Query

In addition to ANN searches, Zilliz Cloud also supports metadata filtering through queries. This page introduces how to use Query, Get, and QueryIterators to perform metadata filtering.

Overview

A Collection can store various types of scalar fields. You can have Zilliz Cloud filter Entities based on one or more scalar fields. Zilliz Cloud offers three types of queries: Query, Get, and QueryIterator. The table below compares these three query types.

	Get	Query	QueryIterator
Applicable scenarios	To find entities that hold the specified primary keys.	To find all or a specified number of entities that meet the custom filtering conditions	To find all entities that meet the custom filtering conditions in paginated queries.
Filtering method	By primary keys	By filtering expressions.	By filtering expressions.
Mandatory parameters	Collection name Primary keys	Collection name Filtering expressions	Collection name Filtering expressions Number of entities to return per query
Optional parameters	Partition name Output fields	Partition name Number of entities to return Output fields	Partition name Number of entities to return in total Output fields
Returns	Returns entities that hold the specified primary keys in the specified collection or partition.	Returns all or a specified number of entities that meet the custom filtering conditions in the specified collection or partition.	Returns all entities that meet the custom filtering conditions in the specified collection or partition through paginated queries.

For more on metadata filtering, refer to Filtering.

Use Get

When you need to find entities by their primary keys, you can use the Get method. The following code examples assume that there are three fields named id, vector, and color in your collection and return the entities with primary keys 1, 2, and 3.

[
        {"id": 0, "vector": [0.3580376395471989, -0.6023495712049978, 0.18414012509913835, -0.26286205330961354, 0.9029438446296592], "color": "pink_8682"},
        {"id": 1, "vector": [0.19886812562848388, 0.06023560599112088, 0.6976963061752597, 0.2614474506242501, 0.838729485096104], "color": "red_7025"},
        {"id": 2, "vector": [0.43742130801983836, -0.5597502546264526, 0.6457887650909682, 0.7894058910881185, 0.20785793220625592], "color": "orange_6781"},
        {"id": 3, "vector": [0.3172005263489739, 0.9719044792798428, -0.36981146090600725, -0.4860894583077995, 0.95791889146345], "color": "pink_9298"},
        {"id": 4, "vector": [0.4452349528804562, -0.8757026943054742, 0.8220779437047674, 0.46406290649483184, 0.30337481143159106], "color": "red_4794"},
        {"id": 5, "vector": [0.985825131989184, -0.8144651566660419, 0.6299267002202009, 0.1206906911183383, -0.1446277761879955], "color": "yellow_4222"},
        {"id": 6, "vector": [0.8371977790571115, -0.015764369584852833, -0.31062937026679327, -0.562666951622192, -0.8984947637863987], "color": "red_9392"},
        {"id": 7, "vector": [-0.33445148015177995, -0.2567135004164067, 0.8987539745369246, 0.9402995886420709, 0.5378064918413052], "color": "grey_8510"},
        {"id": 8, "vector": [0.39524717779832685, 0.4000257286739164, -0.5890507376891594, -0.8650502298996872, -0.6140360785406336], "color": "white_9381"},
        {"id": 9, "vector": [0.5718280481994695, 0.24070317428066512, -0.3737913482606834, -0.06726932177492717, -0.6980531615588608], "color": "purple_4976"},
]

You can get entities by their IDs as follows.

Python

from pymilvus import MilvusClient

client = MilvusClient(
    uri="YOUR_CLUSTER_ENDPOINT",
    token="YOUR_CLUSTER_TOKEN"
)

res = client.get(
    collection_name="query_collection",
    ids=[0, 1, 2],
    output_fields=["vector", "color"]
)

print(res)

Java

import io.milvus.v2.client.ConnectConfig;
import io.milvus.v2.client.MilvusClientV2;
import io.milvus.v2.service.vector.request.GetReq
import io.milvus.v2.service.vector.request.GetResp
import java.util.*;

MilvusClientV2 client = new MilvusClientV2(ConnectConfig.builder()
        .uri("YOUR_CLUSTER_ENDPOINT")
        .token("YOUR_CLUSTER_TOKEN")
        .build());
        
