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2 Commits
samples-li
...
fanalyzer
| Author | SHA1 | Date | |
|---|---|---|---|
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ba16f5e7cf | ||
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4a1a91abf9 |
4
.github/workflows/build.yml
vendored
4
.github/workflows/build.yml
vendored
@@ -39,6 +39,10 @@ jobs:
|
|||||||
sudo apt-get update
|
sudo apt-get update
|
||||||
sudo apt-get install libipc-run-perl
|
sudo apt-get install libipc-run-perl
|
||||||
- run: make prove_installcheck
|
- run: make prove_installcheck
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||||||
|
- if: ${{ matrix.os == 'ubuntu-22.04' }}
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||||||
|
run: make clean && make
|
||||||
|
env:
|
||||||
|
PG_CFLAGS: -Werror -fanalyzer
|
||||||
mac:
|
mac:
|
||||||
runs-on: macos-latest
|
runs-on: macos-latest
|
||||||
if: ${{ !startsWith(github.ref_name, 'windows') }}
|
if: ${{ !startsWith(github.ref_name, 'windows') }}
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||||||
|
|||||||
@@ -1,7 +1,6 @@
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|||||||
## 0.5.1 (2023-10-10)
|
## 0.5.1 (unreleased)
|
||||||
|
|
||||||
- Improved performance of HNSW index builds
|
- Improved performance of index scans for IVFFlat after updates and deletes
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||||||
- Added check for MVCC-compliant snapshot for index scans
|
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||||||
|
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||||||
## 0.5.0 (2023-08-28)
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## 0.5.0 (2023-08-28)
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||||||
|
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||||||
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|||||||
@@ -2,7 +2,7 @@
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|||||||
"name": "vector",
|
"name": "vector",
|
||||||
"abstract": "Open-source vector similarity search for Postgres",
|
"abstract": "Open-source vector similarity search for Postgres",
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||||||
"description": "Supports L2 distance, inner product, and cosine distance",
|
"description": "Supports L2 distance, inner product, and cosine distance",
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||||||
"version": "0.5.1",
|
"version": "0.5.0",
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||||||
"maintainer": [
|
"maintainer": [
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"Andrew Kane <andrew@ankane.org>"
|
"Andrew Kane <andrew@ankane.org>"
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||||||
],
|
],
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||||||
@@ -20,7 +20,7 @@
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"vector": {
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"vector": {
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||||||
"file": "sql/vector.sql",
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"file": "sql/vector.sql",
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||||||
"docfile": "README.md",
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"docfile": "README.md",
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||||||
"version": "0.5.1",
|
"version": "0.5.0",
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||||||
"abstract": "Open-source vector similarity search for Postgres"
|
"abstract": "Open-source vector similarity search for Postgres"
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||||||
}
|
}
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||||||
},
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},
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||||||
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2
Makefile
2
Makefile
@@ -1,5 +1,5 @@
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EXTENSION = vector
|
EXTENSION = vector
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EXTVERSION = 0.5.1
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EXTVERSION = 0.5.0
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||||||
|
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MODULE_big = vector
|
MODULE_big = vector
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DATA = $(wildcard sql/*--*.sql)
|
DATA = $(wildcard sql/*--*.sql)
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|||||||
@@ -1,5 +1,5 @@
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EXTENSION = vector
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EXTENSION = vector
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||||||
EXTVERSION = 0.5.1
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EXTVERSION = 0.5.0
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|
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OBJS = 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\vector.obj
|
OBJS = 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\vector.obj
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HEADERS = src\vector.h
|
HEADERS = src\vector.h
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@@ -18,7 +18,7 @@ Compile and install the extension (supports Postgres 11+)
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|
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```sh
|
```sh
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cd /tmp
|
cd /tmp
|
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git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
|
git clone --branch v0.5.0 https://github.com/pgvector/pgvector.git
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cd pgvector
|
cd pgvector
|
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make
|
make
|
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make install # may need sudo
|
make install # may need sudo
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@@ -509,7 +509,7 @@ Then use `nmake` to build:
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|
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```cmd
|
```cmd
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set "PGROOT=C:\Program Files\PostgreSQL\15"
|
set "PGROOT=C:\Program Files\PostgreSQL\15"
|
||||||
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
|
git clone --branch v0.5.0 https://github.com/pgvector/pgvector.git
|
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cd pgvector
|
cd pgvector
|
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nmake /F Makefile.win
|
nmake /F Makefile.win
|
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nmake /F Makefile.win install
|
nmake /F Makefile.win install
|
||||||
@@ -530,7 +530,7 @@ This adds pgvector to the [Postgres image](https://hub.docker.com/_/postgres) (r
|
|||||||
You can also build the image manually:
|
You can also build the image manually:
|
||||||
|
|
||||||
```sh
|
```sh
|
||||||
git clone --branch v0.5.1 https://github.com/pgvector/pgvector.git
|
git clone --branch v0.5.0 https://github.com/pgvector/pgvector.git
|
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cd pgvector
|
cd pgvector
|
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docker build --build-arg PG_MAJOR=15 -t myuser/pgvector .
|
docker build --build-arg PG_MAJOR=15 -t myuser/pgvector .
