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Posted to issues@systemml.apache.org by "Mike Dusenberry (JIRA)" <ji...@apache.org> on 2016/05/09 17:48:12 UTC

[jira] [Updated] (SYSTEMML-668) Python MLOutput.getDF() Can't Access JVM SQLContext

     [ https://issues.apache.org/jira/browse/SYSTEMML-668?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Mike Dusenberry updated SYSTEMML-668:
-------------------------------------
    Description: In PySpark, access to the JVM SQLContext from a PySpark SQLContext instance -has changed from {{sqlContext._scala_SQLContext}} to {{sqlContext._ssql_ctx}}- has always been official exposed via {{sqlContext._ssql_ctx}}.  However, we have been using an unofficial variable, {{sqlContext._scala_SQLContext}}, which has been renamed in 2.0, breaking any previous code using the former construct, such as our Python {{MLOutput.getDF(...)}} method.  Therefore, we just need to update our PySpark API to use the official access point.  (was: In PySpark, access to the JVM SQLContext from a PySpark SQLContext instance has changed from {{sqlContext._scala_SQLContext}} to {{sqlContext._ssql_ctx}}, breaking any previous code using the former construct, such as our Python {{MLOutput.getDF(...)}} method.)

> Python MLOutput.getDF() Can't Access JVM SQLContext
> ---------------------------------------------------
>
>                 Key: SYSTEMML-668
>                 URL: https://issues.apache.org/jira/browse/SYSTEMML-668
>             Project: SystemML
>          Issue Type: Bug
>            Reporter: Mike Dusenberry
>            Assignee: Mike Dusenberry
>            Priority: Minor
>
> In PySpark, access to the JVM SQLContext from a PySpark SQLContext instance -has changed from {{sqlContext._scala_SQLContext}} to {{sqlContext._ssql_ctx}}- has always been official exposed via {{sqlContext._ssql_ctx}}.  However, we have been using an unofficial variable, {{sqlContext._scala_SQLContext}}, which has been renamed in 2.0, breaking any previous code using the former construct, such as our Python {{MLOutput.getDF(...)}} method.  Therefore, we just need to update our PySpark API to use the official access point.



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