open_mfdataset memory leak, very simple case. v0.12

MCVE Code Sample

import glob
import xarray as xr
import numpy as np
from memory_profiler import profile

def CreateTestFiles():
        # create a bunch of files
        xlen = int(1e2)
        ylen = int(1e2)
        xdim = np.arange(xlen)
        ydim = np.arange(ylen)

        nfiles = 100
        for i in range(nfiles):
                data = np.random.rand(xlen, ylen, 1)
                datafile = xr.DataArray(data, coords=[xdim, ydim, i], dims=['x', 'y', 'time'])
                datafile.to_netcdf('testfiles/datafile_{}.nc'.format(i))

@profile
def ReadFiles():
        xr.open_mfdataset(glob.glob('testfiles/*'), concat_dim='time')

if __name__ == '__main__':
        # write out files for testing 
        CreateTestFiles()

        # loop thru file read step
        for i in range(100):
                ReadFiles()
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usage:

mprof run simplest_case.py
mprof plot

(mprof is a python memory profiling library)

Problem Description

dask version 1.1.4
xarray version 0.12
python 3.7.3

There appears to be a persistent memory leak in open_mfdataset. I'm creating a model calibration script that runs for ~1000 iterations, opening and closing the same set of files (dimensions are the same, but the data is different) with each iteration. I eventually run out of memory because of the leak. This simple case captures the same behavior. Closing the files with .close() does not fix the problem.

Is there a work around for this? I've perused some of the issues but cannot tell if this has been resolved.

Output of xr.show_versions()

The entry point is xr.open_mfdataset in the supplied simplest_case.py MCVE; start by running it under mprof with the listed versions and inspecting repeated calls. Compare memory behavior with the described close() attempt. Done means repeated reads no longer show persistent growth, with the behavior covered by a regression test.