[GitHub] [incubator-sedona] edurdevic commented on a change in pull request #558: Updated Databricks setup documentation

[GitBox <gi...@apache.org>]

edurdevic commented on a change in pull request #558:
URL: https://github.com/apache/incubator-sedona/pull/558#discussion_r740173570



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File path: docs/download/databricks.md
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@@ -4,13 +4,66 @@ You just need to install the Sedona jars and Sedona Python on Databricks using D
 
 ## Advanced editions
 
-If you are not using the free version of Databricks, there is an issue with the path where Sedona Python looks for the jar. Thanks to the report from Sedona user @amoyrand.
+### Databricks DBR 7.x (Recommended)
 
-Two steps to fix this:
+If you are using the commercial version of Databricks up to version 7.x you can install the Sedona jars and Sedona Python using the Databricks default web UI and everything should work.
 
-1. Upload the jars in /dbfs/FileStore/jars/
-2. Add this line to the config `.config("spark.jars", "/dbfs/FileStore/jars/sedona-python-adapter-3.0_2.12-{{ sedona.current_version }}.jar") \`
+### Databricks DBR 8.x, 9.x, 10.x
+
+If you are not using the free version of Databricks, there are currently some compatibility issues with DBR 8.x+. Specifically, the `ST_intersect` join query will throw a `java.lang.NoSuchMethodError` exception.
+
+
+## Install Sedona from the web UI
+
+1) From the Libraries tab install from Maven Coordinates
+    ```
+    org.apache.sedona:sedona-python-adapter-3.0_2.12:{{ sedona.current_version }}
+    org.datasyslab:geotools-wrapper:{{ sedona.current_geotools }}
+    ```
+
+2) From the Libraries tab install from PyPI
+    ```
+    apache-sedona
+    ```
+
+3) (Optional) You can speed up the serialization of geometry types by adding to your spark configurations (`Cluster` -> `Edit` -> `Configuration` -> `Advanced options`) the following lines:
+
+    ```
+    spark.serializer org.apache.spark.serializer.KryoSerializer
+    spark.kryo.registrator org.apache.sedona.core.serde.SedonaKryoRegistrator
+    ```
+
+    *This options are not compatible with the commercial Databricks DBR versions (8.x+).*
+
+## Initialise
+
+After you have installed the libraries and started the cluster, you can initialize the Sedona `ST_*` functions and types by running from your code: 
+
+(scala)
+```Scala
+import org.apache.sedona.sql.utils.SedonaSQLRegistrator
+SedonaSQLRegistrator.registerAll(sparkSession)
+```
+
+(or python)
+```Python
+from sedona.register.geo_registrator import SedonaRegistrator
+SedonaRegistrator.registerAll(spark)
+```
 
 ## Pure SQL environment
+ 
+In order to use the Sedona `ST_*` functions from SQL, you need to register the Sedona bindings. There are two ways to do that:
+
+1) Insert a python (or scala) cell at the beginning of your SQL notebook to activate the bindings
+
+    ```Python
+    %python
+    from sedona.register.geo_registrator import SedonaRegistrator
+    SedonaRegistrator.registerAll(spark)
+    ```
+
+2) Install the sedona libraries from the [cluster init-scripts](https://docs.databricks.com/clusters/init-scripts.html) and activate the bindings by adding `spark.sql.extensions org.apache.sedona.viz.sql.SedonaVizExtensions,org.apache.sedona.sql.SedonaSqlExtensions` to your cluster's spark configuration. This way you can activate the Sedona bindings without typing any python or scala code. 

Review comment:
       Yes, good point @alexott. 
   I added some example scripts to be run in a notebook that will create the init script and download the dependencies via CURL. Please let me know if there is a better way to get the maven URL. 




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