[jira] [Commented] (SPARK-12928) Oracle FLOAT datatype is not properly handled when reading via JDBC

["Eemeli Niemelä (JIRA)" <ji...@apache.org>]

    [ https://issues.apache.org/jira/browse/SPARK-12928?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15260031#comment-15260031 ] 

Eemeli Niemelä commented on SPARK-12928:
----------------------------------------

With pyspark this FLOAT-error appears with exception 
{noformat}
ValueError: (ValueError(u'Could not parse datatype: decimal(38,-127)',)
{noformat}

workaround: change dataframe fieldtype by hand before frame is collected, eg.

> Oracle FLOAT datatype is not properly handled when reading via JDBC
> -------------------------------------------------------------------
>
>                 Key: SPARK-12928
>                 URL: https://issues.apache.org/jira/browse/SPARK-12928
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 1.6.0
>         Environment: Oracle Database 11g Enterprise Edition   11.2.0.3.0      64bit Production
>            Reporter: Greg Michalopoulos
>            Priority: Minor
>   Original Estimate: 24h
>  Remaining Estimate: 24h
>
> When trying to read in a table from Oracle and saveAsParquet, an IllegalArgumentException is thrown when a column of FLOAT datatype is encountered.
> Below is the code being run:
> {code}val jdbcDF = sqlContext.read.format("jdbc").options(
>   Map("url" -> jdbcConnectionString,
>           "dbtable" -> "(select someFloat from someTable)",
>           "fetchSize" -> fetchSize)).load()
>   jdbcDF.saveAsParquetFile(destinationDirectory + table)
> {code}
> Here is the exception:
> {code}java.lang.IllegalArgumentException: Unsupported dataType: {"type":"struct","fields":[{"name":"someFloat","type":"decimal(38,-127)","nullable":true,"metadata":{"name":"someFloat"}}]}, [1.1] failure: `TimestampType' expected but `{' found
> {code}
> From the exception it was clear that the FLOAT datatype was presenting itself as scale -127 which appears to be the problem. 



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