Bridging Geospatial Gaps in Distributed Computing

This chapter explores the challenges of processing geospatial data within distributed computing systems, specifically discussing the limitations of Apache Spark. It highlights the role of Apache Sedona in enhancing spatial data handling and optimizing large-scale data operations. Real-world applications and user scenarios are examined, showcasing the integration of Sedona with popular tools to streamline geospatial data management.