GetReq getReq = GetReq.builder()
        .collectionName("query_collection")
        .ids(Arrays.asList(0, 1, 2))
        .outputFields(Arrays.asList("vector", "color"))
        .build();

GetResp getResp = client.get(getReq);

List<QueryResp.QueryResult> results = getResp.getGetResults();
for (QueryResp.QueryResult result : results) {
    System.out.println(result.getEntity());
}

// Output
// {color=pink_8682, vector=[0.35803765, -0.6023496, 0.18414013, -0.26286206, 0.90294385], id=0}
// {color=red_7025, vector=[0.19886813, 0.060235605, 0.6976963, 0.26144746, 0.8387295], id=1}
// {color=orange_6781, vector=[0.43742132, -0.55975026, 0.6457888, 0.7894059, 0.20785794], id=2}

NodeJS

import { MilvusClient, DataType } from "@zilliz/milvus2-sdk-node";

const address = "YOUR_CLUSTER_ENDPOINT";
const token = "YOUR_CLUSTER_TOKEN";
const client = new MilvusClient({address, token});

const res = client.get({
    collection_name="query_collection",
    ids=[0,1,2],
    output_fields=["vector", "color"]
})

cURL

export CLUSTER_ENDPOINT="YOUR_CLUSTER_ENDPOINT"
export TOKEN="YOUR_CLUSTER_TOKEN"

curl --request POST \
--url "${CLUSTER_ENDPOINT}/v2/vectordb/entities/get" \
--header "Authorization: Bearer ${TOKEN}" \
--header "Content-Type: application/json" \
-d '{
    "collectionName": "quick_setup",
    "id": [0, 1, 2],
    "outputFields": ["vector", "color"]
}'

# {"code":0,"cost":0,"data":[{"color":"pink_8682","id":0,"vector":[0.35803765,-0.6023496,0.18414013,-0.26286206,0.90294385]},{"color":"red_7025","id":1,"vector":[0.19886813,0.060235605,0.6976963,0.26144746,0.8387295]},{"color":"orange_6781","id":2,"vector":[0.43742132,-0.55975026,0.6457888,0.7894059,0.20785794]}]}

Use Query

When you need to find entities by custom filtering conditions, use the Query method. The following code examples assume there are three fields named id, vector, and color and return the specified number of entities that hold a color value starting with red.

Python

from pymilvus import MilvusClient

client = MilvusClient(
    uri="YOUR_CLUSTER_ENDPOINT",
    token="YOUR_CLUSTER_TOKEN"
)

res = client.query(
    collection_name="query_collection",
    filter="color like \"red%\"",
    output_fields=["vector", "color"],
    limit=3
)

Java

import io.milvus.v2.service.vector.request.QueryReq
import io.milvus.v2.service.vector.request.QueryResp

QueryReq queryReq = QueryReq.builder()
        .collectionName("query_collection")
        .filter("color like \"red%\"")
        .outputFields(Arrays.asList("vector", "color"))
        .limit(3)
        .build();

QueryResp getResp = client.query(queryReq);

List<QueryResp.QueryResult> results = getResp.getQueryResults();
for (QueryResp.QueryResult result : results) {
    System.out.println(result.getEntity());
}

// Output
// {color=red_7025, vector=[0.19886813, 0.060235605, 0.6976963, 0.26144746, 0.8387295], id=1}
// {color=red_4794, vector=[0.44523495, -0.8757027, 0.82207793, 0.4640629, 0.3033748], id=4}
// {color=red_9392, vector=[0.8371978, -0.015764369, -0.31062937, -0.56266695, -0.8984948], id=6}

Go

import (
    "context"
    "fmt"
    "log"

