/* Add one to error message to ceil */
+	if (totalSize > (Size) maintenance_work_mem * 1024L)
+		ereport(ERROR,
+				(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
+				 errmsg("memory required is %zu MB, maintenance_work_mem is %d MB",
+						totalSize / (1024 * 1024) + 1, maintenance_work_mem / 1024)));
 
 	/* Ensure indexing does not overflow */
-	if (numCenters > INT_MAX / numCenters)
+	if (numCenters * numCenters > INT_MAX)
 		elog(ERROR, "Indexing overflow detected. Please report a bug.");
 
 	/* Set support functions */
@@ -541,7 +562,7 @@ CheckCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeIn
  * We use spherical k-means for inner product and cosine
  */
 void
-IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo, Size memoryUsed)
+IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const IvfflatTypeInfo * typeInfo)
 {
 	MemoryContext kmeansCtx = AllocSetContextCreate(CurrentMemoryContext,
 													"Ivfflat kmeans temporary context",
@@ -551,7 +572,7 @@ IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers, const Iv
 	if (samples->length == 0)
 		RandomCenters(index, centers, typeInfo);
 	else
-		ElkanKmeans(index, samples, centers, typeInfo, memoryUsed);
+		ElkanKmeans(index, samples, centers, typeInfo);
 
 	CheckCenters(index, centers, typeInfo);
 

src/ivfscan.c

@@ -298,9 +298,6 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
 	so->tupdesc = CreateTemplateTupleDesc(2);
 	TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
 	TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
-#if PG_VERSION_NUM >= 190000
-	TupleDescFinalize(so->tupdesc);
-#endif
 
 	/* Prep sort */
 	so->sortstate = InitScanSortState(so->tupdesc);

src/ivfutils.c

@@ -6,9 +6,7 @@
 #include "halfutils.h"
 #include "halfvec.h"
 #include "ivfflat.h"
-#include "miscadmin.h"
 #include "storage/bufmgr.h"
-#include "utils/memutils.h"
 #include "utils/relcache.h"
 #include "utils/varbit.h"
 #include "vector.h"
@@ -23,15 +21,11 @@
 VectorArray
 VectorArrayInit(int maxlen, int dimensions, Size itemsize)
 {
-	VectorArray res;
+	VectorArray res = palloc(sizeof(VectorArrayData));
-
-	if (maxlen < 1 || dimensions < 1 || itemsize == 0)
-		elog(ERROR, "cannot create vector array");
 
 	/* Ensure items are aligned to prevent UB */
 	itemsize = MAXALIGN(itemsize);
 
-	res = palloc(sizeof(VectorArrayData));
 	res->length = 0;
 	res->maxlen = maxlen;
 	res->dim = dimensions;
@@ -94,40 +88,6 @@ IvfflatCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value)
 	return DatumGetFloat8(FunctionCall1Coll(procinfo, collation, value)) > 0;
 }
 
-/*
- * Normalize vectors
- */
-void
-IvfflatNormVectors(const IvfflatTypeInfo * typeInfo, Oid collation, VectorArray arr, MemoryContext tmpCtx)
-{
-	MemoryContext oldCtx = MemoryContextSwitchTo(tmpCtx);
-
-	for (int i = 0; i < arr->length; i++)
-	{
-		Datum		value = PointerGetDatum(VectorArrayGet(arr, i));
-		Datum		newValue = IvfflatNormValue(typeInfo, collation, value);
-
-		VectorArraySet(arr, i, DatumGetPointer(newValue));
-		MemoryContextReset(tmpCtx);
-	}
-
-	MemoryContextSwitchTo(oldCtx);
-}
-
-/*
- * Check memory usage
- */
-void
-IvfflatCheckMemoryUsage(Size totalSize)
-{
-	/* Add one to error message to ceil */
-	if (totalSize > maintenance_work_mem * (Size) 1024)
-		ereport(ERROR,
-				(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
-				 errmsg("memory required is %zu MB, maintenance_work_mem is %d MB",
-						totalSize / (1024 * 1024) + 1, maintenance_work_mem / 1024)));
-}
-
 /*
  * New buffer
  */

src/sparsevec.c

@@ -182,10 +182,10 @@ sparsevec_isspace(char ch)
 static int
 CompareIndices(const void *a, const void *b)
 {
-	if (((const SparseInputElement *) a)->index < ((const SparseInputElement *) b)->index)
+	if (((SparseInputElement *) a)->index < ((SparseInputElement *) b)->index)
 		return -1;
 
