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Scaling HDFS to More Than 1 Million Operations Per Second with HopsFS

机译:使用HopsFS将HDFS扩展到每秒超过100万次操作

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HopsFS is an open-source, next generation distribution of the Apache Hadoop Distributed File System (HDFS) that replaces the main scalability bottleneck in HDFS, single node in-memory metadata service, with a no-shared state distributed system built on a NewSQL database. By removing the metadata bottleneck in Apache HDFS, HopsFS enables significantly larger cluster sizes, more than an order of magnitude higher throughput, and significantly lower client latencies for large clusters. In this paper, we detail the techniques and optimizations that enable HopsFS to surpass 1 million file system operations per second - at least 16 times higher throughput than HDFS. In particular, we discuss how we exploit recent high performance features from NewSQL databases, such as application defined partitioning, partition-pruned index scans, and distribution aware transactions. Together with more traditional techniques, such as batching and write-ahead caches, we show how many incremental optimizations have enabled a revolution in distributed hierarchical file system performance.
机译:HopsFS是Apache Hadoop分布式文件系统(HDFS)的开源下一代发行版,它取代了建立在NewSQL数据库上的无共享状态分布式系统,从而取代了HDFS中的主要可伸缩性瓶颈,单节点内存元数据服务。 。通过消除Apache HDFS中的元数据瓶颈,HopsFS可以实现更大的集群大小,更高的吞吐量(一个数量级以上)和大大降低的大型集群客户端延迟。在本文中,我们详细介绍了使HopsFS每秒超过100万个文件系统操作的技术和优化-吞吐量至少是HDFS的16倍。特别是,我们讨论了如何利用NewSQL数据库的最新高性能功能,例如应用程序定义的分区,分区修剪的索引扫描和可识别分发的事务。与更传统的技术(例如批处理和预写高速缓存)一起,我们展示了多少增量优化使分布式分层文件系统性能发生了革命。

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