Applying In-Memory Storage to Low Latency Semantic Web Applications
msra
摘要
The storage and query of RDF is a challenging problem: the graph structure of RDF combined with unpredictable query patterns means that even simple queries generate a lot of random access, inhibiting the performance of disk-backed stores. RDF store performance is thus typically poor compared to traditional RDBMSs, inhibiting the use of RDF in large scale, low latency applications. As available memory on mid range servers scales into tens of gigabytes, in-memory DBMSs are an attractive alternative for managing a wide variety of datasets. We argue that RDF would benefit from such in-memory storage, justifying this with a detailed analysis of the popular Jena Memory Model, aimed at evaluating and improving the Memory Model's capacity to work with large datasets for low latency applications. From this analysis we conclude that while in-memory storage offers promising performance, Jena's data structures must be redesigned to support reduced memory overhead while maintaining performance.
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关键词
jena,cache,rdf,jvm,java,dbms,database,memory,semantic web
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