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abstract

Exploring memory locality for big data analytics in virtualized clusters

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Published:24 September 2017Publication History

ABSTRACT

In this work, we investigate techniques to improve the performance of big data analytics in virtualized clusters by effectively increasing the utilization of cached data and efficiently using scarce memory resources.

References

  1. Ganesh Ananthanarayanan, Ali Ghodsi, Scott Shenker, and Ion Stoica. 2011. Disk-locality in Datacenter Computing Considered Irrelevant. In Proceedings of the 13th USENIX Conference on Hot Topics in Operating Systems (HotOS'11).Google ScholarGoogle ScholarDigital LibraryDigital Library
  2. Ganesh Ananthanarayanan, Ali Ghodsi, Andrew Wang, Dhruba Borthakur, Srikanth Kandula, Scott Shenker, and Ion Stoica. 2012. PACMan: Coordinated Memory Caching for Parallel Jobs. In Proceedings of the 9th USENIX Conference on Networked Systems Design and Implementation (NSDI'12).Google ScholarGoogle Scholar
  3. Apache Hadoop 2017. Apache Hadoop Centralized Cache Management in HDFS. (2017). http://hadoop.apache.org/docs/r2.4.1/hadoop-project-dist/hadoop-hdfs/CentralizedCacheManagement.html.Google ScholarGoogle Scholar
  4. Jaewon Kwak, Eunji Hwang, Tae-kyung Yoo, Beomseok Nam, and Young-ri Choi. 2016. In-Memory Caching Orchestration for Hadoop. In Proceedings of the 16th IEEE/ACM International Symposium on Cluster, Cloud and Grid Computing (CC-Grid'16).Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Exploring memory locality for big data analytics in virtualized clusters

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    • Published in

      cover image ACM Conferences
      SoCC '17: Proceedings of the 2017 Symposium on Cloud Computing
      September 2017
      672 pages
      ISBN:9781450350280
      DOI:10.1145/3127479

      Copyright © 2017 Owner/Author

      Permission to make digital or hard copies of part or all of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for third-party components of this work must be honored. For all other uses, contact the Owner/Author.

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 24 September 2017

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      Acceptance Rates

      Overall Acceptance Rate169of722submissions,23%

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