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Generating efficient safe query plans for probabilistic databases
Authors:Biao   Yuni   
Affiliation:aDepartment of Computer Science, Renmin University of China, Beijing 100872, PR China;bKey Laboratory of Data Engineering and Knowledge Engineering, Ministry of Education, Beijing 100872, PR China;cDepartment of Computer and Information Science, Indiana University–Purdue University, Indianapolis 46202, United States
Abstract:Managing uncertain information using probabilistic databases has drawn much attention recently in many fields. Generating efficient safe plans is the key to evaluating queries whose data complexities are PTIME. In this paper, we propose a new approach generating efficient safe plans for queries. Our algorithm adopts effective preprocessing and multiway split techniques, thus the generating safe plans avoid unnecessary probabilistic cartesian-products and have the minimum number of probabilistic projections. Further, we extend existing transformation rules to allow the safe plans generated by the Safe-Plan algorithm [N. Dalvi, D. Suciu, Efficient query evaluation on probabilistic database, The VLDB Journal 16 (4) (2007) 523–544] and the proposed algorithm to be transformed by each other. Applying our approach through the TPC-H benchmark queries, the experiments show that the safe plans generated by our algorithm are more efficient than those generated by the Safe-Plan algorithm.
Keywords:Probabilistic databases   Safe plan   Query evaluation
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