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Add deprecation warnings for Ray Workflows and cluster-wide storage (#51309)
Ray Workflows is an experimental library that has gone unmaintained for quite some time, so it's being explicitly deprecated. The Ray cluster-wide `storage` configuration was added for Workflows and was also never maintained beyond adding the experimental version, so it's being deprecated alongside it. This PR adds: - A warning banner to the workflows documentation pages and sidebar. - A printed warning on `ray.workflow` import. - A deprecation notice in the docstring and CLI help string for `storage` - A printed warning on `storage` usage in `ray.init` or `ray start`. --------- Signed-off-by: Edward Oakes <ed.nmi.oakes@gmail.com>
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‎doc/source/ray-more-libs/index.rst

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raydp
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mars-on-ray
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modin/index
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Ray Workflows (Alpha) <../workflows/index>
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Ray Workflows (Deprecated) <../workflows/index>
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.. TODO: we added the three Ray Core examples below, since they don't really belong there.

‎doc/source/workflows/advanced.rst

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Advanced Topics
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===============
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.. warning::
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The experimental Ray Workflows library has been deprecated and will be removed in a
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future version of Ray.
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Skipping Checkpoints
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--------------------
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This example skips checkpointing the output of ``read_data``. During recovery, ``read_data`` would be executed again if recovery requires its output.
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If the output of a task is another task (i.e., for dynamic workflows), we skip checkpointing the entire task.
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If the output of a task is another task (i.e., for dynamic workflows), we skip checkpointing the entire task.

‎doc/source/workflows/basics.rst

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Getting Started
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===============
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.. note::
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Workflows is a library that provides strong durability for Ray task graphs.
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If you’re brand new to Ray, we recommend starting with the :ref:`core walkthrough <core-walkthrough>` instead.
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.. warning::
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The experimental Ray Workflows library has been deprecated and will be removed in a
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future version of Ray.
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Your first workflow
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-------------------

‎doc/source/workflows/comparison.rst

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API Comparisons
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===============
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.. warning::
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The experimental Ray Workflows library has been deprecated and will be removed in a
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future version of Ray.
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Comparison between Ray Core APIs and Workflows
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----------------------------------------------
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Ray Workflows is built on top of Ray, and offers a mostly consistent subset of its API while providing durability. This section highlights some of the differences:

‎doc/source/workflows/events.rst

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Events
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======
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.. warning::
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The experimental Ray Workflows library has been deprecated and will be removed in a
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future version of Ray.
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To allow an event to trigger a workflow, Ray Workflows supports pluggable event systems. Using the event framework provides a few properties.
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1. Waits for events efficiently (without requiring a running workflow task while waiting).

‎doc/source/workflows/index.rst

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.. warning::
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Ray Workflows is available as **alpha** in Ray 2.0+. Expect rough corners and
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for its APIs and storage format to change. Please file feature requests and
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bug reports on GitHub Issues or join the discussion on the
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`Ray Slack <https://www.ray.io/join-slack>`__.
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The experimental Ray Workflows library has been deprecated and will be removed in a
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future version of Ray.
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Ray Workflows implements high-performance, *durable* application workflows using
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Ray tasks as the underlying execution engine. It enables task-based Ray jobs

‎doc/source/workflows/key-concepts.rst

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Key Concepts
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------------
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.. warning::
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The experimental Ray Workflows library has been deprecated and will be removed in a
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future version of Ray.
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.. note::
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Workflows is a library that provides strong durability for Ray task graphs.
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If you’re brand new to Ray, we recommend starting with the :ref:`core walkthrough <core-walkthrough>` instead.

‎doc/source/workflows/management.rst

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Workflow Management
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===================
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.. warning::
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The experimental Ray Workflows library has been deprecated and will be removed in a
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future version of Ray.
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Workflow IDs
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------------
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Each workflow has a unique ``workflow_id``. By default, when you call ``.run()``

‎doc/source/workflows/metadata.rst

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Workflow Metadata
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=================
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.. warning::
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The experimental Ray Workflows library has been deprecated and will be removed in a
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future version of Ray.
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Observability is important for workflows - sometimes we not only want
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to get the output, but also want to gain insights on the internal
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states (e.g., to measure the performance or find bottlenecks).

‎python/ray/_private/worker.py

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namespace: A namespace is a logical grouping of jobs and named actors.
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runtime_env: The runtime environment to use
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for this job (see :ref:`runtime-environments` for details).
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storage: [Experimental] Specify a URI for persistent cluster-wide storage.
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This storage path must be accessible by all nodes of the cluster, otherwise
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an error will be raised. This option can also be specified as the
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RAY_STORAGE env var.
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storage: [DEPRECATED] Cluster-wide storage configuration is deprecated and will
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be removed in a future version of Ray.
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_enable_object_reconstruction: If True, when an object stored in
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the distributed plasma store is lost due to node failure, Ray will
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attempt to reconstruct the object by re-executing the task that
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else:
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driver_mode = SCRIPT_MODE
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if storage is not None:
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warnings.warn(
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"Cluster-wide storage configuration is deprecated and will be removed in a "
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"future version of Ray."
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)
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global _global_node
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if global_worker.connected:

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