Removed comment [skip ci]

.github/workflows/build.yml

@@ -8,18 +8,18 @@ jobs:
       fail-fast: false
       matrix:
         include:
-          # - postgres: 18
-          #   os: ubuntu-24.04
           - postgres: 17
             os: ubuntu-24.04
           - postgres: 16
-            os: ubuntu-22.04
+            os: ubuntu-24.04
           - postgres: 15
             os: ubuntu-22.04
           - postgres: 14
-            os: ubuntu-20.04
+            os: ubuntu-22.04
           - postgres: 13
             os: ubuntu-20.04
+          - postgres: 12
+            os: ubuntu-20.04
     steps:
       - uses: actions/checkout@v4
       - uses: ankane/setup-postgres@v1

CHANGELOG.md

@@ -1,13 +1,5 @@
-## 0.8.0 (unreleased)
+## 0.7.4 (unreleased)
 
-- Added casts for arrays to `sparsevec`
-- Improved cost estimation
-- Reduced memory usage for HNSW index scans
-- Dropped support for Postgres 12
-
-## 0.7.4 (2024-08-05)
-
-- Fixed locking for parallel HNSW index builds
 - Fixed compilation error with GCC 14 on i386 when SSE2 is not enabled
 
 ## 0.7.3 (2024-07-22)

Dockerfile

@@ -1,4 +1,4 @@
-ARG PG_MAJOR=17
+ARG PG_MAJOR=16
 FROM postgres:$PG_MAJOR
 ARG PG_MAJOR
 

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": "0.7.4",
+	"version": "0.7.3",
 	"maintainer": [
 		"Andrew Kane <andrew@ankane.org>"
 	],
@@ -20,7 +20,7 @@
 		"vector": {
 			"file": "sql/vector.sql",
 			"docfile": "README.md",
-			"version": "0.7.4",
+			"version": "0.7.3",
 			"abstract": "Open-source vector similarity search for Postgres"
 		}
 	},

Makefile

@@ -1,5 +1,5 @@
 EXTENSION = vector
-EXTVERSION = 0.7.4
+EXTVERSION = 0.7.3
 
 MODULE_big = vector
 DATA = $(wildcard sql/*--*--*.sql)
@@ -66,7 +66,7 @@ dist:
 	git archive --format zip --prefix=$(EXTENSION)-$(EXTVERSION)/ --output dist/$(EXTENSION)-$(EXTVERSION).zip master
 
 # for Docker
-PG_MAJOR ?= 17
+PG_MAJOR ?= 16
 
 .PHONY: docker
 

Makefile.win

@@ -1,5 +1,5 @@
 EXTENSION = vector
-EXTVERSION = 0.7.4
+EXTVERSION = 0.7.3
 
 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

@@ -21,7 +21,7 @@ Compile and install the extension (supports Postgres 12+)
 
 ```sh
 cd /tmp
-git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
+git clone --branch v0.7.3 https://github.com/pgvector/pgvector.git
 cd pgvector
 make
 make install # may need sudo
@@ -46,14 +46,12 @@ Then use `nmake` to build:
 ```cmd
 set "PGROOT=C:\Program Files\PostgreSQL\16"
 cd %TEMP%
-git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
+git clone --branch v0.7.3 https://github.com/pgvector/pgvector.git
 cd pgvector
 nmake /F Makefile.win
 nmake /F Makefile.win install
 ```
 
-Note: Postgres 17 is not supported yet due to an upstream issue
-
 See the [installation notes](#installation-notes---windows) if you run into issues
 
 You can also install it with [Docker](#docker) or [conda-forge](#conda-forge).
@@ -102,15 +100,13 @@ Or add a vector column to an existing table
 ALTER TABLE items ADD COLUMN embedding vector(3);
 ```
 
-Also supports [half-precision](#half-precision-vectors), [binary](#binary-vectors), and [sparse](#sparse-vectors) vectors
-
 Insert vectors
 
 ```sql
 INSERT INTO items (embedding) VALUES ('[1,2,3]'), ('[4,5,6]');
 ```
 
-Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py))
+Or load vectors in bulk using `COPY` ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py))
 
 ```sql
 COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
@@ -149,8 +145,6 @@ Supported distance functions are:
 - `<#>` - (negative) inner product
 - `<=>` - cosine distance
 - `<+>` - L1 distance (added in 0.7.0)
-- `<~>` - Hamming distance (binary vectors, added in 0.7.0)
-- `<%>` - Jaccard distance (binary vectors, added in 0.7.0)
 
 Get the nearest neighbors to a row
 
@@ -208,7 +202,7 @@ You can add an index to use approximate nearest neighbor search, which trades so
 
 Supported index types are:
 
-- [HNSW](#hnsw)
+- [HNSW](#hnsw) - added in 0.5.0
 - [IVFFlat](#ivfflat)
 
 ## HNSW
@@ -479,7 +473,7 @@ SELECT * FROM items ORDER BY embedding::halfvec(3) <-> '[1,2,3]' LIMIT 5;
 
 ## Binary Vectors
 
-Use the `bit` type to store binary vectors ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/imagehash/example.py))
+Use the `bit` type to store binary vectors ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/hash_image_search.py))
 
 ```sql
 CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
@@ -557,7 +551,7 @@ SELECT id, content FROM items, plainto_tsquery('hello search') query
     WHERE textsearch @@ query ORDER BY ts_rank_cd(textsearch, query) DESC LIMIT 5;
 ```
 
-You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search/rrf.py) or a [cross-encoder](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search/cross_encoder.py) to combine results.
+You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search_rrf.py) or a [cross-encoder](https://github.com/pgvector/pgvector-python/blob/master/examples/hybrid_search.py) to combine results.
 
 ## Indexing Subvectors
 
@@ -603,7 +597,7 @@ Be sure to restart Postgres for changes to take effect.
 
 ### Loading
 
-Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/loading/example.py)).
+Use `COPY` for bulk loading data ([example](https://github.com/pgvector/pgvector-python/blob/master/examples/bulk_loading.py)).
 
 ```sql
 COPY items (embedding) FROM STDIN WITH (FORMAT BINARY);
@@ -693,7 +687,7 @@ 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)).
+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.py)).
 
 ## Languages
 
@@ -989,7 +983,7 @@ l2_normalize(sparsevec) → sparsevec | Normalize with Euclidean norm | 0.7.0
 If your machine has multiple Postgres installations, specify the path to [pg_config](https://www.postgresql.org/docs/current/app-pgconfig.html) with:
 
 ```sh
-export PG_CONFIG=/Library/PostgreSQL/17/bin/pg_config
+export PG_CONFIG=/Library/PostgreSQL/16/bin/pg_config
 ```
 
 Then re-run the installation instructions (run `make clean` before `make` if needed). If `sudo` is needed for `make install`, use:
@@ -1000,11 +994,11 @@ sudo --preserve-env=PG_CONFIG make install
 
 A few common paths on Mac are:
 
-- EDB installer - `/Library/PostgreSQL/17/bin/pg_config`
+- EDB installer - `/Library/PostgreSQL/16/bin/pg_config`
-- Homebrew (arm64) - `/opt/homebrew/opt/postgresql@17/bin/pg_config`
+- Homebrew (arm64) - `/opt/homebrew/opt/postgresql@16/bin/pg_config`
-- Homebrew (x86-64) - `/usr/local/opt/postgresql@17/bin/pg_config`
+- Homebrew (x86-64) - `/usr/local/opt/postgresql@16/bin/pg_config`
 
-Note: Replace `17` with your Postgres server version
+Note: Replace `16` with your Postgres server version
 
 ### Missing Header
 
@@ -1013,10 +1007,10 @@ If compilation fails with `fatal error: postgres.h: No such file or directory`,
 For Ubuntu and Debian, use:
 
 ```sh
-sudo apt install postgresql-server-dev-17
+sudo apt install postgresql-server-dev-16
 ```
 
-Note: Replace `17` with your Postgres server version
+Note: Replace `16` with your Postgres server version
 
 ### Missing SDK
 
@@ -1049,17 +1043,17 @@ If installation fails with `Access is denied`, re-run the installation instructi
 Get the [Docker image](https://hub.docker.com/r/pgvector/pgvector) with:
 
 ```sh
-docker pull pgvector/pgvector:pg17
+docker pull pgvector/pgvector:pg16
 ```
 
-This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `17` with your Postgres server version, and run it the same way).
+This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (replace `16` with your Postgres server version, and run it the same way).
 
 You can also build the image manually:
 
 ```sh
-git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
+git clone --branch v0.7.3 https://github.com/pgvector/pgvector.git
 cd pgvector
-docker build --pull --build-arg PG_MAJOR=17 -t myuser/pgvector .
+docker build --pull --build-arg PG_MAJOR=16 -t myuser/pgvector .
 ```
 
 ### Homebrew
@@ -1070,7 +1064,7 @@ With Homebrew Postgres, you can use:
 brew install pgvector
 ```
 
-Note: This only adds it to the `postgresql@17` and `postgresql@14` formulas
+Note: This only adds it to the `postgresql@14` formula
 
 ### PGXN
 
@@ -1085,22 +1079,22 @@ pgxn install vector
 Debian and Ubuntu packages are available from the [PostgreSQL APT Repository](https://wiki.postgresql.org/wiki/Apt). Follow the [setup instructions](https://wiki.postgresql.org/wiki/Apt#Quickstart) and run:
 
 ```sh
-sudo apt install postgresql-17-pgvector
+sudo apt install postgresql-16-pgvector
 ```
 
-Note: Replace `17` with your Postgres server version
+Note: Replace `16` with your Postgres server version
 
 ### Yum
 
 RPM packages are available from the [PostgreSQL Yum Repository](https://yum.postgresql.org/). Follow the [setup instructions](https://www.postgresql.org/download/linux/redhat/) for your distribution and run:
 