|
||||||
```
|
```
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|
|||||||
@@ -1,2 +0,0 @@
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-- complain if script is sourced in psql, rather than via CREATE EXTENSION
|
|
||||||
\echo Use "ALTER EXTENSION vector UPDATE TO '0.5.1'" to load this file. \quit
|
|
||||||
@@ -57,8 +57,6 @@
|
|||||||
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
|
/* PROGRESS_CREATEIDX_SUBPHASE_INITIALIZE is 1 */
|
||||||
#define PROGRESS_HNSW_PHASE_LOAD 2
|
#define PROGRESS_HNSW_PHASE_LOAD 2
|
||||||
|
|
||||||
#define HNSW_MAX_SIZE (BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData)) - sizeof(ItemIdData))
|
|
||||||
|
|
||||||
#define HNSW_ELEMENT_TUPLE_SIZE(_dim) MAXALIGN(offsetof(HnswElementTupleData, vec) + VECTOR_SIZE(_dim))
|
#define HNSW_ELEMENT_TUPLE_SIZE(_dim) MAXALIGN(offsetof(HnswElementTupleData, vec) + VECTOR_SIZE(_dim))
|
||||||
#define HNSW_NEIGHBOR_TUPLE_SIZE(level, m) MAXALIGN(offsetof(HnswNeighborTupleData, indextids) + ((level) + 2) * (m) * sizeof(ItemPointerData))
|
#define HNSW_NEIGHBOR_TUPLE_SIZE(level, m) MAXALIGN(offsetof(HnswNeighborTupleData, indextids) + ((level) + 2) * (m) * sizeof(ItemPointerData))
|
||||||
|
|
||||||
@@ -112,13 +110,11 @@ typedef struct HnswCandidate
|
|||||||
{
|
{
|
||||||
HnswElement element;
|
HnswElement element;
|
||||||
float distance;
|
float distance;
|
||||||
bool closer;
|
|
||||||
} HnswCandidate;
|
} HnswCandidate;
|
||||||
|
|
||||||
typedef struct HnswNeighborArray
|
typedef struct HnswNeighborArray
|
||||||
{
|
{
|
||||||
int length;
|
int length;
|
||||||
bool closerSet;
|
|
||||||
HnswCandidate *items;
|
HnswCandidate *items;
|
||||||
} HnswNeighborArray;
|
} HnswNeighborArray;
|
||||||
|
|
||||||
|
|||||||
@@ -117,12 +117,12 @@ CreateElementPages(HnswBuildState * buildstate)
|
|||||||
ListCell *lc;
|
ListCell *lc;
|
||||||
|
|
||||||
/* Calculate sizes */
|
/* Calculate sizes */
|
||||||
maxSize = HNSW_MAX_SIZE;
|
maxSize = BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData));
|
||||||
etupSize = HNSW_ELEMENT_TUPLE_SIZE(dimensions);
|
etupSize = HNSW_ELEMENT_TUPLE_SIZE(dimensions);
|
||||||
|
|
||||||
/* Allocate once */
|
/* Allocate once */
|
||||||
etup = palloc0(etupSize);
|
etup = palloc0(etupSize);
|
||||||
ntup = palloc0(BLCKSZ);
|
ntup = palloc0(maxSize);
|
||||||
|
|
||||||
/* Prepare first page */
|
/* Prepare first page */
|
||||||
buf = HnswNewBuffer(index, forkNum);
|
buf = HnswNewBuffer(index, forkNum);
|
||||||
|
|||||||
@@ -135,7 +135,7 @@ WriteNewElementPages(Relation index, HnswElement e, int m, BlockNumber insertPag
|
|||||||
etupSize = HNSW_ELEMENT_TUPLE_SIZE(dimensions);
|
etupSize = HNSW_ELEMENT_TUPLE_SIZE(dimensions);
|
||||||
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
|
ntupSize = HNSW_NEIGHBOR_TUPLE_SIZE(e->level, m);
|
||||||
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
|
combinedSize = etupSize + ntupSize + sizeof(ItemIdData);
|
||||||
maxSize = HNSW_MAX_SIZE;
|
maxSize = BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(HnswPageOpaqueData));
|
||||||
minCombinedSize = etupSize + HNSW_NEIGHBOR_TUPLE_SIZE(0, m) + sizeof(ItemIdData);
|
minCombinedSize = etupSize + HNSW_NEIGHBOR_TUPLE_SIZE(0, m) + sizeof(ItemIdData);
|
||||||
|
|
||||||
/* Prepare element tuple */
|
/* Prepare element tuple */
|
||||||
|
|||||||
@@ -160,11 +160,6 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
|
|||||||
if (scan->orderByData == NULL)
|
if (scan->orderByData == NULL)
|
||||||
elog(ERROR, "cannot scan hnsw index without order");
|
elog(ERROR, "cannot scan hnsw index without order");
|
||||||
|
|
||||||
/* Requires MVCC-compliant snapshot as not able to maintain a pin */
|
|
||||||
/* https://www.postgresql.org/docs/current/index-locking.html */
|
|
||||||
if (!IsMVCCSnapshot(scan->xs_snapshot))
|
|
||||||
elog(ERROR, "non-MVCC snapshots are not supported with hnsw");
|
|
||||||
|
|
||||||
/* Get scan value */
|
/* Get scan value */
|
||||||
value = GetScanValue(scan);
|
value = GetScanValue(scan);
|
||||||
|
|
||||||
@@ -206,6 +201,15 @@ hnswgettuple(IndexScanDesc scan, ScanDirection dir)
|
|||||||
scan->xs_ctup.t_self = *heaptid;
|
scan->xs_ctup.t_self = *heaptid;
|
||||||
#endif
|
#endif
|
||||||
|
|
||||||
|
/*
|
||||||
|
* Typically, an index scan must maintain a pin on the index page
|
||||||
|
* holding the item last returned by amgettuple. However, this is not
|
||||||
|
* needed with the current vacuum strategy, which ensures scans do not
|
||||||
|
* visit tuples in danger of being marked as deleted.
|
||||||
|
*
|
||||||
|
* https://www.postgresql.org/docs/current/index-locking.html
|
||||||
|
*/
|
||||||
|
|
||||||
scan->xs_recheckorderby = false;
|
scan->xs_recheckorderby = false;
|
||||||
return true;
|
return true;
|
||||||
}
|
}
|
||||||
|
|||||||
115
src/hnswutils.c
115
src/hnswutils.c
@@ -139,7 +139,6 @@ HnswInitNeighbors(HnswElement element, int m)
|
|||||||
a = &element->neighbors[lc];
|
a = &element->neighbors[lc];
|
||||||
a->length = 0;
|
a->length = 0;
|
||||||
a->items = palloc(sizeof(HnswCandidate) * lm);
|
a->items = palloc(sizeof(HnswCandidate) * lm);
|
||||||
a->closerSet = false;
|
|
||||||
}
|
}
|
||||||
}
|
}
|
||||||
|
|
||||||
@@ -693,34 +692,6 @@ HnswSearchLayer(Datum q, List *ep, int ef, int lc, Relation index, FmgrInfo *pro
|
|||||||
return w;
|
return w;
|
||||||
}
|
}
|
||||||
|
|
||||||
/*
|
|
||||||
* Compare candidate distances
|
|
||||||
*/
|
|
||||||
static int
|
|
||||||
#if PG_VERSION_NUM >= 130000
|
|
||||||
CompareCandidateDistances(const ListCell *a, const ListCell *b)
|
|
||||||
#else
|
|
||||||
CompareCandidateDistances(const void *a, const void *b)
|
|
||||||
#endif
|
|
||||||
{
|
|
||||||
HnswCandidate *hca = lfirst((ListCell *) a);
|
|
||||||
HnswCandidate *hcb = lfirst((ListCell *) b);
|
|
||||||
|
|
||||||
if (hca->distance < hcb->distance)
|
|
||||||
return 1;
|
|
||||||
|
|
||||||
if (hca->distance > hcb->distance)
|
|
||||||
return -1;
|
|
||||||
|
|
||||||
if (hca->element < hcb->element)
|
|
||||||
return 1;
|
|
||||||
|
|
||||||
if (hca->element > hcb->element)
|
|
||||||
return -1;
|
|
||||||
|
|
