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Benchmarking the Availability and Fault Tolerance of Cassandra

机译:基准Cassandra的可用性和容错性

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To be able to handle big data workloads, modern NoSQL database management systems like Cassandra are designed to scale well over multiple machines. However, with each additional machine in a cluster, the likelihood for hardware failure increases. In order to still achieve high availability and fault tolerance, the data needs to be replicated within the cluster. Predictable and stable response times are required by many applications even in the case of a node failure. While Cassandra guarantees high availability, the influence of a node failure on the system performance is still unclear. In this paper, we therefore focus on the availability and fault tolerance of Cassandra. We analyze the impact of a node outage within a Cassandra cluster on the throughput and latency for different workloads. Our results show that Cassandra is well suited to achieve high availability while preserving table response times in case of a node failure. Especially for read intensive applications that require high availability, Cassandra is a good choice.
机译:为了能够处理大数据工作负载,像Cassandra这样的现代NoSQL数据库管理系统旨在通过多台机器进行扩展。但是,对于集群中的每台额外机器,硬件故障的可能性增加。为了仍然达到高可用性和容错,数据需要在群集中复制。即使在节点故障的情况下,许多应用程序也需要预测和稳定的响应时间。虽然Cassandra保证了高可用性,但节点故障对系统性能的影响尚不清楚。在本文中,我们专注于Cassandra的可用性和容错。我们分析了在Cassandra集群中的节点中断对不同工作负载的吞吐量和延迟的影响。我们的结果表明,Cassandra非常适合在节点故障的情况下保留表响应时间的同时实现高可用性。特别是对于需要高可用性的阅读密集型应用,Cassandra是一个不错的选择。

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