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fix typo again
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@rjzamora
rjzamora committed Sep 16, 2024
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Expand Up @@ -114,7 +114,7 @@ cuDF Spilling

When executing an ETL workflow with `Dask cuDF <https://docs.rapids.ai/api/dask-cudf/stable/>`_
(i.e. Dask DataFrame), it is usually best to leverage `native spilling support in cuDF
<https://docs.rapids.ai/api/cudf/stable/developer_guide/library_design/#spilling-to-host-memory>_`.
<https://docs.rapids.ai/api/cudf/stable/developer_guide/library_design/#spilling-to-host-memory>`_.

Native cuDF spilling has an important advantage over the other methodologies mentioned
above. When JIT-unspill or default spilling are used, the worker is only able to spill
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