2013年
Optimization for iterative queries on MapReduce
Proceedings of the VLDB Endowment
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- 巻
- 7
- 号
- 4
- 開始ページ
- 241
- 終了ページ
- 252
- 記述言語
- 英語
- 掲載種別
- 研究論文(学術雑誌)
- DOI
- 10.14778/2732240.2732243
- 出版者・発行元
- Association for Computing Machinery
We propose OptIQ, a query optimization approach for iterative queries in distributed environment. OptIQ removes redundant computations among different iterations by extending the traditional techniques of view materialization and incremental view evaluation. First, OptIQ decomposes iterative queries into invariant and variant views, and materializes the former view. Redundant computations are removed by reusing the materialized view among iterations. Second, OptIQ incrementally evaluates the variant view, so that redundant computations are removed by skipping the evaluation on converged tuples in the variant view. We verify the effectiveness of OptIQ through the queries of PageRank and k-means clustering on real datasets. The results show that OptIQ achieves high efficiency, up to five times faster than is possible without removing the redundant computations among iterations. © 2013 VLDB Endowment 2150-8097/13/12.
- ID情報
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- DOI : 10.14778/2732240.2732243
- ISSN : 2150-8097
- SCOPUS ID : 84896956234