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主鍵搜尋Compatible with Milvus 2.6.9+

進行相似度搜尋時，系統總是會要求您提供一個或多個查詢向量，即使這些查詢向量已經存在於目標集合中也是如此。為了避免在搜尋前先檢索向量，您可以改用主鍵來替代。

概述

在電子商務平台上，使用者可輸入關鍵字來檢索相符的商品。當使用者瀏覽商品詳情頁時，平台也會在頁面底部顯示一份相似商品清單，供使用者進行比較。

這些推薦商品會根據其與關鍵字或當前商品的相似度進行排序。為實現此功能，平台開發人員需要在實際進行相似度搜尋之前，先從 Milvus 擷取關鍵字或當前商品的向量表示，這會增加平台與 Milvus 之間的往返次數，並導致大量高維度浮點數值透過網路傳輸。

為簡化您的應用程式與 Milvus 之間的互動邏輯、減少往返次數，並避免透過網路傳輸大量高維度浮點數值，建議考慮使用主鍵搜尋。

在主鍵搜尋中，您無需提供任何查詢向量。取而代之的是，系統會要求您提供包含查詢向量的實體之主鍵（ids ）。

限制與規範

  • 使用主鍵進行的搜尋適用於所有向量資料類型，惟源自 VarChar 欄位的稀疏向量欄位除外（例如 BM25 函式中的情況）。

  • 您可以在過濾、範圍和分組搜尋中使用主鍵代替查詢向量，並可選擇啟用分頁功能。然而，此功能不適用於混合搜尋和搜尋迭代器。

  • 對於涉及嵌入清單的相似度搜尋，您仍需檢索查詢向量、將其排列成嵌入清單，並執行搜尋。

  • 在 RESTful API 中，您無法使用主鍵代替查詢向量。

  • 對於任何不存在的主鍵或格式不正確的主鍵，Milvus 會提示錯誤。

  • 主鍵與查詢向量互斥。若同時提供兩者，亦會導致錯誤。

範例

以下範例假設所有提供的 Int64 ID 均存在於目標集合中。

主鍵不會用於篩選；它們僅用於向量檢索。

要進行基本的主鍵搜尋，只需將查詢向量替換為主鍵即可。

Python Java NodeJS Go cURL C++ 
from pymilvus import MilvusClient

client = MilvusClient(
    uri="http://localhost:19530",
    token="root:Milvus"
)

res = client.search(
    collection_name="quick_setup",
    anns_field="vector",
    ids=[551, 296, 43], # a list of primary keys
    limit=3,
    search_params={"metric_type": "IP"}
)

for hits in res:
    for hit in hits:
        print(hit)

import io.milvus.v2.client.ConnectConfig;
import io.milvus.v2.client.MilvusClientV2;
import io.milvus.v2.service.vector.request.SearchReq;
import io.milvus.v2.service.vector.response.SearchResp;
import io.milvus.v2.common.IndexParam;

MilvusClientV2 client = new MilvusClientV2(ConnectConfig.builder()
        .uri("http://localhost:19530")
        .token("root:Milvus")
        .build());

List<Object> ids = Arrays.asList(551L, 296L, 43L);
SearchResp searchResp = client.search(SearchReq.builder()
        .collectionName("quick_setup")
        .annsField("vector")
        .ids(ids)
        .limit(3)
        .metricType(IndexParam.MetricType.IP)
        .build());
List<List<SearchResp.SearchResult>> searchResults = searchResp.getSearchResults();
for (List<SearchResp.SearchResult> results : searchResults) {
    System.out.println("TopK results:");
    for (SearchResp.SearchResult result : results) {
        System.out.println(result);
    }
}

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

const client = new MilvusClient({
    address: "http://localhost:19530",
    token: "root:Milvus",
});

const res = await client.search({
    collection_name: "quick_setup",
    anns_field: "vector",
    ids: [551, 296, 43], // a list of primary keys
    limit: 3,
    metric_type: "IP",
});

console.log(res.results);

import (
    "context"
    "fmt"

