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Incremental Organization for Data Recording and Warehousing.

H. V. Jagadish, P. P. S. Narayan, S. Seshadri, S. Sudarshan, Rama Kanneganti: Incremental Organization for Data Recording and Warehousing. VLDB 1997: 16-25
@inproceedings{DBLP:conf/vldb/JagadishNSSK97,
  author    = {H. V. Jagadish and
               P. P. S. Narayan and
               S. Seshadri and
               S. Sudarshan and
               Rama Kanneganti},
  editor    = {Matthias Jarke and
               Michael J. Carey and
               Klaus R. Dittrich and
               Frederick H. Lochovsky and
               Pericles Loucopoulos and
               Manfred A. Jeusfeld},
  title     = {Incremental Organization for Data Recording and Warehousing},
  booktitle = {VLDB'97, Proceedings of 23rd International Conference on Very
               Large Data Bases, August 25-29, 1997, Athens, Greece},
  publisher = {Morgan Kaufmann},
  year      = {1997},
  isbn      = {1-55860-470-7},
  pages     = {16-25},
  ee        = {db/conf/vldb/JagadishNSSK97.html},
  crossref  = {DBLP:conf/vldb/97},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

Data warehouses and recording systems typically have a large continuous stream of incoming data, that must be stored in a manner suitable for future access. Access to stored records is usually based on a key. Organizing the data on disk as the data arrives using standard techniques would result in either (a) one or more I/Os to store each incoming record (to keep the data clustered by the key), which is too expensive when data arrival rates are very high, or (b) many I/Os to locate records for a particular customer (if data is stored clustered by arrival order).

We study two techniques, inspired by external sorting algorithms, to store data incrementally as it arrives, simultaneously providing good performance for recording and querying. We present concurrency control and recovery schemes for both techniques. We show the benefits of our techniques both analytically and experimentally.

Copyright © 1997 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

ACM SIGMOD Anthology

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Printed Edition

Matthias Jarke, Michael J. Carey, Klaus R. Dittrich, Frederick H. Lochovsky, Pericles Loucopoulos, Manfred A. Jeusfeld (Eds.): VLDB'97, Proceedings of 23rd International Conference on Very Large Data Bases, August 25-29, 1997, Athens, Greece. Morgan Kaufmann 1997, ISBN 1-55860-470-7
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Electronic Edition


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Referenced by

  1. Peter Muth, Patrick E. O'Neil, Achim Pick, Gerhard Weikum: The LHAM Log-Structured History Data Access Method. VLDB J. 8(3-4): 199-221(2000)
  2. H. V. Jagadish: Review - A Novel Index Supporting High Volume Data Warehouse Insertion. ACM SIGMOD Digital Review 1: (1999)
  3. Chris Jermaine, Anindya Datta, Edward Omiecinski: A Novel Index Supporting High Volume Data Warehouse Insertion. VLDB 1999: 235-246
  4. Peter Muth, Patrick E. O'Neil, Achim Pick, Gerhard Weikum: Design, Implementation, and Performance of the LHAM Log-Structured History Data Access Method. VLDB 1998: 452-463
BibTeX
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