Use f32 [skip ci]

Started Neon intrinsics [skip ci]
2026-07-22 20:15:46 +08:00 · 2024-04-27 23:02:00 -07:00 · 2024-04-27 22:50:47 -07:00
87 changed files with 1155 additions and 2863 deletions
--- a/.github/workflows/build.yml
+++ b/.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
+            os: ubuntu-22.04
          - postgres: 16
            os: ubuntu-22.04
          - 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
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,35 +1,4 @@
-## 0.8.0 (unreleased)
+## 0.7.0 (unreleased)
 - Added support for inline filtering with HNSW
 - Added casts for arrays to `sparsevec`
 - 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)
 - 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)
 - Fixed `failed to add index item` error with `sparsevec`
 - Fixed compilation error with FreeBSD ARM
 - Fixed compilation warning with MSVC and Postgres 16
 ## 0.7.2 (2024-06-11)
 - Fixed initialization fork for indexes on unlogged tables
 ## 0.7.1 (2024-06-03)
 - Improved performance of on-disk HNSW index builds
 - Fixed `undefined symbol` error with GCC 8
 - Fixed compilation error with universal binaries on Mac
 - Fixed compilation warning with Clang < 14
 ## 0.7.0 (2024-04-29)
 - Added `halfvec` type
 - Added `sparsevec` type
--- a/2
+++ b/2
@@ -1,4 +1,4 @@
-ARG PG_MAJOR=17
+ARG PG_MAJOR=16
 FROM postgres:$PG_MAJOR
 ARG PG_MAJOR
--- 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": "0.7.4",
+	"version": "0.6.2",
 	"maintainer": [
 		"Andrew Kane <andrew@ankane.org>"
 	],
@@ -20,7 +20,7 @@
 		"vector": {
 			"file": "sql/vector.sql",
 			"docfile": "README.md",
-			"version": "0.7.4",
+			"version": "0.6.2",
 			"abstract": "Open-source vector similarity search for Postgres"
 		}
 	},
--- a/11
+++ b/11
@@ -1,9 +1,8 @@
 EXTENSION = vector
-EXTVERSION = 0.7.4
+EXTVERSION = 0.6.2
 MODULE_big = vector
-DATA = $(wildcard sql/*--*--*.sql)
+DATA = $(wildcard sql/*--*.sql)
 DATA_built = sql/$(EXTENSION)--$(EXTVERSION).sql
 OBJS = src/bitutils.o src/bitvec.o src/halfutils.o src/halfvec.o src/hnsw.o src/hnswbuild.o src/hnswinsert.o src/hnswscan.o src/hnswutils.o src/hnswvacuum.o src/ivfbuild.o src/ivfflat.o src/ivfinsert.o src/ivfkmeans.o src/ivfscan.o src/ivfutils.o src/ivfvacuum.o src/sparsevec.o src/vector.o
 HEADERS = src/halfvec.h src/sparsevec.h src/vector.h
@@ -43,6 +42,8 @@ all: sql/$(EXTENSION)--$(EXTVERSION).sql
 sql/$(EXTENSION)--$(EXTVERSION).sql: sql/$(EXTENSION).sql
 	cp $< $@
 EXTRA_CLEAN = sql/$(EXTENSION)--$(EXTVERSION).sql
 PG_CONFIG ?= pg_config
 PGXS := $(shell $(PG_CONFIG) --pgxs)
 include $(PGXS)
@@ -52,7 +53,7 @@ ifeq ($(PROVE),)
 	PROVE = prove
 endif
-# for Postgres < 15
+# for Postgres 15
 PROVE_FLAGS += -I ./test/perl
 prove_installcheck:
@@ -66,7 +67,7 @@ dist:
 	git archive --format zip --prefix=$(EXTENSION)-$(EXTVERSION)/ --output dist/$(EXTENSION)-$(EXTVERSION).zip master
 # for Docker
-PG_MAJOR ?= 17
+PG_MAJOR ?= 16
 .PHONY: docker
--- a/Makefile.win
+++ b/Makefile.win
@@ -1,11 +1,10 @@
 EXTENSION = vector
-EXTVERSION = 0.7.4
+EXTVERSION = 0.6.2
 DATA_built = sql\$(EXTENSION)--$(EXTVERSION).sql
 OBJS = src\bitutils.obj src\bitvec.obj src\halfutils.obj src\halfvec.obj src\hnsw.obj src\hnswbuild.obj src\hnswinsert.obj src\hnswscan.obj src\hnswutils.obj src\hnswvacuum.obj src\ivfbuild.obj src\ivfflat.obj src\ivfinsert.obj src\ivfkmeans.obj src\ivfscan.obj src\ivfutils.obj src\ivfvacuum.obj src\sparsevec.obj src\vector.obj
 HEADERS = src\halfvec.h src\sparsevec.h src\vector.h
-REGRESS = bit btree cast copy halfvec hnsw_bit hnsw_halfvec hnsw_sparsevec hnsw_vector ivfflat_bit ivfflat_halfvec ivfflat_vector sparsevec vector_type
+REGRESS = bit btree cast copy halfvec hnsw_bit hnsw_halfvec hnsw_sparsevec hnsw_vector ivfflat_bit ivfflat_halfvec ivfflat_vector sparsevec vector
 REGRESS_OPTS = --inputdir=test --load-extension=$(EXTENSION)
 # For /arch flags
@@ -20,6 +19,11 @@ PG_CFLAGS = $(PG_CFLAGS) $(OPTFLAGS) /O2 /fp:fast
 # https://learn.microsoft.com/en-us/cpp/error-messages/tool-errors/vectorizer-and-parallelizer-messages
 # PG_CFLAGS = $(PG_CFLAGS) /Qvec-report:2
 all: sql\$(EXTENSION)--$(EXTVERSION).sql
 sql\$(EXTENSION)--$(EXTVERSION).sql: sql\$(EXTENSION).sql
 	copy sql\$(EXTENSION).sql $@
 # TODO use pg_config
 !ifndef PGROOT
 !error PGROOT is not set
@@ -39,18 +43,15 @@ SHLIB = $(EXTENSION).dll
 LIBS = "$(LIBDIR)\postgres.lib"
 all: $(SHLIB) $(DATA_built)
 .c.obj:
 	$(CC) $(CFLAGS) /c $< /Fo$@
 $(SHLIB): $(OBJS)
 	$(CC) $(CFLAGS) $(OBJS) $(LIBS) /link /DLL /OUT:$(SHLIB)
-sql\$(EXTENSION)--$(EXTVERSION).sql: sql\$(EXTENSION).sql
+all: $(SHLIB)
 	copy sql\$(EXTENSION).sql $@
-install: all
+install:
 	copy $(SHLIB) "$(PKGLIBDIR)"
 	copy $(EXTENSION).control "$(SHAREDIR)\extension"
 	copy sql\$(EXTENSION)--*.sql "$(SHAREDIR)\extension"
@@ -69,6 +70,6 @@ uninstall:
 clean:
 	del /f $(SHLIB) $(EXTENSION).lib $(EXTENSION).exp
 	del /f $(DATA_built)
 	del /f $(OBJS)
 	del /f sql\$(EXTENSION)--$(EXTVERSION).sql
 	del /f /s /q results regression.diffs regression.out tmp_check tmp_check_iso log output_iso
--- a/README.md
+++ b/README.md
@@ -5,8 +5,7 @@ Open-source vector similarity search for Postgres
 Store your vectors with the rest of your data. Supports:
 - exact and approximate nearest neighbor search
- single-precision, half-precision, binary, and sparse vectors
+- L2 distance, inner product, and cosine distance
 - L2 distance, inner product, cosine distance, L1 distance, Hamming distance, and Jaccard distance
 - any [language](#languages) with a Postgres client
 Plus [ACID](https://en.wikipedia.org/wiki/ACID) compliance, point-in-time recovery, JOINs, and all of the other [great features](https://www.postgresql.org/about/) of Postgres
@@ -21,7 +20,7 @@ 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 v0.6.2 https://github.com/pgvector/pgvector.git
 cd pgvector
 make
 make install # may need sudo
@@ -46,14 +45,12 @@ 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 v0.6.2 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).
@@ -84,7 +81,7 @@ 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 (`<+>`, added in 0.7.0)
+Also supports inner product (`<#>`), cosine distance (`<=>`), and L1 distance (`<+>`, unreleased)
 Note: `<#>` returns the negative inner product since Postgres only supports `ASC` order index scans on operators
@@ -102,15 +99,13 @@ 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);
@@ -148,9 +143,7 @@ Supported distance functions are:
 - `<->` - L2 distance
 - `<#>` - (negative) inner product
 - `<=>` - cosine distance
- `<+>` - L1 distance (added in 0.7.0)
+- `<+>` - L1 distance (unreleased)
 - `<~>` - 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 +201,7 @@ 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
@@ -223,8 +216,6 @@ L2 distance
 CREATE INDEX ON items USING hnsw (embedding vector_l2_ops);
 ```
 Note: Use `halfvec_l2_ops` for `halfvec` and `sparsevec_l2_ops` for `sparsevec` (and similar with the other distance functions)
 Inner product
 ```sql
@@ -237,19 +228,19 @@ Cosine distance
 CREATE INDEX ON items USING hnsw (embedding vector_cosine_ops);
 ```
-L1 distance - added in 0.7.0
+L1 distance - unreleased
 ```sql
 CREATE INDEX ON items USING hnsw (embedding vector_l1_ops);
 ```
-Hamming distance - added in 0.7.0
+Hamming distance - unreleased
 ```sql
 CREATE INDEX ON items USING hnsw (embedding bit_hamming_ops);
 ```
-Jaccard distance - added in 0.7.0
+Jaccard distance - unreleased
 ```sql
 CREATE INDEX ON items USING hnsw (embedding bit_jaccard_ops);
@@ -258,9 +249,9 @@ 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 (added in 0.7.0)
+- `halfvec` - up to 4,000 dimensions (unreleased)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
+- `bit` - up to 64,000 dimensions (unreleased)
- `sparsevec` - up to 1,000 non-zero elements (added in 0.7.0)
+- `sparsevec` - up to 1,000 non-zero elements (unreleased)
 ### Index Options
@@ -353,8 +344,6 @@ L2 distance
 CREATE INDEX ON items USING ivfflat (embedding vector_l2_ops) WITH (lists = 100);
 ```
 Note: Use `halfvec_l2_ops` for `halfvec` (and similar with the other distance functions)
 Inner product
 ```sql
@@ -367,7 +356,7 @@ Cosine distance
 CREATE INDEX ON items USING ivfflat (embedding vector_cosine_ops) WITH (lists = 100);
 ```
-Hamming distance - added in 0.7.0
+Hamming distance - unreleased
 ```sql
 CREATE INDEX ON items USING ivfflat (embedding bit_hamming_ops) WITH (lists = 100);
@@ -376,8 +365,8 @@ 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 (added in 0.7.0)
+- `halfvec` - up to 4,000 dimensions (unreleased)
- `bit` - up to 64,000 dimensions (added in 0.7.0)
+- `bit` - up to 64,000 dimensions (unreleased)
 ### Query Options
@@ -439,12 +428,6 @@ Create an index on one [or more](https://www.postgresql.org/docs/current/indexes
 CREATE INDEX ON items (category_id);
 ```
 Or a composite HNSW index for approximate search (added in 0.8.0)
 ```sql
 CREATE INDEX ON items USING hnsw (embedding vector_l2_ops, category_id);
 ```
 Or a [partial index](https://www.postgresql.org/docs/current/indexes-partial.html) on the vector column for approximate search
 ```sql
@@ -457,9 +440,9 @@ Use [partitioning](https://www.postgresql.org/docs/current/ddl-partitioning.html
 CREATE TABLE items (embedding vector(3), category_id int) PARTITION BY LIST(category_id);
 ```
-## Half-Precision Vectors
+## Half Vectors
-*Added in 0.7.0*
+*Unreleased*
 Use the `halfvec` type to store half-precision vectors
@@ -467,11 +450,11 @@ Use the `halfvec` type to store half-precision vectors
 CREATE TABLE items (id bigserial PRIMARY KEY, embedding halfvec(3));
 ```
-## Half-Precision Indexing
+## Half Indexing
-*Added in 0.7.0*
+*Unreleased*
-Index vectors at half precision for smaller indexes
+Index vectors at half precision for smaller indexes and faster build times
 ```sql
 CREATE INDEX ON items USING hnsw ((embedding::halfvec(3)) halfvec_l2_ops);
@@ -485,30 +468,30 @@ 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));
 INSERT INTO items (embedding) VALUES ('000'), ('111');
 ```
-Get the nearest neighbors by Hamming distance (added in 0.7.0)
+Get the nearest neighbors by Hamming distance
 ```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;
 ```
 Or (unreleased)
 ```sql
 SELECT * FROM items ORDER BY embedding <~> '101' LIMIT 5;
 ```
 Also supports Jaccard distance (`<%>`)
 ## Binary Quantization
-*Added in 0.7.0*
+*Unreleased*
 Use expression indexing for binary quantization
@@ -532,7 +515,7 @@ SELECT * FROM (
 ## Sparse Vectors
-*Added in 0.7.0*
+*Unreleased*
 Use the `sparsevec` type to store sparse vectors
@@ -563,11 +546,11 @@ 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
-*Added in 0.7.0*
+*Unreleased*
 Use expression indexing to index subvectors
@@ -609,7 +592,7 @@ 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);
@@ -699,7 +682,7 @@ 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
@@ -743,7 +726,7 @@ Yes, pgvector uses the write-ahead log (WAL), which allows for replication and p
 #### What if I want to index vectors with more than 2,000 dimensions?
-You can use [half-precision indexing](#half-precision-indexing) to index up to 4,000 dimensions or [binary quantization](#binary-quantization) to index up to 64,000 dimensions. Another option is [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction).
+You’ll need to use [dimensionality reduction](https://en.wikipedia.org/wiki/Dimensionality_reduction) at the moment.
 #### Can I store vectors with different dimensions in the same column?
@@ -806,7 +789,7 @@ SELECT pg_size_pretty(pg_relation_size('index_name'));
 #### Why isn’t a query using an index?
-The query needs to have an `ORDER BY` and `LIMIT`, and the `ORDER BY` must be the result of a distance operator (not an expression) in ascending order.
+The query needs to have an `ORDER BY` and `LIMIT`, and the `ORDER BY` must be the result of a distance operator, not an expression.
