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Query Evaluation Techniques for Large Databases.

Goetz Graefe: Query Evaluation Techniques for Large Databases. ACM Comput. Surv. 25(2): 73-170(1993)
@article{DBLP:journals/csur/Graefe93,
  author    = {Goetz Graefe},
  title     = {Query Evaluation Techniques for Large Databases},
  journal   = {ACM Comput. Surv.},
  volume    = {25},
  number    = {2},
  year      = {1993},
  pages     = {73-170},
  ee        = {http://doi.acm.org/10.1145/152610.152611},
  bibsource = {DBLP, http://dblp.uni-trier.de}
}

Abstract

Database management systems will continue to manage large data volumes. Thus, efficient algorithms for accessing and manipulating large sets and sequences will be required to provide acceptable performance. The advent of object-oriented and extensible database systems will not solve this problem. On the contrary, modern data models exacerbate the problem: In order to manipulate large sets of complex objects as efficiently as today's database systems manipulate simple records, query-processing algorithms and software will become more complex, and a solid understanding of algorithm and architectural issues is essential for the designer of database management software.

This survey provides a foundation for the design and implementation of query execution facilities in new database management systems. It describes a wide array of practical query evaluation techniques for both relational and postrelational database systems, including iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, types of parallel query execution and their implementation, and special operators for emerging database application domains.

Copyright © 1993 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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