基于Solr的司法大数据检索模型研究与实现

Research and realization on judicial large data retrieval mode

围绕司法领域信息要素的高维性特征以及司法信息要素间的紧耦合性特征,针对司法数据检索技术中由高维信息要素间的紧耦合性导致的检索效率问题,研究和实现了一个基于Solr的司法大数据检索模型。该模型采用Solr超级集群作为数据索引库,采用HBase集群作为数据存储库,通过引入数据与索引分离、redis缓存、动态参数调整、动态cache释放等设计思路,实现了一个高效、可靠、可扩展的司法大数据检索模型。

Based on the high dimensionality and the tight coupling of judicial fields and the retrieval efficiency,a judicialbig data retrieval model based on Solr is studied and implemented.This model uses the Solr supercluster as the data indexlibrary,and uses the HBase cluster as the data repository.By introducing the separation of data and index,redis cache,dynamic parameter adjustment and dynamic cache release,a high efficiency,reliable and scalable judicial big data retrievalmodel is designed.