An Apache Spark-based analytics platform optimized for Azure.
Hello, Not, but I used a quickest possible workaround;
Instead of calling fs commands to create_table or write_table I have instead saved the dataframe as a delta table and afterwards registered the table as fs one. This way there weren't any problems nor delays, except not having a direct definition of partitions which was not a big pain in my use-case.
However, the command to drop table, which was very slow as well, now runs fast. But the above-mentioned commands still perform endlessly for originally described dataframe of 400k lines s (I think the longest run was over 1.5h after I cancelled the command).