 ```sql
 -- index
@@ -881,23 +864,23 @@ Operator | Description | Added
 \+ | element-wise addition |
 \- | element-wise subtraction |
 \* | element-wise multiplication | 0.5.0
-\|\| | concatenate | 0.7.0
+\|\| | concatenate | unreleased
 <-> | Euclidean distance |
 <#> | negative inner product |
 <=> | cosine distance |
-<+> | taxicab distance | 0.7.0
+<+> | taxicab distance | unreleased
 ### Vector Functions
 Function | Description | Added
 --- | --- | ---
-binary_quantize(vector) → bit | binary quantize | 0.7.0
+binary_quantize(vector) → bit | binary quantize | unreleased
 cosine_distance(vector, vector) → double precision | cosine distance |
 inner_product(vector, vector) → double precision | inner product |
 l1_distance(vector, vector) → double precision | taxicab distance | 0.5.0
 l2_distance(vector, vector) → double precision | Euclidean distance |
-l2_normalize(vector) → vector | Normalize with Euclidean norm | 0.7.0
+l2_normalize(vector) → vector | Normalize with Euclidean norm | unreleased
-subvector(vector, integer, integer) → vector | subvector | 0.7.0
+subvector(vector, integer, integer) → vector | subvector | unreleased
 vector_dims(vector) → integer | number of dimensions |
 vector_norm(vector) → double precision | Euclidean norm |
@@ -916,35 +899,35 @@ Each half vector takes `2 * dimensions + 8` bytes of storage. Each element is a
 Operator | Description | Added
 --- | --- | ---
-\+ | element-wise addition | 0.7.0
+\+ | element-wise addition | unreleased
-\- | element-wise subtraction | 0.7.0
+\- | element-wise subtraction | unreleased
-\* | element-wise multiplication | 0.7.0
+\* | element-wise multiplication | unreleased
-\|\| | concatenate | 0.7.0
+\|\| | concatenate | unreleased
-<-> | Euclidean distance | 0.7.0
+<-> | Euclidean distance | unreleased
-<#> | negative inner product | 0.7.0
+<#> | negative inner product | unreleased
-<=> | cosine distance | 0.7.0
+<=> | cosine distance | unreleased
-<+> | taxicab distance | 0.7.0
+<+> | taxicab distance | unreleased
 ### Halfvec Functions
 Function | Description | Added
 --- | --- | ---
-binary_quantize(halfvec) → bit | binary quantize | 0.7.0
+binary_quantize(halfvec) → bit | binary quantize | unreleased
-cosine_distance(halfvec, halfvec) → double precision | cosine distance | 0.7.0
+cosine_distance(halfvec, halfvec) → double precision | cosine distance | unreleased
-inner_product(halfvec, halfvec) → double precision | inner product | 0.7.0
+inner_product(halfvec, halfvec) → double precision | inner product | unreleased
-l1_distance(halfvec, halfvec) → double precision | taxicab distance | 0.7.0
+l1_distance(halfvec, halfvec) → double precision | taxicab distance | unreleased
-l2_distance(halfvec, halfvec) → double precision | Euclidean distance | 0.7.0
+l2_distance(halfvec, halfvec) → double precision | Euclidean distance | unreleased
-l2_norm(halfvec) → double precision | Euclidean norm | 0.7.0
+l2_norm(halfvec) → double precision | Euclidean norm | unreleased
-l2_normalize(halfvec) → halfvec | Normalize with Euclidean norm | 0.7.0
+l2_normalize(halfvec) → halfvec | Normalize with Euclidean norm | unreleased
-subvector(halfvec, integer, integer) → halfvec | subvector | 0.7.0
+subvector(halfvec, integer, integer) → halfvec | subvector | unreleased
-vector_dims(halfvec) → integer | number of dimensions | 0.7.0
+vector_dims(halfvec) → integer | number of dimensions | unreleased
 ### Halfvec Aggregate Functions
 Function | Description | Added
 --- | --- | ---
-avg(halfvec) → halfvec | average | 0.7.0
+avg(halfvec) → halfvec | average | unreleased
-sum(halfvec) → halfvec | sum | 0.7.0
+sum(halfvec) → halfvec | sum | unreleased
 ### Bit Type
@@ -954,15 +937,15 @@ Each bit vector takes `dimensions / 8 + 8` bytes of storage. See the [Postgres d
 Operator | Description | Added
 --- | --- | ---
-<~> | Hamming distance | 0.7.0
+<~> | Hamming distance | unreleased
-<%> | Jaccard distance | 0.7.0
+<%> | Jaccard distance | unreleased
 ### Bit Functions
 Function | Description | Added
 --- | --- | ---
-hamming_distance(bit, bit) → double precision | Hamming distance | 0.7.0
+hamming_distance(bit, bit) → double precision | Hamming distance | unreleased
-jaccard_distance(bit, bit) → double precision | Jaccard distance | 0.7.0
+jaccard_distance(bit, bit) → double precision | Jaccard distance | unreleased
 ### Sparsevec Type
@@ -972,21 +955,21 @@ Each sparse vector takes `8 * non-zero elements + 16` bytes of storage. Each ele
 Operator | Description | Added
 --- | --- | ---
-<-> | Euclidean distance | 0.7.0
+<-> | Euclidean distance | unreleased
-<#> | negative inner product | 0.7.0
+<#> | negative inner product | unreleased
-<=> | cosine distance | 0.7.0
+<=> | cosine distance | unreleased
-<+> | taxicab distance | 0.7.0
+<+> | taxicab distance | unreleased
 ### Sparsevec Functions
 Function | Description | Added
 --- | --- | ---
-cosine_distance(sparsevec, sparsevec) → double precision | cosine distance | 0.7.0
+cosine_distance(sparsevec, sparsevec) → double precision | cosine distance | unreleased
-inner_product(sparsevec, sparsevec) → double precision | inner product | 0.7.0
+inner_product(sparsevec, sparsevec) → double precision | inner product | unreleased
-l1_distance(sparsevec, sparsevec) → double precision | taxicab distance | 0.7.0
+l1_distance(sparsevec, sparsevec) → double precision | taxicab distance | unreleased
-l2_distance(sparsevec, sparsevec) → double precision | Euclidean distance | 0.7.0
+l2_distance(sparsevec, sparsevec) → double precision | Euclidean distance | unreleased
-l2_norm(sparsevec) → double precision | Euclidean norm | 0.7.0
+l2_norm(sparsevec) → double precision | Euclidean norm | unreleased
-l2_normalize(sparsevec) → sparsevec | Normalize with Euclidean norm | 0.7.0
+l2_normalize(sparsevec) → sparsevec | Normalize with Euclidean norm | unreleased
 ## Installation Notes - Linux and Mac
@@ -995,7 +978,7 @@ 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:
@@ -1006,11 +989,11 @@ 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
@@ -1019,10 +1002,10 @@ 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
@@ -1055,17 +1038,17 @@ 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 v0.6.2 https://github.com/pgvector/pgvector.git
 cd pgvector
-docker build --pull --build-arg PG_MAJOR=17 -t myuser/pgvector .
+docker build --build-arg PG_MAJOR=16 -t myuser/pgvector .
 ```
 ### Homebrew
@@ -1076,7 +1059,7 @@ 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
@@ -1091,22 +1074,22 @@ 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
@@ -1195,7 +1178,6 @@ Thanks to:
 - [k-means++: The Advantage of Careful Seeding](https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf)
 - [Concept Decompositions for Large Sparse Text Data using Clustering](https://www.cs.utexas.edu/users/inderjit/public_papers/concept_mlj.pdf)
 - [Efficient and Robust Approximate Nearest Neighbor Search using Hierarchical Navigable Small World Graphs](https://arxiv.org/ftp/arxiv/papers/1603/1603.09320.pdf)
 - [HQANN: Efficient and Robust Similarity Search for Hybrid Queries with Structured and Unstructured Constraints](https://arxiv.org/pdf/2207.07940.pdf)
 ## History
--- a/sql/vector--0.7.0--0.7.1.sql
+++ b/sql/vector--0.7.0--0.7.1.sql
@@ -1,2 +0,0 @@
 -- complain if script is sourced in psql, rather than via CREATE EXTENSION
 \echo Use "ALTER EXTENSION vector UPDATE TO '0.7.1'" to load this file. \quit
--- a/sql/vector--0.7.1--0.7.2.sql
+++ b/sql/vector--0.7.1--0.7.2.sql
@@ -1,2 +0,0 @@
 -- complain if script is sourced in psql, rather than via CREATE EXTENSION
 \echo Use "ALTER EXTENSION vector UPDATE TO '0.7.2'" to load this file. \quit
--- a/sql/vector--0.7.2--0.7.3.sql
+++ b/sql/vector--0.7.2--0.7.3.sql
@@ -1,2 +0,0 @@
 -- complain if script is sourced in psql, rather than via CREATE EXTENSION
 \echo Use "ALTER EXTENSION vector UPDATE TO '0.7.3'" to load this file. \quit
--- a/sql/vector--0.7.3--0.7.4.sql
+++ b/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
--- a/sql/vector--0.7.4--0.8.0.sql
+++ b/sql/vector--0.7.4--0.8.0.sql
@@ -1,34 +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;
 CREATE FUNCTION hnsw_attribute_distance(integer, integer) RETURNS float8
 	AS 'MODULE_PATHNAME', 'hnsw_int4_attribute_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
 CREATE OPERATOR CLASS vector_integer_ops
 	DEFAULT FOR TYPE integer USING hnsw AS
 	OPERATOR 2 = (integer, integer),
 	FUNCTION 4 hnsw_attribute_distance(integer, integer);
--- a/sql/vector.sql
+++ b/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 <-> (
@@ -916,13 +892,3 @@ 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);
 -- hnsw attributes
 CREATE FUNCTION hnsw_attribute_distance(integer, integer) RETURNS float8
 	AS 'MODULE_PATHNAME', 'hnsw_int4_attribute_distance' LANGUAGE C IMMUTABLE STRICT PARALLEL SAFE;
 CREATE OPERATOR CLASS vector_integer_ops
 	DEFAULT FOR TYPE integer USING hnsw AS
 	OPERATOR 2 = (integer, integer),
 	FUNCTION 4 hnsw_attribute_distance(integer, integer);
--- a/src/bitutils.c
+++ b/src/bitutils.c
@@ -11,7 +11,7 @@
 #ifdef BIT_DISPATCH
 #include <immintrin.h>
-#if defined(USE__GET_CPUID)
+#if defined(HAVE__GET_CPUID)
 #include <cpuid.h>
 #else
 #include <intrin.h>
@@ -173,7 +173,7 @@ SupportsAvx512Popcount()
 {
 	unsigned int exx[4] = {0, 0, 0, 0};
-#if defined(USE__GET_CPUID)
+#if defined(HAVE__GET_CPUID)
 	__get_cpuid(1, &exx[0], &exx[1], &exx[2], &exx[3]);
 #else
 	__cpuid(exx, 1);
@@ -187,7 +187,7 @@ SupportsAvx512Popcount()
 	if ((_xgetbv(0) & 0xe6) != 0xe6)
 		return false;
-#if defined(USE__GET_CPUID)
+#if defined(HAVE__GET_CPUID)
 	__get_cpuid_count(7, 0, &exx[0], &exx[1], &exx[2], &exx[3]);
 #else
 	__cpuidex(exx, 7, 0);
--- a/src/bitutils.h
+++ b/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);
--- a/src/bitvec.c
+++ b/src/bitvec.c
@@ -3,7 +3,6 @@
 #include "bitutils.h"
 #include "bitvec.h"
 #include "utils/varbit.h"
 #include "vector.h"
 #if PG_VERSION_NUM >= 160000
 #include "varatt.h"
@@ -41,7 +40,7 @@ CheckDims(VarBit *a, VarBit *b)
 /*
 * Get the Hamming distance between two bit vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hamming_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(hamming_distance);
 Datum
 hamming_distance(PG_FUNCTION_ARGS)
 {
@@ -56,7 +55,7 @@ hamming_distance(PG_FUNCTION_ARGS)
 /*
 * Get the Jaccard distance between two bit vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(jaccard_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(jaccard_distance);
 Datum
 jaccard_distance(PG_FUNCTION_ARGS)
 {
--- a/src/halfutils.c
+++ b/src/halfutils.c
@@ -1,12 +1,14 @@
 #include "postgres.h"
 #include <arm_neon.h>
 #include "halfutils.h"
 #include "halfvec.h"
 #ifdef HALFVEC_DISPATCH
 #include <immintrin.h>
-#if defined(USE__GET_CPUID)
+#if defined(HAVE__GET_CPUID)
 #include <cpuid.h>
 #else
 #include <intrin.h>
@@ -28,9 +30,27 @@ static float
 HalfvecL2SquaredDistanceDefault(int dim, half * ax, half * bx)
 {
 	float		distance = 0.0;
 	int			i = 0;
 /* TODO Improve */
 #ifdef __ARM_FEATURE_FP16_VECTOR_ARITHMETIC
 	int			count = (dim / 4) * 4;
 	float32x4_t dist = vmovq_n_f32(0);
 	for (; i < count; i += 4)
 	{
 		float16x4_t axs = vld1_f16((const __fp16 *) (ax + i));
 		float16x4_t bxs = vld1_f16((const __fp16 *) (bx + i));
 		float32x4_t diff = vsubq_f32(vcvt_f32_f16(axs), vcvt_f32_f16(bxs));
 		dist = vfmaq_f32(dist, diff, diff);
 	}
 	distance += vaddvq_f32(dist);
 #endif
 	/* Auto-vectorized */
-	for (int i = 0; i < dim; i++)
+	for (; i < dim; i++)
 	{
 		float		diff = HalfToFloat4(ax[i]) - HalfToFloat4(bx[i]);
@@ -254,7 +274,7 @@ SupportsCpuFeature(unsigned int feature)
 {
 	unsigned int exx[4] = {0, 0, 0, 0};
-#if defined(USE__GET_CPUID)
+#if defined(HAVE__GET_CPUID)
 	__get_cpuid(1, &exx[0], &exx[1], &exx[2], &exx[3]);
 #else
 	__cpuid(exx, 1);
--- a/src/halfvec.c
+++ b/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))
@@ -159,10 +164,28 @@ 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
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_in);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_in);
 Datum
 halfvec_in(PG_FUNCTION_ARGS)
 {
@@ -276,7 +299,7 @@ halfvec_in(PG_FUNCTION_ARGS)
 /*
 * Convert internal representation to textual representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_out);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_out);
 Datum
 halfvec_out(PG_FUNCTION_ARGS)
 {
@@ -322,7 +345,7 @@ halfvec_out(PG_FUNCTION_ARGS)
 /*
 * Convert type modifier
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_typmod_in);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_typmod_in);
 Datum
 halfvec_typmod_in(PG_FUNCTION_ARGS)
 {
@@ -353,7 +376,7 @@ halfvec_typmod_in(PG_FUNCTION_ARGS)
 /*
 * Convert external binary representation to internal representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_recv);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_recv);
 Datum
 halfvec_recv(PG_FUNCTION_ARGS)
 {
@@ -387,7 +410,7 @@ halfvec_recv(PG_FUNCTION_ARGS)
 /*
 * Convert internal representation to the external binary representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_send);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_send);
 Datum
 halfvec_send(PG_FUNCTION_ARGS)
 {
@@ -407,7 +430,7 @@ halfvec_send(PG_FUNCTION_ARGS)
 * Convert half vector to half vector
 * This is needed to check the type modifier
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec);
 Datum
 halfvec(PG_FUNCTION_ARGS)
 {
@@ -422,7 +445,7 @@ halfvec(PG_FUNCTION_ARGS)
 /*
 * Convert array to half vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(array_to_halfvec);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(array_to_halfvec);
 Datum
 array_to_halfvec(PG_FUNCTION_ARGS)
 {
@@ -496,7 +519,7 @@ array_to_halfvec(PG_FUNCTION_ARGS)
 /*
 * Convert half vector to float4[]
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_to_float4);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_to_float4);
 Datum
 halfvec_to_float4(PG_FUNCTION_ARGS)
 {
@@ -520,7 +543,7 @@ halfvec_to_float4(PG_FUNCTION_ARGS)
 /*
 * Convert vector to half vec
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_to_halfvec);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_halfvec);
 Datum
 vector_to_halfvec(PG_FUNCTION_ARGS)
 {
@@ -542,7 +565,7 @@ vector_to_halfvec(PG_FUNCTION_ARGS)
 /*
 * Get the L2 distance between half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l2_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_distance);
 Datum
 halfvec_l2_distance(PG_FUNCTION_ARGS)
 {
@@ -557,7 +580,7 @@ halfvec_l2_distance(PG_FUNCTION_ARGS)
 /*
 * Get the L2 squared distance between half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l2_squared_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_squared_distance);
 Datum
 halfvec_l2_squared_distance(PG_FUNCTION_ARGS)
 {
@@ -572,7 +595,7 @@ halfvec_l2_squared_distance(PG_FUNCTION_ARGS)
 /*
 * Get the inner product of two half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_inner_product);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_inner_product);
 Datum
 halfvec_inner_product(PG_FUNCTION_ARGS)
 {
@@ -587,7 +610,7 @@ halfvec_inner_product(PG_FUNCTION_ARGS)
 /*
 * Get the negative inner product of two half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_negative_inner_product);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_negative_inner_product);
 Datum
 halfvec_negative_inner_product(PG_FUNCTION_ARGS)
 {
@@ -602,7 +625,7 @@ halfvec_negative_inner_product(PG_FUNCTION_ARGS)
 /*
 * Get the cosine distance between two half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_cosine_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_cosine_distance);
 Datum
 halfvec_cosine_distance(PG_FUNCTION_ARGS)
 {
@@ -634,7 +657,7 @@ halfvec_cosine_distance(PG_FUNCTION_ARGS)
 * Currently uses angular distance since needs to satisfy triangle inequality
 * Assumes inputs are unit vectors (skips norm)
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_spherical_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_spherical_distance);
 Datum
 halfvec_spherical_distance(PG_FUNCTION_ARGS)
 {
@@ -658,7 +681,7 @@ halfvec_spherical_distance(PG_FUNCTION_ARGS)
 /*
 * Get the L1 distance between two half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l1_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l1_distance);
 Datum
 halfvec_l1_distance(PG_FUNCTION_ARGS)
 {
@@ -673,7 +696,7 @@ halfvec_l1_distance(PG_FUNCTION_ARGS)
 /*
