Journal of Information Processing Systems

  • 제4권1호
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  • Pages.9-16
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  • 2008
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  • 1976-913X(pISSN)
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  • 2092-805X(eISSN)
한국정보처리학회 (Korea Information Processing Society)
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Two-Tier Storage DBMS for High-Performance Query Processing

  • Eo, Sang-Hun (Dept. of Information Engineering, Inha University) ;
  • Li, Yan (Dept. of Information Engineering, Inha University) ;
  • Kim, Ho-Seok (LG Mobile Handset R&D Center of Mobile Communications Company, LG Electronics Inc) ;
  • Bae, Hae-Young (Dept. of Information Engineering, Inha University)
  • 발행 : 2008.03.31
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초록

This paper describes the design and implementation of a two-tier DBMS for handling massive data and providing faster response time. In the present day, the main requirements of DBMS are figured out using two aspects. The first is handling large amounts of data. And the second is providing fast response time. But in fact, Traditional DBMS cannot fulfill both the requirements. The disk-oriented DBMS can handle massive data but the response time is relatively slower than the memory-resident DBMS. On the other hand, the memory-resident DBMS can provide fast response time but they have original restrictions of database size. In this paper, to meet the requirements of handling large volumes of data and providing fast response time, a two-tier DBMS is proposed. The cold-data which does not require fast response times are managed by disk storage manager, and the hot-data which require fast response time among the large volumes of data are handled by memory storage manager as snapshots. As a result, the proposed system performs significantly better than disk-oriented DBMS with an added advantage to manage massive data at the same time.

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참고문헌

  1. Bijit Hore, Hakan Hacigumus, Bala Iyer, Sharad Mehrotrasss, “Indexing text data under space constraints,” Proceedings of the thirteenth ACM international conference on Information and knowledge management CIKM '04, November 2004
  2. Goetz Graefe, Michael Zwilling, “Transaction support for indexed summary views,” Proceedings of the 2004 ACM SIGMOD international conference on Management of data, June 2004
  3. Sven Helmer, Guido Moerkotte, “A performance study of four index structures for set-valued attributes of low cardinality,” The International Journal on Very Large Data Bases, Volume 12, Issue 3, October 2003
  4. Zhifeng Chen, Yan Zhang, Yuanyuan Zhou, Heidi Scott, Berni Schiefer, “Empirical evaluation of multilevel buffer cache collaboration for storage systems,” Proceedings of the 2005 ACM SIGMETRICS international conference on Measurement and modeling of computer systems SIGMETRICS '05, Volume 33 Issue 1, June 2005
  5. Wenhu Tian, Pat Martin, Wendy Powley, “Techniques for automatically sizing multiple buffer pools in DB2,” Proceedings of the 2003 conference of the Centre for Advanced Studies on Collaborative research, October 2003
  6. Stephane Bressan, Chong Leng Goh, Beng Chin Ooi, Kian-Lee Tan, “A framework for modeling buffer replacement strategies,” Proceedings of the ninth international conference on Information and knowledge management, November 2000
  7. Jonathan Goldstein, Per-Ake Larson, “Optimizing queries using materialized views: a practical, scalable solution,” Proceedings of the 2001 ACM SIGMOD international conference on Management of data, 2001
  8. James J. Lu, Guido Moerkotte, Joachim Schue, V. S. Subrahmanian, “Efficient maintenance of materialized mediated views,” Proceedings of the 1995 ACM SIGMOD international conference on Management of data, 1995
  9. Minwen Ji, “Affinity-based management of main memory database clusters,” ACM Transactions on Internet Technology (TOIT), Volume 2 Issue 4, November 2002
  10. Philip Bohannon, Peter Mcllroy, Rajeev Rastogi, “Main-memory index structures with fixed-size partial keys,” Proceedings of the 2001 ACM SIGMOD International conference on Management of data SIGMOD '01, Volume 30 Issue 2, May 2001
  11. Tobin J. Lehman and Michael J. Carey, “A Study of Index Structures for Main Memory Database Management Systems,” Proceedings of the Twelfth International Conference on Very Large Data Bases, 1986
  12. Ying Xia, Sung-Hee Kim, Sook-Kyoung Cho, Kee- Wook Rim, Hae-Young Bae, “Dynamic versioning concurrency control for index-based data access in main memory database systems,” Proceedings of the tenth international conference on Information and knowledge management, October 2001
  13. Tobin J.Lehman, J. Shekita and Luis-Felipe Cabrera, “An Evaluation of Starburst's Memory Resident Storage Component,” IEEE Transactions on knowledge and data Engineering, Vol. 4, NO. 6, DECEMBER, 1992
  14. Michael Stonebraker, “Managing Persistent Objects in a Multi-Level Store,” SIGMOD Conference, pp2- 11, 1991
  15. Kong-Rim Choi, Kyung-Chang Kim, “T*-tree: a main memory database index structure for real time applications,” Proceedings of the Third International Workshop on Real-Time Computing Systems Application (RTCSA '96), October 1996
  16. Tobin Jon Lehman, “Design and performance evaluation of a main memory relational database system (t tree),” Doctoral Thesis, January 1986
  17. D. Bitton, D. DeWitt, and C. Turbyfill, “Benchmarking simple database operations,” in Proc. 9th Int. Conf. on Very Large Databases, Nov. 1983
  18. S. Park, W. chung, and M. Kim GMS, “Spatial database management system,” Proc. of the KISS Spring Conf, April, 2003