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The Pig Mix Benchmark on Pig, MapReduce, and HPCC Systems

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

16 Scopus citations

Abstract

Soon after Google published MapReduce, their paradigm for processing large amounts of data, the open-source world followed with the Hadoop ecosystem. Later on, Lexis Nexis, the company behind the world's largest database of legal documents, open-sourced its Big Data processing platform, called the High-Performance Computing Cluster (HPCC). This paper makes three contributions. First, we describe our additions and improvements to the Pig Mix benchmark, the set of queries originally written for Apache Pig, and the porting of Pig Mix to HPCC. Second, we compare the performance of queries written in Pig, Java MapReduce, and ECL. Last, we draw conclusions and issue recommendations for future system benchmarks and large-scale data-processing platforms.

Original languageEnglish
Title of host publicationProceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015
EditorsCarminati Barbara, Latifur Khan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages643-648
Number of pages6
ISBN (Electronic)9781467372787
DOIs
StatePublished - 17 Aug 2015
Event4th IEEE International Congress on Big Data, BigData Congress 2015 - New York City, United States
Duration: 27 Jun 20152 Jul 2015

Publication series

NameProceedings - 2015 IEEE International Congress on Big Data, BigData Congress 2015

Conference

Conference4th IEEE International Congress on Big Data, BigData Congress 2015
Country/TerritoryUnited States
CityNew York City
Period27/06/152/07/15

Bibliographical note

Publisher Copyright:
© 2015 IEEE.

Keywords

  • Benchmark
  • Big Data
  • HPCC Systems
  • MapReduce
  • Performance
  • PigMix

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