Added support for inline filtering with IVFFlat

2026-07-22 12:07:34 +08:00 · 2024-10-10 17:07:47 -07:00
34 changed files with 484 additions and 1136 deletions
--- a/.github/workflows/build.yml
+++ b/.github/workflows/build.yml
@@ -8,8 +8,8 @@ jobs:
      fail-fast: false
      matrix:
        include:
-          - postgres: 18
-            os: ubuntu-24.04
+          # - postgres: 18
+          #   os: ubuntu-24.04
          - postgres: 17
            os: ubuntu-24.04
          - postgres: 16
@@ -46,10 +46,10 @@ jobs:
      fail-fast: false
      matrix:
        include:
-          - postgres: 17
-            os: macos-15
+          - postgres: 16
+            os: macos-14
          - postgres: 14
-            os: macos-13
+            os: macos-12
    steps:
      - uses: actions/checkout@v4
      - uses: ankane/setup-postgres@v1
@@ -70,13 +70,12 @@ jobs:
          tar xf $TAG.tar.gz
          mv postgres-$TAG postgres
        env:
-          TAG: ${{ matrix.postgres == 17 && 'REL_17_2' || 'REL_14_15' }}
+          TAG: ${{ matrix.postgres == 16 && 'REL_16_2' || 'REL_14_11' }}
      - run: make prove_installcheck PROVE_FLAGS="-I ./postgres/src/test/perl -I ./test/perl"
        env:
          PERL5LIB: /Users/runner/perl5/lib/perl5
-      - run: make clean && $(brew --prefix llvm@$LLVM_VERSION)/bin/scan-build --status-bugs make
+      - run: make clean && $(brew --prefix llvm@15)/bin/scan-build --status-bugs make
        env:
-          LLVM_VERSION: ${{ matrix.os == 'macos-15' && 18 || 15 }}
          PG_CFLAGS: -DUSE_ASSERT_CHECKING
  windows:
    runs-on: windows-latest
@@ -126,7 +125,7 @@ jobs:
      - uses: actions/checkout@v4
      - uses: ankane/setup-postgres-valgrind@v1
        with:
-          postgres-version: 17
+          postgres-version: 16
          check-ub: yes
      - run: make OPTFLAGS=""
      - run: sudo --preserve-env=PG_CONFIG make install
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,10 +1,10 @@
-## 0.8.0 (2024-10-30)
+## 0.8.0 (unreleased)

- Added support for iterative index scans
+- Added support for inline filtering with IVFFlat
 - Added casts for arrays to `sparsevec`
- Improved cost estimation for better index selection when filtering
- Improved performance of HNSW index scans
+- Improved cost estimation
 - Improved performance of HNSW inserts and on-disk index builds
+- Reduced memory usage for HNSW index scans
 - Dropped support for Postgres 12

 ## 0.7.4 (2024-08-05)
--- a/2
+++ b/2
@@ -1,4 +1,4 @@
-Portions Copyright (c) 1996-2025, PostgreSQL Global Development Group
+Portions Copyright (c) 1996-2024, PostgreSQL Global Development Group

 Portions Copyright (c) 1994, The Regents of the University of California

--- a/META.json
+++ b/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": "0.8.0",
+	"version": "0.7.4",
 	"maintainer": [
 		"Andrew Kane <andrew@ankane.org>"
 	],
@@ -12,7 +12,7 @@
 	"prereqs": {
 		"runtime": {
 			"requires": {
-				"PostgreSQL": "13.0.0"
+				"PostgreSQL": "12.0.0"
 			}
 		}
 	},
@@ -20,7 +20,7 @@
 		"vector": {
 			"file": "sql/vector.sql",
 			"docfile": "README.md",
-			"version": "0.8.0",
+			"version": "0.7.4",
 			"abstract": "Open-source vector similarity search for Postgres"
 		}
 	},
--- a/2
+++ b/2
@@ -1,5 +1,5 @@
 EXTENSION = vector
-EXTVERSION = 0.8.0
+EXTVERSION = 0.7.4

 MODULE_big = vector
 DATA = $(wildcard sql/*--*--*.sql)
--- a/Makefile.win
+++ b/Makefile.win
@@ -1,5 +1,5 @@
 EXTENSION = vector
-EXTVERSION = 0.8.0
+EXTVERSION = 0.7.4

 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
--- a/README.md
+++ b/README.md
@@ -17,11 +17,11 @@ Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recove

 ### Linux and Mac

-Compile and install the extension (supports Postgres 13+)
+Compile and install the extension (supports Postgres 12+)

 ```sh
 cd /tmp
-git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git
+git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
 cd pgvector
 make
 make install # may need sudo
@@ -46,12 +46,14 @@ Then use `nmake` to build:
 ```cmd
 set "PGROOT=C:\Program Files\PostgreSQL\16"
 cd %TEMP%
-git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git
+git clone --branch v0.7.4 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).
@@ -82,7 +84,7 @@ Get the nearest neighbors by L2 distance
 SELECT * FROM items ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
 ```

-Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`)
+Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`, added in 0.7.0)

 Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators

@@ -146,9 +148,9 @@ Supported distance functions are:
 - `<->` - L2 distance
 - `<#>` - (negative) inner product
 - `<=>` - cosine distance
- `<+>` - L1 distance
- `<~>` - Hamming distance (binary vectors)
- `<%>` - Jaccard distance (binary vectors)
+- `<+>` - 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

@@ -235,19 +237,19 @@ Cosine distance
 CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
 ```

-L1 distance
+L1 distance - added in 0.7.0

 ```sql
 CREATE INDEX ON items USING hnsw (embedding vector_l1_ops);
 ```

-Hamming distance
+Hamming distance - added in 0.7.0

 ```sql
 CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
 ```

-Jaccard distance
+Jaccard distance - added in 0.7.0

 ```sql
 CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
@@ -256,9 +258,9 @@ CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
 Supported types are:

 - `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions
- `bit` - up to 64,000 dimensions
- `sparsevec` - up to 1,000 non-zero elements
+- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
+- `bit` - up to 64,000 dimensions (added in 0.7.0)
+- `sparsevec` - up to 1,000 non-zero elements (added in 0.7.0)

 ### Index Options

@@ -312,7 +314,7 @@ Note: Do not set `maintenance_work_mem` so high that it exhausts the memory on t

 Like other index types, it’s faster to create an index after loading your initial data

-You can also speed up index creation by increasing the number of parallel workers (2 by default)
+Starting with 0.6.0, you can also speed up index creation by increasing the number of parallel workers (2 by default)

 ```sql
 SET max_parallel_maintenance_workers = 7; -- plus leader
@@ -322,7 +324,7 @@ For a large number of workers, you may also need to increase `max_parallel_worke

 ### Indexing Progress

-Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
+Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+

 ```sql
 SELECT phase, round(100.0 * blocks_done / nullif(blocks_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
@@ -365,7 +367,7 @@ Cosine distance
 CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
 ```

-Hamming distance
+Hamming distance - added in 0.7.0

 ```sql
 CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100);
@@ -374,8 +376,8 @@ CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 10
 Supported types are:

 - `vector` - up to 2,000 dimensions
- `halfvec` - up to 4,000 dimensions
- `bit` - up to 64,000 dimensions
+- `halfvec` - up to 4,000 dimensions (added in 0.7.0)
+- `bit` - up to 64,000 dimensions (added in 0.7.0)

 ### Query Options

@@ -408,7 +410,7 @@ For a large number of workers, you may also need to increase `max_parallel_worke

 ### Indexing Progress

-Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING)
+Check [indexing progress](https://www.postgresql.org/docs/current/progress-reporting.html#CREATE-INDEX-PROGRESS-REPORTING) with Postgres 12+

 ```sql
 SELECT phase, round(100.0 * tuples_done / nullif(tuples_total, 0), 1) AS "%" FROM pg_stat_progress_create_index;
@@ -425,128 +427,40 @@ Note: `%` is only populated during the `loading tuples` phase

 ## Filtering

-There are a few ways to index nearest neighbor queries with a `WHERE` clause.
+There are a few ways to index nearest neighbor queries with a `WHERE` clause

 ```sql
 SELECT * FROM items WHERE category_id = 123 ORDER BY embedding <-> '[3,1,2]' LIMIT 5;
 ```

-A good place to start is creating an index on the filter column. This can provide fast, exact nearest neighbor search in many cases. Postgres has a number of [index types](https://www.postgresql.org/docs/current/indexes-types.html) for this: B-tree (default), hash, GiST, SP-GiST, GIN, and BRIN.
+Create an index on one [or more](https://www.postgresql.org/docs/current/indexes-multicolumn.html) of the `WHERE` columns for exact search

 ```sql
 CREATE INDEX ON items (category_id);
 ```

-For multiple columns, consider a [multicolumn index](https://www.postgresql.org/docs/current/indexes-multicolumn.html).
+Or a composite IVFFlat index for approximate search (added in 0.8.0)

 ```sql
-CREATE INDEX ON items (location_id, category_id);
+CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops, category_id) WITH (lists = 100);
 ```

-Exact indexes work well for conditions that match a low percentage of rows. Otherwise, [approximate indexes](#indexing) can work better.
-
-```sql
-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, 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;
-```
-
-If filtering by only a few distinct values, consider [partial indexing](https://www.postgresql.org/docs/current/indexes-partial.html).
+Or a [partial index](https://www.postgresql.org/docs/current/indexes-partial.html) on the vector column for approximate search

 ```sql
 CREATE INDEX ON items USING hnsw (embedding vector_l2_ops) WHERE (category_id = 123);
 ```

-If filtering by many different values, consider [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html).
+Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html) for approximate search on many different values of the `WHERE` columns

 ```sql
 CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
 ```

-## Iterative Index Scans
-
-*Added in 0.8.0*
-
-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`).
-
-Iterative scans can use strict or relaxed ordering.
-
-Strict ensures results are in the exact order by distance
-
-```sql
-SET hnsw.iterative_scan = strict_order;
-```
-
-Relaxed allows results to be slightly out of order by distance, but provides better recall
-
-```sql
-SET hnsw.iterative_scan = relaxed_order;
-# or
-SET ivfflat.iterative_scan = relaxed_order;
-```
-
-With relaxed ordering, you can use a [materialized CTE](https://www.postgresql.org/docs/current/queries-with.html#QUERIES-WITH-CTE-MATERIALIZATION) to get strict ordering
-
-```sql
-WITH relaxed_results AS MATERIALIZED (
-    SELECT id, embedding <-> '[1,2,3]' AS distance FROM items WHERE category_id = 123 ORDER BY distance LIMIT 5
-) SELECT * FROM relaxed_results ORDER BY distance;
-```
-
-For queries that filter by distance, use a materialized CTE and place the distance filter outside of it for best performance (due to the [current behavior](https://www.postgresql.org/message-id/flat/CAOdR5yGUoMQ6j7M5hNUXrySzaqZVGf_Ne%2B8fwZMRKTFxU1nbJg%40mail.gmail.com) of the Postgres executor)
-
-```sql
-WITH nearest_results AS MATERIALIZED (
-    SELECT id, embedding <-> '[1,2,3]' AS distance FROM items ORDER BY distance LIMIT 5
-) SELECT * FROM nearest_results WHERE distance < 5 ORDER BY distance;
-```
-
-Note: Place any other filters inside the CTE
-
-### Iterative Scan Options
-
-Since scanning a large portion of an approximate index is expensive, there are options to control when a scan ends.
-
-#### HNSW
-
-Specify the max number of tuples to visit (20,000 by default)
-
-```sql
-SET hnsw.max_scan_tuples = 20000;
-```
-
-Note: This is approximate and does not affect the initial scan
-
-Specify the max amount of memory to use, as a multiple of `work_mem` (1 by default)
-
-```sql
-SET hnsw.scan_mem_multiplier = 2;
-```
-
-Note: Try increasing this if increasing `hnsw.max_scan_tuples` does not improve recall
-
-#### IVFFlat
-
-Specify the max number of probes
-
-```sql
-SET ivfflat.max_probes = 100;
-```
-
-Note: If this is lower than `ivfflat.probes`, `ivfflat.probes` will be used
-
 ## Half-Precision Vectors

