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universalmind303 committed Jul 30, 2024
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2 changes: 1 addition & 1 deletion docs/source/conf.py
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"learn/install": "../install.html",
"learn/user_guides/dataframes": "intro-dataframes.html",
"learn/user_guides/types_and_ops": "intro-dataframes.html",
"learn/user_guides/remote_cluster_execution": "scaling-up.html",
"learn/user_guides/remote_cluster_execution": "distributed-computing.html",
"learn/quickstart": "learn/10-min.html",
"learn/10-min": "../10-min.html",
}
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2 changes: 1 addition & 1 deletion docs/source/migration_guides/coming_from_dask.rst
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Expand Up @@ -118,7 +118,7 @@ Dask supports the same data types as pandas. Daft is built to support many more
Distributed Computing and Remote Clusters
-----------------------------------------

Both Dask and Daft support distributed computing on remote clusters. In Dask, you create a Dask cluster either locally or remotely and perform computations in parallel there. Currently, Daft supports distributed cluster computing :doc:`with Ray <../user_guide/poweruser/scaling-up>`. Support for running Daft computations on Dask clusters is on the roadmap.
Both Dask and Daft support distributed computing on remote clusters. In Dask, you create a Dask cluster either locally or remotely and perform computations in parallel there. Currently, Daft supports distributed cluster computing :doc:`with Ray <../user_guide/poweruser/distributed-computing>`. Support for running Daft computations on Dask clusters is on the roadmap.

Cloud support for both Dask and Daft is the same.

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2 changes: 1 addition & 1 deletion docs/source/user_guide/poweruser.rst
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Expand Up @@ -5,4 +5,4 @@ The Daft Poweruser

poweruser/memory
poweruser/partitioning
poweruser/scaling-up
poweruser/distributed-computing
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@@ -1,5 +1,3 @@
.. _scaling_up:

Distributed Computing
=====================

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"\n",
"*EDIT (June 2023): Our hosted version of the full dataset is temporarily unavailable. Please enjoy the demo with the sample dataset for now.*\n",
"\n",
"**Note:** This demo runs best on a cluster with many GPUs available. Information on how to connect Daft to a cluster is available [here](https://www.getdaft.io/projects/docs/en/stable/learn/user_guides/scaling-up.html). \n",
"**Note:** This demo runs best on a cluster with many GPUs available. Information on how to connect Daft to a cluster is available [here](https://www.getdaft.io/projects/docs/en/stable/learn/user_guides/poweruser/distributed-computing.html). \n",
"\n",
"If running on a single node, you can use the provided subsample of the data, which is 75MB in size. If you like, you can also truncate either dataset to a desired number of rows using `df.limit`."
]
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"name": "python",
"nbconvert_exporter": "python",
"pygments_lexer": "ipython3",
"version": "3.9.6"
"version": "3.11.4"
}
},
"nbformat": 4,
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2 changes: 1 addition & 1 deletion tutorials/intro.ipynb
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"\n",
"![image.png](attachment:image.png)\n",
"\n",
"See ([Daft Documentation: Distributed Computing](https://www.getdaft.io/projects/docs/en/latest/learn/user_guides/scaling-up.html))"
"See ([Daft Documentation: Distributed Computing](https://www.getdaft.io/projects/docs/en/latest/user_guide/poweruser/distributed-computing.html))"
]
},
{
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2 changes: 1 addition & 1 deletion tutorials/talks_and_demos/linkedin-03-05-2024.ipynb
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"\n",
"![image.png](attachment:image.png)\n",
"\n",
"See ([Daft Documentation: Distributed Computing](https://www.getdaft.io/projects/docs/en/latest/learn/user_guides/scaling-up.html))"
"See ([Daft Documentation: Distributed Computing](https://www.getdaft.io/projects/docs/en/stable/learn/user_guides/poweruser/distributed-computing.html))"
]
},
{
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