2025云数据仓库架构下技术实践与性能优化

云数据仓库ByteHouse架构下的RAG技术实践与性能优化RAG 全文检索&混合检索GraphRAG实践Conclusion&RAG相关技术简NaiveNaiveHybridHybridRRF:(ReciprocalRankmentionedacrossvarious Agentic AdaptiveZhao,Siyun,etal."RetrievalAugmentedGeneration(RAG)andBeyond:AComprehensiveSurveyonHowtoMakeyourLLMsuseExternalDataMoreWisely."arXivpreprintarXiv:2409.14924(2024).

Jeong,Soyeong,etal."Adaptive-rag:Learningtoadaptretrieval-augmentedlargelanguagemodelsthroughquestionRAGMemory数据 大模型向量检索（Dense&

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p-bsed（NSW）：图

降低向量索引内存用量,ProductVector->CentroidFloat->Float->

基于Vamana图结构 ByteHouse简介多年域内业务打磨（字节90OLAP场景），基础型软件，基础型软件，造……Scaleout，2000并行计算容器化（计算资源 云原生数仓ByteHouse在RAG场景的优势SQL支持：接口灵活+OLAPOLAPGISVector ByteHouseByteHouseVector支持Share-Nothing与存算分离两种框架HNSW、HNSWSQ、IVF_PQ_FSSearchLateColumnCacheShare-Share-Compute-StorageCompute-StorageByteHouseByteHouseVector

One-passComputationIndex-granularityVectorColumnLate

Cohere(768DIM)alt0<OpenAI(1536DIM)0 日志查询,

QA、文档检索、 ByteHouseByteHouse完善ByteHouse对半结构化和非结构化数据存SegmentStructforFrequencyStatistics Reader-Level

TB级数据量IO3.5HybridHybridHybridSearchRRFMinMax msmarcosubdataset：～7000rows

VectorFullTextRRFHybridGraphRAG FrompointsearchtographsearchGraphRAGGraphRAGwith

FutureFuturePlanasSearchVectorEmbeddingSparseFullText索引性能优化：索引WAND Dis