Hi Fabian,
thanks for your quick response. I just figured out that I forgot to mention
a small but probably relevant detail: I am working with the streaming api.
Although there is a way to access the overall job settings, I need a
solution to "reduce" the view on configuration options available on
operator level.
For example, I would like to pass instance specific settings like an
operator identifier but there might be different operators in the overall
program.
Best
Christian
2016-01-13 10:52 GMT+01:00 Fabian Hueske <fhue...@gmail.com>:
> Hi Christian,
>
> the open method is called by the Flink workers when the parallel tasks are
> initialized.
> The configuration parameter is the configuration object of the operator.
> You can set parameters in the operator config as follows:
>
> DataSet<String> text = ...
> DataSet<Tuple2<String, Integer> wc = text.flatMap(new
> Tokenizer()).getParameters().setString("myKey", "myVal");
>
> Best, Fabian
>
>
> 2016-01-13 10:29 GMT+01:00 Christian Kreutzfeldt <mnx...@gmail.com>:
>
>> Hi
>>
>> While working on a RichFilterFunction implementation I was wondering, if
>> there is a much better way to access configuration
>> options read from file during startup. Actually, I am
>> using getRuntimeContext().getExecutionConfig().getGlobalJobParameters()
>> to get access to my settings.
>>
>> Reason for that is, that the Configuration parameter provided to the open
>> function does not carry my settings. That is probably
>> the case as I
>> use this.executionEnvironment.getConfig().setGlobalJobParameters(cfg) to
>> pass my configuration into the environment
>> which in turn is not passed on as part of the open call - I found no
>> other way to handle configuration ;-)
>>
>> My question is: who is responsible for calling the open function, where
>> does the configuration parameter has its origins aka where
>> is its content taken from and is it possible to define somewhere in the
>> main program which configuration to pass into a specific operator?
>>
>> Best
>> Christian
>>
>
>
