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