+*Added in 0.7.0*
+
 Use the `halfvec` type to store half-precision vectors

 ```sql
@@ -555,6 +469,8 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));

 ## Half-Precision Indexing

+*Added in 0.7.0*
+
 Index vectors at half precision for smaller indexes

 ```sql
@@ -576,16 +492,24 @@ CREATE TABLE items (id bigserial PRIMARY KEY, embedding bit(3));
 INSERT INTO items (embedding) VALUES ('000'), ('111');
 ```

-Get the nearest neighbors by Hamming distance
+Get the nearest neighbors by Hamming distance (added in 0.7.0)

 ```sql
 SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
 ```

+Or (before 0.7.0)
+
+```sql
+SELECT * FROM items ORDER BY bit_count(embedding # '101') LIMIT 5;
+```
+
 Also supports Jaccard distance (`<%>`)

 ## Binary Quantization

+*Added in 0.7.0*
+
 Use expression indexing for binary quantization

 ```sql
@@ -608,6 +532,8 @@ SELECT * FROM (

 ## Sparse Vectors

+*Added in 0.7.0*
+
 Use the `sparsevec` type to store sparse vectors

 ```sql
@@ -641,6 +567,8 @@ You can use [Reciprocal Rank Fusion](https://github.com/pgvector/pgvector-python

 ## Indexing Subvectors

+*Added in 0.7.0*
+
 Use expression indexing to index subvectors

 ```sql
@@ -783,12 +711,8 @@ C | [pgvector-c](https://github.com/pgvector/pgvector-c)
 C++ | [pgvector-cpp](https://github.com/pgvector/pgvector-cpp)
 C#, F#, Visual Basic | [pgvector-dotnet](https://github.com/pgvector/pgvector-dotnet)
 Crystal | [pgvector-crystal](https://github.com/pgvector/pgvector-crystal)
-D | [pgvector-d](https://github.com/pgvector/pgvector-d)
 Dart | [pgvector-dart](https://github.com/pgvector/pgvector-dart)
 Elixir | [pgvector-elixir](https://github.com/pgvector/pgvector-elixir)
-Erlang | [pgvector-erlang](https://github.com/pgvector/pgvector-erlang)
-Fortran | [pgvector-fortran](https://github.com/pgvector/pgvector-fortran)
-Gleam | [pgvector-gleam](https://github.com/pgvector/pgvector-gleam)
 Go | [pgvector-go](https://github.com/pgvector/pgvector-go)
 Haskell | [pgvector-haskell](https://github.com/pgvector/pgvector-haskell)
 Java, Kotlin, Groovy, Scala | [pgvector-java](https://github.com/pgvector/pgvector-java)
@@ -802,7 +726,6 @@ Perl | [pgvector-perl](https://github.com/pgvector/pgvector-perl)
 PHP | [pgvector-php](https://github.com/pgvector/pgvector-php)
 Python | [pgvector-python](https://github.com/pgvector/pgvector-python)
 R | [pgvector-r](https://github.com/pgvector/pgvector-r)
-Raku | [pgvector-raku](https://github.com/pgvector/pgvector-raku)
 Ruby | [pgvector-ruby](https://github.com/pgvector/pgvector-ruby), [Neighbor](https://github.com/ankane/neighbor)
 Rust | [pgvector-rust](https://github.com/pgvector/pgvector-rust)
 Swift | [pgvector-swift](https://github.com/pgvector/pgvector-swift)
@@ -924,7 +847,7 @@ ALTER TABLE items ALTER COLUMN embedding SET STORAGE PLAIN;

 #### Why are there less results for a query after adding an HNSW index?

-Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`), which is 40 by default. There may be even less results due to dead tuples or filtering conditions in the query. Enabling [iterative index scans](#iterative-index-scans) can help address this.
+Results are limited by the size of the dynamic candidate list (`hnsw.ef_search`). There may be even less results due to dead tuples or filtering conditions in the query. We recommend setting `hnsw.ef_search` to at least twice the `LIMIT` of the query. If you need more than 500 results, use an IVFFlat index instead.

 Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).

@@ -936,7 +859,7 @@ The index was likely created with too little data for the number of lists. Drop
 DROP INDEX index_name;
 ```

-Results can also be limited by the number of probes (`ivfflat.probes`). Enabling [iterative index scans](#iterative-index-scans) can address this.
+Results can also be limited by the number of probes (`ivfflat.probes`).

 Also, note that `NULL` vectors are not indexed (as well as zero vectors for cosine distance).

@@ -1103,13 +1026,7 @@ Note: Replace `17` with your Postgres server version

 ### Missing SDK

-If compilation fails and the output includes `warning: no such sysroot directory` on Mac, your Postgres installation points to a path that no longer exists.
-
-```sh
-pg_config --cppflags
-```
-
-Reinstall Postgres to fix this.
+If compilation fails and the output includes `warning: no such sysroot directory` on Mac, reinstall Xcode Command Line Tools.

 ### Portability

@@ -1127,14 +1044,6 @@ make OPTFLAGS=""

 If compilation fails with `Cannot open include file: 'postgres.h': No such file or directory`, make sure `PGROOT` is correct.

-### Mismatched Architecture
-
-If compilation fails with `error C2196: case value '4' already used`, make sure `vcvars64.bat` was called. Then run `nmake /F Makefile.win clean` and re-run the installation instructions.
-
-### Missing Symbol
-
-If linking fails with `unresolved external symbol float_to_shortest_decimal_bufn` with Postgres 17.0-17.2, upgrade to Postgres 17.3+.
-
 ### Permissions

 If installation fails with `Access is denied`, re-run the installation instructions as an administrator.
@@ -1154,17 +1063,11 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
 You can also build the image manually:

 ```sh
-git clone --branch v0.8.0 https://github.com/pgvector/pgvector.git
+git clone --branch v0.7.4 https://github.com/pgvector/pgvector.git
 cd pgvector
 docker build --pull --build-arg PG_MAJOR=17 -t myuser/pgvector .
 ```

-If you increase `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
-
-```sh
-docker run --shm-size=1g ...
-```
-
 ### Homebrew

 With Homebrew Postgres, you can use:
@@ -1210,7 +1113,7 @@ Note: Replace `17` with your Postgres server version
 Install the FreeBSD package with:

 ```sh
-pkg install postgresql16-pgvector
+pkg install postgresql15-pgvector
 ```

 or the port with:
@@ -1252,6 +1155,36 @@ You can check the version in the current database with:
 SELECT extversion FROM pg_extension WHERE extname = 'vector';
 ```

+## Upgrade Notes
+
+### 0.6.0
+
+#### Postgres 12
+
+If upgrading with Postgres 12, remove this line from `sql/vector--0.5.1--0.6.0.sql`:
+
+```sql
+ALTER TYPE vector SET (STORAGE = external);
+```
+
+Then run `make install` and `ALTER EXTENSION vector UPDATE;`.
+
+#### Docker
+
+The Docker image is now published in the `pgvector` org, and there are tags for each supported version of Postgres (rather than a `latest` tag).
+
+```sh
+docker pull pgvector/pgvector:pg16
+# or
+docker pull pgvector/pgvector:0.6.0-pg16
+```
+
+Also, if you’ve increased `maintenance_work_mem`, make sure `--shm-size` is at least that size to avoid an error with parallel HNSW index builds.
+
+```sh
+docker run --shm-size=1g ...
+```
+
 ## Thanks

 Thanks to:
--- a/sql/vector--0.7.4--0.8.0.sql
+++ b/sql/vector--0.7.4--0.8.0.sql
@@ -24,3 +24,5 @@ CREATE CAST (double precision[] AS sparsevec)

 CREATE CAST (numeric[] AS sparsevec)
 	WITH FUNCTION array_to_sparsevec(numeric[], integer, boolean) AS ASSIGNMENT;
+
+-- TODO add ivfflat attributes
--- a/sql/vector.sql
+++ b/sql/vector.sql
@@ -916,3 +916,13 @@ CREATE OPERATOR CLASS sparsevec_l1_ops
 	OPERATOR 1 <+> (sparsevec, sparsevec) FOR ORDER BY float_ops,
 	FUNCTION 1 l1_distance(sparsevec, sparsevec),
 	FUNCTION 3 hnsw_sparsevec_support(internal);
+
+-- ivfflat attributes
+
+CREATE OPERATOR CLASS vector_integer_ops
+	DEFAULT FOR TYPE integer USING ivfflat AS
+	OPERATOR 2 < ,
+	OPERATOR 3 <= ,
+	OPERATOR 4 = ,
+	OPERATOR 5 >= ,
+	OPERATOR 6 > ;
--- a/src/bitutils.h
+++ b/src/bitutils.h
@@ -8,9 +8,6 @@
 #error "Requires PostgreSQL 13+"
 #endif

-/* Check architecture in first header */
-StaticAssertDecl(sizeof(Datum) == SIZEOF_DATUM, "Architecture mismatch");
-
 extern uint64 (*BitHammingDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 distance);
 extern double (*BitJaccardDistance) (uint32 bytes, unsigned char *ax, unsigned char *bx, uint64 ab, uint64 aa, uint64 bb);

--- a/src/hnsw.c
+++ b/src/hnsw.c
@@ -18,17 +18,7 @@
 #define MarkGUCPrefixReserved(x) EmitWarningsOnPlaceholders(x)
 #endif

-static const struct config_enum_entry hnsw_iterative_scan_options[] = {
-	{"off", HNSW_ITERATIVE_SCAN_OFF, false},
-	{"relaxed_order", HNSW_ITERATIVE_SCAN_RELAXED, false},
-	{"strict_order", HNSW_ITERATIVE_SCAN_STRICT, false},
-	{NULL, 0, false}
-};
-
 int			hnsw_ef_search;
-int			hnsw_iterative_scan;
-int			hnsw_max_scan_tuples;
-double		hnsw_scan_mem_multiplier;
 int			hnsw_lock_tranche_id;
 static relopt_kind hnsw_relopt_kind;

@@ -79,20 +69,6 @@ HnswInit(void)
 							"Valid range is 1..1000.", &hnsw_ef_search,
 							HNSW_DEFAULT_EF_SEARCH, HNSW_MIN_EF_SEARCH, HNSW_MAX_EF_SEARCH, PGC_USERSET, 0, NULL, NULL, NULL);

-	DefineCustomEnumVariable("hnsw.iterative_scan", "Sets the mode for iterative scans",
-							 NULL, &hnsw_iterative_scan,
-							 HNSW_ITERATIVE_SCAN_OFF, hnsw_iterative_scan_options, PGC_USERSET, 0, NULL, NULL, NULL);
-
-	/* This is approximate and does not affect the initial scan */
-	DefineCustomIntVariable("hnsw.max_scan_tuples", "Sets the max number of tuples to visit for iterative scans",
-							NULL, &hnsw_max_scan_tuples,
-							20000, 1, INT_MAX, PGC_USERSET, 0, NULL, NULL, NULL);
-
-	/* Same range as hash_mem_multiplier */
-	DefineCustomRealVariable("hnsw.scan_mem_multiplier", "Sets the multiple of work_mem to use for iterative scans",
-							 NULL, &hnsw_scan_mem_multiplier,
-							 1, 1, 1000, PGC_USERSET, 0, NULL, NULL, NULL);
-
 	MarkGUCPrefixReserved("hnsw");
 }

@@ -137,10 +113,6 @@ hnswcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
 		*indexSelectivity = 0;
 		*indexCorrelation = 0;
 		*indexPages = 0;
-#if PG_VERSION_NUM >= 180000
-		/* See "On disable_cost" thread on pgsql-hackers */
-		path->path.disabled_nodes = 2;
-#endif
 		return;
 	}

