ACM SIGMOD Anthology VLDB dblp.uni-trier.de

Cache Conscious Indexing for Decision-Support in Main Memory.

Jun Rao, Kenneth A. Ross: Cache Conscious Indexing for Decision-Support in Main Memory. VLDB 1999: 78-89
@inproceedings{DBLP:conf/vldb/RaoR99,
  author    = {Jun Rao and
               Kenneth A. Ross},
  editor    = {Malcolm P. Atkinson and
               Maria E. Orlowska and
               Patrick Valduriez and
               Stanley B. Zdonik and
               Michael L. Brodie},
  title     = {Cache Conscious Indexing for Decision-Support in Main Memory},
  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     = {78-89},
  ee        = {db/conf/vldb/RaoR99.html},
  crossref  = {DBLP:conf/vldb/99},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

We study indexing techniques for main memory, including hash indexes, binary search trees, T-trees, B+-trees, interpolation search, and binary search on arrays. In a decision-support context, our primary concerns are the lookup time, and the space occupied by the index structure.

Our goal is to provide faster lookup times than binary search by paying attention to reference locality and cache behavior, with- out using substantial extra space. We propose a new indexing technique called ``Cache-Sensitive Search Trees'' (CSS-trees). Our technique stores a directory structure on top of a sorted array. Nodes in this directory have size matching the cache-line size of the machine. We store the directory in an array and do not store internal-node pointers; child nodes can be found by performing arithmetic on array o sets.

We compare the algorithms based on their time and space requirements. We have implemented all of the techniques, and present a performance study on two popular modern machines. We demonstrate that with a small space overhead, we can reduce the cost of binary search on the array by more than a factor of two. We also show that our technique dominates B+-trees, T-trees, and binary search trees in terms of both space and time. A cache simulation verifies that the gap is due largely to cache misses.

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

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Referenced by

  1. Jun Rao, Kenneth A. Ross: Making B+-Trees Cache Conscious in Main Memory. SIGMOD Conference 2000: 475-486
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