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Slow jobs or unresponsiveness

Sometimes, if the SparkContext cannot connect to a Spark standalone master, then the driver may display errors such as the following:

02/05/17 12:44:45 ERROR AppClient$ClientActor: All masters are unresponsive! Giving up. 02/05/17 12:45:31 ERROR SparkDeploySchedulerBackend: Application has been killed. Reason: All masters are unresponsive! Giving up. 02/05/17 12:45:35 ERROR TaskSchedulerImpl: Exiting due to error from cluster scheduler: Spark cluster looks down

At other times, the driver is able to connect to the master node but the master is unable to communicate back to the driver. Then, multiple attempts to connect are made even though the driver will report that it could not connect to the Master's log directory. ...

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