    "github.com/milvus-io/milvus/client/v3/column"
    "github.com/milvus-io/milvus/client/v3/milvusclient"
)

ctx := context.Background()

client, err := milvusclient.New(ctx, &milvusclient.ClientConfig{
    Address: "localhost:19530",
    APIKey:  "root:Milvus",
})
if err != nil {
    fmt.Println(err.Error())
    // handle error
}
defer client.Close(ctx)

ids := column.NewColumnInt64("id", []int64{551, 296, 43}) // a list of primary keys
resultSets, err := client.Search(ctx, milvusclient.NewSearchByIDsOption(
    "quick_setup", // collectionName
    3,             // limit
    ids,
).WithANNSField("vector").
    WithSearchParam("metric_type", "IP"))
if err != nil {
    fmt.Println(err.Error())
    // handle error
}

for _, resultSet := range resultSets {
    fmt.Println("IDs: ", resultSet.IDs)
    fmt.Println("Scores: ", resultSet.Scores)
}

# restful
curl -X POST "http://localhost:19530/v2/vectordb/entities/search" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer root:Milvus" \
  -H "Request-Timeout: 10" \
  -d '{
    "collectionName": "quick_setup",
    "annsField": "vector",
    "ids": [551, 296, 43],
    "limit": 3
  }' 

auto searchRequest = milvus::SearchRequest()
                         .WithCollectionName("quick_setup")
                         .WithAnnsField("vector")
                         .WithIDs({551, 296, 43})
                         .WithLimit(3)
                         .WithMetricType(milvus::MetricType::IP);

milvus::SearchResponse searchResponse;
auto status = client->Search(searchRequest, searchResponse);
if (!status.IsOk()) {
    std::cerr << "Search failed: " << status.Message() << std::endl;
    return;
}

for (const auto& result : searchResponse.Results().Results()) {
    const auto ids = result.Ids().IntIDArray();
    for (size_t i = 0; i < result.Scores().size(); ++i) {
        std::cout << "id=" << ids[i] << ", score=" << result.Scores()[i] << std::endl;
    }
}

範例 2：使用主鍵進行篩選搜尋

以下範例假設「color」和「likes」是目標集合中兩個由模式定義的欄位。

Python Java NodeJS Go cURL C++ 
res = client.search(
    collection_name="my_collection",
    ids=[551, 296, 43], #
    filter='color like "red%" and likes > 50',
    output_fields=["color", "likes"],
    limit=3,
)

List<Object> ids = Arrays.asList(551L, 296L, 43L);
SearchResp searchResp = client.search(SearchReq.builder()
        .collectionName("my_collection")
        .ids(ids)
        .filter("color like \"red%\" and likes > 50")
        .limit(3)
        .outputFields(Arrays.asList("color", "likes"))
        .build());
List<List<SearchResp.SearchResult>> searchResults = searchResp.getSearchResults();
for (List<SearchResp.SearchResult> results : searchResults) {
    System.out.println("TopK results:");
    for (SearchResp.SearchResult result : results) {
        System.out.println(result);
    }
}

const res = await client.search({
    collection_name: "my_collection",
    ids: [551, 296, 43],
    filter: 'color like "red%" and likes > 50',
    output_fields: ["id", "color", "likes"],
    limit: 3,
});

console.log(res.results);

ids := column.NewColumnInt64("id", []int64{551, 296, 43})
resultSets, err := client.Search(ctx, milvusclient.NewSearchByIDsOption(
    "my_collection", // collectionName
    3,               // limit
    ids,
).WithFilter(`color like "red%" and likes > 50`).
    WithOutputFields("color", "likes"))
if err != nil {
    fmt.Println(err.Error())
    // handle error
}

for _, resultSet := range resultSets {
    fmt.Println("IDs: ", resultSet.IDs)
    fmt.Println("Scores: ", resultSet.Scores)
    fmt.Println("color: ", resultSet.GetColumn("color"))
    fmt.Println("likes: ", resultSet.GetColumn("likes"))
}

