Performance impact of JobTracker failure in Hadoop

Young Pil Kim, Cheol Ho Hong, Chuck Yoo

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


In this paper, we analyze the performance impact of JobTracker failure in Hadoop. A JobTracker failure is a serious problem that affects the overall job processing performance. We describe the cause of failure and the system behaviors because of failed job processing in the Hadoop. On the basis of the analysis, we build a job completion time model that reflects failure effects. Our model is based on a stochastic process with a node crash probability. With our model, we run simulation of performance impact with very credible failure data available from USENIX called computer failure data repository that have been collected for past 9-years. The results show that the performance impact is very severe in that the job completion time increases about four times typically, and in a worst case, it increases up to 68 times.

Original languageEnglish
Pages (from-to)1265-1281
Number of pages17
JournalInternational Journal of Communication Systems
Issue number7
Publication statusPublished - 2015 May 10

Bibliographical note

Publisher Copyright:
Copyright © 2014 John Wiley & Sons, Ltd.


  • Hadoop
  • JobTracker
  • failure analysis
  • large-scale data processing

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Electrical and Electronic Engineering


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