@inproceedings{9f29dc6999bf46239b2107fcb1c8d0cb,
title = "MapReduce application profiler",
abstract = "MapReduce is a programming model popularized by Google to process large data in clusters and has become a key technology on cloud computing nowadays. Due to the feature of simplicity, MapReduce attracts many application developers to develop related applications. However, MapReduce currently has few solutions to help application developers with the tasks of profiling their applications. In this paper, MapReduce Application Profiler (MRAP) is proposed to facilitate profiling MapReduce applications in clusters.",
author = "Huang, {Tzu Chi} and Chu, {Kuo Chih} and Chiu, {Chui Ming} and Shieh, {Ce Kuen}",
year = "2014",
doi = "10.1007/978-94-007-7262-5_84",
language = "English",
isbn = "9789400772618",
series = "Lecture Notes in Electrical Engineering",
publisher = "Springer Verlag",
pages = "741--749",
booktitle = "Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013",
address = "Germany",
note = "Advanced Technologies, Embedded and Multimedia for Human-Centric Computing, HumanCom and EMC 2013 ; Conference date: 23-08-2013 Through 25-08-2013",
}