Name
Abstract | ||
|---|---|---|
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 9years. 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. Copyright © 2014 John Wiley & Sons, Ltd. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1002/dac.2759 | Int. J. Communication Systems |
Keywords | Field | DocType |
Hadoop,large‐scale data processing,failure analysis,JobTracker | Crash,Computer science,Stochastic process,Real-time computing,Time model,Information repository | Journal |
Volume | Issue | ISSN |
28 | 7 | 1074-5351 |
Citations | PageRank | References |
3 | 0.41 | 20 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Young-Pil Kim | 1 | 21 | 5.53 |
| Cheol-Ho Hong | 2 | 115 | 10.66 |
| Chuck Yoo | 3 | 45 | 8.42 |