Regarding the ‘partiality’ you mention in option one, wouldn’t you have to give 
that up anyway to maintain exactly once processing? Suppose input message A 
results in asynchronous queries/futures B and C, and imagine the following 
series of events:

1.       Your function receives A

2.       Asynchronous calls start for B and C

3.       B completes, and its result is immediately emitted.

4.       Your job is restarted before C returns

How would Flink restart the job without either dropping C or duplicating B?  I 
think the only answer is for the function to hold on to results generated by A 
until they have all completed, then emit them all at once, and I have a 
suspicion that under the hood, that’s what a flat map is doing.

From: Konstantinos Barmpis [mailto:konstantinos.barm...@york.ac.uk]
Sent: Thursday, July 12, 2018 8:42 AM
To: user@flink.apache.org
Subject: Regarding the use of RichAsyncFunction as a FlatMap

I was wondering if there is a way to create an asynchronous flatmap function in 
Flink.

As far as I am aware, the asynchronous function only accepts a single result 
future as its return (which can be the aggregate list of the flatmap, but then 
partiality is lost as we have to wait for all of the results to be aggregated 
before returning).

Alternatively, using a normal FlatMap seems to require a way to keep the 
current instance alive as it waits for the results and emits them one at a 
time, as otherwise Flink may consider it terminated (as the function call 
returns immediately) and close the channel.

Is there some third option I am unaware of (or using one of the above two in a 
different way?),

Cheers.




--
Konstantinos Barmpis | Research Associate
White Rose Grid Enterprise Systems Group
Dept. of Computer Science
University of York
Tel: +44 (0) 1904-32 5653

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