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Selection and replacement algorithms for memory performance improvement in Spark

  • Published:2015-08-28 Issue:8 Volume:28 Page:2473-2486
  • ISSN:1532-0626
  • Container-title:Concurrency and Computation: Practice and Experience
  • language:en
  • Short-container-title:Concurrency Computat.: Pract. Exper.

Author:

Duan Mingxing1,Li Kenli12,Tang Zhuo12,Xiao Guoqing1,Li Keqin123

Affiliation:

1. College of Information Science and Engineering; Hunan University; Changsha Hunan China

2. National Supercomputing Center in Changsha; Changsha Hunan 410082 China

3. Department of Computer Science; State University of New York; New Paltz NY 12561 USA

Funder

Key Program of National Natural Science Foundation of China

National Natural Science Foundation of China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Reference18 articles.

1. SaC-FRAPP: a scalable and cost-effective framework for privacy preservation over big data on cloud;Zhang;Concurrency and Computation: Practice and Experience,2013

2. Big data: the future of biocuration;Howe;Nature,2008

3. The pathologies of big data;Jacobs;Communications of the ACM,2009

4. The age of big data;Lohr;New York Times,2012

5. Wikipedia Apache Spark http://en.wikipedia.org/wiki/Apache_{S}park

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3. Memory management optimization strategy in Spark framework based on less contention;The Journal of Supercomputing;2022-07-27

4. Intermediate data placement and cache replacement strategy under Spark platform;Journal of Parallel and Distributed Computing;2022-05

5. Cache Replacement Strategy Based on User Behaviour Analysis for a Massive Small File Storage System;2022 14th International Conference on Computer and Automation Engineering (ICCAE);2022-03-25
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