Issue
I am setting up a cluster for running image analysis (moving from MPI to Dask and Dask.distributed). I connect to the master node via tunneling and I don't know how to access bokeh server.
Steps
1. Connect to my server master node via ssh tunneling:ssh -L 7000:localhost:7000 [email protected]
2. Start dask-scheduler --port 7001 --bokeh 7002
3. ssh to the nodes I want to use (also tunneling on port 7000) and start dask-worker --memory-limit=200e9
4. Start a jupyter notebook --port=7000 --no-browser and open a chromesession and point the browser to localhost:7000
5. Start a Client() pointing to the scheduler address
6. X11 forwarding is broken and I cannot use it from my laptop
When I look at the output from the dask-scheduler page i get:
distributed.scheduler - INFO - -----------------------------------------------
distributed.scheduler - INFO - Scheduler at: tcp://130.237.132.207:7001
distributed.scheduler - INFO - http at: 0.0.0.0:9786
distributed.scheduler - INFO - bokeh at: 0.0.0.0:7002
distributed.scheduler - INFO - Local Directory: /tmp/scheduler-4we9jlcj
distributed.scheduler - INFO - -----------------------------------------------
distributed.scheduler - INFO - Register tcp://192.168.0.3:43973
distributed.scheduler - INFO - Starting worker compute stream,
tcp://192.168.0.3:43973
distributed.scheduler - INFO - Receive client connection: Client-6967349a-
872f-11e7-a595-0cc47a8ebf44
and the client seems to connect correctly to the workers:
Scheduler: tcp://130.237.132.207:7001
Dashboard: http://130.237.132.207:7002
Workers: 1
Cores: 56
Memory: 200.00 GB
Questions
1) Is it correct to point the browser to port 7000 instead of port 7001 where the schedule is set? FYI: I cannot load anything from the browser if I use localhost:7001 or any of the IP addressed of scheduler and dashboard.
2) How can I get access to the bokeh graph to evaluate performance?
3) Additional bonus: is there a way that I can start multiple workers with dask-ssh and passing parameters such as --memory-limit
Thanks!