python - Why does Dask perform so slower while multiprocessing …
Sep 6, 2019 · 36 dask delayed 10.288054704666138s my cpu has 6 physical cores Question Why does Dask perform so slower while multiprocessing perform so much faster? Am I using …
dask - Make Pandas DataFrame apply () use all cores? - Stack …
As of August 2017, Pandas DataFame.apply() is unfortunately still limited to working with a single core, meaning that a multi-core machine will waste the majority of its compute-time when you …
How to see progress of Dask compute task? - Stack Overflow
Jul 29, 2024 · I would like to see a progress bar on Jupyter notebook while I'm running a compute task using Dask, I'm counting all values of id column from a large csv file +4GB, so any ideas? …
How to Set Dask Dashboard Address with SLURMRunner …
Dec 17, 2024 · I am trying to run a Dask Scheduler and Workers on a remote cluster using SLURMRunner from dask-jobqueue. I want to bind the Dask dashboard to 0.0.0.0 (so it’s …
dask: difference between client.persist and client.compute
Jan 23, 2017 · So if you persist a dask dataframe with 100 partitions you get back a dask dataframe with 100 partitions, with each partition pointing to a future currently running on the …
Unable to use dask-sql due to 'dask_expr.io' module
Jul 7, 2025 · maybe it need to instal some other module to import dask_expr.io. Or maybe it needs older (or newer) version.
python - dask: What does memory_limit control? - Stack Overflow
Oct 4, 2021 · The documentation you've linked to talks about command-line options for dask-worker. Your code snippet uses the keyword argument memory_limit which I believe is different.
How to transform Dask.DataFrame to pd.DataFrame?
Aug 18, 2016 · How can I transform my resulting dask.DataFrame into pandas.DataFrame (let's say I am done with heavy lifting, and just want to apply sklearn to my aggregate result)?
Strategy for partitioning dask dataframes efficiently
Jun 20, 2017 · The documentation for Dask talks about repartioning to reduce overhead here. They however seem to indicate you need some knowledge of what your dataframe will look …
python - Difference between dask.distributed LocalCluster with …
Sep 2, 2019 · What is the difference between the following LocalCluster configurations for dask.distributed? Client(n_workers=4, processes=False, threads_per_worker=1) versus …