||||||
return 0;
|
|
||||||
}
|
|
||||||
|
|
||||||
/*
|
/*
|
||||||
* Calculate the distance between elements
|
* Calculate the distance between elements
|
||||||
*/
|
*/
|
||||||
@@ -777,77 +748,33 @@ CheckElementCloser(HnswCandidate * e, List *r, int lc, FmgrInfo *procinfo, Oid c
|
|||||||
* Algorithm 4 from paper
|
* Algorithm 4 from paper
|
||||||
*/
|
*/
|
||||||
static List *
|
static List *
|
||||||
SelectNeighbors(List *c, int m, int lc, FmgrInfo *procinfo, Oid collation, HnswElement e2, HnswCandidate * newCandidate, HnswCandidate * *pruned, bool sortCandidates)
|
SelectNeighbors(List *c, int m, int lc, FmgrInfo *procinfo, Oid collation, HnswCandidate * *pruned)
|
||||||
{
|
{
|
||||||
List *r = NIL;
|
List *r = NIL;
|
||||||
List *w = list_copy(c);
|
List *w = list_copy(c);
|
||||||
pairingheap *wd;
|
pairingheap *wd;
|
||||||
bool mustCalculate = !e2->neighbors[lc].closerSet;
|
|
||||||
List *added = NIL;
|
|
||||||
bool removedAny = false;
|
|
||||||
|
|
||||||
if (list_length(w) <= m)
|
if (list_length(w) <= m)
|
||||||
return w;
|
return w;
|
||||||
|
|
||||||
wd = pairingheap_allocate(CompareNearestCandidates, NULL);
|
wd = pairingheap_allocate(CompareNearestCandidates, NULL);
|
||||||
|
|
||||||
/* Ensure order of candidates is deterministic for closer caching */
|
|
||||||
if (sortCandidates)
|
|
||||||
list_sort(w, CompareCandidateDistances);
|
|
||||||
|
|
||||||
while (list_length(w) > 0 && list_length(r) < m)
|
while (list_length(w) > 0 && list_length(r) < m)
|
||||||
{
|
{
|
||||||
/* Assumes w is already ordered desc */
|
/* Assumes w is already ordered desc */
|
||||||
HnswCandidate *e = llast(w);
|
HnswCandidate *e = llast(w);
|
||||||
|
bool closer;
|
||||||
|
|
||||||
w = list_delete_last(w);
|
w = list_delete_last(w);
|
||||||
|
|
||||||
/* Use previous state of r and wd to skip work when possible */
|
closer = CheckElementCloser(e, r, lc, procinfo, collation);
|
||||||
if (mustCalculate)
|
|
||||||
e->closer = CheckElementCloser(e, r, lc, procinfo, collation);
|
|
||||||
else if (list_length(added) > 0)
|
|
||||||
{
|
|
||||||
/*
|
|
||||||
* If the current candidate was closer, we only need to compare it
|
|
||||||
* with the other candidates that we have added.
|
|
||||||
*/
|
|
||||||
if (e->closer)
|
|
||||||
{
|
|
||||||
e->closer = CheckElementCloser(e, added, lc, procinfo, collation);
|
|
||||||
|
|
||||||
if (!e->closer)
|
if (closer)
|
||||||
removedAny = true;
|
|
||||||
}
|
|
||||||
else
|
|
||||||
{
|
|
||||||
/*
|
|
||||||
* If we have removed any candidates from closer, a candidate
|
|
||||||
* that was not closer earlier might now be.
|
|
||||||
*/
|
|
||||||
if (removedAny)
|
|
||||||
{
|
|
||||||
e->closer = CheckElementCloser(e, r, lc, procinfo, collation);
|
|
||||||
if (e->closer)
|
|
||||||
added = lappend(added, e);
|
|
||||||
}
|
|
||||||
}
|
|
||||||
}
|
|
||||||
else if (e == newCandidate)
|
|
||||||
{
|
|
||||||
e->closer = CheckElementCloser(e, r, lc, procinfo, collation);
|
|
||||||
if (e->closer)
|
|
||||||
added = lappend(added, e);
|
|
||||||
}
|
|
||||||
|
|
||||||
if (e->closer)
|
|
||||||
r = lappend(r, e);
|
r = lappend(r, e);
|
||||||
else
|
else
|
||||||
pairingheap_add(wd, &(CreatePairingHeapNode(e)->ph_node));
|
pairingheap_add(wd, &(CreatePairingHeapNode(e)->ph_node));
|
||||||
}
|
}
|
||||||
|
|
||||||
/* Cached value can only be used in future if sorted deterministically */
|
|
||||||
e2->neighbors[lc].closerSet = sortCandidates;
|
|
||||||
|
|
||||||
/* Keep pruned connections */
|
/* Keep pruned connections */
|
||||||
while (!pairingheap_is_empty(wd) && list_length(r) < m)
|
while (!pairingheap_is_empty(wd) && list_length(r) < m)
|
||||||
r = lappend(r, ((HnswPairingHeapNode *) pairingheap_remove_first(wd))->inner);
|
r = lappend(r, ((HnswPairingHeapNode *) pairingheap_remove_first(wd))->inner);
|
||||||
@@ -901,6 +828,28 @@ AddConnections(HnswElement element, List *neighbors, int m, int lc)
|
|||||||
a->items[a->length++] = *((HnswCandidate *) lfirst(lc2));
|
a->items[a->length++] = *((HnswCandidate *) lfirst(lc2));
|
||||||
}
|
}
|
||||||
|
|
||||||
|
/*
|
||||||
|
* Compare candidate distances
|
||||||
|
*/
|
||||||
|
static int
|
||||||
|
#if PG_VERSION_NUM >= 130000
|
||||||
|
CompareCandidateDistances(const ListCell *a, const ListCell *b)
|
||||||
|
#else
|
||||||
|
CompareCandidateDistances(const void *a, const void *b)
|
||||||
|
#endif
|
||||||
|
{
|
||||||
|
HnswCandidate *hca = lfirst((ListCell *) a);
|
||||||
|
HnswCandidate *hcb = lfirst((ListCell *) b);
|
||||||
|
|
||||||
|
if (hca->distance < hcb->distance)
|
||||||
|
return 1;
|
||||||
|
|
||||||
|
if (hca->distance > hcb->distance)
|
||||||
|
return -1;
|
||||||
|
|
||||||
|
return 0;
|
||||||
|
}
|
||||||
|
|
||||||
/*
|
/*
|
||||||
* Update connections
|
* Update connections
|
||||||
*/
|
*/
|
||||||
@@ -954,12 +903,13 @@ HnswUpdateConnection(HnswElement element, HnswCandidate * hc, int m, int lc, int
|
|||||||
{
|
{
|
||||||
List *c = NIL;
|
List *c = NIL;
|
||||||
|
|
||||||
/* Add candidates */
|
/* Add and sort candidates */
|
||||||
for (int i = 0; i < currentNeighbors->length; i++)
|
for (int i = 0; i < currentNeighbors->length; i++)
|
||||||
c = lappend(c, ¤tNeighbors->items[i]);
|
c = lappend(c, ¤tNeighbors->items[i]);
|
||||||
c = lappend(c, &hc2);
|
c = lappend(c, &hc2);
|
||||||
|
list_sort(c, CompareCandidateDistances);
|
||||||
|
|
||||||
SelectNeighbors(c, m, lc, procinfo, collation, hc->element, &hc2, &pruned, true);
|
SelectNeighbors(c, m, lc, procinfo, collation, &pruned);
|
||||||
|
|
||||||
/* Should not happen */
|
/* Should not happen */
|
||||||
if (pruned == NULL)
|
if (pruned == NULL)
|
||||||
@@ -1058,12 +1008,7 @@ HnswInsertElement(HnswElement element, HnswElement entryPoint, Relation index, F
|
|||||||
else
|
else
|
||||||
lw = w;
|
lw = w;
|
||||||
|
|
||||||
/*
|
neighbors = SelectNeighbors(lw, lm, lc, procinfo, collation, NULL);
|
||||||
* Candidates are sorted, but not deterministically. Could set
|
|
||||||
* sortCandidates to true for in-memory builds to enable closer
|
|
||||||
* caching, but there does not seem to be a difference in performance.
