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/issues/1822#issuecomment-357549143,https://api.github.com/repos/pydata/xarray/issues/1822,357549143,MDEyOklzc3VlQ29tbWVudDM1NzU0OTE0Mw==,25473287,2018-01-14T22:44:15Z,2018-01-14T22:44:15Z,NONE,"I agree that they can be both implemented, and dask is useful for out-of-core. If anyone would like to contribute, please see [JiaweiZhuang/xESMF#3 (comment)](https://github.com/JiaweiZhuang/xESMF/issues/3#issuecomment-357548515) for my preliminary experiments with `xr.apply_ufunc`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,287969295
https://github.com/pydata/xarray/issues/1822#issuecomment-357533707,https://api.github.com/repos/pydata/xarray/issues/1822,357533707,MDEyOklzc3VlQ29tbWVudDM1NzUzMzcwNw==,25473287,2018-01-14T19:05:29Z,2018-01-14T19:05:29Z,NONE,"Thanks for bringing this up... I've made more experiments and realized that Numba is actually faster than `scipy.sparse`, and also shows excellent parallel efficiency. See [this notebook](https://github.com/JiaweiZhuang/sparse_dot/blob/master/sparse_dot_benchmark.ipynb) for all details. Thus I consider switch to Numba and add parallel support in the next version. It should fit better than `xr.apply_ufunc` in this case. Let's discuss in the original thread if you have further suggestions.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,287969295