Hi,

Should we discuss also about the design of distinct for the stream case?
It might go well in the context of tables as well as in the context of 
aggregates over windows...

Dr. Radu Tudoran
Senior Research Engineer - Big Data Expert
IT R&D Division


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-----Original Message-----
From: Fabian Hueske (JIRA) [mailto:j...@apache.org] 
Sent: Monday, February 06, 2017 2:56 PM
To: dev@flink.apache.org
Subject: [jira] [Created] (FLINK-5722) Implement DISTINCT as dedicated operator

Fabian Hueske created FLINK-5722:
------------------------------------

             Summary: Implement DISTINCT as dedicated operator
                 Key: FLINK-5722
                 URL: https://issues.apache.org/jira/browse/FLINK-5722
             Project: Flink
          Issue Type: Improvement
          Components: Table API & SQL
    Affects Versions: 1.2.0, 1.3.0
            Reporter: Fabian Hueske


DISTINCT is currently implemented for batch Table API / SQL as an aggregate 
which groups on all fields. Grouped aggregates are implemented as GroupReduce 
with sort-based combiner.

This operator can be more efficiently implemented by using ReduceFunction and 
hinting a HashCombine strategy. The same ReduceFunction can be used for all 
DISTINCT operations and can be assigned with appropriate forward field 
annotations.

We would need a custom conversion rule which translates distinct aggregations 
(grouping on all fields and returning all fields) into a custom DataSetRelNode.



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