[
https://issues.apache.org/jira/browse/SPARK-7196?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14521240#comment-14521240
]
Liang-Chi Hsieh commented on SPARK-7196:
----------------------------------------
[~kgeis] I can't reproduce your problem. As I test in unit test, after applying
the [pr|https://github.com/apache/spark/pull/5777], the decimal type have
precision and scale now through jdbc. Can you check if you apply the pr and
your data schema in original database? If both are checked, can you give us a
snippet of example data for test? Thanks.
> decimal precision lost when loading DataFrame from JDBC
> -------------------------------------------------------
>
> Key: SPARK-7196
> URL: https://issues.apache.org/jira/browse/SPARK-7196
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 1.3.1
> Reporter: Ken Geis
>
> I have a decimal database field that is defined as 10.2 (i.e. ##########.##).
> When I load it into Spark via sqlContext.jdbc(..), the type of the
> corresponding field in the DataFrame is DecimalType, with precisionInfo None.
> Because of that loss of precision information, SPARK-4176 is triggered when I
> try to .saveAsTable(..).
--
This message was sent by Atlassian JIRA
(v6.3.4#6332)
---------------------------------------------------------------------
To unsubscribe, e-mail: [email protected]
For additional commands, e-mail: [email protected]
