Google Professional Data Engineer
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NO.34 Scaling a Cloud Dataproc cluster typically involves _____.
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A
increasing or decreasing the number of worker nodes
B
increasing or decreasing the number of master nodes
C
moving memory to run more applications on a single node
D
deleting applications from unused nodes periodically
Explanation:
After creating a Cloud Dataproc cluster, you can scale the cluster by increasing or decreasing the number of worker nodes in the cluster at any time, even when jobs are running on the cluster. Cloud Dataproc clusters are typically scaled to:
- increase the number of workers to make a job run faster
- decrease the number of workers to save money
- increase the number of nodes to expand available Hadoop Distributed Filesystem (HDFS) storage
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