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https://issues.apache.org/jira/browse/SPARK-10439?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14731392#comment-14731392
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Apache Spark commented on SPARK-10439:
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User 'vanzin' has created a pull request for this issue:
https://github.com/apache/spark/pull/8606
> Catalyst should check for overflow / underflow of date and timestamp values
> ---------------------------------------------------------------------------
>
> Key: SPARK-10439
> URL: https://issues.apache.org/jira/browse/SPARK-10439
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.5.0
> Reporter: Marcelo Vanzin
> Priority: Minor
>
> While testing some code, I noticed that a few methods in {{DateTimeUtils}}
> are prone to overflow and underflow.
> For example, {{millisToDays}} can overflow the return type ({{Int}}) if a
> large enough input value is provided.
> Similarly, {{fromJavaTimestamp}} converts milliseconds to microseconds, which
> can overflow if the input is {{> Long.MAX_VALUE / 1000}} (or underflow in the
> negative case).
> There might be others but these were the ones that caught my eye.
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