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Low Latency and High Throughput Write-Ahead Logging Using CAPI-Flash

机译:使用CAPI-Flash的低延迟和高吞吐量写入预先记录

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摘要

High-velocity data imposes high durability overheads on Big Data technology components such as NoSQL data stores. In Apache Cassandra and MongoDB, widely used NoSQL solutions with high scalability and availability, write-ahead logging is used to provide durability. However, current write-ahead logging techniques are limited by the excessive overhead in the I/O subsystem. To address this performance gap, we have designed a novel CAPI-Flash based high performance durable logging mechanism for Apache Cassandra and MongoDB. We take advantage of the high throughput, low latency path to flash storage provided by the Coherent Accelerator Processor Interface (CAPI) on IBM POWER8 Systems. Our experimental results show that for insert-only workloads, CAPI-Flash logging provides up to 70 and 514 percent improvement in throughput compared to Cassandra and MongoDB's durable alternatives, respectively. It also provides average of 45 percent increase in throughput with Cassandra and average of 115 percent increase in throughput with MongoDB for update-mostly and update-only workloads.
机译:高速数据对NoSQL数据存储等大数据技术组件施加高耐久性开销。在Apache Cassandra和MongoDB中,广泛使用的NoSQL解决方案具有高可扩展性和可用性,注销日志记录用于提供耐用性。然而,当前的写入测井技术受I / O子系统中过度开销的限制。为了解决这种性能缺口,我们设计了一种基于CAPI-Flash的高性能耐用测井机制,适用于Apache Cassandra和MongoDB。我们利用IBM Power8系统上的相干加速器处理器接口(CAPI)提供的闪存存储的高吞吐量,低延迟路径。我们的实验结果表明,与Cassandra和MongoDB的持久替代品相比,Capi-Flash测井可以分别提供高达70%和514%的提高吞吐量。它还提供了Cassandra的吞吐量增加了45%,并且使用MongoDB的吞吐量增加了115%的吞吐量,用于更新和仅更新的工作负载。

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