| Article ID | Journal | Published Year | Pages | File Type |
|---|---|---|---|---|
| 489914 | Procedia Computer Science | 2015 | 6 Pages |
Abstract
The Map Reduce framework provides a scalable model for large scale data intensive computing and fault tolerance. In this paper, we propose an algorithm to improve the I/O performance of the Hadoop distributed file system. The results prove that the proposed algorithm show better I/O performance with comparatively less synchronization
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Physical Sciences and Engineering
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