Name
Abstract | ||
|---|---|---|
Most contemporary database systems query optimizers exploit System-R's bottom-up dynamic programming method (DP) to find the optimal query execution plan (QEP) without evaluating redundant subplans. The distinguished exceptions are Volcano/Cascades using transforms to generate new plans according to a topdown approach. As recent research has revealed, bottom-up dynamic programming can improve performance with respect to the shape of the join graph and parallelism. However top-down join enumeration dynamic programming method can derive upper bounds for the costs of the plans it generates which is not available to typical bottom-up DP method. In this paper, we propose a comprehensive and practical framework for parallelizing top-down dynamic programming query optimization with complex non-inner join in the multi-core processor architecture, referred as PTDhyp. We have implemented such a search strategy and experimental results show that can improve optimization time effective compared to known existing algorithms. © 2011 ACADEMY PUBLISHER. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.4304/jcp.6.10.2004-2012 | JCP |
Keywords | Field | DocType |
dynamic programming,join-order,multi-core,query optimization,multi core | Query optimization,Hash join,Dynamic programming,Computer science,Parallel computing,Top-down and bottom-up design,Sort-merge join,Theoretical computer science,Exploit,Multi-core processor,Microarchitecture | Journal |
Volume | Issue | Citations |
6 | 10 | 1 |
PageRank | References | Authors |
0.37 | 9 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wanli Zuo | 1 | 342 | 42.73 |
| Yongheng Chen | 2 | 18 | 4.50 |
| Fengling He | 3 | 68 | 7.88 |
| Kerui Chen | 4 | 16 | 2.78 |