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A Comprehensive Review of Straggler Handling Algorithms for MapReduce Framework

초록

영어

Distributed computing accomplished broad appropriation because of consequently parallelizing and transparently executing tasks in distributed environments. Straggling tasks is an essential test confronted by all Big Data Processing Frameworks for example MapReduce, Dryad, and Spark. Stragglers are the assignments that run much slower than different tasks and since a job completes just when it’s last undertaking completions, stragglers postponement work fruition. Stragglers extraordinarily impact little occupations such that employments comprising of a couple of undertakings. Such occupations are fundamentally deferred regardless of the fact that a solitary undertaking is moderate .This paper survey stragglers recognition and rescheduling systems proposed so far and brings up their strengths and shortcomings. This paper additionally displays wise attributes and impediments of the existing state- of-the- craftsmanship calculations to take care of the issue of stragglers relief.

목차

Abstract
 1. Introduction
 2. MapReduce Framework
 3. Why Stragglers Exist
 4. Techniques
 5. Conclusion and Future Work
 References

저자정보

  • Umesh Kumar YMCA University of Science and Technology, Faridabad, 121006, India
  • Jitendar Kumar YMCA University of Science and Technology, Faridabad, 121006, India

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