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Production deployment tracking #4
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This failed on another malformed url issue (really, a missing data issue), which had slipped through the cracks due to an error in the unit tests. I fixed this in #5, and redeployed on merge of that PR. 🤞 Updates to follow. |
The third deployment failed with the error reported in #6, which hopefully fixes the issue. |
The fourth deployment proceeded well, caching 2655 of some 2900 or so files before stalling of unclear reasons. I've just re-deployed from #7. |
🎉 Success! import xarray as xr
p = "https://ncsa.osn.xsede.org/Pangeo/pangeo-forge/aqua-modis-feedstock/aqua-modis-682286948-6702057605-1/aqua-modis.zarr"
ds = xr.open_dataset(p, engine="zarr", chunks={})
ds.nbytes/1e9 # --> 757.954773176 GB
ds
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Opening this issue as a place to track progress of production deployments on GCP Dataflow. So far:
make_dates
function had some inaccurate assumptions built into it.The text was updated successfully, but these errors were encountered: