issues: 1465287257
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| id | node_id | number | title | user | state | locked | assignee | milestone | comments | created_at | updated_at | closed_at | author_association | active_lock_reason | draft | pull_request | body | reactions | performed_via_github_app | state_reason | repo | type |
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| 1465287257 | I_kwDOAMm_X85XVoJZ | 7325 | Support reading Zarr data via TensorStore | 1217238 | open | 0 | 1 | 2022-11-27T00:12:17Z | 2023-05-11T01:24:27Z | MEMBER | 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. |
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13221727 | issue |