# restful
curl -X POST "http://localhost:19530/v2/vectordb/entities/search" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer root:Milvus" \
  -H "Request-Timeout: 10" \
  -d '{
    "collectionName": "my_collection",
    "annsField": "vector",
    "ids": [551, 296, 43],
    "filter": "color like \\"red%\\" and likes > 50",
    "outputFields": ["color", "likes"],
    "limit": 3
  }' 

auto searchRequest = milvus::SearchRequest()
                         .WithCollectionName("my_collection")
                         .WithIDs({551, 296, 43})
                         .WithFilter(R"(color like "red%" and likes > 50)")
                         .WithOutputFields({"color", "likes"})
                         .WithLimit(3);

milvus::SearchResponse searchResponse;
auto status = client->Search(searchRequest, searchResponse);
if (!status.IsOk()) {
    std::cerr << "Search failed: " << status.Message() << std::endl;
    return;
}

for (const auto& result : searchResponse.Results().Results()) {
    const auto ids = result.Ids().IntIDArray();
    const auto colors = result.OutputField<milvus::VarCharFieldData>("color");
    const auto likes = result.OutputField<milvus::Int64FieldData>("likes");
    for (size_t i = 0; i < result.Scores().size(); ++i) {
        std::cout << "id=" << ids[i]
                  << ", score=" << result.Scores()[i]
                  << ", color=" << colors->Data()[i]
                  << ", likes=" << likes->Data()[i] << std::endl;
    }
}

範例 3：使用主鍵進行範圍搜尋

Python Java NodeJS Go cURL C++ 
res = client.search(
    collection_name="my_collection",
    ids=[551, 296, 43],
    limit=3,
    search_params={
        "params": {
            "radius": 0.4,
            "range_filter": 0.6
        }
    }
)

Map<String, Object> params = new HashMap<>();
params.put("radius", "0.4");
params.put("range_filter", "0.6");

List<Object> ids = Arrays.asList(551L, 296L, 43L);
SearchResp searchResp = client.search(SearchReq.builder()
        .collectionName("my_collection")
        .ids(ids)
        .limit(3)
        .searchParams(params)
        .build());
List<List<SearchResp.SearchResult>> searchResults = searchResp.getSearchResults();
for (List<SearchResp.SearchResult> results : searchResults) {
    System.out.println("TopK results:");
    for (SearchResp.SearchResult result : results) {
        System.out.println(result);
    }
}

const res = await client.search({
    collection_name: "my_collection",
    ids: [551, 296, 43],
    limit: 3,
    params: {
        radius: 0.4,
        range_filter: 0.6,
    },
});

console.log(res.results);

annParam := index.NewCustomAnnParam()
annParam.WithRadius(0.4)
annParam.WithRangeFilter(0.6)

ids := column.NewColumnInt64("id", []int64{551, 296, 43})
resultSets, err := client.Search(ctx, milvusclient.NewSearchByIDsOption(
    "my_collection", // collectionName
    3,               // limit
    ids,
).WithANNSField("vector").
    WithAnnParam(annParam))
if err != nil {
    fmt.Println(err.Error())
    // handle error
}

for _, resultSet := range resultSets {
    fmt.Println("IDs: ", resultSet.IDs)
    fmt.Println("Scores: ", resultSet.Scores)
}

