什么是Milvus?
- Milvus,一个开源的高功用向量数据库,它在各种使用场景中展现出强大的功用和灵活性。
在许多现代使用中,处理和剖析大规模向量数据变得越来越重要。例如,在图画和视频查找、推荐体系、自然语言处理和生物信息学等范畴,向量数据被广泛使用。
项目布景
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在公司推荐体系中,咱们需要根据用户的前史行为和爱好,为其推荐相关的内容。所以将用户和内容表明为向量,并使用 Milvus 进行类似度匹配。通过将用户向量和内容向量存储在 Milvus 中,并使用其高效的类似度查询功用,咱们可以快速找到与用户爱好最匹配的内容,并进行个性化推荐。
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向量的生成由spark任务生成数据并写入,本文只写SpringBoot集成Milvus实现数据查询部分,面向C端,功用已测
Maven依靠引入
- 开始使用的是1.x版别,后来因为2.x新增了过滤挑选功用,晋级了版别为2.2.3,1版别和2版别查询还是有一些区别,建议选用2版别
<dependency>
<groupId>io.milvus</groupId>
<artifactId>milvus-sdk-java</artifactId>
<version>2.2.3</version>
</dependency>
自动装备
@Configuration
public class MilvusConfiguration {
/**
* milvus ip addr
*/
@Value("${milvus.config.ipAddr}")
private String ipAddr;
/**
* milvus port
*/
@Value("${milvus.config.port}")
private Integer port;
@Bean
@Scope("singleton")
public MilvusServiceClient getMilvusClient() {
return getMilvusFactory().getMilvusClient();
}
@Bean(initMethod = "init", destroyMethod = "close")
public MilvusRestClientFactory getMilvusFactory() {
return MilvusRestClientFactory.build(ipAddr, port);
}
}
milvus Rest client 封装
public class MilvusRestClientFactory {
private static String IP_ADDR;
private static Integer PORT ;
private MilvusServiceClient milvusServiceClient;
private ConnectParam.Builder connectParamBuilder;
private static MilvusRestClientFactory milvusRestClientFactory = new MilvusRestClientFactory();
private MilvusRestClientFactory(){
}
public static MilvusRestClientFactory build(String ipAddr, Integer port) {
IP_ADDR = ipAddr;
PORT = port;
return milvusRestClientFactory;
}
private ConnectParam.Builder connectParamBuilder(String host, int port) {
return ConnectParam.newBuilder().withHost(host).withPort(port);
}
public void init() {
connectParamBuilder = connectParamBuilder(IP_ADDR,PORT);
ConnectParam connectParam = connectParamBuilder.build();
milvusServiceClient =new MilvusServiceClient(connectParam);
}
public MilvusServiceClient getMilvusClient() {
return milvusServiceClient;
}
public void close() {
if (milvusServiceClient != null) {
try {
milvusServiceClient.close();
} catch (Exception e) {
e.printStackTrace();
}
}
}
}
查询
写入数据不同,获取成果不同,我这里最终获取的是Long类型的数据调集,仅供参考
- 同步查找milvus
/**
* 同步查找milvus
* @param collectionName 表名
* @param vectors 查询向量
* @param topK 最类似的向量个数
* @return
*/
public List<Long> search(String collectionName, List<List<Float>> vectors, Integer topK) {
Assert.notNull(collectionName, "collectionName is null");
Assert.notNull(vectors, "vectors is null");
Assert.notEmpty(vectors, "vectors is empty");
Assert.notNull(topK, "topK is null");
int nprobeVectorSize = vectors.get(0).size();
String paramsInJson = "{"nprobe": " + nprobeVectorSize + "}";
SearchParam searchParam =
SearchParam.newBuilder().withCollectionName(collectionName)
.withParams(paramsInJson)
.withMetricType(MetricType.IP)
.withVectors(vectors)
.withVectorFieldName("embedding")
.withTopK(topK)
.build();
R<SearchResults> searchResultsR = milvusServiceClient.search(searchParam);
SearchResults searchResultsRData = searchResultsR.getData();
List<Long> topksList = searchResultsRData.getResults().getIds().getIntId().getDataList();
return topksList;
}
- 同步查找milvus,添加过滤条件查找
/**
* 同步查找milvus,添加过滤条件查找
*
* @param collectionName 表名
* @param vectors 查询向量
* @param topK 最类似的向量个数
* @param exp 过滤条件:status=1
* @return
*/
public List<Long> search(String collectionName, List<List<Float>> vectors, Integer topK, String exp) {
Assert.notNull(collectionName, "collectionName is null");
Assert.notNull(vectors, "vectors is null");
Assert.notEmpty(vectors, "vectors is empty");
Assert.notNull(topK, "topK is null");
Assert.notNull(exp, "exp is null");
int nprobeVectorSize = vectors.get(0).size();
String paramsInJson = "{"nprobe": " + nprobeVectorSize + "}";
SearchParam searchParam =
SearchParam.newBuilder().withCollectionName(collectionName)
.withParams(paramsInJson)
.withMetricType(MetricType.IP)
.withVectors(vectors)
.withExpr(exp)
.withVectorFieldName("embedding")
.withTopK(topK)
.build();
R<SearchResults> searchResultsR = milvusServiceClient.search(searchParam);
SearchResults searchResultsRData = searchResultsR.getData();
List<Long> topksList = searchResultsRData.getResults().getIds().getIntId().getDataList();
return topksList;
}
- 异步查找milvus:针对实时成果要求不高的场景
/**
* 异步查找milvus
*
* @param collectionName 表名
* @param vectors 查询向量
* @param partitionList 最类似的向量个数
* @param topK
* @return
*/
public List<Long> searchAsync(String collectionName, List<List<Float>> vectors,
List<String> partitionList, Integer topK) throws ExecutionException, InterruptedException {
Assert.notNull(collectionName, "collectionName is null");
Assert.notNull(vectors, "vectors is null");
Assert.notEmpty(vectors, "vectors is empty");
Assert.notNull(partitionList, "partitionList is null");
Assert.notEmpty(partitionList, "partitionList is empty");
Assert.notNull(topK, "topK is null");
int nprobeVectorSize = vectors.get(0).size();
String paramsInJson = "{"nprobe": " + nprobeVectorSize + "}";
SearchParam searchParam =
SearchParam.newBuilder().withCollectionName(collectionName)
.withParams(paramsInJson)
.withVectors(vectors)
.withTopK(topK)
.withPartitionNames(partitionList)
.build();
ListenableFuture<R<SearchResults>> listenableFuture = milvusServiceClient.searchAsync(searchParam);
List<Long> resultIdsList = listenableFuture.get().getData().getResults().getTopksList();
return resultIdsList;
}
- 获取分区调集
/**
* 获取分区调集
* @param collectionName 表名
* @return
*/
public List<String> getPartitionsList(String collectionName) {
Assert.notNull(collectionName, "collectionName is null");
ShowPartitionsParam searchParam = ShowPartitionsParam.newBuilder().withCollectionName(collectionName).build();
List<ByteString> byteStrings = milvusServiceClient.showPartitions(searchParam).getData().getPartitionNamesList().asByteStringList();
List<String> partitionList = Lists.newLinkedList();
byteStrings.forEach(s -> {
partitionList.add(s.toStringUtf8());
});
return partitionList;
}
yml装备数据
milvus:
config:
ipAddr: xxx.xxx.xxx.xxx
port: 19531