International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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Volume 172 - Issue 4 |
Published: Aug 2017 |
Authors: Swati R. Mahendrakar, B. M. Patil |
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Swati R. Mahendrakar, B. M. Patil . PRISM: Fine-Grained Phase and Resource Information-aware Scheduler for Map-Reduce. International Journal of Computer Applications. 172, 4 (Aug 2017), 32-39. DOI=10.5120/ijca2017915130
@article{ 10.5120/ijca2017915130, author = { Swati R. Mahendrakar,B. M. Patil }, title = { PRISM: Fine-Grained Phase and Resource Information-aware Scheduler for Map-Reduce }, journal = { International Journal of Computer Applications }, year = { 2017 }, volume = { 172 }, number = { 4 }, pages = { 32-39 }, doi = { 10.5120/ijca2017915130 }, publisher = { Foundation of Computer Science (FCS), NY, USA } }
%0 Journal Article %D 2017 %A Swati R. Mahendrakar %A B. M. Patil %T PRISM: Fine-Grained Phase and Resource Information-aware Scheduler for Map-Reduce%T %J International Journal of Computer Applications %V 172 %N 4 %P 32-39 %R 10.5120/ijca2017915130 %I Foundation of Computer Science (FCS), NY, USA
In recent years, Map Reduce has become a popular model with regard to data-intensive computation. Map Reduce can significantly reduce the execution time of data-intensive jobs. In order to achieve this objective, Map Reduce breaks down each job into small map and reduce tasks and executes them in parallel across a large number of machines. However, existing solutions mainly focus on scheduling at the task-level, which offer sub-optimal job performance, because tasks may have resource requirements which may vary during their lifetime. This makes it difficult for existing system’s task-level schedulers to effectively utilize available resources in order to reduce job execution time. To avoid this limitation, PRISM is introduced. PRISM stands for Phase and Resource Information-aware Scheduler for Map-Reduce. PRISM consists of various clusters that perform resource-aware scheduling at the level of phases. PRISM can be defined as a fine-grained resource-aware Map Reduce scheduler that divides tasks into phases. Here, each phase has a constant resource usage profile, so that not a single phase suffers from starvation. PRISM also offers high resource utilization and provides 1:3x improvements in job running time as compared to the current Hadoop schedulers.