{"action":"created","issue":{"url":"https://api.github.com/repos/JuliaParallel/DistributedArrays.jl/issues/176","repository_url":"https://api.github.com/repos/JuliaParallel/DistributedArrays.jl","labels_url":"https://api.github.com/repos/JuliaParallel/DistributedArrays.jl/issues/176/labels{/name}","comments_url":"https://api.github.com/repos/JuliaParallel/DistributedArrays.jl/issues/176/comments","events_url":"https://api.github.com/repos/JuliaParallel/DistributedArrays.jl/issues/176/events","html_url":"https://github.com/JuliaParallel/DistributedArrays.jl/issues/176","id":365273515,"node_id":"MDU6SXNzdWUzNjUyNzM1MTU=","number":176,"title":"Load Files Into Portions of Arrays","user":{"login":"r-barnes","id":3118036,"node_id":"MDQ6VXNlcjMxMTgwMzY=","avatar_url":"https://avatars0.githubusercontent.com/u/3118036?v=4","gravatar_id":"","url":"https://api.github.com/users/r-barnes","html_url":"https://github.com/r-barnes","followers_url":"https://api.github.com/users/r-barnes/followers","following_url":"https://api.github.com/users/r-barnes/following{/other_user}","gists_url":"https://api.github.com/users/r-barnes/gists{/gist_id}","starred_url":"https://api.github.com/users/r-barnes/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/r-barnes/subscriptions","organizations_url":"https://api.github.com/users/r-barnes/orgs","repos_url":"https://api.github.com/users/r-barnes/repos","events_url":"https://api.github.com/users/r-barnes/events{/privacy}","received_events_url":"https://api.github.com/users/r-barnes/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":3,"created_at":"2018-09-30T23:46:53Z","updated_at":"2018-10-01T14:56:49Z","closed_at":null,"author_association":"NONE","body":"I have a large number of matrices stored to disk on a distributed system. Together, they represent a grid of data, like so:\r\n\r\n    X X X X\r\n    X X X X\r\n    X X X X \r\n\r\nwhere each `X` is a matrix contained in a different file.\r\n\r\nEventually, I'll do focal operations which will require transmitting data at the borders of these matrices between machines. DistributedArrays seems like a good way of doing this.\r\n\r\nBut it's unclear whether it's possible to force distributed arrays to break the data apart into an `m x n` grid where the portion of the distributed array allotted to each processor is guaranteed to be a specified size. (More generally, the particular size could vary between processes as long as each entry of a given row and each entry of a given column of the grid had the same shape.)\r\n\r\nIs there a way to induce and enforce this behavior?\r\n\r\nPerhaps a constructor could be added?"},"comment":{"url":"https://api.github.com/repos/JuliaParallel/DistributedArrays.jl/issues/comments/425938723","html_url":"https://github.com/JuliaParallel/DistributedArrays.jl/issues/176#issuecomment-425938723","issue_url":"https://api.github.com/repos/JuliaParallel/DistributedArrays.jl/issues/176","id":425938723,"node_id":"MDEyOklzc3VlQ29tbWVudDQyNTkzODcyMw==","user":{"login":"vchuravy","id":145258,"node_id":"MDQ6VXNlcjE0NTI1OA==","avatar_url":"https://avatars2.githubusercontent.com/u/145258?v=4","gravatar_id":"","url":"https://api.github.com/users/vchuravy","html_url":"https://github.com/vchuravy","followers_url":"https://api.github.com/users/vchuravy/followers","following_url":"https://api.github.com/users/vchuravy/following{/other_user}","gists_url":"https://api.github.com/users/vchuravy/gists{/gist_id}","starred_url":"https://api.github.com/users/vchuravy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/vchuravy/subscriptions","organizations_url":"https://api.github.com/users/vchuravy/orgs","repos_url":"https://api.github.com/users/vchuravy/repos","events_url":"https://api.github.com/users/vchuravy/events{/privacy}","received_events_url":"https://api.github.com/users/vchuravy/received_events","type":"User","site_admin":false},"created_at":"2018-10-01T14:56:48Z","updated_at":"2018-10-01T14:56:48Z","author_association":"MEMBER","body":"Yes in theory you can use any chunk type which includes sparse arrays, I can't promise you that we do smart things with it though ;)"}}
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