Efficient Massively Parallel Join Optimization for Large Queries
Riccardo Mancini, Srinivas Karthik, Bikash Chandra, Vasilis Mageirakos, Anastasia Ailamaki
2022Proceedings of the 2022 International Conference on Management of Data19 citationsDOIOpen Access PDF
Abstract
Modern data analytical workloads often need to run queries over a large number of tables. An optimal query plan for such queries is crucial for being able to run these queries within acceptable time bounds. However, with queries involving many tables, finding the optimal join order becomes a bottleneck in query optimization. Due to the exponential nature of join order optimization, optimizers resort to heuristic solutions after a threshold number of tables. Our objective is two fold: (a) reduce the optimization time for generating optimal plans; and (b) improve the quality of the heuristic solution.
Topics & Concepts
Computer scienceBottleneckJoin (topology)Query optimizationHeuristicQuery planMassively parallelTheoretical computer scienceMathematical optimizationParallel computingSargableData miningInformation retrievalMathematicsWeb search querySearch engineArtificial intelligenceEmbedded systemCombinatoricsData Management and AlgorithmsAdvanced Database Systems and QueriesGraph Theory and Algorithms