brysd opened a new issue, #6290: URL: https://github.com/apache/iceberg/issues/6290
Hi, going through all the documentation with respect to partition evolution and metadata I was wondering whether it's possible to retrieve the actual definition of on which column or columns and potential transform(s) a table is partitioned. (https://iceberg.apache.org/docs/latest/spark-queries/, and https://iceberg.apache.org/spec/) Using spark SQL the partitions table provides only an insight in the actual partition values, not on how this is constructed. It points to partition spec id's but where can we find the actual partition spec by using Spark SQL or the pyiceberg api? It's not clear whether this is supported with pyspark or not. Since we want to dynamically change partitions we first would need to know whether partitions already exist and if yes, which table fields and/or transform functions are being used for the partitioning. thx! -- 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] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
