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Posted to issues@spark.apache.org by "Takuya Ueshin (JIRA)" <ji...@apache.org> on 2017/06/12 20:09:01 UTC
[jira] [Resolved] (SPARK-17914) Spark SQL casting to TimestampType
with nanosecond results in incorrect timestamp
[ https://issues.apache.org/jira/browse/SPARK-17914?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Takuya Ueshin resolved SPARK-17914.
-----------------------------------
Resolution: Fixed
Fix Version/s: 2.3.0
2.2.1
Issue resolved by pull request 18252
[https://github.com/apache/spark/pull/18252]
> Spark SQL casting to TimestampType with nanosecond results in incorrect timestamp
> ---------------------------------------------------------------------------------
>
> Key: SPARK-17914
> URL: https://issues.apache.org/jira/browse/SPARK-17914
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.6.1
> Reporter: Oksana Romankova
> Assignee: Anton Okolnychyi
> Fix For: 2.2.1, 2.3.0
>
>
> In some cases when timestamps contain nanoseconds they will be parsed incorrectly.
> Examples:
> "2016-05-14T15:12:14.0034567Z" -> "2016-05-14 15:12:14.034567"
> "2016-05-14T15:12:14.000345678Z" -> "2016-05-14 15:12:14.345678"
> The issue seems to be happening in DateTimeUtils.stringToTimestamp(). It assumes that only 6 digit fraction of a second will be passed.
> With this being the case I would suggest either discarding nanoseconds automatically, or throw an exception prompting to pre-format timestamps to microsecond precision first before casting to the Timestamp.
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