Skew characteristics and their effects on parallel relational query processing

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Liu, Kevin H (1997) Skew characteristics and their effects on parallel relational query processing. Research Master thesis, Victoria University of Technology.

Abstract

As queries grow increasingly complex and large data sets are becoming prevalent, Parallel Query Processing, database sizes grow dramatically particularly in Decision Support Systems (DSS) , and OnLine Analytic Processing Systems ( OIAP) which have recently emerged as important database applications. In these systems, performance is a critical issue and speeding up the system has always been an objective but the processing power of individual processors can only handle a small fraction of current applications. As a result, parallel processing is exploited to improve database systems performance. In the thesis we focus on relational database systems and study skew characteristics and their effects on parallel query processing.

Item type Thesis (Research Master thesis)
URI https://vuir.vu.edu.au/id/eprint/30101
Subjects Historical > FOR Classification > 0806 Information Systems
Current > Division/Research > Other
Keywords parallel processing, skew prediction, hash partitioning, data skew, skew taxonomy, parallel processing, aggregate functions, terabyte database simulation model, intra-query processing allocation, parallel systems, performance, optimal processor allocation, parallel query execution
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