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Exploring Cascaded Write Amplification in LSM-Tree Based Key-Value Stores with Solid-State Disks

机译:在带有固态磁盘的基于LSM-Tree的键值存储中探索级联写放大

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Log-structured merge tree (i.e., LSM-tree) based key-value stores, which are widely used in big-data applications, provide high performance. NAND Flash-based Solid state disks (i.e., SSDs) become the popular devices that alternative to hard disk drives (i.e., HDDs) because of the high performance and low power consumption. LSM-tree KV stores with SSDs are deployed in large-scale storage systems to achieve high performance in the cloud. However, the host-side write amplification in LSM-tree KV stores and the device-side write amplification in SSDs can impair the overall system performance. The former that is attributed to compaction has a burn on I/O bandwidth between two sides. The latter, which results from garbage collection in NAND Flash memory, blocks user I/Os from the host and degrades the SSD performance. In this study, we explored cascaded write amplification in LSM-tree KV stores with SSDs. Our primary goal is to comprehensively study two-level cascaded write amplification on the host and device sides. We quantitatively analyze the impact of two-level write amplification on overall performance. This work reveals details of cascaded write amplification and helps developers in the software stacks of LSM-tree based KV stores with SSDs.
机译:基于日志结构的合并树(即LSM树)的键值存储广泛应用于大数据应用程序中,可提供高性能。基于NAND闪存的固态磁盘(SSD)由于高性能和低功耗而成为替代硬盘驱动器(HDD)的流行设备。具有SSD的LSM树KV存储被部署在大规模存储系统中,以在云中实现高性能。但是,LSM树KV存储中的主机侧写放大和SSD中的设备侧写放大会损害整体系统性能。归因于压缩的前者在两侧之间的I / O带宽上有消耗。后者是由NAND闪存中的垃圾回收导致的​​,它阻止了主机的用户I / O,并降低了SSD性能。在这项研究中,我们探索了带有SSD的LSM树KV商店中的级联写放大。我们的主要目标是全面研究主机和设备端的两级级联写放大。我们定量分析两级写入放大对整体性能的影响。这项工作揭示了级联写放大的细节,并帮助开发人员在基于LSM树的带有SSD的KV商店的软件堆栈中。

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