Date of Publication :21st November 2017
Abstract: The big data is the idea of the gigantic scope of information, which is being made step by step. In current years dealing with this information is the significance test. Hadoop is an open source proposition which is utilized successfully to deal with the big data applications. The two central ideas of the Hadoop are MapReduce and Hadoop conveyed document framework. HDFS is the capacity system and guide lessen is the programming dialect. Results are created quicker than other customary database operations. A few dialects which encourage us to program the MapReduce system inside brief time frame.
Reference :
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- Yaxiong Zhao, Jie Wu “Dache: A Data Aware Caching for Big-Data Applications Using The Map Reduce Framework” International Journal of Tsinghua Science And Technology, Volume 19 Number 1, February 2014, Pages 39-49
- Jefffrey Dean, Sanjay Ghemawat “MapReduce: Simplified Data Processing on Large Clusters” Communications of the ACM, Volume 51, Number 1, Pages 107-113.
- Sasiniveda.G, Revathi.N “Data Analysis using Mapper and Reducer with Optimal Configuration in Hadoop” International Journal of Computer Trends and Technology (IJCTT), Volume 04 Number 03, February 2013, Pages 264-268.
- Karan B.Maniar, Chintan B.Khatri “Data Science: Bigtable, Mapreduce and Google File System” International Journal of Computer Trends and Technology (IJCTT), Volume 16 Number 03, October 2014, Pages 115-118.
- Tom White “Hadoop the definitive guide” Proc. O’Reilly Media, Edition 3, May 2012. [6] Chuck Lam “Hadoop in Action” Proc. Manning Publication, Edition 1, December 2012.
- Donald Miner, Adam Shook “Mapreduce Design Patterns” Proc. O’Reilly Media, November 2012
- Ramesh Kumar, Dr.Vijay Singh Rathore “Efficient Capabilities of Processing of Big data using Hadoop Map Reduce” International Journal of Advanced Research in Computer and Communication Engineering, Volume 03 Issue 06, June 2014, Pages 7123-7126
- Shital Suryawanshi, Prof.V.S.Wadne “Big Data Mining using Map Reduce: A Survey Paper” IOSR International Journal Computer Engineering, Volume 16 Issue 06, Nov- Dec 2014, Pages 37-40