spark-issues mailing list archives

Site index · List index
Message view « Date » · « Thread »
Top « Date » · « Thread »
From "holdenk (JIRA)" <>
Subject [jira] [Commented] (SPARK-12072) python dataframe ._jdf.schema().json() breaks on large metadata dataframes
Date Tue, 01 Dec 2015 21:01:11 GMT


holdenk commented on SPARK-12072:

Around what # of attrs are you seeing failures at? Do you think we should instead pass the
schema as native Java objects and add some utils for Python to work with them?

> python dataframe ._jdf.schema().json() breaks on large metadata dataframes
> --------------------------------------------------------------------------
>                 Key: SPARK-12072
>                 URL:
>             Project: Spark
>          Issue Type: Bug
>          Components: PySpark
>    Affects Versions: 1.5.2
>            Reporter: Rares Mirica
> 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())

This message was sent by Atlassian JIRA

To unsubscribe, e-mail:
For additional commands, e-mail:

View raw message