--- a/src/hnsw.h
+++ b/src/hnsw.h
@@ -109,24 +109,14 @@

 /* Variables */
 extern int	hnsw_ef_search;
-extern int	hnsw_iterative_scan;
-extern int	hnsw_max_scan_tuples;
-extern double hnsw_scan_mem_multiplier;
 extern int	hnsw_lock_tranche_id;

-typedef enum HnswIterativeScanMode
-{
-	HNSW_ITERATIVE_SCAN_OFF,
-	HNSW_ITERATIVE_SCAN_RELAXED,
-	HNSW_ITERATIVE_SCAN_STRICT
-}			HnswIterativeScanMode;
-
 typedef struct HnswElementData HnswElementData;
 typedef struct HnswNeighborArray HnswNeighborArray;

 #define HnswPtrDeclare(type, relptrtype, ptrtype) \
 	relptr_declare(type, relptrtype); \
-	typedef union { type *ptr; relptrtype relptr; } ptrtype
+	typedef union { type *ptr; relptrtype relptr; } ptrtype;

 /* Pointers that can be absolute or relative */
 /* Use char for DatumPtr so works with Pointer */
@@ -142,7 +132,6 @@ struct HnswElementData
 	uint8		heaptidsLength;
 	uint8		level;
 	uint8		deleted;
-	uint8		version;
 	uint32		hash;
 	HnswNeighborsPtr neighbors;
 	BlockNumber blkno;
@@ -330,10 +319,10 @@ typedef struct HnswElementTupleData
 	uint8		type;
 	uint8		level;
 	uint8		deleted;
-	uint8		version;
+	uint8		unused;
 	ItemPointerData heaptids[HNSW_HEAPTIDS];
 	ItemPointerData neighbortid;
-	uint16		unused;
+	uint16		unused2;
 	Vector		data;
 }			HnswElementTupleData;

@@ -342,7 +331,7 @@ typedef HnswElementTupleData * HnswElementTuple;
 typedef struct HnswNeighborTupleData
 {
 	uint8		type;
-	uint8		version;
+	uint8		unused;
 	uint16		count;
 	ItemPointerData indextids[FLEXIBLE_ARRAY_MEMBER];
 }			HnswNeighborTupleData;
@@ -367,13 +356,6 @@ typedef struct HnswScanOpaqueData
 	const		HnswTypeInfo *typeInfo;
 	bool		first;
 	List	   *w;
-	visited_hash v;
-	pairingheap *discarded;
-	HnswQuery	q;
-	int			m;
-	int64		tuples;
-	double		previousDistance;
-	Size		maxMemory;
 	MemoryContext tmpCtx;

 	/* Support functions */
@@ -417,7 +399,7 @@ bool		HnswCheckNorm(HnswSupport * support, Datum value);
 Buffer		HnswNewBuffer(Relation index, ForkNumber forkNum);
 void		HnswInitPage(Buffer buf, Page page);
 void		HnswInit(void);
-List	   *HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples);
+List	   *HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement);
 HnswElement HnswGetEntryPoint(Relation index);
 void		HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint);
 void	   *HnswAlloc(HnswAllocator * allocator, Size size);
--- a/src/hnswinsert.c
+++ b/src/hnswinsert.c
@@ -36,7 +36,7 @@ GetInsertPage(Relation index)
 * Check for a free offset
 */
 static bool
-HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size etupSize, Size ntupSize, Buffer *nbuf, Page *npage, OffsetNumber *freeOffno, OffsetNumber *freeNeighborOffno, BlockNumber *newInsertPage, uint8 *tupleVersion)
+HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size etupSize, Size ntupSize, Buffer *nbuf, Page *npage, OffsetNumber *freeOffno, OffsetNumber *freeNeighborOffno, BlockNumber *newInsertPage)
 {
 	OffsetNumber offno;
 	OffsetNumber maxoffno = PageGetMaxOffsetNumber(page);
@@ -98,7 +98,6 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
 			{
 				*freeOffno = offno;
 				*freeNeighborOffno = neighborOffno;
-				*tupleVersion = etup->version;
 				return true;
 			}
 			else if (*nbuf != buf)
@@ -154,7 +153,6 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
 	OffsetNumber freeOffno = InvalidOffsetNumber;
 	OffsetNumber freeNeighborOffno = InvalidOffsetNumber;
 	BlockNumber newInsertPage = InvalidBlockNumber;
-	uint8		tupleVersion;
 	char	   *base = NULL;

 	/* Calculate sizes */
@@ -204,7 +202,7 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
 		}

 		/* Next, try space from a deleted element */
-		if (HnswFreeOffset(index, buf, page, e, etupSize, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage, &tupleVersion))
+		if (HnswFreeOffset(index, buf, page, e, etupSize, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage))
 		{
 			if (nbuf != buf)
 			{
@@ -214,10 +212,6 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
 					npage = GenericXLogRegisterBuffer(state, nbuf, 0);
 			}

-			/* Set tuple version */
-			etup->version = tupleVersion;
-			ntup->version = tupleVersion;
-
 			break;
 		}

--- a/src/hnswscan.c
+++ b/src/hnswscan.c
@@ -5,7 +5,6 @@
 #include "pgstat.h"
 #include "storage/bufmgr.h"
 #include "storage/lmgr.h"
-#include "utils/float.h"
 #include "utils/memutils.h"

 /*
@@ -22,57 +21,25 @@ GetScanItems(IndexScanDesc scan, Datum value)
 	int			m;
 	HnswElement entryPoint;
 	char	   *base = NULL;
-	HnswQuery  *q = &so->q;
+	HnswQuery	q;
+
+	q.value = value;

 	/* Get m and entry point */
 	HnswGetMetaPageInfo(index, &m, &entryPoint);

-	q->value = value;
-	so->m = m;
-
 	if (entryPoint == NULL)
 		return NIL;

-	ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, support, false));
+	ep = list_make1(HnswEntryCandidate(base, entryPoint, &q, index, support, false));

 	for (int lc = entryPoint->level; lc >= 1; lc--)
 	{
-		w = HnswSearchLayer(base, q, ep, 1, lc, index, support, m, false, NULL, NULL, NULL, true, NULL);
+		w = HnswSearchLayer(base, &q, ep, 1, lc, index, support, m, false, NULL);
 		ep = w;
 	}

-	return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, support, m, false, NULL, &so->v, hnsw_iterative_scan != HNSW_ITERATIVE_SCAN_OFF ? &so->discarded : NULL, true, &so->tuples);
-}
-
-/*
- * Resume scan at ground level with discarded candidates
- */
-static List *
-ResumeScanItems(IndexScanDesc scan)
-{
-	HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
-	Relation	index = scan->indexRelation;
-	List	   *ep = NIL;
-	char	   *base = NULL;
-	int			batch_size = hnsw_ef_search;
-
-	if (pairingheap_is_empty(so->discarded))
-		return NIL;
-
-	/* Get next batch of candidates */
-	for (int i = 0; i < batch_size; i++)
-	{
-		HnswSearchCandidate *sc;
-
-		if (pairingheap_is_empty(so->discarded))
-			break;
-
-		sc = HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded));
-
-		ep = lappend(ep, sc);
-	}
-
-	return HnswSearchLayer(base, &so->q, ep, batch_size, 0, index, &so->support, so->m, false, NULL, &so->v, &so->discarded, false, &so->tuples);
+	return HnswSearchLayer(base, &q, ep, hnsw_ef_search, 0, index, support, m, false, NULL);
 }

 /*
@@ -102,17 +69,6 @@ GetScanValue(IndexScanDesc scan)
 	return value;
 }

-#if defined(HNSW_MEMORY)
-/*
- * Show memory usage
- */
-static void
-ShowMemoryUsage(HnswScanOpaque so)
-{
-	elog(INFO, "memory: %zu KB, tuples: " INT64_FORMAT, MemoryContextMemAllocated(so->tmpCtx, false) / 1024, so->tuples);
-}
-#endif
-
 /*
 * Prepare for an index scan
 */
@@ -121,29 +77,19 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
 {
 	IndexScanDesc scan;
 	HnswScanOpaque so;
-	double		maxMemory;

 	scan = RelationGetIndexScan(index, nkeys, norderbys);

 	so = (HnswScanOpaque) palloc(sizeof(HnswScanOpaqueData));
 	so->typeInfo = HnswGetTypeInfo(index);
+	so->first = true;
+	so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
+									   "Hnsw scan temporary context",
+									   ALLOCSET_DEFAULT_SIZES);

 	/* Set support functions */
 	HnswInitSupport(&so->support, index);

-	/*
-	 * Use a lower max allocation size than default to allow scanning more
-	 * tuples for iterative search before exceeding work_mem
-	 */
-	so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
-									   "Hnsw scan temporary context",
-									   0, 8 * 1024, 256 * 1024);
-
-	/* Calculate max memory */
-	/* Add 256 extra bytes to fill last block when close */
-	maxMemory = (double) work_mem * hnsw_scan_mem_multiplier * 1024.0 + 256;
-	so->maxMemory = Min(maxMemory, (double) SIZE_MAX);
-
 	scan->opaque = so;

 	return scan;
@@ -158,11 +104,6 @@ hnswrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int no
 	HnswScanOpaque so = (HnswScanOpaque) scan->opaque;

 	so->first = true;
-	/* v and discarded are allocated in tmpCtx */
-	so->v.tids = NULL;
-	so->discarded = NULL;
-	so->tuples = 0;
-	so->previousDistance = -get_float8_infinity();
 	MemoryContextReset(so->tmpCtx);

 	if (keys && scan->numberOfKeys > 0)
@@ -220,89 +161,26 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
 		so->first = false;

 #if defined(HNSW_MEMORY)
-		ShowMemoryUsage(so);
+		elog(INFO, "memory: %zu KB", MemoryContextMemAllocated(so->tmpCtx, false) / 1024);
 #endif
 	}

-	for (;;)
+	while (list_length(so->w) > 0)
 	{
 		char	   *base = NULL;
-		HnswSearchCandidate *sc;
-		HnswElement element;
+		HnswSearchCandidate *sc = llast(so->w);
+		HnswElement element = HnswPtrAccess(base, sc->element);
 		ItemPointer heaptid;

-		if (list_length(so->w) == 0)
-		{
-			if (hnsw_iterative_scan == HNSW_ITERATIVE_SCAN_OFF)
-				break;
-
-			/* Empty index */
-			if (so->discarded == NULL)
-				break;
-
-			/* Reached max number of tuples or memory limit */
-			if (so->tuples >= hnsw_max_scan_tuples || MemoryContextMemAllocated(so->tmpCtx, false) > so->maxMemory)
-			{
-				if (pairingheap_is_empty(so->discarded))
-					break;
-
-				/* Return remaining tuples */
-				so->w = lappend(so->w, HnswGetSearchCandidate(w_node, pairingheap_remove_first(so->discarded)));
-			}
-			else
-			{
-				/*
-				 * Locking ensures when neighbors are read, the elements they
-				 * reference will not be deleted (and replaced) during the
-				 * iteration.
-				 *
-				 * Elements loaded into memory on previous iterations may have
-				 * been deleted (and replaced), so when reading neighbors, the
-				 * element version must be checked.
-				 */
-				LockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
-
-				so->w = ResumeScanItems(scan);
-
-				UnlockPage(scan->indexRelation, HNSW_SCAN_LOCK, ShareLock);
-
-#if defined(HNSW_MEMORY)
-				ShowMemoryUsage(so);
-#endif
-			}
-
-			if (list_length(so->w) == 0)
-				break;
-		}
-
-		sc = llast(so->w);
-		element = HnswPtrAccess(base, sc->element);
-
 		/* Move to next element if no valid heap TIDs */
 		if (element->heaptidsLength == 0)
 		{
 			so->w = list_delete_last(so->w);
-
-			/* Mark memory as free for next iteration */
-			if (hnsw_iterative_scan != HNSW_ITERATIVE_SCAN_OFF)
-			{
-				pfree(element);
-				pfree(sc);
-			}
-
 			continue;
 		}

 		heaptid = &element->heaptids[--element->heaptidsLength];

