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BigData and MapReduce with Hadoop
| Content Provider | Semantic Scholar |
|---|---|
| Author | Trobec, Roman Rashkovska, Aleksandra Mežnar, Peter Lipej, Andrej |
| Copyright Year | 2012 |
| Abstract | The paper describes the application of the MapReduce paradigm for processing and analyzing large amounts of data, coming from a computer simulation for a specific scientific problem. The Apache Hadoop open source distribution was installed on a cluster built of six computing nodes, each with four cores. The implemented MapReduce job pipeline is described and the essential Java code segments are presented. The experimental measurements of the employed MapReduce tasks execution times result in a speedup of 20, which indicates that a high level of parallelism is achieved. |
| File Format | PDF HTM / HTML |
| Alternate Webpage(s) | http://pluton.ijs.si/CLASS/files/KC_CLASS_IJS_Tomasic_2012.pdf |
| Alternate Webpage(s) | http://videolectures.net/site/normal_dl/tag=735305/classconference2012_tomasic_hadoop_01.pdf |
| Language | English |
| Access Restriction | Open |
| Content Type | Text |
| Resource Type | Article |