An analysis of Crime data under Apache Pig on Big Data

Abstract

The most important social problem that occurs all around the world is crime. Crime arousing affects children's development, security of public and socio-economic condition of an adult. Discernment about crime rate factors is demanding for government and policy makers in their try to minimize the crime and boost the civilian's life essence. We analyzing big data related to the crimes and crime rate in our paper. In this paper, we familiarize with social problem of crime using apache pig with hadoop, which implicate discovery of verisimilar vicious crime incident selective with the incident-level crime data which is provided by past identical crime incidents. The incident-level crime data stored as a dataset of crime which add type of crime, ID of the criminal, incident date and location are crime limitation or parameters used in this paper. In this paper a big data analysis based analyzing large scale crime data under Apache Pig used various commands in the grunt shell with hadoop distributed file system. Big data analysis gathering problem-solving data set of crime is a burdensome process due to secretiveness principle. So, it's a state-of-the-art method used crime dataset as an input for analyzing large scale crime data that will definitely help out for decision makers, policy makers and government to minimize the crime.