-		if (hnsw_iterative_scan == HNSW_ITERATIVE_SCAN_STRICT)
-		{
-			if (sc->distance < so->previousDistance)
-				continue;
-
-			so->previousDistance = sc->distance;
-		}
-
 		MemoryContextSwitchTo(oldCtx);

 		scan->xs_heaptid = *heaptid;
--- a/src/hnswutils.c
+++ b/src/hnswutils.c
@@ -251,8 +251,6 @@ HnswInitElement(char *base, ItemPointer heaptid, int m, double ml, int maxLevel,

 	element->level = level;
 	element->deleted = 0;
-	/* Start at one to make it easier to find issues */
-	element->version = 1;

 	HnswInitNeighbors(base, element, m, allocator);

@@ -432,7 +430,6 @@ HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element)
 	etup->type = HNSW_ELEMENT_TUPLE_TYPE;
 	etup->level = element->level;
 	etup->deleted = 0;
-	etup->version = element->version;
 	for (int i = 0; i < HNSW_HEAPTIDS; i++)
 	{
 		if (i < element->heaptidsLength)
@@ -475,7 +472,6 @@ HnswSetNeighborTuple(char *base, HnswNeighborTuple ntup, HnswElement e, int m)
 	}

 	ntup->count = idx;
-	ntup->version = e->version;
 }

 /*
@@ -486,7 +482,6 @@ HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHe
 {
 	element->level = etup->level;
 	element->deleted = etup->deleted;
-	element->version = etup->version;
 	element->neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
 	element->neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
 	element->heaptidsLength = 0;
@@ -581,34 +576,21 @@ GetElementDistance(char *base, HnswElement element, HnswQuery * q, HnswSupport *
 	return HnswGetDistance(q->value, value, support);
 }

-/*
- * Allocate a search candidate
- */
-static HnswSearchCandidate *
-HnswInitSearchCandidate(char *base, HnswElement element, double distance)
-{
-	HnswSearchCandidate *sc = palloc(sizeof(HnswSearchCandidate));
-
-	HnswPtrStore(base, sc->element, element);
-	sc->distance = distance;
-	return sc;
-}
-
 /*
 * Create a candidate for the entry point
 */
 HnswSearchCandidate *
 HnswEntryCandidate(char *base, HnswElement entryPoint, HnswQuery * q, Relation index, HnswSupport * support, bool loadVec)
 {
+	HnswSearchCandidate *sc = palloc(sizeof(HnswSearchCandidate));
 	bool		inMemory = index == NULL;
-	double		distance;

+	HnswPtrStore(base, sc->element, entryPoint);
 	if (inMemory)
-		distance = GetElementDistance(base, entryPoint, q, support);
+		sc->distance = GetElementDistance(base, entryPoint, q, support);
 	else
-		HnswLoadElement(entryPoint, &distance, q, index, support, loadVec, NULL);
-
-	return HnswInitSearchCandidate(base, entryPoint, distance);
+		HnswLoadElement(entryPoint, &sc->distance, q, index, support, loadVec, NULL);
+	return sc;
 }

 /*
@@ -626,21 +608,6 @@ CompareNearestCandidates(const pairingheap_node *a, const pairingheap_node *b, v
 	return 0;
 }

-/*
- * Compare discarded candidate distances
- */
-static int
-CompareNearestDiscardedCandidates(const pairingheap_node *a, const pairingheap_node *b, void *arg)
-{
-	if (HnswGetSearchCandidateConst(w_node, a)->distance < HnswGetSearchCandidateConst(w_node, b)->distance)
-		return 1;
-
-	if (HnswGetSearchCandidateConst(w_node, a)->distance > HnswGetSearchCandidateConst(w_node, b)->distance)
-		return -1;
-
-	return 0;
-}
-
 /*
 * Compare candidate distances
 */
@@ -761,11 +728,8 @@ HnswLoadNeighborTids(HnswElement element, ItemPointerData *indextids, Relation i

 	ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, element->neighborOffno));

-	/*
-	 * Ensure the neighbor tuple has not been deleted or replaced between
-	 * index scan iterations
-	 */
-	if (ntup->version != element->version || ntup->count != (element->level + 2) * m)
+	/* Ensure expected neighbors */
+	if (ntup->count != (element->level + 2) * m)
 	{
 		UnlockReleaseBuffer(buf);
 		return false;
@@ -811,13 +775,13 @@ HnswLoadUnvisitedFromDisk(HnswElement element, HnswUnvisited * unvisited, int *u
 * Algorithm 2 from paper
 */
 List *
-HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement, visited_hash * v, pairingheap **discarded, bool initVisited, int64 *tuples)
+HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation index, HnswSupport * support, int m, bool inserting, HnswElement skipElement)
 {
 	List	   *w = NIL;
 	pairingheap *C = pairingheap_allocate(CompareNearestCandidates, NULL);
 	pairingheap *W = pairingheap_allocate(CompareFurthestCandidates, NULL);
 	int			wlen = 0;
-	visited_hash vh;
+	visited_hash v;
 	ListCell   *lc2;
 	HnswNeighborArray *localNeighborhood = NULL;
 	Size		neighborhoodSize = 0;
@@ -826,19 +790,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
 	int			unvisitedLength;
 	bool		inMemory = index == NULL;

-	if (v == NULL)
-	{
-		v = &vh;
-		initVisited = true;
-	}
-
-	if (initVisited)
-	{
-		InitVisited(base, v, inMemory, ef, m);
-
-		if (discarded != NULL)
-			*discarded = pairingheap_allocate(CompareNearestDiscardedCandidates, NULL);
-	}
+	InitVisited(base, &v, inMemory, ef, m);

 	/* Create local memory for neighborhood if needed */
 	if (inMemory)
@@ -853,14 +805,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
 		HnswSearchCandidate *sc = (HnswSearchCandidate *) lfirst(lc2);
 		bool		found;

-		if (initVisited)
-		{
-			AddToVisited(base, v, sc->element, inMemory, &found);
-
-			/* OK to count elements instead of tuples */
-			if (tuples != NULL)
-				(*tuples)++;
-		}
+		AddToVisited(base, &v, sc->element, inMemory, &found);

 		pairingheap_add(C, &sc->c_node);
 		pairingheap_add(W, &sc->w_node);
@@ -886,13 +831,9 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in
 		cElement = HnswPtrAccess(base, c->element);

 		if (inMemory)
-			HnswLoadUnvisitedFromMemory(base, cElement, unvisited, &unvisitedLength, v, lc, localNeighborhood, neighborhoodSize);
+			HnswLoadUnvisitedFromMemory(base, cElement, unvisited, &unvisitedLength, &v, lc, localNeighborhood, neighborhoodSize);
 		else
-			HnswLoadUnvisitedFromDisk(cElement, unvisited, &unvisitedLength, v, index, m, lm, lc);
-
-		/* OK to count elements instead of tuples */
-		if (tuples != NULL)
-			(*tuples) += unvisitedLength;
+			HnswLoadUnvisitedFromDisk(cElement, unvisited, &unvisitedLength, &v, index, m, lm, lc);

 		for (int i = 0; i < unvisitedLength; i++)
 		{
@@ -916,30 +857,25 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in

 				/* Avoid any allocations if not adding */
 				eElement = NULL;
-				HnswLoadElementImpl(blkno, offno, &eDistance, q, index, support, inserting, alwaysAdd || discarded != NULL ? NULL : &f->distance, &eElement);
+				HnswLoadElementImpl(blkno, offno, &eDistance, q, index, support, inserting, alwaysAdd ? NULL : &f->distance, &eElement);

 				if (eElement == NULL)
 					continue;
 			}

-			if (eElement == NULL || !(eDistance < f->distance || alwaysAdd))
-			{
-				if (discarded != NULL)
-				{
-					/* Create a new candidate */
-					e = HnswInitSearchCandidate(base, eElement, eDistance);
-					pairingheap_add(*discarded, &e->w_node);
-				}
-
+			if (!(eDistance < f->distance || alwaysAdd))
 				continue;
-			}
+
+			Assert(!eElement->deleted);

 			/* Make robust to issues */
 			if (eElement->level < lc)
 				continue;

 			/* Create a new candidate */
-			e = HnswInitSearchCandidate(base, eElement, eDistance);
+			e = palloc(sizeof(HnswSearchCandidate));
+			HnswPtrStore(base, e->element, eElement);
+			e->distance = eDistance;
 			pairingheap_add(C, &e->c_node);
 			pairingheap_add(W, &e->w_node);

@@ -954,12 +890,7 @@ HnswSearchLayer(char *base, HnswQuery * q, List *ep, int ef, int lc, Relation in

 				/* No need to decrement wlen */
 				if (wlen > ef)
-				{
-					HnswSearchCandidate *d = HnswGetSearchCandidate(w_node, pairingheap_remove_first(W));
-
-					if (discarded != NULL)
-						pairingheap_add(*discarded, &d->w_node);
-				}
+					pairingheap_remove_first(W);
 			}
 		}
 	}
@@ -1294,7 +1225,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
 	/* 1st phase: greedy search to insert level */
 	for (int lc = entryLevel; lc >= level + 1; lc--)
 	{
-		w = HnswSearchLayer(base, &q, ep, 1, lc, index, support, m, true, skipElement, NULL, NULL, true, NULL);
+		w = HnswSearchLayer(base, &q, ep, 1, lc, index, support, m, true, skipElement);
 		ep = w;
 	}

@@ -1313,7 +1244,7 @@ HnswFindElementNeighbors(char *base, HnswElement element, HnswElement entryPoint
 		List	   *lw = NIL;
 		ListCell   *lc2;

-		w = HnswSearchLayer(base, &q, ep, efConstruction, lc, index, support, m, true, skipElement, NULL, NULL, true, NULL);
+		w = HnswSearchLayer(base, &q, ep, efConstruction, lc, index, support, m, true, skipElement);

 		/* Convert search candidates to candidates */
 		foreach(lc2, w)
@@ -1393,7 +1324,7 @@ hnsw_halfvec_support(PG_FUNCTION_ARGS)
 	};

 	PG_RETURN_POINTER(&typeInfo);
-}
+};

 FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_bit_support);
 Datum
@@ -1406,7 +1337,7 @@ hnsw_bit_support(PG_FUNCTION_ARGS)
 	};

 	PG_RETURN_POINTER(&typeInfo);
-}
+};

 FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnsw_sparsevec_support);
 Datum
@@ -1419,4 +1350,4 @@ hnsw_sparsevec_support(PG_FUNCTION_ARGS)
 	};

 	PG_RETURN_POINTER(&typeInfo);
-}
+};
--- a/src/hnswvacuum.c
+++ b/src/hnswvacuum.c
@@ -9,10 +9,6 @@
 #include "storage/lmgr.h"
 #include "utils/memutils.h"

-#if PG_VERSION_NUM >= 180000
-#define vacuum_delay_point() vacuum_delay_point(false)
-#endif
-
 /*
 * Check if deleted list contains an index TID
 */
@@ -531,14 +527,6 @@ MarkDeleted(HnswVacuumState * vacuumstate)
 			for (int i = 0; i < ntup->count; i++)
 				ItemPointerSetInvalid(&ntup->indextids[i]);