 * Get the dimensions of a half vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_vector_dims);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_vector_dims);
 Datum
 halfvec_vector_dims(PG_FUNCTION_ARGS)
 {
@@ -685,7 +708,7 @@ halfvec_vector_dims(PG_FUNCTION_ARGS)
 /*
 * Get the L2 norm of a half vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l2_norm);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_norm);
 Datum
 halfvec_l2_norm(PG_FUNCTION_ARGS)
 {
@@ -707,7 +730,7 @@ halfvec_l2_norm(PG_FUNCTION_ARGS)
 /*
 * Normalize a half vector with the L2 norm
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_l2_normalize);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_l2_normalize);
 Datum
 halfvec_l2_normalize(PG_FUNCTION_ARGS)
 {
@@ -746,7 +769,7 @@ halfvec_l2_normalize(PG_FUNCTION_ARGS)
 /*
 * Add half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_add);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_add);
 Datum
 halfvec_add(PG_FUNCTION_ARGS)
 {
@@ -785,7 +808,7 @@ halfvec_add(PG_FUNCTION_ARGS)
 /*
 * Subtract half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_sub);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_sub);
 Datum
 halfvec_sub(PG_FUNCTION_ARGS)
 {
@@ -824,7 +847,7 @@ halfvec_sub(PG_FUNCTION_ARGS)
 /*
 * Multiply half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_mul);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_mul);
 Datum
 halfvec_mul(PG_FUNCTION_ARGS)
 {
@@ -866,7 +889,7 @@ halfvec_mul(PG_FUNCTION_ARGS)
 /*
 * Concatenate half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_concat);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_concat);
 Datum
 halfvec_concat(PG_FUNCTION_ARGS)
 {
@@ -890,7 +913,7 @@ halfvec_concat(PG_FUNCTION_ARGS)
 /*
 * Quantize a half vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_binary_quantize);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_binary_quantize);
 Datum
 halfvec_binary_quantize(PG_FUNCTION_ARGS)
 {
@@ -908,7 +931,7 @@ halfvec_binary_quantize(PG_FUNCTION_ARGS)
 /*
 * Get a subvector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_subvector);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_subvector);
 Datum
 halfvec_subvector(PG_FUNCTION_ARGS)
 {
@@ -982,7 +1005,7 @@ halfvec_cmp_internal(HalfVector * a, HalfVector * b)
 /*
 * Less than
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_lt);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_lt);
 Datum
 halfvec_lt(PG_FUNCTION_ARGS)
 {
@@ -995,7 +1018,7 @@ halfvec_lt(PG_FUNCTION_ARGS)
 /*
 * Less than or equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_le);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_le);
 Datum
 halfvec_le(PG_FUNCTION_ARGS)
 {
@@ -1008,7 +1031,7 @@ halfvec_le(PG_FUNCTION_ARGS)
 /*
 * Equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_eq);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_eq);
 Datum
 halfvec_eq(PG_FUNCTION_ARGS)
 {
@@ -1021,7 +1044,7 @@ halfvec_eq(PG_FUNCTION_ARGS)
 /*
 * Not equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_ne);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_ne);
 Datum
 halfvec_ne(PG_FUNCTION_ARGS)
 {
@@ -1034,7 +1057,7 @@ halfvec_ne(PG_FUNCTION_ARGS)
 /*
 * Greater than or equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_ge);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_ge);
 Datum
 halfvec_ge(PG_FUNCTION_ARGS)
 {
@@ -1047,7 +1070,7 @@ halfvec_ge(PG_FUNCTION_ARGS)
 /*
 * Greater than
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_gt);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_gt);
 Datum
 halfvec_gt(PG_FUNCTION_ARGS)
 {
@@ -1060,7 +1083,7 @@ halfvec_gt(PG_FUNCTION_ARGS)
 /*
 * Compare half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_cmp);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_cmp);
 Datum
 halfvec_cmp(PG_FUNCTION_ARGS)
 {
@@ -1073,7 +1096,7 @@ halfvec_cmp(PG_FUNCTION_ARGS)
 /*
 * Accumulate half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_accum);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_accum);
 Datum
 halfvec_accum(PG_FUNCTION_ARGS)
 {
@@ -1134,7 +1157,7 @@ halfvec_accum(PG_FUNCTION_ARGS)
 /*
 * Average half vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_avg);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_avg);
 Datum
 halfvec_avg(PG_FUNCTION_ARGS)
 {
@@ -1168,7 +1191,7 @@ halfvec_avg(PG_FUNCTION_ARGS)
 /*
 * Convert sparse vector to half vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_to_halfvec);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_to_halfvec);
 Datum
 sparsevec_to_halfvec(PG_FUNCTION_ARGS)
 {
--- a/src/halfvec.h
+++ b/src/halfvec.h
@@ -9,7 +9,7 @@
 /* TODO Move to better place */
 #ifndef DISABLE_DISPATCH
 /* Only enable for more recent compilers to keep build process simple */
-#if defined(__x86_64__) && defined(__GNUC__) && __GNUC__ >= 9
+#if defined(__x86_64__) && defined(__GNUC__) && __GNUC__ >= 8
 #define USE_DISPATCH
 #elif defined(__x86_64__) && defined(__clang_major__) && __clang_major__ >= 7
 #define USE_DISPATCH
@@ -19,17 +19,9 @@
 #endif
 /* target_clones requires glibc */
-#if defined(USE_DISPATCH) && defined(__gnu_linux__) && defined(__has_attribute)
+#if defined(USE_DISPATCH) && defined(__gnu_linux__)
 /* Use separate line for portability */
 #if __has_attribute(target_clones)
 #define USE_TARGET_CLONES
 #endif
 #endif
 /* Apple clang check needed for universal binaries on Mac */
 #if defined(USE_DISPATCH) && (defined(HAVE__GET_CPUID) || defined(__apple_build_version__))
 #define USE__GET_CPUID
 #endif
 #if defined(USE_DISPATCH)
 #define HALFVEC_DISPATCH
@@ -38,7 +30,7 @@
 /* F16C has better performance than _Float16 (on x86-64) */
 #if defined(__F16C__)
 #define F16C_SUPPORT
-#elif defined(__FLT16_MAX__) && !defined(HALFVEC_DISPATCH) && !defined(__FreeBSD__) && (!defined(__i386__) || defined(__SSE2__))
+#elif defined(__FLT16_MAX__) && !defined(HALFVEC_DISPATCH)
 #define FLT16_SUPPORT
 #endif
--- a/src/hnsw.c
+++ b/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
 }
 /*
@@ -220,20 +187,22 @@ hnswvalidate(Oid opclassoid)
 *
 * See https://www.postgresql.org/docs/current/index-api.html
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(hnswhandler);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(hnswhandler);
 Datum
 hnswhandler(PG_FUNCTION_ARGS)
 {
 	IndexAmRoutine *amroutine = makeNode(IndexAmRoutine);
 	amroutine->amstrategies = 0;
-	amroutine->amsupport = 4;
+	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 */
 	amroutine->amcanunique = false;
-	amroutine->amcanmulticol = true;
+	amroutine->amcanmulticol = false;
 	amroutine->amoptionalkey = true;
 	amroutine->amsearcharray = false;
 	amroutine->amsearchnulls = false;
@@ -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;
@@ -285,17 +247,3 @@ hnswhandler(PG_FUNCTION_ARGS)
 	PG_RETURN_POINTER(amroutine);
 }
 /*
 * Get the distance between two int4 attributes
 */
 PGDLLEXPORT PG_FUNCTION_INFO_V1(hnsw_int4_attribute_distance);
 Datum
 hnsw_int4_attribute_distance(PG_FUNCTION_ARGS)
 {
 	int32		a = PG_GETARG_INT32(0);
 	int32		b = PG_GETARG_INT32(1);
 	double		distance = ((double) a) - ((double) b);
 	PG_RETURN_FLOAT8(distance);
 }
--- a/src/hnsw.h
+++ b/src/hnsw.h
@@ -19,7 +19,6 @@
 #define HNSW_DISTANCE_PROC 1
 #define HNSW_NORM_PROC 2
 #define HNSW_TYPE_INFO_PROC 3
 #define HNSW_ATTRIBUTE_DISTANCE_PROC 4
 #define HNSW_VERSION	1
 #define HNSW_MAGIC_NUMBER 0xA953A953
@@ -77,6 +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)
@@ -105,8 +109,6 @@
 #define HnswPtrPointer(hp) (hp).ptr
 #define HnswPtrOffset(hp) relptr_offset((hp).relptr)
 #define HnswUseIndexTuple(index) (IndexRelationGetNumberOfAttributes(index) > 1)
 /* Variables */
 extern int	hnsw_ef_search;
 extern int	hnsw_lock_tranche_id;
@@ -124,7 +126,6 @@ HnswPtrDeclare(HnswElementData, HnswElementRelptr, HnswElementPtr);
 HnswPtrDeclare(HnswNeighborArray, HnswNeighborArrayRelptr, HnswNeighborArrayPtr);
 HnswPtrDeclare(HnswNeighborArrayPtr, HnswNeighborsRelptr, HnswNeighborsPtr);
 HnswPtrDeclare(char, DatumRelptr, DatumPtr);
 HnswPtrDeclare(IndexTupleData, IndexTupleRelptr, IndexTuplePtr);
 struct HnswElementData
 {
@@ -140,7 +141,6 @@ struct HnswElementData
 	OffsetNumber neighborOffno;
 	BlockNumber neighborPage;
 	DatumPtr	value;
 	IndexTuplePtr itup;
 	LWLock		lock;
 };
@@ -160,14 +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;
 	double		distance;
 	bool		matches;
 }			HnswSearchCandidate;
 /* HNSW index options */
 typedef struct HnswOptions
@@ -191,8 +188,8 @@ typedef struct HnswGraph
 	/* Allocations state */
 	LWLock		allocatorLock;
-	Size		memoryUsed;
+	long		memoryUsed;
-	Size		memoryTotal;
+	long		memoryTotal;
 	/* Flushed state */
 	LWLock		flushLock;
@@ -262,17 +259,15 @@ typedef struct HnswBuildState
 	double		reltuples;
 	/* Support functions */
-	FmgrInfo   *procinfo[2];
+	FmgrInfo   *procinfo;
 	FmgrInfo   *normprocinfo;
-	Oid		   *collation;
+	Oid			collation;
 	/* Variables */
 	HnswGraph	graphData;
 	HnswGraph  *graph;
 	double		ml;
 	int			maxLevel;
 	bool		useIndexTuple;
 	TupleDesc	tupdesc;
 	/* Memory */
 	MemoryContext graphCtx;
@@ -341,9 +336,9 @@ typedef struct HnswScanOpaqueData
 	MemoryContext tmpCtx;
 	/* Support functions */
-	FmgrInfo   *procinfo[2];
+	FmgrInfo   *procinfo;
 	FmgrInfo   *normprocinfo;
-	Oid		   *collation;
+	Oid			collation;
 }			HnswScanOpaqueData;
 typedef HnswScanOpaqueData * HnswScanOpaque;
@@ -361,8 +356,8 @@ typedef struct HnswVacuumState
 	int			efConstruction;
 	/* Support functions */
-	FmgrInfo   *procinfo[2];
+	FmgrInfo   *procinfo;
-	Oid		   *collation;
+	Oid			collation;
 	/* Variables */
 	struct tidhash_hash *deleted;
@@ -383,32 +378,28 @@ bool		HnswCheckNorm(FmgrInfo *procinfo, Oid collation, Datum value);
 Buffer		HnswNewBuffer(Relation index, ForkNumber forkNum);
 void		HnswInitPage(Buffer buf, Page page);
 void		HnswInit(void);
-List	   *HnswSearchLayer(char *base, Datum q, IndexTuple qtup, ScanKeyData *keyData, List *ep, int ef, int lc, Relation index, FmgrInfo **procinfo, Oid *collation, int m, bool inserting, HnswElement skipElement, bool inMemory);
+List	   *HnswSearchLayer(char *base, Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *procinfo, Oid collation, int m, bool inserting, HnswElement skipElement);
 HnswElement HnswGetEntryPoint(Relation index);
 void		HnswGetMetaPageInfo(Relation index, int *m, HnswElement * entryPoint);
 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, bool inMemory);
+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, IndexTuple qtup, ScanKeyData *keyData, Relation rel, FmgrInfo **procinfo, Oid *collation, bool loadVec, bool inMemory);
+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);
 HnswNeighborArray *HnswInitNeighborArray(int lm, HnswAllocator * allocator);
 void		HnswInitNeighbors(char *base, HnswElement element, int m, HnswAllocator * alloc);
 bool		HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull, ItemPointer heap_tid, bool building);
-void		HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo **procinfo, Oid *collation, HnswElement e, int m, bool checkExisting, bool building);
+void		HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building);
-void		HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec, Relation index);
+void		HnswLoadElementFromTuple(HnswElement element, HnswElementTuple etup, bool loadHeaptids, bool loadVec);
-void		HnswLoadElement(HnswElement element, double *distance, bool *matches, Datum *q, IndexTuple qtup, ScanKeyData *keyData, Relation index, FmgrInfo **procinfo, Oid *collation, bool loadVec, double *maxDistance);
+void		HnswLoadElement(HnswElement element, float *distance, Datum *q, Relation index, FmgrInfo *procinfo, Oid collation, bool loadVec);
-void		HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element, bool useIndexTuple);
+void		HnswSetElementTuple(char *base, HnswElementTuple etup, HnswElement element);
-void		HnswUpdateConnection(char *base, HnswNeighborArray * neighbors, HnswElement newElement, float distance, int lm, int *updateIdx, Relation index, FmgrInfo **procinfo, Oid *collation);
+void		HnswUpdateConnection(char *base, HnswElement element, HnswCandidate * hc, int lm, int lc, int *updateIdx, Relation index, FmgrInfo *procinfo, Oid collation);
-bool		HnswLoadNeighborTids(HnswElement element, ItemPointerData *indextids, Relation index, int m, int lm, int lc);
+void		HnswLoadNeighbors(HnswElement element, Relation index, int m);
 void		HnswInitLockTranche(void);
 const		HnswTypeInfo *HnswGetTypeInfo(Relation index);
 PGDLLEXPORT void HnswParallelBuildMain(dsm_segment *seg, shm_toc *toc);
 void		HnswInitProcinfo(FmgrInfo **procinfo, Oid **collation, Relation index);
 Size		HnswGetElementTupleSize(char *base, HnswElement element, bool useIndexTuple);
 bool		HnswIndexTupleIsEqual(IndexTuple a, IndexTuple b, TupleDesc tupdesc);
 /* Index access methods */
 IndexBuildResult *hnswbuild(Relation heap, Relation index, IndexInfo *indexInfo);
--- a/src/hnswbuild.c
+++ b/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
 */
@@ -148,7 +158,6 @@ CreateGraphPages(HnswBuildState * buildstate)
 	Page		page;
 	HnswElementPtr iter = buildstate->graph->head;
 	char	   *base = buildstate->hnswarea;
 	bool		useIndexTuple = buildstate->useIndexTuple;
 	/* Calculate sizes */
 	maxSize = HNSW_MAX_SIZE;
@@ -168,6 +177,7 @@ CreateGraphPages(HnswBuildState * buildstate)
 		Size		etupSize;
 		Size		ntupSize;
 		Size		combinedSize;
 		Pointer		valuePtr = HnswPtrAccess(base, element->value);
 		/* Update iterator */
 		iter = element->next;
@@ -176,17 +186,15 @@ CreateGraphPages(HnswBuildState * buildstate)
 		MemSet(etup, 0, HNSW_TUPLE_ALLOC_SIZE);
 		/* Calculate sizes */
-		etupSize = HnswGetElementTupleSize(base, element, useIndexTuple);
+		etupSize = HNSW_ELEMENT_TUPLE_SIZE(VARSIZE_ANY(valuePtr));
 		ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, buildstate->m);
 		combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
 		/* 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, useIndexTuple);
+		HnswSetElementTuple(base, etup, element);
 		/* Keep element and neighbors on the same page if possible */
 		if (PageGetFreeSpace(page) < etupSize || (combinedSize <= maxSize && PageGetFreeSpace(page) < combinedSize))
@@ -327,29 +335,20 @@ AddDuplicateInMemory(HnswElement element, HnswElement dup)
 * Find duplicate element
 */
 static bool
-FindDuplicateInMemory(char *base, HnswElement element, bool useIndexTuple, TupleDesc tupdesc)
+FindDuplicateInMemory(char *base, HnswElement element)
 {
 	HnswNeighborArray *neighbors = HnswGetNeighbors(base, element, 0);
 	Datum		value = HnswGetValue(base, element);
 	IndexTuple	itup = HnswPtrAccess(base, element->itup);
 	for (int i = 0; i < neighbors->length; i++)
 	{
 		HnswCandidate *neighbor = &neighbors->items[i];
 		HnswElement neighborElement = HnswPtrAccess(base, neighbor->element);
 		Datum		neighborValue = HnswGetValue(base, neighborElement);
-		if (useIndexTuple)
+		/* Exit early since ordered by distance */
-		{
+		if (!datumIsEqual(value, neighborValue, false, -1))
-			/* Exit early since ordered by distance */
+			return false;
 			if (!HnswIndexTupleIsEqual(itup, HnswPtrAccess(base, neighborElement->itup), tupdesc))
 				return false;
 		}
 		else
 		{
 			/* Exit early since ordered by distance */
 			if (!datumIsEqual(value, HnswGetValue(base, neighborElement), false, -1))
 				return false;
 		}
 		/* Check for space */
 		if (AddDuplicateInMemory(element, neighborElement))
@@ -375,18 +374,12 @@ AddElementInMemory(char *base, HnswGraph * graph, HnswElement element)
 * Update neighbors
 */
 static void
-UpdateNeighborsInMemory(char *base, Relation index, FmgrInfo **procinfo, Oid *collation, HnswElement e, int m)
+UpdateNeighborsInMemory(char *base, FmgrInfo *procinfo, Oid collation, HnswElement e, int m)
 {
 	for (int lc = e->level; lc >= 0; lc--)
 	{
 		int			lm = HnswGetLayerM(m, lc);
-		Size		neighborsSize = HNSW_NEIGHBOR_ARRAY_SIZE(lm);
+		HnswNeighborArray *neighbors = HnswGetNeighbors(base, e, lc);
 		HnswNeighborArray *neighbors = palloc(neighborsSize);
 		/* Copy neighbors to local memory */
 		LWLockAcquire(&e->lock, LW_SHARED);
 		memcpy(neighbors, HnswGetNeighbors(base, e, lc), neighborsSize);
 		LWLockRelease(&e->lock);
 		for (int i = 0; i < neighbors->length; i++)
 		{
@@ -396,8 +389,9 @@ UpdateNeighborsInMemory(char *base, Relation index, FmgrInfo **procinfo, Oid *co
 			/* Keep scan-build happy on Mac x86-64 */
 			Assert(neighborElement);
 			/* Use element for lock instead of hc since hc can be replaced */
 			LWLockAcquire(&neighborElement->lock, LW_EXCLUSIVE);
-			HnswUpdateConnection(base, HnswGetNeighbors(base, neighborElement, lc), e, hc->distance, lm, NULL, index, procinfo, collation);
+			HnswUpdateConnection(base, e, hc, lm, lc, NULL, NULL, procinfo, collation);
 			LWLockRelease(&neighborElement->lock);
 		}
 	}
@@ -407,20 +401,20 @@ UpdateNeighborsInMemory(char *base, Relation index, FmgrInfo **procinfo, Oid *co
 * Update graph in memory
 */
 static void
-UpdateGraphInMemory(FmgrInfo **procinfo, Oid *collation, HnswElement element, int m, int efConstruction, HnswElement entryPoint, HnswBuildState * buildstate)
+UpdateGraphInMemory(FmgrInfo *procinfo, Oid collation, HnswElement element, int m, int efConstruction, HnswElement entryPoint, HnswBuildState * buildstate)
 {
 	HnswGraph  *graph = buildstate->graph;
 	char	   *base = buildstate->hnswarea;
 	/* Look for duplicate */
-	if (FindDuplicateInMemory(base, element, buildstate->useIndexTuple, buildstate->tupdesc))
+	if (FindDuplicateInMemory(base, element))
 		return;
 	/* Add element */
 	AddElementInMemory(base, graph, element);
 	/* Update neighbors */
-	UpdateNeighborsInMemory(base, buildstate->index, procinfo, collation, element, m);
+	UpdateNeighborsInMemory(base, procinfo, collation, element, m);
 	/* Update entry point if needed (already have lock) */
 	if (entryPoint == NULL || element->level > entryPoint->level)
@@ -433,9 +427,8 @@ UpdateGraphInMemory(FmgrInfo **procinfo, Oid *collation, HnswElement element, in
 static void
 InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
 {
-	Relation	index = buildstate->index;
+	FmgrInfo   *procinfo = buildstate->procinfo;
-	FmgrInfo  **procinfo = buildstate->procinfo;
+	Oid			collation = buildstate->collation;
 	Oid		   *collation = buildstate->collation;
 	HnswGraph  *graph = buildstate->graph;
 	HnswElement entryPoint;
 	LWLock	   *entryLock = &graph->entryLock;
@@ -468,7 +461,7 @@ InsertTupleInMemory(HnswBuildState * buildstate, HnswElement element)
 	}
 	/* Find neighbors for element */
-	HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, false, true);
+	HnswFindElementNeighbors(base, element, entryPoint, NULL, procinfo, collation, m, efConstruction, false);
 	/* Update graph in memory */
 	UpdateGraphInMemory(procinfo, collation, element, m, efConstruction, entryPoint, buildstate);
@@ -491,11 +484,6 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
 	Pointer		valuePtr;
 	LWLock	   *flushLock = &graph->flushLock;
 	char	   *base = buildstate->hnswarea;
 	bool		useIndexTuple = buildstate->useIndexTuple;
 	TupleDesc	tupdesc = buildstate->tupdesc;
 	IndexTuple	itup;
 	Size		itupSize;
 	IndexTuple	itupPtr;
 	/* Detoast once for all calls */
 	Datum		value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
@@ -507,10 +495,10 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
 	/* Normalize if needed */
 	if (buildstate->normprocinfo != NULL)
 	{
-		if (!HnswCheckNorm(buildstate->normprocinfo, buildstate->collation[0], value))
+		if (!HnswCheckNorm(buildstate->normprocinfo, buildstate->collation, value))
 			return false;
-		value = HnswNormValue(typeInfo, buildstate->collation[0], value);
+		value = HnswNormValue(typeInfo, buildstate->collation, value);
 	}
 	/* Get datum size */
@@ -561,17 +549,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
 	/* Ok, we can proceed to allocate the element */
 	element = HnswInitElement(base, heaptid, buildstate->m, buildstate->ml, buildstate->maxLevel, allocator);
-
+	valuePtr = HnswAlloc(allocator, valueSize);
 	if (useIndexTuple)
 	{
 		/* TODO fix */
 		values[0] = value;
 		itup = index_form_tuple(tupdesc, values, isnull);
 		itupSize = IndexTupleSize(itup);
 		itupPtr = HnswAlloc(allocator, itupSize);
 	}
 	else
 		valuePtr = HnswAlloc(allocator, valueSize);
 	/*
 	 * We have now allocated the space needed for the element, so we don't
@@ -581,19 +559,8 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heaptid, Hn
 	LWLockRelease(&graph->allocatorLock);
 	/* Copy the datum */
-	if (useIndexTuple)
+	memcpy(valuePtr, DatumGetPointer(value), valueSize);
-	{
+	HnswPtrStore(base, element->value, valuePtr);
 		bool		unused;
 		memcpy(itupPtr, itup, itupSize);
 		HnswPtrStore(base, element->itup, itupPtr);
 		HnswPtrStore(base, element->value, DatumGetPointer(index_getattr(itupPtr, 1, tupdesc, &unused)));
 	}
 	else
 	{
 		memcpy(valuePtr, DatumGetPointer(value), valueSize);
 		HnswPtrStore(base, element->value, valuePtr);
 	}
 	/* Create a lock for the element */
 	LWLockInitialize(&element->lock, hnsw_lock_tranche_id);
@@ -611,13 +578,17 @@ 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;
@@ -643,7 +614,7 @@ BuildCallback(Relation index, ItemPointer tid, Datum *values,
 * Initialize the graph
 */
 static void
-InitGraph(HnswGraph * graph, char *base, Size memoryTotal)
+InitGraph(HnswGraph * graph, char *base, long memoryTotal)
 {
 	/* Initialize the lock tranche if needed */
 	HnswInitLockTranche();
@@ -680,7 +651,11 @@ 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;
 }
@@ -716,52 +691,30 @@ 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")));
 	/* TODO See if needed */
 	if (IndexRelationGetNumberOfKeyAttributes(index) > 2)
 		elog(ERROR, "index cannot have more than two columns");
 	if (!OidIsValid(index_getprocid(index, 1, HNSW_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, HNSW_ATTRIBUTE_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,
+		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;
 	/* Get support functions */
-	HnswInitProcinfo(buildstate->procinfo, &buildstate->collation, index);
+	buildstate->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
 	buildstate->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
 	buildstate->collation = index->rd_indcollation[0];
-	InitGraph(&buildstate->graphData, NULL, (Size) maintenance_work_mem * 1024L);
+	InitGraph(&buildstate->graphData, NULL, maintenance_work_mem * 1024L);
 	buildstate->graph = &buildstate->graphData;
 	buildstate->ml = HnswGetMl(buildstate->m);
 	buildstate->maxLevel = HnswGetMaxLevel(buildstate->m);
 	buildstate->useIndexTuple = HnswUseIndexTuple(index);
 	buildstate->tupdesc = RelationGetDescr(index);
 	buildstate->graphCtx = GenerationContextCreate(CurrentMemoryContext,
 												   "Hnsw build graph context",
@@ -1168,8 +1121,8 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
 	BuildGraph(buildstate, forkNum);
-	if (RelationNeedsWAL(index) || forkNum == INIT_FORKNUM)
+	if (RelationNeedsWAL(index))
-		log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true);
+		log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocks(index), true);
 	FreeBuildState(buildstate);
 }
--- a/src/hnswinsert.c
+++ b/src/hnswinsert.c
@@ -36,15 +36,14 @@ 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)
+HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size ntupSize, Buffer *nbuf, Page *npage, OffsetNumber *freeOffno, OffsetNumber *freeNeighborOffno, BlockNumber *newInsertPage)
 {
 	OffsetNumber offno;
 	OffsetNumber maxoffno = PageGetMaxOffsetNumber(page);
 	for (offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
 	{
-		ItemId		eitemid = PageGetItemId(page, offno);
+		HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, PageGetItemId(page, offno));
 		HnswElementTuple etup = (HnswElementTuple) PageGetItem(page, eitemid);
 		/* Skip neighbor tuples */
 		if (!HnswIsElementTuple(etup))
@@ -55,9 +54,7 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
 			BlockNumber elementPage = BufferGetBlockNumber(buf);
 			BlockNumber neighborPage = ItemPointerGetBlockNumber(&etup->neighbortid);
 			OffsetNumber neighborOffno = ItemPointerGetOffsetNumber(&etup->neighbortid);
-			ItemId		nitemid;
+			ItemId		itemid;
 			Size		pageFree;
 			Size		npageFree;
 			if (!BlockNumberIsValid(*newInsertPage))
 				*newInsertPage = elementPage;
@@ -76,25 +73,10 @@ HnswFreeOffset(Relation index, Buffer buf, Page page, HnswElement element, Size
 				*npage = BufferGetPage(*nbuf);
 			}
-			nitemid = PageGetItemId(*npage, neighborOffno);
+			itemid = PageGetItemId(*npage, neighborOffno);
-			/* Ensure aligned for space check */
+			/* Check for space on neighbor tuple page */
-			Assert(etupSize == MAXALIGN(etupSize));
+			if (PageGetFreeSpace(*npage) + ItemIdGetLength(itemid) - sizeof(ItemIdData) >= ntupSize)
 			Assert(ntupSize == MAXALIGN(ntupSize));
 			/*
 			 * Calculate free space individually since tuples are overwritten
 			 * individually (in separate calls to PageIndexTupleOverwrite)
 			 */
 			pageFree = ItemIdGetLength(eitemid) + PageGetExactFreeSpace(page);
 			npageFree = ItemIdGetLength(nitemid);
 			if (neighborPage != elementPage)
 				npageFree += PageGetExactFreeSpace(*npage);
 			else if (pageFree >= etupSize)
 				npageFree += pageFree - etupSize;
 			/* Check for space */
 			if (pageFree >= etupSize && npageFree >= ntupSize)
 			{
 				*freeOffno = offno;
 				*freeNeighborOffno = neighborOffno;
@@ -154,10 +136,9 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
 	OffsetNumber freeNeighborOffno = InvalidOffsetNumber;
 	BlockNumber newInsertPage = InvalidBlockNumber;
 	char	   *base = NULL;
 	bool		useIndexTuple = HnswUseIndexTuple(index);
 	/* Calculate sizes */
-	etupSize = HnswGetElementTupleSize(base, e, useIndexTuple);
+	etupSize = HNSW_ELEMENT_TUPLE_SIZE(VARSIZE_ANY(HnswPtrAccess(base, e->value)));
 	ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
 	combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
 	maxSize = HNSW_MAX_SIZE;
@@ -165,7 +146,7 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
 	/* Prepare element tuple */
 	etup = palloc0(etupSize);
-	HnswSetElementTuple(base, etup, e, useIndexTuple);
+	HnswSetElementTuple(base, etup, e);
 	/* Prepare neighbor tuple */
 	ntup = palloc0(ntupSize);
@@ -203,7 +184,7 @@ 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))
+		if (HnswFreeOffset(index, buf, page, e, ntupSize, &nbuf, &npage, &freeOffno, &freeNeighborOffno, &newInsertPage))
 		{
 			if (nbuf != buf)
 			{
@@ -335,107 +316,6 @@ AddElementOnDisk(Relation index, HnswElement e, int m, BlockNumber insertPage, B
 		*updatedInsertPage = newInsertPage;
 }
 /*
 * Load neighbors
 */
 static HnswNeighborArray *
 HnswLoadNeighbors(HnswElement element, Relation index, int m, int lm, int lc)
 {
 	char	   *base = NULL;
 	HnswNeighborArray *neighbors = HnswInitNeighborArray(lm, NULL);
 	ItemPointerData indextids[HNSW_MAX_M * 2];
 	if (!HnswLoadNeighborTids(element, indextids, index, m, lm, lc))
 		return neighbors;
 	for (int i = 0; i < lm; i++)
 	{
 		ItemPointer indextid = &indextids[i];
 		HnswElement e;
 		HnswCandidate *hc;
 		if (!ItemPointerIsValid(indextid))
 			break;
 		e = HnswInitElementFromBlock(ItemPointerGetBlockNumber(indextid), ItemPointerGetOffsetNumber(indextid));
 		hc = &neighbors->items[neighbors->length++];
 		HnswPtrStore(base, hc->element, e);
 	}
 	return neighbors;
 }
 /*
 * Load elements for insert
 */
 static void
 LoadElementsForInsert(HnswNeighborArray * neighbors, Datum q, IndexTuple qtup, int *idx, Relation index, FmgrInfo **procinfo, Oid *collation)
 {
 	char	   *base = NULL;
 	for (int i = 0; i < neighbors->length; i++)
 	{
 		HnswCandidate *hc = &neighbors->items[i];
 		HnswElement element = HnswPtrAccess(base, hc->element);
 		double		distance;
 		bool		matches;
 		HnswLoadElement(element, &distance, &matches, &q, qtup, NULL, index, procinfo, collation, true, NULL);
 		hc->distance = distance;
 		/* Prune element if being deleted */
 		if (element->heaptidsLength == 0)
 		{
 			*idx = i;
 			break;
 		}
 	}
 }
 /*
 * Get update index
 */
 static int
 GetUpdateIndex(HnswElement element, HnswElement newElement, float distance, int m, int lm, int lc, Relation index, FmgrInfo **procinfo, Oid *collation, MemoryContext updateCtx)
 {
 	char	   *base = NULL;
 	int			idx = -1;
 	HnswNeighborArray *neighbors;
 	MemoryContext oldCtx = MemoryContextSwitchTo(updateCtx);
 	/*
 	 * Get latest neighbors since they may have changed. Do not lock yet since
 	 * selecting neighbors can take time. Could use optimistic locking to
 	 * retry if another update occurs before getting exclusive lock.
 	 */
 	neighbors = HnswLoadNeighbors(element, index, m, lm, lc);
 	/*
 	 * Could improve performance for vacuuming by checking neighbors against
 	 * list of elements being deleted to find index. It's important to exclude
 	 * already deleted elements for this since they can be replaced at any
 	 * time.
 	 */
 	if (neighbors->length < lm)
 		idx = -2;
 	else
 	{
 		Datum		q = HnswGetValue(base, element);
 		IndexTuple	qtup = HnswPtrAccess(base, element->itup);;
 		LoadElementsForInsert(neighbors, q, qtup, &idx, index, procinfo, collation);
 		if (idx == -1)
 			HnswUpdateConnection(base, neighbors, newElement, distance, lm, &idx, index, procinfo, collation);
 	}
 	MemoryContextSwitchTo(oldCtx);
 	MemoryContextReset(updateCtx);
 	return idx;
 }
 /*
 * Check if connection already exists
 */
@@ -456,94 +336,14 @@ ConnectionExists(HnswElement e, HnswNeighborTuple ntup, int startIdx, int lm)
 	return false;
 }
 /*
 * Update neighbor
 */
 static void
 UpdateNeighborOnDisk(HnswElement element, HnswElement newElement, int idx, int m, int lm, int lc, Relation index, bool checkExisting, bool building)
 {
 	Buffer		buf;
 	Page		page;
 	GenericXLogState *state;
 	HnswNeighborTuple ntup;
 	int			startIdx;
 	OffsetNumber offno = element->neighborOffno;
 	/* Register page */
 	buf = ReadBuffer(index, element->neighborPage);
 	LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
 	if (building)
 	{
 		state = NULL;
 		page = BufferGetPage(buf);
 	}
 	else
 	{
 		state = GenericXLogStart(index);
 		page = GenericXLogRegisterBuffer(state, buf, 0);
 	}
 	/* Get tuple */
 	ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, offno));
 	/* Calculate index for update */
 	startIdx = (element->level - lc) * m;
 	/* Check for existing connection */
 	if (checkExisting && ConnectionExists(newElement, ntup, startIdx, lm))
 		idx = -1;
 	else if (idx == -2)
 	{
 		/* Find free offset if still exists */
 		/* TODO Retry updating connections if not */
 		for (int j = 0; j < lm; j++)
 		{
 			if (!ItemPointerIsValid(&ntup->indextids[startIdx + j]))
 			{
 				idx = startIdx + j;
 				break;
 			}
 		}
 	}
 	else
 		idx += startIdx;
 	/* Make robust to issues */
 	if (idx >= 0 && idx < ntup->count)
 	{
 		ItemPointer indextid = &ntup->indextids[idx];
 		/* Update neighbor on the buffer */
 		ItemPointerSet(indextid, newElement->blkno, newElement->offno);
 		/* Commit */
 		if (building)
 			MarkBufferDirty(buf);
 		else
 			GenericXLogFinish(state);
 	}
 	else if (!building)
 		GenericXLogAbort(state);
 	UnlockReleaseBuffer(buf);
 }
 /*
 * Update neighbors
 */
 void
-HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo **procinfo, Oid *collation, HnswElement e, int m, bool checkExisting, bool building)
+HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement e, int m, bool checkExisting, bool building)
 {
 	char	   *base = NULL;
 	/* Use separate memory context to improve performance for larger vectors */
 	MemoryContext updateCtx = GenerationContextCreate(CurrentMemoryContext,
 													  "Hnsw insert update context",
 #if PG_VERSION_NUM >= 150000
 													  128 * 1024, 128 * 1024,
 #endif
 													  128 * 1024);
 	for (int lc = e->level; lc >= 0; lc--)
 	{
 		int			lm = HnswGetLayerM(m, lc);
@@ -552,20 +352,92 @@ HnswUpdateNeighborsOnDisk(Relation index, FmgrInfo **procinfo, Oid *collation, H
 		for (int i = 0; i < neighbors->length; i++)
 		{
 			HnswCandidate *hc = &neighbors->items[i];
 			Buffer		buf;
 			Page		page;
 			GenericXLogState *state;
 			HnswNeighborTuple ntup;
 			int			idx = -1;
 			int			startIdx;
 			HnswElement neighborElement = HnswPtrAccess(base, hc->element);
-			int			idx;
+			OffsetNumber offno = neighborElement->neighborOffno;
-			idx = GetUpdateIndex(neighborElement, e, hc->distance, m, lm, lc, index, procinfo, collation, updateCtx);
+			/* Get latest neighbors since they may have changed */
 			/* Do not lock yet since selecting neighbors can take time */
 			HnswLoadNeighbors(neighborElement, index, m);
 			/*
 			 * Could improve performance for vacuuming by checking neighbors
 			 * against list of elements being deleted to find index. It's
 			 * important to exclude already deleted elements for this since
 			 * they can be replaced at any time.
 			 */
 			/* Select neighbors */
 			HnswUpdateConnection(NULL, e, hc, lm, lc, &idx, index, procinfo, collation);
 			/* New element was not selected as a neighbor */
 			if (idx == -1)
 				continue;
-			UpdateNeighborOnDisk(neighborElement, e, idx, m, lm, lc, index, checkExisting, building);
+			/* Register page */
 			buf = ReadBuffer(index, neighborElement->neighborPage);
 			LockBuffer(buf, BUFFER_LOCK_EXCLUSIVE);
 			if (building)
 			{
 				state = NULL;
 				page = BufferGetPage(buf);
 			}
 			else
 			{
 				state = GenericXLogStart(index);
 				page = GenericXLogRegisterBuffer(state, buf, 0);
 			}
 			/* Get tuple */
 			ntup = (HnswNeighborTuple) PageGetItem(page, PageGetItemId(page, offno));
 			/* Calculate index for update */
 			startIdx = (neighborElement->level - lc) * m;
 			/* Check for existing connection */
 			if (checkExisting && ConnectionExists(e, ntup, startIdx, lm))
 				idx = -1;
 			else if (idx == -2)
 			{
 				/* Find free offset if still exists */
 				/* TODO Retry updating connections if not */
 				for (int j = 0; j < lm; j++)
 				{
 					if (!ItemPointerIsValid(&ntup->indextids[startIdx + j]))
 					{
 						idx = startIdx + j;
 						break;
 					}
 				}
 			}
 			else
 				idx += startIdx;
 			/* Make robust to issues */
 			if (idx >= 0 && idx < ntup->count)
 			{
 				ItemPointer indextid = &ntup->indextids[idx];
 				/* Update neighbor on the buffer */
 				ItemPointerSet(indextid, e->blkno, e->offno);
 				/* Commit */
 				if (building)
 					MarkBufferDirty(buf);
 				else
 					GenericXLogFinish(state);
 			}
 			else if (!building)
 				GenericXLogAbort(state);
 			UnlockReleaseBuffer(buf);
 		}
 	}
 	MemoryContextDelete(updateCtx);
 }
 /*
@@ -633,26 +505,16 @@ FindDuplicateOnDisk(Relation index, HnswElement element, bool building)
 	char	   *base = NULL;
 	HnswNeighborArray *neighbors = HnswGetNeighbors(base, element, 0);
 	Datum		value = HnswGetValue(base, element);
 	IndexTuple	itup = HnswPtrAccess(base, element->itup);
 	TupleDesc	tupdesc = RelationGetDescr(index);
 	for (int i = 0; i < neighbors->length; i++)
 	{
 		HnswCandidate *neighbor = &neighbors->items[i];
 		HnswElement neighborElement = HnswPtrAccess(base, neighbor->element);
 		Datum		neighborValue = HnswGetValue(base, neighborElement);
-		if (HnswUseIndexTuple(index))
+		/* Exit early since ordered by distance */
-		{
+		if (!datumIsEqual(value, neighborValue, false, -1))
-			/* Exit early since ordered by distance */
+			return false;
 			if (!HnswIndexTupleIsEqual(itup, HnswPtrAccess(base, neighborElement->itup), tupdesc))
 				return false;
 		}
 		else
 		{
 			/* Exit early since ordered by distance */
 			if (!datumIsEqual(value, HnswGetValue(base, neighborElement), false, -1))
 				return false;
 		}
 		if (AddDuplicateOnDisk(index, element, neighborElement, building))
 			return true;
@@ -665,7 +527,7 @@ FindDuplicateOnDisk(Relation index, HnswElement element, bool building)
 * Update graph on disk
 */
 static void
-UpdateGraphOnDisk(Relation index, FmgrInfo **procinfo, Oid *collation, HnswElement element, int m, int efConstruction, HnswElement entryPoint, bool building)
+UpdateGraphOnDisk(Relation index, FmgrInfo *procinfo, Oid collation, HnswElement element, int m, int efConstruction, HnswElement entryPoint, bool building)
 {
 	BlockNumber newInsertPage = InvalidBlockNumber;
@@ -698,13 +560,11 @@ HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull,
 	HnswElement element;
 	int			m;
 	int			efConstruction = HnswGetEfConstruction(index);
-	FmgrInfo   *procinfo[2];
+	FmgrInfo   *procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
-	Oid		   *collation;
+	Oid			collation = index->rd_indcollation[0];
 	LOCKMODE	lockmode = ShareLock;
 	char	   *base = NULL;
 	HnswInitProcinfo(procinfo, &collation, index);
 	/*
 	 * Get a shared lock. This allows vacuum to ensure no in-flight inserts
 	 * before repairing graph. Use a page lock so it does not interfere with
@@ -717,23 +577,7 @@ HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull,
 	/* Create an element */
 	element = HnswInitElement(base, heap_tid, m, HnswGetMl(m), HnswGetMaxLevel(m), NULL);
-	if (HnswUseIndexTuple(index))
+	HnswPtrStore(base, element->value, DatumGetPointer(value));
 	{
 		/* TODO no toast */
 		TupleDesc	tupdesc = RelationGetDescr(index);
 		IndexTuple	itup;
 		bool		unused;
 		/* TODO fix */
 		values[0] = value;
 		itup = index_form_tuple(tupdesc, values, isnull);
 		HnswPtrStore(base, element->itup, itup);
 		HnswPtrStore(base, element->value, DatumGetPointer(index_getattr(itup, 1, tupdesc, &unused)));
 	}
 	else
 		HnswPtrStore(base, element->value, DatumGetPointer(value));
 	/* Prevent concurrent inserts when likely updating entry point */
 	if (entryPoint == NULL || element->level > entryPoint->level)
@@ -750,7 +594,7 @@ HnswInsertTupleOnDisk(Relation index, Datum value, Datum *values, bool *isnull,
 	}
 	/* Find neighbors for element */
-	HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, false, false);
+	HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, false);
 	/* Update graph on disk */
 	UpdateGraphOnDisk(index, procinfo, collation, element, m, efConstruction, entryPoint, building);
@@ -770,7 +614,7 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
 	Datum		value;
 	const		HnswTypeInfo *typeInfo = HnswGetTypeInfo(index);
 	FmgrInfo   *normprocinfo;
-	Oid		   *collation = index->rd_indcollation;
+	Oid			collation = index->rd_indcollation[0];
 	/* Detoast once for all calls */
 	value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
@@ -783,10 +627,10 @@ HnswInsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_ti
 	normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
 	if (normprocinfo != NULL)
 	{
-		if (!HnswCheckNorm(normprocinfo, collation[0], value))
+		if (!HnswCheckNorm(normprocinfo, collation, value))
 			return;
-		value = HnswNormValue(typeInfo, collation[0], value);
+		value = HnswNormValue(typeInfo, collation, value);
 	}
 	HnswInsertTupleOnDisk(index, value, values, isnull, heap_tid, false);
--- a/src/hnswscan.c
+++ b/src/hnswscan.c
@@ -15,15 +15,13 @@ GetScanItems(IndexScanDesc scan, Datum q)
 {
 	HnswScanOpaque so = (HnswScanOpaque) scan->opaque;
 	Relation	index = scan->indexRelation;
-	FmgrInfo  **procinfo = so->procinfo;
+	FmgrInfo   *procinfo = so->procinfo;
-	Oid		   *collation = so->collation;
+	Oid			collation = so->collation;
 	List	   *ep;
 	List	   *w;
 	int			m;
 	HnswElement entryPoint;
 	char	   *base = NULL;
 	bool		inMemory = false;
 	ScanKeyData *keyData = scan->keyData;
 	/* Get m and entry point */
 	HnswGetMetaPageInfo(index, &m, &entryPoint);
@@ -31,15 +29,15 @@ GetScanItems(IndexScanDesc scan, Datum q)
 	if (entryPoint == NULL)
 		return NIL;
-	ep = list_make1(HnswEntryCandidate(base, entryPoint, q, NULL, keyData, index, procinfo, collation, false, inMemory));
+	ep = list_make1(HnswEntryCandidate(base, entryPoint, q, index, procinfo, collation, false));
 	for (int lc = entryPoint->level; lc >= 1; lc--)
 	{
-		w = HnswSearchLayer(base, q, NULL, keyData, ep, 1, lc, index, procinfo, collation, m, false, NULL, inMemory);
+		w = HnswSearchLayer(base, q, ep, 1, lc, index, procinfo, collation, m, false, NULL);
 		ep = w;
 	}
-	return HnswSearchLayer(base, q, NULL, keyData, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL, inMemory);
+	return HnswSearchLayer(base, q, ep, hnsw_ef_search, 0, index, procinfo, collation, m, false, NULL);
 }
 /*
@@ -63,7 +61,7 @@ GetScanValue(IndexScanDesc scan)
 		/* Normalize if needed */
 		if (so->normprocinfo != NULL)
-			value = HnswNormValue(so->typeInfo, so->collation[0], value);
+			value = HnswNormValue(so->typeInfo, so->collation, value);
 	}
 	return value;
@@ -88,8 +86,9 @@ hnswbeginscan(Relation index, int nkeys, int norderbys)
 									   ALLOCSET_DEFAULT_SIZES);
 	/* Set support functions */
-	HnswInitProcinfo(so->procinfo, &so->collation, index);
+	so->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
 	so->normprocinfo = HnswOptionalProcInfo(index, HNSW_NORM_PROC);
 	so->collation = index->rd_indcollation[0];
 	scan->opaque = so;
@@ -161,20 +160,20 @@ 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;
 		/* Move to next element if no valid heap TIDs */
-		if (!hc->matches || element->heaptidsLength == 0)
+		if (element->heaptidsLength == 0)
 		{
 			so->w = list_delete_last(so->w);
 			continue;
--- a/src/hnswutils.c
+++ b/src/hnswutils.c
--- a/src/hnswvacuum.c
+++ b/src/hnswvacuum.c
@@ -189,8 +189,8 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
 	GenericXLogState *state;
 	int			m = vacuumstate->m;
 	int			efConstruction = vacuumstate->efConstruction;
-	FmgrInfo  **procinfo = vacuumstate->procinfo;
+	FmgrInfo   *procinfo = vacuumstate->procinfo;
-	Oid		   *collation = vacuumstate->collation;
+	Oid			collation = vacuumstate->collation;
 	BufferAccessStrategy bas = vacuumstate->bas;
 	HnswNeighborTuple ntup = vacuumstate->ntup;
 	Size		ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(element->level, m);
@@ -205,7 +205,7 @@ RepairGraphElement(HnswVacuumState * vacuumstate, HnswElement element, HnswEleme
 	element->heaptidsLength = 0;
 	/* Find neighbors for element, skipping itself */
-	HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, true, false);
+	HnswFindElementNeighbors(base, element, entryPoint, index, procinfo, collation, m, efConstruction, true);
 	/* Zero memory for each element */
 	MemSet(ntup, 0, HNSW_TUPLE_ALLOC_SIZE);
@@ -256,7 +256,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
 		LockPage(index, HNSW_UPDATE_LOCK, ShareLock);
 		/* Load element */
-		HnswLoadElement(highestPoint, NULL, NULL, NULL, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true, NULL);
+		HnswLoadElement(highestPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true);
 		/* Repair if needed */
 		if (NeedsUpdated(vacuumstate, highestPoint))
@@ -294,7 +294,7 @@ RepairGraphEntryPoint(HnswVacuumState * vacuumstate)
 			 * is outdated, this can remove connections at higher levels in
 			 * the graph until they are repaired, but this should be fine.
