Spring AI 中的 Apache Cassandra 向量数据库集成了 Apache Cassandra 的向量功能,提供向量存储和搜索能力。
Apache Cassandra 向量数据库支持:
基本设置
< dependency >
< groupId > org.springframework.ai </ groupId >
< artifactId > spring-ai-cassandra-vectordb </ artifactId >
< version > ${spring-ai.version} </ version >
</ dependency >
# Apache Cassandra 向量数据库配置
spring.ai.cassandra.vectordb.enabled =true
spring.ai.cassandra.vectordb.contact-points =localhost
spring.ai.cassandra.vectordb.port =9042
spring.ai.cassandra.vectordb.keyspace =vectordb
spring.ai.cassandra.vectordb.table =vectors
@ Service
public class CassandraVectorService {
private final CassandraVectorClient vectorClient ;
public CassandraVectorService ( CassandraVectorClient vectorClient ) {
this . vectorClient = vectorClient;
}
public void storeVector ( String id , float [] vector ) {
vectorClient . store (id, vector);
}
public List < SearchResult > searchSimilar ( float [] queryVector , int k ) {
return vectorClient . search (queryVector, k);
}
}
向量操作
1. 向量存储
@ Configuration
public class CassandraVectorStorageConfig {
@ Bean
public VectorStorage cassandraVectorStorage ( CassandraVectorProperties properties ) {
return new CassandraVectorStorage (properties);
}
}
2. 相似性搜索
@ Configuration
public class CassandraSimilaritySearchConfig {
@ Bean
public SimilaritySearch cassandraSimilaritySearch ( CassandraVectorProperties properties ) {
return new CassandraSimilaritySearch (properties);
}
}
3. 批量操作
@ Service
public class BatchVectorService {
private final CassandraVectorClient vectorClient ;
public void batchStore ( List < VectorDocument > documents ) {
vectorClient . batchStore (documents);
}
public List < List < SearchResult >> batchSearch ( List < float []> queryVectors , int k ) {
return vectorClient . batchSearch (queryVectors, k);
}
}
高级特性
自定义复制策略
@ Configuration
public class ReplicationStrategyConfig {
@ Bean
public ReplicationStrategy replicationStrategy () {
return SimpleStrategy . builder ()
. replicationFactor ( 3 )
. build ();
}
}
一致性级别配置
@ Configuration
public class ConsistencyLevelConfig {
@ Bean
public ConsistencyLevel consistencyLevel () {
return ConsistencyLevel . LOCAL_QUORUM ;
}
}
management.endpoints.web.exposure.include =cassandra-vectordb
management.endpoint.cassandra-vectordb.enabled =true
最佳实践
使用 Apache Cassandra 向量数据库时,请考虑以下最佳实践:
数据建模 :设计高效的数据模型
复制 :配置适当的复制
一致性 :选择合适的一致性级别
压缩 :优化压缩策略
监控 :设置全面的监控
故障排除
常见问题及解决方案:
连接问题
性能问题
存储问题
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