Unnecessarily Large Data Request #74

sgdecker · 2022-03-11T20:07:49Z

I'm not sure if this is a bug report, feature request, or user error. I'm trying to access a giant dataset from the NCAR RDA in a smart way (only downloading what's necessary for the calculation), but a large data request is made anyway that exceeds the server's 500 MB limit.

Here's my code:

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 fails with

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

because the data request is too large.

Folks at NCAR tell me the request comes across as

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

essentially pulling an entire variable.

Is what I'm trying to do supposed to work?

I can use siphon directly w/o issue:

import numpy as np
import matplotlib.pyplot as plt
from siphon.catalog import TDSCatalog

catUrl = ('https://rda.ucar.edu/thredds/catalog/files/g/ds612.0/'
          'PGW3D/2006/catalog.xml')
catalog = TDSCatalog(catUrl)
U_file = 'wrf3d_d01_PGW_U_20060718.nc'
V_file = 'wrf3d_d01_PGW_V_20060718.nc'
ds = catalog.datasets[U_file]
dataset = ds.remote_access()
u = dataset.variables['U']
ds = catalog.datasets[V_file]
dataset = ds.remote_access()
v = dataset.variables['V']
speed = np.hypot(u[1, 10, 0:1014, 0:1359], v[1, 10, 0:1014, 0:1359])
plt.imshow(speed)
plt.show()

but in that case I don't have all the xarray niceties w/o extra work.

The text was updated successfully, but these errors were encountered:

martindurant · 2022-03-11T20:30:35Z

As you can see, xarray is calling pydap, which then does the fetch. I don't suppose there's anything that we can do about how that happens at the intake level. You might want to cross-post on xarray or pydap, though. Perhaps someone might chime in here on how siphon does this differently.

Since the target file is, eventually, just a netCDF, you could pass its URL or an open fsspec file directly to xarray (presumably with engine "h5netcdf"), or kerchunk it.

dopplershift · 2022-03-17T21:58:40Z

Since it's DAP, you can also try to make sure xarray is using the netcdf4 engine, since netCDF-c is usually compiled with DAP support.

sgdecker · 2022-03-18T17:57:02Z

I tried the following variations:

Variation 1

catalog_u = intake.open_thredds_merged(wrf_url, driver='netcdf',
                                       path=['*_U_2006060*'])
catalog_v = intake.open_thredds_merged(wrf_url, driver='netcdf',
                                       path=['*_V_2006060*'])

Output

Traceback (most recent call last):
  File "/home/decker/classes/met325/rda_plot.py", line 14, in <module>
    ds_u = catalog_u.to_dask()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 69, in to_dask
    return self.read_chunked()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 44, in read_chunked
    self._load_metadata()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake/source/base.py", line 236, in _load_metadata
    self._schema = self._get_schema()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 18, in _get_schema
    self._open_dataset()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_thredds/source.py", line 82, in _open_dataset
    cat = ThreddsCatalog(self.urlpath, driver=self.driver)
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_thredds/cat.py", line 30, in __init__
    super().__init__(**kwargs)
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake/catalog/base.py", line 110, in __init__
    self.force_reload()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake/catalog/base.py", line 168, in force_reload
    self._load()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_thredds/cat.py", line 81, in _load
    {
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_thredds/cat.py", line 87, in <dictcomp>
    {'urlpath': access_urls(ds, self), 'chunks': {}},
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_thredds/cat.py", line 75, in access_urls
    url = ds.access_urls[driver_for_access_urls]
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/siphon/catalog.py", line 221, in __getitem__
    return super(CaseInsensitiveDict, self).__getitem__(CaseInsensitiveStr(key))
KeyError: 'HTTPServer'

Variation 2

catalog_u = intake.open_thredds_merged(wrf_url,
                                       xarray_kwargs={'engine': 'netcdf4'},
                                       path=['*_U_2006060*'])
catalog_v = intake.open_thredds_merged(wrf_url,
                                       xarray_kwargs={'engine': 'netcdf4'},
                                       path=['*_V_2006060*'])

Output

Dataset(s):   0%|                                        | 0/9 [00:00<?, ?it/s]Traceback (most recent call last):
  File "/home/decker/classes/met325/rda_plot.py", line 16, in <module>
    ds_u = catalog_u.to_dask()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 69, in to_dask
    return self.read_chunked()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 44, in read_chunked
    self._load_metadata()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake/source/base.py", line 236, in _load_metadata
    self._schema = self._get_schema()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 18, in _get_schema
    self._open_dataset()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_thredds/source.py", line 90, in _open_dataset
    data = [
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_thredds/source.py", line 91, in <listcomp>
    ds(xarray_kwargs=self.xarray_kwargs).to_dask()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 69, in to_dask
    return self.read_chunked()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 44, in read_chunked
    self._load_metadata()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake/source/base.py", line 236, in _load_metadata
    self._schema = self._get_schema()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 18, in _get_schema
    self._open_dataset()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/opendap.py", line 98, in _open_dataset
    self._ds = xr.open_dataset(store, chunks=self.chunks, **self._kwargs)
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/api.py", line 495, in open_dataset
    backend_ds = backend.open_dataset(
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/netCDF4_.py", line 550, in open_dataset
    store = NetCDF4DataStore.open(
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/netCDF4_.py", line 352, in open
    raise ValueError(
ValueError: can only read bytes or file-like objects with engine='scipy' or 'h5netcdf'
Dataset(s):   0%|                                        | 0/9 [00:01<?, ?it/s]

Variation 3

catalog_u = intake.open_thredds_merged(wrf_url,
                                       xarray_kwargs={'engine': 'h5netcdf'},
                                       path=['*_U_2006060*'])
catalog_v = intake.open_thredds_merged(wrf_url,
                                       xarray_kwargs={'engine': 'h5netcdf'},
                                       path=['*_V_2006060*'])

Output

Dataset(s):   0%|                                        | 0/9 [00:00<?, ?it/s]Traceback (most recent call last):
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/file_manager.py", line 199, in _acquire_with_cache_info
    file = self._cache[self._key]
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/lru_cache.py", line 53, in __getitem__
    value = self._cache[key]
KeyError: [<class 'h5netcdf.core.File'>, (<xarray.backends.pydap_.PydapDataStore object at 0x7f374deb7160>,), 'r', (('decode_vlen_strings', True), ('invalid_netcdf', None))]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "/home/decker/classes/met325/rda_plot.py", line 16, in <module>
    ds_u = catalog_u.to_dask()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 69, in to_dask
    return self.read_chunked()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 44, in read_chunked
    self._load_metadata()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake/source/base.py", line 236, in _load_metadata
    self._schema = self._get_schema()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 18, in _get_schema
    self._open_dataset()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_thredds/source.py", line 90, in _open_dataset
    data = [
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_thredds/source.py", line 91, in <listcomp>
    ds(xarray_kwargs=self.xarray_kwargs).to_dask()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 69, in to_dask
    return self.read_chunked()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 44, in read_chunked
    self._load_metadata()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake/source/base.py", line 236, in _load_metadata
    self._schema = self._get_schema()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/base.py", line 18, in _get_schema
    self._open_dataset()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/intake_xarray/opendap.py", line 98, in _open_dataset
    self._ds = xr.open_dataset(store, chunks=self.chunks, **self._kwargs)
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/api.py", line 495, in open_dataset
    backend_ds = backend.open_dataset(
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/h5netcdf_.py", line 374, in open_dataset
    store = H5NetCDFStore.open(
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/h5netcdf_.py", line 178, in open
    return cls(manager, group=group, mode=mode, lock=lock, autoclose=autoclose)
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/h5netcdf_.py", line 123, in __init__
    self._filename = find_root_and_group(self.ds)[0].filename
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/h5netcdf_.py", line 189, in ds
    return self._acquire()
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/h5netcdf_.py", line 181, in _acquire
    with self._manager.acquire_context(needs_lock) as root:
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/contextlib.py", line 135, in __enter__
    return next(self.gen)
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/file_manager.py", line 187, in acquire_context
    file, cached = self._acquire_with_cache_info(needs_lock)
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/xarray/backends/file_manager.py", line 205, in _acquire_with_cache_info
    file = self._opener(*self._args, **kwargs)
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/h5netcdf/core.py", line 951, in __init__
    self._h5file = h5py.File(
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/h5py/_hl/files.py", line 486, in __init__
    name = filename_encode(name)
  File "/home/decker/local/miniconda3/envs/met325/lib/python3.10/site-packages/h5py/_hl/compat.py", line 19, in filename_encode
    filename = fspath(filename)
TypeError: expected str, bytes or os.PathLike object, not PydapDataStore
Dataset(s):   0%|                                        | 0/9 [00:01<?, ?it/s]

I'll have to look into some of the other methods that were suggested, but this is not turning out to be as straightforward as I had hoped.

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Unnecessarily Large Data Request #74

Unnecessarily Large Data Request #74

sgdecker commented Mar 11, 2022

martindurant commented Mar 11, 2022

dopplershift commented Mar 17, 2022

sgdecker commented Mar 18, 2022

Unnecessarily Large Data Request #74

Unnecessarily Large Data Request #74

Comments

sgdecker commented Mar 11, 2022

martindurant commented Mar 11, 2022

dopplershift commented Mar 17, 2022

sgdecker commented Mar 18, 2022

Variation 1

Output

Variation 2

Output

Variation 3

Output