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https://issues.apache.org/jira/browse/HIVE-18831?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16388881#comment-16388881
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Sahil Takiar commented on HIVE-18831:
-------------------------------------
Before this patch the console output would look like:
{code}
Job failed with org.apache.hadoop.hive.ql.metadata.HiveException: [Error
20003]: An error occurred when trying to close the Operator running your custom
script.
FAILED: Execution Error, return code 3 from
org.apache.hadoop.hive.ql.exec.spark.SparkTask. Spark job failed during
runtime. Please check stacktrace for the root cause.
{code}
Now it looks like:
{code}
FAILED: Execution Error, return code 3 from
org.apache.hadoop.hive.ql.exec.spark.SparkTask. Spark job failed due to Spark
task failures: Job failed with
org.apache.hadoop.hive.ql.metadata.HiveException: [Error 20003]: An error
occurred when trying to close the Operator running your custom script.
{code}
So pretty much just combined these two lines and cleaned up the error message a
bit.
> Differentiate errors that are thrown by Spark tasks
> ---------------------------------------------------
>
> Key: HIVE-18831
> URL: https://issues.apache.org/jira/browse/HIVE-18831
> Project: Hive
> Issue Type: Sub-task
> Components: Spark
> Reporter: Sahil Takiar
> Priority: Major
> Attachments: HIVE-18831.1.patch
>
>
> We propagate exceptions from Spark task failures to the client well, but we
> don't differentiate between errors from HS2 / RSC vs. errors thrown by
> individual tasks.
> Main motivation is that when the client sees a propagated Spark exception its
> difficult to know what part of the excution threw the exception.
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