Add atmospheric circulation benchmark #1554
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dcherian
reviewed
Sep 21, 2024
dcherian
reviewed
Sep 21, 2024
| temdiags = zonal_means.merge(anomaly[["uv", "vt", "uw"]].mean("longitude")) | ||
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| # This is incredibly slow, takes a while for flox to construct the graph | ||
| daily = temdiags.resample(time="D").mean() |
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Upstream issue: xarray-contrib/flox#396
This is almost certainly equally slow to set up without flox. Both will create a large number of dask arrays (=number of days in the dataset) apply the reduction, then concatenate.
Co-authored-by: Deepak Cherian <dcherian@users.noreply.github.com>
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@dcherian does this look good to include from your perspective? |
hendrikmakait
approved these changes
Sep 24, 2024
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| # # Users often rework things via a rechunk to make this a blockwise problem | ||
| # daily = ( | ||
| # temdiags.chunk(time=24) | ||
| # .resample(time="D") | ||
| # .mean() | ||
| # ) |
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Did you leave this here on purpose?
Suggested change
| # # Users often rework things via a rechunk to make this a blockwise problem | |
| # daily = ( | |
| # temdiags.chunk(time=24) | |
| # .resample(time="D") | |
| # .mean() | |
| # ) |
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Yeah, just for future reference in case it's needed. I think keeping for context doesn't hurt. We can always remove it later
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xref #1545 (comment)
cc @dcherian @hendrikmakait
EDIT: Here's a run of the "small" version of this test https://cloud.coiled.io/clusters/598243/account/dask-engineering-gcp/information?quick=Just+mine. Takes ~9 minutes and costs ~$0.20