Map reduce, pig and hive on climatic condition

Abstract

This paper addresses recent growth within thes caleand kind of Earth science knowledge has provided new opportunities to massive knowledge analytics analysis for understanding the Earth's physical processes. There has been associate upsurge of natural science datasets within the past few decades that are being frequently collected mistreatment various modes of acquisition, at deferent scales of observation, and in numerous knowledge sorts and formats. Earth science knowledge sets but exhibit some distinctive characteristics (e.g. adherence to physical properties and spatiotemporal constraints), that gift challengestoancientdata-centric approaches.In this paper the comparative study of Hadoop’s programming paradigm (Map reduce)andHadoop’s ecosystems Hive and Pig.The processing time of map reduce, hive and pig is implement edona data set with simple queries. It is observed that Map reduce processes the datain shorter time ascompared with Map reduceand Hive. It is not necessary that only Map Reduce is useful other techniques are also useful under differentconstraints.