Query Optimization in Parallel Database Systems
Query optimization in Parallel database with parallel join technique considering skewing and load balancing
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In this book, we simulated a parallel database and developed a partition join where both skew effects and load balancing techniques were adopted. A parallel database system seeks to improve performance through parallelization of various operations, such as loading data, building indexes and evaluating queries. Although data may be stored in a distributed fashion, the distribution is governed solely by performance considerations. Parallel databases improve processing and input/output speeds by using multiple CPUs and disks in parallel. Centralized and client-server database systems are not powe...
In this book, we simulated a parallel database and developed a partition join where both skew effects and load balancing techniques were adopted. A parallel database system seeks to improve performance through parallelization of various operations, such as loading data, building indexes and evaluating queries. Although data may be stored in a distributed fashion, the distribution is governed solely by performance considerations. Parallel databases improve processing and input/output speeds by using multiple CPUs and disks in parallel. Centralized and client-server database systems are not powerful enough to handle such applications. In parallel processing, many operations are performed simultaneously, as opposed to serial processing, in which the computational steps are performed sequentially. In this work, a novel approach for parallel join was simulated in a parallel environment in addition to other join techniques in a database system. Different load balancing techniques are also discussed with their advantages and disadvantages. An extensive experimental result is also noted with proper graphical representation.
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