A team member came up with a clever solution. For anyone's reference, one way is to place the Gradient Boosting Decision Tree classification part (via XGBoost) in a separate Python process, to get around logging that can raise errors. Then the Storm bolt can communicate with that via a multiprocessing library. Related links:
- http://stackoverflow.com/questions/6920858/ interprocess-communication-in-python <http://stackoverflow.com/questions/6920858/interprocess-communication-in-python> - https://docs.python.org/3/library/multiprocessing.html On Wed, Apr 12, 2017 at 1:20 AM, Derek S. Chan <[email protected]> wrote: > Hi All, > > I'm part of a graduate team at UC Berkeley. In Storm, does anyone know > how users can silence logging from XGBoost's predict (not train) method? My > team has been delayed for several days, unclear how to get around this > logging issue, and seeks to overcome ASAP. > > Thanks, > Derek >
