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https://issues.apache.org/jira/browse/SPARK-18491?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15673665#comment-15673665
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Sean Owen commented on SPARK-18491:
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You are just talking about the convenience of schema inference. You can still
design your code as you like and 'manually' specify a column type to be a date
or timestamp. If that's all this is then I suspect it reduces to a to-do to
support Java.time soon in inference.
> Spark uses mutable classes for date/time types mapping
> ------------------------------------------------------
>
> Key: SPARK-18491
> URL: https://issues.apache.org/jira/browse/SPARK-18491
> Project: Spark
> Issue Type: Improvement
> Reporter: Damian Momot
> Priority: Minor
>
> TimestampType is mapped to java.sql.Timestamp
> DateType is mapped to java.sql.Date
> Those both java types are mutable and thus their usage is highly discourage,
> especially in distributed computing which uses lazy, functional approach
> Mapping to immutable joda times should be enough for now (until scala 2.12 +
> jdk8 java.time is available for spark)
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