Distance matrix offsets | Qdrant

Retrieves sparse matrix of pairwise distances between points sampled from the collection. Output is a form of row and column offsets and list of distances.

Path parameters

collection_namestringRequired

Name of the collection to search in

Query parameters

consistencyinteger or enumOptional

Define read consistency guarantees for the operation

timeoutintegerOptional>=1

If set, overrides global timeout for this request. Unit is seconds.

Request

This endpoint expects an object.

shard_keystring or uint64 or list of strings or uint64s or anyOptional

Specify in which shards to look for the points, if not specified - look in all shards

filterobject or anyOptional

Look only for points which satisfies this conditions

sampleintegerOptional>=2

How many points to select and search within. Default is 10.

limitintegerOptional>=1

How many neighbours per sample to find. Default is 3.

usingstringOptional

Define which vector name to use for querying. If missing, the default vector is used.

Response

successful operation

timedoubleOptional

Time spent to process this request

statusstringOptional

resultobjectOptional

1	from qdrant_client import QdrantClient, models
2
3	client = QdrantClient(url="http://localhost:6333")
4
5	client.search_matrix_offsets(
6	collection_name="{collection_name}",
7	sample=100,
8	limit=5,
9	query_filter=models.Filter(
10	must=[
11	models.FieldCondition(
12	key="color", match=models.MatchValue(value="red")
13	),
14	]
15	),
16	)

1	{
2	"time": 0.002,
3	"status": "ok",
4	"result": {
5	"offsets_row": [
6	1000000
7	],
8	"offsets_col": [
9	1000000
10	],
11	"scores": [
12	1.1
13	],
14	"ids": [
15	42
16	]
17	}
18	}

Path parameters

Headers

Query parameters

Request

Response