Web UI Documentation (#983)

* Initial Draft of Documentation

* Cleanup

* Fix line lengths and modify some text.

doc/source/index.rst

@@ -21,6 +21,7 @@ Ray
    actors.rst
    using-ray-with-gpus.rst
    rllib.rst
+   webui.rst
 
 .. toctree::
    :maxdepth: 1

doc/source/webui.rst

@@ -0,0 +1,142 @@
+Web UI
+======
+
+Dependencies
+------------
+
+To use the UI, you will need to install the following.
+
+.. code-block:: bash
+
+  pip install jupyter ipywidgets bokeh
+
+If you see an error like
+
+.. code-block:: bash
+
+  Widget Javascript not detected. It may not be installed properly.
+
+Then you may need to run the following.
+
+.. code-block:: bash
+
+  jupyter nbextension enable --py --sys-prefix widgetsnbextension
+
+**Note:** If you are building Ray from source, then you will also need a
+``python2`` executable.
+
+Running the Web UI
+------------------
+
+Currently, the web UI is launched automatically when ``ray.init`` is called. The
+command will print a URL of the form:
+
+.. code-block:: text
+
+  =============================================================================
+  View the web UI at http://localhost:8889/notebooks/ray_ui92131.ipynb?token=89354a314e5a81bf56e023ad18bda3a3d272ee216f342938
+  =============================================================================
+
+If you are running Ray on your local machine, then you can head directly to that
+URL with your browser to see the Jupyter notebook. Otherwise, if you are using
+Ray remotely, such as on EC2, you will need to ensure that port is open on that
+machine. Typically, when you ssh into the machine, you can also port forward
+with the ``-L`` option as such:
+
+.. code-block:: bash
+
+  ssh -L <port>:localhost:<port> <user>@<ip-address>
+
+So for the above URL, you would use the port 8889. The Jupyter notebook attempts
+to run on port 8888, but if that fails it tries successive ports until it finds
+an open port.
+
+You can also open the port on the machine as well, which is not recommended for
+security as the machine would be open to the Internet. In this case, you would
+need to replace localhost by the public IP the remote machine is using.
+
+Once you have navigated to the URL, start the UI by clicking on the following.
+
+.. code-block:: text
+
+  Kernel -> Restart and Run all
+
+Features
+--------
+
+The UI supports a search for additional details on Task IDs and Object IDs, a
+task timeline, a distribution of task completion times, and time series for CPU
+utilization and cluster usage.
+
+Task and Object IDs
+~~~~~~~~~~~~~~~~~~~
+
+These widgets show additional details about an object or task given the ID. If
+you have the object in Python, the ID can be found by simply calling ``.hex`` on
+an Object ID as below:
+
+.. code-block:: python
+
+   # This will return a hex string of the ID.
+   objectid = ray.put(1)
+   literal_id = objectid.hex()
+
+and pasting in the returned string with no quotes. Otherwise, they can be found
+in the task timeline in the output area below the timeline when you select a
+task.
+
+For Task IDs, they can be found by searching for an object ID the task created,
+or via the task timeline in the output area.
+
+The additional details for tasks here can also be found in the task timeline;
+the search just provides an easier method to find a specific task when you have
+millions.
+
+Task Timeline
+~~~~~~~~~~~~~
+
+There are three components to this widget: the controls for the widget at the
+top, the timeline itself, and the details area at the bottom. In the controls,
+you first select whether you want to select a subset of tasks via the time they
+were completed or by the number of tasks. You can control the percentages either
+via a double sided slider, or by setting specific values in the text boxes. If
+you choose to select by the number of tasks, then entering a negative number N
+in the text field denotes the last N tasks run, while a positive value N denotes
+the first N tasks run. If there are ten tasks and you enter -1 into the field,
+then the slider will show 90% to 100%, where 1 would show 0% to 10%. Finally,
+you can choose if you want edges for task submission (if a task invokes another
+task) or object dependencies (if the result from a task is passed to another
+task) to be added, and if you want the different phases of a task broken up into
+separate tasks in the timeline.
+
+For the timeline, each node has its own dropdown with a timeline, and each row
+in the dropdown is a worker. Moving and zooming are handled by selecting the
+appropiate icons on the floating taskbar. The first is selection, the second
+panning, the third zooming, and the fourth timing. To shown edges, you can
+enable Flow Events in View Options.
+
+If you have selection enabled in the floating taskbar and select a task, then
+the details area at the bottom will fill up with information such as task ID,
+function ID, and the duration in seconds of each phase of the task.
+
+Time Distributions and Time Series
+~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
+
+The completion time distribution, CPU utilization, and cluster usage all have
+the same task selection controls as the task timeline.
+
+The task completion time distribution tracks the histogram of completion tasks
+for all tasks selected.
+
+CPU utilization gives you a count of how many CPU cores are being used at a
+given time. As typically each core has a worker assigned to it, this is
+equivalent to utilization of the workers running in Ray.
+
+Cluster Usage gives you a heat-map with time on the x-axis, node IP addresses on
+the y-axis, and coloring based on how many tasks were running on that node at
+that given time.
+
+Troubleshooting
+---------------
+
+The Ray timeline visualization may not work in Firefox or Safari.