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https://issues.apache.org/jira/browse/SPARK-30668?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17025651#comment-17025651
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Maxim Gekk commented on SPARK-30668:
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> This is not mentioned in the migration guide.
It is mentioned:
{code}
- The `unix_timestamp`, `date_format`, `to_unix_timestamp`,
`from_unixtime`, `to_date`, `to_timestamp` functions. New implementation
supports pattern formats as described here
https://docs.oracle.com/javase/8/docs/api/java/time/format/DateTimeFormatter.html
and performs strict checking of its input. For example, the `2015-07-22
10:00:00` timestamp cannot be parse if pattern is `yyyy-MM-dd` because the
parser does not consume whole input. Another example is the `31/01/2015 00:00`
input cannot be parsed by the `dd/MM/yyyy hh:mm` pattern because `hh` supposes
hours in the range `1-12`.
{code}
> Do we have a simple way to remove such a behavior change?
The change is related to the migration to Proleptic Gregorian calendar. To
remove the behavior, you need to revert most of
https://issues.apache.org/jira/browse/SPARK-26651 and maybe more.
> For example, converting the pattern for users?
Even it is possible to convert patterns, the result can be different for old
dates due to the calendar system.
> Can we let users choose different parsing mechanisms between SimpleDateFormat
> and DateTimeFormat?
No, a flag was removed 1 year ago, see
https://issues.apache.org/jira/browse/SPARK-26503 and see
https://github.com/apache/spark/pull/23391#discussion_r244414750
> to_timestamp failed to parse 2020-01-27T20:06:11.847-0800 using pattern
> "yyyy-MM-dd'T'HH:mm:ss.SSSz"
> ----------------------------------------------------------------------------------------------------
>
> Key: SPARK-30668
> URL: https://issues.apache.org/jira/browse/SPARK-30668
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 3.0.0
> Reporter: Xiao Li
> Priority: Blocker
>
> {code:java}
> SELECT to_timestamp("2020-01-27T20:06:11.847-0800",
> "yyyy-MM-dd'T'HH:mm:ss.SSSz")
> {code}
> This can return a valid value in Spark 2.4 but return NULL in the latest
> master
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