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Merge branch 'main' of github.com:asg017/sqlite-vec

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Alex Garcia 2026-02-13 06:47:20 -08:00
commit fb31b780f5
3 changed files with 492 additions and 2 deletions
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139
sqlite-vec.c
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@ -5305,11 +5305,21 @@ static int vec0Close(sqlite3_vtab_cursor *cur) {
typedef enum { typedef enum {
// If any values are updated, please update the ARCHITECTURE.md docs accordingly! // If any values are updated, please update the ARCHITECTURE.md docs accordingly!
// ~~~ KNN QUERIES ~~~ //
VEC0_IDXSTR_KIND_KNN_MATCH = '{', VEC0_IDXSTR_KIND_KNN_MATCH = '{',
VEC0_IDXSTR_KIND_KNN_K = '}', VEC0_IDXSTR_KIND_KNN_K = '}',
VEC0_IDXSTR_KIND_KNN_ROWID_IN = '[', VEC0_IDXSTR_KIND_KNN_ROWID_IN = '[',
// argv[i] is a constraint on a PARTITON KEY column in a KNN query
//
VEC0_IDXSTR_KIND_KNN_PARTITON_CONSTRAINT = ']', VEC0_IDXSTR_KIND_KNN_PARTITON_CONSTRAINT = ']',
// argv[i] is a constraint on the distance column in a KNN query
VEC0_IDXSTR_KIND_KNN_DISTANCE_CONSTRAINT = '*',
// ~~~ POINT QUERIES ~~~ //
VEC0_IDXSTR_KIND_POINT_ID = '!', VEC0_IDXSTR_KIND_POINT_ID = '!',
// ~~~ ??? ~~~ //
VEC0_IDXSTR_KIND_METADATA_CONSTRAINT = '&', VEC0_IDXSTR_KIND_METADATA_CONSTRAINT = '&',
} vec0_idxstr_kind; } vec0_idxstr_kind;
@ -5318,11 +5328,22 @@ typedef enum {
typedef enum { typedef enum {
// If any values are updated, please update the ARCHITECTURE.md docs accordingly! // If any values are updated, please update the ARCHITECTURE.md docs accordingly!
// Equality constraint on a PARTITON KEY column, ex `user_id = 123`
VEC0_PARTITION_OPERATOR_EQ = 'a', VEC0_PARTITION_OPERATOR_EQ = 'a',
// "Greater than" constraint on a PARTITON KEY column, ex `year > 2024`
VEC0_PARTITION_OPERATOR_GT = 'b', VEC0_PARTITION_OPERATOR_GT = 'b',
// "Less than or equal to" constraint on a PARTITON KEY column, ex `year <= 2024`
VEC0_PARTITION_OPERATOR_LE = 'c', VEC0_PARTITION_OPERATOR_LE = 'c',
// "Less than" constraint on a PARTITON KEY column, ex `year < 2024`
VEC0_PARTITION_OPERATOR_LT = 'd', VEC0_PARTITION_OPERATOR_LT = 'd',
// "Greater than or equal to" constraint on a PARTITON KEY column, ex `year >= 2024`
VEC0_PARTITION_OPERATOR_GE = 'e', VEC0_PARTITION_OPERATOR_GE = 'e',
// "Not equal to" constraint on a PARTITON KEY column, ex `year != 2024`
VEC0_PARTITION_OPERATOR_NE = 'f', VEC0_PARTITION_OPERATOR_NE = 'f',
} vec0_partition_operator; } vec0_partition_operator;
typedef enum { typedef enum {
@ -5335,6 +5356,15 @@ typedef enum {
VEC0_METADATA_OPERATOR_IN = 'g', VEC0_METADATA_OPERATOR_IN = 'g',
} vec0_metadata_operator; } vec0_metadata_operator;
typedef enum {
VEC0_DISTANCE_CONSTRAINT_GT = 'a',
VEC0_DISTANCE_CONSTRAINT_GE = 'b',
VEC0_DISTANCE_CONSTRAINT_LT = 'c',
VEC0_DISTANCE_CONSTRAINT_LE = 'd',
} vec0_distance_constraint_operator;
static int vec0BestIndex(sqlite3_vtab *pVTab, sqlite3_index_info *pIdxInfo) { static int vec0BestIndex(sqlite3_vtab *pVTab, sqlite3_index_info *pIdxInfo) {
vec0_vtab *p = (vec0_vtab *)pVTab; vec0_vtab *p = (vec0_vtab *)pVTab;
/** /**
@ -5494,6 +5524,7 @@ static int vec0BestIndex(sqlite3_vtab *pVTab, sqlite3_index_info *pIdxInfo) {
} }
#endif #endif
// find any PARTITION KEY column constraints
for (int i = 0; i < pIdxInfo->nConstraint; i++) { for (int i = 0; i < pIdxInfo->nConstraint; i++) {
if (!pIdxInfo->aConstraint[i].usable) if (!pIdxInfo->aConstraint[i].usable)
continue; continue;
@ -5548,6 +5579,7 @@ static int vec0BestIndex(sqlite3_vtab *pVTab, sqlite3_index_info *pIdxInfo) {
} }
// find any metadata column constraints
for (int i = 0; i < pIdxInfo->nConstraint; i++) { for (int i = 0; i < pIdxInfo->nConstraint; i++) {
if (!pIdxInfo->aConstraint[i].usable) if (!pIdxInfo->aConstraint[i].usable)
continue; continue;
@ -5644,6 +5676,58 @@ static int vec0BestIndex(sqlite3_vtab *pVTab, sqlite3_index_info *pIdxInfo) {
} }
// find any distance column constraints
for (int i = 0; i < pIdxInfo->nConstraint; i++) {
if (!pIdxInfo->aConstraint[i].usable)
continue;
int iColumn = pIdxInfo->aConstraint[i].iColumn;
int op = pIdxInfo->aConstraint[i].op;
if(op == SQLITE_INDEX_CONSTRAINT_LIMIT || op == SQLITE_INDEX_CONSTRAINT_OFFSET) {
continue;
}
if(vec0_column_distance_idx(p) != iColumn) {
continue;
}
char value = 0;
switch(op) {
case SQLITE_INDEX_CONSTRAINT_GT: {
value = VEC0_DISTANCE_CONSTRAINT_GT;
break;
}
case SQLITE_INDEX_CONSTRAINT_GE: {
value = VEC0_DISTANCE_CONSTRAINT_GE;
break;
}
case SQLITE_INDEX_CONSTRAINT_LT: {
value = VEC0_DISTANCE_CONSTRAINT_LT;
break;
}
case SQLITE_INDEX_CONSTRAINT_LE: {
value = VEC0_DISTANCE_CONSTRAINT_LE;
break;
}
default: {
// IMP TODO
rc = SQLITE_ERROR;
vtab_set_error(
pVTab,
"Illegal WHERE constraint on distance column in a KNN query. "
"Only one of GT, GE, LT, LE constraints are allowed."