 ```sh
-sudo yum install pgvector_17
+sudo yum install pgvector_16
 # or
-sudo dnf install pgvector_17
+sudo dnf install pgvector_16
 ```
 
-Note: Replace `17` with your Postgres server version
+Note: Replace `16` with your Postgres server version
 
 ### pkg
 

sql/vector--0.7.3--0.7.4.sql

@@ -1,2 +0,0 @@
--- complain if script is sourced in psql, rather than via CREATE EXTENSION
-\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.4'" to load this file. \quit

sql/vector--0.7.4--0.8.0.sql

@@ -1,26 +0,0 @@
--- complain if script is sourced in psql, rather than via CREATE EXTENSION
-\echo Use "ALTER EXTENSION vector UPDATE TO '0.8.0'" to load this file. \quit
-
-CREATE FUNCTION array_to_sparsevec(integer[], integer, boolean) RETURNS sparsevec
-	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-
-CREATE FUNCTION array_to_sparsevec(real[], integer, boolean) RETURNS sparsevec
-	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-
-CREATE FUNCTION array_to_sparsevec(double precision[], integer, boolean) RETURNS sparsevec
-	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-
-CREATE FUNCTION array_to_sparsevec(numeric[], integer, boolean) RETURNS sparsevec
-	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-
-CREATE CAST (integer[] AS sparsevec)
-	WITH FUNCTION array_to_sparsevec(integer[], integer, boolean) AS ASSIGNMENT;
-
-CREATE CAST (real[] AS sparsevec)
-	WITH FUNCTION array_to_sparsevec(real[], integer, boolean) AS ASSIGNMENT;
-
-CREATE CAST (double precision[] AS sparsevec)
-	WITH FUNCTION array_to_sparsevec(double precision[], integer, boolean) AS ASSIGNMENT;
-
-CREATE CAST (numeric[] AS sparsevec)
-	WITH FUNCTION array_to_sparsevec(numeric[], integer, boolean) AS ASSIGNMENT;

sql/vector.sql

@@ -782,18 +782,6 @@ CREATE FUNCTION halfvec_to_sparsevec(halfvec, integer, boolean) RETURNS sparseve
 CREATE FUNCTION sparsevec_to_halfvec(sparsevec, integer, boolean) RETURNS halfvec
 	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
 
-CREATE FUNCTION array_to_sparsevec(integer[], integer, boolean) RETURNS sparsevec
-	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-
-CREATE FUNCTION array_to_sparsevec(real[], integer, boolean) RETURNS sparsevec
-	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-
-CREATE FUNCTION array_to_sparsevec(double precision[], integer, boolean) RETURNS sparsevec
-	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-
-CREATE FUNCTION array_to_sparsevec(numeric[], integer, boolean) RETURNS sparsevec
-	AS 'MODULE_PATHNAME' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
-
 -- sparsevec casts
 
 CREATE CAST (sparsevec AS sparsevec)
@@ -811,18 +799,6 @@ CREATE CAST (sparsevec AS halfvec)
 CREATE CAST (halfvec AS sparsevec)
 	WITH FUNCTION halfvec_to_sparsevec(halfvec, integer, boolean) AS IMPLICIT;
 
-CREATE CAST (integer[] AS sparsevec)
-	WITH FUNCTION array_to_sparsevec(integer[], integer, boolean) AS ASSIGNMENT;
-
-CREATE CAST (real[] AS sparsevec)
-	WITH FUNCTION array_to_sparsevec(real[], integer, boolean) AS ASSIGNMENT;
-
-CREATE CAST (double precision[] AS sparsevec)
-	WITH FUNCTION array_to_sparsevec(double precision[], integer, boolean) AS ASSIGNMENT;
-
-CREATE CAST (numeric[] AS sparsevec)
-	WITH FUNCTION array_to_sparsevec(numeric[], integer, boolean) AS ASSIGNMENT;
-
 -- sparsevec operators
 
 CREATE OPERATOR <-> (

src/bitutils.h

@@ -4,8 +4,8 @@
 #include "postgres.h"
 
 /* Check version in first header */
-#if PG_VERSION_NUM < 130000
+#if PG_VERSION_NUM < 120000
-#error "Requires PostgreSQL 13+"
+#error "Requires PostgreSQL 12+"
 #endif
 
 extern uint64 (*BitHammingDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance);

src/halfvec.c

@@ -19,6 +19,11 @@
 #include "utils/numeric.h"
 #include "vector.h"
 
+#if PG_VERSION_NUM < 130000
+#define TYPALIGN_DOUBLE 'd'
+#define TYPALIGN_INT 'i'
+#endif
+
 #define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
 #define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
 
@@ -159,6 +164,24 @@ CheckStateArray(ArrayType *statearray, const char *caller)
 	return (float8 *) ARR_DATA_PTR(statearray);
 }
 
+#if PG_VERSION_NUM < 120003
+static pg_noinline void
+float_overflow_error(void)
+{
+	ereport(ERROR,
+			(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
+			 errmsg("value out of range: overflow")));
+}
+
+static pg_noinline void
+float_underflow_error(void)
+{
+	ereport(ERROR,
+			(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
+			 errmsg("value out of range: underflow")));
+}
+#endif
+
 /*
  * Convert textual representation to internal representation
  */

src/hnsw.c

@@ -9,10 +9,8 @@
 #include "commands/vacuum.h"
 #include "hnsw.h"
 #include "miscadmin.h"
-#include "utils/float.h"
 #include "utils/guc.h"
 #include "utils/selfuncs.h"
-#include "utils/spccache.h"
 
 #if PG_VERSION_NUM < 150000
 #define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
@@ -61,9 +59,17 @@ HnswInit(void)
 
 	hnsw_relopt_kind = add_reloption_kind();
 	add_int_reloption(hnsw_relopt_kind, "m", "Max number of connections",
-					  HNSW_DEFAULT_M, HNSW_MIN_M, HNSW_MAX_M, AccessExclusiveLock);
+					  HNSW_DEFAULT_M, HNSW_MIN_M, HNSW_MAX_M
+#if PG_VERSION_NUM >= 130000
+					  ,AccessExclusiveLock
+#endif
+		);
 	add_int_reloption(hnsw_relopt_kind, "ef_construction", "Size of the dynamic candidate list for construction",
-					  HNSW_DEFAULT_EF_CONSTRUCTION, HNSW_MIN_EF_CONSTRUCTION, HNSW_MAX_EF_CONSTRUCTION, AccessExclusiveLock);
+					  HNSW_DEFAULT_EF_CONSTRUCTION, HNSW_MIN_EF_CONSTRUCTION, HNSW_MAX_EF_CONSTRUCTION
+#if PG_VERSION_NUM >= 130000
+					  ,AccessExclusiveLock
+#endif
+		);
 
 	DefineCustomIntVariable("hnsw.ef_search", "Sets the size of the dynamic candidate list for search",
 							"Valid range is 1..1000.", &hnsw_ef_search,
@@ -100,16 +106,14 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
 {
 	GenericCosts costs;
 	int			m;
-	double		ratio;
+	int			entryLevel;
-	double		startupPages;
-	double		spc_seq_page_cost;
 	Relation	index;
 
 	/* Never use index without order */
 	if (path->indexorderbys == NULL)
 	{
-		*indexStartupCost = get_float8_infinity();
+		*indexStartupCost = DBL_MAX;
-		*indexTotalCost = get_float8_infinity();
+		*indexTotalCost = DBL_MAX;
 		*indexSelectivity = 0;
 		*indexCorrelation = 0;
 		*indexPages = 0;
@@ -118,71 +122,21 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
 
 	MemSet(&costs, 0, sizeof(costs));
 
-	genericcostestimate(root, path, loop_count, &costs);
-
 	index = index_open(path->indexinfo->indexoid, NoLock);
 	HnswGetMetaPageInfo(index, &m, NULL);
 	index_close(index, NoLock);
 
-	/*
+	/* Approximate entry level */
-	 * HNSW cost estimation follows a formula that accounts for the total
+	entryLevel = (int) -log(1.0 / path->indexinfo->tuples) * HnswGetMl(m);
-	 * number of tuples indexed combined with the parameters that most
-	 * influence the duration of the index scan, namely: m - the number of
-	 * tuples that are scanned in each step of the HNSW graph traversal
-	 * ef_search - which influences the total number of steps taken at layer 0
-	 *
-	 * The source of the vector data can impact how many steps it takes to
-	 * converge on the set of vectors to return to the executor. Currently, we
-	 * use a hardcoded scaling factor (HNSWScanScalingFactor) to help
-	 * influence that, but this could later become a configurable parameter
-	 * based on the cost estimations.
-	 *
-	 * The tuple estimator formula is below:
-	 *
-	 * numIndexTuples = entryLevel * m + layer0TuplesMax * layer0Selectivity
-	 *
-	 * "entryLevel * m" represents the floor of tuples we need to scan to get
-	 * to layer 0 (L0).
-	 *
-	 * "layer0TuplesMax" is the estimated total number of tuples we'd scan at
-	 * L0 if we weren't discarding already visited tuples as part of the scan.
-	 *
-	 * "layer0Selectivity" estimates the percentage of tuples that are scanned
-	 * at L0, accounting for previously visited tuples, multiplied by the
-	 * "scalingFactor" (currently hardcoded).
-	 */
-	if (path->indexinfo->tuples > 0)
-	{
-		double		scalingFactor = 0.55;
-		int			entryLevel = (int) (log(path->indexinfo->tuples) * HnswGetMl(m));
-		int			layer0TuplesMax = HnswGetLayerM(m, 0) * hnsw_ef_search;
-		double		layer0Selectivity = scalingFactor * log(path->indexinfo->tuples) / (log(m) * (1 + log(hnsw_ef_search)));
 
-		ratio = (entryLevel * m + layer0TuplesMax * layer0Selectivity) / path->indexinfo->tuples;
+	/* TODO Improve estimate of visited tuples (currently underestimates) */
+	/* Account for number of tuples (or entry level), m, and ef_search */
+	costs.numIndexTuples = (entryLevel + 2) * m;
 
-		if (ratio > 1)
+	genericcostestimate(root, path, loop_count, &costs);
-			ratio = 1;
-	}
-	else
-		ratio = 1;
 
-	get_tablespace_page_costs(path->indexinfo->reltablespace, NULL, &spc_seq_page_cost);
+	/* Use total cost since most work happens before first tuple is returned */
-
+	*indexStartupCost = costs.indexTotalCost;
-	/* Startup cost is cost before returning the first row */
-	costs.indexStartupCost = costs.indexTotalCost * ratio;
-
-	/* Adjust cost if needed since TOAST not included in seq scan cost */
-	startupPages = costs.numIndexPages * ratio;
-	if (startupPages > path->indexinfo->rel->pages && ratio < 0.5)
-	{
-		/* Change all page cost from random to sequential */
-		costs.indexStartupCost -= startupPages * (costs.spc_random_page_cost - spc_seq_page_cost);
-
-		/* Remove cost of extra pages */
-		costs.indexStartupCost -= (startupPages - path->indexinfo->rel->pages) * spc_seq_page_cost;
-	}
-
-	*indexStartupCost = costs.indexStartupCost;
 	*indexTotalCost = costs.indexTotalCost;
 	*indexSelectivity = costs.indexSelectivity;
 	*indexCorrelation = costs.indexCorrelation;
@@ -200,10 +154,23 @@ hnswoptions(Datum reloptions, bool validate)
 		{"ef_construction", RELOPT_TYPE_INT, offsetof(HnswOptions, efConstruction)},
 	};
 
+#if PG_VERSION_NUM >= 130000
 	return (bytea *) build_reloptions(reloptions, validate,
 									  hnsw_relopt_kind,
 									  sizeof(HnswOptions),
