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Stephanie Wang
41b8675d04
* Clean up plasma subscribers on EPIPE First pass at a monitoring script - monitor can detect local scheduler death Clean up task table upon local scheduler death in monitoring script Don't schedule to dead local schedulers in global scheduler Have global scheduler update the db clients table, monitor script cleans up state Documentation Monitor script should scan tables before beginning to read from subscription channel Fix for python3 Redirect monitor output to redis logs, fix hanging in multinode tests * Publish auxiliary addresses as part of db_client deletion notifications * Fix test case? * Small changes. * Use SCAN instead of KEYS * Address comments * Address more comments * Free redis module strings
Ray
Ray is an experimental distributed execution engine. It is under development and not ready to be used.
The goal of Ray is to make it easy to write machine learning applications that run on a cluster while providing the development and debugging experience of working on a single machine.
View the documentation.