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https://issues.apache.org/jira/browse/FLINK-17074?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=17264243#comment-17264243
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Theo Diefenthal commented on FLINK-17074:
-----------------------------------------

What would now be the preferred approach to select multiple fields from a POJO 
as key? Say I have a POJO with 10 fields and I want to use three of them (with 
different types) as key. With the old API, I just specified the three field 
names. Now I need to build up a KeySelector, create a tuple and put my fields 
in there and build up proper field types deduced from the POJO field types 
myself? Is there a utility method somewhere?

> Deprecate DataStream.keyBy() that use tuple/expression keys
> -----------------------------------------------------------
>
>                 Key: FLINK-17074
>                 URL: https://issues.apache.org/jira/browse/FLINK-17074
>             Project: Flink
>          Issue Type: Improvement
>          Components: API / DataStream, API / Scala
>            Reporter: Aljoscha Krettek
>            Assignee: Etienne Chauchot
>            Priority: Major
>              Labels: pull-request-available, starter
>             Fix For: 1.11.0
>
>
> Currently you can either specify a {{KeySelector}}, tuple positions, and 
> expression keys? I think {{KeySelectors}} are strictly superior and with 
> lambdas (or function references) quite easy to use.  Tuple/expression keys 
> use reflection underneath to do the field accesses, so performance is 
> strictly worse. Also, when using a {{KeySelector}} you will have a meaningful 
> key type {{KEY}} in your operations while for tuple/expression keys the key 
> type is simply {{Tuple}}.
> Tuple/expression keys were introduced before Java got support for lambdas in 
> Java 8 and before we added the Table API. Nowadays, using a lambda is little 
> more typing than using an expression key but is (possibly) faster and more 
> type safe. The Table API should be used for these more 
> expression-based/relational use cases.



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