|
|
||||||
*/
|
|
||||||
neighbors = SelectNeighbors(lw, lm, lc, procinfo, collation, element, NULL, NULL, false);
|
|
||||||
|
|
||||||
AddConnections(element, neighbors, lm, lc);
|
AddConnections(element, neighbors, lm, lc);
|
||||||
|
|
||||||
|
|||||||
@@ -11,7 +11,6 @@
|
|||||||
#include "miscadmin.h"
|
#include "miscadmin.h"
|
||||||
#include "storage/bufmgr.h"
|
#include "storage/bufmgr.h"
|
||||||
#include "tcop/tcopprot.h"
|
#include "tcop/tcopprot.h"
|
||||||
#include "utils/datum.h"
|
|
||||||
#include "utils/memutils.h"
|
#include "utils/memutils.h"
|
||||||
|
|
||||||
#if PG_VERSION_NUM >= 140000
|
#if PG_VERSION_NUM >= 140000
|
||||||
@@ -66,18 +65,11 @@
|
|||||||
static void
|
static void
|
||||||
AddSample(Datum *values, IvfflatBuildState * buildstate)
|
AddSample(Datum *values, IvfflatBuildState * buildstate)
|
||||||
{
|
{
|
||||||
MemoryContext oldCtx;
|
VectorArray samples = buildstate->samples;
|
||||||
Datum value;
|
int targsamples = samples->maxlen;
|
||||||
int targsamples = buildstate->targsamples;
|
|
||||||
|
|
||||||
/* Use memory context since detoast can allocate */
|
|
||||||
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
|
|
||||||
|
|
||||||
/* Detoast once for all calls */
|
/* Detoast once for all calls */
|
||||||
value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
|
Datum value = PointerGetDatum(PG_DETOAST_DATUM(values[0]));
|
||||||
|
|
||||||
/* Restore memory context */
|
|
||||||
MemoryContextSwitchTo(oldCtx);
|
|
||||||
|
|
||||||
/*
|
/*
|
||||||
* Normalize with KMEANS_NORM_PROC since spherical distance function
|
* Normalize with KMEANS_NORM_PROC since spherical distance function
|
||||||
@@ -89,23 +81,18 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
|
|||||||
return;
|
return;
|
||||||
}
|
}
|
||||||
|
|
||||||
/* Copy datum */
|
if (samples->length < targsamples)
|
||||||
value = datumCopy(value, false, -1);
|
{
|
||||||
|
VectorArraySet(samples, samples->length, DatumGetVector(value));
|
||||||
/* Reset memory context */
|
samples->length++;
|
||||||
MemoryContextReset(buildstate->tmpCtx);
|
}
|
||||||
|
|
||||||
if (list_length(buildstate->samples) < targsamples)
|
|
||||||
buildstate->samples = lappend(buildstate->samples, DatumGetVector(value));
|
|
||||||
else
|
else
|
||||||
{
|
{
|
||||||
if (buildstate->rowstoskip < 0)
|
if (buildstate->rowstoskip < 0)
|
||||||
buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, list_length(buildstate->samples), targsamples);
|
buildstate->rowstoskip = reservoir_get_next_S(&buildstate->rstate, samples->length, targsamples);
|
||||||
|
|
||||||
if (buildstate->rowstoskip <= 0)
|
if (buildstate->rowstoskip <= 0)
|
||||||
{
|
{
|
||||||
ListCell *lc;
|
|
||||||
|
|
||||||
#if PG_VERSION_NUM >= 150000
|
#if PG_VERSION_NUM >= 150000
|
||||||
int k = (int) (targsamples * sampler_random_fract(&buildstate->rstate.randstate));
|
int k = (int) (targsamples * sampler_random_fract(&buildstate->rstate.randstate));
|
||||||
#else
|
#else
|
||||||
@@ -113,8 +100,7 @@ AddSample(Datum *values, IvfflatBuildState * buildstate)
|
|||||||
#endif
|
#endif
|
||||||
|
|
||||||
Assert(k >= 0 && k < targsamples);
|
Assert(k >= 0 && k < targsamples);
|
||||||
lc = list_nth_cell(buildstate->samples, k);
|
VectorArraySet(samples, k, DatumGetVector(value));
|
||||||
lfirst(lc) = DatumGetVector(value);
|
|
||||||
}
|
}
|
||||||
|
|
||||||
buildstate->rowstoskip -= 1;
|
buildstate->rowstoskip -= 1;
|
||||||
@@ -129,13 +115,21 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
|
|||||||
bool *isnull, bool tupleIsAlive, void *state)
|
bool *isnull, bool tupleIsAlive, void *state)
|
||||||
{
|
{
|
||||||
IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
|
IvfflatBuildState *buildstate = (IvfflatBuildState *) state;
|
||||||
|
MemoryContext oldCtx;
|
||||||
|
|
||||||
/* Skip nulls */
|
/* Skip nulls */
|
||||||
if (isnull[0])
|
if (isnull[0])
|
||||||
return;
|
return;
|
||||||
|
|
||||||
|
/* Use memory context since detoast can allocate */
|
||||||
|
oldCtx = MemoryContextSwitchTo(buildstate->tmpCtx);
|
||||||
|
|
||||||
/* Add sample */
|
/* Add sample */
|
||||||
AddSample(values, buildstate);
|
AddSample(values, state);
|
||||||
|
|
||||||
|
/* Reset memory context */
|
||||||
|
MemoryContextSwitchTo(oldCtx);
|
||||||
|
MemoryContextReset(buildstate->tmpCtx);
|
||||||
}
|
}
|
||||||
|
|
||||||
/*
|
/*
|
||||||
@@ -144,7 +138,7 @@ SampleCallback(Relation index, CALLBACK_ITEM_POINTER, Datum *values,
|
|||||||
static void
|
static void
|
||||||
SampleRows(IvfflatBuildState * buildstate)
|
SampleRows(IvfflatBuildState * buildstate)
|
||||||
{
|
{
|
||||||
int targsamples = buildstate->targsamples;
|
int targsamples = buildstate->samples->maxlen;
|
||||||
BlockNumber totalblocks = RelationGetNumberOfBlocks(buildstate->heap);
|
BlockNumber totalblocks = RelationGetNumberOfBlocks(buildstate->heap);
|
||||||
|
|
||||||
buildstate->rowstoskip = -1;
|
buildstate->rowstoskip = -1;
|
||||||
@@ -455,13 +449,12 @@ ComputeCenters(IvfflatBuildState * buildstate)
|
|||||||
|
|
||||||
/* Sample rows */
|
/* Sample rows */
|
||||||
/* TODO Ensure within maintenance_work_mem */
|
/* TODO Ensure within maintenance_work_mem */
|
||||||
buildstate->samples = NIL;
|
buildstate->samples = VectorArrayInit(numSamples, buildstate->dimensions);
|
||||||
buildstate->targsamples = numSamples;
|
|
||||||
if (buildstate->heap != NULL)
|
if (buildstate->heap != NULL)
|
||||||
{
|
{
|
||||||
SampleRows(buildstate);
|
SampleRows(buildstate);
|
||||||
|
|
||||||
if (list_length(buildstate->samples) < buildstate->lists)
|
if (buildstate->samples->length < buildstate->lists)
|
||||||
{
|
{
|
||||||
ereport(NOTICE,
|
ereport(NOTICE,
|
||||||
(errmsg("ivfflat index created with little data"),
|
(errmsg("ivfflat index created with little data"),
|
||||||
@@ -474,7 +467,7 @@ ComputeCenters(IvfflatBuildState * buildstate)
|
|||||||
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers));
|
IvfflatBench("k-means", IvfflatKmeans(buildstate->index, buildstate->samples, buildstate->centers));
|
||||||
|
|
||||||
/* Free samples before we allocate more memory */
|
/* Free samples before we allocate more memory */
|
||||||
list_free_deep(buildstate->samples);
|
VectorArrayFree(buildstate->samples);
|
||||||
}
|
}
|
||||||
|
|
||||||
/*
|
/*
|
||||||
|
|||||||
@@ -80,10 +80,6 @@
|
|||||||
#define RandomInt() random()
|
#define RandomInt() random()
|
||||||
#endif
|
#endif
|
||||||
|
|
||||||
#if PG_VERSION_NUM < 130000
|
|
||||||
#define list_sort(list, cmp) list_qsort(list, cmp)
|
|
||||||
#endif
|
|
||||||
|
|
||||||
/* Variables */
|
/* Variables */
|
||||||
extern int ivfflat_probes;
|
extern int ivfflat_probes;
|
||||||
|
|
||||||
@@ -182,8 +178,7 @@ typedef struct IvfflatBuildState
|
|||||||
Oid collation;
|
Oid collation;
|
||||||
|
|
||||||
/* Variables */
|
/* Variables */
|
||||||
List *samples;
|
VectorArray samples;
|
||||||
int targsamples;
|
|
||||||
VectorArray centers;
|
VectorArray centers;
|
||||||
ListInfo *listInfo;
|
ListInfo *listInfo;
|
||||||
Vector *normvec;
|
Vector *normvec;
|
||||||
@@ -251,6 +246,8 @@ typedef struct IvfflatScanOpaqueData
|
|||||||
int probes;
|
int probes;
|
||||||
int dimensions;
|
int dimensions;
|
||||||
bool first;
|
bool first;
|
||||||
|
Buffer buf;
|
||||||
|
ItemPointerData heaptid;
|
||||||
|
|
||||||
/* Sorting */
|
/* Sorting */
|
||||||
Tuplesortstate *sortstate;
|
Tuplesortstate *sortstate;
|
||||||
@@ -279,7 +276,7 @@ typedef IvfflatScanOpaqueData * IvfflatScanOpaque;
|
|||||||
VectorArray VectorArrayInit(int maxlen, int dimensions);
|
VectorArray VectorArrayInit(int maxlen, int dimensions);
|
||||||
void VectorArrayFree(VectorArray arr);
|
void VectorArrayFree(VectorArray arr);
|
||||||
void PrintVectorArray(char *msg, VectorArray arr);
|
void PrintVectorArray(char *msg, VectorArray arr);
|
||||||
void IvfflatKmeans(Relation index, List *samples, VectorArray centers);
|
void IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers);
|
||||||
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
|
FmgrInfo *IvfflatOptionalProcInfo(Relation index, uint16 procnum);
|
||||||
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
|
bool IvfflatNormValue(FmgrInfo *procinfo, Oid collation, Datum *value, Vector * result);
|
||||||
int IvfflatGetLists(Relation index);
|
int IvfflatGetLists(Relation index);
|
||||||
|
|||||||
@@ -99,7 +99,7 @@ InsertTuple(Relation index, Datum *values, bool *isnull, ItemPointer heap_tid, R
|
|||||||
|
|
||||||
/* Get tuple size */
|
/* Get tuple size */
|
||||||
itemsz = MAXALIGN(IndexTupleSize(itup));
|
itemsz = MAXALIGN(IndexTupleSize(itup));
|
||||||
Assert(itemsz <= BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(IvfflatPageOpaqueData)) - sizeof(ItemIdData));
|
Assert(itemsz <= BLCKSZ - MAXALIGN(SizeOfPageHeaderData) - MAXALIGN(sizeof(IvfflatPageOpaqueData)));
|
||||||
|
|
||||||
/* Find a page to insert the item */
|
/* Find a page to insert the item */
|
||||||
for (;;)
|
for (;;)
|
||||||
|
|||||||
@@ -12,20 +12,20 @@
|
|||||||
* https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf
|
* https://theory.stanford.edu/~sergei/papers/kMeansPP-soda.pdf
|
||||||
*/
|
*/
|
||||||
static void
|
static void
|
||||||
InitCenters(Relation index, List *samples, VectorArray centers, float *lowerBound)
|
InitCenters(Relation index, VectorArray samples, VectorArray centers, float *lowerBound)
|
||||||
{
|
{
|
||||||
FmgrInfo *procinfo;
|
FmgrInfo *procinfo;
|
||||||
Oid collation;
|
Oid collation;
|
||||||
int64 j;
|
int64 j;
|
||||||
float *weight = palloc(list_length(samples) * sizeof(float));
|
float *weight = palloc(samples->length * sizeof(float));
|
||||||
int numCenters = centers->maxlen;
