html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/pull/1024#issuecomment-258619392,https://api.github.com/repos/pydata/xarray/issues/1024,258619392,MDEyOklzc3VlQ29tbWVudDI1ODYxOTM5Mg==,4160723,2016-11-05T15:37:46Z,2016-11-05T15:37:46Z,MEMBER,"> we already cache an index in memory for any labeled indexing operations

Oh yes, true!

> So at best, you could do something like ds.isel(mesh_edge=slice(int(1e6)))

Indeed, that doesn't look very nice.

> For out-of-core operations with labels on big unstructured meshes, you really need a generalization of the pandas.Index that doesn't need to live in memory

From what I intend to do next with xarray, I'd say that extending its support for out-of-core operations to big indexes would be a great feature! I haven't seen yet how `dask.Dataframe` works internally (including `dask.Dataframe.index`and `dask.Dataframe.loc`), but I guess maybe this could be transposed in some way to the indexing logic in xarray? Though I'm certainly missing a lot of potential issues here... Anyway, I can open a new issue to discuss more about this if you think it's worth it.
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https://github.com/pydata/xarray/pull/1024#issuecomment-258496425,https://api.github.com/repos/pydata/xarray/issues/1024,258496425,MDEyOklzc3VlQ29tbWVudDI1ODQ5NjQyNQ==,4160723,2016-11-04T17:29:54Z,2016-11-04T17:29:54Z,MEMBER,"Option D seems indeed the cleanest and safest option, but

> Even eagerly loading indexes is potentially problematic, if loading the index values is expensive.

I can see use cases where this might happen. For example, It is common for 1, 2 or higher-dimension unstructured meshes that the coordinates x, y, z are arranged as 1-d arrays of length that equals the number of nodes (which can be very high!). See for example [ugrid conventions](http://ugrid-conventions.github.io/ugrid-conventions/).

I admit that currently xarray is perhaps not very suited for handling unstructured meshes, but IMO it has great potential (especially considering multi-index support) and I'd love to use it here.
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