skip to main content
research-article

Scalable query result caching for web applications

Published:01 August 2008Publication History
Skip Abstract Section

Abstract

The backend database system is often the performance bottleneck when running web applications. A common approach to scale the database component is query result caching, but it faces the challenge of maintaining a high cache hit rate while efficiently ensuring cache consistency as the database is updated. In this paper we introduce Ferdinand, the first proxy-based cooperative query result cache with fully distributed consistency management. To maintain a high cache hit rate, Ferdinand uses both a local query result cache on each proxy server and a distributed cache. Consistency management is implemented with a highly scalable publish/subscribe system. We implement a fully functioning Ferdinand prototype and evaluate its performance compared to several alternative query-caching approaches, showing that our high cache hit rate and consistency management are both critical for Ferdinand's performance gains over existing systems.

References

  1. G. Alonso. Partial database replication and group communication primitives. In Proc. European Research Seminar on Advances in Distributed Systems, 1997.Google ScholarGoogle Scholar
  2. M. Altinel, C. Bornhovd, S. Krishnamurthy, C. Mohan, H. Pirahesh, and B. Reinwald. Cache tables: Paving the way for an adaptive database cache. In Proc. International Conference on Very Large Data Bases, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. K. Amiri, S. Park, R. Tewari, and S. Padmanabhan. DBProxy: A dynamic data cache for Web applications. In Proc. International Conference on Data Engineering, 2003.Google ScholarGoogle ScholarCross RefCross Ref
  4. K. Amiri, S. Sprenkle, R. Tewari, and S. Padmanabhan. Exploiting templates to scale consistency maintenance in edge database caches. In Proc. International Workshop on Web Content Caching and Distribution, 2003.Google ScholarGoogle Scholar
  5. E. Brynojolfsson, M. Smith, and Y. Hu. Consumer surplus in the digital economy: Estimating the value of increased product variety at online booksellers. MIT Sloan Working paper No. 4305--03, 2003.Google ScholarGoogle Scholar
  6. M. Castro, P. Druschel, A-M. Kermarrec, and A. Rowstron. SCRIBE: A large-scale and decentralised application-level multicast infrastructure. IEEE Journal on Selected Areas in Communication, October 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. I. Chabbouh and M. Makpangou. Caching dynamic content with automatic fragmentation. In G. Kotsis, D. Taniar, S. Bressan, I. K. Ibrahim, and S. Mokhtar, editors, ii WAS, volume 196 of [email protected], pages 975--986. Austrian Computer Society, 2005.Google ScholarGoogle Scholar
  8. J. Challenger, P. Dantzig, and A. Iyengar. A scalable system for consistently caching dynamic web data. In Proceedings of the 18th Annual Joint Conference of the IEEE Computer and Communications Societies, New York, New York, 1999.Google ScholarGoogle ScholarCross RefCross Ref
  9. J. Challenger, P. Dantzig, A. Iyengar, and K. Witting. A fragment-based approach for efficiently creating dynamic web content. ACM Trans. Internet Techn., 5(2):359--389, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. B. Chandramouli, J. Xie, and J. Yang. On the database/network interface in large-scale publish/subscribe systems. In Proc. ACM SIGMOD International Conference on Management of Data, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. L. Gao, M. Dahlin, A. Nayate, J. Zheng, and A. Iyengar. Improving availability and performance with application-specific data replication. IEEE Transactions on Knowlege and Data Engineering, 17(1):106--120, Jan 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  12. C. Garrod, A. Manjhi, A. Ailamaki, P. Gibbons, B. M. Maggs, T. Mowry, C. Olston, and A. Tomasic. Scalable consistency management for web database caches. Technical Report CMU-CS-06-128, Carnegie Mellon University, July 2006.Google ScholarGoogle Scholar
