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Note that explicit resource allocation is experimental, fix typos (#25038)
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@ -132,10 +132,14 @@ group by default. This can be thought of as Datasets requesting resources from t
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margins of the cluster, outside of those ML library placement groups.
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Although this is the default behavior, you can force all Datasets workloads to be
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schedule without a placement group by specifying a placement group as the global
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scheduled within a placement group by specifying a placement group as the global
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scheduling strategy for all Datasets tasks/actors, using the global
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:class:`DatasetContext <ray.data.DatasetContext>`:
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:class:`DatasetContext <ray.data.DatasetContext>`.
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.. note::
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This is an experimental feature subject to change as we work to improve our
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resource allocation model for Datasets.
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.. literalinclude:: ./doc_code/key_concepts.py
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:language: python
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