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We were testing the schema validation with the Databricks connection, and we found a problem with partitioned tables.
SODA uses the columns # Partition Information and # col_name for the validation (check the first image).
We think this happens because of the table's describe (second image)
Is there anything that we can change on our side like a setting? Or is it a bug on SODA side that needs to be fixed?
The info for partition is irrelevant because the column appears in the first list and then in the partition information.
The text was updated successfully, but these errors were encountered:
In pyspark one can do this: partitions_columns = [col.name for col in spark.catalog.listColumns("schema_name.table_name") if col.isPartition] and non_paritions_columns = [col.name for col in spark.catalog.listColumns("schema_name.table_name") if not col.isPartition]
We were testing the schema validation with the Databricks connection, and we found a problem with partitioned tables.
SODA uses the columns # Partition Information and # col_name for the validation (check the first image).
We think this happens because of the table's describe (second image)
Is there anything that we can change on our side like a setting? Or is it a bug on SODA side that needs to be fixed?
The info for partition is irrelevant because the column appears in the first list and then in the partition information.
The text was updated successfully, but these errors were encountered: