issue_comments

So using a cleaner minimal example it does appear that the files are closed after the dataset is closed. However, they are all open during dataset loading - this is what blows past the OSX default max open file limit.

I think this could be a real issue when using Xarray to handle too-big-for-ram datasets - you could easily be trying to access 1000s of files (especially with weather data), so Xarray should limit the number it holds open at any one time during data load. Not being familiar with the internals I'm not sure if this is an issue in Xarray itself or in the Dask backend.

@shoyer thanks - here's how i'm using mfdataset - not using any options. I'm going to try using the h5netcdf backend to see if I get the same results. I'm still not 100% confident that I'm tracking open files correctly with lsof so I'm going to try to make a minimal example to investigate.

``` python

def weather_dataset(root_path: Path, *, start_date: datetime = None, end_date: datetime = None): flat_files_paths = get_dset_file_paths(root_path, start_date=start_date, end_date=end_date) # Convert Paths to list of strings for xarray dataset = xr.open_mfdataset([str(f) for f in flat_files_paths]) return dataset

def cfsr_weather_loader(db, site_lookup_fn=None, dset_start=None, dset_end=None, site_conf=None): # Pull values out of the dt_conf = site_conf if site_conf else WEATHER_CFSR dset_start = dset_start if dset_start else dt_conf['start_dt'] dset_end = dset_end if dset_end else dt_conf['end_dt']

if site_lookup_fn is None:
    site_lookup_fn = site_lookup_postcode_district

def weather_loader(site_id, start_date, end_date, resample=None):
    # using the tuple because always getting mixed up with lon/lat
    geo_lookup = site_lookup_fn(site_id, db)

    # With statement should ensure dset is closed after loading.
    with weather_dataset(WEATHER_CFSR['path'],
                         start_date=dset_start,
                         end_date=dset_end) as weather:
        data = weighted_regional_timeseries(weather, start_date, end_date,
                                            lon=geo_lookup.lon,
                                            lat=geo_lookup.lat,
                                            weights=geo_lookup.weights)

    # RENAME from CFSR standard
    data = data.rename(columns=WEATHER_RENAME)

    if resample is not None:
        data = data.resample(resample).mean()
    data.irradiance /= 1000.0  # convert irradiance to kW
    return data

return weather_loader

```

So on investigation, even though my dataset creation is wrapped in a with block, using lsof to check the file handles held by my iPython kernel suggests that all the input files are still open. Are you certain that the backend correctly closes files in a multifile dataset? Is there a way to explicitly force this to happen?

I still hit this issue after wrapping my open_mfdataset in a with statement. I'm suspecting to be an OSX problem, MacOS has a very low default max-open-files limit for applications started from the shell (like 256). It's not yet clear to me whether my datasets are being correctly closed, investigating...

It seems to happen even with a freshly restarted notebook, but I'll try a with statement to see if helps. On 3 Jun 2016 19:53, "Stephan Hoyer" notifications@github.com wrote:

I suspect you hit this in IPython after rerunning cells, because file handles are only automatically closed when programs exit. You might find it a good idea to explicitly close files by calling .close() (or using a "with" statement) on Datasets opened with open_mfdataset.

On Fri, Jun 3, 2016 at 11:08 AM, mangecoeur notifications@github.com wrote:

I'm also running into this error - but strangely it only happens when using IPython interactive backend. I have some tests which work fine, but doing the same in IPython fails.

I'm opening a few hundred files (about 10Mb each, one per month across a few variables). I'm using the default NetCDF backend.

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I'm also running into this error - but strangely it only happens when using IPython interactive backend. I have some tests which work fine, but doing the same in IPython fails.

I'm opening a few hundred files (about 10Mb each, one per month across a few variables). I'm using the default NetCDF backend.