ACM SIGMOD Anthology VLDB dblp.uni-trier.de

WATCHMAN : A Data Warehouse Intelligent Cache Manager.

Peter Scheuermann, Junho Shim, Radek Vingralek: WATCHMAN : A Data Warehouse Intelligent Cache Manager. VLDB 1996: 51-62
@inproceedings{DBLP:conf/vldb/ScheuermannSV96,
  author    = {Peter Scheuermann and
               Junho Shim and
               Radek Vingralek},
  editor    = {T. M. Vijayaraman and
               Alejandro P. Buchmann and
               C. Mohan and
               Nandlal L. Sarda},
  title     = {WATCHMAN : A Data Warehouse Intelligent Cache Manager},
  booktitle = {VLDB'96, Proceedings of 22th International Conference on Very
               Large Data Bases, September 3-6, 1996, Mumbai (Bombay), India},
  publisher = {Morgan Kaufmann},
  year      = {1996},
  isbn      = {1-55860-382-4},
  pages     = {51-62},
  ee        = {db/conf/vldb/ScheuermannSV96.html},
  crossref  = {DBLP:conf/vldb/96},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Data warehouses store large volumes of data that are being used frequently by decision support applications which involve complex queries. Since data warehouses are updated infrequently, it becomes desirable to cache not only query execution plans, but also the retrieved sets of queries. In this paper we report on the design of an intelligent cache manager for retrieved sets in a data warehousing environment, called WATCHMAN. Our cache manager employs two novel, complementary algorithms for cache replacement and for cache admission. WATCHMAN aims at minimizing query response time and its cache replacement policy swaps out entire retrieved sets of queries instead of individual pages. The cache replacement and admission algorithms make use of a profit metric, which considers for each retrieved set its average rate of reference, its size, and execution cost of the associated query. We report on a performance evaluation based on the TPC-D and Set Query benchmarks. These experiments show that WATCHMAN achieves a substantial performance improvement in decision support environment as compared to a traditional LRU replacement algorithm.

Copyright © 1996 by the VLDB Endowment. Permission to copy without fee all or part of this material is granted provided that the copies are not made or distributed for direct commercial advantage, the VLDB copyright notice and the title of the publication and its date appear, and notice is given that copying is by the permission of the Very Large Data Base Endowment. To copy otherwise, or to republish, requires a fee and/or special permission from the Endowment.


Online Paper

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Printed Edition

T. M. Vijayaraman, Alejandro P. Buchmann, C. Mohan, Nandlal L. Sarda (Eds.): VLDB'96, Proceedings of 22th International Conference on Very Large Data Bases, September 3-6, 1996, Mumbai (Bombay), India. Morgan Kaufmann 1996, ISBN 1-55860-382-4
Contents BibTeX

Electronic Edition

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Referenced by

  1. Olga Kapitskaia, Raymond T. Ng, Divesh Srivastava: Evolution and Revolutions in LDAP Directory Caches. EDBT 2000: 202-216
  2. Prasad Deshpande, Jeffrey F. Naughton: Aggregate Aware Caching for Multi-Dimensional Queries. EDBT 2000: 167-182
  3. Gerhard Weikum, Arnd Christian König, Achim Kraiss, Markus Sinnwell: Towards Self-Tuning Memory Management for Data Servers. IEEE Data Eng. Bull. 22(2): 3-11(1999)
  4. Yannis Kotidis, Nick Roussopoulos: DynaMat: A Dynamic View Management System for Data Warehouses. SIGMOD Conference 1999: 371-382
  5. H. V. Jagadish, Laks V. S. Lakshmanan, Divesh Srivastava: Snakes and Sandwiches: Optimal Clustering Strategies for a Data Warehouse. SIGMOD Conference 1999: 37-48
  6. Achim Kraiss, Gerhard Weikum: Integrated Document Caching and Prefetching in Storage Hierarchies Based on Markov-Chain Predictions. VLDB J. 7(3): 141-162(1998)
  7. Prasad Deshpande, Karthikeyan Ramasamy, Amit Shukla, Jeffrey F. Naughton: Caching Multidimensional Queries Using Chunks. SIGMOD Conference 1998: 259-270
  8. Dimitri Theodoratos, Timos K. Sellis: Data Warehouse Configuration. VLDB 1997: 126-135
  9. Achim Kraiss, Gerhard Weikum: Vertical Data Migration in Large Near-Line Document Archives Based on Markov-Chain Predictions. VLDB 1997: 246-255
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