searchAsync()

Performs a vector search asynchronously and returns a future.

public CompletableFuture<SearchResp> searchAsync(SearchReq request)

This method uses the same request parameters as search() but returns a CompletableFuture<SearchResp> immediately. Use the returned future to consume the result or handle the exceptional completion when the operation fails.

Request Syntax

CompletableFuture<SearchResp> future = client.searchAsync(SearchReq.builder()
    .collectionName(String collectionName)
    .data(List<BaseVector> data)
    .annsField(String annsField)
    .limit(long limit)
    .build());

For the full list of SearchReq builder methods, refer to search().

RETURN TYPE:

CompletableFuture

RETURNS:

A future completed with a SearchResp object that contains search results, recalls, cost, scanned byte counts, and cache hit ratio, or completed exceptionally when the operation fails. The SearchResp object exposes the following getters:

  • getSearchResults() (List>) -

    The search results, one list per query vector. Each SearchResult has the following getters:

    • getEntity() (Map) -

      The retrieved entity data.

    • getScore() (Float) -

      The similarity score of the result.

    • getId() (Object) -

      The primary key value of the result.

    • getPrimaryKey() (String) -

      The primary key value rendered as a string.

    • getHighlightResults() (Map) -

      Highlighting results keyed by field name.

    • getHighlightResult(String fieldName) (HighlightResult) -

      The highlighting result for one requested field, or null when no result exists.

    • getElementOffset() (Long) -

      The element offset for array-of-struct subfield search. null for ordinary searches.

  • getSessionTs() (long) -

    The session timestamp used for the search.

    Each HighlightResult exposes the following getters:

    • getFieldName() (String) -

      The field name used for highlighting.

    • getFragments() (List) -

      The highlighted text fragments.

    • getScores() (List) -

      The relevance scores for the fragments.

  • getRecalls() (List) -

    The recall values of the search, one per query vector.

  • getCost() (Long) -

    The time cost of the search operation, in milliseconds.

  • getScannedRemoteBytes() (Long) -

    The number of bytes scanned from remote storage.

  • getScannedTotalBytes() (Long) -

    The total number of bytes scanned during the search.

  • getCacheHitRatio() (Float) -

    The cache hit ratio of the search.

EXCEPTIONS:

  • MilvusClientException

    This exception will be raised when request validation, transport, or server execution fails.

Example

import io.milvus.v2.client.ConnectConfig;
import io.milvus.v2.client.MilvusClientV2;
import io.milvus.v2.common.DataType;
import io.milvus.v2.common.IndexParam;
import io.milvus.v2.service.collection.request.AddFieldReq;
import io.milvus.v2.service.collection.request.CreateCollectionReq;
import io.milvus.v2.service.collection.request.LoadCollectionReq;
import io.milvus.v2.service.vector.request.InsertReq;
import io.milvus.v2.service.vector.request.SearchReq;
import io.milvus.v2.service.vector.request.data.FloatVec;
import io.milvus.v2.service.vector.response.SearchResp;
import com.google.gson.Gson;
import com.google.gson.JsonObject;
import java.util.Collections;
import java.util.concurrent.CompletableFuture;

ConnectConfig connectConfig = ConnectConfig.builder()
        .uri("http://localhost:19530")
        .token("root:Milvus")
        .build();

MilvusClientV2 client = new MilvusClientV2(connectConfig);

// Create a collection with an "id" field and a "vector" field with dimension 3
CreateCollectionReq.CollectionSchema collectionSchema = MilvusClientV2.CreateSchema();
collectionSchema.addField(AddFieldReq.builder().fieldName("id").dataType(DataType.Int64).isPrimaryKey(Boolean.TRUE).autoID(Boolean.FALSE).build());
collectionSchema.addField(AddFieldReq.builder().fieldName("vector").dataType(DataType.FloatVector).dimension(3).build());
IndexParam indexParam = IndexParam.builder()
        .fieldName("vector")
        .metricType(IndexParam.MetricType.COSINE)
        .build();
client.createCollection(CreateCollectionReq.builder()
        .collectionName("my_collection")
        .collectionSchema(collectionSchema)
        .indexParams(Collections.singletonList(indexParam))
        .build());

// Insert a row
JsonObject row = new JsonObject();
row.addProperty("id", 0L);
row.add("vector", new Gson().toJsonTree(new float[]{0.1f, 0.2f, 0.3f}));
client.insert(InsertReq.builder()
        .collectionName("my_collection")
        .data(Collections.singletonList(row))
        .build());

// Load the collection
client.loadCollection(LoadCollectionReq.builder().collectionName("my_collection").build());

CompletableFuture<SearchResp> future = client.searchAsync(SearchReq.builder()
        .collectionName("my_collection")
        .data(Collections.singletonList(new FloatVec(new float[]{0.1f, 0.2f, 0.3f})))
        .annsField("vector")
        .limit(10)
        .build());
SearchResp response = future.get();

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