-			/* Increment version */
-			/* This is used to avoid incorrect reads for iterative scans */
-			/* Reserve some bits for future use */
-			etup->version++;
-			if (etup->version > 15)
-				etup->version = 1;
-			ntup->version = etup->version;
-
 			/*
 			 * We modified the tuples in place, no need to call
 			 * PageIndexTupleOverwrite
--- a/src/ivfbuild.c
+++ b/src/ivfbuild.c
@@ -138,7 +138,7 @@ SampleRows(IvfflatBuildState * buildstate)
 * Add tuple to sort
 */
 static void
-AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState * buildstate)
+AddTupleToSort(Relation index, ItemPointer tid, Datum *values, bool *isnull, IvfflatBuildState * buildstate)
 {
 	double		distance;
 	double		minDistance = DBL_MAX;
@@ -184,6 +184,11 @@ AddTupleToSort(Relation index, ItemPointer tid, Datum *values, IvfflatBuildState
 	slot->tts_isnull[1] = false;
 	slot->tts_values[2] = value;
 	slot->tts_isnull[2] = false;
+	for (int i = 1; i < buildstate->tupdesc->natts; i++)
+	{
+		slot->tts_values[2 + i] = values[i];
+		slot->tts_isnull[2 + i] = isnull[i];
+	}
 	ExecStoreVirtualTuple(slot);

 	/*
@@ -215,7 +220,7 @@ BuildCallback(Relation index, ItemPointer tid, Datum *values,
 	oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);

 	/* Add tuple to sort */
-	AddTupleToSort(index, tid, values, buildstate);
+	AddTupleToSort(index, tid, values, isnull, buildstate);

 	/* Reset memory context */
 	MemoryContextSwitchTo(oldCtx);
@@ -226,19 +231,20 @@ BuildCallback(Relation index, ItemPointer tid, Datum *values,
 * Get index tuple from sort state
 */
 static inline void
-GetNextTuple(Tuplesortstate *sortstate, TupleDesc tupdesc, TupleTableSlot *slot, IndexTuple *itup, int *list)
+GetNextTuple(Tuplesortstate *sortstate, TupleDesc tupdesc, TupleTableSlot *slot, Datum *values, bool *isnull, IndexTuple *itup, int *list)
 {
 	if (tuplesort_gettupleslot(sortstate, true, false, slot, NULL))
 	{
-		Datum		value;
-		bool		isnull;
+		bool		unused;

-		*list = DatumGetInt32(slot_getattr(slot, 1, &isnull));
-		value = slot_getattr(slot, 3, &isnull);
+		*list = DatumGetInt32(slot_getattr(slot, 1, &unused));
+
+		for (int i = 0; i < tupdesc->natts; i++)
+			values[i] = slot_getattr(slot, 3 + i, &isnull[i]);

 		/* Form the index tuple */
-		*itup = index_form_tuple(tupdesc, &value, &isnull);
-		(*itup)->t_tid = *((ItemPointer) DatumGetPointer(slot_getattr(slot, 2, &isnull)));
+		*itup = index_form_tuple(tupdesc, values, isnull);
+		(*itup)->t_tid = *((ItemPointer) DatumGetPointer(slot_getattr(slot, 2, &unused)));
 	}
 	else
 		*list = -1;
@@ -256,12 +262,14 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)

 	TupleTableSlot *slot = MakeSingleTupleTableSlot(buildstate->sortdesc, &TTSOpsMinimalTuple);
 	TupleDesc	tupdesc = buildstate->tupdesc;
+	Datum	   *values = palloc(tupdesc->natts * sizeof(Datum));
+	bool	   *isnull = palloc(tupdesc->natts * sizeof(bool));

 	pgstat_progress_update_param(PROGRESS_CREATEIDX_SUBPHASE, PROGRESS_IVFFLAT_PHASE_LOAD);

 	pgstat_progress_update_param(PROGRESS_CREATEIDX_TUPLES_TOTAL, buildstate->indtuples);

-	GetNextTuple(buildstate->sortstate, tupdesc, slot, &itup, &list);
+	GetNextTuple(buildstate->sortstate, tupdesc, slot, values, isnull, &itup, &list);

 	for (int i = 0; i < buildstate->centers->length; i++)
 	{
@@ -297,7 +305,7 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)

 			pgstat_progress_update_param(PROGRESS_CREATEIDX_TUPLES_DONE, ++inserted);

-			GetNextTuple(buildstate->sortstate, tupdesc, slot, &itup, &list);
+			GetNextTuple(buildstate->sortstate, tupdesc, slot, values, isnull, &itup, &list);
 		}

 		insertPage = BufferGetBlockNumber(buf);
@@ -307,6 +315,9 @@ InsertTuples(Relation index, IvfflatBuildState * buildstate, ForkNumber forkNum)
 		/* Set the start and insert pages */
 		IvfflatUpdateList(index, buildstate->listInfo[i], insertPage, InvalidBlockNumber, startPage, forkNum);
 	}
+
+	pfree(values);
+	pfree(isnull);
 }

 /*
@@ -330,6 +341,19 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
 				(errcode(ERRCODE_FEATURE_NOT_SUPPORTED),
 				 errmsg("type not supported for ivfflat index")));

+	/* TODO See if needed */
+	if (IndexRelationGetNumberOfKeyAttributes(index) > 3)
+		elog(ERROR, "index cannot have more than three columns");
+
+	if (!OidIsValid(index_getprocid(index, 1, IVFFLAT_DISTANCE_PROC)))
+		elog(ERROR, "first column must be a vector");
+
+	for (int i = 1; i < IndexRelationGetNumberOfKeyAttributes(index); i++)
+	{
+		if (OidIsValid(index_getprocid(index, i + 1, IVFFLAT_DISTANCE_PROC)))
+			elog(ERROR, "column %d cannot be a vector", i + 1);
+	}
+
 	/* Require column to have dimensions to be indexed */
 	if (buildstate->dimensions < 0)
 		ereport(ERROR,
@@ -357,10 +381,11 @@ InitBuildState(IvfflatBuildState * buildstate, Relation heap, Relation index, In
 				 errmsg("dimensions must be greater than one for this opclass")));

 	/* Create tuple description for sorting */
-	buildstate->sortdesc = CreateTemplateTupleDesc(3);
+	buildstate->sortdesc = CreateTemplateTupleDesc(2 + buildstate->tupdesc->natts);
 	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);
+	for (int i = 0; i < buildstate->tupdesc->natts; i++)
+		TupleDescInitEntry(buildstate->sortdesc, (AttrNumber) (3 + i), NULL, buildstate->tupdesc->attrs[i].atttypid, -1, 0);

 	buildstate->slot = MakeSingleTupleTableSlot(buildstate->sortdesc, &TTSOpsVirtual);

--- a/src/ivfflat.c
+++ b/src/ivfflat.c
@@ -17,16 +17,8 @@
 #endif

 int			ivfflat_probes;
-int			ivfflat_iterative_scan;
-int			ivfflat_max_probes;
 static relopt_kind ivfflat_relopt_kind;

-static const struct config_enum_entry ivfflat_iterative_scan_options[] = {
-	{"off", IVFFLAT_ITERATIVE_SCAN_OFF, false},
-	{"relaxed_order", IVFFLAT_ITERATIVE_SCAN_RELAXED, false},
-	{NULL, 0, false}
-};
-
 /*
 * Initialize index options and variables
 */
@@ -41,15 +33,6 @@ IvfflatInit(void)
 							"Valid range is 1..lists.", &ivfflat_probes,
 							IVFFLAT_DEFAULT_PROBES, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);

-	DefineCustomEnumVariable("ivfflat.iterative_scan", "Sets the mode for iterative scans",
-							 NULL, &ivfflat_iterative_scan,
-							 IVFFLAT_ITERATIVE_SCAN_OFF, ivfflat_iterative_scan_options, PGC_USERSET, 0, NULL, NULL, NULL);
-
-	/* If this is less than probes, probes is used */
-	DefineCustomIntVariable("ivfflat.max_probes", "Sets the max number of probes for iterative scans",
-							NULL, &ivfflat_max_probes,
-							IVFFLAT_MAX_LISTS, IVFFLAT_MIN_LISTS, IVFFLAT_MAX_LISTS, PGC_USERSET, 0, NULL, NULL, NULL);
-
 	MarkGUCPrefixReserved("ivfflat");
 }

@@ -99,10 +82,6 @@ ivfflatcostestimate(PlannerInfo *root, IndexPath *path, double loop_count,
 		*indexSelectivity = 0;
 		*indexCorrelation = 0;
 		*indexPages = 0;
-#if PG_VERSION_NUM >= 180000
-		/* See "On disable_cost" thread on pgsql-hackers */
-		path->path.disabled_nodes = 2;
-#endif
 		return;
 	}

@@ -188,7 +167,7 @@ ivfflathandler(PG_FUNCTION_ARGS)
 	amroutine->amcanorderbyop = true;
 	amroutine->amcanbackward = false;	/* can change direction mid-scan */
 	amroutine->amcanunique = false;
-	amroutine->amcanmulticol = false;
+	amroutine->amcanmulticol = true;
 	amroutine->amoptionalkey = true;
 	amroutine->amsearcharray = false;
 	amroutine->amsearchnulls = false;
--- a/src/ivfflat.h
+++ b/src/ivfflat.h
@@ -80,14 +80,6 @@

 /* Variables */
 extern int	ivfflat_probes;
-extern int	ivfflat_iterative_scan;
-extern int	ivfflat_max_probes;
-
-typedef enum IvfflatIterativeScanMode
-{
-	IVFFLAT_ITERATIVE_SCAN_OFF,
-	IVFFLAT_ITERATIVE_SCAN_RELAXED
-}			IvfflatIterativeScanMode;

 typedef struct VectorArrayData
 {
@@ -256,11 +248,8 @@ typedef struct IvfflatScanOpaqueData
 {
 	const		IvfflatTypeInfo *typeInfo;
 	int			probes;
-	int			maxProbes;
 	int			dimensions;
 	bool		first;
-	Datum		value;
-	MemoryContext tmpCtx;

 	/* Sorting */
 	Tuplesortstate *sortstate;
@@ -277,9 +266,7 @@ typedef struct IvfflatScanOpaqueData

 	/* Lists */
 	pairingheap *listQueue;
-	BlockNumber *listPages;
-	int			listIndex;
-	IvfflatScanList *lists;
+	IvfflatScanList lists[FLEXIBLE_ARRAY_MEMBER];	/* must come last */
 }			IvfflatScanOpaqueData;

 typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
--- a/src/ivfinsert.c
+++ b/src/ivfinsert.c
@@ -78,6 +78,8 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
 	BlockNumber insertPage = InvalidBlockNumber;
 	ListInfo	listInfo;
 	BlockNumber originalInsertPage;
+	TupleDesc	tupdesc = RelationGetDescr(index);
+	Datum	   *newValues = palloc(tupdesc->natts * sizeof(Datum));

 	/* Detoast once for all calls */
 	value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
@@ -102,8 +104,12 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
 	Assert(BlockNumberIsValid(insertPage));
 	originalInsertPage = insertPage;

+	newValues[0] = value;
+	for (int i = 1; i < tupdesc->natts; i++)
+		newValues[i] = values[i];
+
 	/* Form tuple */
-	itup = index_form_tuple(RelationGetDescr(index), &value, isnull);
+	itup = index_form_tuple(tupdesc, newValues, isnull);
 	itup->t_tid = *heap_tid;

 	/* Get tuple size */
--- a/src/ivfscan.c
+++ b/src/ivfscan.c
@@ -10,7 +10,10 @@
 #include "miscadmin.h"
 #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)
@@ -62,7 +65,7 @@ GetScanLists(IndexScanDesc scan, Datum value)
 			/* Use procinfo from the index instead of scan key for performance */
 			distance = DatumGetFloat8(so->distfunc(so->procinfo, so->collation, PointerGetDatum(&list->center), value));

-			if (listCount < so->maxProbes)
+			if (listCount < so->probes)
 			{
 				IvfflatScanList *scanlist;

@@ -75,7 +78,7 @@ GetScanLists(IndexScanDesc scan, Datum value)
 				pairingheap_add(so->listQueue, &scanlist->ph_node);