-	if (((const SparseInputElement *) a)->index > ((const SparseInputElement *) b)->index)
+	if (((SparseInputElement *) a)->index > ((SparseInputElement *) b)->index)
 		return 1;
 
 	return 0;
@@ -895,28 +895,24 @@ SparsevecInnerProduct(SparseVector * a, SparseVector * b)
 	float	   *ax = SPARSEVEC_VALUES(a);
 	float	   *bx = SPARSEVEC_VALUES(b);
 	float		distance = 0.0;
-	int			bpos = 0;
+	int			i = 0;
+	int			j = 0;
 
-	for (int i = 0; i < a->nnz; i++)
+	while (i < a->nnz && j < b->nnz)
 	{
 		int			ai = a->indices[i];
-
-		for (int j = bpos; j < b->nnz; j++)
-		{
 		int			bi = b->indices[j];
 
-			/* Only update when the same index */
 		if (ai == bi)
+		{
 			distance += ax[i] * bx[j];
-
+			i++;
-			/* Update start for next iteration */
+			j++;
-			if (ai >= bi)
-				bpos = j + 1;
-
-			/* Found or passed it */
-			if (bi >= ai)
-				break;
 		}
+		else if (ai < bi)
+			i++;
+		else
+			j++;
 	}
 
 	return distance;

src/vector.c

@@ -40,7 +40,7 @@
 #endif
 
 #if PG_VERSION_NUM >= 180000
-PG_MODULE_MAGIC_EXT(.name = "vector", .version = "0.8.5");
+PG_MODULE_MAGIC_EXT(.name = "vector",.version = "0.8.2");
 #else
 PG_MODULE_MAGIC;
 #endif

test/expected/hnsw_bit.out

@@ -49,11 +49,3 @@ CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
 CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
 ERROR:  column cannot have more than 64000 dimensions for hnsw index
 DROP TABLE t;
--- dimensions
-CREATE TABLE t (val bit(64000));
-CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
-DROP TABLE t;
-CREATE TABLE t (val bit(64001));
-CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
-ERROR:  column cannot have more than 64000 dimensions for hnsw index
-DROP TABLE t;

test/expected/hnsw_halfvec.out

@@ -100,11 +100,3 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::halfvec)) t
 (1 row)
 
 DROP TABLE t;
--- dimensions
-CREATE TABLE t (val halfvec(4000));
-CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
-DROP TABLE t;
-CREATE TABLE t (val halfvec(4001));
-CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
-ERROR:  column cannot have more than 4000 dimensions for hnsw index
-DROP TABLE t;

test/expected/hnsw_vector.out

@@ -161,7 +161,6 @@ ERROR:  value 1001 out of bounds for option "ef_construction"
 DETAIL:  Valid values are between "4" and "1000".
 CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
 ERROR:  ef_construction must be greater than or equal to 2 * m
-DROP TABLE t;
 SHOW hnsw.ef_search;
  hnsw.ef_search 
 ----------------
@@ -199,11 +198,4 @@ SET hnsw.scan_mem_multiplier = 0;
 ERROR:  0 is outside the valid range for parameter "hnsw.scan_mem_multiplier" (1 .. 1000)
 SET hnsw.scan_mem_multiplier = 1001;
 ERROR:  1001 is outside the valid range for parameter "hnsw.scan_mem_multiplier" (1 .. 1000)
--- dimensions
-CREATE TABLE t (val vector(2000));
-CREATE INDEX ON t USING hnsw (val vector_l2_ops);
-DROP TABLE t;
-CREATE TABLE t (val vector(2001));
-CREATE INDEX ON t USING hnsw (val vector_l2_ops);
-ERROR:  column cannot have more than 2000 dimensions for hnsw index
 DROP TABLE t;

test/expected/ivfflat_bit.out

@@ -35,32 +35,3 @@ NOTICE:  ivfflat index created with little data
 DETAIL:  This will cause low recall.
 HINT:  Drop the index until the table has more data.
 DROP TABLE t;
--- dimensions
-CREATE TABLE t (val bit(64000));
-CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
-DROP TABLE t;
-CREATE TABLE t (val bit(64001));
-CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
-ERROR:  column cannot have more than 64000 dimensions for ivfflat index
-DROP TABLE t;
--- memory
-SET maintenance_work_mem = '1MB';
-CREATE TABLE t (val bit(64000));
-CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
-DROP TABLE t;
-RESET maintenance_work_mem;
-SET maintenance_work_mem = '29MB';
-CREATE TABLE t (val bit(64000));
-INSERT INTO t (val) VALUES (B'0'::bit(64000));
-CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
-DROP TABLE t;
-RESET maintenance_work_mem;

test/expected/ivfflat_halfvec.out

@@ -82,32 +82,3 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t
 (1 row)
 
