摘要
I/O parallelism is considered to be a promising approach to achieving highperformance in parallel data warehousing systems where huge amounts of data and complex analyticalqueries have to be processed. This paper proposes a parallel secondary data cube storage structure(PHC for short) to efficiently support the processing of range sum queries and dynamic updates ondata cube using parallel computing systems. Based on PHC, two parallel algorithms for processingrange sum queries and updates are proposed also. Both the algorithms have the same time complexity,O(log^d n/P). The analytical and experimental results show that PHC and the parallel algorithms havehigh performance and achieve optimum speedup.
I/O parallelism is considered to be a promising approach to achieving highperformance in parallel data warehousing systems where huge amounts of data and complex analyticalqueries have to be processed. This paper proposes a parallel secondary data cube storage structure(PHC for short) to efficiently support the processing of range sum queries and dynamic updates ondata cube using parallel computing systems. Based on PHC, two parallel algorithms for processingrange sum queries and updates are proposed also. Both the algorithms have the same time complexity,O(log^d n/P). The analytical and experimental results show that PHC and the parallel algorithms havehigh performance and achieve optimum speedup.
基金
国家自然科学基金，黑龙江省自然科学基金
