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The Value of Merge-Join and Hash-Join in SQL Server.

Goetz Graefe: The Value of Merge-Join and Hash-Join in SQL Server. VLDB 1999: 250-253
@inproceedings{DBLP:conf/vldb/Graefe99,
  author    = {Goetz Graefe},
  editor    = {Malcolm P. Atkinson and
               Maria E. Orlowska and
               Patrick Valduriez and
               Stanley B. Zdonik and
               Michael L. Brodie},
  title     = {The Value of Merge-Join and Hash-Join in SQL Server},
  booktitle = {VLDB'99, Proceedings of 25th International Conference on Very
               Large Data Bases, September 7-10, 1999, Edinburgh, Scotland,
               UK},
  publisher = {Morgan Kaufmann},
  year      = {1999},
  isbn      = {1-55860-615-7},
  pages     = {250-253},
  ee        = {db/conf/vldb/Graefe99.html},
  crossref  = {DBLP:conf/vldb/99},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Microsoft SQL Server was successful for many years for transaction processing and decision support workloads with neither merge join nor hash join, relying entirely on nested loops and index nested loops join. How much difference do additional join algorithms really make, and how much system performance do they actually add? In a pure OLTP workload that requires only record-to-record navigation, intuition agrees that index nested loops join is sufficient. For a DSS workload, however, the question is much more complex. To answer this question, we have analyzed TPC-D query performance using an internal build of SQL Server with merge-join and hash-join enabled and disabled. It shows that merge join and hash join are both required to achieve the best performance for decision support workloads.

Copyright © 1999 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

Malcolm P. Atkinson, Maria E. Orlowska, Patrick Valduriez, Stanley B. Zdonik, Michael L. Brodie (Eds.): VLDB'99, Proceedings of 25th International Conference on Very Large Data Bases, September 7-10, 1999, Edinburgh, Scotland, UK. Morgan Kaufmann 1999, ISBN 1-55860-615-7
Contents BibTeX

References

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Referenced by

  1. Surajit Chaudhuri, Gerhard Weikum: Rethinking Database System Architecture: Towards a Self-Tuning RISC-Style Database System. VLDB 2000: 1-10
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