    "github.com/milvus-io/milvus/client/v2"
)

func ExampleClient_Query_basic() {
    ctx, cancel := context.WithCancel(context.Background())
    defer cancel()

    milvusAddr := "YOUR_CLUSTER_ENDPOINT"
    token := "YOUR_CLUSTER_TOKEN"

    cli, err := client.New(ctx, &client.ClientConfig{
        Address: milvusAddr,
        APIKey:  token,
    })
    if err != nil {
        log.Fatal("failed to connect to milvus server: ", err.Error())
    }

    defer cli.Close(ctx)

    resultSet, err := cli.Query(ctx, client.NewQueryOption("query_collection").
        WithFilter(`color like "red%"`).
        WithOutputFields("vector", "color").
        WithLimit(3))

    fmt.Println(resultSet.GetColumn("color"))
}

NodeJS

import { MilvusClient, DataType } from "@zilliz/milvus2-sdk-node";

const address = "YOUR_CLUSTER_ENDPOINT";
const token = "YOUR_CLUSTER_TOKEN";
const client = new MilvusClient({address, token});

const res = client.query({
    collection_name="quick_setup",
    filter='color like "red%"',
    output_fields=["vector", "color"],
    limit(3)
})

cURL

export CLUSTER_ENDPOINT="YOUR_CLUSTER_ENDPOINT"
export TOKEN="YOUR_CLUSTER_TOKEN"

curl --request POST \
--url "${CLUSTER_ENDPOINT}/v2/vectordb/entities/query" \
--header "Authorization: Bearer ${TOKEN}" \
--header "Content-Type: application/json" \
-d '{
    "collectionName": "quick_setup",
    "filter": "color like \"red%\"",
    "limit": 3,
    "outputFields": ["vector", "color"]
}'
#{"code":0,"cost":0,"data":[{"color":"red_7025","id":1,"vector":[0.19886813,0.060235605,0.6976963,0.26144746,0.8387295]},{"color":"red_4794","id":4,"vector":[0.44523495,-0.8757027,0.82207793,0.4640629,0.3033748]},{"color":"red_9392","id":6,"vector":[0.8371978,-0.015764369,-0.31062937,-0.56266695,-0.8984948]}]}

Use QueryIterator

When you need to find entities by custom filtering conditions through paginated queries, create a QueryIterator and use its next() method to iterate over all entities to find those meeting the filtering conditions. The following code examples assume that there are three fields named id, vector, and color and return all entities that hold a color value starting with red.

Python

from pymilvus import connections, Collection

connections.connect(
    uri="YOUR_CLUSTER_ENDPOINT",
    token="YOUR_CLUSTER_TOKEN"
)

collection = Collection("query_collection")

iterator = collection.query_iterator(
    batch_size=10,
    expr="color like \"red%\"",
    output_fields=["color"]
)

results = []

while True:
    result = iterator.next()
    if not result:
        iterator.close()
        break

    print(result)
    results += result

Java

import io.milvus.orm.iterator.QueryIterator;
import io.milvus.response.QueryResultsWrapper;
import io.milvus.v2.common.ConsistencyLevel;
import io.milvus.v2.service.vector.request.QueryIteratorReq;

QueryIteratorReq req = QueryIteratorReq.builder()
        .collectionName("query_collection")
        .expr("color like \"red%\"")
        .batchSize(50L)
        .outputFields(Collections.singletonList("color"))
        .consistencyLevel(ConsistencyLevel.BOUNDED)
        .build();
QueryIterator queryIterator = client.queryIterator(req);

while (true) {
    List<QueryResultsWrapper.RowRecord> res = queryIterator.next();
    if (res.isEmpty()) {
        queryIterator.close();
        break;
    }

    for (QueryResultsWrapper.RowRecord record : res) {
        System.out.println(record);
    }
}

// Output
// [color:red_7025, id:1]
// [color:red_4794, id:4]
// [color:red_9392, id:6]

NodeJS

import { MilvusClient, DataType } from "@zilliz/milvus2-sdk-node";

const iterator = await milvusClient.queryIterator({
  collection_name: 'query_collection',
  batchSize: 10,
  expr: 'color like "red%"',
  output_fields: ['color'],
});

const results = [];
for await (const value of iterator) {
  results.push(...value);
  page += 1;
}

cURL

# 暂无此方法

Queries in Partitions

You can also perform queries within one or multiple partitions by including the partition names in the Get, Query, or QueryIterator request. The following code examples assume that there is a partition named PartitionA in the collection.

Python

from pymilvus import MilvusClient
client = MilvusClient(
    uri="YOUR_CLUSTER_ENDPOINT",
    token="YOUR_CLUSTER_TOKEN"
)

res = client.get(
    collection_name="query_collection",
    partitionNames=["partitionA"],
    ids=[0, 1, 2],
    output_fields=["vector", "color"]
)

from pymilvus import MilvusClient

client = MilvusClient(
    uri="YOUR_CLUSTER_ENDPOINT",
    token="YOUR_CLUSTER_TOKEN"
)

res = client.query(
    collection_name="query_collection",
    partitionNames=["partitionA"],
    filter="color like \"red%\"",
    output_fields=["vector", "color"],
    limit=3
)

# 使用 QueryIterator
from pymilvus import connections, Collection

connections.connect(
    uri="YOUR_CLUSTER_ENDPOINT",
    token="YOUR_CLUSTER_TOKEN"
)

collection = Collection("query_collection")

iterator = collection.query_iterator(
    partition_names=["partitionA"],
    batch_size=10,
    expr="color like \"red%\"",
    output_fields=["color"]
)

results = []

while True:
    result = iterator.next()
    if not result:
        iterator.close()
        break

    print(result)
    results += result

Java

GetReq getReq = GetReq.builder()
        .collectionName("query_collection")
        .partitionName("partitionA")
        .ids(Arrays.asList(10, 11, 12))
        .outputFields(Collections.singletonList("color"))
        .build();

GetResp getResp = client.get(getReq);

QueryReq queryReq = QueryReq.builder()
        .collectionName("query_collection")
        .partitionNames(Collections.singletonList("partitionA"))
        .filter("color like \"red%\"")
        .outputFields(Collections.singletonList("color"))
        .limit(3)
        .build();

QueryResp getResp = client.query(queryReq);

QueryIteratorReq req = QueryIteratorReq.builder()
        .collectionName("query_collection")
        .partitionNames(Collections.singletonList("partitionA"))
        .expr("color like \"red%\"")
        .batchSize(50L)
        .outputFields(Collections.singletonList("color"))
        .consistencyLevel(ConsistencyLevel.BOUNDED)
        .build();
QueryIterator queryIterator = client.queryIterator(req);

NodeJS

import { MilvusClient, DataType } from "@zilliz/milvus2-sdk-node";

const address = "YOUR_CLUSTER_ENDPOINT";
const token = "YOUR_CLUSTER_TOKEN";
const client = new MilvusClient({address, token});

// 使用 Get 方法
var res = client.query({
    collection_name="query_collection",
    partition_names=["partitionA"],
    filter='color like "red%"',
    output_fields=["vector", "color"],
    limit(3)
})

// 使用 Query 方法
res = client.query({
    collection_name="query_collection",
    partition_names=["partitionA"],
    filter="color like \"red%\"",
    output_fields=["vector", "color"],
    limit(3)
})

// 暂不支持使用 QueryIterator
const iterator = await milvusClient.queryIterator({
  collection_name: 'query_collection',
  partition_names: ['partitionA'],
  batchSize: 10,
  expr: 'color like "red%"',
  output_fields: ['vector', 'color'],
});

const results = [];
for await (const value of iterator) {
  results.push(...value);
  page += 1;
}

cURL

export CLUSTER_ENDPOINT="YOUR_CLUSTER_ENDPOINT"
export TOKEN="YOUR_CLUSTER_TOKEN"

# 使用 Get 方法
curl --request POST \
--url "${CLUSTER_ENDPOINT}/v2/vectordb/entities/get" \
--header "Authorization: Bearer ${TOKEN}" \
--header "Content-Type: application/json" \
-d '{
    "collectionName": "query_collection",
    "partitionNames": ["partitionA"],
    "id": [0, 1, 2],
    "outputFields": ["vector", "color"]
}'

# 使用 Query 方法
curl --request POST \
--url "${CLUSTER_ENDPOINT}/v2/vectordb/entities/get" \
--header "Authorization: Bearer ${TOKEN}" \
--header "Content-Type: application/json" \
-d '{
    "collectionName": "query_collection",
    "partitionNames": ["partitionA"],
    "filter": "color like \"red%\"",
    "limit": 3,
    "outputFields": ["vector", "color"],
    "id": [0, 1, 2]
}'