You are viewing a plain text version of this content. The canonical link for it is here.

Posted to issues@flink.apache.org by "Huang Xingbo (Jira)" <ji...@apache.org> on 2021/01/12 04:41:00 UTC

[jira] [Created] (FLINK-20933) Config Python Operator Use Managed Memory In Python DataStream

Huang Xingbo created FLINK-20933:
------------------------------------

             Summary: Config Python Operator Use Managed Memory In Python DataStream
                 Key: FLINK-20933
                 URL: https://issues.apache.org/jira/browse/FLINK-20933
             Project: Flink
          Issue Type: Bug
          Components: API / Python
    Affects Versions: 1.12.0, 1.13.0
            Reporter: Huang Xingbo


Now the way to set `Python DataStream Operator` to use managed memory is to set a hook in the `execute` method of `Python StreamExecutionEnvironment` to traverse the `StreamGraph` and set the `Python Operator` to use managed memory.
But when the user’s job uses `from_data_stream` to convert the `DataStream` to a `Table`, the `TableEnvironment.execute` method is used at the end rather than `StreamExecutionEnvironment.execute`, so the `Python DataStream` related operators will not have `Managed Memory` set.



--
This message was sent by Atlassian Jira
(v8.3.4#803005)