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  • shoyer · 3 ✖

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  • Convert xarray dataset to dask dataframe or delayed objects · 3 ✖

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  • MEMBER · 3 ✖
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259213382 https://github.com/pydata/xarray/issues/1093#issuecomment-259213382 https://api.github.com/repos/pydata/xarray/issues/1093 MDEyOklzc3VlQ29tbWVudDI1OTIxMzM4Mg== shoyer 1217238 2016-11-08T18:09:11Z 2016-11-08T18:09:34Z MEMBER

The other component that would help for this is some utility function inside xarray to split a Dataset (or DataArray) into sub-datasets for each chunk. Something like:

python def split_by_chunks(dataset): chunk_slices = {} for dim, chunks in dataset.chunks.items(): slices = [] start = 0 for chunk in chunks: stop = start + chunk slices.append(slice(start, stop)) start = stop chunk_slices[dim] = slices for slices in itertools.product(*chunk_slices.values()): selection = dict(zip(chunk_slices.keys(), slices)) yield (selection, dataset[selection])

 
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   Convert xarray dataset to dask dataframe or delayed objects 187872991
259207151 https://github.com/pydata/xarray/issues/1093#issuecomment-259207151 https://api.github.com/repos/pydata/xarray/issues/1093 MDEyOklzc3VlQ29tbWVudDI1OTIwNzE1MQ== shoyer 1217238 2016-11-08T17:46:23Z 2016-11-08T17:46:23Z MEMBER

Can you explain why you think this could benefit from collection duck typing?

Then we could use xarray's normal indexing operations to create a new sub-datasets, wrap them with dask.delayed and start chaining on delayed method calls like to_dataframe. The duck typing is necessary so that dask.delayed knows how to pull the dask graph out from the input Dataset.

 
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   Convert xarray dataset to dask dataframe or delayed objects 187872991
259052436 https://github.com/pydata/xarray/issues/1093#issuecomment-259052436 https://api.github.com/repos/pydata/xarray/issues/1093 MDEyOklzc3VlQ29tbWVudDI1OTA1MjQzNg== shoyer 1217238 2016-11-08T05:55:19Z 2016-11-08T05:55:19Z MEMBER

CC @mrocklin @jcrist

This is a good use case for dask collection duck typing: https://github.com/dask/dask/pull/1068

 
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   Convert xarray dataset to dask dataframe or delayed objects 187872991

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