|
int numCenters = centers->maxlen;
|
||||||
int numSamples = list_length(samples);
|
int numSamples = samples->length;
|
||||||
|
|
||||||
procinfo = index_getprocinfo(index, 1, IVFFLAT_KMEANS_DISTANCE_PROC);
|
procinfo = index_getprocinfo(index, 1, IVFFLAT_KMEANS_DISTANCE_PROC);
|
||||||
collation = index->rd_indcollation[0];
|
collation = index->rd_indcollation[0];
|
||||||
|
|
||||||
/* Choose an initial center uniformly at random */
|
/* Choose an initial center uniformly at random */
|
||||||
VectorArraySet(centers, 0, list_nth(samples, RandomInt() % list_length(samples)));
|
VectorArraySet(centers, 0, VectorArrayGet(samples, RandomInt() % samples->length));
|
||||||
centers->length++;
|
centers->length++;
|
||||||
|
|
||||||
for (j = 0; j < numSamples; j++)
|
for (j = 0; j < numSamples; j++)
|
||||||
@@ -42,7 +42,7 @@ InitCenters(Relation index, List *samples, VectorArray centers, float *lowerBoun
|
|||||||
|
|
||||||
for (j = 0; j < numSamples; j++)
|
for (j = 0; j < numSamples; j++)
|
||||||
{
|
{
|
||||||
Vector *vec = list_nth(samples, j);
|
Vector *vec = VectorArrayGet(samples, j);
|
||||||
double distance;
|
double distance;
|
||||||
|
|
||||||
/* Only need to compute distance for new center */
|
/* Only need to compute distance for new center */
|
||||||
@@ -74,7 +74,7 @@ InitCenters(Relation index, List *samples, VectorArray centers, float *lowerBoun
|
|||||||
break;
|
break;
|
||||||
}
|
}
|
||||||
|
|
||||||
VectorArraySet(centers, i + 1, list_nth(samples, j));
|
VectorArraySet(centers, i + 1, VectorArrayGet(samples, j));
|
||||||
centers->length++;
|
centers->length++;
|
||||||
}
|
}
|
||||||
|
|
||||||
@@ -106,41 +106,25 @@ CompareVectors(const void *a, const void *b)
|
|||||||
return vector_cmp_internal((Vector *) a, (Vector *) b);
|
return vector_cmp_internal((Vector *) a, (Vector *) b);
|
||||||
}
|
}
|
||||||
|
|
||||||
/*
|
|
||||||
* Compare list vectors
|
|
||||||
*/
|
|
||||||
static int
|
|
||||||
#if PG_VERSION_NUM >= 130000
|
|
||||||
CompareListVectors(const ListCell *a, const ListCell *b)
|
|
||||||
#else
|
|
||||||
CompareListVectors(const void *a, const void *b)
|
|
||||||
#endif
|
|
||||||
{
|
|
||||||
Vector *va = lfirst((ListCell *) a);
|
|
||||||
Vector *vb = lfirst((ListCell *) b);
|
|
||||||
|
|
||||||
return CompareVectors(va, vb);
|
|
||||||
}
|
|
||||||
|
|
||||||
/*
|
/*
|
||||||
* Quick approach if we have little data
|
* Quick approach if we have little data
|
||||||
*/
|
*/
|
||||||
static void
|
static void
|
||||||
QuickCenters(Relation index, List *samples, VectorArray centers)
|
QuickCenters(Relation index, VectorArray samples, VectorArray centers)
|
||||||
{
|
{
|
||||||
int dimensions = centers->dim;
|
int dimensions = centers->dim;
|
||||||
Oid collation = index->rd_indcollation[0];
|
Oid collation = index->rd_indcollation[0];
|
||||||
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
|
FmgrInfo *normprocinfo = IvfflatOptionalProcInfo(index, IVFFLAT_KMEANS_NORM_PROC);
|
||||||
|
|
||||||
/* Copy existing vectors while avoiding duplicates */
|
/* Copy existing vectors while avoiding duplicates */
|
||||||
if (list_length(samples) > 0)
|
if (samples->length > 0)
|
||||||
{
|
{
|
||||||
list_sort(samples, CompareListVectors);
|
qsort(samples->items, samples->length, VECTOR_SIZE(samples->dim), CompareVectors);
|
||||||
for (int i = 0; i < list_length(samples); i++)
|
for (int i = 0; i < samples->length; i++)
|
||||||
{
|
{
|
||||||
Vector *vec = list_nth(samples, i);
|
Vector *vec = VectorArrayGet(samples, i);
|
||||||
|
|
||||||
if (i == 0 || CompareVectors(vec, list_nth(samples, i - 1)) != 0)
|
if (i == 0 || CompareVectors(vec, VectorArrayGet(samples, i - 1)) != 0)
|
||||||
{
|
{
|
||||||
VectorArraySet(centers, centers->length, vec);
|
VectorArraySet(centers, centers->length, vec);
|
||||||
centers->length++;
|
centers->length++;
|
||||||
@@ -176,7 +160,7 @@ QuickCenters(Relation index, List *samples, VectorArray centers)
|
|||||||
* https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
|
* https://www.aaai.org/Papers/ICML/2003/ICML03-022.pdf
|
||||||
*/
|
*/
|
||||||
static void
|
static void
|
||||||
ElkanKmeans(Relation index, List *samples, VectorArray centers)
|
ElkanKmeans(Relation index, VectorArray samples, VectorArray centers)
|
||||||
{
|
{
|
||||||
FmgrInfo *procinfo;
|
FmgrInfo *procinfo;
|
||||||
FmgrInfo *normprocinfo;
|
FmgrInfo *normprocinfo;
|
||||||
@@ -187,7 +171,7 @@ ElkanKmeans(Relation index, List *samples, VectorArray centers)
|
|||||||
int64 k;
|
int64 k;
|
||||||
int dimensions = centers->dim;
|
int dimensions = centers->dim;
|
||||||
int numCenters = centers->maxlen;
|
int numCenters = centers->maxlen;
|
||||||
int numSamples = list_length(samples);
|
int numSamples = samples->length;
|
||||||
VectorArray newCenters;
|
VectorArray newCenters;
|
||||||