);
goto done;
}
}
pIdxInfo->aConstraintUsage[i].argvIndex = argvIndex++;
pIdxInfo->aConstraintUsage[i].omit = 1;
sqlite3_str_appendchar(idxStr, 1, VEC0_IDXSTR_KIND_KNN_DISTANCE_CONSTRAINT);
sqlite3_str_appendchar(idxStr, 1, value);
sqlite3_str_appendchar(idxStr, 1, '_');
sqlite3_str_appendchar(idxStr, 1, '_');
}
pIdxInfo->idxNum = iMatchVectorTerm; pIdxInfo->idxNum = iMatchVectorTerm;
@ -5672,7 +5756,6 @@ static int vec0BestIndex(sqlite3_vtab *pVTab, sqlite3_index_info *pIdxInfo) {
} }
pIdxInfo->needToFreeIdxStr = 1; pIdxInfo->needToFreeIdxStr = 1;
rc = SQLITE_OK; rc = SQLITE_OK;
done: done:
@ -6560,12 +6643,15 @@ int vec0Filter_knn_chunks_iter(vec0_vtab *p, sqlite3_stmt *stmtChunks,
int numValueEntries = (idxStrLength-1) / 4; int numValueEntries = (idxStrLength-1) / 4;
assert(numValueEntries == argc); assert(numValueEntries == argc);
int hasMetadataFilters = 0; int hasMetadataFilters = 0;
int hasDistanceConstraints = 0;
for(int i = 0; i < argc; i++) { for(int i = 0; i < argc; i++) {
int idx = 1 + (i * 4); int idx = 1 + (i * 4);
char kind = idxStr[idx + 0]; char kind = idxStr[idx + 0];
if(kind == VEC0_IDXSTR_KIND_METADATA_CONSTRAINT) { if(kind == VEC0_IDXSTR_KIND_METADATA_CONSTRAINT) {
hasMetadataFilters = 1; hasMetadataFilters = 1;
break; }
else if(kind == VEC0_IDXSTR_KIND_KNN_DISTANCE_CONSTRAINT) {
hasDistanceConstraints = 1;
} }
} }
@ -6752,6 +6838,55 @@ int vec0Filter_knn_chunks_iter(vec0_vtab *p, sqlite3_stmt *stmtChunks,
chunk_distances[i] = result; chunk_distances[i] = result;
} }
if(hasDistanceConstraints) {
for(int i = 0; i < argc; i++) {
int idx = 1 + (i * 4);
char kind = idxStr[idx + 0];
// TODO casts f64 to f32, is that a problem?
f32 target = (f32) sqlite3_value_double(argv[i]);
if(kind != VEC0_IDXSTR_KIND_KNN_DISTANCE_CONSTRAINT) {
continue;
}
vec0_distance_constraint_operator op = idxStr[idx + 1];
switch(op) {
case VEC0_DISTANCE_CONSTRAINT_GE: {
for(int i = 0; i < p->chunk_size;i++) {
if(bitmap_get(b, i) && !(chunk_distances[i] >= target)) {
bitmap_set(b, i, 0);
}
}
break;
}
case VEC0_DISTANCE_CONSTRAINT_GT: {
for(int i = 0; i < p->chunk_size;i++) {
if(bitmap_get(b, i) && !(chunk_distances[i] > target)) {
bitmap_set(b, i, 0);
}
}
break;
}
case VEC0_DISTANCE_CONSTRAINT_LE: {
for(int i = 0; i < p->chunk_size;i++) {
if(bitmap_get(b, i) && !(chunk_distances[i] <= target)) {
bitmap_set(b, i, 0);
}
}
break;
}
case VEC0_DISTANCE_CONSTRAINT_LT: {
for(int i = 0; i < p->chunk_size;i++) {
if(bitmap_get(b, i) && !(chunk_distances[i] < target)) {
bitmap_set(b, i, 0);
}
}
break;
}
}
}
}
int used1; int used1;
min_idx(chunk_distances, p->chunk_size, b, chunk_topk_idxs, min_idx(chunk_distances, p->chunk_size, b, chunk_topk_idxs,
min(k, p->chunk_size), bTaken, &used1); min(k, p->chunk_size), bTaken, &used1);

273
tests/__snapshots__/test-knn-distance-constraints.ambr Normal file
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@ -0,0 +1,273 @@
# serializer version: 1
# name: test_normal
OrderedDict({
'sql': 'SELECT * FROM v',
'rows': list([
OrderedDict({
'rowid': 1,
'embedding': b'\x00\x00\x80?',
