• Mansi Bhadoria
• Dr.Sachin Goyal
• Dr.Ratish Agarwal
• Dr.Mahesh Pawar

the conventional relational knowledge based systems cannot accommodate the necessity of analyzing data with enormous capacity and diverse formats, i.e., Big Data. Apache Hadoop since the 1st generation of ASCII text files massive knowledge resolution delivered a steady circulated knowledge space and resource supervision arrangement. Nevertheless, MapReduce framework, sole passage of employing the equivalent computing authority of Hadoop is that the API. Given a drag, one wishes to code a corresponding MapReduce platform in Java, which is time consuming. Moreover, Hadoop concentrates upon high output as an alternative of low latency. Therefore, Hadoop will be a poor fit interactive processing. The necessity of interactive Big Data administering required decoupling of data storage from analysis. The simple SQL queries of traditional relational database systems is however the most accessible analyzing tool that people devoid of programming backdrop can also profit from. Consequently, Big Data SQL engines have been twirled off in the Hadoop Ecosystem. Hence , we can be managing apache hive which is in a hadoop ecosystem and functions similar as SQL so effortlessly work on bigdata by by means of SQL (Hive) on Hadoop (Storing and handling bigdata). In this dissertation we can also send off recommended that parameter tuning is also significant in terms of processing for the reason that accurate tuning takes fewer time and throughout which we can certainly analyze bigdata in a reduced amount of time.

Hadoop, SQL, performance, tuning parameters, Hive, Mapreduce

"PERFORMANCE ENHANCEMENT OF SQL-ON-HADOOP ENVIRONMENT USING PARAMETERS TUNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.626-630, August-2018, Available :http://www.jetir.org/papers/JETIR1808241.pdf

"PERFORMANCE ENHANCEMENT OF SQL-ON-HADOOP ENVIRONMENT USING PARAMETERS TUNING", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp626-630, August-2018, Available at : http://www.jetir.org/papers/JETIR1808241.pdf