int *centerCounts;
|
int *centerCounts;
|
||||||
int *closestCenters;
|
int *closestCenters;
|
||||||
@@ -198,7 +182,7 @@ ElkanKmeans(Relation index, List *samples, VectorArray centers)
|
|||||||
float *newcdist;
|
float *newcdist;
|
||||||
|
|
||||||
/* Calculate allocation sizes */
|
/* Calculate allocation sizes */
|
||||||
Size samplesSize = 0;
|
Size samplesSize = VECTOR_ARRAY_SIZE(samples->maxlen, samples->dim);
|
||||||
Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->dim);
|
Size centersSize = VECTOR_ARRAY_SIZE(centers->maxlen, centers->dim);
|
||||||
Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, dimensions);
|
Size newCentersSize = VECTOR_ARRAY_SIZE(numCenters, dimensions);
|
||||||
Size centerCountsSize = sizeof(int) * numCenters;
|
Size centerCountsSize = sizeof(int) * numCenters;
|
||||||
@@ -342,7 +326,7 @@ ElkanKmeans(Relation index, List *samples, VectorArray centers)
|
|||||||
if (upperBound[j] <= halfcdist[closestCenters[j] * numCenters + k])
|
if (upperBound[j] <= halfcdist[closestCenters[j] * numCenters + k])
|
||||||
continue;
|
continue;
|
||||||
|
|
||||||
vec = list_nth(samples, j);
|
vec = VectorArrayGet(samples, j);
|
||||||
|
|
||||||
/* Step 3a */
|
/* Step 3a */
|
||||||
if (rj)
|
if (rj)
|
||||||
@@ -393,7 +377,7 @@ ElkanKmeans(Relation index, List *samples, VectorArray centers)
|
|||||||
{
|
{
|
||||||
int closestCenter;
|
int closestCenter;
|
||||||
|
|
||||||
vec = list_nth(samples, j);
|
vec = VectorArrayGet(samples, j);
|
||||||
closestCenter = closestCenters[j];
|
closestCenter = closestCenters[j];
|
||||||
|
|
||||||
/* Increment sum and count of closest center */
|
/* Increment sum and count of closest center */
|
||||||
@@ -530,9 +514,9 @@ CheckCenters(Relation index, VectorArray centers)
|
|||||||
* We use spherical k-means for inner product and cosine
|
* We use spherical k-means for inner product and cosine
|
||||||
*/
|
*/
|
||||||
void
|
void
|
||||||
IvfflatKmeans(Relation index, List *samples, VectorArray centers)
|
IvfflatKmeans(Relation index, VectorArray samples, VectorArray centers)
|
||||||
{
|
{
|
||||||
if (list_length(samples) <= centers->maxlen)
|
if (samples->length <= centers->maxlen)
|
||||||
QuickCenters(index, samples, centers);
|
QuickCenters(index, samples, centers);
|
||||||
else
|
else
|
||||||
ElkanKmeans(index, samples, centers);
|
ElkanKmeans(index, samples, centers);
|
||||||
|
|||||||
@@ -143,6 +143,10 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
|||||||
bool isnull;
|
bool isnull;
|
||||||
ItemId itemid = PageGetItemId(page, offno);
|
ItemId itemid = PageGetItemId(page, offno);
|
||||||
|
|
||||||
|
/* Skip dead tuples */
|
||||||
|
if (scan->ignore_killed_tuples && ItemIdIsDead(itemid))
|
||||||
|
continue;
|
||||||
|
|
||||||
itup = (IndexTuple) PageGetItem(page, itemid);
|
itup = (IndexTuple) PageGetItem(page, itemid);
|
||||||
datum = index_getattr(itup, 1, tupdesc, &isnull);
|
datum = index_getattr(itup, 1, tupdesc, &isnull);
|
||||||
|
|
||||||
@@ -157,6 +161,8 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
|||||||
slot->tts_isnull[0] = false;
|
slot->tts_isnull[0] = false;
|
||||||
slot->tts_values[1] = PointerGetDatum(&itup->t_tid);
|
slot->tts_values[1] = PointerGetDatum(&itup->t_tid);
|
||||||
slot->tts_isnull[1] = false;
|
slot->tts_isnull[1] = false;
|
||||||
|
slot->tts_values[2] = Int32GetDatum((int) searchPage);
|
||||||
|
slot->tts_isnull[2] = false;
|
||||||
ExecStoreVirtualTuple(slot);
|
ExecStoreVirtualTuple(slot);
|
||||||
|
|
||||||
tuplesort_puttupleslot(so->sortstate, slot);
|
tuplesort_puttupleslot(so->sortstate, slot);
|
||||||
@@ -181,6 +187,55 @@ GetScanItems(IndexScanDesc scan, Datum value)
|
|||||||
tuplesort_performsort(so->sortstate);
|
tuplesort_performsort(so->sortstate);
|
||||||
}
|
}
|
||||||
|
|
||||||
|
/*
|
||||||
|
* Mark prior tuple as dead
|
||||||
|
*/
|
||||||
|
static void
|
||||||
|
MarkPriorTupleDead(IndexScanDesc scan)
|
||||||
|
{
|
||||||
|
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
|
||||||
|
Buffer buf = so->buf;
|
||||||
|
Page page;
|
||||||
|
OffsetNumber maxoffno;
|
||||||
|
|
||||||
|
/* Safety check */
|
||||||
|
if (!BufferIsValid(so->buf) || !ItemPointerIsValid(&so->heaptid))
|
||||||
|
return;
|
||||||
|
|
||||||
|
/* Only a shared locked is needed for ItemIdMarkDead */
|
||||||
|
LockBuffer(buf, BUFFER_LOCK_SHARE);
|
||||||
|
page = BufferGetPage(buf);
|
||||||
|
maxoffno = PageGetMaxOffsetNumber(page);
|
||||||
|
|
||||||
|
for (OffsetNumber offno = FirstOffsetNumber; offno <= maxoffno; offno = OffsetNumberNext(offno))
|
||||||
|
{
|
||||||
|
ItemId itemid = PageGetItemId(page, offno);
|
||||||
|
IndexTuple itup = (IndexTuple) PageGetItem(page, itemid);
|
||||||
|
|
||||||
|
/*
|
||||||
|
* Find tuple. Since buffer has been pinned, tuple cannot have been
|
||||||
|
* vacuumed (and heap TID reused).
