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Posted to issues@spark.apache.org by "Maciej Bryński (JIRA)" <ji...@apache.org> on 2016/10/21 03:39:58 UTC
[jira] [Comment Edited] (SPARK-18022)
java.lang.NullPointerException instead of real exception when saving DF to
MySQL
[ https://issues.apache.org/jira/browse/SPARK-18022?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15593846#comment-15593846 ]
Maciej Bryński edited comment on SPARK-18022 at 10/21/16 3:39 AM:
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Only improvement in error handling.
Because right now I'm getting only NPE and have to guess whats the real reason of error.
was (Author: maver1ck):
Only improvement in error handling.
> java.lang.NullPointerException instead of real exception when saving DF to MySQL
> --------------------------------------------------------------------------------
>
> Key: SPARK-18022
> URL: https://issues.apache.org/jira/browse/SPARK-18022
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.0.1
> Reporter: Maciej Bryński
> Priority: Minor
>
> Hi,
> I have found following issue.
> When there is an exception while saving dataframe to MySQL I'm unable to get it.
> Instead of I'm getting following stacktrace.
> {code}
> 16/10/20 06:00:35 WARN TaskSetManager: Lost task 56.0 in stage 10.0 (TID 3753, dwh-hn28.adpilot.co): java.lang.NullPointerException: Cannot suppress a null exception.
> at java.lang.Throwable.addSuppressed(Throwable.java:1046)
> at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$.savePartition(JdbcUtils.scala:256)
> at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:314)
> at org.apache.spark.sql.execution.datasources.jdbc.JdbcUtils$$anonfun$saveTable$1.apply(JdbcUtils.scala:313)
> at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$28.apply(RDD.scala:902)
> at org.apache.spark.rdd.RDD$$anonfun$foreachPartition$1$$anonfun$apply$28.apply(RDD.scala:902)
> at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1916)
> at org.apache.spark.SparkContext$$anonfun$runJob$5.apply(SparkContext.scala:1916)
> at org.apache.spark.scheduler.ResultTask.runTask(ResultTask.scala:70)
> at org.apache.spark.scheduler.Task.run(Task.scala:86)
> at org.apache.spark.executor.Executor$TaskRunner.run(Executor.scala:274)
> at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
> at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
> at java.lang.Thread.run(Thread.java:745)
> {code}
> The real exception could be for example duplicate on primary key etc.
> With this it's very difficult to debugging apps.
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