DocumentCode :
2439818
Title :
MapReduce programming with apache Hadoop
Author :
Bhandarkar, Milind
Author_Institution :
Yahoo! Inc., Hadoop Solutions Architect
fYear :
2010
fDate :
19-23 April 2010
Firstpage :
1
Lastpage :
1
Abstract :
Summary form of only given: Apache Hadoop has become the platform of choice for developing large-scale data-intensive applications. In this tutorial, we will discuss design philosophy of Hadoop, describe how to design and develop Hadoop applications and higher-level application frameworks to crunch several terabytes of data, using anywhere from four to 4,000 computers. We will discuss solutions to common problems encountered in maximizing Hadoop application performance. We will also describe several frameworks and utilities developed using Hadoop that increase programmer-productivity and application-performance.
Keywords :
Java; distributed processing; Apache Hadoop design philosphy; Hadoop IPDPS 2010 symposium tutorial; Hadoop application performance; MapReduce programming; large scale data intensive applications; Application software; Biographies; Computational modeling; Large-scale systems; Parallel programming; Rockets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Parallel & Distributed Processing (IPDPS), 2010 IEEE International Symposium on
Conference_Location :
Atlanta, GA
ISSN :
1530-2075
Print_ISBN :
978-1-4244-6442-5
Type :
conf
DOI :
10.1109/IPDPS.2010.5470377
Filename :
5470377
Link To Document :
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