Hi guys, I'm newbie in the Beam community, but as someone who has used DataFlow in the past I've been following the podling since you came to ASK. I'm very happy to see that 0.1.0-incubating is finally going out, congratulations for such great milestone.
I discussed with some of you guys in the last ApacheCon, and for me was good to know the Python SDK was just a matter of time and should come to Beam at some point. So coming back to the original plans < http://beam.incubator.apache.org/beam/python/sdk/2016/02/25/python-sdk-now-public.html>, do you manage any timeline to bring the Python SDK to Beam? So I'd like to bring a question how Beam plans to deal with the distribution of resources across all nodes, something I know it not really clean with some runners (e.g., Spark). More concretely, we're using Keras < http://keras.io/>, a deep learning Python library that is capable of running on top of either TensorFlow or Theano. Historically I know DataFlow and TensorFlow are not very compatible. But I wonder if the project has already discussed how to support running Keras (TensorFlow) tasks on Beam. For us is more for querying than for training, so I'd like to know if the Beam Model could natively support the distribution of the models (sometimes several GB). Thanks in advance. Cheers, -- Sergio Fernández Partner Technology Manager Redlink GmbH m: +43 6602747925 e: [email protected] w: http://redlink.co