 DROP TABLE t;
--- dimensions
-CREATE TABLE t (val halfvec(4000));
-CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
-DROP TABLE t;
-CREATE TABLE t (val halfvec(4001));
-CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
-ERROR:  column cannot have more than 4000 dimensions for ivfflat index
-DROP TABLE t;
--- memory
-SET maintenance_work_mem = '1MB';
-CREATE TABLE t (val halfvec(4000));
-CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
-DROP TABLE t;
-RESET maintenance_work_mem;
-SET maintenance_work_mem = '6MB';
-CREATE TABLE t (val halfvec(4000));
-INSERT INTO t (val) VALUES (array_fill(0, ARRAY[4000]));
-CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
-DROP TABLE t;
-RESET maintenance_work_mem;

test/expected/ivfflat_vector.out

@@ -143,7 +143,6 @@ DETAIL:  Valid values are between "1" and "32768".
 CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
 ERROR:  value 32769 out of bounds for option "lists"
 DETAIL:  Valid values are between "1" and "32768".
-DROP TABLE t;
 SHOW ivfflat.probes;
  ivfflat.probes 
 ----------------
@@ -173,32 +172,4 @@ SET ivfflat.max_probes = 0;
 ERROR:  0 is outside the valid range for parameter "ivfflat.max_probes" (1 .. 32768)
 SET ivfflat.max_probes = 32769;
 ERROR:  32769 is outside the valid range for parameter "ivfflat.max_probes" (1 .. 32768)
--- dimensions
-CREATE TABLE t (val vector(2000));
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
 DROP TABLE t;
-CREATE TABLE t (val vector(2001));
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
-ERROR:  column cannot have more than 2000 dimensions for ivfflat index
-DROP TABLE t;
--- memory
-SET maintenance_work_mem = '1MB';
-CREATE TABLE t (val vector(2000));
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
-DROP TABLE t;
-RESET maintenance_work_mem;
-SET maintenance_work_mem = '5MB';
-CREATE TABLE t (val vector(2000));
-INSERT INTO t (val) VALUES (array_fill(0, ARRAY[2000]));
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
-DROP TABLE t;
-RESET maintenance_work_mem;

test/sql/hnsw_bit.sql

@@ -33,13 +33,3 @@ CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
 CREATE INDEX ON t USING hnsw ((val::bit(3)) bit_hamming_ops);
 CREATE INDEX ON t USING hnsw ((val::bit(64001)) bit_hamming_ops);
 DROP TABLE t;
-
--- dimensions
-
-CREATE TABLE t (val bit(64000));
-CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
-DROP TABLE t;
-
-CREATE TABLE t (val bit(64001));
-CREATE INDEX ON t USING hnsw (val bit_hamming_ops);
-DROP TABLE t;

test/sql/hnsw_halfvec.sql

@@ -56,13 +56,3 @@ SELECT * FROM t ORDER BY val <+> '[3,3,3]';
 SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::halfvec)) t2;
 
 DROP TABLE t;
-
--- dimensions
-
-CREATE TABLE t (val halfvec(4000));
-CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
-DROP TABLE t;
-
-CREATE TABLE t (val halfvec(4001));
-CREATE INDEX ON t USING hnsw (val halfvec_l2_ops);
-DROP TABLE t;

test/sql/hnsw_vector.sql

@@ -95,28 +95,23 @@ CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 101);
 CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 3);
 CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (ef_construction = 1001);
 CREATE INDEX ON t USING hnsw (val vector_l2_ops) WITH (m = 16, ef_construction = 31);
-DROP TABLE t;
 
 SHOW hnsw.ef_search;
+
 SET hnsw.ef_search = 0;
 SET hnsw.ef_search = 1001;
 
 SHOW hnsw.iterative_scan;
+
 SET hnsw.iterative_scan = on;
 
 SHOW hnsw.max_scan_tuples;
+
 SET hnsw.max_scan_tuples = 0;
 
 SHOW hnsw.scan_mem_multiplier;
+
 SET hnsw.scan_mem_multiplier = 0;
 SET hnsw.scan_mem_multiplier = 1001;
 
