Dear Spark Users, Currently is there a way to dynamically allocate resources to Spark on Mesos? Within Spark we can specify the CPU cores, memory before running job. The way I understand is that the Spark job will not run if the CPU/Mem requirement is not met. This may lead to decrease in overall utilization of the cluster. An alternative behavior is to launch the job with the best resource offer Mesos is able to give. Is this possible with the current implementation?
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