Skip to main content

Characterizing Database User’s Access Patterns

  • Conference paper
Database and Expert Systems Applications (DEXA 2004)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 3180))

Included in the following conference series:

Abstract

Much work has been done on characterizing the workload of a database system. Previous studies focused on providing different types of statistical summaries, and modeling the run-time behavior on the physical resource level. In this paper, we focus on characterizing the database system’s workload from the view of database users. We use user access patterns to describe how a client application or a group of users accesses the data of a database system. The user access patterns include a set of user access events that represent the format of the queries and a set of user access graphs that represent the query execution orders. User access patterns can help database administrators tune the system, help database users optimize queries, and help to predict and cache future queries. In this paper, we present several approaches to using user access patterns to improve system performance, and report some experimental results.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 84.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Bezenek, T., Cain, H., Dickson, R., Heil, T., Martin, M., Mc-Curdy, C., Rajwar, R., Weglarz, E., Zilles, C., Lipasti, M.: Characterizing a Java implementation of TPC-W. In: Third CAECW Workshop (2000)

    Google Scholar 

  2. Calzarossa, M., Serazzi, G.: Workload characterization: A survey. Proc. IEEE 81(8), 1136–1150 (1993)

    Article  Google Scholar 

  3. Chaudhuri, S., Ganesan, P., Narasayya, V.: Primitives for workload summarization and implications for SQL. In: VLDB 2003, pp. 730–741. Morgan Kaufmann, San Francisco (2003)

    Chapter  Google Scholar 

  4. Dan, A., Yu, P.S., Chung, J.-Y.: Database access characterization for buffer hit prediction. In: Proc. of the Ninth ICDE 1993, pp. 134–143. IEEE Computer Society, Los Alamitos (1993)

    Google Scholar 

  5. Dan, A., Yu, P.S., Chung, J.-Y.: Characterization of database access pattern for analytic prediction of buffer hit probability. VLDB Journal 4(1), 127–154 (1995)

    Article  Google Scholar 

  6. Hsu, W.W., Smith, A.J., Young, H.C.: Characteristics of production database workloads and the TPC benchmarks. IBM Systems Journal 40(3) (2001)

    Google Scholar 

  7. Klaassen, O.: Modeling data base reference behavior. In: Computer Performance Evaluation: Modelling Techniques and Tools, p. 47. North Holland, Amsterdam (1992)

    Google Scholar 

  8. Luo, Q., Naughton, J.F.: Form-based proxy caching for database-backed web sites. In: Proceedings of VLDB 2001, pp. 191–200 (2001)

    Google Scholar 

  9. Nikolaou, C., Labrinidis, A., Bohn, V., Ferguson, D., Artavanis, M., Kloukinas, C., Marazakis, M.: The impact of workload clustering on transaction routing. Technical Report TR98-0238 (1998)

    Google Scholar 

  10. Sapia, C.: PROMISE: predicting query behavior to enable predictive caching strategies for OLAP systems. In: Kambayashi, Y., Mohania, M., Tjoa, A.M. (eds.) DaWaK 2000. LNCS, vol. 1874, pp. 224–233. Springer, Heidelberg (2000)

    Chapter  Google Scholar 

  11. Transaction Processing Performance Council (TPC). TPC Benchmark-W (Web Commerce) - standard specification revision 1.6 (February 2002)

    Google Scholar 

  12. Smith, W.D.: Intel Corporation. TPC-W: Benchmarking an ecommerce solution (February 2000)

    Google Scholar 

  13. Yao, Q., An, A.: SQL-Relay: An event-driven rule-based database (demonstration). In: International Conference on Web-Age Information Management (2003)

    Google Scholar 

  14. Yao, Q., An, A.: Using user access patterns for semantic query caching. In: Database and Expert Systems Applications (2003)

    Google Scholar 

  15. Yu, P.S., Chen, M.-S., Heiss, H.-U., Lee, S.: On workload characterization of relational database environments. Software Engineering 18(4), 347–355 (1992)

    Article  Google Scholar 

  16. Yu, P.S., Dan, A.: Performance analysis of affinity clustering on transaction processing coupling architecture. IEEE TKDE 6(5), 764–786 (1994)

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2004 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Yao, Q., An, A. (2004). Characterizing Database User’s Access Patterns. In: Galindo, F., Takizawa, M., Traunmüller, R. (eds) Database and Expert Systems Applications. DEXA 2004. Lecture Notes in Computer Science, vol 3180. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-30075-5_51

Download citation

  • DOI: https://doi.org/10.1007/978-3-540-30075-5_51

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-22936-0

  • Online ISBN: 978-3-540-30075-5

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics