DocumentCode :
3144389
Title :
Scheduling and processor allocation for parallel execution of multijoin queries
Author :
Chen, Ming-Syan ; Yu, Philip S. ; Wu, Kun-Lung
Author_Institution :
IBM Thomas J. Watson Res. Center, Yorktown Heights, NY, USA
fYear :
1992
fDate :
2-3 Feb 1992
Firstpage :
58
Lastpage :
67
Abstract :
The authors deal with two major issues to exploit inter-operator parallelism within a multijoin query: join sequence scheduling and processor allocation. For the first issue, they propose and evaluate by simulation several methods to determine the general join sequences, or the bush execution trees. Despite their simplicity, the proposed heuristics can lead to the general join sequences which significantly outperform the optimal sequential join sequence. In addition, several heuristics to determine the processor allocation, categorized by bottom-up and top-down approaches, were derived and evaluated by simulation. As confirmed by the simulation, by first using the join sequence heuristics to build a busy tree and then applying the concept of synchronous execution time to the busy tree for processor allocation, an efficient two-step approach to schedule and execute multijoin queries in a multiprocessor system can be obtained
Keywords :
database theory; parallel programming; programming theory; scheduling; bottom up heuristics; bush execution trees; inter-operator parallelism; join sequence scheduling; multijoin queries; multiprocessor system; parallel execution; processor allocation; simulation evaluation; synchronous execution time; top down heuristics; Database machines; Database systems; Degradation; Industrial relations; Iron; Job shop scheduling; Multiprocessing systems; Processor scheduling; Relational databases; System performance;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Engineering, 1992. Proceedings. Eighth International Conference on
Conference_Location :
Tempe, AZ
Print_ISBN :
0-8186-2545-7
Type :
conf
DOI :
10.1109/ICDE.1992.213205
Filename :
213205
Link To Document :
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