Hi Shivaraj,
Thanks for reaching out to Microsoft Q&A.
The error you're encountering is commonly related to permissions or configuration issues in the Spark environment. Let's troubleshoot a few potential issues:
Table Registration Permissions: Verify that the service principal or identity running your Spark job has appropriate permissions to write to the Hive metastore. Ensure it has the CREATE
and INSERT
privileges for table registration.
- Path Conflicts: Since you're using
saveAsTable
with a specific path, conflicts can arise if the table's path doesn't match the Hive metastore location. You may want to first try saving without specifying the path, as shown below, and see if the table registers correctly:
Ensure Mount Accessibility: Although you mentioned being able to access the mount location, ensure there are no temporary access issues by reading a small file from the mount location as a test before writing the table.df.write.mode("overwrite").format("csv").saveAsTable("Employee_Ext")
- Writing Format and Table Configuration: Hive tables typically expect a specific structure, like Parquet or Delta, rather than CSV. If the Hive metastore is configured with certain expectations, the
csv
format may not be compatible for table registration. You could try usingparquet
instead, which is better suited for Hive table operations:
Check Log Details: Review the full error logs, particularly those showingdf.write.mode("overwrite").format("parquet").option("path", "/mnt/sepadls/bronze/Employee").saveAsTable("Employee_Ext")
Task failed
, as they might contain more details on the specific cause (e.g., disk space, permissions, or any other environmental constraints).
If none of these resolve the issue, try cleaning up the existing files in the path (/mnt/sepadls/bronze/Employee
) before running the job again, as sometimes partial writes can cause subsequent job failures.
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