 			 */
-			HnswLoadElement(entryPoint, NULL, NULL, NULL, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true, NULL);
+			HnswLoadElement(entryPoint, NULL, NULL, index, vacuumstate->procinfo, vacuumstate->collation, true);
 			if (NeedsUpdated(vacuumstate, entryPoint))
 			{
@@ -370,7 +370,7 @@ RepairGraph(HnswVacuumState * vacuumstate)
 			/* Create an element */
 			element = HnswInitElementFromBlock(blkno, offno);
-			HnswLoadElementFromTuple(element, etup, false, true, index);
+			HnswLoadElementFromTuple(element, etup, false, true);
 			elements = lappend(elements, element);
 		}
@@ -440,7 +440,6 @@ MarkDeleted(HnswVacuumState * vacuumstate)
 	BlockNumber insertPage = InvalidBlockNumber;
 	Relation	index = vacuumstate->index;
 	BufferAccessStrategy bas = vacuumstate->bas;
 	bool		useIndexTuple = HnswUseIndexTuple(index);
 	/*
 	 * Wait for index scans to complete. Scans before this point may contain
@@ -522,14 +521,7 @@ MarkDeleted(HnswVacuumState * vacuumstate)
 			/* Overwrite element */
 			etup->deleted = 1;
-			if (useIndexTuple)
+			MemSet(&etup->data, 0, VARSIZE_ANY(&etup->data));
 			{
 				IndexTuple	itup = (IndexTuple) &etup->data;
 				MemSet(itup, 0, IndexTupleSize(itup));
 			}
 			else
 				MemSet(&etup->data, 0, VARSIZE_ANY(&etup->data));
 			/* Overwrite neighbors */
 			for (int i = 0; i < ntup->count; i++)
@@ -581,7 +573,8 @@ InitVacuumState(HnswVacuumState * vacuumstate, IndexVacuumInfo *info, IndexBulkD
 	vacuumstate->callback_state = callback_state;
 	vacuumstate->efConstruction = HnswGetEfConstruction(index);
 	vacuumstate->bas = GetAccessStrategy(BAS_BULKREAD);
-	HnswInitProcinfo(vacuumstate->procinfo, &vacuumstate->collation, index);
+	vacuumstate->procinfo = index_getprocinfo(index, 1, HNSW_DISTANCE_PROC);
 	vacuumstate->collation = index->rd_indcollation[0];
 	vacuumstate->ntup = palloc0(HNSW_TUPLE_ALLOC_SIZE);
 	vacuumstate->tmpCtx = AllocSetContextCreate(CurrentMemoryContext,
 												"Hnsw vacuum temporary context",
--- a/src/ivfbuild.c
+++ b/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)
@@ -1006,10 +1006,6 @@ BuildIndex(Relation heap, Relation index, IndexInfo *indexInfo,
 	CreateListPages(index, buildstate->centers, buildstate->dimensions, buildstate->lists, forkNum, &buildstate->listInfo);
 	CreateEntryPages(buildstate, forkNum);
 	/* Write WAL for initialization fork since GenericXLog functions do not */
 	if (forkNum == INIT_FORKNUM)
 		log_newpage_range(index, forkNum, 0, RelationGetNumberOfBlocksInFork(index, forkNum), true);
 	FreeBuildState(buildstate);
 }
--- a/src/ivfflat.c
+++ b/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
 }
 /*
@@ -154,7 +181,7 @@ ivfflatvalidate(Oid opclassoid)
 *
 * See https://www.postgresql.org/docs/current/index-api.html
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflathandler);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(ivfflathandler);
 Datum
 ivfflathandler(PG_FUNCTION_ARGS)
 {
@@ -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 */
--- a/src/ivfflat.h
+++ b/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;
--- a/src/ivfinsert.c
+++ b/src/ivfinsert.c
@@ -94,9 +94,6 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
 		value = IvfflatNormValue(typeInfo, collation, value);
 	}
 	/* Ensure index is valid */
 	IvfflatGetMetaPageInfo(index, NULL, NULL);
 	/* Find the insert page - sets the page and list info */
 	FindInsertPage(index, values, &insertPage, &listInfo);
 	Assert(BlockNumberIsValid(insertPage));
--- a/src/ivfkmeans.c
+++ b/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 */
--- a/src/ivfscan.c
+++ b/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;
--- a/src/ivfutils.c
+++ b/src/ivfutils.c
@@ -170,11 +170,7 @@ IvfflatGetMetaPageInfo(Relation index, int *lists, int *dimensions)
 	page = BufferGetPage(buf);
 	metap = IvfflatPageGetMeta(page);
-	if (unlikely(metap->magicNumber != IVFFLAT_MAGIC_NUMBER))
+	*lists = metap->lists;
 		elog(ERROR, "ivfflat index is not valid");
 	if (lists != NULL)
 		*lists = metap->lists;
 	if (dimensions != NULL)
 		*dimensions = metap->dimensions;
@@ -342,7 +338,7 @@ IvfflatGetTypeInfo(Relation index)
 		return (const IvfflatTypeInfo *) DatumGetPointer(FunctionCall0Coll(procinfo, InvalidOid));
 }
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_halfvec_support);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(ivfflat_halfvec_support);
 Datum
 ivfflat_halfvec_support(PG_FUNCTION_ARGS)
 {
@@ -357,7 +353,7 @@ ivfflat_halfvec_support(PG_FUNCTION_ARGS)
 	PG_RETURN_POINTER(&typeInfo);
 };
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(ivfflat_bit_support);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(ivfflat_bit_support);
 Datum
 ivfflat_bit_support(PG_FUNCTION_ARGS)
 {
--- a/src/sparsevec.c
+++ b/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
@@ -190,7 +188,7 @@ CompareIndices(const void *a, const void *b)
 /*
 * Convert textual representation to internal representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_in);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_in);
 Datum
 sparsevec_in(PG_FUNCTION_ARGS)
 {
@@ -411,7 +409,7 @@ sparsevec_in(PG_FUNCTION_ARGS)
 /*
 * Convert internal representation to textual representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_out);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_out);
 Datum
 sparsevec_out(PG_FUNCTION_ARGS)
 {
@@ -464,7 +462,7 @@ sparsevec_out(PG_FUNCTION_ARGS)
 /*
 * Convert type modifier
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_typmod_in);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_typmod_in);
 Datum
 sparsevec_typmod_in(PG_FUNCTION_ARGS)
 {
@@ -495,7 +493,7 @@ sparsevec_typmod_in(PG_FUNCTION_ARGS)
 /*
 * Convert external binary representation to internal representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_recv);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_recv);
 Datum
 sparsevec_recv(PG_FUNCTION_ARGS)
 {
@@ -547,7 +545,7 @@ sparsevec_recv(PG_FUNCTION_ARGS)
 /*
 * Convert internal representation to the external binary representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_send);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_send);
 Datum
 sparsevec_send(PG_FUNCTION_ARGS)
 {
@@ -574,7 +572,7 @@ sparsevec_send(PG_FUNCTION_ARGS)
 * Convert sparse vector to sparse vector
 * This is needed to check the type modifier
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec);
 Datum
 sparsevec(PG_FUNCTION_ARGS)
 {
@@ -589,7 +587,7 @@ sparsevec(PG_FUNCTION_ARGS)
 /*
 * Convert dense vector to sparse vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_to_sparsevec);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_sparsevec);
 Datum
 vector_to_sparsevec(PG_FUNCTION_ARGS)
 {
@@ -632,7 +630,7 @@ vector_to_sparsevec(PG_FUNCTION_ARGS)
 /*
 * Convert half vector to sparse vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_to_sparsevec);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_to_sparsevec);
 Datum
 halfvec_to_sparsevec(PG_FUNCTION_ARGS)
 {
@@ -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
 */
@@ -854,7 +721,7 @@ SparsevecL2SquaredDistance(SparseVector * a, SparseVector * b)
 /*
 * Get the L2 distance between sparse vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l2_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_distance);
 Datum
 sparsevec_l2_distance(PG_FUNCTION_ARGS)
 {
@@ -870,7 +737,7 @@ sparsevec_l2_distance(PG_FUNCTION_ARGS)
 * Get the L2 squared distance between sparse vectors
 * This saves a sqrt calculation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l2_squared_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_squared_distance);
 Datum
 sparsevec_l2_squared_distance(PG_FUNCTION_ARGS)
 {
@@ -921,7 +788,7 @@ SparsevecInnerProduct(SparseVector * a, SparseVector * b)
 /*
 * Get the inner product of two sparse vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_inner_product);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_inner_product);
 Datum
 sparsevec_inner_product(PG_FUNCTION_ARGS)
 {
@@ -936,7 +803,7 @@ sparsevec_inner_product(PG_FUNCTION_ARGS)
 /*
 * Get the negative inner product of two sparse vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_negative_inner_product);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_negative_inner_product);
 Datum
 sparsevec_negative_inner_product(PG_FUNCTION_ARGS)
 {
@@ -951,7 +818,7 @@ sparsevec_negative_inner_product(PG_FUNCTION_ARGS)
 /*
 * Get the cosine distance between two sparse vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_cosine_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_cosine_distance);
 Datum
 sparsevec_cosine_distance(PG_FUNCTION_ARGS)
 {
@@ -996,7 +863,7 @@ sparsevec_cosine_distance(PG_FUNCTION_ARGS)
 /*
 * Get the L1 distance between two sparse vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l1_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l1_distance);
 Datum
 sparsevec_l1_distance(PG_FUNCTION_ARGS)
 {
@@ -1045,7 +912,7 @@ sparsevec_l1_distance(PG_FUNCTION_ARGS)
 /*
 * Get the L2 norm of a sparse vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l2_norm);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_norm);
 Datum
 sparsevec_l2_norm(PG_FUNCTION_ARGS)
 {
@@ -1063,7 +930,7 @@ sparsevec_l2_norm(PG_FUNCTION_ARGS)
 /*
 * Normalize a sparse vector with the L2 norm
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_l2_normalize);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_l2_normalize);
 Datum
 sparsevec_l2_normalize(PG_FUNCTION_ARGS)
 {
@@ -1173,7 +1040,7 @@ sparsevec_cmp_internal(SparseVector * a, SparseVector * b)
 /*
 * Less than
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_lt);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_lt);
 Datum
 sparsevec_lt(PG_FUNCTION_ARGS)
 {
@@ -1186,7 +1053,7 @@ sparsevec_lt(PG_FUNCTION_ARGS)
 /*
 * Less than or equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_le);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_le);
 Datum
 sparsevec_le(PG_FUNCTION_ARGS)
 {
@@ -1199,7 +1066,7 @@ sparsevec_le(PG_FUNCTION_ARGS)
 /*
 * Equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_eq);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_eq);
 Datum
 sparsevec_eq(PG_FUNCTION_ARGS)
 {
@@ -1212,7 +1079,7 @@ sparsevec_eq(PG_FUNCTION_ARGS)
 /*
 * Not equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_ne);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_ne);
 Datum
 sparsevec_ne(PG_FUNCTION_ARGS)
 {
@@ -1225,7 +1092,7 @@ sparsevec_ne(PG_FUNCTION_ARGS)
 /*
 * Greater than or equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_ge);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_ge);
 Datum
 sparsevec_ge(PG_FUNCTION_ARGS)
 {
@@ -1238,7 +1105,7 @@ sparsevec_ge(PG_FUNCTION_ARGS)
 /*
 * Greater than
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_gt);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_gt);
 Datum
 sparsevec_gt(PG_FUNCTION_ARGS)
 {
@@ -1251,7 +1118,7 @@ sparsevec_gt(PG_FUNCTION_ARGS)
 /*
 * Compare sparse vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_cmp);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_cmp);
 Datum
 sparsevec_cmp(PG_FUNCTION_ARGS)
 {
--- a/src/vector.c
+++ b/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))
@@ -155,10 +160,28 @@ 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
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_in);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_in);
 Datum
 vector_in(PG_FUNCTION_ARGS)
 {
@@ -271,7 +294,7 @@ vector_in(PG_FUNCTION_ARGS)
 /*
 * Convert internal representation to textual representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_out);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_out);
 Datum
 vector_out(PG_FUNCTION_ARGS)
 {
@@ -325,7 +348,7 @@ PrintVector(char *msg, Vector * vector)
 /*
 * Convert type modifier
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_typmod_in);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_typmod_in);
 Datum
 vector_typmod_in(PG_FUNCTION_ARGS)
 {
@@ -356,7 +379,7 @@ vector_typmod_in(PG_FUNCTION_ARGS)
 /*
 * Convert external binary representation to internal representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_recv);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_recv);
 Datum
 vector_recv(PG_FUNCTION_ARGS)
 {
@@ -390,7 +413,7 @@ vector_recv(PG_FUNCTION_ARGS)
 /*
 * Convert internal representation to the external binary representation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_send);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_send);
 Datum
 vector_send(PG_FUNCTION_ARGS)
 {
@@ -410,7 +433,7 @@ vector_send(PG_FUNCTION_ARGS)
 * Convert vector to vector
 * This is needed to check the type modifier
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector);
 Datum
 vector(PG_FUNCTION_ARGS)
 {
@@ -425,7 +448,7 @@ vector(PG_FUNCTION_ARGS)
 /*
 * Convert array to vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(array_to_vector);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(array_to_vector);
 Datum
 array_to_vector(PG_FUNCTION_ARGS)
 {
@@ -499,7 +522,7 @@ array_to_vector(PG_FUNCTION_ARGS)
 /*
 * Convert vector to float4[]
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_to_float4);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_to_float4);
 Datum
 vector_to_float4(PG_FUNCTION_ARGS)
 {
@@ -523,7 +546,7 @@ vector_to_float4(PG_FUNCTION_ARGS)
 /*
 * Convert half vector to vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(halfvec_to_vector);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(halfvec_to_vector);
 Datum
 halfvec_to_vector(PG_FUNCTION_ARGS)
 {
@@ -561,7 +584,7 @@ VectorL2SquaredDistance(int dim, float *ax, float *bx)
 /*
 * Get the L2 distance between vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l2_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(l2_distance);
 Datum
 l2_distance(PG_FUNCTION_ARGS)
 {
@@ -577,7 +600,7 @@ l2_distance(PG_FUNCTION_ARGS)
 * Get the L2 squared distance between vectors
 * This saves a sqrt calculation
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_l2_squared_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_l2_squared_distance);
 Datum
 vector_l2_squared_distance(PG_FUNCTION_ARGS)
 {
@@ -604,7 +627,7 @@ VectorInnerProduct(int dim, float *ax, float *bx)
 /*
 * Get the inner product of two vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(inner_product);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(inner_product);
 Datum
 inner_product(PG_FUNCTION_ARGS)
 {
@@ -619,7 +642,7 @@ inner_product(PG_FUNCTION_ARGS)
 /*
 * Get the negative inner product of two vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_negative_inner_product);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_negative_inner_product);
 Datum
 vector_negative_inner_product(PG_FUNCTION_ARGS)
 {
@@ -653,7 +676,7 @@ VectorCosineSimilarity(int dim, float *ax, float *bx)
 /*
 * Get the cosine distance between two vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(cosine_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(cosine_distance);
 Datum
 cosine_distance(PG_FUNCTION_ARGS)
 {
@@ -685,7 +708,7 @@ cosine_distance(PG_FUNCTION_ARGS)
 * Currently uses angular distance since needs to satisfy triangle inequality
 * Assumes inputs are unit vectors (skips norm)
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_spherical_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_spherical_distance);
 Datum
 vector_spherical_distance(PG_FUNCTION_ARGS)
 {
@@ -722,7 +745,7 @@ VectorL1Distance(int dim, float *ax, float *bx)
 /*
 * Get the L1 distance between two vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l1_distance);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(l1_distance);
 Datum
 l1_distance(PG_FUNCTION_ARGS)
 {
@@ -737,7 +760,7 @@ l1_distance(PG_FUNCTION_ARGS)
 /*
 * Get the dimensions of a vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_dims);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_dims);
 Datum
 vector_dims(PG_FUNCTION_ARGS)
 {
@@ -749,7 +772,7 @@ vector_dims(PG_FUNCTION_ARGS)
 /*
 * Get the L2 norm of a vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_norm);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_norm);
 Datum
 vector_norm(PG_FUNCTION_ARGS)
 {
@@ -767,7 +790,7 @@ vector_norm(PG_FUNCTION_ARGS)
 /*
 * Normalize a vector with the L2 norm
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(l2_normalize);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(l2_normalize);
 Datum
 l2_normalize(PG_FUNCTION_ARGS)
 {
@@ -806,7 +829,7 @@ l2_normalize(PG_FUNCTION_ARGS)
 /*
 * Add vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_add);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_add);
 Datum
 vector_add(PG_FUNCTION_ARGS)
 {
@@ -839,7 +862,7 @@ vector_add(PG_FUNCTION_ARGS)
 /*
 * Subtract vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_sub);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_sub);
 Datum
 vector_sub(PG_FUNCTION_ARGS)
 {
@@ -872,7 +895,7 @@ vector_sub(PG_FUNCTION_ARGS)
 /*
 * Multiply vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_mul);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_mul);
 Datum
 vector_mul(PG_FUNCTION_ARGS)
 {
@@ -908,7 +931,7 @@ vector_mul(PG_FUNCTION_ARGS)
 /*
 * Concatenate vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_concat);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_concat);
 Datum
 vector_concat(PG_FUNCTION_ARGS)
 {
@@ -932,7 +955,7 @@ vector_concat(PG_FUNCTION_ARGS)
 /*
 * Quantize a vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(binary_quantize);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(binary_quantize);
 Datum
 binary_quantize(PG_FUNCTION_ARGS)
 {
@@ -950,7 +973,7 @@ binary_quantize(PG_FUNCTION_ARGS)
 /*
 * Get a subvector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(subvector);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(subvector);
 Datum
 subvector(PG_FUNCTION_ARGS)
 {
@@ -1024,7 +1047,7 @@ vector_cmp_internal(Vector * a, Vector * b)
 /*
 * Less than
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_lt);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_lt);
 Datum
 vector_lt(PG_FUNCTION_ARGS)
 {
@@ -1037,7 +1060,7 @@ vector_lt(PG_FUNCTION_ARGS)
 /*
 * Less than or equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_le);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_le);
 Datum
 vector_le(PG_FUNCTION_ARGS)
 {
@@ -1050,7 +1073,7 @@ vector_le(PG_FUNCTION_ARGS)
 /*
 * Equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_eq);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_eq);
 Datum
 vector_eq(PG_FUNCTION_ARGS)
 {
@@ -1063,7 +1086,7 @@ vector_eq(PG_FUNCTION_ARGS)
 /*
 * Not equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_ne);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_ne);
 Datum
 vector_ne(PG_FUNCTION_ARGS)
 {
@@ -1076,7 +1099,7 @@ vector_ne(PG_FUNCTION_ARGS)
 /*
 * Greater than or equal
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_ge);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_ge);
 Datum
 vector_ge(PG_FUNCTION_ARGS)
 {
@@ -1089,7 +1112,7 @@ vector_ge(PG_FUNCTION_ARGS)
 /*
 * Greater than
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_gt);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_gt);
 Datum
 vector_gt(PG_FUNCTION_ARGS)
 {
@@ -1102,7 +1125,7 @@ vector_gt(PG_FUNCTION_ARGS)
 /*
 * Compare vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_cmp);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_cmp);
 Datum
 vector_cmp(PG_FUNCTION_ARGS)
 {
@@ -1115,7 +1138,7 @@ vector_cmp(PG_FUNCTION_ARGS)
 /*
 * Accumulate vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_accum);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_accum);
 Datum
 vector_accum(PG_FUNCTION_ARGS)
 {
@@ -1176,7 +1199,7 @@ vector_accum(PG_FUNCTION_ARGS)
 /*
 * Combine vectors or half vectors (also used for halfvec_combine)
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_combine);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_combine);
 Datum
 vector_combine(PG_FUNCTION_ARGS)
 {
@@ -1247,7 +1270,7 @@ vector_combine(PG_FUNCTION_ARGS)
 /*
 * Average vectors
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(vector_avg);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(vector_avg);
 Datum
 vector_avg(PG_FUNCTION_ARGS)
 {
@@ -1281,7 +1304,7 @@ vector_avg(PG_FUNCTION_ARGS)
 /*
 * Convert sparse vector to dense vector
 */
-FUNCTION_PREFIX PG_FUNCTION_INFO_V1(sparsevec_to_vector);
+PGDLLEXPORT PG_FUNCTION_INFO_V1(sparsevec_to_vector);
 Datum
 sparsevec_to_vector(PG_FUNCTION_ARGS)
 {
--- a/src/vector.h
+++ b/src/vector.h
@@ -20,11 +20,4 @@ Vector	   *InitVector(int dim);
 void		PrintVector(char *msg, Vector * vector);
 int			vector_cmp_internal(Vector * a, Vector * b);
 /* TODO Move to better place */
 #if PG_VERSION_NUM >= 160000
 #define FUNCTION_PREFIX
 #else
 #define FUNCTION_PREFIX PGDLLEXPORT
 #endif
 #endif
--- a/test/expected/cast.out
+++ b/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;
--- a/test/expected/vector.out
+++ b/test/expected/vector.out
@@ -0,0 +1,3 @@
 -- complain if script is sourced in psql, rather than via CREATE EXTENSION
 \echo Use "CREATE EXTENSION vector" to load this file. \quit
 Use "CREATE EXTENSION vector" to load this file.
