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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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1340994913 | I_kwDOAMm_X85P7fVh | 6924 | Memory Leakage Issue When Running to_netcdf | lassiterdc 64621312 | closed | 0 | 2 | 2022-08-16T23:58:17Z | 2023-01-17T18:38:40Z | 2023-01-17T18:38:40Z | NONE | What is your issue?I have a zarr file that I'd like to convert to a netcdf which is too large to fit in memory. My computer has 32GB of RAM so writing ~5.5GB chunks shouldn't be a problem. However, within seconds of running this script, my memory usage quickly tops out consuming the available ~20GB and the script fails. Data: Dropbox link to zarr file containing radar rainfall data for 6/28/2014 over the United States that is around 1.8GB in total. Code: ```python import xarray as xr import zarr fpath_zarr = "out_zarr_20140628.zarr" ds_from_zarr = xr.open_zarr(store=fpath_zarr, chunks={'outlat':3500, 'outlon':7000, 'time':30}) ds_from_zarr.to_netcdf("ds_zarr_to_nc.nc", encoding= {"rainrate":{"zlib":True}}) ``` Outputs:
Package versions:
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1340474484 | I_kwDOAMm_X85P5gR0 | 6920 | Writing a netCDF file is slow | lassiterdc 64621312 | closed | 1 | 3 | 2022-08-16T14:48:37Z | 2022-08-16T17:05:37Z | 2022-08-16T17:05:37Z | NONE | What is your issue?This has been discussed in another thread, but the proposed solution there (first Data: dropbox link to 717 netcdf files containing radar rainfall data for 6/28/2014 over the United States that is around 1GB in total. Code: ```python %% Import librariesimport xarray as xr from glob import glob import pandas as pd import time import dask dask.config.set(**{'array.slicing.split_large_chunks': False}) files = glob("data/*.nc") %% functionsdef extract_file_timestep(fname): fname = fname.split('/')[-1] fname = fname.split(".") ftype = fname.pop(-1) fname = ''.join(fname) str_tstep = fname.split("_")[-1] if ftype == "nc": date_format = '%Y%m%d%H%M' if ftype == "grib2": date_format = '%Y%m%d-%H%M%S'
def ds_preprocessing(ds): tstamp = extract_file_timestep(ds.encoding['source']) ds.coords["time"] = tstamp ds = ds.expand_dims({"time":1}) ds = ds.rename({"lon":"longitude", "lat":"latitude", "mrms_a2m":"rainrate"}) ds = ds.chunk(chunks={"latitude":3500, "longitude":7000, "time":1}) return ds %% Loading and formatting datalst_ds = [] start_time = time.time() for f in files: ds = xr.open_dataset(f, chunks={"latitude":3500, "longitude":7000}) ds = ds_preprocessing(ds) lst_ds.append(ds) ds_comb_frm_lst = xr.concat(lst_ds, dim="time") print("Time to load dataset using concat on list of datasets: {}".format(time.time() - start_time)) start_time = time.time() ds_comb_frm_open_mfdataset = xr.open_mfdataset(files, chunks={"latitude":3500, "longitude":7000}, concat_dim = "time", preprocess=ds_preprocessing, combine="nested") print("Time to load dataset using open_mfdataset: {}".format(time.time() - start_time)) %% exporting to netcdfstart_time = time.time() ds_comb_frm_lst.to_netcdf("ds_comb_frm_lst.nc", encoding= {"rainrate":{"zlib":True}}) print("Time to export dataset created using concat on list of datasets: {}".format(time.time() - start_time)) start_time = time.time() ds_comb_frm_open_mfdataset.to_netcdf("ds_comb_frm_open_mfdataset.nc", encoding= {"rainrate":{"zlib":True}}) print("Time to export dataset created using open_mfdataset: {}".format(time.time() - start_time)) ``` |
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1332143835 | I_kwDOAMm_X85PZubb | 6892 | 2 Dimension Plot Producing Discontinuous Grid | lassiterdc 64621312 | closed | 0 | 1 | 2022-08-08T16:59:14Z | 2022-08-08T17:12:41Z | 2022-08-08T17:11:44Z | NONE | What is your issue?Problem: I'm expecting a plot that looks like the one here (Plotting-->Two Dimensions-->Simple Example) with a continuous grid, but instead I'm getting the plot below which has a discontinuous grid. This could be due to different spacing in the x and y dimensions (0.005 spacing in the Reprex:
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1308176241 | I_kwDOAMm_X85N-S9x | 6805 | PermissionError: [Errno 13] Permission denied | lassiterdc 64621312 | closed | 0 | 5 | 2022-07-18T16:05:31Z | 2022-07-18T17:58:38Z | 2022-07-18T17:58:38Z | NONE | What is your issue?This was raised about a year ago but still seems to be unresolved, so I'm hoping this will bring attention back to the issue. (https://github.com/pydata/xarray/issues/5488) Data: dropbox sharing link Description: This folder contains 2 files each containing 1 day's worth of 1kmx1km gridded precipitation rate data from the National Severe Storms Laboratory. Each is about a gig (sorry they're so big, but it's what I'm working with!) Code: ```python import xarray as xr f_in_ncs = "data/" f_in_nc = "data/20190520.nc" %% worksds = xr.open_dataset(f_in_nc, chunks={'outlat':3500, 'outlon':7000, 'time':50}) %% doesn't workmf_ds = xr.open_mfdataset(f_in_ncs, concat_dim = "time",
chunks={'outlat':3500, 'outlon':7000, 'time':50},
combine = "nested", engine = 'netcdf4')
KeyError Traceback (most recent call last) File c:\Users\Daniel\anaconda3\envs\mrms\lib\site-packages\xarray\backends\file_manager.py:199, in CachingFileManager._acquire_with_cache_info(self, needs_lock) 198 try: --> 199 file = self._cache[self._key] 200 except KeyError: File c:\Users\Daniel\anaconda3\envs\mrms\lib\site-packages\xarray\backends\lru_cache.py:53, in LRUCache.getitem(self, key) 52 with self._lock: ---> 53 value = self._cache[key] 54 self._cache.move_to_end(key) KeyError: [<class 'netCDF4._netCDF4.Dataset'>, ('d:\mrms_processing\_reprex\2022-7-18_open_mfdataset\data',), 'r', (('clobber', True), ('diskless', False), ('format', 'NETCDF4'), ('persist', False))] During handling of the above exception, another exception occurred: PermissionError Traceback (most recent call last) Input In [4], in <cell line: 5>() 1 import xarray as xr 3 f_in_ncs = "data/" ----> 5 ds = xr.open_mfdataset(f_in_ncs, concat_dim = "time", 6 chunks={'outlat':3500, 'outlon':7000, 'time':50}, 7 combine = "nested", engine = 'netcdf4') File c:\Users\Daniel\anaconda3\envs\mrms\lib\site-packages\xarray\backends\api.py:908, in open_mfdataset(paths, chunks, concat_dim, compat, preprocess, engine, data_vars, coords, combine, parallel, join, attrs_file, combine_attrs, **kwargs) ... File src\netCDF4_netCDF4.pyx:2307, in netCDF4._netCDF4.Dataset.init() File src\netCDF4_netCDF4.pyx:1925, in netCDF4._netCDF4._ensure_nc_success() PermissionError: [Errno 13] Permission denied: b'd:\mrms_processing\_reprex\2022-7-18_open_mfdataset\data' ``` |
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completed | xarray 13221727 | issue |
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