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https://issues.apache.org/jira/browse/SPARK-10439?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14737644#comment-14737644
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Davies Liu commented on SPARK-10439:
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There are many places there could be overflow, even for A + B, so I think it's
not big deal.
If we really want to handle them gracefully, those bound checking should be
performed during inbound, turn them into null if overflow, not crash (raise
exception).
> 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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