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  • Support parallel writes to zarr store · 1 ✖

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511174605 https://github.com/pydata/xarray/issues/3096#issuecomment-511174605 https://api.github.com/repos/pydata/xarray/issues/3096 MDEyOklzc3VlQ29tbWVudDUxMTE3NDYwNQ== shoyer 1217238 2019-07-14T05:28:22Z 2019-07-14T05:28:43Z MEMBER

With regards to open_mfdataset(), I checked the code and realized under the hood it's only calling multiple open_dataset(). I was worried it would load the values (and not only metadata) in memory, but I checked it on one file and it apparently does not. Can you confirm this ? In this case I could probably open my whole dataset at once, which would be very convenient.

Yes, this is the suggested workflow! open_mfdataset opens a collection of files lazily (with dask) into a single xarray dataset, suitable for converting into zarr all at once with to_zarr().

It is definitely possible to create a zarr dataset and then write to it in parallel with a bunch of processes, but not via xarray's to_zarr() method -- which can only parallelize with dask. You would have to create the dataset and write to it with the zarr Python API directly.

 
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