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Design and Analysis of a Relational Join Operation for VLSI.

M. J. Menon, David K. Hsiao: Design and Analysis of a Relational Join Operation for VLSI. VLDB 1981: 44-55
@inproceedings{DBLP:conf/vldb/MenonH81,
  author    = {M. J. Menon and
               David K. Hsiao},
  title     = {Design and Analysis of a Relational Join Operation for VLSI},
  booktitle = {Very Large Data Bases, 7th International Conference, September
               9-11, 1981, Cannes, France, Proceedings},
  publisher = {IEEE Computer Society},
  year      = {1981},
  pages     = {44-55},
  ee        = {db/conf/vldb/MenonH81.html},
  crossref  = {DBLP:conf/vldb/81},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}
BibTeX

Abstract

In this paper, we will first prqpase a new organization of processors and memories for hardware realization of the relational join operation. Algorithmic analysis of the time complexity of the join operation shows that it is linear in the cardinalities of the source, target and result relations which is optimal.

Queueing analysis of the join operation is also used to arrive at closed-form equations for various design parameters such as the sizes of the memories associated with the processors. It is seen that in order to perform joins at a rate commensurate with the output rate of relational tuples, the memories associated with the processors in the hardware must satisfy certain constraints of speed and size. The various constraints and their order of importance are clearly indicated.

We also show how to select an optimum chip design for the join operation, where the design is considered optimal if it gives the best performance for a certain fixed cost. This method may be employed by database machine designers in order to arrive at the optimal values for

(1) the number of processors on a chip, and
(2) the sizes of the memories to be placed on a chip.

Due to the length of the paper, it is not possible to describe the extensions of this method to perform inequality joins and m-way joins. We also exclude a favorable comparison of this method with other schemes proposed for some other database machines. However, the reader may obtain detailed expositions on the extensions and comparative study in the References9.

Copyright © 1981 by The Institute of Electrical and Electronic Engineers, Inc. (IEEE). Abstract used with permission.


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Very Large Data Bases, 7th International Conference, September 9-11, 1981, Cannes, France, Proceedings. IEEE Computer Society 1981
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References

[1]
E. F. Codd: A Relational Model of Data for Large Shared Data Banks. Commun. ACM 13(6): 377-387(1970) BibTeX
[2]
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[3]
Edward Babb: Implementing a Relational Database by Means of Specialized Hardware. ACM Trans. Database Syst. 4(1): 1-29(1979) BibTeX
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Referenced by

  1. Masaru Kitsuregawa, Miyuki Nakano, Lilian Harada, Mikio Takagi: Functional Disk System for Relational Database. ICDE 1987: 88-95
  2. Sakti Pramanik, David Ittner: Use of Graph-Theoretic Models for Optimal Relational Database Accesses to Perform Join. ACM Trans. Database Syst. 10(1): 57-74(1985)
  3. Marian S. Furman: An Efficient Implementation of a Relational Data Base. VLDB 1985: 181-191
  4. Matthias Jarke, Jürgen Koch: Query Optimization in Database Systems. ACM Comput. Surv. 16(2): 111-152(1984)
  5. T. Nakayama, Masahito Hirakawa, Tadao Ichikawa: Architecture and Algorithm for Parallel Execution of a Join Operation. ICDE 1984: 160-166
  6. Yang-Chang Hong: A Pipeline and Parallel Architecture for Supporting Database Management Systems. ICDE 1984: 152-159
  7. Paula B. Hawthorn: Microprocessor Assisted Tuple Access, Decompression and Assembly for Statistical Database Systems. VLDB 1982: 223-233
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