--- a/test/expected/vector_type.out
+++ b/test/expected/vector_type.out
@@ -1,672 +0,0 @@
 SELECT '[1,2,3]'::vector;
 vector  
 ---------
 [1,2,3]
 (1 row)
 SELECT '[-1,-2,-3]'::vector;
   vector   
 ------------
 [-1,-2,-3]
 (1 row)
 SELECT '[1.,2.,3.]'::vector;
 vector  
 ---------
 [1,2,3]
 (1 row)
 SELECT ' [ 1,  2 ,    3  ] '::vector;
 vector  
 ---------
 [1,2,3]
 (1 row)
 SELECT '[1.23456]'::vector;
  vector   
 -----------
 [1.23456]
 (1 row)
 SELECT '[hello,1]'::vector;
 ERROR:  invalid input syntax for type vector: "[hello,1]"
 LINE 1: SELECT '[hello,1]'::vector;
               ^
 SELECT '[NaN,1]'::vector;
 ERROR:  NaN not allowed in vector
 LINE 1: SELECT '[NaN,1]'::vector;
               ^
 SELECT '[Infinity,1]'::vector;
 ERROR:  infinite value not allowed in vector
 LINE 1: SELECT '[Infinity,1]'::vector;
               ^
 SELECT '[-Infinity,1]'::vector;
 ERROR:  infinite value not allowed in vector
 LINE 1: SELECT '[-Infinity,1]'::vector;
               ^
 SELECT '[1.5e38,-1.5e38]'::vector;
       vector       
 --------------------
 [1.5e+38,-1.5e+38]
 (1 row)
 SELECT '[1.5e+38,-1.5e+38]'::vector;
       vector       
 --------------------
 [1.5e+38,-1.5e+38]
 (1 row)
 SELECT '[1.5e-38,-1.5e-38]'::vector;
       vector       
 --------------------
 [1.5e-38,-1.5e-38]
 (1 row)
 SELECT '[4e38,1]'::vector;
 ERROR:  "4e38" is out of range for type vector
 LINE 1: SELECT '[4e38,1]'::vector;
               ^
 SELECT '[-4e38,1]'::vector;
 ERROR:  "-4e38" is out of range for type vector
 LINE 1: SELECT '[-4e38,1]'::vector;
               ^
 SELECT '[1e-46,1]'::vector;
 vector 
 --------
 [0,1]
 (1 row)
 SELECT '[-1e-46,1]'::vector;
 vector 
 --------
 [-0,1]
 (1 row)
 SELECT '[1,2,3'::vector;
 ERROR:  invalid input syntax for type vector: "[1,2,3"
 LINE 1: SELECT '[1,2,3'::vector;
               ^
 SELECT '[1,2,3]9'::vector;
 ERROR:  invalid input syntax for type vector: "[1,2,3]9"
 LINE 1: SELECT '[1,2,3]9'::vector;
               ^
 DETAIL:  Junk after closing right brace.
 SELECT '1,2,3'::vector;
 ERROR:  invalid input syntax for type vector: "1,2,3"
 LINE 1: SELECT '1,2,3'::vector;
               ^
 DETAIL:  Vector contents must start with "[".
 SELECT ''::vector;
 ERROR:  invalid input syntax for type vector: ""
 LINE 1: SELECT ''::vector;
               ^
 DETAIL:  Vector contents must start with "[".
 SELECT '['::vector;
 ERROR:  invalid input syntax for type vector: "["
 LINE 1: SELECT '['::vector;
               ^
 SELECT '[ '::vector;
 ERROR:  invalid input syntax for type vector: "[ "
 LINE 1: SELECT '[ '::vector;
               ^
 SELECT '[,'::vector;
 ERROR:  invalid input syntax for type vector: "[,"
 LINE 1: SELECT '[,'::vector;
               ^
 SELECT '[]'::vector;
 ERROR:  vector must have at least 1 dimension
 LINE 1: SELECT '[]'::vector;
               ^
 SELECT '[ ]'::vector;
 ERROR:  vector must have at least 1 dimension
 LINE 1: SELECT '[ ]'::vector;
               ^
 SELECT '[,]'::vector;
 ERROR:  invalid input syntax for type vector: "[,]"
 LINE 1: SELECT '[,]'::vector;
               ^
 SELECT '[1,]'::vector;
 ERROR:  invalid input syntax for type vector: "[1,]"
 LINE 1: SELECT '[1,]'::vector;
               ^
 SELECT '[1a]'::vector;
 ERROR:  invalid input syntax for type vector: "[1a]"
 LINE 1: SELECT '[1a]'::vector;
               ^
 SELECT '[1,,3]'::vector;
 ERROR:  invalid input syntax for type vector: "[1,,3]"
 LINE 1: SELECT '[1,,3]'::vector;
               ^
 SELECT '[1, ,3]'::vector;
 ERROR:  invalid input syntax for type vector: "[1, ,3]"
 LINE 1: SELECT '[1, ,3]'::vector;
               ^
 SELECT '[1,2,3]'::vector(3);
 vector  
 ---------
 [1,2,3]
 (1 row)
 SELECT '[1,2,3]'::vector(2);
 ERROR:  expected 2 dimensions, not 3
 SELECT '[1,2,3]'::vector(3, 2);
 ERROR:  invalid type modifier
 LINE 1: SELECT '[1,2,3]'::vector(3, 2);
                          ^
 SELECT '[1,2,3]'::vector('a');
 ERROR:  invalid input syntax for type integer: "a"
 LINE 1: SELECT '[1,2,3]'::vector('a');
                          ^
 SELECT '[1,2,3]'::vector(0);
 ERROR:  dimensions for type vector must be at least 1
 LINE 1: SELECT '[1,2,3]'::vector(0);
                          ^
 SELECT '[1,2,3]'::vector(16001);
 ERROR:  dimensions for type vector cannot exceed 16000
 LINE 1: SELECT '[1,2,3]'::vector(16001);
                          ^
 SELECT unnest('{"[1,2,3]", "[4,5,6]"}'::vector[]);
 unnest  
 ---------
 [1,2,3]
 [4,5,6]
 (2 rows)
 SELECT '{"[1,2,3]"}'::vector(2)[];
 ERROR:  expected 2 dimensions, not 3
 SELECT '[1,2,3]'::vector + '[4,5,6]';
 ?column? 
 ----------
 [5,7,9]
 (1 row)
 SELECT '[3e38]'::vector + '[3e38]';
 ERROR:  value out of range: overflow
 SELECT '[1,2]'::vector + '[3]';
 ERROR:  different vector dimensions 2 and 1
 SELECT '[1,2,3]'::vector - '[4,5,6]';
  ?column?  
 ------------
 [-3,-3,-3]
 (1 row)
 SELECT '[-3e38]'::vector - '[3e38]';
 ERROR:  value out of range: overflow
 SELECT '[1,2]'::vector - '[3]';
 ERROR:  different vector dimensions 2 and 1
 SELECT '[1,2,3]'::vector * '[4,5,6]';
 ?column?  
 -----------
 [4,10,18]
 (1 row)
 SELECT '[1e37]'::vector * '[1e37]';
 ERROR:  value out of range: overflow
 SELECT '[1e-37]'::vector * '[1e-37]';
 ERROR:  value out of range: underflow
 SELECT '[1,2]'::vector * '[3]';
 ERROR:  different vector dimensions 2 and 1
 SELECT '[1,2,3]'::vector || '[4,5]';
  ?column?   
 -------------
 [1,2,3,4,5]
 (1 row)
 SELECT array_fill(0, ARRAY[16000])::vector || '[1]';
 ERROR:  vector cannot have more than 16000 dimensions
 SELECT '[1,2,3]'::vector < '[1,2,3]';
 ?column? 
 ----------
 f
 (1 row)
 SELECT '[1,2,3]'::vector < '[1,2]';
 ?column? 
 ----------
 f
 (1 row)
 SELECT '[1,2,3]'::vector <= '[1,2,3]';
 ?column? 
 ----------
 t
 (1 row)
 SELECT '[1,2,3]'::vector <= '[1,2]';
 ?column? 
 ----------
 f
 (1 row)
 SELECT '[1,2,3]'::vector = '[1,2,3]';
 ?column? 
 ----------
 t
 (1 row)
 SELECT '[1,2,3]'::vector = '[1,2]';
 ?column? 
 ----------
 f
 (1 row)
 SELECT '[1,2,3]'::vector != '[1,2,3]';
 ?column? 
 ----------
 f
 (1 row)
 SELECT '[1,2,3]'::vector != '[1,2]';
 ?column? 
 ----------
 t
 (1 row)
 SELECT '[1,2,3]'::vector >= '[1,2,3]';
 ?column? 
 ----------
 t
 (1 row)
 SELECT '[1,2,3]'::vector >= '[1,2]';
 ?column? 
 ----------
 t
 (1 row)
 SELECT '[1,2,3]'::vector > '[1,2,3]';
 ?column? 
 ----------
 f
 (1 row)
 SELECT '[1,2,3]'::vector > '[1,2]';
 ?column? 
 ----------
 t
 (1 row)
 SELECT vector_cmp('[1,2,3]', '[1,2,3]');
 vector_cmp 
 ------------
          0
 (1 row)
 SELECT vector_cmp('[1,2,3]', '[0,0,0]');
 vector_cmp 
 ------------
          1
 (1 row)
 SELECT vector_cmp('[0,0,0]', '[1,2,3]');
 vector_cmp 
 ------------
         -1
 (1 row)
 SELECT vector_cmp('[1,2]', '[1,2,3]');
 vector_cmp 
 ------------
         -1
 (1 row)
 SELECT vector_cmp('[1,2,3]', '[1,2]');
 vector_cmp 
 ------------
          1
 (1 row)
 SELECT vector_cmp('[1,2]', '[2,3,4]');
 vector_cmp 
 ------------
         -1
 (1 row)
 SELECT vector_cmp('[2,3]', '[1,2,3]');
 vector_cmp 
 ------------
          1
 (1 row)
 SELECT vector_dims('[1,2,3]'::vector);
 vector_dims 
 -------------
           3
 (1 row)
 SELECT round(vector_norm('[1,1]')::numeric, 5);
  round  
 ---------
 1.41421
 (1 row)
 SELECT vector_norm('[3,4]');
 vector_norm 
 -------------
           5
 (1 row)
 SELECT vector_norm('[0,1]');
 vector_norm 
 -------------
           1
 (1 row)
 SELECT vector_norm('[3e37,4e37]')::real;
 vector_norm 
 -------------
       5e+37
 (1 row)
 SELECT vector_norm('[0,0]');
 vector_norm 
 -------------
           0
 (1 row)
 SELECT vector_norm('[2]');
 vector_norm 
 -------------
           2
 (1 row)
 SELECT l2_distance('[0,0]'::vector, '[3,4]');
 l2_distance 
 -------------
           5
 (1 row)
 SELECT l2_distance('[0,0]'::vector, '[0,1]');
 l2_distance 
 -------------
           1
 (1 row)
 SELECT l2_distance('[1,2]'::vector, '[3]');
 ERROR:  different vector dimensions 2 and 1
 SELECT l2_distance('[3e38]'::vector, '[-3e38]');
 l2_distance 
 -------------
    Infinity
 (1 row)
 SELECT l2_distance('[1,1,1,1,1,1,1,1,1]'::vector, '[1,1,1,1,1,1,1,4,5]');
 l2_distance 
 -------------
           5
 (1 row)
 SELECT '[0,0]'::vector <-> '[3,4]';
 ?column? 
 ----------
        5
 (1 row)
 SELECT inner_product('[1,2]'::vector, '[3,4]');
 inner_product 
 ---------------
            11
 (1 row)
 SELECT inner_product('[1,2]'::vector, '[3]');
 ERROR:  different vector dimensions 2 and 1
 SELECT inner_product('[3e38]'::vector, '[3e38]');
 inner_product 
 ---------------
      Infinity
 (1 row)
 SELECT inner_product('[1,1,1,1,1,1,1,1,1]'::vector, '[1,2,3,4,5,6,7,8,9]');
 inner_product 
 ---------------
            45
 (1 row)
 SELECT '[1,2]'::vector <#> '[3,4]';
 ?column? 
 ----------
      -11
 (1 row)
 SELECT cosine_distance('[1,2]'::vector, '[2,4]');
 cosine_distance 
 -----------------
               0
 (1 row)
 SELECT cosine_distance('[1,2]'::vector, '[0,0]');
 cosine_distance 
 -----------------
             NaN
 (1 row)
 SELECT cosine_distance('[1,1]'::vector, '[1,1]');
 cosine_distance 
 -----------------
               0
 (1 row)
 SELECT cosine_distance('[1,0]'::vector, '[0,2]');
 cosine_distance 
 -----------------
               1
 (1 row)
 SELECT cosine_distance('[1,1]'::vector, '[-1,-1]');
 cosine_distance 
 -----------------
               2
 (1 row)
 SELECT cosine_distance('[1,2]'::vector, '[3]');
 ERROR:  different vector dimensions 2 and 1
 SELECT cosine_distance('[1,1]'::vector, '[1.1,1.1]');
 cosine_distance 
 -----------------
               0
 (1 row)
 SELECT cosine_distance('[1,1]'::vector, '[-1.1,-1.1]');
 cosine_distance 
 -----------------
               2
 (1 row)
 SELECT cosine_distance('[3e38]'::vector, '[3e38]');
 cosine_distance 
 -----------------
             NaN
 (1 row)
 SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[1,2,3,4,5,6,7,8,9]');
 cosine_distance 
 -----------------
               0
 (1 row)
 SELECT cosine_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[-1,-2,-3,-4,-5,-6,-7,-8,-9]');
 cosine_distance 
 -----------------
               2
 (1 row)
 SELECT '[1,2]'::vector <=> '[2,4]';
 ?column? 
 ----------
        0
 (1 row)
 SELECT l1_distance('[0,0]'::vector, '[3,4]');
 l1_distance 
 -------------
           7
 (1 row)
 SELECT l1_distance('[0,0]'::vector, '[0,1]');
 l1_distance 
 -------------
           1
 (1 row)
 SELECT l1_distance('[1,2]'::vector, '[3]');
 ERROR:  different vector dimensions 2 and 1
 SELECT l1_distance('[3e38]'::vector, '[-3e38]');
 l1_distance 
 -------------
    Infinity
 (1 row)
 SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[1,2,3,4,5,6,7,8,9]');
 l1_distance 
 -------------
           0
 (1 row)
 SELECT l1_distance('[1,2,3,4,5,6,7,8,9]'::vector, '[0,3,2,5,4,7,6,9,8]');
 l1_distance 
 -------------
           9
 (1 row)
 SELECT '[0,0]'::vector <+> '[3,4]';
 ?column? 
