Optimizing the Join Operation on Hive to Accelerate Cross-Matching in Astronomy

Liang Li, Dixin Tang, Taoying Liu, Hong Liu, Wei Li, Chenzhou Cui
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引用次数: 5

Abstract

Cross-matching in astronomy is a basic procedure for comprehensibly analyzing the relations among different celestial objects. The aim is to search celestial objects in different catalogs and to determine if they are the same object. Basically, cross-matching can be expressed as a join query statement. Since celestial catalogs usually contain billion of stars, the join operator must be carefully designed and optimized for efficiency. In this paper, we focus on fulfilling cross-matching by MapReduce based join operators. The challenge is how to optimize the join operators to satisfy specific requirements of cross-matching. Therefore, we propose an optimized method and investigate its efficiency by theoretical analysis and experiment. Our study shows that the method has a remarkable improvement to previous work, especially when the data is very large.
优化Hive上的Join操作加速天文学交叉匹配
交叉匹配是天文学中全面分析天体间关系的基本方法。目的是搜索不同星表中的天体,并确定它们是否为同一天体。基本上,交叉匹配可以表示为连接查询语句。由于天体目录通常包含数十亿颗恒星,因此必须仔细设计和优化连接操作符以提高效率。在本文中,我们着重于通过基于MapReduce的连接算子实现交叉匹配。难点在于如何优化连接操作符以满足交叉匹配的特定要求。为此,我们提出了一种优化方法,并通过理论分析和实验验证了其有效性。我们的研究表明,该方法比以往的工作有了显著的改进,特别是在数据量很大的情况下。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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