 									  tab, lengthof(tab));
+#else
+	relopt_value *options;
+	int			numoptions;
+	HnswOptions *rdopts;
+
+	options = parseRelOptions(reloptions, validate, hnsw_relopt_kind, &numoptions);
+	rdopts = allocateReloptStruct(sizeof(HnswOptions), options, numoptions);
+	fillRelOptions((void *) rdopts, sizeof(HnswOptions), options, numoptions,
+				   validate, tab, lengthof(tab));
+
+	return (bytea *) rdopts;
+#endif
 }
 
 /*
@@ -228,7 +195,9 @@ hnswhandler(PG_FUNCTION_ARGS)
 
 	amroutine->amstrategies = 0;
 	amroutine->amsupport = 3;
+#if PG_VERSION_NUM >= 130000
 	amroutine->amoptsprocnum = 0;
+#endif
 	amroutine->amcanorder = false;
 	amroutine->amcanorderbyop = true;
 	amroutine->amcanbackward = false;	/* can change direction mid-scan */
@@ -241,24 +210,17 @@ hnswhandler(PG_FUNCTION_ARGS)
 	amroutine->amclusterable = false;
 	amroutine->ampredlocks = false;
 	amroutine->amcanparallel = false;
-#if PG_VERSION_NUM >= 170000
-	amroutine->amcanbuildparallel = true;
-#endif
 	amroutine->amcaninclude = false;
+#if PG_VERSION_NUM >= 130000
 	amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */
-#if PG_VERSION_NUM >= 160000
-	amroutine->amsummarizing = false;
-#endif
 	amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL;
+#endif
 	amroutine->amkeytype = InvalidOid;
 
 	/* Interface functions */
 	amroutine->ambuild = hnswbuild;
 	amroutine->ambuildempty = hnswbuildempty;
 	amroutine->aminsert = hnswinsert;
-#if PG_VERSION_NUM >= 170000
-	amroutine->aminsertcleanup = NULL;
-#endif
 	amroutine->ambulkdelete = hnswbulkdelete;
 	amroutine->amvacuumcleanup = hnswvacuumcleanup;
 	amroutine->amcanreturn = NULL;

src/hnsw.h

@@ -76,6 +76,11 @@
 #define SeedRandom(seed) srandom(seed)
 #endif
 
+#if PG_VERSION_NUM < 130000
+#define list_delete_last(list) list_truncate(list, list_length(list) - 1)
+#define list_sort(list, cmp) ((list) = list_qsort(list, cmp))
+#endif
+
 #define HnswIsElementTuple(tup) ((tup)->type == HNSW_ELEMENT_TUPLE_TYPE)
 #define HnswIsNeighborTuple(tup) ((tup)->type == HNSW_NEIGHBOR_TUPLE_TYPE)
 
@@ -155,13 +160,11 @@ struct HnswNeighborArray
 	HnswCandidate items[FLEXIBLE_ARRAY_MEMBER];
 };
 
-typedef struct HnswSearchCandidate
+typedef struct HnswPairingHeapNode
 {
-	pairingheap_node c_node;
+	pairingheap_node ph_node;
-	pairingheap_node w_node;
+	HnswCandidate *inner;
-	HnswElementPtr element;
+}			HnswPairingHeapNode;
-	float		distance;
-}			HnswSearchCandidate;
 
 /* HNSW index options */
 typedef struct HnswOptions
@@ -382,7 +385,7 @@ void	   *HnswAlloc(HnswAllocator * allocator, Size size);
 HnswElement HnswInitElement(char *base, ItemPointer tid, int m, double ml, int maxLevel, HnswAllocator * alloc);
 HnswElement HnswInitElementFromBlock(BlockNumber blkno, OffsetNumber offno);
 void		HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint, Relation index, FmgrInfo *procinfo, Oid collation, int m, int efConstruction, bool existing);
-HnswSearchCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec);
+HnswCandidate *HnswEntryCandidate(char *base, HnswElement em, Datum q, Relation rel, FmgrInfo *procinfo, Oid collation, bool loadVec);
 void		HnswUpdateMetaPage(Relation index, int updateEntry, HnswElement entryPoint, BlockNumber insertPage, ForkNumber forkNum, bool building);
 void		HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m);
 void		HnswAddHeapTid(HnswElement element, ItemPointer heaptid);

src/hnswbuild.c

@@ -60,6 +60,12 @@
 #include "pgstat.h"
 #endif
 
+#if PG_VERSION_NUM >= 130000
+#define CALLBACK_ITEM_POINTER ItemPointer tid
+#else
+#define CALLBACK_ITEM_POINTER HeapTuple hup
+#endif
+
 #if PG_VERSION_NUM >= 140000
 #include "utils/backend_status.h"
 #include "utils/wait_event.h"
@@ -69,6 +75,10 @@
 #define PARALLEL_KEY_HNSW_AREA			UINT64CONST(0xA000000000000002)
 #define PARALLEL_KEY_QUERY_TEXT			UINT64CONST(0xA000000000000003)
 
+#if PG_VERSION_NUM < 130000
+#define GENERATIONCHUNK_RAWSIZE (SIZEOF_SIZE_T + SIZEOF_VOID_P * 2)
+#endif
+
 /*
  * Create the metapage
  */
@@ -182,9 +192,7 @@ CreateGraphPages(HnswBuildState * buildstate)
 
 		/* Initial size check */
 		if (etupSize > HNSW_TUPLE_ALLOC_SIZE)
-			ereport(ERROR,
+			elog(ERROR, "index tuple too large");
-					(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
-					 errmsg("index tuple too large")));
 
 		HnswSetElementTuple(base, etup, element);
 
@@ -575,13 +583,17 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
  * Callback for table_index_build_scan
  */
 static void
-BuildCallback(Relation index, ItemPointer tid, Datum *values,
+BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
 			  bool *isnull, bool tupleIsAlive, void *state)
 {
 	HnswBuildState *buildstate = (HnswBuildState *) state;
 	HnswGraph  *graph = buildstate->graph;
 	MemoryContext oldCtx;
 
+#if PG_VERSION_NUM < 130000
+	ItemPointer tid = &hup->t_self;
+#endif
+
 	/* Skip nulls */
 	if (isnull[0])
 		return;
@@ -644,7 +656,11 @@ HnswMemoryContextAlloc(Size size, void *state)
 	HnswBuildState *buildstate = (HnswBuildState *) state;
 	void	   *chunk = MemoryContextAlloc(buildstate->graphCtx, size);
 
+#if PG_VERSION_NUM >= 130000
 	buildstate->graphData.memoryUsed = MemoryContextMemAllocated(buildstate->graphCtx, false);
+#else
+	buildstate->graphData.memoryUsed += MAXALIGN(size);
+#endif
 
 	return chunk;
 }
@@ -680,25 +696,17 @@ InitBuildState(HnswBuildState * buildstate, Relation heap, Relation index, Index
 
 	/* Disallow varbit since require fixed dimensions */
 	if (TupleDescAttr(index->rd_att, 0)->atttypid == VARBITOID)
-		ereport(ERROR,
+		elog(ERROR, "type not supported for hnsw index");
-				(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
-				 errmsg("type not supported for hnsw index")));
 
 	/* Require column to have dimensions to be indexed */
 	if (buildstate->dimensions < 0)
-		ereport(ERROR,
+		elog(ERROR, "column does not have dimensions");
-				(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
-				 errmsg("column does not have dimensions")));
 
 	if (buildstate->dimensions > buildstate->typeInfo->maxDimensions)
-		ereport(ERROR,
+		elog(ERROR, "column cannot have more than %d dimensions for hnsw index", buildstate->typeInfo->maxDimensions);
-				(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
-				 errmsg("column cannot have more than %d dimensions for hnsw index", buildstate->typeInfo->maxDimensions)));
 
 	if (buildstate->efConstruction < 2 * buildstate->m)
-		ereport(ERROR,
+		elog(ERROR, "ef_construction must be greater than or equal to 2 * m");
-				(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
-				 errmsg("ef_construction must be greater than or equal to 2 * m")));
 
 	buildstate->reltuples = 0;
 	buildstate->indtuples = 0;

src/hnswinsert.c

@@ -379,12 +379,8 @@ HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, Hns
 			HnswElement neighborElement = HnswPtrAccess(base, hc->element);
 			OffsetNumber offno = neighborElement->neighborOffno;
 
-			/*
+			/* Get latest neighbors since they may have changed */
-			 * Get latest neighbors since they may have changed. Do not lock
+			/* Do not lock yet since selecting neighbors can take time */
-			 * yet since selecting neighbors can take time. Could use
-			 * optimistic locking to retry if another update occurs before
-			 * getting exclusive lock.
-			 */
 			HnswLoadNeighbors(neighborElement, index, m);
 
 			/*

src/hnswscan.c

@@ -160,15 +160,15 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
 
 		so->first = false;
 
-#if defined(HNSW_MEMORY)
+#if defined(HNSW_MEMORY) && PG_VERSION_NUM >= 130000
-		elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(so->tmpCtx, false) / 1024);
+		elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(so->tmpCtx, false) / (1024 * 1024));
 #endif
 	}
 
 	while (list_length(so->w) > 0)
 	{
 		char	   *base = NULL;
-		HnswSearchCandidate *hc = llast(so->w);
+		HnswCandidate *hc = llast(so->w);
 		HnswElement element = HnswPtrAccess(base, hc->element);
 		ItemPointer heaptid;
 

src/hnswutils.c

@@ -5,7 +5,6 @@
 #include "access/generic_xlog.h"
 #include "catalog/pg_type.h"
 #include "catalog/pg_type_d.h"
-#include "common/hashfn.h"
 #include "fmgr.h"
 #include "hnsw.h"
 #include "lib/pairingheap.h"
@@ -15,6 +14,12 @@
 #include "utils/memdebug.h"
 #include "utils/rel.h"
 
+#if PG_VERSION_NUM >= 130000
+#include "common/hashfn.h"
+#else
+#include "utils/hashutils.h"
+#endif
+
 #if PG_VERSION_NUM < 170000
 static inline uint64
 murmurhash64(uint64 data)
@@ -107,12 +112,6 @@ typedef union
 	tidhash_hash *tids;
 }			visited_hash;
 
-typedef union
-{
-	HnswElement element;
-	ItemPointerData indextid;
-}			HnswUnvisited;
-
 /*
  * Get the max number of connections in an upper layer for each element in the index
  */
@@ -548,19 +547,19 @@ HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHe
 /*
  * Load an element and optionally get its distance from q
  */
-static void
+void
-HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance, HnswElement * element)
+HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance)
 {
 	Buffer		buf;
 	Page		page;
 	HnswElementTuple etup;
 
 	/* Read vector */
-	buf = ReadBuffer(index, blkno);
+	buf = ReadBuffer(index, element->blkno);
 	LockBuffer(buf, BUFFER_LOCK_SHARE);
 	page = BufferGetPage(buf);
 
-	etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
+	etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, element->offno));
 
 	Assert(HnswIsElementTuple(etup));
 
@@ -575,32 +574,19 @@ HnswLoadElementImpl(BlockNumber blkno, OffsetNumber offno, float *distance, Datu
 
 	/* Load element */
 	if (distance == NULL || maxDistance == NULL || *distance < *maxDistance)
-	{
+		HnswLoadElementFromTuple(element, etup, true, loadVec);
-		if (*element == NULL)
-			*element = HnswInitElementFromBlock(blkno, offno);
-
-		HnswLoadElementFromTuple(*element, etup, true, loadVec);
-	}
 
 	UnlockReleaseBuffer(buf);
 }
 
 /*
- * Load an element and optionally get its distance from q
+ * Get the distance for a candidate
- */
-void
-HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec, float *maxDistance)
-{
-	HnswLoadElementImpl(element->blkno, element->offno, distance, q, index, procinfo, collation, loadVec, maxDistance, &element);
-}
-
-/*
- * Get the distance for an element
  */
 static float
-GetElementDistance(char *base, HnswElement element, Datum q, FmgrInfo *procinfo, Oid collation)
+GetCandidateDistance(char *base, HnswCandidate * hc, Datum q, FmgrInfo *procinfo, Oid collation)
 {
-	Datum		value = HnswGetValue(base, element);
+	HnswElement hce = HnswPtrAccess(base, hc->element);
+	Datum		value = HnswGetValue(base, hce);
 
 	return DatumGetFloat8(FunctionCall2Coll(procinfo, collation, q, value));
 }
@@ -608,32 +594,29 @@ GetElementDistance(char *base, HnswElement element, Datum q, FmgrInfo *procinfo,
 /*
  * Create a candidate for the entry point
  */
-HnswSearchCandidate *
+HnswCandidate *
 HnswEntryCandidate(char *base, HnswElement entryPoint, Datum q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec)
 {
-	HnswSearchCandidate *hc = palloc(sizeof(HnswSearchCandidate));
+	HnswCandidate *hc = palloc(sizeof(HnswCandidate));
 
 	HnswPtrStore(base, hc->element, entryPoint);
 	if (index == NULL)
-		hc->distance = GetElementDistance(base, entryPoint, q, procinfo, collation);
+		hc->distance = GetCandidateDistance(base, hc, q, procinfo, collation);
 	else
 		HnswLoadElement(entryPoint, &hc->distance, &q, index, procinfo, collation, loadVec, NULL);
 	return hc;
 }
 
-#define HnswGetSearchCandidate(membername, ptr) pairingheap_container(HnswSearchCandidate, membername, ptr)
-#define HnswGetSearchCandidateConst(membername, ptr) pairingheap_const_container(HnswSearchCandidate, membername, ptr)
-
 /*
  * Compare candidate distances
  */
 static int
 CompareNearestCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg)
 {
-	if (HnswGetSearchCandidateConst(c_node, a)->distance < HnswGetSearchCandidateConst(c_node, b)->distance)
+	if (((const HnswPairingHeapNode *) a)->inner->distance < ((const HnswPairingHeapNode *) b)->inner->distance)
 		return 1;
 
-	if (HnswGetSearchCandidateConst(c_node, a)->distance > HnswGetSearchCandidateConst(c_node, b)->distance)
+	if (((const HnswPairingHeapNode *) a)->inner->distance > ((const HnswPairingHeapNode *) b)->inner->distance)
 		return -1;
 
 	return 0;
@@ -645,15 +628,27 @@ CompareNearestCandidates(const pairingheap_node *a, const pairingheap_node *b, v
 static int
 CompareFurthestCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg)
 {
-	if (HnswGetSearchCandidateConst(w_node, a)->distance < HnswGetSearchCandidateConst(w_node, b)->distance)
+	if (((const HnswPairingHeapNode *) a)->inner->distance < ((const HnswPairingHeapNode *) b)->inner->distance)
 		return -1;
 
-	if (HnswGetSearchCandidateConst(w_node, a)->distance > HnswGetSearchCandidateConst(w_node, b)->distance)
+	if (((const HnswPairingHeapNode *) a)->inner->distance > ((const HnswPairingHeapNode *) b)->inner->distance)
 		return 1;
 
 	return 0;
 }
 
+/*
+ * Create a pairing heap node for a candidate
+ */
+static HnswPairingHeapNode *
+CreatePairingHeapNode(HnswCandidate * c)
+{
+	HnswPairingHeapNode *node = palloc(sizeof(HnswPairingHeapNode));
+
+	node->inner = c;
+	return node;
+}
+
 /*
  * Init visited
  */
@@ -672,11 +667,11 @@ InitVisited(char *base, visited_hash * v, Relation index, int ef, int m)
  * Add to visited
  */
 static inline void
-AddToVisited(char *base, visited_hash * v, HnswElementPtr elementPtr, Relation index, bool *found)
+AddToVisited(char *base, visited_hash * v, HnswCandidate * hc, Relation index, bool *found)
 {
 	if (index != NULL)
 	{
-		HnswElement element = HnswPtrAccess(base, elementPtr);
+		HnswElement element = HnswPtrAccess(base, hc->element);
 		ItemPointerData indextid;
 
 		ItemPointerSet(&indextid, element->blkno, element->offno);
@@ -684,15 +679,23 @@ AddToVisited(char *base, visited_hash * v, HnswElementPtr elementPtr, Relation i
 	}
 	else if (base != NULL)
 	{
-		HnswElement element = HnswPtrAccess(base, elementPtr);
+#if PG_VERSION_NUM >= 130000
+		HnswElement element = HnswPtrAccess(base, hc->element);
 
-		offsethash_insert_hash(v->offsets, HnswPtrOffset(elementPtr), element->hash, found);
+		offsethash_insert_hash(v->offsets, HnswPtrOffset(hc->element), element->hash, found);
+#else
+		offsethash_insert(v->offsets, HnswPtrOffset(hc->element), found);
+#endif
 	}
 	else
 	{
-		HnswElement element = HnswPtrAccess(base, elementPtr);
+#if PG_VERSION_NUM >= 130000
+		HnswElement element = HnswPtrAccess(base, hc->element);
 
-		pointerhash_insert_hash(v->pointers, (uintptr_t) HnswPtrPointer(elementPtr), element->hash, found);
+		pointerhash_insert_hash(v->pointers, (uintptr_t) HnswPtrPointer(hc->element), element->hash, found);
+#else
+		pointerhash_insert(v->pointers, (uintptr_t) HnswPtrPointer(hc->element), found);
+#endif
 	}
 }
 
@@ -700,96 +703,20 @@ AddToVisited(char *base, visited_hash * v, HnswElementPtr elementPtr, Relation i
  * Count element towards ef
  */
 static inline bool
-CountElement(HnswElement skipElement, HnswElement e)
+CountElement(char *base, HnswElement skipElement, HnswCandidate * hc)
 {
+	HnswElement e;
+
 	if (skipElement == NULL)
 		return true;
 
 	/* Ensure does not access heaptidsLength during in-memory build */
 	pg_memory_barrier();
 
-	/* Keep scan-build happy on Mac x86-64 */
+	e = HnswPtrAccess(base, hc->element);
-	Assert(e);
-
 	return e->heaptidsLength != 0;
 }
 
-/*
- * Load unvisited neighbors from memory
- */
-static void
-HnswLoadUnvisitedFromMemory(char *base, HnswElement element, HnswUnvisited * unvisited, int *unvisitedLength, visited_hash * v, int lc, HnswNeighborArray * localNeighborhood, Size neighborhoodSize)
-{
-	/* Get the neighborhood at layer lc */
-	HnswNeighborArray *neighborhood = HnswGetNeighbors(base, element, lc);
-
-	/* Copy neighborhood to local memory */
-	LWLockAcquire(&element->lock, LW_SHARED);
-	memcpy(localNeighborhood, neighborhood, neighborhoodSize);
-	LWLockRelease(&element->lock);
-
-	*unvisitedLength = 0;
-
-	for (int i = 0; i < localNeighborhood->length; i++)
-	{
-		HnswCandidate *hc = &localNeighborhood->items[i];
-		bool		found;
-
-		AddToVisited(base, v, hc->element, NULL, &found);
-
-		if (!found)
-			unvisited[(*unvisitedLength)++].element = HnswPtrAccess(base, hc->element);
-	}
-}
-
-/*
- * Load unvisited neighbors from disk
- */
-static void
-HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *unvisitedLength, visited_hash * v, Relation index, int m, int lm, int lc)
-{
-	Buffer		buf;
-	Page		page;
-	HnswNeighborTuple ntup;
-	int			start;
-	ItemPointerData indextids[HNSW_MAX_M * 2];
-
-	buf = ReadBuffer(index, element->neighborPage);
-	LockBuffer(buf, BUFFER_LOCK_SHARE);
-	page = BufferGetPage(buf);
-
-	ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, element->neighborOffno));
-
-	/* Ensure expected neighbors */
-	if (ntup->count != (element->level + 2) * m)
-	{
-		UnlockReleaseBuffer(buf);
-		return;
-	}
-
-	/* Copy to minimize lock time */
-	start = (element->level - lc) * m;
-	memcpy(&indextids, ntup->indextids + start, lm * sizeof(ItemPointerData));
-
-	UnlockReleaseBuffer(buf);
-
-	*unvisitedLength = 0;
-
-	for (int i = 0; i < lm; i++)
-	{
-		ItemPointer indextid = &indextids[i];
-		bool		found;
-
-		if (!ItemPointerIsValid(indextid))
-			break;
-
-		tidhash_insert(v->tids, *indextid, &found);
-
-		if (!found)
-			unvisited[(*unvisitedLength)++].indextid = *indextid;
-	}
-}
-
 /*
  * Algorithm 2 from paper
  */
@@ -802,45 +729,43 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
 	int			wlen = 0;
 	visited_hash v;
 	ListCell   *lc2;
-	HnswNeighborArray *localNeighborhood = NULL;
+	HnswNeighborArray *neighborhoodData = NULL;
-	Size		neighborhoodSize = 0;
+	Size		neighborhoodSize;
-	int			lm = HnswGetLayerM(m, lc);
-	HnswUnvisited *unvisited = palloc(lm * sizeof(HnswUnvisited));
-	int			unvisitedLength;
 
 	InitVisited(base, &v, index, ef, m);
 
 	/* Create local memory for neighborhood if needed */
 	if (index == NULL)
 	{
-		neighborhoodSize = HNSW_NEIGHBOR_ARRAY_SIZE(lm);
+		neighborhoodSize = HNSW_NEIGHBOR_ARRAY_SIZE(HnswGetLayerM(m, lc));
-		localNeighborhood = palloc(neighborhoodSize);
+		neighborhoodData = palloc(neighborhoodSize);
 	}
 
 	/* Add entry points to v, C, and W */
 	foreach(lc2, ep)
 	{
-		HnswSearchCandidate *hc = (HnswSearchCandidate *) lfirst(lc2);
+		HnswCandidate *hc = (HnswCandidate *) lfirst(lc2);
 		bool		found;
 
-		AddToVisited(base, &v, hc->element, index, &found);
+		AddToVisited(base, &v, hc, index, &found);
 
-		pairingheap_add(C, &hc->c_node);
+		pairingheap_add(C, &(CreatePairingHeapNode(hc)->ph_node));
-		pairingheap_add(W, &hc->w_node);
+		pairingheap_add(W, &(CreatePairingHeapNode(hc)->ph_node));
 
 		/*
 		 * Do not count elements being deleted towards ef when vacuuming. It
 		 * would be ideal to do this for inserts as well, but this could
 		 * affect insert performance.
 		 */
-		if (CountElement(skipElement, HnswPtrAccess(base, hc->element)))
+		if (CountElement(base, skipElement, hc))
 			wlen++;
 	}
 
 	while (!pairingheap_is_empty(C))
 	{
-		HnswSearchCandidate *c = HnswGetSearchCandidate(c_node, pairingheap_remove_first(C));
+		HnswNeighborArray *neighborhood;
-		HnswSearchCandidate *f = HnswGetSearchCandidate(w_node, pairingheap_first(W));
+		HnswCandidate *c = ((HnswPairingHeapNode *) pairingheap_remove_first(C))->inner;
+		HnswCandidate *f = ((HnswPairingHeapNode *) pairingheap_first(W))->inner;
 		HnswElement cElement;
 
 		if (c->distance > f->distance)
@@ -848,67 +773,73 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
 
 		cElement = HnswPtrAccess(base, c->element);
 
+		if (HnswPtrIsNull(base, cElement->neighbors))
+			HnswLoadNeighbors(cElement, index, m);
+
+		/* Get the neighborhood at layer lc */
+		neighborhood = HnswGetNeighbors(base, cElement, lc);
+
+		/* Copy neighborhood to local memory if needed */
 		if (index == NULL)
-			HnswLoadUnvisitedFromMemory(base, cElement, unvisited, &unvisitedLength, &v, lc, localNeighborhood, neighborhoodSize);
