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  • martindurant · 5 ✖

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  • zarr as persistent store for xarray · 5 ✖

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id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
281990573 https://github.com/pydata/xarray/issues/1223#issuecomment-281990573 https://api.github.com/repos/pydata/xarray/issues/1223 MDEyOklzc3VlQ29tbWVudDI4MTk5MDU3Mw== martindurant 6042212 2017-02-23T13:25:36Z 2017-02-23T13:25:36Z CONTRIBUTOR

@alimanfoo , do you think this work would make more sense as part of zarr rather than as part of xarray?

 
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   zarr as persistent store for xarray 202260275
281860859 https://github.com/pydata/xarray/issues/1223#issuecomment-281860859 https://api.github.com/repos/pydata/xarray/issues/1223 MDEyOklzc3VlQ29tbWVudDI4MTg2MDg1OQ== martindurant 6042212 2017-02-23T01:25:52Z 2017-02-23T01:25:52Z CONTRIBUTOR

True, xarray_to_zarr is unchanged from before. The dataset functions could supercede, since a single xarray is just a special case of a dataset; or we could decide that for the special case it is worth having short-cut functions. I was worried about the number of metadata files being created, since on a remote system like S3, there is a large overhead to reading many small files.

 
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   zarr as persistent store for xarray 202260275
281813651 https://github.com/pydata/xarray/issues/1223#issuecomment-281813651 https://api.github.com/repos/pydata/xarray/issues/1223 MDEyOklzc3VlQ29tbWVudDI4MTgxMzY1MQ== martindurant 6042212 2017-02-22T21:42:49Z 2017-02-22T21:43:05Z CONTRIBUTOR

@alimanfoo , in the new dataset save function, I do exactly as you suggest, with everything getting put as a dict into the main zarr group attributes, with special attribute names "attrs" for the data-set root, "coords" for the set of coordinate objects and "variables" for the set of variables objects (all of these have their own attributes in xarray).

 
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   zarr as persistent store for xarray 202260275
279181938 https://github.com/pydata/xarray/issues/1223#issuecomment-279181938 https://api.github.com/repos/pydata/xarray/issues/1223 MDEyOklzc3VlQ29tbWVudDI3OTE4MTkzOA== martindurant 6042212 2017-02-11T22:56:56Z 2017-02-11T22:56:56Z CONTRIBUTOR

I have developed my example a little to sidestep subclassing you suggest, which seemed tricky to implement.

Please see https://gist.github.com/martindurant/06a1e98c91f0033c4649a48a2f943390 (dataset_to/from_zarr functions)

I can use the zarr groups structure to mirror at least typical use of xarrays: variables, coordinates and sets of attributes on each. I have tested this with s3 too, stealing a little code from dask to show the idea. 

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   zarr as persistent store for xarray 202260275
274202189 https://github.com/pydata/xarray/issues/1223#issuecomment-274202189 https://api.github.com/repos/pydata/xarray/issues/1223 MDEyOklzc3VlQ29tbWVudDI3NDIwMjE4OQ== martindurant 6042212 2017-01-20T22:57:07Z 2017-01-20T22:57:07Z CONTRIBUTOR

3: a json-like representation such as used by the hidden .xarray item would also do.

 
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   zarr as persistent store for xarray 202260275

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