Query evaluation techniques for large databases

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Query evaluation techniques for large databases (1993)

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by Goetz Graefe

Venue:	ACM COMPUTING SURVEYS
Citations:	766 - 11 self

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@ARTICLE{Graefe93queryevaluation,
    author = {Goetz Graefe},
    title = {Query evaluation techniques for large databases},
    journal = {ACM COMPUTING SURVEYS},
    year = {1993},
    volume = {25},
    pages = {73--170}
}

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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 it: 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 post-relational 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.

Keyphrases

evaluation technique large database large set wide array post-relational database system modern data model complex query evaluation plan database management system acceptable performance query execution facility iterative execution practical query evaluation technique simple record parallel query execution new database management system efficient algorithm database system special operator extensible database system hash-based set architectural issue complex object database application domain large data volume database management software solid understanding query processing algorithm

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