issue_comments: 1065536538

I believe I am experiencing a similar issue, although with code that I thought was smart enough to chunk the data request into smaller pieces: ``` import numpy as np import xarray as xr from dask.diagnostics import ProgressBar import intake

wrf_url = ('https://rda.ucar.edu/thredds/catalog/files/g/ds612.0/' 'PGW3D/2006/catalog.xml') catalog_u = intake.open_thredds_merged(wrf_url, path=['_U_2006060']) catalog_v = intake.open_thredds_merged(wrf_url, path=['_V_2006060'])

ds_u = catalog_u.to_dask() ds_u['U'] = ds_u.U.chunk("auto") ds_v = catalog_v.to_dask() ds_v['V'] = ds_v.V.chunk("auto") ds = xr.merge((ds_u, ds_v))

def unstagger(ds, var, coord, new_coord): var1 = ds[var].isel({coord: slice(None, -1)}) var2 = ds[var].isel({coord: slice(1, None)}) return ((var1 + var2) / 2).rename({coord: new_coord})

with ProgressBar(): ds['U_unstaggered'] = unstagger(ds, 'U', 'west_east_stag', 'west_east') ds['V_unstaggered'] = unstagger(ds, 'V', 'south_north_stag', 'south_north') ds['speed'] = np.hypot(ds.U_unstaggered, ds.V_unstaggered) ds.speed.isel(bottom_top=10).sel(Time='2006-06-07T18:00').plot() ```

This throws an error because, according to the RDA help folks, a request for an entire variable is made, which far exceeds their server's 500 MB request limit: rda.ucar.edu/thredds/dodsC/files/g/ds612.0/PGW3D/2006/wrf3d_d01_PGW_U_20060607.nc.dods?U%5B0:1: 7%5D%5B0:1:49%5D%5B0:1:1014%5D%5B0:1:1359%5D

Here's the error: Traceback (most recent call last): File "/home/decker/classes/met325/rda_plot.py", line 29, in <module> ds.speed.isel(bottom_top=10).sel(Time='2006-06-07T18:00').plot() File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/plot/plot.py", line 862, in __call__ return plot(self._da, **kwargs) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/plot/plot.py", line 293, in plot darray = darray.squeeze().compute() File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/core/dataarray.py", line 951, in compute return new.load(**kwargs) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/core/dataarray.py", line 925, in load ds = self._to_temp_dataset().load(**kwargs) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/core/dataset.py", line 862, in load evaluated_data = da.compute(*lazy_data.values(), **kwargs) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/dask/base.py", line 571, in compute results = schedule(dsk, keys, **kwargs) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/dask/threaded.py", line 79, in get results = get_async( File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/dask/local.py", line 507, in get_async raise_exception(exc, tb) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/dask/local.py", line 315, in reraise raise exc File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/dask/local.py", line 220, in execute_task result = _execute_task(task, data) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/dask/core.py", line 119, in _execute_task return func(*(_execute_task(a, cache) for a in args)) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/dask/array/core.py", line 116, in getter c = np.asarray(c) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/core/indexing.py", line 357, in __array__ return np.asarray(self.array, dtype=dtype) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/core/indexing.py", line 521, in __array__ return np.asarray(self.array, dtype=dtype) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/core/indexing.py", line 422, in __array__ return np.asarray(array[self.key], dtype=None) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/conventions.py", line 62, in __getitem__ return np.asarray(self.array[key], dtype=self.dtype) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/core/indexing.py", line 422, in __array__ return np.asarray(array[self.key], dtype=None) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/pydap_.py", line 39, in __getitem__ return indexing.explicit_indexing_adapter( File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/core/indexing.py", line 711, in explicit_indexing_adapter result = raw_indexing_method(raw_key.tuple) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/pydap_.py", line 47, in _getitem result = robust_getitem(array, key, catch=ValueError) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/common.py", line 64, in robust_getitem return array[key] File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/pydap/model.py", line 323, in __getitem__ out.data = self._get_data_index(index) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/pydap/model.py", line 353, in _get_data_index return self._data[index] File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/pydap/handlers/dap.py", line 170, in __getitem__ raise_for_status(r) File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/pydap/net.py", line 38, in raise_for_status raise HTTPError( webob.exc.HTTPError: 403 403 I thought smaller requests would automagically happen with this code. Is it intended that a large request be made?