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- Dataset to zarr not working with newest s3fs Storage (s3fs > 0.5.0) · 5 ✖
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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738728863 | https://github.com/pydata/xarray/issues/4478#issuecomment-738728863 | https://api.github.com/repos/pydata/xarray/issues/4478 | MDEyOklzc3VlQ29tbWVudDczODcyODg2Mw== | forman 206773 | 2020-12-04T11:18:33Z | 2020-12-04T11:18:33Z | NONE | I'm still suffering from Here are my relevant packages:
Thanks in advance! |
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Dataset to zarr not working with newest s3fs Storage (s3fs > 0.5.0) 712782711 | |
704365715 | https://github.com/pydata/xarray/issues/4478#issuecomment-704365715 | https://api.github.com/repos/pydata/xarray/issues/4478 | MDEyOklzc3VlQ29tbWVudDcwNDM2NTcxNQ== | jhnnsrs 3322897 | 2020-10-06T15:46:21Z | 2020-10-06T15:46:21Z | NONE | Welcome to the world of light-sheet microscopy. And this would be considered a tiny dataset.. 😄 @rabernat thanks for the tip. I was wondering what would be best chunk-size for s3 bucket storages. Will aim for that size once performance tweaking. Thanks a lot! |
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Dataset to zarr not working with newest s3fs Storage (s3fs > 0.5.0) 712782711 | |
704351253 | https://github.com/pydata/xarray/issues/4478#issuecomment-704351253 | https://api.github.com/repos/pydata/xarray/issues/4478 | MDEyOklzc3VlQ29tbWVudDcwNDM1MTI1Mw== | jhnnsrs 3322897 | 2020-10-06T15:27:56Z | 2020-10-06T15:27:56Z | NONE | Confirmed! Works like a charm. Went up all the way to (1024,1024,100,3,1) without any issues. Thanks for the fast fix! 👍 |
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Dataset to zarr not working with newest s3fs Storage (s3fs > 0.5.0) 712782711 | |
702815971 | https://github.com/pydata/xarray/issues/4478#issuecomment-702815971 | https://api.github.com/repos/pydata/xarray/issues/4478 | MDEyOklzc3VlQ29tbWVudDcwMjgxNTk3MQ== | jhnnsrs 3322897 | 2020-10-02T15:58:44Z | 2020-10-02T15:58:44Z | NONE | Okay. That was too fast. Wasn't able to get the django implementation running, so I setup a testing environment with a docker composition running minio and a python3.8 based container with the libraries (repo attached). The setup runs fine for dask arrays of size (1024,1024,8,2,1) but causes the same asyncio problematic at (1024,1024,10,2,1) (tested with random arrays) |
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Dataset to zarr not working with newest s3fs Storage (s3fs > 0.5.0) 712782711 | |
702635437 | https://github.com/pydata/xarray/issues/4478#issuecomment-702635437 | https://api.github.com/repos/pydata/xarray/issues/4478 | MDEyOklzc3VlQ29tbWVudDcwMjYzNTQzNw== | jhnnsrs 3322897 | 2020-10-02T09:51:32Z | 2020-10-02T09:51:32Z | NONE | Thanks for the troubleshooting. I encountered the problem within an sync worker in django channels (has been and is still working with s3fs=0.4.1 ) (same error). So I tried running the refactored relevant code in a vanilla python script on a linux docker container with WSL2 backend, no event loops and no threads running. Same results and the reason I posted in in xarray issues. No coming back to this problem a day the vanilla script works perfectly sound and gets the job down! The Django sync worker example still runs into problems:
I guess this is now more of a problem with the way django >=3.1 and particularly django-channels is dealing with the event loop. Do you have by any chance quick thoughts on this? Is there a way to get the django "superpowered" event loop instead of the asyncio one? Anyway will mark this bug report as resolved as it is cleary not xarrays issue. Thanks a lot ! |
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Dataset to zarr not working with newest s3fs Storage (s3fs > 0.5.0) 712782711 |
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