 				/* Calculate max distance */
-				if (listCount == so->maxProbes)
+				if (listCount == so->probes)
 					maxDistance = GetScanList(pairingheap_first(so->listQueue))->distance;
 			}
 			else if (distance < maxDistance)
@@ -99,11 +102,34 @@ GetScanLists(IndexScanDesc scan, Datum value)

 		UnlockReleaseBuffer(cbuf);
 	}
+}

-	for (int i = listCount - 1; i >= 0; i--)
-		so->listPages[i] = GetScanList(pairingheap_remove_first(so->listQueue))->startPage;
+/*
+ * Check if matches scan keys
+ */
+static bool
+MatchesScanKeys(IndexScanDesc scan, IndexTuple itup, TupleDesc tupdesc)
+{
+	for (int i = 0; i < scan->numberOfKeys; i++)
+	{
+		ScanKey		key = &scan->keyData[i];
+		bool		attnull = key->sk_flags & SK_ISNULL;
+		bool		isnull;
+		Datum		value = index_getattr(itup, key->sk_attno, tupdesc, &isnull);

-	Assert(pairingheap_is_empty(so->listQueue));
+		if (isnull || attnull)
+		{
+			if (isnull != attnull)
+				return false;
+		}
+		else
+		{
+			if (!DatumGetBool(FunctionCall2Coll(&key->sk_func, key->sk_collation, value, key->sk_argument)))
+				return false;
+		}
+	}
+
+	return true;
 }

 /*
@@ -114,15 +140,13 @@ GetScanItems(IndexScanDesc scan, Datum value)
 {
 	IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
 	TupleDesc	tupdesc = RelationGetDescr(scan->indexRelation);
+	double		tuples = 0;
 	TupleTableSlot *slot = so->vslot;
-	int			batchProbes = 0;
-
-	tuplesort_reset(so->sortstate);

 	/* Search closest probes lists */
-	while (so->listIndex < so->maxProbes && (++batchProbes) <= so->probes)
+	while (!pairingheap_is_empty(so->listQueue))
 	{
-		BlockNumber searchPage = so->listPages[so->listIndex++];
+		BlockNumber searchPage = GetScanList(pairingheap_remove_first(so->listQueue))->startPage;

 		/* Search all entry pages for list */
 		while (BlockNumberIsValid(searchPage))
@@ -144,6 +168,10 @@ GetScanItems(IndexScanDesc scan, Datum value)
 				ItemId		itemid = PageGetItemId(page, offno);

 				itup = (IndexTuple) PageGetItem(page, itemid);
+
+				if (!MatchesScanKeys(scan, itup, tupdesc))
+					continue;
+
 				datum = index_getattr(itup, 1, tupdesc, &isnull);

 				/*
@@ -160,6 +188,8 @@ GetScanItems(IndexScanDesc scan, Datum value)
 				ExecStoreVirtualTuple(slot);

 				tuplesort_puttupleslot(so->sortstate, slot);
+
+				tuples++;
 			}

 			searchPage = IvfflatPageGetOpaque(page)->nextblkno;
@@ -168,11 +198,13 @@ GetScanItems(IndexScanDesc scan, Datum value)
 		}
 	}

-	tuplesort_performsort(so->sortstate);
+	if (tuples < 100)
+		ereport(DEBUG1,
+				(errmsg("index scan found few tuples"),
+				 errdetail("Index may have been created with little data."),
+				 errhint("Recreate the index and possibly decrease lists.")));

-#if defined(IVFFLAT_MEMORY)
-	elog(INFO, "memory: %zu MB", MemoryContextMemAllocated(CurrentMemoryContext, true) / (1024 * 1024));
-#endif
+	tuplesort_performsort(so->sortstate);
 }

 /*
@@ -209,13 +241,7 @@ GetScanValue(IndexScanDesc scan)

 		/* Normalize if needed */
 		if (so->normprocinfo != NULL)
-		{
-			MemoryContext oldCtx = MemoryContextSwitchTo(so->tmpCtx);
-
 			value = IvfflatNormValue(so->typeInfo, so->collation, value);
-
-			MemoryContextSwitchTo(oldCtx);
-		}
 	}

 	return value;
@@ -246,30 +272,19 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
 	int			lists;
 	int			dimensions;
 	int			probes = ivfflat_probes;
-	int			maxProbes;
-	MemoryContext oldCtx;

 	scan = RelationGetIndexScan(index, nkeys, norderbys);

 	/* Get lists and dimensions from metapage */
 	IvfflatGetMetaPageInfo(index, &lists, &dimensions);

-	if (ivfflat_iterative_scan != IVFFLAT_ITERATIVE_SCAN_OFF)
-		maxProbes = Max(ivfflat_max_probes, probes);
-	else
-		maxProbes = probes;
-
 	if (probes > lists)
 		probes = lists;

-	if (maxProbes > lists)
-		maxProbes = lists;
-
-	so = (IvfflatScanOpaque) palloc(sizeof(IvfflatScanOpaqueData));
+	so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
 	so->typeInfo = IvfflatGetTypeInfo(index);
 	so->first = true;
 	so->probes = probes;
-	so->maxProbes = maxProbes;
 	so->dimensions = dimensions;

 	/* Set support functions */
@@ -277,12 +292,6 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
 	so->normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_NORM_PROC);
 	so->collation = index->rd_indcollation[0];

-	so->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
-									   "Ivfflat scan temporary context",
-									   ALLOCSET_DEFAULT_SIZES);
-
-	oldCtx = MemoryContextSwitchTo(so->tmpCtx);
-
 	/* Create tuple description for sorting */
 	so->tupdesc = CreateTemplateTupleDesc(2);
 	TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
@@ -303,11 +312,6 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
 	so->bas = GetAccessStrategy(BAS_BULKREAD);

 	so->listQueue = pairingheap_allocate(CompareLists, scan);
-	so->listPages = palloc(maxProbes * sizeof(BlockNumber));
-	so->listIndex = 0;
-	so->lists = palloc(maxProbes * sizeof(IvfflatScanList));
-
-	MemoryContextSwitchTo(oldCtx);

 	scan->opaque = so;

@@ -322,9 +326,11 @@ ivfflatrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int
 {
 	IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;

+	if (!so->first)
+		tuplesort_reset(so->sortstate);
+
 	so->first = true;
 	pairingheap_reset(so->listQueue);
-	so->listIndex = 0;

 	if (keys && scan->numberOfKeys > 0)
 		memmove(scan->keyData, keys, scan->numberOfKeys * sizeof(ScanKeyData));
@@ -340,8 +346,6 @@ bool
 ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
 {
 	IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
-	ItemPointer heaptid;
-	bool		isnull;

 	/*
 	 * Index can be used to scan backward, but Postgres doesn't support
@@ -369,23 +373,28 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
 		IvfflatBench("GetScanLists", GetScanLists(scan, value));
 		IvfflatBench("GetScanItems", GetScanItems(scan, value));
 		so->first = false;
-		so->value = value;
+
+#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));
 	}

-	while (!tuplesort_gettupleslot(so->sortstate, true, false, so->mslot, NULL))
+	if (tuplesort_gettupleslot(so->sortstate, true, false, so->mslot, NULL))
 	{
-		if (so->listIndex == so->maxProbes)
-			return false;
+		bool		isnull;
+		ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->mslot, 2, &isnull));

-		IvfflatBench("GetScanItems", GetScanItems(scan, so->value));
+		scan->xs_heaptid = *heaptid;
+		scan->xs_recheck = false;
+		scan->xs_recheckorderby = false;
+		return true;
 	}

-	heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->mslot, 2, &isnull));
-
-	scan->xs_heaptid = *heaptid;
-	scan->xs_recheck = false;
-	scan->xs_recheckorderby = false;
-	return true;
+	return false;
 }

 /*
@@ -396,10 +405,12 @@ ivfflatendscan(IndexScanDesc scan)
 {
 	IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;

-	/* Free any temporary files */
+	pairingheap_free(so->listQueue);
 	tuplesort_end(so->sortstate);
+	FreeAccessStrategy(so->bas);
+	FreeTupleDesc(so->tupdesc);

-	MemoryContextDelete(so->tmpCtx);
+	/* TODO Free vslot and mslot without freeing TupleDesc */

 	pfree(so);
 	scan->opaque = NULL;
--- a/src/ivfutils.c
+++ b/src/ivfutils.c
@@ -355,7 +355,7 @@ ivfflat_halfvec_support(PG_FUNCTION_ARGS)
 	};

 	PG_RETURN_POINTER(&typeInfo);
-}
+};

 FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_bit_support);
 Datum
@@ -370,4 +370,4 @@ ivfflat_bit_support(PG_FUNCTION_ARGS)
 	};

 	PG_RETURN_POINTER(&typeInfo);
-}
+};
--- a/src/ivfvacuum.c
+++ b/src/ivfvacuum.c
@@ -5,10 +5,6 @@
 #include "ivfflat.h"
 #include "storage/bufmgr.h"

-#if PG_VERSION_NUM >= 180000
-#define vacuum_delay_point() vacuum_delay_point(false)
-#endif
-
 /*
 * Bulk delete tuples from the index
 */
@@ -30,7 +26,7 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
 		Page		cpage;
 		OffsetNumber coffno;
 		OffsetNumber cmaxoffno;
-		BlockNumber listPages[MaxOffsetNumber];
+		BlockNumber startPages[MaxOffsetNumber];
 		ListInfo	listInfo;

 		cbuf = ReadBuffer(index, blkno);
@@ -44,7 +40,7 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,
 		{
 			IvfflatList list = (IvfflatList) PageGetItem(cpage, PageGetItemId(cpage, coffno));

-			listPages[coffno - FirstOffsetNumber] = list->startPage;
+			startPages[coffno - FirstOffsetNumber] = list->startPage;
 		}

 		listInfo.blkno = blkno;
@@ -54,7 +50,7 @@ ivfflatbulkdelete(IndexVacuumInfo *info, IndexBulkDeleteResult *stats,

 		for (coffno = FirstOffsetNumber; coffno <= cmaxoffno; coffno = OffsetNumberNext(coffno))
 		{
-			BlockNumber searchPage = listPages[coffno - FirstOffsetNumber];
+			BlockNumber searchPage = startPages[coffno - FirstOffsetNumber];
 			BlockNumber insertPage = InvalidBlockNumber;

 			/* Iterate over entry pages */
--- a/src/sparsevec.c
+++ b/src/sparsevec.c
@@ -4,7 +4,6 @@
 #include <math.h>

 #include "catalog/pg_type.h"
-#include "common/shortest_dec.h"
 #include "common/string.h"
 #include "fmgr.h"
 #include "halfutils.h"
@@ -13,10 +12,17 @@
 #include "sparsevec.h"
 #include "utils/array.h"
 #include "utils/builtins.h"
-#include "utils/float.h"
 #include "utils/lsyscache.h"
 #include "vector.h"

+#if PG_VERSION_NUM >= 120000
+#include "common/shortest_dec.h"
+#include "utils/float.h"
+#else
+#include <float.h>
+#include "utils/builtins.h"
+#endif
+
 typedef struct SparseInputElement
 {
 	int32		index;
--- a/test/expected/hnsw_vector.out
+++ b/test/expected/hnsw_vector.out
@@ -99,38 +99,6 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::vector)) t2
     4
 (1 row)