# restful
curl -X POST "http://localhost:19530/v2/vectordb/entities/search" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer root:Milvus" \
  -H "Request-Timeout: 10" \
  -d '{
    "collectionName": "my_collection",
    "annsField": "vector",
    "ids": [551, 296, 43],
    "limit": 3,
    "searchParams": {
      "params": {
        "radius": 0.4,
        "range_filter": 0.6
      }
    }
  }' 

auto searchRequest = milvus::SearchRequest()
                         .WithCollectionName("my_collection")
                         .WithAnnsField("vector")
                         .WithIDs({551, 296, 43})
                         .WithRadius(0.4)
                         .WithRangeFilter(0.6)
                         .WithLimit(3);

milvus::SearchResponse searchResponse;
auto status = client->Search(searchRequest, searchResponse);
if (!status.IsOk()) {
    std::cerr << "Search failed: " << status.Message() << std::endl;
    return;
}

for (const auto& result : searchResponse.Results().Results()) {
    const auto ids = result.Ids().IntIDArray();
    for (size_t i = 0; i < result.Scores().size(); ++i) {
        std::cout << "id=" << ids[i] << ", score=" << result.Scores()[i] << std::endl;
    }
}

範例 4：使用主鍵進行分組搜尋

以下範例假設「docId 」是目標集合中由模式定義的欄位。

Python Java NodeJS Go cURL C++ 
res = client.search(
    collection_name="my_collection",
    ids=[551, 296, 43],
    limit=3,
    group_by_field="docId",
    output_fields=["docId"]
)

List<Object> ids = Arrays.asList(551L, 296L, 43L);
SearchResp searchResp = client.search(SearchReq.builder()
        .collectionName("my_collection")
        .ids(ids)
        .limit(3)
        .groupByFieldName("docId")
        .outputFields(Collections.singletonList("docId"))
        .build());
List<List<SearchResp.SearchResult>> searchResults = searchResp.getSearchResults();
for (List<SearchResp.SearchResult> results : searchResults) {
    System.out.println("TopK results:");
    for (SearchResp.SearchResult result : results) {
        System.out.println(result);
    }
}

const res = await client.search({
    collection_name: "my_collection",
    ids: [551, 296, 43],
    limit: 3,
    group_by_field: "docId",
    output_fields: ["id", "docId"],
});

console.log(res.results);

ids := column.NewColumnInt64("id", []int64{551, 296, 43})
resultSets, err := client.Search(ctx, milvusclient.NewSearchByIDsOption(
    "my_collection", // collectionName
    3,               // limit
    ids,
).WithGroupByField("docId").
    WithOutputFields("docId"))
if err != nil {
    fmt.Println(err.Error())
    // handle error
}

for _, resultSet := range resultSets {
    fmt.Println("IDs: ", resultSet.IDs)
    fmt.Println("Scores: ", resultSet.Scores)
    fmt.Println("docId: ", resultSet.GetColumn("docId"))
}

# restful
curl -X POST "http://localhost:19530/v2/vectordb/entities/search" \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer root:Milvus" \
  -H "Request-Timeout: 10" \
  -d '{
    "collectionName": "my_collection",
    "annsField": "vector",
    "ids": [551, 296, 43],
    "limit": 3,
    "groupingField": "docId",
    "outputFields": ["docId"]
  }' 

auto searchRequest = milvus::SearchRequest()
                         .WithCollectionName("my_collection")
                         .WithAnnsField("vector")
                         .WithIDs({551, 296, 43})
                         .WithGroupByField("docId")
                         .WithOutputFields({"docId"})
                         .WithLimit(3);

milvus::SearchResponse searchResponse;
auto status = client->Search(searchRequest, searchResponse);
if (!status.IsOk()) {
    std::cerr << "Search failed: " << status.Message() << std::endl;
    return;
}

for (const auto& result : searchResponse.Results().Results()) {
    const auto ids = result.Ids().IntIDArray();
    const auto docIds = result.OutputField<milvus::Int64FieldData>("docId");
    for (size_t i = 0; i < result.Scores().size(); ++i) {
        std::cout << "id=" << ids[i]
                  << ", score=" << result.Scores()[i]
                  << ", docId=" << docIds->Data()[i] << std::endl;
    }
}

翻譯者DeepL

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