I've set up a distributed system using dask. When I start the scheduler using the Python API, the dask scheduler doesn't mention starting the dashboard. As expected, I can not reach it on the address I would expect it to be.
Since bokeh is installed, I'd expect the dashboard to be started. When I start the scheduler using the command line however, the dashboard starts correctly. Why is it that starting the scheduler through the python api does not start the dashboard?
Relevant information:
- python 3.6.7
- dask 1.0.0
- dask-glm 0.2.0
- dask-ml 0.11.0
- distributed 1.25.1
- bokeh 1.0.3
- tornado 5.1.1 (also tried with 4.5)
Output scheduler (via python api):
orval$ python3 myscheduler.py
distributed.scheduler - INFO - Clear task state
distributed.scheduler - INFO - Scheduler at: tcp://10.33.14.65:8786
Code myscheduler.py:
from distributed import Scheduler
from tornado.ioloop import IOLoop
from threading import Thread
s = Scheduler()
s.start('tcp://:8786') # Listen on TCP port 8786
loop = IOLoop.current()
loop.start()
Starting the scheduler through the command line:
distributed.scheduler - INFO - -----------------------------------------------
distributed.scheduler - INFO - Clear task state
distributed.scheduler - INFO - Scheduler at: tcp://10.33.14.65:8786
distributed.scheduler - INFO - bokeh at: :8787
distributed.scheduler - INFO - Local Directory: /tmp/scheduler-pg2wz3cg
distributed.scheduler - INFO - -----------------------------------------------