--- dimensions
-
-CREATE TABLE t (val vector(2000));
-CREATE INDEX ON t USING hnsw (val vector_l2_ops);
-DROP TABLE t;
-
-CREATE TABLE t (val vector(2001));
-CREATE INDEX ON t USING hnsw (val vector_l2_ops);
 DROP TABLE t;

test/sql/ivfflat_bit.sql

@@ -21,28 +21,3 @@ CREATE INDEX ON t USING ivfflat ((val::bit(3)) bit_hamming_ops) WITH (lists = 1)
 CREATE INDEX ON t USING ivfflat ((val::bit(64001)) bit_hamming_ops) WITH (lists = 1);
 CREATE INDEX ON t USING ivfflat ((val::bit(2)) bit_hamming_ops) WITH (lists = 5);
 DROP TABLE t;
-
--- dimensions
-
-CREATE TABLE t (val bit(64000));
-CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
-DROP TABLE t;
-
-CREATE TABLE t (val bit(64001));
-CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
-DROP TABLE t;
-
--- memory
-
-SET maintenance_work_mem = '1MB';
-CREATE TABLE t (val bit(64000));
-CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
-DROP TABLE t;
-RESET maintenance_work_mem;
-
-SET maintenance_work_mem = '29MB';
-CREATE TABLE t (val bit(64000));
-INSERT INTO t (val) VALUES (B'0'::bit(64000));
-CREATE INDEX ON t USING ivfflat (val bit_hamming_ops);
-DROP TABLE t;
-RESET maintenance_work_mem;

test/sql/ivfflat_halfvec.sql

@@ -43,28 +43,3 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> '[0,0,0]') t2;
 SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::halfvec)) t2;
 
 DROP TABLE t;
-
--- dimensions
-
-CREATE TABLE t (val halfvec(4000));
-CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
-DROP TABLE t;
-
-CREATE TABLE t (val halfvec(4001));
-CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
-DROP TABLE t;
-
--- memory
-
-SET maintenance_work_mem = '1MB';
-CREATE TABLE t (val halfvec(4000));
-CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
-DROP TABLE t;
-RESET maintenance_work_mem;
-
-SET maintenance_work_mem = '6MB';
-CREATE TABLE t (val halfvec(4000));
-INSERT INTO t (val) VALUES (array_fill(0, ARRAY[4000]));
-CREATE INDEX ON t USING ivfflat (val halfvec_l2_ops);
-DROP TABLE t;
-RESET maintenance_work_mem;

test/sql/ivfflat_vector.sql

@@ -81,40 +81,19 @@ DROP TABLE t;
 CREATE TABLE t (val vector(3));
 CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 0);
 CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);
-DROP TABLE t;
 
 SHOW ivfflat.probes;
+
 SET ivfflat.probes = 0;
 SET ivfflat.probes = 32769;
 
 SHOW ivfflat.iterative_scan;
+
 SET ivfflat.iterative_scan = on;
 
 SHOW ivfflat.max_probes;
+
 SET ivfflat.max_probes = 0;
 SET ivfflat.max_probes = 32769;
 
--- dimensions
-
-CREATE TABLE t (val vector(2000));
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
 DROP TABLE t;
-
-CREATE TABLE t (val vector(2001));
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
-DROP TABLE t;
-
--- memory
-
-SET maintenance_work_mem = '1MB';
-CREATE TABLE t (val vector(2000));
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
-DROP TABLE t;
-RESET maintenance_work_mem;
-
-SET maintenance_work_mem = '5MB';
-CREATE TABLE t (val vector(2000));
-INSERT INTO t (val) VALUES (array_fill(0, ARRAY[2000]));
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops);
-DROP TABLE t;
-RESET maintenance_work_mem;

