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