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allow cluster script to update worker code on nodes (#243)

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Robert Nishihara
2016-07-11 17:58:16 -07:00
committed by Philipp Moritz
parent 86aef1bc56
commit 8952ff8cf9
3 changed files with 79 additions and 26 deletions
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doc/using-ray-on-a-cluster.md
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@@ -45,30 +45,38 @@ until the installation has completed. The standard output from the nodes will
be redirected to your terminal.
5. To check that the installation succeeded, you can ssh to each node, cd into
the directory `ray/test/`, and run the tests (e.g., `python runtest.py`).
6. Now that Ray has been installed, you can start the cluster (the scheduler,
object stores, and workers) with the command
`start_ray("/home/ubuntu/ray/scripts/default_worker.py")`, where the second
argument is the path on each node in the cluster to the worker code that you
would like to use. After completing successfully, this command will print out a
command that can be run on the head node to attach a shell (the driver) to the
cluster. For example,
6. Create a directory (for example, `mkdir ~/example_ray_code`) containing the
worker `worker.py` code along with the code for any modules imported by
`worker.py`. For example,
```
cp ray/scripts/default_worker.py ~/example_ray_code/worker.py
cp ray/scripts/example_functions.py ~/example_ray_code/
```
7. Start the cluster (the scheduler, object stores, and workers) with the
command `start_ray("~/example_ray_code")`, where the second argument is the
local path to the worker code that you would like to use. This command will copy
the worker code to each node and will start the cluster. After completing
successfully, this command will print out a command that can be run on the head
node to attach a shell (the driver) to the cluster. For example,
```
source "$RAY_HOME/setup-env.sh";
python "$RAY_HOME/scripts/shell.py" --scheduler-address=52.50.28.103:10001 --objstore-address=52.50.28.103:20001 --worker-address=52.50.28.103:30001 --attach
python "$RAY_HOME/scripts/shell.py" --scheduler-address=12.34.56.789:10001 --objstore-address=12.34.56.789:20001 --worker-address=12.34.56.789:30001 --attach
```
7. Note that there are several more commands that can be run from within
8. Note that there are several more commands that can be run from within
`cluster.py`.
- `install_ray()` - This pulls the Ray source code on each node, builds all
of the third party libraries, and builds the project itself.
- `start_ray(worker_path, num_workers_per_node=10)` - This starts a
- `start_ray(worker_directory, num_workers_per_node=10)` - This starts a
scheduler process on the head node, and it starts an object store and some
workers on each node.
- `stop_ray()` - This shuts down the cluster (killing all of the processes).
- `restart_workers(worker_path, num_workers_per_node=10)` - This kills the
current workers and starts new workers using the worker code from the
- `restart_workers(worker_directory, num_workers_per_node=10)` - This kills
the current workers and starts new workers using the worker code from the
given file. Currently, this can only run when there are no tasks currently
executing on any of the workers.
- `update_ray()` - This pulls the latest Ray source code and builds it.