Explanation:
The primary difference between cluster and client execution modes in Apache Spark lies in the location of the driver program. In cluster mode, the driver runs on a worker node within the cluster, managed by the cluster manager (e.g., YARN, Kubernetes). This allows the client to disconnect after submission. In client mode, the driver runs on the client machine (e.g., an edge node), which means the client must remain active for the duration of the job.
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What is the difference between cluster mode and client mode in terms of execution?
A
The cluster execution mode runs the driver on a worker node within a cluster, while the client execution mode runs the driver on the client machine (also known as a gateway machine or edge node).
B
The cluster execution mode is run on a local cluster, while the client execution mode is run in the cloud.
C
The cluster execution mode distributes executors across worker nodes in a cluster, while the client execution mode runs a Spark job entirely on one client machine.
D
The cluster execution mode runs the driver on the cluster machine (also known as a gateway machine or edge node), while the client execution mode runs the driver on a worker node within a cluster.
E
The cluster execution mode distributes executors across worker nodes in a cluster, while the client execution mode submits a Spark job from a remote machine to be run on a remote, unconfigurable cluster.