chore: import upstream snapshot with attribution
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.. _observability-debug-hangs:
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Debugging Hangs
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===============
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View stack traces in Ray Dashboard
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-----------------------------------
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The :ref:`Ray dashboard <observability-getting-started>` lets you profile Ray Driver or Worker processes, by clicking on the "CPU profiling" or "Stack Trace" actions for active Worker processes, Tasks, Actors, and Job's driver process.
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.. image:: /images/profile.png
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:align: center
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:width: 80%
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Clicking "Stack Trace" will return the current stack trace sample using ``py-spy``. By default, only the Python stack
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trace is shown. To show native code frames, set the URL parameter ``native=1`` (only supported on Linux).
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.. image:: /images/stack.png
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:align: center
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:width: 60%
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.. note::
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You may run into permission errors when using py-spy in the docker containers. To fix the issue:
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* if you start Ray manually in a Docker container, follow the `py-spy documentation`_ to resolve it.
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* if you are a KubeRay user, follow the :ref:`guide to configure KubeRay <kuberay-pyspy-integration>` and resolve it.
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.. note::
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The following errors are conditional and not signals of failures for your Python programs:
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* If you see "No such file or direction", check if your worker process has exited.
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* If you see "No stack counts found", check if your worker process was sleeping and not active in the last 5s.
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.. _`py-spy documentation`: https://github.com/benfred/py-spy#how-do-i-run-py-spy-in-docker
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Use ``ray stack`` CLI command
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------------------------------
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Once ``py-spy`` is installed (it is automatically installed if "Ray Dashboard" component is included when :ref:`installing Ray <installation>`), you can run ``ray stack`` to dump the stack traces of all Ray Worker processes on
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the current node.
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This document discusses some common problems that people run into when using Ray
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as well as some known problems. If you encounter other problems, please
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`let us know`_.
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.. _`let us know`: https://github.com/ray-project/ray/issues
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