-		else
-			HnswLoadUnvisitedFromDisk(cElement, unvisited, &unvisitedLength, &v, index, m, lm, lc);
-
-		for (int i = 0; i < unvisitedLength; i++)
 		{
-			HnswElement eElement;
+			LWLockAcquire(&cElement->lock, LW_SHARED);
-			HnswSearchCandidate *e;
+			memcpy(neighborhoodData, neighborhood, neighborhoodSize);
-			float		eDistance;
+			LWLockRelease(&cElement->lock);
-			bool		alwaysAdd = wlen < ef;
+			neighborhood = neighborhoodData;
+		}
 
-			f = HnswGetSearchCandidate(w_node, pairingheap_first(W));
+		for (int i = 0; i < neighborhood->length; i++)
+		{
+			HnswCandidate *e = &neighborhood->items[i];
+			bool		visited;
 
-			if (index == NULL)
+			AddToVisited(base, &v, e, index, &visited);
+
+			if (!visited)
 			{
-				eElement = unvisited[i].element;
+				float		eDistance;
-				eDistance = GetElementDistance(base, eElement, q, procinfo, collation);
+				HnswElement eElement = HnswPtrAccess(base, e->element);
-			}
+				bool		alwaysAdd = wlen < ef;
-			else
-			{
-				ItemPointer indextid = &unvisited[i].indextid;
-				BlockNumber blkno = ItemPointerGetBlockNumber(indextid);
-				OffsetNumber offno = ItemPointerGetOffsetNumber(indextid);
 
-				/* Avoid any allocations if not adding */
+				f = ((HnswPairingHeapNode *) pairingheap_first(W))->inner;
-				eElement = NULL;
-				HnswLoadElementImpl(blkno, offno, &eDistance, &q, index, procinfo, collation, inserting, alwaysAdd ? NULL : &f->distance, &eElement);
 
-				if (eElement == NULL)
+				if (index == NULL)
-					continue;
+					eDistance = GetCandidateDistance(base, e, q, procinfo, collation);
-			}
+				else
+					HnswLoadElement(eElement, &eDistance, &q, index, procinfo, collation, inserting, alwaysAdd ? NULL : &f->distance);
 
-			if (!(eDistance < f->distance || alwaysAdd))
+				if (eDistance < f->distance || alwaysAdd)
-				continue;
+				{
+					HnswCandidate *ec;
 
-			Assert(!eElement->deleted);
+					Assert(!eElement->deleted);
 
-			/* Make robust to issues */
+					/* Make robust to issues */
-			if (eElement->level < lc)
+					if (eElement->level < lc)
-				continue;
+						continue;
 
-			/* Create a new candidate */
+					/* Copy e */
-			e = palloc(sizeof(HnswSearchCandidate));
+					ec = palloc(sizeof(HnswCandidate));
-			HnswPtrStore(base, e->element, eElement);
+					HnswPtrStore(base, ec->element, eElement);
-			e->distance = eDistance;
+					ec->distance = eDistance;
-			pairingheap_add(C, &e->c_node);
-			pairingheap_add(W, &e->w_node);
 
-			/*
+					pairingheap_add(C, &(CreatePairingHeapNode(ec)->ph_node));
-			 * Do not count elements being deleted towards ef when vacuuming.
+					pairingheap_add(W, &(CreatePairingHeapNode(ec)->ph_node));
-			 * It would be ideal to do this for inserts as well, but this
-			 * could affect insert performance.
-			 */
-			if (CountElement(skipElement, eElement))
-			{
-				wlen++;
 
-				/* No need to decrement wlen */
+					/*
-				if (wlen > ef)
+					 * Do not count elements being deleted towards ef when
-					pairingheap_remove_first(W);
+					 * vacuuming. It would be ideal to do this for inserts as
+					 * well, but this could affect insert performance.
+					 */
+					if (CountElement(base, skipElement, e))
+					{
+						wlen++;
+
+						/* No need to decrement wlen */
+						if (wlen > ef)
+							pairingheap_remove_first(W);
+					}
+				}
 			}
 		}
 	}
@@ -916,7 +847,7 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
 	/* Add each element of W to w */
 	while (!pairingheap_is_empty(W))
 	{
-		HnswSearchCandidate *hc = HnswGetSearchCandidate(w_node, pairingheap_remove_first(W));
+		HnswCandidate *hc = ((HnswPairingHeapNode *) pairingheap_remove_first(W))->inner;
 
 		w = lappend(w, hc);
 	}
@@ -928,10 +859,17 @@ HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, F
  * Compare candidate distances with pointer tie-breaker
  */
 static int
+#if PG_VERSION_NUM >= 130000
 CompareCandidateDistances(const ListCell *a, const ListCell *b)
 {
 	HnswCandidate *hca = lfirst(a);
 	HnswCandidate *hcb = lfirst(b);
+#else
+CompareCandidateDistances(const void *a, const void *b)
+{
+	HnswCandidate *hca = lfirst(*(ListCell **) a);
+	HnswCandidate *hcb = lfirst(*(ListCell **) b);
+#endif
 
 	if (hca->distance < hcb->distance)
 		return 1;
@@ -952,10 +890,17 @@ CompareCandidateDistances(const ListCell *a, const ListCell *b)
  * Compare candidate distances with offset tie-breaker
  */
 static int
+#if PG_VERSION_NUM >= 130000
 CompareCandidateDistancesOffset(const ListCell *a, const ListCell *b)
 {
 	HnswCandidate *hca = lfirst(a);
 	HnswCandidate *hcb = lfirst(b);
+#else
+CompareCandidateDistancesOffset(const void *a, const void *b)
+{
+	HnswCandidate *hca = lfirst(*(ListCell **) a);
+	HnswCandidate *hcb = lfirst(*(ListCell **) b);
+#endif
 
 	if (hca->distance < hcb->distance)
 		return 1;
@@ -1165,7 +1110,7 @@ HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm
 				if (HnswPtrIsNull(base, hc3Element->value))
 					HnswLoadElement(hc3Element, &hc3->distance, &q, index, procinfo, collation, true, NULL);
 				else
-					hc3->distance = GetElementDistance(base, hc3Element, q, procinfo, collation);
+					hc3->distance = GetCandidateDistance(base, hc3, q, procinfo, collation);
 
 				/* Prune element if being deleted */
 				if (hc3Element->heaptidsLength == 0)
@@ -1237,6 +1182,7 @@ RemoveElements(char *base, List *w, HnswElement skipElement)
 	return w2;
 }
 
+#if PG_VERSION_NUM >= 130000
 /*
  * Precompute hash
  */
@@ -1252,6 +1198,7 @@ PrecomputeHash(char *base, HnswElement element)
 	else
 		element->hash = hash_offset(HnswPtrOffset(ptr));
 }
+#endif
 
 /*
  * Algorithm 1 from paper
@@ -1266,9 +1213,11 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
 	Datum		q = HnswGetValue(base, element);
 	HnswElement skipElement = existing ? element : NULL;
 
+#if PG_VERSION_NUM >= 130000
 	/* Precompute hash */
 	if (index == NULL)
 		PrecomputeHash(base, element);
+#endif
 
 	/* No neighbors if no entry point */
 	if (entryPoint == NULL)
@@ -1297,27 +1246,16 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
 	{
 		int			lm = HnswGetLayerM(m, lc);
 		List	   *neighbors;
-		List	   *lw = NIL;
+		List	   *lw;
-		ListCell   *lc2;
 
 		w = HnswSearchLayer(base, q, ep, efConstruction, lc, index, procinfo, collation, m, true, skipElement);
 
-		/* Convert search candidates to candidates */
-		foreach(lc2, w)
-		{
-			HnswSearchCandidate *sc = lfirst(lc2);
-			HnswCandidate *hc = palloc(sizeof(HnswCandidate));
-
-			hc->element = sc->element;
-			hc->distance = sc->distance;
-
-			lw = lappend(lw, hc);
-		}
-
 		/* Elements being deleted or skipped can help with search */
 		/* but should be removed before selecting neighbors */
 		if (index != NULL)
-			lw = RemoveElements(base, lw, skipElement);
+			lw = RemoveElements(base, w, skipElement);
+		else
+			lw = w;
 
 		/*
 		 * Candidates are sorted, but not deterministically. Could set
@@ -1342,9 +1280,7 @@ SparsevecCheckValue(Pointer v)
 	SparseVector *vec = (SparseVector *) v;
 
 	if (vec->nnz > HNSW_MAX_NNZ)
-		ereport(ERROR,
+		elog(ERROR, "sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ);
-				(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
-				 errmsg("sparsevec cannot have more than %d non-zero elements for hnsw index", HNSW_MAX_NNZ)));
 }
 
 /*

src/ivfbuild.c

@@ -26,6 +26,12 @@
 #include "pgstat.h"
 #endif
 
+#if PG_VERSION_NUM >= 130000
+#define CALLBACK_ITEM_POINTER ItemPointer tid
+#else
+#define CALLBACK_ITEM_POINTER HeapTuple hup
+#endif
+
 #if PG_VERSION_NUM >= 140000
 #include "utils/backend_status.h"
 #include "utils/wait_event.h"
@@ -90,7 +96,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
  * Callback for sampling
  */
 static void
-SampleCallback(Relation index, ItemPointer tid, Datum *values,
+SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
 			   bool *isnull, bool tupleIsAlive, void *state)
 {
 	IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
@@ -201,12 +207,16 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
  * Callback for table_index_build_scan
  */
 static void
-BuildCallback(Relation index, ItemPointer tid, Datum *values,
+BuildCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
 			  bool *isnull, bool tupleIsAlive, void *state)
 {
 	IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
 	MemoryContext oldCtx;
 
+#if PG_VERSION_NUM < 130000
+	ItemPointer tid = &hup->t_self;
+#endif
+
 	/* Skip nulls */
 	if (isnull[0])
 		return;
@@ -325,20 +335,14 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
 
 	/* Disallow varbit since require fixed dimensions */
 	if (TupleDescAttr(index->rd_att, 0)->atttypid == VARBITOID)
-		ereport(ERROR,
+		elog(ERROR, "type not supported for ivfflat index");
-				(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
-				 errmsg("type not supported for ivfflat index")));
 
 	/* Require column to have dimensions to be indexed */
 	if (buildstate->dimensions < 0)
-		ereport(ERROR,
+		elog(ERROR, "column does not have dimensions");
-				(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
-				 errmsg("column does not have dimensions")));
 
 	if (buildstate->dimensions > buildstate->typeInfo->maxDimensions)
-		ereport(ERROR,
+		elog(ERROR, "column cannot have more than %d dimensions for ivfflat index", buildstate->typeInfo->maxDimensions);
-				(errcode(ERRCODE_PROGRAM_LIMIT_EXCEEDED),
-				 errmsg("column cannot have more than %d dimensions for ivfflat index", buildstate->typeInfo->maxDimensions)));
 
 	buildstate->reltuples = 0;
 	buildstate->indtuples = 0;
@@ -351,9 +355,7 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
 
 	/* Require more than one dimension for spherical k-means */
 	if (buildstate->kmeansnormprocinfo != NULL && buildstate->dimensions == 1)
-		ereport(ERROR,
+		elog(ERROR, "dimensions must be greater than one for this opclass");
-				(errcode(ERRCODE_INVALID_PARAMETER_VALUE),
-				 errmsg("dimensions must be greater than one for this opclass")));
 
 	/* Create tuple description for sorting */
