remibaar commented on issue #1137: URL: https://github.com/apache/sedona/issues/1137#issuecomment-1837121675
> Another alternative to fix this is that: use `sedona-spark` jar which does not shade anything, and manually download all dependency jars of Sedona Please correct me if I am wrong. With this method you also will not be able to use both the H3 of Sedona and the H3 of Databricks. Because they use different major versions (Sedona uses 4.1.1, Databricks uses 3.7.0), which are incompatible. My personal recommendation would be to remove the H3 3.7.0 jar from the Databricks runtime. This disables the H3 functions of Databricks, but allows the use of the H3 functions of Sedona. In my opinion the H3 functions of Sedona are more feature complete. For example one of the features I need is the `fullCover` of the `ST_H3CellIDs` function. Which is not available at the Databricks implementation, but is at Sedona -- 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: issues-unsubscr...@sedona.apache.org For queries about this service, please contact Infrastructure at: us...@infra.apache.org
