Processing large amounts of spatial data involves a lot of overheads, higher latency, lower bandwidth, high processing time and a well defined framework. All the issues addressed needs to be solved using different tools available in big data analytics. In this project, we will be focusing on solving these issues and combining the benefits of RDMA with SparkGIS framework to improve the overall performance in distributed computing. Our main goal is to understand RDMA and it’s deployment, configuring RDMA over Conventional Ethernet(RoCE), deploying RDMA-Spark on RoCE and finally deploying SparkGIS on RDMA-Spark. After all these deployments are done, we will shift our focus to optimizing SparkGIS for more accurate and faster results.