 ----------
        7
 (1 row)
 SELECT l2_normalize('[3,4]'::vector);
 l2_normalize 
 --------------
 [0.6,0.8]
 (1 row)
 SELECT l2_normalize('[3,0]'::vector);
 l2_normalize 
 --------------
 [1,0]
 (1 row)
 SELECT l2_normalize('[0,0.1]'::vector);
 l2_normalize 
 --------------
 [0,1]
 (1 row)
 SELECT l2_normalize('[0,0]'::vector);
 l2_normalize 
 --------------
 [0,0]
 (1 row)
 SELECT l2_normalize('[3e38]'::vector);
 l2_normalize 
 --------------
 [1]
 (1 row)
 SELECT binary_quantize('[1,0,-1]'::vector);
 binary_quantize 
 -----------------
 100
 (1 row)
 SELECT binary_quantize('[0,0.1,-0.2,-0.3,0.4,0.5,0.6,-0.7,0.8,-0.9,1]'::vector);
 binary_quantize 
 -----------------
 01001110101
 (1 row)
 SELECT subvector('[1,2,3,4,5]'::vector, 1, 3);
 subvector 
 -----------
 [1,2,3]
 (1 row)
 SELECT subvector('[1,2,3,4,5]'::vector, 3, 2);
 subvector 
 -----------
 [3,4]
 (1 row)
 SELECT subvector('[1,2,3,4,5]'::vector, -1, 3);
 subvector 
 -----------
 [1]
 (1 row)
 SELECT subvector('[1,2,3,4,5]'::vector, 3, 9);
 subvector 
 -----------
 [3,4,5]
 (1 row)
 SELECT subvector('[1,2,3,4,5]'::vector, 1, 0);
 ERROR:  vector must have at least 1 dimension
 SELECT subvector('[1,2,3,4,5]'::vector, 3, -1);
 ERROR:  vector must have at least 1 dimension
 SELECT subvector('[1,2,3,4,5]'::vector, -1, 2);
 ERROR:  vector must have at least 1 dimension
 SELECT subvector('[1,2,3,4,5]'::vector, 2147483647, 10);
 ERROR:  vector must have at least 1 dimension
 SELECT subvector('[1,2,3,4,5]'::vector, 3, 2147483647);
 subvector 
 -----------
 [3,4,5]
 (1 row)
 SELECT subvector('[1,2,3,4,5]'::vector, -2147483644, 2147483647);
 subvector 
 -----------
 [1,2]
 (1 row)
 SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
    avg    
 -----------
 [2,3.5,5]
 (1 row)
 SELECT avg(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
    avg    
 -----------
 [2,3.5,5]
 (1 row)
 SELECT avg(v) FROM unnest(ARRAY[]::vector[]) v;
 avg 
 -----
 (1 row)
 SELECT avg(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
 ERROR:  expected 2 dimensions, not 1
 SELECT avg(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
   avg   
 ---------
 [3e+38]
 (1 row)
 SELECT vector_avg(array_agg(n)) FROM generate_series(1, 16002) n;
 ERROR:  vector cannot have more than 16000 dimensions
 SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]']) v;
   sum    
 ----------
 [4,7,10]
 (1 row)
 SELECT sum(v) FROM unnest(ARRAY['[1,2,3]'::vector, '[3,5,7]', NULL]) v;
   sum    
 ----------
 [4,7,10]
 (1 row)
 SELECT sum(v) FROM unnest(ARRAY[]::vector[]) v;
 sum 
 -----
 (1 row)
 SELECT sum(v) FROM unnest(ARRAY['[1,2]'::vector, '[3]']) v;
 ERROR:  different vector dimensions 2 and 1
 SELECT sum(v) FROM unnest(ARRAY['[3e38]'::vector, '[3e38]']) v;
 ERROR:  value out of range: overflow
--- a/test/perl/PostgreSQL/Test/Cluster.pm
+++ b/test/perl/PostgreSQL/Test/Cluster.pm
@@ -1,11 +0,0 @@
 package PostgreSQL::Test::Cluster;
 use PostgresNode;
 sub new
 {
 	my ($class, $name) = @_;
 	return get_new_node($name);
 }
 1;
--- a/test/perl/PostgreSQL/Test/Utils.pm
+++ b/test/perl/PostgreSQL/Test/Utils.pm
@@ -1,5 +0,0 @@
 package PostgreSQL::Test::Utils;
 use TestLib;
 1;
--- a/test/perl/PostgresNode.pm
+++ b/test/perl/PostgresNode.pm
@@ -0,0 +1,8 @@
 use PostgreSQL::Test::Cluster;
 sub get_new_node
 {
 	return PostgreSQL::Test::Cluster->new(@_);
 }
 1;
--- a/test/perl/TestLib.pm
+++ b/test/perl/TestLib.pm
@@ -0,0 +1,3 @@
 use PostgreSQL::Test::Utils;
 1;
--- a/test/sql/cast.sql
+++ b/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;
--- a/test/sql/vector_type.sql
+++ b/test/sql/vector_type.sql
--- a/test/t/001_ivfflat_wal.pl
+++ b/test/t/001_ivfflat_wal.pl
@@ -2,9 +2,9 @@
 # Test generic xlog record work for ivfflat index replication.
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $dim = 32;
@@ -49,7 +49,7 @@ sub test_index_replay
 my $array_sql = join(",", ('random()') x $dim);
 # Initialize primary node
-$node_primary = PostgreSQL::Test::Cluster->new('primary');
+$node_primary = get_new_node('primary');
 $node_primary->init(allows_streaming => 1);
 if ($dim > 32)
 {
@@ -67,7 +67,7 @@ my $backup_name = 'my_backup';
 $node_primary->backup($backup_name);
 # Create streaming replica linking to primary
-$node_replica = PostgreSQL::Test::Cluster->new('replica');
+$node_replica = get_new_node('replica');
 $node_replica->init_from_backup($node_primary, $backup_name, has_streaming => 1);
 $node_replica->start;
--- a/test/t/002_ivfflat_vacuum.pl
+++ b/test/t/002_ivfflat_vacuum.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $dim = 3;
@@ -15,7 +15,7 @@ for (1 .. $dim)
 my $array_sql = join(", ", @r);
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/003_ivfflat_vector_build_recall.pl
+++ b/test/t/003_ivfflat_vector_build_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -49,7 +49,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/004_ivfflat_vector_insert_recall.pl
+++ b/test/t/004_ivfflat_vector_insert_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -48,7 +48,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/005_ivfflat_query_recall.pl
+++ b/test/t/005_ivfflat_query_recall.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/006_ivfflat_lists.pl
+++ b/test/t/006_ivfflat_lists.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/007_ivfflat_inserts.pl
+++ b/test/t/007_ivfflat_inserts.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $dim = 768;
@@ -9,7 +9,7 @@ my $dim = 768;
 my $array_sql = join(",", ('random()') x $dim);
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/008_ivfflat_centers.pl
+++ b/test/t/008_ivfflat_centers.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/009_ivfflat_filtering.pl
+++ b/test/t/009_ivfflat_filtering.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $dim = 3;
@@ -11,7 +11,7 @@ my $limit = 20;
 my $array_sql = join(",", ('random()') x $dim);
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
@@ -94,7 +94,8 @@ like($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();
--- a/test/t/010_hnsw_wal.pl
+++ b/test/t/010_hnsw_wal.pl
@@ -2,9 +2,9 @@
 # Test generic xlog record work for hnsw index replication.
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $dim = 32;
@@ -49,7 +49,7 @@ sub test_index_replay
 my $array_sql = join(",", ('random()') x $dim);
 # Initialize primary node
-$node_primary = PostgreSQL::Test::Cluster->new('primary');
+$node_primary = get_new_node('primary');
 $node_primary->init(allows_streaming => 1);
 if ($dim > 32)
 {
@@ -67,7 +67,7 @@ my $backup_name = 'my_backup';
 $node_primary->backup($backup_name);
 # Create streaming replica linking to primary
-$node_replica = PostgreSQL::Test::Cluster->new('replica');
+$node_replica = get_new_node('replica');
 $node_replica->init_from_backup($node_primary, $backup_name, has_streaming => 1);
 $node_replica->start;
--- a/test/t/011_hnsw_vacuum.pl
+++ b/test/t/011_hnsw_vacuum.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $dim = 3;
@@ -15,7 +15,7 @@ for (1 .. $dim)
 my $array_sql = join(", ", @r);
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/012_hnsw_vector_build_recall.pl
+++ b/test/t/012_hnsw_vector_build_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -47,7 +47,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
@@ -91,7 +91,7 @@ for my $i (0 .. $#operators)
 	));
 	# Test approximate results
-	my $min = $operator eq "<#>" ? 0.97 : 0.99;
+	my $min = $operator eq "<#>" ? 0.98 : 0.99;
 	test_recall($min, $operator);
 	$node->safe_psql("postgres", "DROP INDEX idx;");
--- a/test/t/013_hnsw_vector_insert_recall.pl
+++ b/test/t/013_hnsw_vector_insert_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -47,7 +47,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
@@ -100,7 +100,7 @@ for my $i (0 .. $#operators)
 	}
 	# Test approximate results
-	my $min = $operator eq "<#>" ? 0.97 : 0.99;
+	my $min = $operator eq "<#>" ? 0.98 : 0.99;
 	test_recall($min, $operator);
 	$node->safe_psql("postgres", "DROP INDEX idx;");
--- a/test/t/014_hnsw_vector_vacuum_recall.pl
+++ b/test/t/014_hnsw_vector_vacuum_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -48,7 +48,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/015_hnsw_vector_duplicates.pl
+++ b/test/t/015_hnsw_vector_duplicates.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/016_hnsw_inserts.pl
+++ b/test/t/016_hnsw_inserts.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Ensures elements and neighbors on both same and different pages
@@ -10,7 +10,7 @@ my $dim = 1900;
 my $array_sql = join(",", ('random()') x $dim);
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/017_hnsw_filtering.pl
+++ b/test/t/017_hnsw_filtering.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $dim = 3;
@@ -11,20 +11,16 @@ my $limit = 20;
 my $array_sql = join(",", ('random()') x $dim);
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $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);");
--- a/test/t/018_aggregates.pl
+++ b/test/t/018_aggregates.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
@@ -53,7 +53,7 @@ sub test_aggregate
 	else
 	{
 		# Does not raise overflow error in this instance due to loss of precision
-		is($res, "[24576,24576,49152]");
+		is($res, "[24576,24576,49152]")
 	}
 }
--- a/test/t/019_storage.pl
+++ b/test/t/019_storage.pl
@@ -1,13 +1,13 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $dim = 1024;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/020_hnsw_bit_build_recall.pl
+++ b/test/t/020_hnsw_bit_build_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -51,7 +51,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/021_hnsw_bit_insert_recall.pl
+++ b/test/t/021_hnsw_bit_insert_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -51,7 +51,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/022_hnsw_bit_vacuum_recall.pl
+++ b/test/t/022_hnsw_bit_vacuum_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -51,7 +51,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/023_hnsw_bit_duplicates.pl
+++ b/test/t/023_hnsw_bit_duplicates.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/024_hnsw_halfvec_build_recall.pl
+++ b/test/t/024_hnsw_halfvec_build_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -48,7 +48,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/025_hnsw_halfvec_insert_recall.pl
+++ b/test/t/025_hnsw_halfvec_insert_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -48,7 +48,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/026_hnsw_halfvec_vacuum_recall.pl
+++ b/test/t/026_hnsw_halfvec_vacuum_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -48,7 +48,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/027_hnsw_halfvec_duplicates.pl
+++ b/test/t/027_hnsw_halfvec_duplicates.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/028_hnsw_sparsevec_build_recall.pl
+++ b/test/t/028_hnsw_sparsevec_build_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -47,7 +47,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
@@ -91,7 +91,7 @@ for my $i (0 .. $#operators)
 	));
 	# Test approximate results
-	my $min = $operator eq "<#>" ? 0.97 : 0.99;
+	my $min = $operator eq "<#>" ? 0.98 : 0.99;
 	test_recall($min, $operator);
 	$node->safe_psql("postgres", "DROP INDEX idx;");
--- a/test/t/029_hnsw_sparsevec_insert_recall.pl
+++ b/test/t/029_hnsw_sparsevec_insert_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -47,7 +47,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
@@ -100,7 +100,7 @@ for my $i (0 .. $#operators)
 	}
 	# Test approximate results
-	my $min = $operator eq "<#>" ? 0.97 : 0.99;
+	my $min = $operator eq "<#>" ? 0.98 : 0.99;
 	test_recall($min, $operator);
 	$node->safe_psql("postgres", "DROP INDEX idx;");
--- a/test/t/030_hnsw_sparsevec_vacuum_recall.pl
+++ b/test/t/030_hnsw_sparsevec_vacuum_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -48,7 +48,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/031_hnsw_sparsevec_duplicates.pl
+++ b/test/t/031_hnsw_sparsevec_duplicates.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/032_ivfflat_halfvec_build_recall.pl
+++ b/test/t/032_ivfflat_halfvec_build_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -51,7 +51,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/033_comparison.pl
+++ b/test/t/033_comparison.pl
@@ -1,14 +1,14 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
 my $array_sql = join(",", ('floor(random() * 2)::int - 1') x 3);
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/034_distance_functions.pl
+++ b/test/t/034_distance_functions.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -10,7 +10,7 @@ my $dim = 5;
 my $array_sql = join(",", ('floor(random() * 4)::int - 2') x $dim);
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/035_ivfflat_bit_build_recall.pl
+++ b/test/t/035_ivfflat_bit_build_recall.pl
@@ -1,7 +1,7 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 my $node;
@@ -51,7 +51,7 @@ sub test_recall
 }
 # Initialize node
-$node = PostgreSQL::Test::Cluster->new('node');
+$node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/036_ivfflat_bit_centers.pl
+++ b/test/t/036_ivfflat_bit_centers.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/037_inputs.pl
+++ b/test/t/037_inputs.pl
@@ -1,11 +1,11 @@
 use strict;
-use warnings FATAL => 'all';
+use warnings;
-use PostgreSQL::Test::Cluster;
+use PostgresNode;
-use PostgreSQL::Test::Utils;
+use TestLib;
 use Test::More;
 # Initialize node
-my $node = PostgreSQL::Test::Cluster->new('node');
+my $node = get_new_node('node');
 $node->init;
 $node->start;
--- a/test/t/038_hnsw_sparsevec_vacuum_insert.pl
+++ b/test/t/038_hnsw_sparsevec_vacuum_insert.pl
@@ -1,42 +0,0 @@
 use strict;
 use warnings FATAL => 'all';
 use PostgreSQL::Test::Cluster;
 use PostgreSQL::Test::Utils;
 use Test::More;
 # Initialize node
 my $node = PostgreSQL::Test::Cluster->new('node');
 $node->init;
 $node->start;
 # Create table and index
 $node->safe_psql("postgres", "CREATE EXTENSION vector;");
 $node->safe_psql("postgres", "CREATE TABLE tst (i serial, v sparsevec(100000));");
 $node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v sparsevec_l2_ops);");
 for (1 .. 3)
 {
 	for (1 .. 100)
 	{
 		my @elements;
 		my %indices;
 		for (1 .. int(rand() * 100))
 		{
 			my $index = int(rand() * (100000 - 1)) + 1;
 			if (!exists($indices{$index}))
 			{
 				my $value = rand();
 				push(@elements, "$index:$value");
 				$indices{$index} = 1;
 			}
 		}
 		my $embedding = "{" . join(",", @elements) . "}/100000";
 		$node->safe_psql("postgres", "INSERT INTO tst (v) VALUES ('$embedding');");
 	}
 	$node->safe_psql("postgres", "DELETE FROM tst WHERE i % 2 = 0;");
 	$node->safe_psql("postgres", "VACUUM tst;");
 	is(1, 1);
 }
 done_testing();
--- a/test/t/039_hnsw_cost.pl
+++ b/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();
--- a/test/t/040_ivfflat_cost.pl
+++ b/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();
--- a/test/t/041_hnsw_filtering.pl
+++ b/test/t/041_hnsw_filtering.pl
@@ -1,109 +0,0 @@
 use strict;
 use warnings FATAL => 'all';
 use PostgreSQL::Test::Cluster;
 use PostgreSQL::Test::Utils;
 use Test::More;
 my $node;
 my @queries = ();
 my @cs = ();
 my @expected;
 my $limit = 20;
 my $dim = 3;
 my $array_sql = join(",", ('random()') x $dim);
 my $nc = 50;
 sub test_recall
 {
 	my ($min, $operator) = @_;
 	my $correct = 0;
 	my $total = 0;
 	my $explain = $node->safe_psql("postgres", qq(
 		SET enable_seqscan = off;
 		EXPLAIN ANALYZE SELECT i FROM tst WHERE c = $cs[0] ORDER BY v $operator '$queries[0]' LIMIT $limit;
 	));
 	like($explain, qr/Index Cond/);
 	for my $i (0 .. $#queries)
 	{
 		my $actual = $node->safe_psql("postgres", qq(
 			SET enable_seqscan = off;
 			SELECT i FROM tst WHERE c = $cs[$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);");
 $node->safe_psql("postgres",
 	"INSERT INTO tst SELECT i, ARRAY[$array_sql], i % $nc FROM generate_series(1, 20000) i;"
 );
 # Generate queries
 for (1 .. 20)
 {
 	my @r = ();
 	for (1 .. $dim)
 	{
 		push(@r, rand());
 	}
 	push(@queries, "[" . join(",", @r) . "]");
 	push(@cs, int(rand() * $nc));
 }
 # Get exact results
@expected = ();
 for my $i (0 .. $#queries)
 {
 	my $res = $node->safe_psql("postgres", "SELECT i FROM tst WHERE c = $cs[$i] ORDER BY v <-> '$queries[$i]' LIMIT $limit;");
 	push(@expected, $res);
 }
 # Add index
 $node->safe_psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops, c);");
 # Test recall
 test_recall(0.99, '<->');
 # Test vacuum
 $node->safe_psql("postgres", "DELETE FROM tst WHERE c > 5;");
 $node->safe_psql("postgres", "VACUUM tst;");
 # Test columns
 my ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (c);");
 like($stderr, qr/first column must be a vector/);
 ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (c, v vector_l2_ops);");
 like($stderr, qr/first column must be a vector/);
 ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops, c, c);");
 like($stderr, qr/index cannot have more than two columns/);
 ($ret, $stdout, $stderr) = $node->psql("postgres", "CREATE INDEX ON tst USING hnsw (v vector_l2_ops, v vector_l2_ops);");
 like($stderr, qr/column 2 cannot be a vector/);
 done_testing();
--- a/vector.control
+++ b/vector.control
@@ -1,4 +1,4 @@
 comment = 'vector data type and ivfflat and hnsw access methods'
-default_version = '0.7.4'
+default_version = '0.6.2'
 module_pathname = '$libdir/vector'
 relocatable = true
Author	SHA1	Message	Date
Andrew Kane	0ff9f6511a	Use f32 [skip ci]	2024-04-27 23:02:00 -07:00
Andrew Kane	17855c9861	Started Neon intrinsics [skip ci]	2024-04-27 22:50:47 -07:00
		`@@ -1,2 +0,0 @@`
			`-- complain if script is sourced in psql, rather than via CREATE EXTENSION`
			`\echo Use "ALTER EXTENSION vector UPDATE TO '0.7.1'" to load this file. \quit`