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Analyzing Failures of a Semi-Structured Supercomputer Log File Efficiently by Using PIG on Hadoop

M.S. Palle1 , K. Jyothsna2 , B. Anusha3

Section:Research Paper, Product Type: Journal Paper
Volume-2 , Issue-1 , Page no. 1-5, Jan-2014

Online published on Feb 04, 2014

Copyright © M.S. Palle, K. Jyothsna, B. Anusha . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: M.S. Palle, K. Jyothsna, B. Anusha, “Analyzing Failures of a Semi-Structured Supercomputer Log File Efficiently by Using PIG on Hadoop,” International Journal of Computer Sciences and Engineering, Vol.2, Issue.1, pp.1-5, 2014.

MLA Style Citation: M.S. Palle, K. Jyothsna, B. Anusha "Analyzing Failures of a Semi-Structured Supercomputer Log File Efficiently by Using PIG on Hadoop." International Journal of Computer Sciences and Engineering 2.1 (2014): 1-5.

APA Style Citation: M.S. Palle, K. Jyothsna, B. Anusha, (2014). Analyzing Failures of a Semi-Structured Supercomputer Log File Efficiently by Using PIG on Hadoop. International Journal of Computer Sciences and Engineering, 2(1), 1-5.

BibTex Style Citation:
@article{Palle_2014,
author = {M.S. Palle, K. Jyothsna, B. Anusha},
title = {Analyzing Failures of a Semi-Structured Supercomputer Log File Efficiently by Using PIG on Hadoop},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2014},
volume = {2},
Issue = {1},
month = {1},
year = {2014},
issn = {2347-2693},
pages = {1-5},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=30},
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=30
TI - Analyzing Failures of a Semi-Structured Supercomputer Log File Efficiently by Using PIG on Hadoop
T2 - International Journal of Computer Sciences and Engineering
AU - M.S. Palle, K. Jyothsna, B. Anusha
PY - 2014
DA - 2014/02/04
PB - IJCSE, Indore, INDIA
SP - 1-5
IS - 1
VL - 2
SN - 2347-2693
ER -

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Abstract

Data sets used to fuel the recently popular concept of �business intelligence� are becoming increasingly large. Conventional database management software is no longer efficient enough however; parallel database management systems and massive data-scale processing systems like MapReduce indeed look promising. Although, MapReduce is a good option, it is difficult to work with, as the programmer would have to think at the mapper and reducer level. In this paper, we present a simple yet efficient way to mine useful information where a program can be written as a series of steps. We have queried a supercomputer log file using Apache�s Hadoop and PIG, obtained results as to when and why the supercomputer had failed and compared these results to that of a traditional program.

Key-Words / Index Term

Big Data, Parallel Processing, Hadoop, MapReduce, Data Mining, Business Intelligence, PIG, Log file analysis, Supercomputer

References

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