test/t/046_hnsw_vacuum_scan.pl

@@ -1,38 +0,0 @@
-use strict;
-use warnings FATAL => 'all';
-use PostgreSQL::Test::Cluster;
-use PostgreSQL::Test::Utils;
-use Test::More;
-
-my $dim = 3;
-my $array_sql = join(",", ('random()') x $dim);
-
-# Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
-$node->init;
-$node->start;
-
-# Create table and index
-$node->safe_psql("postgres", "CREATE EXTENSION vector;");
-$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector($dim));");
-$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
-$node->safe_psql("postgres",
-    "INSERT INTO tst (v) SELECT ARRAY[$array_sql] FROM generate_series(1, 1000) i;"
-);
-$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops);");
-$node->safe_psql("postgres", "DELETE FROM tst");
-
-# Test HNSW_SCAN_LOCK at the beginning of MarkDeleted is effective
-$node->pgbench(
-    "--no-vacuum --client=5 --transactions=1000",
-    0,
-    [qr{actually processed}],
-    [qr{^$}],
-    "concurrent SELECTs and VACUUM",
-    {
-        "046_hnsw_vacuum_scan_select\@1000" => "SELECT i FROM tst ORDER BY v <-> '[0,0,0]' LIMIT 10;",
-        "046_hnsw_vacuum_scan_vacuum\@1" => "VACUUM tst;"
-    }
-);
-
-done_testing();

test/t/047_hnsw_vacuum_insert.pl

@@ -1,39 +0,0 @@
-use strict;
-use warnings FATAL => 'all';
-use PostgreSQL::Test::Cluster;
-use PostgreSQL::Test::Utils;
-use Test::More;
-
-my $dim = 3;
-my $array_sql = join(",", ('random()') x $dim);
-
-# Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
-$node->init;
-$node->start;
-
-# Create table and index
-$node->safe_psql("postgres", "CREATE EXTENSION vector;");
-$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector($dim));");
-$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
-$node->safe_psql("postgres",
-    "INSERT INTO tst (v) SELECT ARRAY[$array_sql] FROM generate_series(1, 1000) i;"
-);
-$node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops);");
-
-# Test no "hnsw graph not repaired" errors
-$node->pgbench(
-    "--no-vacuum --client=5 --transactions=1000",
-    0,
-    [qr{actually processed}],
-    [qr{^$}],
-    "concurrent INSERTs, DELETEs, SELECTs, and VACUUM",
-    {
-        "047_hnsw_vacuum_insert_insert\@500" => "INSERT INTO tst (v) VALUES (ARRAY[$array_sql]);",
-        "047_hnsw_vacuum_insert_delete\@500" => "DELETE FROM tst WHERE i = (SELECT i FROM tst LIMIT 1);",
-        "047_hnsw_vacuum_insert_select\@20" => "SELECT i FROM tst ORDER BY v <-> (SELECT ARRAY[$array_sql]::vector) LIMIT 10;",
-        "047_hnsw_vacuum_insert_vacuum\@1" => "VACUUM tst;"
-    }
-);
-
-done_testing();

test/t/048_ivfflat_vacuum_insert.pl

@@ -1,39 +0,0 @@
-use strict;
-use warnings FATAL => 'all';
-use PostgreSQL::Test::Cluster;
-use PostgreSQL::Test::Utils;
-use Test::More;
-
-my $dim = 3;
-my $array_sql = join(",", ('random()') x $dim);
-
-# Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
-$node->init;
-$node->start;
-
-# Create table and index
-$node->safe_psql("postgres", "CREATE EXTENSION vector;");
-$node->safe_psql("postgres", "CREATE TABLE tst (i serial, v vector($dim));");
-$node->safe_psql("postgres", "ALTER TABLE tst SET (autovacuum_enabled = false);");
-$node->safe_psql("postgres",
-    "INSERT INTO tst (v) SELECT ARRAY[$array_sql] FROM generate_series(1, 1000) i;"
-);
-$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops) WITH (lists = 10);");
-
-# Test no errors
-$node->pgbench(
-    "--no-vacuum --client=5 --transactions=1500",
-    0,
-    [qr{actually processed}],
-    [qr{^$}],
-    "concurrent INSERTs, DELETEs, SELECTs, and VACUUM",
-    {
-        "048_ivfflat_vacuum_insert_insert\@500" => "INSERT INTO tst (v) VALUES (ARRAY[$array_sql]);",
-        "048_ivfflat_vacuum_insert_delete\@500" => "DELETE FROM tst WHERE i = (SELECT i FROM tst LIMIT 1);",
-        "048_ivfflat_vacuum_insert_select\@500" => "SELECT i FROM tst ORDER BY v <-> (SELECT ARRAY[$array_sql]::vector) LIMIT 10;",
-        "048_ivfflat_vacuum_insert_vacuum\@1" => "VACUUM tst;"
-    }
-);
-
-done_testing();

vector.control

@@ -1,4 +1,4 @@
 comment = 'vector data type and ivfflat and hnsw access methods'
-default_version = '0.8.5'
+default_version = '0.8.2'
 module_pathname = '$libdir/vector'
 relocatable = true