Yogesh Kumar Gupta* and Gunjan Barhaiya Pages 1 - 8 ( 8 )
Background: In this astronomically immense world tremendous amount of data engendering in every minute from the different domain which is referred to Big Data. In the last few years the data is incrementing day by day across the world. This Research fixates on the analysis of malefaction rates of 5 different states year wise, all the analysis is done utilizing Apache Pig.
Methods: The goal of the work is to analyze the astronomically immense malefaction data and find the estimate number of malefaction transpires in sundry states. This is done in Apache pig environment utilizing “Pig Latin” as language. A short code is indicted in Pig Latin which is utilized to load and process the data into Map reduce environment, afterwards the result are obtained with the detail of minimum and maximum mapper and reducer timing.
Result: The data is visualized into graphs to make analysis to analyze the variation of malefaction rates in distinct states. After analyzing the malefaction against women, murder cases are very high in 2006-2010 as compared to other year groups whereas abducting and rape cases incremented perpetually from 2001 to 2014 respectively. Similarly all the reports regarding to different malefaction rates are visualized above by utilizing graphs.
Conclusion: Various results are found with sundry queries and everything is represented graphically for better understanding and comparison. This avails us to find which state is affected by which crime. The expeditiousness of Apache pig can additionally be optically discerned as this immensely colossal crime data processed in short time with precision.
Big Data, Hadoop, Apache Pig, MapReduce, Crime Rates
Department of Computer Science, Faculty of Mathematics and Computing, Banasthali Vidyapith, Jaipur, Department of Computer Science, Faculty of Mathematics and Computing, Banasthali Vidyapith, Jaipur