'is_odd': 1,
}),
OrderedDict({
'rowid': 2,
'embedding': b'\x00\x00\x00@',
'is_odd': 0,
}),
OrderedDict({
'rowid': 3,
'embedding': b'\x00\x00@@',
'is_odd': 1,
}),
OrderedDict({
'rowid': 4,
'embedding': b'\x00\x00\x80@',
'is_odd': 0,
}),
OrderedDict({
'rowid': 5,
'embedding': b'\x00\x00\xa0@',
'is_odd': 1,
}),
OrderedDict({
'rowid': 6,
'embedding': b'\x00\x00\xc0@',
'is_odd': 0,
}),
OrderedDict({
'rowid': 7,
'embedding': b'\x00\x00\xe0@',
'is_odd': 1,
}),
OrderedDict({
'rowid': 8,
'embedding': b'\x00\x00\x00A',
'is_odd': 0,
}),
OrderedDict({
'rowid': 9,
'embedding': b'\x00\x00\x10A',
'is_odd': 1,
}),
OrderedDict({
'rowid': 10,
'embedding': b'\x00\x00 A',
'is_odd': 0,
}),
OrderedDict({
'rowid': 11,
'embedding': b'\x00\x000A',
'is_odd': 1,
}),
OrderedDict({
'rowid': 12,
'embedding': b'\x00\x00@A',
'is_odd': 0,
}),
OrderedDict({
'rowid': 13,
'embedding': b'\x00\x00PA',
'is_odd': 1,
}),
OrderedDict({
'rowid': 14,
'embedding': b'\x00\x00`A',
'is_odd': 0,
}),
OrderedDict({
'rowid': 15,
'embedding': b'\x00\x00pA',
'is_odd': 1,
}),
OrderedDict({
'rowid': 16,
'embedding': b'\x00\x00\x80A',
'is_odd': 0,
}),
OrderedDict({
'rowid': 17,
'embedding': b'\x00\x00\x88A',
'is_odd': 1,
}),
]),
})
# ---
# name: test_normal.1
OrderedDict({
'sql': 'select rowid, distance from v where embedding match ? and k = ? ',
'rows': list([
OrderedDict({
'rowid': 1,
'distance': 0.0,
}),
OrderedDict({
'rowid': 2,
'distance': 1.0,
}),
OrderedDict({
'rowid': 3,
'distance': 2.0,
}),
OrderedDict({
'rowid': 4,
'distance': 3.0,
}),
OrderedDict({
'rowid': 5,
'distance': 4.0,
}),
]),
})
# ---
# name: test_normal.2
OrderedDict({
'sql': 'select rowid, distance from v where embedding match ? and k = ? AND distance > 5',
'rows': list([
OrderedDict({
'rowid': 7,
'distance': 6.0,
}),
OrderedDict({
'rowid': 8,
'distance': 7.0,
}),
OrderedDict({
'rowid': 9,
'distance': 8.0,
}),
OrderedDict({
'rowid': 10,
'distance': 9.0,
}),
OrderedDict({
'rowid': 11,
'distance': 10.0,
}),
]),
})
# ---
# name: test_normal.3
OrderedDict({
'sql': 'select rowid, distance from v where embedding match ? and k = ? AND distance >= 5',
'rows': list([
OrderedDict({
'rowid': 6,
'distance': 5.0,
}),
OrderedDict({
'rowid': 7,
'distance': 6.0,
}),
OrderedDict({
'rowid': 8,
'distance': 7.0,
}),
OrderedDict({
'rowid': 9,
'distance': 8.0,
}),
OrderedDict({
'rowid': 10,
'distance': 9.0,
}),
]),
})
# ---
# name: test_normal.4
OrderedDict({
'sql': 'select rowid, distance from v where embedding match ? and k = ? AND distance < 3',
'rows': list([
OrderedDict({
'rowid': 1,
'distance': 0.0,
}),
OrderedDict({
'rowid': 2,
'distance': 1.0,
}),
OrderedDict({
'rowid': 3,
'distance': 2.0,
}),
]),
})
# ---
# name: test_normal.5
OrderedDict({
'sql': 'select rowid, distance from v where embedding match ? and k = ? AND distance <= 3',
'rows': list([
OrderedDict({
'rowid': 1,
'distance': 0.0,
}),
OrderedDict({
'rowid': 2,
'distance': 1.0,
}),
OrderedDict({
'rowid': 3,
'distance': 2.0,
}),
OrderedDict({
'rowid': 4,
'distance': 3.0,
}),
]),
})
# ---
# name: test_normal.6
OrderedDict({
