Horizontal Data Partitioning in Database Design.

@inproceedings{DBLP:conf/sigmod/CeriNP82,
  author    = {Stefano Ceri and
               Mauro Negri and
               Giuseppe Pelagatti},
  editor    = {Mario Schkolnick},
  title     = {Horizontal Data Partitioning in Database Design},
  booktitle = {Proceedings of the 1982 ACM SIGMOD International Conference on
               Management of Data, Orlando, Florida, June 2-4, 1982},
  publisher = {ACM Press},
  year      = {1982},
  pages     = {128-136},
  ee        = {http://doi.acm.org/10.1145/582353.582376, db/conf/sigmod/CeriNP82.html},
  crossref  = {DBLP:conf/sigmod/82},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

In this paper the problem of horizontally partitioning data on a set of resources is considered.

The main optimization parameter is the number of accesses performed by the application programs to different portions of data. The concepts which are required for the determination of relevant portions of data are defined and a methodology for determining the access parameters is proposed.

The formulation of the general partitioning problem in 3 specific application enviroments is shown: distributed database design, file partitioning on a primary and a secondary memory and data distribution on different devices.

It is shown that the analytical models of these specific applications use the parameters of the general formulation.

Copyright © 1982 by the ACM, Inc., used by permission. Permission to make digital or hard copies is granted provided that copies are not made or distributed for profit or direct commercial advantage, and that copies show this notice on the first page or initial screen of a display along with the full citation.

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Referenced by

1. Ladjel Bellatreche, Kamalakar Karlapalem, Qing Li: Derived Horizontal Class Partitioning in OODBs: Design Strategies, Analytical Model and Evaluation. ER 1998: 465-479
2. John F. Roddick, Noel G. Craske, Thomas J. Richards: Handling Discovered Structure in Database Systems. IEEE Trans. Knowl. Data Eng. 8(2): 227-240(1996)
3. Sakti Pramanik, Sungwon Jung: Description and Identification of Distributed Fragments of Recursive Relations. IEEE Trans. Knowl. Data Eng. 8(6): 1002-1016(1996)
4. Wei Sun, Mark Allen Weiss: An Improved Algorithm for Implication Testing Involving Arithmetic Inequalities. IEEE Trans. Knowl. Data Eng. 6(6): 997-1001(1994)
5. Minyoung Ra, Y.-S. Park: Data Fragmentation and Allocation for PC-Based Distributed Database Design. DASFAA 1993: 90-96
6. Sakti Pramanik, David T. Kao, David Vineyard: Fragmentation of Recursive Relations in Distributed Datbases. EDBT 1992: 389-404
7. Xian-He Sun, Nabil Kamel, Lionel M. Ni: Solving Implication Problems in Database Applications. SIGMOD Conference 1989: 185-192
8. Peter M. G. Apers: Data Allocation in Distributed Database Systems. ACM Trans. Database Syst. 13(3): 263-304(1988)
9. Domenico Saccà, Gio Wiederhold: Database Partitioning in a Cluster of Processors. ACM Trans. Database Syst. 10(1): 29-56(1985)
10. Shamkant B. Navathe, Stefano Ceri, Gio Wiederhold, Jinglie Dou: Vertical Partitioning Algorithms for Database Design. ACM Trans. Database Syst. 9(4): 680-710(1984)
11. Elisa Bertino: Distributed Database Design Using the Entity-Relationship Model. ER 1983: 189-203