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计算机系统应用英文版:2013,22(7):133-136
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混合散列连接算法随机I/O消除
(1.浙江工业大学 计算机科学与技术学院, 杭州 310014;2.杭州市公安局 交通警察局科研所, 杭州 310014)
Towards Eliminating Random I/O in Hybrid Hash Joins
(1.School of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310014, China;2.Insititute of Traffic Control, Hangzhou Municipal Public Security Bureau Traffic Police Division, Hangzhou 310014, China)
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Received:December 10, 2012    Revised:January 15, 2013
中文摘要: 混合散列连接算法(HHJ)是数据库管理系统查询处理中一种重要的连接算法. 本文提出通过缓存优化来减少随机I/O的缓存优化混合散列连接算法(OHHJ), 即通过合理优化分区阶段桶缓存的大小来尽量减少分区过程中产生的随机I/O. 文章通过对分区(桶)大小、桶缓存大小、可用缓存大小、关系表大小与硬盘随机I/O访问特性之间的关系进行定量分析, 得出桶大小以及桶缓存大小最优分配的启发式. 实验结果表明OHHJ可以较好地减少传统HHJ算法分区阶段产生的随机I/O, 提升了算法性能.
Abstract:HHJ is one of the mostly used core join algorithms for query processing in a database management system. This paper proposes a buffer-optimized hybrid hash join algorithm(OHHJ) by optimizing the bucket buffer to reduce the random I/O in hash join, i.e., to minimize the random I/O by optimizing the bucket buffer size in partition phase. By quantitatively analyzing the relationship between the bucket size, bucket buffer size, available memory size, relation size and random I/O access characteristics of hard disk, we have derived the heuristics for allocating the optimal bucket and bucket buffer sizes. The experimental results demonstrate that OHHJ can effectively reduce random I/O in HHJ during partition phase, and thus enhance the performance of the algorithm.
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基金项目:国家自然科学基金(61070042);浙江省自然科学基金(Y13F020114,Y1090096)
引用文本:
刘明超,杨良怀,周为钢.混合散列连接算法随机I/O消除.计算机系统应用,2013,22(7):133-136
LIU Ming-Chao,YANG Liang Huai,ZHOU Wei-Gang.Towards Eliminating Random I/O in Hybrid Hash Joins.COMPUTER SYSTEMS APPLICATIONS,2013,22(7):133-136