'sql': 'select rowid, distance from v where embedding match ? and k = ? AND distance > 7 AND distance <= 10',
'rows': list([
OrderedDict({
'rowid': 9,
'distance': 8.0,
}),
OrderedDict({
'rowid': 10,
'distance': 9.0,
}),
OrderedDict({
'rowid': 11,
'distance': 10.0,
}),
]),
})
# ---
# name: test_normal.7
OrderedDict({
'sql': 'select rowid, distance from v where embedding match ? and k = ? AND distance BETWEEN 7 AND 10',
'rows': list([
OrderedDict({
'rowid': 8,
'distance': 7.0,
}),
OrderedDict({
'rowid': 9,
'distance': 8.0,
}),
OrderedDict({
'rowid': 10,
'distance': 9.0,
}),
OrderedDict({
'rowid': 11,
'distance': 10.0,
}),
]),
})
# ---
# name: test_normal.8
OrderedDict({
'sql': 'select rowid, distance from v where embedding match ? and k = ? AND is_odd == TRUE AND distance BETWEEN 7 AND 10',
'rows': list([
OrderedDict({
'rowid': 9,
'distance': 8.0,
}),
OrderedDict({
'rowid': 11,
'distance': 10.0,
}),
]),
})
# ---

82
tests/test-knn-distance-constraints.py Normal file
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@ -0,0 +1,82 @@
import sqlite3
from collections import OrderedDict
def test_normal(db, snapshot):
db.execute("create virtual table v using vec0(embedding float[1], is_odd boolean, chunk_size=8)")
db.executemany(
"insert into v(rowid, is_odd, embedding) values (?1, ?1 % 2, ?2)",
[
[1, "[1]"],
[2, "[2]"],
[3, "[3]"],
[4, "[4]"],
[5, "[5]"],
[6, "[6]"],
[7, "[7]"],
[8, "[8]"],
[9, "[9]"],
[10, "[10]"],
[11, "[11]"],
[12, "[12]"],
[13, "[13]"],
[14, "[14]"],
[15, "[15]"],
[16, "[16]"],
[17, "[17]"],
],
)
assert exec(db,"SELECT * FROM v") == snapshot()
BASE_KNN = "select rowid, distance from v where embedding match ? and k = ? "
assert exec(db, BASE_KNN, ["[1]", 5]) == snapshot()
assert exec(db, BASE_KNN + "AND distance > 5", ["[1]", 5]) == snapshot()
assert exec(db, BASE_KNN + "AND distance >= 5", ["[1]", 5]) == snapshot()
assert exec(db, BASE_KNN + "AND distance < 3", ["[1]", 5]) == snapshot()
assert exec(db, BASE_KNN + "AND distance <= 3", ["[1]", 5]) == snapshot()
assert exec(db, BASE_KNN + "AND distance > 7 AND distance <= 10", ["[1]", 5]) == snapshot()
assert exec(db, BASE_KNN + "AND distance BETWEEN 7 AND 10", ["[1]", 5]) == snapshot()
assert exec(db, BASE_KNN + "AND is_odd == TRUE AND distance BETWEEN 7 AND 10", ["[1]", 5]) == snapshot()
class Row:
def __init__(self):
pass
def __repr__(self) -> str:
return repr()
def exec(db, sql, parameters=[]):
try:
rows = db.execute(sql, parameters).fetchall()
except (sqlite3.OperationalError, sqlite3.DatabaseError) as e:
return {
"error": e.__class__.__name__,
"message": str(e),
}
a = []
for row in rows:
o = OrderedDict()
for k in row.keys():
o[k] = row[k]
a.append(o)
result = OrderedDict()
result["sql"] = sql
result["rows"] = a
return result
def vec0_shadow_table_contents(db, v):
shadow_tables = [
row[0]
for row in db.execute(
"select name from sqlite_master where name like ? order by 1", [f"{v}_%"]
).fetchall()
]
o = {}
for shadow_table in shadow_tables:
if shadow_table.endswith("_info"):
continue
o[shadow_table] = exec(db, f"select * from {shadow_table}")
return o