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1 row where author_association = "CONTRIBUTOR", issue = 267628781 and user = 6574622 sorted by updated_at descending

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user 1

  • d70-t · 1 ✖

issue 1

  • Low memory/out-of-core index? · 1 ✖

author_association 1

  • CONTRIBUTOR · 1 ✖
id html_url issue_url node_id user created_at updated_at ▲ author_association body reactions performed_via_github_app issue
824207037 https://github.com/pydata/xarray/issues/1650#issuecomment-824207037 https://api.github.com/repos/pydata/xarray/issues/1650 MDEyOklzc3VlQ29tbWVudDgyNDIwNzAzNw== d70-t 6574622 2021-04-21T16:46:54Z 2021-06-15T16:18:54Z CONTRIBUTOR

I'd be interested in this kind of thing as well. :+1:

We are having long time series data, which we would like to access via opendap or zarr over HTTP. Currently, the time coordinate variable is already more than 1 GB in size, which makes loading the dataset very slow or even impossible given the limitations of the opendap server and my home internet wire. Nonetheless, we know that the timestamps are in order and reasonably close to equidistant. Thus binary search or even interpolation search should be a quick method to find the right indices.

 
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   Low memory/out-of-core index? 267628781

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