 	buildstate->tupdesc = CreateTemplateTupleDesc(3);
@@ -560,20 +562,6 @@ PrintKmeansMetrics(IvfflatBuildState * buildstate)
 }
 #endif
 
-/*
- * Initialize build sort state
- */
-static Tuplesortstate *
-InitBuildSortState(TupleDesc tupdesc, int memory, SortCoordinate coordinate)
-{
-	AttrNumber	attNums[] = {1};
-	Oid			sortOperators[] = {Int4LessOperator};
-	Oid			sortCollations[] = {InvalidOid};
-	bool		nullsFirstFlags[] = {false};
-
-	return tuplesort_begin_heap(tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, memory, coordinate, false);
-}
-
 /*
  * Within leader, wait for end of heap scan
  */
@@ -621,6 +609,12 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
 	double		reltuples;
 	IndexInfo  *indexInfo;
 
+	/* Sort options, which must match AssignTuples */
+	AttrNumber	attNums[] = {1};
+	Oid			sortOperators[] = {Int4LessOperator};
+	Oid			sortCollations[] = {InvalidOid};
+	bool		nullsFirstFlags[] = {false};
+
 	/* Initialize local tuplesort coordination state */
 	coordinate = palloc0(sizeof(SortCoordinateData));
 	coordinate->isWorker = true;
@@ -633,7 +627,7 @@ IvfflatParallelScanAndSort(IvfflatSpool * ivfspool, IvfflatShared * ivfshared, S
 	InitBuildState(&buildstate, ivfspool->heap, ivfspool->index, indexInfo);
 	memcpy(buildstate.centers->items, ivfcenters, buildstate.centers->itemsize * buildstate.centers->maxlen);
 	buildstate.centers->length = buildstate.centers->maxlen;
-	ivfspool->sortstate = InitBuildSortState(buildstate.tupdesc, sortmem, coordinate);
+	ivfspool->sortstate = tuplesort_begin_heap(buildstate.tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, sortmem, coordinate, false);
 	buildstate.sortstate = ivfspool->sortstate;
 	scan = table_beginscan_parallel(ivfspool->heap,
 									ParallelTableScanFromIvfflatShared(ivfshared));
@@ -930,6 +924,12 @@ AssignTuples(IvfflatBuildState * buildstate)
 	int			parallel_workers = 0;
 	SortCoordinate coordinate = NULL;
 
+	/* Sort options, which must match IvfflatParallelScanAndSort */
+	AttrNumber	attNums[] = {1};
+	Oid			sortOperators[] = {Int4LessOperator};
+	Oid			sortCollations[] = {InvalidOid};
+	bool		nullsFirstFlags[] = {false};
+
 	pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_ASSIGN);
 
 	/* Calculate parallel workers */
@@ -950,7 +950,7 @@ AssignTuples(IvfflatBuildState * buildstate)
 	}
 
 	/* Begin serial/leader tuplesort */
-	buildstate->sortstate = InitBuildSortState(buildstate->tupdesc, maintenance_work_mem, coordinate);
+	buildstate->sortstate = tuplesort_begin_heap(buildstate->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, maintenance_work_mem, coordinate, false);
 
 	/* Add tuples to sort */
 	if (buildstate->heap != NULL)

src/ivfflat.c

@@ -7,7 +7,6 @@
 #include "commands/progress.h"
 #include "commands/vacuum.h"
 #include "ivfflat.h"
-#include "utils/float.h"
 #include "utils/guc.h"
 #include "utils/selfuncs.h"
 #include "utils/spccache.h"
@@ -27,7 +26,11 @@ IvfflatInit(void)
 {
 	ivfflat_relopt_kind = add_reloption_kind();
 	add_int_reloption(ivfflat_relopt_kind, "lists", "Number of inverted lists",
-					  IVFFLAT_DEFAULT_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, AccessExclusiveLock);
+					  IVFFLAT_DEFAULT_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS
+#if PG_VERSION_NUM >= 130000
+					  ,AccessExclusiveLock
+#endif
+		);
 
 	DefineCustomIntVariable("ivfflat.probes", "Sets the number of probes",
 							"Valid range is 1..lists.", &ivfflat_probes,
@@ -69,16 +72,14 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
 	GenericCosts costs;
 	int			lists;
 	double		ratio;
-	double		sequentialRatio = 0.5;
-	double		startupPages;
 	double		spc_seq_page_cost;
 	Relation	index;
 
 	/* Never use index without order */
 	if (path->indexorderbys == NULL)
 	{
-		*indexStartupCost = get_float8_infinity();
+		*indexStartupCost = DBL_MAX;
-		*indexTotalCost = get_float8_infinity();
+		*indexTotalCost = DBL_MAX;
 		*indexSelectivity = 0;
 		*indexCorrelation = 0;
 		*indexPages = 0;
@@ -87,8 +88,6 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
 
 	MemSet(&costs, 0, sizeof(costs));
 
-	genericcostestimate(root, path, loop_count, &costs);
-
 	index = index_open(path->indexinfo->indexoid, NoLock);
 	IvfflatGetMetaPageInfo(index, &lists, NULL);
 	index_close(index, NoLock);
@@ -98,26 +97,41 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
 	if (ratio > 1.0)
 		ratio = 1.0;
 
+	/*
+	 * This gives us the subset of tuples to visit. This value is passed into
+	 * the generic cost estimator to determine the number of pages to visit
+	 * during the index scan.
+	 */
+	costs.numIndexTuples = path->indexinfo->tuples * ratio;
+
+	genericcostestimate(root, path, loop_count, &costs);
+
 	get_tablespace_page_costs(path->indexinfo->reltablespace, NULL, &spc_seq_page_cost);
 
-	/* Change some page cost from random to sequential */
-	costs.indexTotalCost -= sequentialRatio * costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
-
-	/* Startup cost is cost before returning the first row */
-	costs.indexStartupCost = costs.indexTotalCost * ratio;
-
 	/* Adjust cost if needed since TOAST not included in seq scan cost */
-	startupPages = costs.numIndexPages * ratio;
+	if (costs.numIndexPages > path->indexinfo->rel->pages && ratio < 0.5)
-	if (startupPages > path->indexinfo->rel->pages && ratio < 0.5)
 	{
-		/* Change rest of page cost from random to sequential */
+		/* Change all page cost from random to sequential */
-		costs.indexStartupCost -= (1 - sequentialRatio) * startupPages * (costs.spc_random_page_cost - spc_seq_page_cost);
+		costs.indexTotalCost -= costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
 
 		/* Remove cost of extra pages */
-		costs.indexStartupCost -= (startupPages - path->indexinfo->rel->pages) * spc_seq_page_cost;
+		costs.indexTotalCost -= (costs.numIndexPages - path->indexinfo->rel->pages) * spc_seq_page_cost;
+	}
+	else
+	{
+		/* Change some page cost from random to sequential */
+		costs.indexTotalCost -= 0.5 * costs.numIndexPages * (costs.spc_random_page_cost - spc_seq_page_cost);
 	}
 
-	*indexStartupCost = costs.indexStartupCost;
+	/*
+	 * If the list selectivity is lower than what is returned from the generic
+	 * cost estimator, use that.
+	 */
+	if (ratio < costs.indexSelectivity)
+		costs.indexSelectivity = ratio;
+
+	/* Use total cost since most work happens before first tuple is returned */
+	*indexStartupCost = costs.indexTotalCost;
 	*indexTotalCost = costs.indexTotalCost;
 	*indexSelectivity = costs.indexSelectivity;
 	*indexCorrelation = costs.indexCorrelation;
@@ -134,10 +148,23 @@ ivfflatoptions(Datum reloptions, bool validate)
 		{"lists", RELOPT_TYPE_INT, offsetof(IvfflatOptions, lists)},
 	};
 
+#if PG_VERSION_NUM >= 130000
 	return (bytea *) build_reloptions(reloptions, validate,
 									  ivfflat_relopt_kind,
 									  sizeof(IvfflatOptions),
 									  tab, lengthof(tab));
+#else
+	relopt_value *options;
+	int			numoptions;
+	IvfflatOptions *rdopts;
+
+	options = parseRelOptions(reloptions, validate, ivfflat_relopt_kind, &numoptions);
+	rdopts = allocateReloptStruct(sizeof(IvfflatOptions), options, numoptions);
+	fillRelOptions((void *) rdopts, sizeof(IvfflatOptions), options, numoptions,
+				   validate, tab, lengthof(tab));
+
+	return (bytea *) rdopts;
+#endif
 }
 
 /*
@@ -162,7 +189,9 @@ ivfflathandler(PG_FUNCTION_ARGS)
 
 	amroutine->amstrategies = 0;
 	amroutine->amsupport = 5;
+#if PG_VERSION_NUM >= 130000
 	amroutine->amoptsprocnum = 0;
+#endif
 	amroutine->amcanorder = false;
 	amroutine->amcanorderbyop = true;
 	amroutine->amcanbackward = false;	/* can change direction mid-scan */
@@ -175,24 +204,17 @@ ivfflathandler(PG_FUNCTION_ARGS)
 	amroutine->amclusterable = false;
 	amroutine->ampredlocks = false;
 	amroutine->amcanparallel = false;
-#if PG_VERSION_NUM >= 170000
-	amroutine->amcanbuildparallel = true;
-#endif
 	amroutine->amcaninclude = false;
+#if PG_VERSION_NUM >= 130000
 	amroutine->amusemaintenanceworkmem = false; /* not used during VACUUM */
-#if PG_VERSION_NUM >= 160000
-	amroutine->amsummarizing = false;
-#endif
 	amroutine->amparallelvacuumoptions = VACUUM_OPTION_PARALLEL_BULKDEL;
+#endif
 	amroutine->amkeytype = InvalidOid;
 
 	/* Interface functions */
 	amroutine->ambuild = ivfflatbuild;
 	amroutine->ambuildempty = ivfflatbuildempty;
 	amroutine->aminsert = ivfflatinsert;
-#if PG_VERSION_NUM >= 170000
-	amroutine->aminsertcleanup = NULL;
-#endif
 	amroutine->ambulkdelete = ivfflatbulkdelete;
 	amroutine->amvacuumcleanup = ivfflatvacuumcleanup;
 	amroutine->amcanreturn = NULL;	/* tuple not included in heapsort */

src/ivfflat.h

@@ -253,9 +253,8 @@ typedef struct IvfflatScanOpaqueData
 	/* Sorting */
 	Tuplesortstate *sortstate;
 	TupleDesc	tupdesc;
-	TupleTableSlot *vslot;
+	TupleTableSlot *slot;
-	TupleTableSlot *mslot;
+	bool		isnull;
-	BufferAccessStrategy bas;
 
 	/* Support functions */
 	FmgrInfo   *procinfo;

src/ivfkmeans.c

@@ -151,8 +151,12 @@ RandomCenters(Relation index, VectorArray centers, const IvfflatTypeInfo * typeI
 static void
 ShowMemoryUsage(MemoryContext context, Size estimatedSize)
 {
+#if PG_VERSION_NUM >= 130000
 	elog(INFO, "total memory: %zu MB",
 		 MemoryContextMemAllocated(context, true) / (1024 * 1024));
+#else
+	MemoryContextStats(context);
+#endif
 	elog(INFO, "estimated memory: %zu MB", estimatedSize / (1024 * 1024));
 }
 #endif
@@ -323,7 +327,7 @@ ElkanKmeans(Relation index, VectorArray samples, VectorArray centers, const Ivff
 	newCenters->length = numCenters;
 
 #ifdef IVFFLAT_MEMORY
-	ShowMemoryUsage(MemoryContextGetParent(CurrentMemoryContext), totalSize);
+	ShowMemoryUsage(MemoryContextGetParent(CurrentMemoryContext));
 #endif
 
 	/* Pick initial centers */

src/ivfscan.c

@@ -11,23 +11,16 @@
 #include "pgstat.h"
 #include "storage/bufmgr.h"
 
-#ifdef IVFFLAT_MEMORY
-#include "utils/memutils.h"
-#endif
-
-#define GetScanList(ptr) pairingheap_container(IvfflatScanList, ph_node, ptr)
-#define GetScanListConst(ptr) pairingheap_const_container(IvfflatScanList, ph_node, ptr)
