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Posted to issues@spark.apache.org by "Nathan Beyer (JIRA)" <ji...@apache.org> on 2016/09/15 22:12:21 UTC
[jira] [Commented] (SPARK-17545) Spark SQL Catalyst doesn't handle
ISO 8601 date without colon in offset
[ https://issues.apache.org/jira/browse/SPARK-17545?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15494666#comment-15494666 ]
Nathan Beyer commented on SPARK-17545:
--------------------------------------
As a workaround, the following format can be set as an option for dataframe reads:
{code}spark.read.option("dateFormat", "yyyy-MM-dd'T'HH:mm:ss.SSSXX").csv(path){code}
> 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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