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Dask DataFrame Is Fast Now
Patrick Hoefler 2024-05-14 10 min read Bar chart showing a nearly 20x improvement in Dask DataFrame performance with the addition of Arrow stings, more efficient shufffling, and a query optimizer. ...
Operations on object data also hold the GIL, which doesn’t matter much for pandas, but is a catastrophy for performance with a parallel system like Dask. Workloads that previously struggled with available memory now fit comfortably in much less space, and are a lot faster because they no longer constantly spill excess data to disk. Dask also did a bad job of hiding internal complexities and left users on their own while navigating the difficulties of distributed computing and running large scale queries.
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