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https://issues.apache.org/jira/browse/SPARK-20427?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16529013#comment-16529013
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Yuming Wang commented on SPARK-20427:
-------------------------------------

[~ORichard]. Please try to use {{customSchema}} to specifying the custom data 
types of the read schema.  
https://github.com/apache/spark/blob/v2.3.1/examples/src/main/scala/org/apache/spark/examples/sql/SQLDataSourceExample.scala#L197




> Issue with Spark interpreting Oracle datatype NUMBER
> ----------------------------------------------------
>
>                 Key: SPARK-20427
>                 URL: https://issues.apache.org/jira/browse/SPARK-20427
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.1.0
>            Reporter: Alexander Andrushenko
>            Assignee: Yuming Wang
>            Priority: Major
>             Fix For: 2.3.0
>
>
> In Oracle exists data type NUMBER. When defining a filed in a table of type 
> NUMBER the field has two components, precision and scale.
> For example, NUMBER(p,s) has precision p and scale s. 
> Precision can range from 1 to 38.
> Scale can range from -84 to 127.
> When reading such a filed Spark can create numbers with precision exceeding 
> 38. In our case it has created fields with precision 44,
> calculated as sum of the precision (in our case 34 digits) and the scale (10):
> "...java.lang.IllegalArgumentException: requirement failed: Decimal precision 
> 44 exceeds max precision 38...".
> The result was, that a data frame was read from a table on one schema but 
> could not be inserted in the identical table on other schema.



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