Big Data Analysis using Spark for Collision Rate near CalStateLA
Keywords:
spark, collision data, gender analysis, geo spatial analysis, big data
Abstract
Police say alcohol, drugs and speed are the three major factors that cause collisions, we thought that it would be insightful to analyze the collision data to ensure the correctness of this conclusion; and also to get further information like what age groups were involved, in what areas have accidents occurred, what were the reasons behind collisions, etc. These experiences can possibly make overall population mindful of the reasons for crashes created by impacts. To analyze more than hundred thousand records we adopted Spark for faster processing of this massive data set. In this paper, we are presenting facts based on data and analytics which lead to conclusions like the number of collisions decreased between 2009 and 2013, Females involved in collisions were much less than males, etc. Moving ahead in our research, we addressed complex analytics like areas near CalStateLA more prone to collisions, brands of cars more involved in collisions and which specific type of collision was most observed.
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Published
2016-10-15
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Copyright (c) 2016 Authors and Global Journals Private Limited
This work is licensed under a Creative Commons Attribution 4.0 International License.