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Posted to issues@spark.apache.org by "Hyukjin Kwon (JIRA)" <ji...@apache.org> on 2019/05/21 04:24:11 UTC
[jira] [Updated] (SPARK-12072) python dataframe
._jdf.schema().json() breaks on large metadata dataframes
[ https://issues.apache.org/jira/browse/SPARK-12072?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Hyukjin Kwon updated SPARK-12072:
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Labels: bulk-closed (was: )
> python dataframe ._jdf.schema().json() breaks on large metadata dataframes
> --------------------------------------------------------------------------
>
> Key: SPARK-12072
> URL: https://issues.apache.org/jira/browse/SPARK-12072
> Project: Spark
> Issue Type: Bug
> Components: PySpark
> Affects Versions: 1.5.2
> Reporter: Rares Mirica
> Priority: Major
> Labels: bulk-closed
>
> When a dataframe contains a column with a large number of values in ml_attr, schema evaluation will routinely fail on getting the schema as json, this will, in turn, cause a bunch of problems with, eg: calling udfs on the schema because calling columns relies on _parse_datatype_json_string(self._jdf.schema().json())
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