A Study of Skew in MapReduce Applications

نویسندگان

  • YongChul Kwon
  • Magdalena Balazinska
  • Bill Howe
  • Jerome Rolia
چکیده

This paper presents a study of skew — highly variable task runtimes — in MapReduce applications. We describe various causes and manifestations of skew as observed in real world Hadoop applications. Runtime task distributions from these applications demonstrate the presence and negative impact of skew on performance behavior. We discuss best practices recommended for avoiding such behavior and their limitations.

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تاریخ انتشار 2011