|
||||||
|
*/
|
||||||
|
if (ItemPointerEquals(&itup->t_tid, &so->heaptid))
|
||||||
|
{
|
||||||
|
/*
|
||||||
|
* Make sure tuple has not already been marked dead to avoid extra
|
||||||
|
* WAL if wal_log_hints or data checksums enabled
|
||||||
|
*/
|
||||||
|
if (!ItemIdIsDead(itemid))
|
||||||
|
{
|
||||||
|
ItemIdMarkDead(itemid);
|
||||||
|
MarkBufferDirtyHint(buf, true);
|
||||||
|
}
|
||||||
|
|
||||||
|
break;
|
||||||
|
}
|
||||||
|
}
|
||||||
|
|
||||||
|
/* Unlock buffer */
|
||||||
|
LockBuffer(buf, BUFFER_LOCK_UNLOCK);
|
||||||
|
}
|
||||||
|
|
||||||
/*
|
/*
|
||||||
* Prepare for an index scan
|
* Prepare for an index scan
|
||||||
*/
|
*/
|
||||||
@@ -206,7 +261,9 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
|
|||||||
probes = lists;
|
probes = lists;
|
||||||
|
|
||||||
so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
|
so = (IvfflatScanOpaque) palloc(offsetof(IvfflatScanOpaqueData, lists) + probes * sizeof(IvfflatScanList));
|
||||||
|
so->buf = InvalidBuffer;
|
||||||
so->first = true;
|
so->first = true;
|
||||||
|
ItemPointerSetInvalid(&so->heaptid);
|
||||||
so->probes = probes;
|
so->probes = probes;
|
||||||
so->dimensions = dimensions;
|
so->dimensions = dimensions;
|
||||||
|
|
||||||
@@ -217,12 +274,13 @@ ivfflatbeginscan(Relation index, int nkeys, int norderbys)
|
|||||||
|
|
||||||
/* Create tuple description for sorting */
|
/* Create tuple description for sorting */
|
||||||
#if PG_VERSION_NUM >= 120000
|
#if PG_VERSION_NUM >= 120000
|
||||||
so->tupdesc = CreateTemplateTupleDesc(2);
|
so->tupdesc = CreateTemplateTupleDesc(3);
|
||||||
#else
|
#else
|
||||||
so->tupdesc = CreateTemplateTupleDesc(2, false);
|
so->tupdesc = CreateTemplateTupleDesc(3, false);
|
||||||
#endif
|
#endif
|
||||||
TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
|
TupleDescInitEntry(so->tupdesc, (AttrNumber) 1, "distance", FLOAT8OID, -1, 0);
|
||||||
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
|
TupleDescInitEntry(so->tupdesc, (AttrNumber) 2, "heaptid", TIDOID, -1, 0);
|
||||||
|
TupleDescInitEntry(so->tupdesc, (AttrNumber) 3, "indexblkno", INT4OID, -1, 0);
|
||||||
|
|
||||||
/* Prep sort */
|
/* Prep sort */
|
||||||
so->sortstate = tuplesort_begin_heap(so->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
|
so->sortstate = tuplesort_begin_heap(so->tupdesc, 1, attNums, sortOperators, sortCollations, nullsFirstFlags, work_mem, NULL, false);
|
||||||
@@ -254,6 +312,7 @@ ivfflatrescan(IndexScanDesc scan, ScanKey keys, int nkeys, ScanKey orderbys, int
|
|||||||
#endif
|
#endif
|
||||||
|
|
||||||
so->first = true;
|
so->first = true;
|
||||||
|
ItemPointerSetInvalid(&so->heaptid);
|
||||||
pairingheap_reset(so->listQueue);
|
pairingheap_reset(so->listQueue);
|
||||||
|
|
||||||
if (keys && scan->numberOfKeys > 0)
|
if (keys && scan->numberOfKeys > 0)
|
||||||
@@ -288,11 +347,6 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
|
|||||||
if (scan->orderByData == NULL)
|
if (scan->orderByData == NULL)
|
||||||
elog(ERROR, "cannot scan ivfflat index without order");
|
elog(ERROR, "cannot scan ivfflat index without order");
|
||||||
|
|
||||||
/* Requires MVCC-compliant snapshot as not able to pin during sorting */
|
|
||||||
/* https://www.postgresql.org/docs/current/index-locking.html */
|
|
||||||
if (!IsMVCCSnapshot(scan->xs_snapshot))
|
|
||||||
elog(ERROR, "non-MVCC snapshots are not supported with ivfflat");
|
|
||||||
|
|
||||||
if (scan->orderByData->sk_flags & SK_ISNULL)
|
if (scan->orderByData->sk_flags & SK_ISNULL)
|
||||||
value = PointerGetDatum(InitVector(so->dimensions));
|
value = PointerGetDatum(InitVector(so->dimensions));
|
||||||
else
|
else
|
||||||
@@ -316,10 +370,17 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
|
|||||||
if (value != scan->orderByData->sk_argument)
|
if (value != scan->orderByData->sk_argument)
|
||||||
pfree(DatumGetPointer(value));
|
pfree(DatumGetPointer(value));
|
||||||
}
|
}
|
||||||
|
else
|
||||||
|
{
|
||||||
|
/* Mark prior tuple as dead */
|
||||||
|
if (scan->kill_prior_tuple)
|
||||||
|
MarkPriorTupleDead(scan);
|
||||||
|
}
|
||||||
|
|
||||||
if (tuplesort_gettupleslot(so->sortstate, true, false, so->slot, NULL))
|
if (tuplesort_gettupleslot(so->sortstate, true, false, so->slot, NULL))
|
||||||
{
|
{
|
||||||
ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
|
ItemPointer heaptid = (ItemPointer) DatumGetPointer(slot_getattr(so->slot, 2, &so->isnull));
|
||||||
|
BlockNumber indexblkno = DatumGetInt32(slot_getattr(so->slot, 3, &so->isnull));
|
||||||
|
|
||||||
#if PG_VERSION_NUM >= 120000
|
#if PG_VERSION_NUM >= 120000
|
||||||
scan->xs_heaptid = *heaptid;
|
scan->xs_heaptid = *heaptid;
|
||||||
@@ -327,6 +388,21 @@ ivfflatgettuple(IndexScanDesc scan, ScanDirection dir)
|
|||||||
scan->xs_ctup.t_self = *heaptid;
|
scan->xs_ctup.t_self = *heaptid;
|
||||||
#endif
|
#endif
|
||||||
|
|
||||||
|
/* Keep track of info needed to mark tuple as dead */
|
||||||
|
so->heaptid = *heaptid;
|
||||||
|
|
||||||
|
/* Unpin buffer */
|
||||||
|
if (BufferIsValid(so->buf))
|
||||||
|
ReleaseBuffer(so->buf);
|
||||||
|
|
||||||
|
/*
|
||||||
|
* An index scan must maintain a pin on the index page holding the
|
||||||
|
* item last returned by amgettuple
|
||||||
|
*
|
||||||
|
* https://www.postgresql.org/docs/current/index-locking.html
|
||||||
|
*/
|
||||||
|
so->buf = ReadBuffer(scan->indexRelation, indexblkno);
|
||||||
|
|
||||||
scan->xs_recheckorderby = false;
|
scan->xs_recheckorderby = false;
|
||||||
return true;
|
return true;
|
||||||
}
|
}
|
||||||
@@ -342,6 +418,10 @@ ivfflatendscan(IndexScanDesc scan)
|
|||||||
{
|
{
|
||||||
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
|
IvfflatScanOpaque so = (IvfflatScanOpaque) scan->opaque;
|
||||||
|
|
||||||
|
/* Release pin */
|
||||||
|
if (BufferIsValid(so->buf))
|
||||||
|
ReleaseBuffer(so->buf);
|
||||||
|
|
||||||
pairingheap_free(so->listQueue);
|
pairingheap_free(so->listQueue);
|
||||||
tuplesort_end(so->sortstate);
|
tuplesort_end(so->sortstate);
|
||||||
|
|
||||||
|
|||||||
@@ -1,4 +1,4 @@
|
|||||||
comment = 'vector data type and ivfflat and hnsw access methods'
|
comment = 'vector data type and ivfflat and hnsw access methods'
|
||||||
default_version = '0.5.1'
|
default_version = '0.5.0'
|
||||||
module_pathname = '$libdir/vector'
|
module_pathname = '$libdir/vector'
|
||||||
relocatable = true
|
relocatable = true
|
||||||
|
|||||||
Reference in New Issue
Block a user