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Optimization of Multi-Join Queries in shared-nothing systems

Journal of Computer Science & Technology 1995年第2期10卷 149-162页

作者： Kian-Lee Tan(Department of Information systems and Computer Science, National University ofSingapore, Lower Kent Ridge Road, Singapore 0511) Department of Information systems and Computer Science National University of Singapore Singapore

This paper proposes a semi-greedy framework for optimizing multi-joinqueries in shared-nothing systems. The plan generated by the framework com-prises several pipelines, each performing several joins. The framework deter-mines the 'optimal' number of joins to be performed in each pipeline. Thedecisions are made based on the cost estimation of the entire processing *** ekisting optimization algorithms are extended under the framework. Ananalytical model is presented and used to compare the quality of plans producedby each optimization algorithm. Our study shows that the new algorithms out-perform their counterparts that are not extended.

关键词： Multi-join optimization shared-nothing systems pipelining,hash join segmented right-deep tree

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Graph algorithms: parallelization and scalability

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Science China(Information Sciences) 2020年第10期63卷 234-254页

作者： Wenfei FAN Kun HE Qian LI Yue WANG School of Informatics University of Edinburgh Shenzhen Institute of Computing Sciences Shenzhen University Beijing Advanced Innovation Center for Big Data and Brain Computing Beihang University Guangdong Province Key Laboratory of Popular High Performance Computers Shenzhen University

For computations on large-scale graphs, one often resorts to parallel algorithms. However, parallel algorithms are difficult to write, debug and analyze. Worse still, it is difficult to make algorithms parallelly scalable, such that the more machines are used, the faster the algorithms run. Indeed, it is not yet known whether any PTIME computational problems admit parallelly scalable algorithms on shared-nothing *** it possible to parallelize sequential graph algorithms and guarantee convergence at the correct results as long as the sequential algorithms are correct? Moreover, does a PTIME parallelly scalable problem exist on shared-nothing systems? This position paper answers both questions in the affirmative.

关键词： parallelization parallel scalability mathsf PTIMExspace problems graph algorithms shared-nothing systems

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