OLAP Query Routing and Physical Design in a Database Cluster

  • Uwe Röhm
  • Klemens Böhm
  • Hans-Jörg Schek
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 1777)


This article quantifies the benefit from simple data organization schemes and elementary query routing techniques for the PowerDB engine, a system that coordinates a cluster of databases. We report on evaluations for a specific scenario: the workload contains OLAP queries, OLTP queries, and simple updates, borrowed from the TPC-R benchmark. We investigate affinity of OLAP queries and different routing strategies for such queries. We then compare two simple data placement schemes, namely full replication and a hybrid one combining partial replication with partitioning. We run different experiments with queries only, with updates only, and with queries concurrently to simple updates. It turns out that hybrid is superior to full replication, even without updates. Our overall conclusion is that coordinator-based routing has good scaleup properties for scenarios with complex analysis queries.


Execution Plan Physical Design Query Performance Hybrid Design Concurrent Execution 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    C.K. Baru, et al. Dbs2 parallel edition. IBM Systems Journal, 34(2), 1995.Google Scholar
  2. 2.
    Michael J. Carey, Miron Livny, and Hongjun Lu. Dynamic task allocation in a distributed database system. In Proceedings of the 5th IEEE Int. Conf. on Distributed Computing Systems (ICDCS), Denver, Colorado, May 1985.Google Scholar
  3. 3.
    D. Ferguson, et al. Satisfying response time goals in transaction processing systems. In Proceedings of the 2nd Int. Conf. on Parallel and Distributed Information Systems, San Diego, 1993.Google Scholar
  4. 4.
    T. Grabs, K. Böhm, and H.-J. Schek. A document engine on a db cluster. High Performance Transaction Systems Workshop (HPTS), Sept. 1999.Google Scholar
  5. 5.
    S. Ghandeharizadeh, D.J. DeWitt, and W. Qureshi. A performance analysis of alternative multi-attribute declustering strategies. In Proceedings of the 1992 ACM SIGMOD Conference, San Diego, California, pages 29–38, 1992.Google Scholar
  6. 6.
    H.V. Jagadish, L.V. Lakshmanan, and D. Srivastava. Snakes and sandwiches: Optimal clustering strategies or a warehouse. In Proceedings of the 1999 ACM SIGMOD Conference, Philadelphia, pages 37–48, June 1999.Google Scholar
  7. 7.
    H. Kaufmann and H.-J. Schek. Extending tp-monitors for intra-transaction parallelism. In Proceedings of PDIS’96, Miami, December 1996.Google Scholar
  8. 8.
    M. Mehta and D.J. DeWitt. Data placement in shared-nothing parallel database systems. VLDB Journal, 6(1):53–721, 1997.CrossRefGoogle Scholar
  9. 9.
    Axel Moenkeberg and Gerhard Weikum. Conflict-driven load control for the avoidance of data-contention trashing. In Proceedings of the 7th IEEE Int. Conf. on Data Engineering (ICDE), Kobe, Japan, pages 632–639, 1991.Google Scholar
  10. 10.
    Oracle Corporation. Oracle8 Server Concepts, Release 8.0, Chapter 5, 1997.Google Scholar
  11. 11.
    M. T. özsu and P. Valduriez. Principles of Distributed Database Systems, chapter 7–9. Prentice Hall, 1991.Google Scholar
  12. 12.
    Erhard Rahm. A framework for workload allocation in distributed transaction processing systems. Systems Software Journal, 18:171–190, 1992.CrossRefGoogle Scholar
  13. 13.
    U. Röhm and K. Böhm. Working together in harmony — an implementation of the corba object query service and its evaluation. In Proc. of the 15th IEEE Int. Conf. on Data Engineering, Sydney, Australia, March 1999.Google Scholar
  14. 14.
    M. Rys, M. C. Norrie, and H.-J. Schek. Intra-transaction parallelism in the mapping of an object model to a relational multi-processor system. In Proc. of the 22nd Int. Conf. on Very Large Databases, Mumbai, India, 1996.Google Scholar
  15. 15.
    A. Thomasian. A performance study of dynamic load balancing in distributed systems. In Proceedings of the 7th IEEE Int. Conf. on Distributed Computing Systems (ICDCS), Berlin, Germany, 1987.Google Scholar
  16. 16.
    Transaction Processing Performance Council. Tpc-r benchmark specification rev. 1.0.1. Technical report, July 1999.Google Scholar
  17. 17.
    P. S. Yu, et al. Analysis of affinity based routing in multi-system data sharing. Performance Evaluation, 7:87–109, 1987.CrossRefGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2000

Authors and Affiliations

  • Uwe Röhm
    • 1
  • Klemens Böhm
    • 1
  • Hans-Jörg Schek
    • 1
  1. 1.Database Research Group, Institute of Information SystemsETH ZentrumZurichSwitzerland

Personalised recommendations