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On Applying Hash Filters To Improving The Execution Of Multi-Join Queries (1997)
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| Venue: | VERY LARGE DATA BASES JOURNAL (VLDBJ |
| Citations: | 5 - 0 self |
BibTeX
@ARTICLE{Chen97onapplying,
author = {Ming-Syan Chen and Hui-I Hsiao and Philip S. Yu},
title = {On Applying Hash Filters To Improving The Execution Of Multi-Join Queries},
journal = {VERY LARGE DATA BASES JOURNAL (VLDBJ},
year = {1997},
volume = {6},
pages = {131}
}
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Abstract
In this paper, we explore an approach of interleaving a bushy execution tree with hash filters to improve the execution of multi-join queries. Similar to semijoins in distributed query processing, hash filters can be applied to eliminate non-matching tuples from joining relations before the execution of a join, thus reducing the join cost. Note that hash filters built in different execution stages of a bushy tree can have different costs and effects. The effect of hash filters is evaluated first. Then, an efficient scheme to determine an effective sequence of hash filters for a bushy execution tree is developed, where hash filters are built and applied based on the join sequence specified in the bushy tree so that not only is the reduction effect optimized but also the cost associated is minimized. Various schemes using hash filters are implemented and evaluated via simulation. It is experimentally shown that the application of hash filters is in general a very powerful means...
