spatial-framework-for-hadoop
A framework enabling spatial data analysis within Hadoop ecosystems using Hive and SparkSQL.
What is spatial-framework-for-hadoop?
Spatial Framework for Hadoop is an open-source library that enables spatial data analysis within Hadoop ecosystems. It provides User-Defined Functions and serialization tools for Hive and SparkSQL, allowing users to process and query geographic data at scale. The framework solves the problem of integrating geospatial analytics into big data workflows without requiring specialized standalone systems.
Data engineers and data scientists working with large-scale spatial data in Hadoop environments, particularly those using Hive or SparkSQL for analytics. It's also relevant for organizations with existing Esri/ArcGIS infrastructure looking to extend spatial capabilities to big data platforms.
Developers choose this framework because it provides native spatial functions within familiar Hadoop tools, avoiding the need for separate geospatial processing systems. Its tight integration with Esri's geometry standards ensures compatibility with ArcGIS workflows while leveraging Hadoop's distributed processing power.
Overview
The Spatial Framework for Hadoop allows developers and data scientists to use the Hadoop data processing system for spatial data analysis.
Use Cases
Best For
Related Projects
Found a gem we're missing?
Open-Awesome is built by the community, for the community. Submit a project, suggest an awesome list, or help improve the catalog on GitHub.
