Using intrinsic data skew to improve hash join performance
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摘要
Hash join is used to join large, unordered relations and operates independently of the data distributions of the join relations. Real-world data sets are not uniformly distributed and often contain significant skew. Although partition skew has been studied for hash joins, no prior work has examined how exploiting data skew can improve the performance of hash join. In this paper, we present histojoin, a join algorithm that uses histograms to identify data skew and improve join performance. Experimental results show that for skewed data sets histojoin performs significantly fewer I/O operations and is faster by 10–60% than hybrid hash join.
论文关键词:Hybrid hash join,Skew,Histogram,Partition,Distribution
论文评审过程:Received 1 April 2008, Revised 14 October 2008, Accepted 4 February 2009, Available online 21 February 2009.
论文官网地址:https://doi.org/10.1016/j.is.2009.02.003