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- Poor memory management with dask=2021.4.0 · 1 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 820706339 | https://github.com/pydata/xarray/issues/5165#issuecomment-820706339 | https://api.github.com/repos/pydata/xarray/issues/5165 | MDEyOklzc3VlQ29tbWVudDgyMDcwNjMzOQ== | slevang 39069044 | 2021-04-15T20:20:26Z | 2021-04-15T20:20:26Z | CONTRIBUTOR | In fact an even simpler calculation also shows the same problem: ```python import xarray as xr import pandas as pd import numpy as np import dask.array as da dates = pd.date_range('1980-01-01', '2019-12-31', freq='D') ds = xr.Dataset( data_vars = { 'x1':( ('time', 'lat', 'lon'), da.random.random(size=(dates.size, 360, 720), chunks=(1, -1, -1))), 'x2':( ('time', 'lat', 'lon'), da.random.random(size=(dates.size, 360, 720), chunks=(1, -1, -1))), }, coords = { 'time': dates, 'lat': np.arange(-90, 90, .5), 'lon': np.arange(-180, 180, .5), } ) ds['x3'] = ds.x2 - ds.x1 ds[['x3']].to_zarr('test-anom', mode='w') ``` |
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Poor memory management with dask=2021.4.0 859218255 |
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