Hey,
The current code supports 2 types of aggregations, simple binary reduce:
T,T=>T and also the grouped version for this, where the reduce function is
applied per a user defined key (so there we keep a map of reduced values).
This can already be used to implement fairly complex logic if we trans
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Hi Gyula,
fair enough!
I used a bad example.
What I really wanted to know is whether your code supports only
aggregation like sum, min, and max where you need to pass only a value
to the next aggregation or also more complex data structures, e.g., a
You are right, but you should never try to compute full stream median,
thats the point :D
On Tue, Apr 21, 2015 at 2:52 PM, Bruno Cadonna <
cado...@informatik.hu-berlin.de> wrote:
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> Hi Gyula,
>
> I read your comments of your PR.
>
> I have a ques
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Hi Gyula,
I read your comments of your PR.
I have a question to this comment:
"It only allows aggregations so we dont need to keep the full history
in a buffer."
What if the user implements an aggregation function like a median?
For a median you n
I have opened a PR for this feature:
https://github.com/apache/flink/pull/614
Cheers,
Gyula
On Tue, Apr 21, 2015 at 1:10 PM, Gyula Fóra wrote:
> Thats a good idea, I will modify my PR to that :)
>
> Gyula
>
> On Tue, Apr 21, 2015 at 12:09 PM, Fabian Hueske wrote:
>
>> Is it possible to switch
Thats a good idea, I will modify my PR to that :)
Gyula
On Tue, Apr 21, 2015 at 12:09 PM, Fabian Hueske wrote:
> Is it possible to switch the order of the statements, i.e.,
>
> dataStream.every(Time.of(4,sec)).reduce(...) instead of
> dataStream.reduce(...).every(Time.of(4,sec))
>
> I think tha
Is it possible to switch the order of the statements, i.e.,
dataStream.every(Time.of(4,sec)).reduce(...) instead of
dataStream.reduce(...).every(Time.of(4,sec))
I think that would be more consistent with the structure of the remaining
API.
Cheers, Fabian
2015-04-21 10:57 GMT+02:00 Gyula Fóra :
Hi Bruno,
Of course you can do that as well. (That's the good part :p )
I will open a PR soon with the proposed changes (first without breaking the
current Api) and I will post it here.
Cheers,
Gyula
On Tuesday, April 21, 2015, Bruno Cadonna
wrote:
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Hi Gyula,
I have a question regarding your suggestion.
Can the current continuous aggregation be also specified with your
proposed periodic aggregation?
I am thinking about something like
dataStream.reduce(...).every(Count.of(1))
Cheers,
Bruno
On
Hey all,
I think we are missing a quite useful feature that could be implemented
(with some slight modifications) on top of the current windowing api.
We currently provide 2 ways of aggregating (or reducing) over streams:
doing a continuous aggregation and always output the aggregated value
(whic
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