Support reading Zarr data via TensorStore

What is your issue?

TensorStore is another high performance API for reading distributed arrays in formats such as Zarr, written in C++.

It could be interesting to write an Xarray storage backend using TensorStore as an alternative way to read Zarr files.

As an exercise, I make a little demo of doing this: https://gist.github.com/shoyer/5b0c485979cc9c36a9685d8cf8e94565

I have not tested it for performance. The main annoyance is that TensorStore doesn't understand Zarr groups or Zarr array attributes, so I needed to write my own helpers for reading this metadata.

Also, there's a bit of an impedance mis-match between TensorStore (where everything returns futures) and Xarray (which assumes that indexing results in numpy arrays). This could likely be improved with some amount of effort -- in particular https://github.com/pydata/xarray/pull/6874/files should help.

CC @jbms who may have better ideas about how to use the TensorStore API.

Start with the linked TensorStore demo gist and inspect the changes in xarray PR #6874. Define the scope for a TensorStore-backed Zarr reader, including group and array metadata and the future-to-indexing mismatch; done should include a tested backend design and implementation.