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https://issues.apache.org/jira/browse/SPARK-17545?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15496525#comment-15496525
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Sean Owen commented on SPARK-17545:
-----------------------------------

I think it depends on how hard it is to handle the quirk and whether it causes 
other problems. It's probably not too hard to also handle this one and not that 
dangerous. If you want to open a PR we can look at it.

> Spark SQL Catalyst doesn't handle ISO 8601 date without colon in offset
> -----------------------------------------------------------------------
>
>                 Key: SPARK-17545
>                 URL: https://issues.apache.org/jira/browse/SPARK-17545
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.0.0
>            Reporter: Nathan Beyer
>
> When parsing a CSV with a date/time column that contains a variant ISO 8601 
> that doesn't include a colon in the offset, casting to Timestamp fails.
> Here's a simple, example CSV content.
> {quote}
> time
> "2015-07-20T15:09:23.736-0500"
> "2015-07-20T15:10:51.687-0500"
> "2015-11-21T23:15:01.499-0600"
> {quote}
> Here's the stack trace that results from processing this data.
> {quote}
> 16/09/14 15:22:59 ERROR Utils: Aborting task
> java.lang.IllegalArgumentException: 2015-11-21T23:15:01.499-0600
>       at 
> org.apache.xerces.jaxp.datatype.XMLGregorianCalendarImpl$Parser.skip(Unknown 
> Source)
>       at 
> org.apache.xerces.jaxp.datatype.XMLGregorianCalendarImpl$Parser.parse(Unknown 
> Source)
>       at 
> org.apache.xerces.jaxp.datatype.XMLGregorianCalendarImpl.<init>(Unknown 
> Source)
>       at 
> org.apache.xerces.jaxp.datatype.DatatypeFactoryImpl.newXMLGregorianCalendar(Unknown
>  Source)
>       at 
> javax.xml.bind.DatatypeConverterImpl._parseDateTime(DatatypeConverterImpl.java:422)
>       at 
> javax.xml.bind.DatatypeConverterImpl.parseDateTime(DatatypeConverterImpl.java:417)
>       at 
> javax.xml.bind.DatatypeConverter.parseDateTime(DatatypeConverter.java:327)
>       at 
> org.apache.spark.sql.catalyst.util.DateTimeUtils$.stringToTime(DateTimeUtils.scala:140)
>       at 
> org.apache.spark.sql.execution.datasources.csv.CSVTypeCast$.castTo(CSVInferSchema.scala:287)
> {quote}
> Somewhat related, I believe Python standard libraries can produce this form 
> of zone offset. The system I got the data from is written in Python.
> https://docs.python.org/2/library/datetime.html#strftime-strptime-behavior



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