[
https://issues.apache.org/jira/browse/SPARK-39348?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17686390#comment-17686390
]
Wei Guo commented on SPARK-39348:
---------------------------------
After PR [https://github.com/apache/spark/pull/26559,] it has been removed.
* Since Spark 2.4, creating a managed table with nonempty location is not
allowed. An exception is thrown when attempting to create a managed table with
nonempty location. To set {{true}} to
{{spark.sql.legacy.allowCreatingManagedTableUsingNonemptyLocation}} restores
the previous behavior. This option will be removed in Spark 3.0.
> Create table in overwrite mode fails when interrupted
> -----------------------------------------------------
>
> Key: SPARK-39348
> URL: https://issues.apache.org/jira/browse/SPARK-39348
> Project: Spark
> Issue Type: Bug
> Components: Input/Output
> Affects Versions: 3.1.1
> Reporter: Max
> Priority: Major
>
> When you attempt to rerun an Apache Spark write operation by cancelling the
> currently running job, the following error occurs:
> {code:java}
> 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.;{code}
> 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.
> You can reproduce the problem by following these steps:
> 1. Create a DataFrame:
> {code:java}
> val df = spark.range(1000){code}
> 2. Write the DataFrame to a location in overwrite mode:
> {code:java}
> df.write.mode(SaveMode.Overwrite).saveAsTable("testdb.testtable"){code}
> 3. Cancel the command while it is executing.
> 4. Re-run the {{write}} command.
--
This message was sent by Atlassian Jira
(v8.20.10#820010)
---------------------------------------------------------------------
To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org
For additional commands, e-mail: issues-h...@spark.apache.org