-
 /*
  * Compare list distances
  */
 static int
 CompareLists(const pairingheap_node *a, const pairingheap_node *b, void *arg)
 {
-	if (GetScanListConst(a)->distance > GetScanListConst(b)->distance)
+	if (((const IvfflatScanList *) a)->distance > ((const IvfflatScanList *) b)->distance)
 		return 1;
 
-	if (GetScanListConst(a)->distance < GetScanListConst(b)->distance)
+	if (((const IvfflatScanList *) a)->distance < ((const IvfflatScanList *) b)->distance)
 		return -1;
 
 	return 0;
@@ -79,14 +72,14 @@ GetScanLists(IndexScanDesc scan, Datum value)
 
 				/* Calculate max distance */
 				if (listCount == so->probes)
-					maxDistance = GetScanList(pairingheap_first(so->listQueue))->distance;
+					maxDistance = ((IvfflatScanList *) pairingheap_first(so->listQueue))->distance;
 			}
 			else if (distance < maxDistance)
 			{
 				IvfflatScanList *scanlist;
 
 				/* Remove */
-				scanlist = GetScanList(pairingheap_remove_first(so->listQueue));
+				scanlist = (IvfflatScanList *) pairingheap_remove_first(so->listQueue);
 
 				/* Reuse */
 				scanlist->startPage = list->startPage;
@@ -94,7 +87,7 @@ GetScanLists(IndexScanDesc scan, Datum value)
 				pairingheap_add(so->listQueue, &scanlist->ph_node);
 
 				/* Update max distance */
-				maxDistance = GetScanList(pairingheap_first(so->listQueue))->distance;
+				maxDistance = ((IvfflatScanList *) pairingheap_first(so->listQueue))->distance;
 			}
 		}
 
@@ -113,12 +106,19 @@ GetScanItems(IndexScanDesc scan, Datum value)
 	IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
 	TupleDesc	tupdesc = RelationGetDescr(scan->indexRelation);
 	double		tuples = 0;
-	TupleTableSlot *slot = so->vslot;
+	TupleTableSlot *slot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsVirtual);
+
+	/*
+	 * Reuse same set of shared buffers for scan
+	 *
+	 * See postgres/src/backend/storage/buffer/README for description
+	 */
+	BufferAccessStrategy bas = GetAccessStrategy(BAS_BULKREAD);
 
 	/* Search closest probes lists */
 	while (!pairingheap_is_empty(so->listQueue))
 	{
-		BlockNumber searchPage = GetScanList(pairingheap_remove_first(so->listQueue))->startPage;
+		BlockNumber searchPage = ((IvfflatScanList *) pairingheap_remove_first(so->listQueue))->startPage;
 
 		/* Search all entry pages for list */
 		while (BlockNumberIsValid(searchPage))
@@ -127,7 +127,7 @@ GetScanItems(IndexScanDesc scan, Datum value)
 			Page		page;
 			OffsetNumber maxoffno;
 
-			buf = ReadBufferExtended(scan->indexRelation, MAIN_FORKNUM, searchPage, RBM_NORMAL, so->bas);
+			buf = ReadBufferExtended(scan->indexRelation, MAIN_FORKNUM, searchPage, RBM_NORMAL, bas);
 			LockBuffer(buf, BUFFER_LOCK_SHARE);
 			page = BufferGetPage(buf);
 			maxoffno = PageGetMaxOffsetNumber(page);
@@ -166,6 +166,8 @@ GetScanItems(IndexScanDesc scan, Datum value)
 		}
 	}
 
+	FreeAccessStrategy(bas);
+
 	if (tuples < 100)
 		ereport(DEBUG1,
 				(errmsg("index scan found few tuples"),
@@ -215,20 +217,6 @@ GetScanValue(IndexScanDesc scan)
 	return value;
 }
 
-/*
- * Initialize scan sort state
- */
-static Tuplesortstate *
-InitScanSortState(TupleDesc tupdesc)
-{
-	AttrNumber	attNums[] = {1};
-	Oid			sortOperators[] = {Float8LessOperator};
-	Oid			sortCollations[] = {InvalidOid};
-	bool		nullsFirstFlags[] = {false};
-
-	return tuplesort_begin_heap(tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
-}
-
 /*
  * Prepare for an index scan
  */
@@ -239,6 +227,10 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
 	IvfflatScanOpaque so;
 	int			lists;
 	int			dimensions;
+	AttrNumber	attNums[] = {1};
+	Oid			sortOperators[] = {Float8LessOperator};
+	Oid			sortCollations[] = {InvalidOid};
+	bool		nullsFirstFlags[] = {false};
 	int			probes = ivfflat_probes;
 
 	scan = RelationGetIndexScan(index, nkeys, norderbys);
@@ -266,18 +258,9 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
 	TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
 
 	/* Prep sort */
-	so->sortstate = InitScanSortState(so->tupdesc);
+	so->sortstate = tuplesort_begin_heap(so->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
 
-	/* Need separate slots for puttuple and gettuple */
+	so->slot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsMinimalTuple);
-	so->vslot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsVirtual);
-	so->mslot = MakeSingleTupleTableSlot(so->tupdesc, &TTSOpsMinimalTuple);
-
-	/*
-	 * Reuse same set of shared buffers for scan
-	 *
-	 * See postgres/src/backend/storage/buffer/README for description
-	 */
-	so->bas = GetAccessStrategy(BAS_BULKREAD);
 
 	so->listQueue = pairingheap_allocate(CompareLists, scan);
 
@@ -294,8 +277,10 @@ ivfflatrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int
 {
 	IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
 
+#if PG_VERSION_NUM >= 130000
 	if (!so->first)
 		tuplesort_reset(so->sortstate);
+#endif
 
 	so->first = true;
 	pairingheap_reset(so->listQueue);
@@ -342,19 +327,14 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
 		IvfflatBench("GetScanItems", GetScanItems(scan, value));
 		so->first = false;
 
-#if defined(IVFFLAT_MEMORY)
-		elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(CurrentMemoryContext, true) / (1024 * 1024));
-#endif
-
 		/* Clean up if we allocated a new value */
 		if (value != scan->orderByData->sk_argument)
 			pfree(DatumGetPointer(value));
 	}
 
-	if (tuplesort_gettupleslot(so->sortstate, true, false, so->mslot, NULL))
+	if (tuplesort_gettupleslot(so->sortstate, true, false, so->slot, NULL))
 	{
-		bool		isnull;
+		ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
-		ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->mslot, 2, &isnull));
 
 		scan->xs_heaptid = *heaptid;
 		scan->xs_recheck = false;
@@ -375,10 +355,6 @@ ivfflatendscan(IndexScanDesc scan)
 
 	pairingheap_free(so->listQueue);
 	tuplesort_end(so->sortstate);
-	FreeAccessStrategy(so->bas);
-	FreeTupleDesc(so->tupdesc);
-
-	/* TODO Free vslot and mslot without freeing TupleDesc */
 
 	pfree(so);
 	scan->opaque = NULL;

src/sparsevec.c

@@ -3,7 +3,6 @@
 #include <limits.h>
 #include <math.h>
 
-#include "catalog/pg_type.h"
 #include "common/string.h"
 #include "fmgr.h"
 #include "halfutils.h"
@@ -12,7 +11,6 @@
 #include "sparsevec.h"
 #include "utils/array.h"
 #include "utils/builtins.h"
-#include "utils/lsyscache.h"
 #include "vector.h"
 
 #if PG_VERSION_NUM >= 120000
@@ -672,137 +670,6 @@ halfvec_to_sparsevec(PG_FUNCTION_ARGS)
 	PG_RETURN_POINTER(result);
 }
 
-/*
- * Convert array to sparse vector
- */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(array_to_sparsevec);
-Datum
-array_to_sparsevec(PG_FUNCTION_ARGS)
-{
-	ArrayType  *array = PG_GETARG_ARRAYTYPE_P(0);
-	int32		typmod = PG_GETARG_INT32(1);
-	SparseVector *result;
-	int16		typlen;
-	bool		typbyval;
-	char		typalign;
-	Datum	   *elemsp;
-	int			nelemsp;
-	int			nnz = 0;
-	float	   *values;
-	int			j = 0;
-
-	if (ARR_NDIM(array) > 1)
-		ereport(ERROR,
-				(errcode(ERRCODE_DATA_EXCEPTION),
-				 errmsg("array must be 1-D")));
-
-	if (ARR_HASNULL(array) && array_contains_nulls(array))
-		ereport(ERROR,
-				(errcode(ERRCODE_NULL_VALUE_NOT_ALLOWED),
-				 errmsg("array must not contain nulls")));
-
-	get_typlenbyvalalign(ARR_ELEMTYPE(array), &typlen, &typbyval, &typalign);
-	deconstruct_array(array, ARR_ELEMTYPE(array), typlen, typbyval, typalign, &elemsp, NULL, &nelemsp);
-
-	CheckDim(nelemsp);
-	CheckExpectedDim(typmod, nelemsp);
-
-#ifdef _MSC_VER
-/* /fp:fast may not propagate +/-Infinity or NaN */
-#define IS_NOT_ZERO(v) (isnan((float) (v)) || isinf((float) (v)) || ((float) (v)) != 0)
-#else
-#define IS_NOT_ZERO(v) (((float) (v)) != 0)
-#endif
-
-	if (ARR_ELEMTYPE(array) == INT4OID)
-	{
-		for (int i = 0; i < nelemsp; i++)
-			nnz += IS_NOT_ZERO(DatumGetInt32(elemsp[i]));
-	}
-	else if (ARR_ELEMTYPE(array) == FLOAT8OID)
-	{
-		for (int i = 0; i < nelemsp; i++)
-			nnz += IS_NOT_ZERO(DatumGetFloat8(elemsp[i]));
-	}
-	else if (ARR_ELEMTYPE(array) == FLOAT4OID)
-	{
-		for (int i = 0; i < nelemsp; i++)
-			nnz += IS_NOT_ZERO(DatumGetFloat4(elemsp[i]));
-	}
-	else if (ARR_ELEMTYPE(array) == NUMERICOID)
-	{
-		for (int i = 0; i < nelemsp; i++)
-			nnz += IS_NOT_ZERO(DirectFunctionCall1(numeric_float4, elemsp[i]));
-	}
-	else
-	{
-		ereport(ERROR,
-				(errcode(ERRCODE_DATA_EXCEPTION),
-				 errmsg("unsupported array type")));
-	}
-
-	result = InitSparseVector(nelemsp, nnz);
-	values = SPARSEVEC_VALUES(result);
-
-#define PROCESS_ARRAY_ELEM(elem) \
-	do { \
-		float v = (float) (elem); \
-		if (IS_NOT_ZERO(v)) { \
-			/* Safety check */ \
-			if (j >= result->nnz) \
-				elog(ERROR, "safety check failed"); \
-			result->indices[j] = i; \
-			values[j] = v; \
-			j++; \
-		} \
-	} while (0)
-
-	if (ARR_ELEMTYPE(array) == INT4OID)
-	{
-		for (int i = 0; i < nelemsp; i++)
-			PROCESS_ARRAY_ELEM(DatumGetInt32(elemsp[i]));
-	}
-	else if (ARR_ELEMTYPE(array) == FLOAT8OID)
-	{
-		for (int i = 0; i < nelemsp; i++)
-			PROCESS_ARRAY_ELEM(DatumGetFloat8(elemsp[i]));
-	}
-	else if (ARR_ELEMTYPE(array) == FLOAT4OID)
-	{
-		for (int i = 0; i < nelemsp; i++)
-			PROCESS_ARRAY_ELEM(DatumGetFloat4(elemsp[i]));
-	}
-	else if (ARR_ELEMTYPE(array) == NUMERICOID)
-	{
-		for (int i = 0; i < nelemsp; i++)
-			PROCESS_ARRAY_ELEM(DatumGetFloat4(DirectFunctionCall1(numeric_float4, elemsp[i])));
-	}
-	else
-	{
-		ereport(ERROR,
-				(errcode(ERRCODE_DATA_EXCEPTION),
-				 errmsg("unsupported array type")));
-	}
-
-#undef PROCESS_ARRAY_ELEM
-#undef IS_NOT_ZERO
-
-	/*
-	 * Free allocation from deconstruct_array. Do not free individual elements
-	 * when pass-by-reference since they point to original array.
-	 */
-	pfree(elemsp);
-
-	if (j != result->nnz)
-		elog(ERROR, "correctness check failed");
-
-	/* Check elements */
-	for (int i = 0; i < result->nnz; i++)
-		CheckElement(values[i]);
-
-	PG_RETURN_POINTER(result);
-}
-
 /*
  * Get the L2 squared distance between sparse vectors
  */

src/vector.c

@@ -26,6 +26,11 @@
 #include "varatt.h"
 #endif
 
+#if PG_VERSION_NUM < 130000
+#define TYPALIGN_DOUBLE 'd'
+#define TYPALIGN_INT 'i'
+#endif
+
 #define STATE_DIMS(x) (ARR_DIMS(x)[0] - 1)
 #define CreateStateDatums(dim) palloc(sizeof(Datum) * (dim + 1))
 
@@ -155,6 +160,24 @@ CheckStateArray(ArrayType *statearray, const char *caller)
 	return (float8 *) ARR_DATA_PTR(statearray);
 }
 
+#if PG_VERSION_NUM < 120003
+static pg_noinline void
+float_overflow_error(void)
+{
+	ereport(ERROR,
+			(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
+			 errmsg("value out of range: overflow")));
+}
+
+static pg_noinline void
+float_underflow_error(void)
+{
+	ereport(ERROR,
+			(errcode(ERRCODE_NUMERIC_VALUE_OUT_OF_RANGE),
+			 errmsg("value out of range: underflow")));
+}
+#endif
+
 /*
  * Convert textual representation to internal representation
  */

test/expected/cast.out

@@ -208,62 +208,6 @@ SELECT '{1:1e-8}/1'::sparsevec::halfvec;
  [0]
 (1 row)
 
-SELECT ARRAY[1,0,2,0,3,0]::sparsevec;
-      array      
------------------
- {1:1,3:2,5:3}/6
-(1 row)
-
-SELECT ARRAY[1.0,0.0,2.0,0.0,3.0,0.0]::sparsevec;
-      array      
------------------
- {1:1,3:2,5:3}/6
-(1 row)
-
-SELECT ARRAY[1,0,2,0,3,0]::float4[]::sparsevec;
-      array      
------------------
- {1:1,3:2,5:3}/6
-(1 row)
-
-SELECT ARRAY[1,0,2,0,3,0]::float8[]::sparsevec;
-      array      
------------------
- {1:1,3:2,5:3}/6
-(1 row)
-
-SELECT ARRAY[1,0,2,0,3,0]::numeric[]::sparsevec;
-      array      
------------------
- {1:1,3:2,5:3}/6
-(1 row)
-
-SELECT '{1,0,2,0,3,0}'::real[]::sparsevec;
-    sparsevec    
------------------
- {1:1,3:2,5:3}/6
-(1 row)
-
-SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(6);
-    sparsevec    
------------------
- {1:1,3:2,5:3}/6
-(1 row)
-
-SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(5);
-ERROR:  expected 5 dimensions, not 6
-SELECT '{NULL}'::real[]::sparsevec;
-ERROR:  array must not contain nulls
-SELECT '{NaN}'::real[]::sparsevec;
-ERROR:  NaN not allowed in sparsevec
-SELECT '{Infinity}'::real[]::sparsevec;
-ERROR:  infinite value not allowed in sparsevec
-SELECT '{-Infinity}'::real[]::sparsevec;
-ERROR:  infinite value not allowed in sparsevec
-SELECT '{}'::real[]::sparsevec;
-ERROR:  sparsevec must have at least 1 dimension
-SELECT '{{1}}'::real[]::sparsevec;
-ERROR:  array must be 1-D
 SELECT array_agg(n)::vector FROM generate_series(1, 16001) n;
 ERROR:  vector cannot have more than 16000 dimensions
 SELECT array_to_vector(array_agg(n), 16001, false) FROM generate_series(1, 16001) n;

test/sql/cast.sql

@@ -58,22 +58,6 @@ SELECT '{}/16001'::sparsevec::halfvec;
 SELECT '{1:65520}/1'::sparsevec::halfvec;
 SELECT '{1:1e-8}/1'::sparsevec::halfvec;
 
-SELECT ARRAY[1,0,2,0,3,0]::sparsevec;
-SELECT ARRAY[1.0,0.0,2.0,0.0,3.0,0.0]::sparsevec;
-SELECT ARRAY[1,0,2,0,3,0]::float4[]::sparsevec;
-SELECT ARRAY[1,0,2,0,3,0]::float8[]::sparsevec;
-SELECT ARRAY[1,0,2,0,3,0]::numeric[]::sparsevec;
-
-SELECT '{1,0,2,0,3,0}'::real[]::sparsevec;
-SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(6);
-SELECT '{1,0,2,0,3,0}'::real[]::sparsevec(5);
-SELECT '{NULL}'::real[]::sparsevec;
-SELECT '{NaN}'::real[]::sparsevec;
-SELECT '{Infinity}'::real[]::sparsevec;
-SELECT '{-Infinity}'::real[]::sparsevec;
-SELECT '{}'::real[]::sparsevec;
-SELECT '{{1}}'::real[]::sparsevec;
-
 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;
 

test/t/009_ivfflat_filtering.pl

@@ -94,7 +94,8 @@ like($explain, qr/Seq Scan/);
 $explain = $node->safe_psql("postgres", qq(
 	EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' < 1 ORDER BY v <-> '$query';
 ));
-like($explain, qr/Seq Scan/);
+# TODO Do not use index
+like($explain, qr/Index Scan using idx/);
 
 # Test attribute index
 $node->safe_psql("postgres", "CREATE INDEX attribute_idx ON tst (c);");
@@ -109,6 +110,7 @@ $node->safe_psql("postgres", "CREATE INDEX partial_idx ON tst USING ivfflat (v v
 $explain = $node->safe_psql("postgres", qq(
 	EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit;
 ));
-like($explain, qr/Index Scan using partial_idx/);
+# TODO Use partial index
+like($explain, qr/Index Scan using idx/);
 
 done_testing();

test/t/017_hnsw_filtering.pl

@@ -18,13 +18,9 @@ $node->start;
 # Create table and index
 $node->safe_psql("postgres", "CREATE EXTENSION vector;");
 $node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim), c int4, t text);");
-$node->safe_psql("postgres", "CREATE TABLE cat (i int4 PRIMARY KEY, t text, b boolean);");
 $node->safe_psql("postgres",
 	"INSERT INTO tst SELECT i, ARRAY[$array_sql], i % $nc, 'test ' || i FROM generate_series(1, 10000) i;"
 );
-$node->safe_psql("postgres",
-	"INSERT INTO cat SELECT i, 'cat ' || i, i % 5 = 0 FROM generate_series(1, $nc) i;"
-);
 $node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v vector_l2_ops);");
 $node->safe_psql("postgres", "ANALYZE tst;");
 
@@ -41,7 +37,8 @@ my $c = int(rand() * $nc);
 my $explain = $node->safe_psql("postgres", qq(
 	EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit;
 ));
-like($explain, qr/Seq Scan/);
+# TODO Do not use index
+like($explain, qr/Index Scan using idx/);
 
 # Test attribute filtering with few rows removed
 $explain = $node->safe_psql("postgres", qq(
@@ -59,7 +56,8 @@ like($explain, qr/Index Scan using idx/);
 $explain = $node->safe_psql("postgres", qq(
 	EXPLAIN ANALYZE SELECT i FROM tst WHERE c < 1 ORDER BY v <-> '$query' LIMIT $limit;
 ));
-like($explain, qr/Seq Scan/);
+# TODO Do not use index
+like($explain, qr/Index Scan using idx/);
 
 # Test attribute filtering with few rows removed like
 $explain = $node->safe_psql("postgres", qq(
@@ -98,25 +96,13 @@ $explain = $node->safe_psql("postgres", qq(
 ));
 like($explain, qr/Seq Scan/);
 
-# Test join
-$explain = $node->safe_psql("postgres", qq(
-	EXPLAIN ANALYZE SELECT cat.t FROM cat INNER JOIN tst ON cat.i = tst.c ORDER BY v <-> '$query' LIMIT $limit;
-));
-like($explain, qr/Index Scan using idx/);
-
-# Test join with attribute filtering
-$explain = $node->safe_psql("postgres", qq(
-	EXPLAIN ANALYZE SELECT cat.t FROM cat INNER JOIN tst ON cat.i = tst.c WHERE cat.b = 't' ORDER BY v <-> '$query' LIMIT $limit;
-));
-like($explain, qr/Index Scan using idx/);
-
 # Test attribute index
 $node->safe_psql("postgres", "CREATE INDEX attribute_idx ON tst (c);");
 $explain = $node->safe_psql("postgres", qq(
 	EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $c ORDER BY v <-> '$query' LIMIT $limit;
 ));
-# Use attribute index
+# TODO Use attribute index
-like($explain, qr/Bitmap Index Scan on attribute_idx/);
+like($explain, qr/Index Scan using idx/);
 
 # Test partial index
 $node->safe_psql("postgres", "CREATE INDEX partial_idx ON tst USING hnsw (v vector_l2_ops) WHERE (c = $c);");

test/t/039_hnsw_cost.pl

@@ -1,60 +0,0 @@
-use strict;
-use warnings FATAL => 'all';
-use PostgreSQL::Test::Cluster;
-use PostgreSQL::Test::Utils;
-use Test::More;
-
-my @dims = (384, 1536);
-my $limit = 10;
-
-# Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
-$node->init;
-$node->start;
-
-$node->safe_psql("postgres", "CREATE EXTENSION vector;");
-
-for my $dim (@dims)
-{
-	my $array_sql = join(",", ('random()') x $dim);
-
-	# Create table and index
-	$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
-	$node->safe_psql("postgres",
-		"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 2000) i;"
-	);
-	$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v vector_l2_ops);");
-	$node->safe_psql("postgres", "ANALYZE tst;");
-
-	# Generate query
-	my @r = ();
-	for (1 .. $dim)
-	{
-		push(@r, rand());
-	}
-	my $query = "[" . join(",", @r) . "]";
-
-	my $explain = $node->safe_psql("postgres", qq(
-		EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v <-> '$query' LIMIT $limit;
-	));
-	like($explain, qr/Index Scan using idx/);
-
-	# 3x the rows are needed for distance filters
-	# since the planner uses DEFAULT_INEQ_SEL for the selectivity (should be 1)
-	# Recreate index for performance
-	$node->safe_psql("postgres", "DROP INDEX idx;");
-	$node->safe_psql("postgres",
-		"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(2001, 6000) i;"
-	);
-	$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING hnsw (v vector_l2_ops);");
-	$node->safe_psql("postgres", "ANALYZE tst;");
-
-	$explain = $node->safe_psql("postgres", qq(
-		EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' < 1 ORDER BY v <-> '$query' LIMIT $limit;
-	));
-	like($explain, qr/Index Scan using idx/);
-
-	$node->safe_psql("postgres", "DROP TABLE tst;");
-}
-
-done_testing();

test/t/040_ivfflat_cost.pl

@@ -1,50 +0,0 @@
-use strict;
-use warnings FATAL => 'all';
-use PostgreSQL::Test::Cluster;
-use PostgreSQL::Test::Utils;
-use Test::More;
-
-my @dims = (384, 1536);
-my $limit = 10;
-
-# Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
-$node->init;
-$node->start;
-
-$node->safe_psql("postgres", "CREATE EXTENSION vector;");
-
-for my $dim (@dims)
-{
-	my $array_sql = join(",", ('random()') x $dim);
-
-	# Create table and index
-	$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim));");
-	$node->safe_psql("postgres",
-		"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 5000) i;"
-	);
-	$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING ivfflat (v vector_l2_ops) WITH (lists = 5);");
-	$node->safe_psql("postgres", "ANALYZE tst;");
-
-	# Generate query
-	my @r = ();
-	for (1 .. $dim)
-	{
-		push(@r, rand());
-	}
-	my $query = "[" . join(",", @r) . "]";
-
-	my $explain = $node->safe_psql("postgres", qq(
-		EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v <-> '$query' LIMIT $limit;
-	));
-	like($explain, qr/Index Scan using idx/);
-
-	$explain = $node->safe_psql("postgres", qq(
-		EXPLAIN ANALYZE SELECT i FROM tst WHERE v <-> '$query' < 1 ORDER BY v <-> '$query' LIMIT $limit;
-	));
-	like($explain, qr/Index Scan using idx/);
-
-	$node->safe_psql("postgres", "DROP TABLE tst;");
-}
-
-done_testing();

vector.control

@@ -1,4 +1,4 @@
 comment = 'vector data type and ivfflat and hnsw access methods'
-default_version = '0.7.4'
+default_version = '0.7.3'
 module_pathname = '$libdir/vector'
 relocatable = true