Adrian is a Cloud Data Engineer of Fabrikum LLC.
He's attempting to append data to a file saved on external storage mount points for Databricks file system (DBFS ) but getting the following error message - OSError: [Errno 95] Operation not supported.
The issue happened when he was trying to append a file from both Python and R notebooks.
What would be the possible workaround to solve the issue?
Click on the arrows to vote for the correct answer
A. B. C. D.Correct Answer: D.
Execute the append on a local disk like /tmp directory and move the entire file at the end of the operation.
The error message "OSError: [Errno 95] Operation not supported" typically occurs when attempting to perform an unsupported operation on a file system. In this case, it seems that Adrian is attempting to append data to a file saved on an external storage mount point for Databricks File System (DBFS), but the operation is not supported.
To solve the issue, there are a few possible workarounds:
A. Create a different Blob storage directory and mount it to DBFS: One possible solution is to create a different Blob storage directory and mount it to DBFS. This can be done by creating a new Blob storage account or container and using the Azure Databricks workspace to mount it as a DBFS volume. Once the new mount point is created, Adrian can attempt to append data to a file saved on this new mount point and see if the issue is resolved.
B. Import Hadoop functions and define the source and destination directory paths: Another possible solution is to import Hadoop functions and define the source and destination directory paths. This can be done by using the Hadoop Distributed File System (HDFS) API to read and write files directly to and from the external storage mount point. To do this, Adrian would need to import the Hadoop libraries and define the source and destination paths using the hdfs:// protocol.
C. Specify the full DBFS path inside the Spark read command: A third possible solution is to specify the full DBFS path inside the Spark read command. This can be done by specifying the full DBFS path to the file in the Spark read command, rather than using the external storage mount point. This will allow Adrian to read and append data to the file directly from DBFS, rather than relying on the external storage mount point.
D. Execute the append on a local disk like /tmp directory and move the entire file at the end of the operation: Finally, Adrian could execute the append on a local disk like the /tmp directory and move the entire file at the end of the operation. This can be done by writing the appended data to a local disk like /tmp and then moving the entire file to the external storage mount point at the end of the operation. This can be a slower and more complicated solution, but it may work in cases where the other solutions do not.
Ultimately, the best solution will depend on the specific use case and the nature of the external storage mount point and DBFS.