[jira] [Resolved] (SPARK-30788) Support `SimpleDateFormat` and `FastDateFormat` as legacy date/timestamp formatters

["Wenchen Fan (Jira)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-30788?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Wenchen Fan resolved SPARK-30788.
---------------------------------
    Fix Version/s: 3.0.0
       Resolution: Fixed

Issue resolved by pull request 27524
[https://github.com/apache/spark/pull/27524]

> Support `SimpleDateFormat` and `FastDateFormat` as legacy date/timestamp formatters
> -----------------------------------------------------------------------------------
>
>                 Key: SPARK-30788
>                 URL: https://issues.apache.org/jira/browse/SPARK-30788
>             Project: Spark
>          Issue Type: Improvement
>          Components: SQL
>    Affects Versions: 3.0.0
>            Reporter: Maxim Gekk
>            Assignee: Maxim Gekk
>            Priority: Major
>             Fix For: 3.0.0
>
>
> To be absolutely sure that Spark 3.0 is compatible with 2.4 when spark.sql.legacy.timeParser.enabled is set to true, need to support SimpleDateFormat and FastDateFormat as legacy parsers/formatters in TimestampFormatter. 
> Spark 2.4.x uses the following parsers for parsing/formatting date/timestamp strings:
> # DateTimeFormat in CSV/JSON datasource
> # SimpleDateFormat - is used in JDBC datasource, in partitions parsing.
> # SimpleDateFormat in strong mode (lenient = false). It is used by the date_format, from_unixtime, unix_timestamp and to_unix_timestamp functions.
> Spark 3.0 should use the same parsers in those cases.



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