Performance Enhancement of MapReduce Framework in Big Data Application Using Load Balancing with Cache
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Research Paper | Computer Science & Engineering | India | Volume 4 Issue 12, December 2015

Performance Enhancement of MapReduce Framework in Big Data Application Using Load Balancing with Cache

Sushant Shirish Nagavkar, Ashishkumar

Hadoop is open source software that is used to store big data, it supports data demanding applications and performs analysis, using a random placement method for parallel processing to give effortlessness and load balance. To achieve maximum parallelism per group to load balance a new Data-gRouping-AWare (DRAW) data placement is used. Problem in big data is when any query executes repeatedly it repeats whole process of execution to obtain result. In MapReduce framework and generates a large amount of intermediate data. Such huge amount of information is thrown away after the tasks finish, because MapReduce is not able to use this data. Dache, a data-aware cache framework for big-data applications gives the produced intermediate results to the cache manager. Task inquiries the cache manager before performing the actual computing work.

Keywords: BEA, Big-data, caching, DACH, DRAW, Hadoop, HDFS, MapReduce

Edition: Volume 4 Issue 12, December 2015

Pages: 1661 - 1667

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Sushant Shirish Nagavkar, Ashishkumar, "Performance Enhancement of MapReduce Framework in Big Data Application Using Load Balancing with Cache", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=NOV152318, Volume 4 Issue 12, December 2015, 1661 - 1667

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Performance Enhancement of MapReduce Framework in Big Data Application Using Load Balancing with Cache

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