A Selective Compression Strategy for Performance Improvement of Database Compression


KIPS Transactions on Software and Data Engineering, Vol. 4, No. 9, pp. 371-376, Sep. 2015
10.3745/KTSDE.2015.4.9.371,   PDF Download:

Abstract

The Internet of Things (IoT) significantly increases the amount of data. Database compression is important for big data because it can reduce costs for storage systems and save I/O bandwidth. However, it could show low performance for write-intensive workloads such as OLTP due to the updates of compressed pages. In this paper, we present practical guidelines for the performance improvement of database compression. Especially, we propose the SELECTIVE strategy, which compresses only tables whose space savings are close to the expected space savings calculated by the compressed page size. Experimental results using the TPC-C benchmark and MySQL show that the strategy can achieve 1.1 times better performance than the uncompressed counterpart with 17.3% space savings.


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Cite this article
[IEEE Style]
K. H. Lee, "A Selective Compression Strategy for Performance Improvement of Database Compression," KIPS Transactions on Software and Data Engineering, vol. 4, no. 9, pp. 371-376, 2015. DOI: 10.3745/KTSDE.2015.4.9.371.

[ACM Style]
Ki Hoon Lee. 2015. A Selective Compression Strategy for Performance Improvement of Database Compression. KIPS Transactions on Software and Data Engineering, 4, 9, (2015), 371-376. DOI: 10.3745/KTSDE.2015.4.9.371.