CAJ | 학술논문

　　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.
　　혼합산렬련접산법(HHJ)시수거고관리계통사순처리중일충중요적련접산법.본문제출통과완존우화래감소수궤 I/O 적완존우화혼합산렬련접산법(OHHJ),즉통과합리우화분구계단통완존적대소래진량감소분구과정중산생적수궤I/O.문장통과대분구(통)대소、통완존대소、가용완존대소、관계표대소여경반수궤I/O방문특성지간적관계진행정량분석,득출통대소이급통완존대소최우분배적계발식.실험결과표명OHHJ가이교호지감소전통HHJ산법분구계단산생적수궤I/O,제승료산법성능.
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.