Hi,
I have a topology which process events and aggregates them in some form and
performs some prediction based on a machine learning (ML) model. Every x
events the one of the bolt involved in the normal processing emit an
"trainModel" event, which is routed to a bolt which is just dedicated to
the training. One the training is done, the new model should be send back
to the prediction bolt. The topology looks like:
InputSpout -> AggregationBolt -> PredictionBolt -> OutputBolt
| /\
\/ |
TrainingBolt -------------+
This works all fine, but I am now not sure how I can get the model back.
My first idea was to connect the normal prediction bolt to the training
bolt, but this does not work, because the input tuple can have ether events
or a model. So I write something like :
input.getBinaryByField("model");
An exception is thrown if the bolt was triggered by an event. Is there way
to distinguish from which bolt / stream the current bolt was triggered?
Cheers,
Klaus
