jbampton commented on code in PR #1672: URL: https://github.com/apache/sedona/pull/1672#discussion_r1826472751
########## README.md: ########## @@ -34,25 +34,26 @@ Join the Sedona monthly community office hour: [Google Calendar](https://calenda ## What is Apache Sedona? -Apache Sedona™ is a spatial computing engine that enables developers to easily process spatial data at any scale within modern cluster computing systems such as Apache Spark and Apache Flink. Sedona developers can express their spatial data processing tasks in Spatial SQL, Spatial Python or Spatial R. Internally, Sedona provides spatial data loading, indexing, partitioning, and query processing/optimization functionality that enable users to efficiently analyze spatial data at any scale. +Apache Sedona™ is a spatial computing engine that enables developers to easily process spatial data at any scale within modern cluster computing systems such as [Apache Spark](https://spark.apache.org/) and [Apache Flink](https://flink.apache.org/). +Sedona developers can express their spatial data processing tasks in [Spatial SQL](https://carto.com/spatial-sql), Spatial Python or Spatial R. Internally, Sedona provides spatial data loading, indexing, partitioning, and query processing/optimization functionality that enable users to efficiently analyze spatial data at any scale.  ### Features Some of the key features of Apache Sedona include: -* Support for a wide range of geospatial data formats, including GeoJSON, WKT, and ESRI Shapefile. +* Support for a wide range of geospatial data formats, including [GeoJSON](https://en.wikipedia.org/wiki/GeoJSON), [WKT](https://en.wikipedia.org/wiki/Well-known_text_representation_of_geometry), and [ESRI](https://www.esri.com) [Shapefile](https://en.wikipedia.org/wiki/Shapefile). * Scalable distributed processing of large vector and raster datasets. * Tools for spatial indexing, spatial querying, and spatial join operations. -* Integration with popular geospatial python tools such as GeoPandas. -* Integration with popular big data tools, such as Spark, Hadoop, Hive, and Flink for data storage and querying. -* A user-friendly API for working with geospatial data in the SQL, Python, Scala and Java languages. +* Integration with popular geospatial python tools such as [GeoPandas](https://geopandas.org). Review Comment: ```suggestion * Integration with popular geospatial Python tools such as [GeoPandas](https://geopandas.org). ``` -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
