NDLI: Elasticity Improvement of Cassandra

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Elasticity Improvement of Cassandra

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Elasticity Improvement of Cassandra

Content Provider	ACM Digital Library
Author	Tokuda, Taiki Miyokawa, Shohei Yamaguchi, Saneyasu
Abstract	Load size for a service on the Internet changes remarkably every hour. Thus, it is expected for service system scales to change dynamically according to load size. KVS (key-value store) is a scalable DBMS (database management system) widely used in large-scale Internet services. In this paper, we focus on Cassandra, a popular open-source KVS implementation, and discuss methods for improving dynamic scaling performance. First, we evaluate node joining time, which is the time to complete adding a node to a running KVS system, and show that its bottleneck process is disk I/O in the existing nodes. Second, we analyze disk accesses in the bottleneck nodes and indicate that some heavily accessed files cause a large number of disk accesses. Third, we propose a method for improving elasticity, which means decreasing node adding and removing time, of Cassandra. The method reduces disk accesses significantly by keeping the heavily accessed file in the page cache. Lastly, we evaluate elasticity of our methods. Our experimental results demonstrate that the method can improve the scaling-up and scaling-down performance of Cassandra.
Starting Page	1
Ending Page	7
Page Count	7
File Format	PDF
ISBN	9781450341424
DOI	10.1145/2857546.2857584
Language	English
Publisher	Association for Computing Machinery (ACM)
Publisher Date	2016-01-04
Publisher Place	New York
Access Restriction	Subscribed
Subject Keyword	Key-value store Cassandra Page cache
Content Type	Text
Resource Type	Article

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