Query evaluation techniques for large databases

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Abstract
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Graefe, Goetz. “Query Evaluation Techniques for Large Databases”. ACM Computing Surveys, vol. 25, no. 2, 1993, pp. 73-169, https://doi.org/10.1145/152610.152611.
Graefe, G. (1993). Query evaluation techniques for large databases. ACM Computing Surveys, 25(2), 73-169. https://doi.org/10.1145/152610.152611
Graefe G. Query evaluation techniques for large databases. ACM Computing Surveys. 1993;25(2):73-169.
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Description

Concerned about database performance with ever-increasing data volumes? This survey provides a comprehensive foundation for designing and implementing efficient query execution facilities in modern database management systems. The paper addresses the challenge of accessing and manipulating large datasets effectively, particularly in the context of object-oriented and extensible databases. This report equips database designers with the knowledge needed to optimize query processing for next-generation database systems. The author reviews a wide array of practical query evaluation techniques relevant to both relational and postrelational systems. Topics include iterative execution of complex query evaluation plans, the duality of sort- and hash-based set-matching algorithms, and types of parallel query execution and their implementation. The study also covers special operators designed for emerging database application domains. This survey serves as a valuable resource for database professionals seeking to improve the performance of their systems. This work provides a solid understanding of algorithm and architectural issues essential for designing database management software that can handle large data volumes efficiently.

Published in ACM Computing Surveys, this article is highly relevant to the journal's focus on providing in-depth surveys of computer science topics. ACM Computing Surveys offers comprehensive overviews of key areas in computing. By presenting a wide range of query evaluation techniques, this paper aligns with the journal's mission of providing foundational knowledge to computer science researchers and practitioners.

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Citations Analysis
The first research to cite this article was titled Encapsulation of parallelism and architecture-independence in extensible database query execution and was published in 1993. The most recent citation comes from a 2024 study titled Encapsulation of parallelism and architecture-independence in extensible database query execution . This article reached its peak citation in 2011 , with 17 citations.It has been cited in 81 different journals, 8% of which are open access. Among related journals, the ACM SIGMOD Record cited this research the most, with 31 citations. The chart below illustrates the annual citation trends for this article.
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