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Using the --base_period argument for percentiles seems to hang with AGCD tasmax/tasmin data and the job runs out of walltime. I haven't applied it yet to other models. Below is the output from one of failed jobs.
rm: cannot remove 'TX10p_AUS-r005_BOM-AGCD_historical_none_year_19790101-20211231.nc': No such file or directory
2023-03-11 09:06:12,661 Array size: (15706, 691, 886)
2023-03-11 09:06:12,662 Chunk size: Frozen({'time': (15706,), 'lat': (35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 35, 26), 'lon': (60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 60, 46)})
2023-03-11 09:06:12,662 ********************************************************************************************
2023-03-11 09:06:12,662 * *
2023-03-11 09:06:12,662 * icclim 6.1.3 *
2023-03-11 09:06:12,662 * *
2023-03-11 09:06:12,662 * *
2023-03-11 09:06:12,662 * Fri Mar 10 22:06:12 2023 *
2023-03-11 09:06:12,662 * *
2023-03-11 09:06:12,662 * BEGIN EXECUTION *
2023-03-11 09:06:12,662 * *
2023-03-11 09:06:12,662 ********************************************************************************************
2023-03-11 09:06:12,662 Processing: 0%
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/xarray/core/dataset.py:4880: PerformanceWarning: Reshaping is producing a large chunk. To accept the large
chunk and silence this warning, set the option
>>> with dask.config.set(**{'array.slicing.split_large_chunks': False}):
... array.reshape(shape)
To avoid creating the large chunks, set the option
>>> with dask.config.set(**{'array.slicing.split_large_chunks': True}):
... array.reshape(shape)Explictly passing ``limit`` to ``reshape`` will also silence this warning
>>> array.reshape(shape, limit='128 MiB')
result = result._unstack_full_reindex(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/xarray/core/variable.py:1722: PerformanceWarning: Reshaping is producing a large chunk. To accept the large
chunk and silence this warning, set the option
>>> with dask.config.set(**{'array.slicing.split_large_chunks': False}):
... array.reshape(shape)
To avoid creating the large chunks, set the option
>>> with dask.config.set(**{'array.slicing.split_large_chunks': True}):
... array.reshape(shape)Explictly passing ``limit`` to ``reshape`` will also silence this warning
>>> array.reshape(shape, limit='128 MiB')
result = result._stack_once(dims, new_dim)
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/xclim/core/cfchecks.py:44: UserWarning: Variable does not have a `cell_methods` attribute.
_check_cell_methods(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/xclim/core/cfchecks.py:48: UserWarning: Variable does not have a `standard_name` attribute.
check_valid(vardata, "standard_name", data["standard_name"])
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
/g/data/xv83/dbi599/miniconda3/envs/icclim/lib/python3.10/site-packages/dask/array/core.py:4806: PerformanceWarning: Increasing number of chunks by factor of 15
result = blockwise(
=>> PBS: job killed: walltime 172826 exceeded limit 172800
The text was updated successfully, but these errors were encountered:
The --base_period calculations successfully complete (notwithstanding #17) on a smaller spatial domain (i.e. as opposed to the whole of Australia at 5km), so the problem is just with scaling up to a bigger grid.
@ngben I couldn't find any dask cluster configurations that would solve the --base_period issue (I think the dask task graph just becomes way to complicated when the base period option is used) so I've added a --nslices option which slices the input dataset along the longitude axis and processes each slice one after the other in a simple loop (before putting everything back together again at the end). It's not the most elegant solution (the whole point of dask is to avoid looping) and it takes quite a few hours to process the whole AGCD grid if you use a large number of slices (I used 200 in a successful example run), but it does successfully run which is the main thing.
Using the
--base_period
argument for percentiles seems to hang with AGCD tasmax/tasmin data and the job runs out of walltime. I haven't applied it yet to other models. Below is the output from one of failed jobs.The text was updated successfully, but these errors were encountered: