Performance Comparison of Containerized HBase Clusters on Kubernetes

Ta-Chun Lo, Chun-Ying Tao, Jyh-Biau Chang, C. Shieh
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Abstract

The demand for large-volume database storage has become an essential issue with the rising trend of big data. Since the NoSQL database performs better than SQL databases when handling extensive data, many developers choose the NoSQL database as their first choice. Among all the NoSQL databases, HBase has become a popular choice due to its flexibility and high efficiency in the big data processing field. HBase is a column-oriented NoSQL database. It uses HDFS storage and is suitable for integrating with Hadoop ecosystem applications. However, deploying an HBase cluster on bare metal or virtual machines could be pretty complicated and time-consuming. The container technology can make HBase installation more convenient. Nevertheless, containerized HBase can be deployed in different ways. Deploying the HBase cluster in a proper approach can achieve higher performance. In this research, we propose two approaches, namely the Container-dedicated approach and the Container-shared approach, to containerize HBase on Kubernetes. Two benchmark tools are used to compare their performance under different workloads. According to experiment results, the Container-dedicated approach is suitable for writeheavy and read/write balanced applications. The container-shared approach shows a better performance in read-heavy applications. The test result will give future developers a reference when designing a containerized HBase cluster.
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Kubernetes上容器化HBase集群性能比较
随着大数据的兴起,对大容量数据库存储的需求已经成为一个必不可少的问题。由于NoSQL数据库在处理大量数据时比SQL数据库性能更好,因此许多开发人员选择NoSQL数据库作为他们的首选。在众多NoSQL数据库中,HBase以其灵活性和高效性成为大数据处理领域的热门选择。HBase是一个面向列的NoSQL数据库。它使用HDFS存储,适合与Hadoop生态系统应用集成。然而,在裸机或虚拟机上部署HBase集群可能非常复杂且耗时。容器技术可以使HBase的安装更加方便。然而,容器化的HBase可以以不同的方式部署。合理部署HBase集群可以获得更高的性能。在本研究中,我们提出了两种方法,即容器专用方法和容器共享方法,以在Kubernetes上容器化HBase。使用两个基准测试工具来比较它们在不同工作负载下的性能。实验结果表明,容器专用方法适用于写量大、读写均衡的应用程序。容器共享方法在大量读取的应用程序中表现出更好的性能。测试结果可为未来开发人员在设计容器化HBase集群时提供参考。
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