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Auto-chunking for ERA5 loading #1608

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Auto-chunking for ERA5 loading #1608

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2 changes: 1 addition & 1 deletion tests/geospatial/workloads/atmospheric_circulation.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,7 +11,7 @@ def atmospheric_circulation(
) -> Delayed:
ds = xr.open_zarr(
"gs://weatherbench2/datasets/era5/1959-2023_01_10-full_37-1h-0p25deg-chunk-1.zarr",
chunks={},
chunks={"time": "auto"},
)
if scale == "small":
# 852.56 GiB (small)
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2 changes: 2 additions & 0 deletions tests/geospatial/workloads/climatology.py
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Original file line number Diff line number Diff line change
Expand Up @@ -72,6 +72,7 @@ def rechunk_map_blocks(
# Load dataset
ds = xr.open_zarr(
"gs://weatherbench2/datasets/era5/1959-2023_01_10-wb13-6h-1440x721.zarr",
chunks={"time": "auto"},
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@jrbourbeau jrbourbeau Nov 15, 2024 •
edited
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This the a case where I think the naive user-code is what we want. This may be slightly better but we want to optimize what most users will have in practice

EDIT: Whoops, I missing @fjetter's comment, which is basically the same as mine

)

if scale == "small":
Expand Down Expand Up @@ -122,6 +123,7 @@ def highlevel_api(
# Load dataset
ds = xr.open_zarr(
"gs://weatherbench2/datasets/era5/1959-2023_01_10-wb13-6h-1440x721.zarr",
chunks={"time": "auto"},
)

if scale == "small":
Expand Down
1 change: 1 addition & 0 deletions tests/geospatial/workloads/rechunking.py
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Original file line number Diff line number Diff line change
Expand Up @@ -11,6 +11,7 @@ def era5_rechunking(
) -> Delayed:
ds = xr.open_zarr(
"gs://weatherbench2/datasets/era5/1959-2023_01_10-full_37-1h-0p25deg-chunk-1.zarr",
chunks={"time": "auto"},
).drop_encoding()

if scale == "small":
Expand Down
1 change: 1 addition & 0 deletions tests/geospatial/workloads/regridding.py
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Original file line number Diff line number Diff line change
Expand Up @@ -13,6 +13,7 @@ def xesmf(
) -> Delayed:
ds = xr.open_zarr(
"gs://weatherbench2/datasets/era5/1959-2023_01_10-full_37-1h-0p25deg-chunk-1.zarr",
chunks={"time": "auto"},
)
# Fixed time range and variable as the interesting part of this benchmark scales with the
# regridding matrix
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