Parallelizing query optimization

Many commercial RDBMSs employ cost-based query optimization exploiting dynamic programming (DP) to efficiently generate the optimal query execution plan. However, optimization time increases rapidly for queries joining more than 10 tables. Randomized or heuristic search algorithms reduce query optimization time for large join queries by considering fewer plans, sacrificing plan optimality. Though commercial systems executing query plans in parallel have existed for over a decade, the optimization of such plans still occurs serially. While modern microprocessors employ multiple cores to accelerate computations, parallelizing query optimization to exploit multi-core parallelism is not as straightforward as it may seem. The DP used in join enumeration belongs to the challenging nonserial polyadic DP class because of its non-uniform data dependencies. In this paper, we propose a comprehensive and practical solution for parallelizing query optimization in the multi-core processor architect...

• Type: Journal
• Year: 2008
• Where: PVLDB
• Authors: Wook-Shin Han, Wooseong Kwak, Jinsoo Lee, Guy M. Lohman, Volker Markl
• Keywords: Cost-based Query Optimization, Optimization Time, PVLDB 2008, Query Optimization