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From "ASF GitHub Bot (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (FLINK-5768) Apply new aggregation functions for datastream and dataset tables
Date Wed, 01 Mar 2017 08:40:45 GMT

    [ https://issues.apache.org/jira/browse/FLINK-5768?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=15889775#comment-15889775
] 

ASF GitHub Bot commented on FLINK-5768:
---------------------------------------

Github user fhueske commented on the issue:

    https://github.com/apache/flink/pull/3423
  
    Hi @shaoxuan-wang, sorry. I missed your comment. If you haven't started reworking the
batch aggregations yet, I agree to do it later and just change the merging to smaller batches.

    
    So far, we always put an emphasis on robustness and tried to avoid memory issues as much
as possible. In batch, most of the JVM memory is maintained by Flink and not available for
regular user-function objects. So I'd suggest to be a bit conservative here and batch 16 rows.
We can also run a few benchmarks to check how much the parameter affects the performance.


> Apply new aggregation functions for datastream and dataset tables
> -----------------------------------------------------------------
>
>                 Key: FLINK-5768
>                 URL: https://issues.apache.org/jira/browse/FLINK-5768
>             Project: Flink
>          Issue Type: Sub-task
>          Components: Table API & SQL
>            Reporter: Shaoxuan Wang
>            Assignee: Shaoxuan Wang
>
> Apply new aggregation functions for datastream and dataset tables
> This includes:
> 1. Change the implementation of the DataStream aggregation runtime code to use new aggregation
functions and aggregate dataStream API.
> 2. DataStream will be always running in incremental mode, as explained in 06/Feb/2017
in FLINK5564.
> 2. Change the implementation of the Dataset aggregation runtime code to use new aggregation
functions.
> 3. Clean up unused class and method.



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