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/1793#issuecomment-360590825,https://api.github.com/repos/pydata/xarray/issues/1793,360590825,MDEyOklzc3VlQ29tbWVudDM2MDU5MDgyNQ==,3019665,2018-01-25T20:29:58Z,2018-01-25T20:29:58Z,NONE,"Yep, using `dask.array.store` regularly with the `distributed` scheduler both on our cluster and in a local Docker image for testing. Am using Zarr Arrays as the targets for `store` to write to. Basically rechunk the data to match the chunking selected for the Zarr Array and then write out in parallel lock-free.

Our cluster uses NFS for things like one's home directory. So these are accessible across nodes. Also there are other types of storage available that are a bit faster and still remain accessible across nodes. So these work pretty well.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,283388962