RDF数据的Skyline优化查询

Skyline query optimization for RDF data

为解决海量RDF数据的Skyline查询问题,通过分析现有Skyline查询算法的优缺点,提出一种针对海量RDF数据的查询机制。对RDF数据的存储结构进行分析,根据RDF数据垂直存储结构,设计一种候选Skyline点筛选策略,提前修剪部分非Skyline元组,减少Skyline支配点计算的数据量;在筛选的基础上,给出基于MapReduce的Skyline并行化查询算法。实验结果表明,提前筛选能有效减小查询的数据集,并行化算法能够有效提高查询的效率。

To address the problem of Skyline query for massive RDF data,an optimizing query method for RDF data was proposed by analyzing the advantages and disadvantages of the existing Skyline query algorithm.To save the time cost of checking dominators in Skyline,a filter strategy for candidate Skyline point was designed,according to the characters of RDF storage mode,which pruned some points that not belonged to Skyline in advance.Skyline parallel query arithmetic was put forward on the basis of MapReduce framework.Experimental results indicate that pruning points in advance can effectively reduce the amount of checking dataset,and parallel query arithmetic can refine the query processing greatly.