{"action":"created","issue":{"url":"https://api.github.com/repos/FTSRG/trainbenchmark/issues/98","repository_url":"https://api.github.com/repos/FTSRG/trainbenchmark","labels_url":"https://api.github.com/repos/FTSRG/trainbenchmark/issues/98/labels{/name}","comments_url":"https://api.github.com/repos/FTSRG/trainbenchmark/issues/98/comments","events_url":"https://api.github.com/repos/FTSRG/trainbenchmark/issues/98/events","html_url":"https://github.com/FTSRG/trainbenchmark/issues/98","id":254030067,"number":98,"title":"Add Spark implementation","user":{"login":"szarnyasg","id":1402801,"avatar_url":"https://avatars3.githubusercontent.com/u/1402801?v=4","gravatar_id":"","url":"https://api.github.com/users/szarnyasg","html_url":"https://github.com/szarnyasg","followers_url":"https://api.github.com/users/szarnyasg/followers","following_url":"https://api.github.com/users/szarnyasg/following{/other_user}","gists_url":"https://api.github.com/users/szarnyasg/gists{/gist_id}","starred_url":"https://api.github.com/users/szarnyasg/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/szarnyasg/subscriptions","organizations_url":"https://api.github.com/users/szarnyasg/orgs","repos_url":"https://api.github.com/users/szarnyasg/repos","events_url":"https://api.github.com/users/szarnyasg/events{/privacy}","received_events_url":"https://api.github.com/users/szarnyasg/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2017-08-30T14:56:29Z","updated_at":"2017-09-22T16:58:28Z","closed_at":null,"author_association":"OWNER","body":"See if it Spark SQL or GraphX can be adapted to this sort of workload. "},"comment":{"url":"https://api.github.com/repos/FTSRG/trainbenchmark/issues/comments/331502657","html_url":"https://github.com/FTSRG/trainbenchmark/issues/98#issuecomment-331502657","issue_url":"https://api.github.com/repos/FTSRG/trainbenchmark/issues/98","id":331502657,"user":{"login":"szarnyasg","id":1402801,"avatar_url":"https://avatars3.githubusercontent.com/u/1402801?v=4","gravatar_id":"","url":"https://api.github.com/users/szarnyasg","html_url":"https://github.com/szarnyasg","followers_url":"https://api.github.com/users/szarnyasg/followers","following_url":"https://api.github.com/users/szarnyasg/following{/other_user}","gists_url":"https://api.github.com/users/szarnyasg/gists{/gist_id}","starred_url":"https://api.github.com/users/szarnyasg/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/szarnyasg/subscriptions","organizations_url":"https://api.github.com/users/szarnyasg/orgs","repos_url":"https://api.github.com/users/szarnyasg/repos","events_url":"https://api.github.com/users/szarnyasg/events{/privacy}","received_events_url":"https://api.github.com/users/szarnyasg/received_events","type":"User","site_admin":false},"created_at":"2017-09-22T16:58:28Z","updated_at":"2017-09-22T16:58:28Z","author_association":"OWNER","body":"- Spark GraphX is not intended for these sort of graph computations.\r\n- Spark SQL would be able to express them: https://spark.apache.org/docs/latest/streaming-programming-guide.html#dataframe-and-sql-operations."}}
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