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首页> 外文期刊>IEEE Transactions on Parallel and Distributed Systems >SEALDB: An Efficient LSM-tree Based KV Store on SMR Drives with Sets and Dynamic Bands
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SEALDB: An Efficient LSM-tree Based KV Store on SMR Drives with Sets and Dynamic Bands

机译：SEALDB：具有集合和动态频带的SMR驱动器上的基于LSM树的高效KV存储

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摘要

Key-value (KV) stores play an increasingly critical role in supporting diverse large-scale applications in modern data centers hosting terabytes of KV items which even might reside on a single server due to virtualization purposes. The combination of the ever-growing volume of KV items and storage/application consolidation is driving a trend of high storage density for KV stores. Shingled Magnetic Recording (SMR) represents a promising technology for increasing disk capacity, which however comes with the increased complexity of handling random writes. To take the best advantages of SMR drives, applications are expected to work in an SMR-friendly way. In this work, we present SEALDB, a Log-Structured Merge tree (LSM-tree) based key-value store that is specifically optimized for SMR drives via avoiding random writes and the corresponding write amplification on SMR drives. First, for LSM-trees, SEALDB collects and groups participating data of each compaction into sets. Using a set as the basic unit for compactions, SEALDB improves compaction efficiency by reducing random I/Os. Second, SEALDB creates variable sized bands on original HM-SMR drives, named dynamic bands. Dynamic bands store sets in an SMR-friendly way to eliminate the auxiliary write amplification from SMR drives. Third, SEALDB employs two light-weight garbage collection (GC) policies to further improve the space efficiency. We demonstrate the advantages of SEALDB via extensive experiments with various workloads. Overall, SEALDB delivers impressive performance compared with LevelDB, e.g., $3.42imes$3.42x/$2.65imes$2.65x faster for random writes (without or with GCs), and $3.96imes$3.96x faster for sequential reads.
机译：关键值（KV）存储在支持承载TB级KV项的现代数据中心中的各种大型应用程序中发挥越来越重要的作用，由于虚拟化目的，这些数据甚至可能驻留在单个服务器上。 KV项目数量的不断增长与存储/应用程序合并的结合，正推动着KV商店高存储密度的趋势。带状磁记录（SMR）是增加磁盘容量的一项有前途的技术，但是随着处理随机写入的复杂性增加。为了充分利用SMR驱动器的优势，应用程序应以对SMR友好的方式工作。在这项工作中，我们介绍SEALDB，这是一种基于日志结构的合并树（LSM-tree）的键值存储，它通过避免随机写入和SMR驱动器上相应的写入放大而专门针对SMR驱动器进行了优化。首先，对于LSM树，SEALDB会将每个压实的参与数据收集并分组。使用一组作为压缩的基本单位，SEALDB通过减少随机I / O来提高压缩效率。其次，SEALDB在原始HM-SMR驱动器上创建大小可变的带，称为动态带。动态波段以SMR友好的方式存储集，以消除SMR驱动器的辅助写放大。第三，SEALDB采取了两种轻型垃圾收集（GC）策略来进一步提高空间效率。我们通过各种工作量的广泛实验证明了SEALDB的优势。总体而言，SEALDB与LevelDB相比提供了令人印象深刻的性能，例如，对于随机写入（不使用GC或不使用GC），其速度分别为$ 3.42×3.42x / $ 2.65×2.65x，而顺序读取的速度为$ 3.96×3.96x。

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