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Posted to issues@spark.apache.org by "Andy Grove (Jira)" <ji...@apache.org> on 2022/03/08 18:51:00 UTC
[jira] [Commented] (SPARK-30788) Support `SimpleDateFormat` and `FastDateFormat` as legacy date/timestamp formatters
[ https://issues.apache.org/jira/browse/SPARK-30788?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17503123#comment-17503123 ]
Andy Grove commented on SPARK-30788:
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[~cloud_fan] [~maxgekk] I think the fix version on this issue should be 3.3.0 and not 3.0.0 ?
> 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: Max Gekk
> Assignee: Max 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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