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https://issues.apache.org/jira/browse/SPARK-7196?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=14522901#comment-14522901
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Ken Geis commented on SPARK-7196:
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I think the problem may be specific to Oracle. If I insert 19999 into a
NUMBER(12,2) Oracle field and retrieve it, the result is 19999. In H2, I do the
same thing, and I get back 19999.00.
I think that Spark is assuming incorrectly that BigDecimals coming out of
result sets have the same scale as the maximum scale allowed for the column.
> 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
> Assignee: Liang-Chi Hsieh
> Fix For: 1.3.2, 1.4.0
>
>
> 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(..).
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