A Selective Compression Strategy for Performance Improvement of Database Compression
2
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
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.
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.
참고문헌 (12)
- K. -H. Lee, "Performance Improvement of Database Compression for OLTP Workloads", IEICE Trans. on Information and Systems, E97-D(4,), pp.976~980 (2014)
- M. Poess, "Data Compression in Oracle", Proc. the Int'l Conf. on Very Large Data Bases(VLDB), pp.937~947 (2003)
- "MySQL 5. 5 Reference Manual"[URL]
- Transaction Processing Performance Council (TPC), "TPC BENCHMARK C", Standard Specification, Revision 5.11, ~ (2010)
- B. Bhattacharje, "Efficient index compression in DB2LUW", Proc. the Int'l Conf. on Very Large Data Bases(VLDB), pp.1462~1473 (2009)
- N. Ordulu, "InnoDB Compression: Present and Future", Percona Live MySQL Conference (2013)
- "zlib"[URL]
- M. A. Roth, "Database Compression", ACM SIGMOD Record, 22(3), pp.31~39 (1993)
- "Database Test 2(DBT2)"[URL]
- P. Zaitsev, "MySQL", InnoDB Performance, Server and Schema, 2004, ~
- "CrystalDiskMark"[URL]
- E. -M. Lee, "Optimizing Index Scans on Flash Memory SSDs", ACM SIGMOD Record, 40(4), pp.5~10 (2011)