Problem

When you attempt to rerun an Apache Spark write operation by cancelling the currently running job, the following error occurs:

Error: org.apache.spark.sql.AnalysisException: Cannot create the managed table('`testdb`.` testtable`').
The associated location ('dbfs:/user/hive/warehouse/testdb.db/metastore_cache_ testtable) already exists.;

Cause

This problem is due to a change in the default behavior of Spark in version 2.4.

This problem can occur if:

• The cluster is terminated while a write operation is in progress.
• A temporary network issue occurs.
• The job is interrupted.

Once the metastore data for a particular table is corrupted, it is hard to recover except by dropping the files in that location manually. Basically, the problem is that a metadata directory called _STARTED isn’t deleted automatically when Databricks tries to overwrite it.

You can reproduce the problem by following these steps:

1. Create a DataFrame:
   val df = spark.range(1000)
2. Write the DataFrame to a location in overwrite mode:
   df.write.mode(SaveMode.Overwrite).saveAsTable("testdb.testtable")
3. Cancel the command while it is executing.
4. Re-run the write command.

Solution

Set the flag spark.sql.legacy.allowCreatingManagedTableUsingNonemptyLocation to true . This flag deletes the _STARTED directory and returns the process to the original state. For example, you can set it in the notebook:

%python
spark.conf.set("spark.sql.legacy.allowCreatingManagedTableUsingNonemptyLocation","true")

Or you can set it in the cluster level Spark config ( AWS | Azure | GCP ):

spark.sql.legacy.allowCreatingManagedTableUsingNonemptyLocation true

Another option is to manually clean up the data directory specified in the error message. You can do this with dbutils.fs.rm .

%scala
dbutils.fs.rm("<path-to-directory>", true)