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Transparent Online Storage Compression at the Block-Level

机译:块级别的透明在线存储压缩

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摘要

In this work, we examine how transparent block-level compression in the I/O path can improve both the space efficiency and performance of online storage. We present ZBD, a block-layer driver that transparently compresses and decompresses data as they flow between the file-system and storage devices. Our system provides support for variable-size blocks, metadata caching, and persistence, as well as block allocation and cleanup. ZBD targets maintaining high performance, by mitigating compression and decompression overheads that can have a significant impact on performance by leveraging modern multicore CPUs through explicit work scheduling. We present two case-studies for compression. First, we examine how our approach can be used to increase the capacity of SSD-based caches, thus increasing their cost-effectiveness. Then, we examine how ZBD can improve the efficiency of online disk-based storage systems. We evaluate our approach in the Linux kernel on a commodity server with multicore CPUs, using Post-Mark, SPECsfs2008, TPC-C, and TPC-H. Preliminary results show that transparent online block-level compression is a viable option for improving effective storage capacity, it can improve I/O performance up to 80% by reducing I/O traffic and seek distance, and has a negative impact on performance, up to 34%, only when single-thread I/O latency is critical. In particular, for SSD-based caching, our results indicate that, in line with current technology trends, compressed caching trades off CPU utilization for performance and enhances SSD efficiency as a storage cache up to 99%.
机译:在这项工作中,我们研究了I / O路径中的透明块级压缩如何提高空间效率和在线存储性能。我们介绍了ZBD,这是一个块层驱动程序,可以在数据在文件系统和存储设备之间流动时透明地压缩和解压缩数据。我们的系统支持可变大小的块,元数据缓存和持久性,以及块分配和清除。 ZBD旨在通过减少压缩和解压缩开销来维持高性能,这些开销可以通过显式的工作调度来利用现代多核CPU,从而对性能产生重大影响。我们提出了两个压缩案例研究。首先,我们研究如何使用我们的方法来增加基于SSD的缓存的容量,从而提高其成本效益。然后,我们研究ZBD如何提高基于磁盘的在线存储系统的效率。我们使用Post-Mark,SPECsfs2008,TPC-C和TPC-H在具有多核CPU的商用服务器上的Linux内核中评估我们的方法。初步结果表明,透明的在线块级压缩是提高有效存储容量的可行选择,它可以通过减少I / O流量和查找距离来将I / O性能提高多达80%,并且对性能产生负面影响。仅当单线程I / O延迟至关重要时,才可达到34%。特别是,对于基于SSD的缓存,我们的结果表明,与当前的技术趋势相一致,压缩缓存权衡了CPU利用率与性能之间的关系,并将SSD的存储缓存效率提高了99%。

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