Pipelined Compaction for the LSM-Tree

Zigang Zhang, Yinliang Yue, Bingsheng He, Jin Xiong, Mingyu Chen, Lixin Zhang, Ninghui Sun
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引用次数: 29

Abstract

Write-optimized data structures like Log-Structured Merge-tree (LSM-tree) and its variants are widely used in key-value storage systems like Big Table and Cassandra. Due to deferral and batching, the LSM-tree based storage systems need background compactions to merge key-value entries and keep them sorted for future queries and scans. Background compactions play a key role on the performance of the LSM-tree based storage systems. Existing studies about the background compaction focus on decreasing the compaction frequency, reducing I/Os or confining compactions on hot data key-ranges. They do not pay much attention to the computation time in background compactions. However, the computation time is no longer negligible, and even the computation takes more than 60% of the total compaction time in storage systems using flash based SSDs. Therefore, an alternative method to speedup the compaction is to make good use of the parallelism of underlying hardware including CPUs and I/O devices. In this paper, we analyze the compaction procedure, recognize the performance bottleneck, and propose the Pipelined Compaction Procedure (PCP) to better utilize the parallelism of CPUs and I/O devices. Theoretical analysis proves that PCP can improve the compaction bandwidth. Furthermore, we implement PCP in real system and conduct extensive experiments. The experimental results show that the pipelined compaction procedure can increase the compaction bandwidth and storage system throughput by 77% and 62% respectively.
lsm树的流水线压缩
写优化的数据结构,如日志结构合并树(Log-Structured Merge-tree, LSM-tree)及其变体,广泛用于Big Table和Cassandra等键值存储系统。由于延迟和批处理,基于lsm树的存储系统需要后台压缩来合并键值条目,并为将来的查询和扫描保持它们的排序。背景压缩对基于lsm树的存储系统的性能起着至关重要的作用。现有关于后台压缩的研究主要集中在降低压缩频率、减少I/ o或限制对热数据键范围的压缩。它们在后台压缩时不太注意计算时间。然而,计算时间不再是可以忽略不计的,甚至在使用基于闪存的ssd的存储系统中,计算时间也超过了总压缩时间的60%。因此,加速压缩的另一种方法是充分利用底层硬件(包括cpu和I/O设备)的并行性。在本文中,我们分析了压缩过程,识别了性能瓶颈,提出了流水线压缩过程(PCP),以更好地利用cpu和I/O设备的并行性。理论分析证明,PCP可以提高压缩带宽。此外,我们在实际系统中实现了PCP,并进行了大量的实验。实验结果表明,采用流水线压缩方式可使压缩带宽和存储系统吞吐量分别提高77%和62%。
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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