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From Fabian Hueske <fhue...@gmail.com>
Subject Re: Create triggers
Date Mon, 02 Nov 2015 09:35:17 GMT
Hi Giacomo,

there is no direct support for use cases like yours. The main issue that it
is not possible to modify the execution of a submitted program. Once it is
running, it cannot be adapted. It is also not possible to inject a
condition into the data flow logic, e.g., if this happens follow this flow
branch, otherwise the other one.

However, the following workaround might work for you:
Once the condition to modify the running program becomes true, you can stop
the running job by filtering out all records. This is the only way to
gracefully quit a job (throwing an exception would also kill the job, but
might not work well, if you still want to store some of the jobs results).
The record filtering can be done by a filter function that read the filter
condition from a broadcast variable.
If the program finishes due to the condition, you can start a new program
with the alternative data source.

This is a bit hacky, but I don't see a different way to do it.

Cheers, Fabian

2015-10-31 11:53 GMT+01:00 Giacomo Licari <giacomo.licari@gmail.com>:

> Hi Fabian,
> thanks a lot for your solution.
>
> Just another question, do you think is possible to execute operations on C
> dataset* , *inside filter or map operators (or any operator), when some
> conditions appear, instead of waiting for the entire A dataset processing?
>
> My purposes are:
> If, while processing A dataset some conditions appear, stop executing
> operations on A dataset and execute operations on C dataset.
>
> Some pseudocode from your solution:
> DataSet<X> A = env.readFile(...);
> DataSet<X> C = env.readFile(...);
>
> A.groupBy().reduce().filter(*Check conditions here and in case start
> processing C*);
>
>
> Thanks,
> Giacomo
>
>
>
>
> On Fri, Oct 30, 2015 at 11:02 PM, Fabian Hueske <fhueske@gmail.com> wrote:
>
>> You refer to the DataSet (batch) API, right?
>>
>> In that case you can evaluate your condition in the program and fetch a
>> DataSet back to the client using List<X> myData = DataSet<X>.collect();
>> Based on the result of the collect() call you can define and execute a
>> new program.
>>
>> Note: collect() will immediately trigger the execution of the program in
>> its current state and bring the result back to the client. There is also a
>> size limitation of results that can be fetched back. This is the Akka
>> framesize which is 10MB by default but could be adapted.
>>
>> It would look similar to this:
>>
>> ExecutionEnvironment env = ...
>>
>> DataSet<X> a = env.readFile(...);
>> List<Y> b = a.groupBy().reduce().filter().collect();
>>
>> DataSet<Z> c;
>> if(b.get(0).equals(...)) {
>>   c = env.readFile(someFile);
>> } else {
>>   c = env.readFile(someOtherFile);
>> }
>>
>> c.map().groupBy().reduce()....writeAsFile(result);
>>
>> env.execute();
>>
>> Cheers, Fabian
>>
>> 2015-10-30 22:40 GMT+01:00 Giacomo Licari <giacomo.licari@gmail.com>:
>>
>>> Hi guys,
>>> I would ask to you how could I create triggers in Flink.
>>>
>>> I would like to perform some operations on a dataset and according to
>>> some conditions, based on an attribute of a Pojo class or Tuple, execute
>>> some triggers.
>>> I mean, starting collecting other datasources' data and performing
>>> operations over them.
>>>
>>> An Example.
>>> I have a dataset of Pojo class Person. My trigger activation condition
>>> is (number of italian people > 100).
>>> If so, I collect another datasource and I execute operations over it.
>>>
>>> Do you think is that possible in Flink?
>>>
>>> Thanks,
>>> Giacomo
>>>
>>
>>
>

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