-DROP TABLE t;
-- iterative
-CREATE TABLE t (val vector(3));
-INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
-CREATE INDEX ON t USING hnsw (val vector_l2_ops);
-SET hnsw.iterative_scan = strict_order;
-SET hnsw.ef_search = 1;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-   val   
---------
- [1,2,3]
- [1,1,1]
- [0,0,0]
-(3 rows)
-
-SET hnsw.iterative_scan = relaxed_order;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-   val   
---------
- [1,2,3]
- [1,1,1]
- [0,0,0]
-(3 rows)
-
-TRUNCATE t;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
- val 
-----
-(0 rows)
-
-RESET hnsw.iterative_scan;
-RESET hnsw.ef_search;
 DROP TABLE t;
 -- unlogged
 CREATE UNLOGGED TABLE t (val vector(3));
@@ -171,31 +139,4 @@ SET hnsw.ef_search = 0;
 ERROR:  0 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
 SET hnsw.ef_search = 1001;
 ERROR:  1001 is outside the valid range for parameter "hnsw.ef_search" (1 .. 1000)
-SHOW hnsw.iterative_scan;
- hnsw.iterative_scan 
---------------------
- off
-(1 row)
-
-SET hnsw.iterative_scan = on;
-ERROR:  invalid value for parameter "hnsw.iterative_scan": "on"
-HINT:  Available values: off, relaxed_order, strict_order.
-SHOW hnsw.max_scan_tuples;
- hnsw.max_scan_tuples 
----------------------
- 20000
-(1 row)
-
-SET hnsw.max_scan_tuples = 0;
-ERROR:  0 is outside the valid range for parameter "hnsw.max_scan_tuples" (1 .. 2147483647)
-SHOW hnsw.scan_mem_multiplier;
- hnsw.scan_mem_multiplier 
--------------------------
- 1
-(1 row)
-
-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)
 DROP TABLE t;
--- a/test/expected/ivfflat_vector.out
+++ b/test/expected/ivfflat_vector.out
@@ -81,46 +81,6 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2
     3
 (1 row)

-DROP TABLE t;
-- iterative
-CREATE TABLE t (val vector(3));
-INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 3);
-SET ivfflat.iterative_scan = relaxed_order;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-   val   
---------
- [1,2,3]
- [1,1,1]
- [0,0,0]
-(3 rows)
-
-SET ivfflat.max_probes = 1;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-   val   
---------
- [1,2,3]
-(1 row)
-
-SET ivfflat.max_probes = 2;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-   val   
---------
- [1,2,3]
- [1,1,1]
-(2 rows)
-
-TRUNCATE t;
-NOTICE:  ivfflat index created with little data
-DETAIL:  This will cause low recall.
-HINT:  Drop the index until the table has more data.
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
- val 
-----
-(0 rows)
-
-RESET ivfflat.iterative_scan;
-RESET ivfflat.max_probes;
 DROP TABLE t;
 -- unlogged
 CREATE UNLOGGED TABLE t (val vector(3));
@@ -149,27 +109,4 @@ SHOW ivfflat.probes;
 1
 (1 row)

-SET ivfflat.probes = 0;
-ERROR:  0 is outside the valid range for parameter "ivfflat.probes" (1 .. 32768)
-SET ivfflat.probes = 32769;
-ERROR:  32769 is outside the valid range for parameter "ivfflat.probes" (1 .. 32768)
-SHOW ivfflat.iterative_scan;
- ivfflat.iterative_scan 
------------------------
- off
-(1 row)
-
-SET ivfflat.iterative_scan = on;
-ERROR:  invalid value for parameter "ivfflat.iterative_scan": "on"
-HINT:  Available values: off, relaxed_order.
-SHOW ivfflat.max_probes;
- ivfflat.max_probes 
--------------------
- 32768
-(1 row)
-
-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)
 DROP TABLE t;
--- a/test/sql/hnsw_vector.sql
+++ b/test/sql/hnsw_vector.sql
@@ -57,26 +57,6 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <+> (SELECT NULL::vector)) t2

 DROP TABLE t;

-- iterative
-
-CREATE TABLE t (val vector(3));
-INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
-CREATE INDEX ON t USING hnsw (val vector_l2_ops);
-
-SET hnsw.iterative_scan = strict_order;
-SET hnsw.ef_search = 1;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-
-SET hnsw.iterative_scan = relaxed_order;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-
-TRUNCATE t;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-
-RESET hnsw.iterative_scan;
-RESET hnsw.ef_search;
-DROP TABLE t;
-
 -- unlogged

 CREATE UNLOGGED TABLE t (val vector(3));
@@ -101,17 +81,4 @@ 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;
-
 DROP TABLE t;
--- a/test/sql/ivfflat_vector.sql
+++ b/test/sql/ivfflat_vector.sql
@@ -44,28 +44,6 @@ SELECT COUNT(*) FROM (SELECT * FROM t ORDER BY val <=> (SELECT NULL::vector)) t2

 DROP TABLE t;

-- iterative
-
-CREATE TABLE t (val vector(3));
-INSERT INTO t (val) VALUES ('[0,0,0]'), ('[1,2,3]'), ('[1,1,1]'), (NULL);
-CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 3);
-
-SET ivfflat.iterative_scan = relaxed_order;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-
-SET ivfflat.max_probes = 1;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-
-SET ivfflat.max_probes = 2;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-
-TRUNCATE t;
-SELECT * FROM t ORDER BY val <-> '[3,3,3]';
-
-RESET ivfflat.iterative_scan;
-RESET ivfflat.max_probes;
-DROP TABLE t;
-
 -- unlogged

 CREATE UNLOGGED TABLE t (val vector(3));
@@ -84,16 +62,4 @@ CREATE INDEX ON t USING ivfflat (val vector_l2_ops) WITH (lists = 32769);

