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首页> 外文期刊>ACM Transactions on Storage >Building Efficient Key-Value Stores via a Lightweight Compaction Tree
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Building Efficient Key-Value Stores via a Lightweight Compaction Tree

机译:通过轻量级压缩树构建高效的键值存储

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摘要

Log-Structure Merge tree (LSM-tree) has been one of the mainstream indexes in key-value systems supporting a variety of write-intensive Internet applications in today's data centers. However, the performance of LSM-tree is seriously hampered by constantly occurring compaction procedures, which incur significant write amplification and degrade the write throughput. To alleviate the performance degradation caused by compactions, we introduce a lightweight compaction tree (LWC-tree), a variant of LSM-tree index optimized for minimizing the write amplification and maximizing the system throughput. The lightweight compaction drastically decreases write amplification by appending data in a table and only merging the metadata that have much smaller size. Using our proposed LWC-tree, we have implemented three key-value LWC-stores on different storage mediums including Shingled Magnetic Recording (SMR) drives, Solid State Drives (SSD), and conventional Hard Disk Drives (HDDs). The LWC-store is particularly optimized for SMR drives, as it eliminates the multiplicative I/O amplification from both LSM-trees and SMR drives. Due to the lightweight compaction procedure, LWC-store reduces the write amplification by a factor of up to 5x compared to the popular LevelDB key-value store. Moreover, the random write throughput of the LWC-tree on SMR drives is significantly improved by up to 467% even compared with LevelDB on conventional HDDs. Furthermore, LWC-tree has wide applicability and delivers impressive performance improvement in various conditions, including different storage mediums (i.e., SMR, HDD, SSD) and various value sizes and access patterns (i.e., uniform and Zipfian).
机译:日志结构合并树(LSM树)是在当今数据中心支持各种写入密集型互联网应用的钥匙值系统中的主流索引之一。然而,通过不断发生的压实程序严重阻碍了LSM树的性能,这导致了显着的写入放大并降低了写入吞吐量。为了缓解由作用引起的性能劣化,我们引入了一个轻量级压缩树(LWC树),是用于最小化写入放大和最大化系统吞吐量的LSM树指数的变体。轻量级压缩通过在表中附加数据并仅合并具有要较小尺寸的元数据来大大降低写入放大。使用我们所提出的LWC树,我们已经在不同的存储介质上实现了三个键值LWC存储,包括凸起的磁记录(SMR)驱动器,固态驱动器(SSD)和传统的硬盘驱动器(HDD)。 LWC-Store特别针对SMR驱动器进行了优化,因为它消除了来自LSM树和SMR驱动器的乘法I / O放大。由于轻量级压缩过程,与流行的Leveldb键值存储相比,LWC-Store将写入放大倍数高达5倍。此外,与常规HDDS上的LeveldB相比,SMR驱动器上的LWC树的随机写入吞吐量显着提高了467%。此外,LWC树具有广泛的适用性,并在各种条件下提供令人印象深刻的性能改进,包括不同的存储介质(即,SMR,HDD,SSD)和各种价值尺寸和访问模式(即,统一和ZIPFIAN)。

著录项

  • 来源
    《ACM Transactions on Storage 》 |2017年第4期| 共28页
  • 作者单位

    Huazhong Univ Sci &

    Technol Sch Comp Sci &

    Technol Wuhan Natl Lab Optoelect Wuhan Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol Sch Comp Sci &

    Technol Wuhan Natl Lab Optoelect Wuhan Hubei Peoples R China;

    Temple Univ Dept Comp &

    Informat Sci Philadelphia PA 19122 USA;

    Temple Univ Dept Comp &

    Informat Sci Philadelphia PA 19122 USA;

    Huazhong Univ Sci &

    Technol Sch Comp Sci &

    Technol Wuhan Natl Lab Optoelect Wuhan Hubei Peoples R China;

    Huazhong Univ Sci &

    Technol Sch Comp Sci &

    Technol Wuhan Natl Lab Optoelect Wuhan Hubei Peoples R China;

  • 收录信息
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 存贮器 ;
  • 关键词

    Lightweight compaction; LSM-tree; write amplification; SMR drives;

    机译:轻量级压实;LSM树;写放大;SMR驱动器;

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