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Distributed_Analytics_of_US_Residential_Zoning
This is a project that aims to do distributed analytics using clusters using a spatial dataset. Our goal with this project was to analyze the impact of single family rresidential zoning in the US and correlate it to quality of life measures in an effort to dissuade a segreggation of zoning types and promote inclusivity. We hoped to be able to compare the results against data from other countries that have more includive zoning laws, but this was not possible due to constraints on data availability and language barriers. For the distributed component, we are using a cluster of 10 machines that are managed by Yarn. To do the processing of data and calculations, we applied Spark using Java and Gradle. The data itself was stored using HDFS and totaled to ~3.2 GB. For more detail on our motivation, procedures, project structure, and results, please reference the latex file or the presentation in the GitHub repo.