issues: 1525802030
This data as json
id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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1525802030 | I_kwDOAMm_X85a8eQu | 7430 | Missing Blocks when loading zarr file | 12512930 | open | 0 | 3 | 2023-01-09T15:19:50Z | 2023-01-13T02:24:24Z | NONE | What happened?Under load blocks of Zarr objects go missing. This happens on our minio server (see example) and on the hpc file system. This happens under load, when the filesystem gets slow, so I guess there must be a timeout somewhere. What did you expect to happen?A complete map. Incomplete map: Complete map, when the filesystem is not under load: Minimal Complete Verifiable Example```Python Calculate global temperature trendsfrom dask.distributed import Client import xarray as xr from scipy import stats from datetime import datetime import matplotlib.pyplot as plt def slope(y): x = list(range(0, len(y))) l = stats.linregress(x, y) return l.slope def main(): print(datetime.now(), "startup", flush = True) print(datetime.now(), "starting dask workers", flush = True) Client(n_workers=1, threads_per_worker=32, memory_limit='64GB')
if name == 'main': main() ``` MVCE confirmation
Relevant log outputNo response Anything else we need to know?This only seems to happen under load, so you will need to stress the server a bit to reproduce it. Environment
INSTALLED VERSIONS
------------------
commit: None
python: 3.8.15 (default, Nov 24 2022, 15:19:38)
[GCC 11.2.0]
python-bits: 64
OS: Linux
OS-release: 4.18.0-372.26.1.el8_6.x86_64
machine: x86_64
processor: x86_64
byteorder: little
LC_ALL: None
LANG: en_US.UTF-8
LOCALE: ('en_US', 'UTF-8')
libhdf5: None
libnetcdf: None
xarray: 2022.11.0
pandas: 1.5.2
numpy: 1.23.5
scipy: 1.9.3
netCDF4: None
pydap: None
h5netcdf: None
h5py: None
Nio: None
zarr: 2.13.3
cftime: None
nc_time_axis: None
PseudoNetCDF: None
rasterio: None
cfgrib: None
iris: None
bottleneck: 1.3.5
dask: 2022.02.1
distributed: 2022.2.1
matplotlib: 3.6.2
cartopy: None
seaborn: None
numbagg: None
fsspec: 2022.11.0
cupy: None
pint: None
sparse: None
flox: None
numpy_groupies: None
setuptools: 65.5.0
pip: 22.3.1
conda: None
pytest: None
IPython: None
sphinx: None
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13221727 | issue |