Fast Multi-Column Sorting in Main-Memory Column-Stores

Wenjian Xu, Ziqiang Feng, Eric Lo
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引用次数: 11

Abstract

Sorting is a crucial operation that could be used to implement SQL operators such as GROUP BY, ORDER BY, and SQL:2003 PARTITION BY. Queries with multiple attributes in those clauses are common in real workloads. When executing queries of that kind, state-of-the-art main-memory column-stores require one round of sorting per input column. With the advent of recent fast scans and denormalization techniques, that kind of multi-column sorting could become a bottleneck. In this paper, we propose a new technique called "code massaging", which manipulates the bits across the columns so that the overall sorting time can be reduced by eliminating some rounds of sorting and/or by improving the degree of SIMD data level parallelism. Empirical results show that a main-memory column-store with code massaging can achieve speedup of up to 4.7X, 4.7X, 4X, and 3.2X on TPC-H, TPC-H skew, TPC-DS, and real workload, respectively.
快速多列排序在主存列存储
排序是一项关键操作,可用于实现诸如GROUP BY、ORDER BY和SQL:2003 PARTITION BY等SQL操作符。在这些子句中具有多个属性的查询在实际工作负载中很常见。在执行这类查询时,最先进的主存列存储需要对每个输入列进行一轮排序。随着最近快速扫描和反规范化技术的出现,这种多列排序可能成为瓶颈。在本文中,我们提出了一种称为“代码处理”的新技术,该技术可以跨列操作位,从而通过消除一些排序轮和/或通过提高SIMD数据级并行度来减少总体排序时间。经验结果表明,带有代码按摩的主存列存储在TPC-H、TPC-H倾斜、TPC-DS和实际工作负载上分别可以实现高达4.7倍、4.7倍、4倍和3.2倍的加速。
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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