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- open_mfdataset memory leak, very simple case. v0.12 · 1 ✖
id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
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530800751 | https://github.com/pydata/xarray/issues/3200#issuecomment-530800751 | https://api.github.com/repos/pydata/xarray/issues/3200 | MDEyOklzc3VlQ29tbWVudDUzMDgwMDc1MQ== | floschl 1262767 | 2019-09-12T12:24:12Z | 2019-09-12T12:36:02Z | NONE | I have observed a similar memleak (config see below). It occurs for both parameters engine=netcdf4 and engine=h5netcdf. Example for loading a 1.2GB netCDF file:
In contrast, the memory is just released with a
Output of
INSTALLED VERSIONS
------------------
commit: None
python: 3.6.7 | packaged by conda-forge | (default, Jul 2 2019, 02:18:42)
[GCC 7.3.0]
python-bits: 64
OS: Linux
OS-release: 4.15.0-62-generic
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: en_US.UTF-8
libhdf5: 1.10.5
libnetcdf: 4.6.2
xarray: 0.12.3
pandas: 0.25.1
numpy: 1.16.4
scipy: 1.2.1
netCDF4: 1.5.1.2
pydap: None
h5netcdf: 0.7.4
h5py: 2.9.0
Nio: None
zarr: None
cftime: 1.0.3.4
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: None
dask: 2.3.0
distributed: 2.3.2
matplotlib: 3.1.1
cartopy: 0.17.0
seaborn: None
numbagg: None
setuptools: 41.0.1
pip: 19.2.3
conda: None
pytest: 5.0.1
IPython: 7.7.0
sphinx: None
|
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open_mfdataset memory leak, very simple case. v0.12 479190812 |
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