  13. T. Groothuyse, S. Sivasubramanian, and G. Pierre. Globetp: template-based database replication for scalable web applications. In Carey L. Williamson, Mary Ellen Zurko, Peter F. Patel-Schneider, and Prashant J. Shenoy, editors, Proc. International Conference on the World Wide Web, pages 301--310. ACM, 2007. Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. S. Iyer, A. Rowstron, and P. Druschel. Squirrel: A decentralized peer-to-peer web cache. In Proc. 21st ACM SIGACT-SIGOPS Principles of Distributed Commuting, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. A. Y. Levy and Y. Sagiv. Queries independent of updates. In Proc. International Conference on Very Large Data Bases, 1993. Google ScholarGoogle ScholarDigital LibraryDigital Library
  16. W. Li, O. Po, W. Hsiung, K. S. Candan, D Agrawal, Y. Akca, and K Taniguchi. CachePortal II: Acceleration of very large scale data center-hosted database-driven web applications. In Proc. International Conference on Very Large Data Bases, 2003. Google ScholarGoogle ScholarDigital LibraryDigital Library
  17. Q. Luo, S. Krishnamurthy, C. Mohan, H. Pirahesh, H. Woo, B. G. Lindsay, and J. F. Naughton. Middle-tier database caching for e-business. In Proc. ACM SIGMOD International Conference on Management of Data, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. A. Manjhi, A. Ailamaki, B. M. Maggs, T. C. Mowry, C. Olston, and A. Tomasic. Simultaneous scalability and security for data-intensive web applications. In Proc. ACM SIGMOD International Conference on Management of Data, 2006. Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. A. Manjhi, P. B. Gibbons, A. Ailamaki, C. Garrod, B. M. Maggs, T. C. Mowry, C. Olston, A. Tomasic, and H. Yu. Invalidation clues for database scalability services. In Proc. International Conference on Data Engineering, 2007.Google ScholarGoogle ScholarCross RefCross Ref
  20. Object Web Consortium. C-JDBC: Flexible database clustering middleware. http://c-jdbc.objectweb.org/.Google ScholarGoogle Scholar
  21. Object Web Consortium. Rice University bidding system. http://rubis.objectweb.org/.Google ScholarGoogle Scholar
  22. C. Olston, A. Manjhi, C. Garrod, A. Ailamaki, B. Maggs, and T. Mowry. A scalability service for dynamic web applications. In Proc. Conference on Innovative Data Systems Research (CIDR), 2005.Google ScholarGoogle Scholar
  23. C. G. Plaxton, R. Rajaraman, and A. W. Richa. Accessing nearby copies of replicated objects in a distributed environment. Theory of Computing Systems, 32:241--280, 1999.Google ScholarGoogle ScholarCross RefCross Ref
  24. A. Rowstron and P. Druschel. Pastry: Scalable, distributed object location and routing for large-scale peer-to-peer systems. In Proc. IFIP/ACM International Conference on Distributed Systems Platforms (Middleware), Heidelberg, Germany, November 2001. Google ScholarGoogle ScholarDigital LibraryDigital Library
  25. S. Sivasubramanian, G. Alonso, G. Pierre, and M. van Steen. GlobeDB: Autonomic data replication for web applications. In Proc. International Conference on the World Wide Web, 2005. Google ScholarGoogle ScholarDigital LibraryDigital Library
  26. Transaction Processing Council. TPC-W specification ver. 1.7. http://www.tpc.org/tpcw/.Google ScholarGoogle Scholar
  27. B. White, J. Lepreau, L. Stoller, R. Ricci, S. Guruprasad, M. Newbold, M. Hibler, C. Barb, and A. Joglekar. An integrated experimental environment for distributed systems and networks. In Proc. Symposium on Operating Systems Design and Implementation, 2002. Google ScholarGoogle ScholarDigital LibraryDigital Library

Index Terms

  1. Scalable query result caching for web applications

                Recommendations

                Comments

                Login options

                Check if you have access through your login credentials or your institution to get full access on this article.

                Sign in

                Full Access

                PDF Format

                View or Download as a PDF file.

                PDF

                eReader

                View online with eReader.

                eReader