 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;
-
 DROP TABLE t;
--- a/test/t/041_ivfflat_inline_filtering.pl
+++ b/test/t/041_ivfflat_inline_filtering.pl
@@ -0,0 +1,197 @@
+use strict;
+use warnings FATAL => 'all';
+use PostgreSQL::Test::Cluster;
+use PostgreSQL::Test::Utils;
+use Test::More;
+
+my $node;
+my @queries = ();
+my @where = ();
+my @expected;
+my $limit = 20;
+my $dim = 3;
+my $array_sql = join(",", ('random()') x $dim);
+my $nc = 100;
+my $nc2 = 10;
+
+sub test_recall
+{
+	my ($probes, $min, $operator) = @_;
+	my $correct = 0;
+	my $total = 0;
+
+	for my $j (0 .. 2)
+	{
+		my $explain = $node->safe_psql("postgres", qq(
+			SET enable_seqscan = off;
+			SET ivfflat.probes = $probes;
+			EXPLAIN ANALYZE SELECT i FROM tst WHERE $where[$j] ORDER BY v $operator '$queries[$j]' LIMIT $limit;
+		));
+		like($explain, qr/Index Cond/);
+	}
+
+	for my $i (0 .. $#queries)
+	{
+		my $actual = $node->safe_psql("postgres", qq(
+			SET enable_seqscan = off;
+			SET ivfflat.probes = $probes;
+			SELECT i FROM tst WHERE $where[$i] ORDER BY v $operator '$queries[$i]' LIMIT $limit;
+		));
+		my @actual_ids = split("\n", $actual);
+		my %actual_set = map { $_ => 1 } @actual_ids;
+
+		is(scalar(@actual_ids), $limit);
+
+		my @expected_ids = split("\n", $expected[$i]);
+
+		foreach (@expected_ids)
+		{
+			if (exists($actual_set{$_}))
+			{
+				$correct++;
+			}
+			$total++;
+		}
+	}
+
+	cmp_ok($correct / $total, ">=", $min, $operator);
+}
+
+# Initialize node
+$node = PostgreSQL::Test::Cluster->new('node');
+$node->init;
+$node->start;
+
+# Create table
+$node->safe_psql("postgres", "CREATE EXTENSION vector;");
+$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector($dim), c int4, c2 int4);");
+$node->safe_psql("postgres",
+	"INSERT INTO tst SELECT i, ARRAY[$array_sql], i % $nc, i % $nc2 FROM generate_series(1, 50000) i;"
+);
+
+# Generate queries
+for my $i (1 .. 100)
+{
+	my @r = ();
+	for (1 .. $dim)
+	{
+		push(@r, rand());
+	}
+	push(@queries, "[" . join(",", @r) . "]");
+
+	if ($i % 3 == 0)
+	{
+		my $c = int(rand() * $nc);
+		push(@where, "c = $c");
+	}
+	elsif ($i % 3 == 1)
+	{
+		my $c2 = int(rand() * $nc2);
+		push(@where, "c2 = $c2");
+	}
+	else
+	{
+		# use c2 to ensure results
+		my $c2 = int(rand() * $nc2);
+		push(@where, "c = $c2 AND c2 = $c2");
+	}
+}
+
+# Add index
+$node->safe_psql("postgres", qq(
+	CREATE INDEX ON tst USING ivfflat (v vector_l2_ops, c, c2) WITH (lists = 100);
+));
+
+# Insert more rows
+$node->safe_psql("postgres",
+	"INSERT INTO tst SELECT i, ARRAY[$array_sql], i % $nc, i % $nc2 FROM generate_series(1, 50000) i;"
+);
+
+# Get exact results
+@expected = ();
+for my $i (0 .. $#queries)
+{
+	my $res = $node->safe_psql("postgres", qq(
+		SET enable_indexscan = off;
+		SELECT i FROM tst WHERE $where[$i] ORDER BY v <-> '$queries[$i]' LIMIT $limit;
+	));
+	push(@expected, $res);
+}
+
+# Test recall
+test_recall(10, 0.99, '<->');
+
+# Test vacuum
+$node->safe_psql("postgres", "DELETE FROM tst WHERE c > 5;");
+$node->safe_psql("postgres", "VACUUM tst;");
+
+# Test less than
+my $explain = $node->safe_psql("postgres", qq(
+	SET enable_seqscan = off;
+	EXPLAIN ANALYZE SELECT i FROM tst WHERE c < 10 ORDER BY v <-> '$queries[0]' LIMIT $limit;
+));
+like($explain, qr/Index Cond: \(c < 10\)/);
+
+# Test less than or equal
+$explain = $node->safe_psql("postgres", qq(
+	SET enable_seqscan = off;
+	EXPLAIN ANALYZE SELECT i FROM tst WHERE c <= 10 ORDER BY v <-> '$queries[0]' LIMIT $limit;
+));
+like($explain, qr/Index Cond: \(c <= 10\)/);
+
+# Test greater than or equal
+$explain = $node->safe_psql("postgres", qq(
+	SET enable_seqscan = off;
+	EXPLAIN ANALYZE SELECT i FROM tst WHERE c >= 90 ORDER BY v <-> '$queries[0]' LIMIT $limit;
+));
+like($explain, qr/Index Cond: \(c >= 90\)/);
+
+# Test greater than
+$explain = $node->safe_psql("postgres", qq(
+	SET enable_seqscan = off;
+	EXPLAIN ANALYZE SELECT i FROM tst WHERE c > 90 ORDER BY v <-> '$queries[0]' LIMIT $limit;
+));
+like($explain, qr/Index Cond: \(c > 90\)/);
+
+# Test multiple attribute columns
+$explain = $node->safe_psql("postgres", qq(
+	SET enable_seqscan = off;
+	EXPLAIN ANALYZE SELECT i FROM tst WHERE c = 1 AND c2 = 1 ORDER BY v <-> '$queries[0]' LIMIT $limit;
+));
+like($explain, qr/Index Cond: \(\(c = 1\) AND \(c2 = 1\)\)/);
+
+# Test only last attribute column
+$explain = $node->safe_psql("postgres", qq(
+	SET enable_seqscan = off;
+	EXPLAIN ANALYZE SELECT i FROM tst WHERE c2 = 1 ORDER BY v <-> '$queries[0]' LIMIT $limit;
+));
+like($explain, qr/Index Cond: \(c2 = 1\)/);
+
+# Test only vector column
+$explain = $node->safe_psql("postgres", qq(
+	SET enable_seqscan = off;
+	EXPLAIN ANALYZE SELECT i FROM tst ORDER BY v <-> '$queries[0]' LIMIT $limit;
+));
+like($explain, qr/Index Scan/);
+
+# Test only attribute columns
+$explain = $node->safe_psql("postgres", qq(
+	SET enable_seqscan = off;
+	EXPLAIN ANALYZE SELECT i FROM tst WHERE c = 1;
+));
+like($explain, qr/Seq Scan/);
+
+# Test columns
+my ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING ivfflat (c);");
+like($stderr, qr/first column must be a vector/);
+
+($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING ivfflat (c, v vector_cosine_ops);");
+like($stderr, qr/first column must be a vector/);
+
+($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_cosine_ops, c, c, c);");
+like($stderr, qr/index cannot have more than three columns/);
+
+($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_cosine_ops, v vector_cosine_ops);");
+like($stderr, qr/column 2 cannot be a vector/);
+
+done_testing();
--- a/test/t/041_ivfflat_iterative_scan.pl
+++ b/test/t/041_ivfflat_iterative_scan.pl
@@ -1,54 +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;
-$node->start;
-
-# Create table
-$node->safe_psql("postgres", "CREATE EXTENSION vector;");
-$node->safe_psql("postgres", "CREATE TABLE tst (i int4 PRIMARY KEY, v vector($dim));");
-$node->safe_psql("postgres",
-	"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
-);
-$node->safe_psql("postgres", "CREATE INDEX ON tst USING ivfflat (v vector_l2_ops);");
-
-my $count = $node->safe_psql("postgres", qq(
-	SET enable_seqscan = off;
-	SET ivfflat.probes = 10;
-	SET ivfflat.iterative_scan = relaxed_order;
-	SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
-));
-is($count, 10);
-
-foreach ((30, 50, 70))
-{
-	my $max_probes = $_;
-	my $expected = $max_probes / 10;
-	my $sum = 0;
-
-	for my $i (1 .. 20)
-	{
-		$count = $node->safe_psql("postgres", qq(
-			SET enable_seqscan = off;
-			SET ivfflat.probes = 10;
-			SET ivfflat.iterative_scan = relaxed_order;
-			SET ivfflat.max_probes = $max_probes;
-			SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst WHERE i = $i) LIMIT 11) t;
-		));
-		$sum += $count;
-	}
-
-	my $avg = $sum / 20;
-	cmp_ok($avg, '>', $expected - 2);
-	cmp_ok($avg, '<', $expected + 2);
-}
-
-done_testing();
--- a/test/t/042_ivfflat_iterative_scan_recall.pl
+++ b/test/t/042_ivfflat_iterative_scan_recall.pl
@@ -1,125 +0,0 @@
-use strict;
-use warnings FATAL => 'all';
-use PostgreSQL::Test::Cluster;
-use PostgreSQL::Test::Utils;
-use Test::More;
-
-my $node;
-my @queries = ();
-my @expected;
-my $limit = 20;
-my @cs = (100, 1000);
-
-sub test_recall
-{
-	my ($c, $probes, $min, $operator) = @_;
-	my $correct = 0;
-	my $total = 0;
-
-	my $explain = $node->safe_psql("postgres", qq(
-		SET enable_seqscan = off;
-		SET ivfflat.probes = $probes;
-		SET ivfflat.iterative_scan = relaxed_order;
-		EXPLAIN ANALYZE SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[0]' LIMIT $limit;
-	));
-	like($explain, qr/Index Scan using idx on tst/);
-
-	for my $i (0 .. $#queries)
-	{
-		my $actual = $node->safe_psql("postgres", qq(
-			SET enable_seqscan = off;
-			SET ivfflat.probes = $probes;
-			SET ivfflat.iterative_scan = relaxed_order;
-			SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[$i]' LIMIT $limit;
-		));
-		my @actual_ids = split("\n", $actual);
-
-		my @expected_ids = split("\n", $expected[$i]);
-		my %expected_set = map { $_ => 1 } @expected_ids;
-
-		foreach (@actual_ids)
-		{
-			if (exists($expected_set{$_}))
-			{
-				$correct++;
-			}
-		}
-
-		$total += $limit;
-	}
-
-	cmp_ok($correct / $total, ">=", $min, "$operator $c");
-}
-
-# Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
-$node->init;
-$node->start;
-
-# Create table
-$node->safe_psql("postgres", "CREATE EXTENSION vector;");
-$node->safe_psql("postgres", "CREATE TABLE tst (i int4, v vector(3));");
-$node->safe_psql("postgres",
-	"INSERT INTO tst SELECT i, ARRAY[random(), random(), random()] FROM generate_series(1, 100000) i;"
-);
-
-# Generate queries
-for (1 .. 20)
-{
-	my $r1 = rand();
-	my $r2 = rand();
-	my $r3 = rand();
-	push(@queries, "[$r1,$r2,$r3]");
-}
-
-# Check each index type
-my @operators = ("<->", "<=>");
-my @opclasses = ("vector_l2_ops", "vector_cosine_ops");
-
-for my $i (0 .. $#operators)
-{
-	my $operator = $operators[$i];
-	my $opclass = $opclasses[$i];
-
-	$node->safe_psql("postgres", "CREATE INDEX idx ON tst USING ivfflat (v $opclass);");
-
-	foreach (@cs)
-	{
-		my $c = $_;
-
-		# Get exact results
-		@expected = ();
-		foreach (@queries)
-		{
-			my $res = $node->safe_psql("postgres", qq(
-				SET enable_indexscan = off;
-				WITH top AS (
-					SELECT v $operator '$_' AS distance FROM tst WHERE i % $c = 0 ORDER BY distance LIMIT $limit
-				)
-				SELECT i FROM tst WHERE (v $operator '$_') <= (SELECT MAX(distance) FROM top)
-			));
-			push(@expected, $res);
-		}
-
-		if ($c == 100)
-		{
-			test_recall($c, 1, 0.57, $operator);
-			test_recall($c, 10, 0.98, $operator);
-		}
-		else
-		{
-			if ($operator eq "<->")
-			{
-				test_recall($c, 1, 0.80, $operator);
-			}
-			else
-			{
-				test_recall($c, 1, 0.88, $operator);
-			}
-		}
-	}
-
-	$node->safe_psql("postgres", "DROP INDEX idx;");
-}
-
-done_testing();
--- a/test/t/043_hnsw_iterative_scan.pl
+++ b/test/t/043_hnsw_iterative_scan.pl
@@ -1,59 +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;
-$node->start;
-
-# Create table
-$node->safe_psql("postgres", "CREATE EXTENSION vector;");
-$node->safe_psql("postgres", "CREATE TABLE tst (i int4 PRIMARY KEY, v vector($dim));");
-$node->safe_psql("postgres",
-	"INSERT INTO tst SELECT i, ARRAY[$array_sql] FROM generate_series(1, 100000) i;"
-);
-$node->safe_psql("postgres", qq(
-	SET maintenance_work_mem = '128MB';
-	SET max_parallel_maintenance_workers = 2;
-	CREATE INDEX ON tst USING hnsw (v vector_l2_ops)
-));
-
-my $count = $node->safe_psql("postgres", qq(
-	SET enable_seqscan = off;
-	SET hnsw.iterative_scan = relaxed_order;
-	SET hnsw.max_scan_tuples = 100000;
-	SET hnsw.scan_mem_multiplier = 2;
-	SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst LIMIT 1) LIMIT 11) t;
-));
-is($count, 10);
-
-foreach ((30000, 50000, 70000))
-{
-	my $max_tuples = $_;
-	my $expected = $max_tuples / 10000;
-	my $sum = 0;
-
-	for my $i (1 .. 20)
-	{
-		$count = $node->safe_psql("postgres", qq(
-			SET enable_seqscan = off;
-			SET hnsw.iterative_scan = relaxed_order;
-			SET hnsw.max_scan_tuples = $max_tuples;
-			SET hnsw.scan_mem_multiplier = 2;
-			SELECT COUNT(*) FROM (SELECT v FROM tst WHERE i % 10000 = 0 ORDER BY v <-> (SELECT v FROM tst WHERE i = $i) LIMIT 11) t;
-		));
-		$sum += $count;
-	}
-
-	my $avg = $sum / 20;
-	cmp_ok($avg, '>', $expected - 2);
-	cmp_ok($avg, '<', $expected + 2);
-}
-
-done_testing();
--- a/test/t/044_hnsw_iterative_scan_recall.pl
+++ b/test/t/044_hnsw_iterative_scan_recall.pl
@@ -1,118 +0,0 @@
-use strict;
-use warnings FATAL => 'all';
-use PostgreSQL::Test::Cluster;
-use PostgreSQL::Test::Utils;
-use Test::More;
-
-my $node;
-my @queries = ();
-my @expected;
-my $limit = 20;
-my $dim = 3;
-my $array_sql = join(",", ('random()') x $dim);
-my @cs = (50, 500);
-
-sub test_recall
-{
-	my ($c, $ef_search, $min, $operator, $mode) = @_;
-	my $correct = 0;
-	my $total = 0;
-
-	my $explain = $node->safe_psql("postgres", qq(
-		SET enable_seqscan = off;
-		SET hnsw.ef_search = $ef_search;
-		SET hnsw.iterative_scan = $mode;
-		EXPLAIN ANALYZE SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[0]' LIMIT $limit;
-	));
-	like($explain, qr/Index Scan using idx on tst/);
-
-	for my $i (0 .. $#queries)
-	{
-		my $actual = $node->safe_psql("postgres", qq(
-			SET enable_seqscan = off;
-			SET hnsw.ef_search = $ef_search;
-			SET hnsw.iterative_scan = $mode;
-			SELECT i FROM tst WHERE i % $c = 0 ORDER BY v $operator '$queries[$i]' LIMIT $limit;
-		));
-		my @actual_ids = split("\n", $actual);
-
-		my @expected_ids = split("\n", $expected[$i]);
-		my %expected_set = map { $_ => 1 } @expected_ids;
-
-		foreach (@actual_ids)
-		{
-			if (exists($expected_set{$_}))
-			{
-				$correct++;
-			}
-		}
-
-		$total += $limit;
-	}
-
-	cmp_ok($correct / $total, ">=", $min, "$operator $mode $c");
-}
-
-# Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
-$node->init;
-$node->start;
-
-# Create table
-$node->safe_psql("postgres", "CREATE EXTENSION vector;");
-$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, 50000) i;"
-);
-
-# Generate queries
-for (1 .. 20)
-{
-	my @r = ();
-	for (1 .. $dim)
-	{
-		push(@r, rand());
-	}
-	push(@queries, "[" . join(",", @r) . "]");
-}
-
-# Check each index type
-my @operators = ("<->", "<=>");
-my @opclasses = ("vector_l2_ops", "vector_cosine_ops");
-
-for my $i (0 .. $#operators)
-{
-	my $operator = $operators[$i];
-	my $opclass = $opclasses[$i];
-
-	$node->safe_psql("postgres", qq(
-		SET maintenance_work_mem = '128MB';
-		CREATE INDEX idx ON tst USING hnsw (v $opclass);
-	));
-
-	foreach (@cs)
-	{
-		my $c = $_;
-
-		# Get exact results
-		@expected = ();
-		foreach (@queries)
-		{
-			my $res = $node->safe_psql("postgres", qq(
-				SET enable_indexscan = off;
-				WITH top AS (
-					SELECT v $operator '$_' AS distance FROM tst WHERE i % $c = 0 ORDER BY distance LIMIT $limit
-				)
-				SELECT i FROM tst WHERE (v $operator '$_') <= (SELECT MAX(distance) FROM top)
-			));
-			push(@expected, $res);
-		}
-
-		test_recall($c, 40, 0.99, $operator, "strict_order");
-		test_recall($c, 40, 0.99, $operator, "relaxed_order");
-	}
-
-	$node->safe_psql("postgres", "DROP INDEX idx;");
-}
-
-done_testing();
--- a/vector.control
+++ b/vector.control
@@ -1,4 +1,4 @@
 comment = 'vector data type and ivfflat and hnsw access methods'
-default_version = '0.8.0'
+default_version = '0.7.4'
 module_pathname = '$libdir/vector'
 relocatable = true