Analyzing Performance of Map Reduce, Pig Latin and Hive on Windows Platform
Journal Title: International Journal of engineering Research and Applications - Year 2017, Vol 7, Issue 9
Abstract
The Hadoop framework allows distributed processing of large data sets across clusters of commodity computers efficiently. MapReduce, the core programming language of the Hadoop Ecosystem processes the data stored in Hadoop Distributed File System (HDFS). It is difficult for non programmers to work with MapReduce. Hadoop supports HiveQL (SQL like statements) which implicitly and immediately translates the queries into one or more MapReduce jobs. To help procedural language developers, Hadoop supports Pig Latin language. This paper runs a text data processing application with MapReduce, Hive and Pig on single node windows platform and compares performance in graphical form.
Authors and Affiliations
Mr. Manishkumar R Solanki, Yashvi Shah, Siddhi Shukla, Shrusti Talati
Keywords
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- EP ID EP392381
- DOI 10.9790/9622-0709043235.
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