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Posted to issues@flink.apache.org by "Seth Wiesman (Jira)" <ji...@apache.org> on 2021/01/15 19:47:00 UTC

[jira] [Updated] (FLINK-20994) Add public method to create TableEnvironment in PyFlink

     [ https://issues.apache.org/jira/browse/FLINK-20994?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Seth Wiesman updated FLINK-20994:
---------------------------------
    Description: 
The Python table Api offers three table environment:
 * TableEnvironment
 * StreamTableEnvironment
 * BatchTableEnvironment

The `TableEnvironment` pydoc states that it a unified interface for pure table applications. However, it is currently missing a public constructor or `create` method to instantiate. This method should be added so users can leverage a unified interface and to better align pyflink with the JVM table apis.

  was:
The Python table Api offers three table environment:
 * TableEnvironment
 * StreamTableEnvironment
 * BatchTableEnvironment

The `TableEnvironment` pydoc states that it a unified interface for pure table applications. How, it is currently missing a public constructor or `create` method to instantiate. This method should be added so users can leverage a unified interface and to better align pyflink with the JVM table apis.


> Add public method to create TableEnvironment in PyFlink
> -------------------------------------------------------
>
>                 Key: FLINK-20994
>                 URL: https://issues.apache.org/jira/browse/FLINK-20994
>             Project: Flink
>          Issue Type: Improvement
>          Components: API / Python
>    Affects Versions: 1.13.0
>            Reporter: Seth Wiesman
>            Priority: Major
>
> The Python table Api offers three table environment:
>  * TableEnvironment
>  * StreamTableEnvironment
>  * BatchTableEnvironment
> The `TableEnvironment` pydoc states that it a unified interface for pure table applications. However, it is currently missing a public constructor or `create` method to instantiate. This method should be added so users can leverage a unified interface and to better align pyflink with the JVM table apis.



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