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Answer: A new job cluster is the preferred choice for updating a dashboard every 30 minutes.
All provided statements accurately describe the differences between using an existing all-purpose cluster and a new job cluster in Databricks, except for the first one. For tasks such as dashboard updates, leveraging an existing all-purpose cluster is advised due to: - **Resource Utilization**: All-purpose clusters are versatile, handling diverse tasks with fluctuating resource needs. Dashboard updates generally don't demand continuous high resource usage, making shared existing clusters ideal. - **Efficiency**: Utilizing existing clusters eliminates the need for creating new ones for each update, enhancing computational resource efficiency. - **Cost Savings**: Maximizing the use of available resources helps in cost optimization by minimizing the number of required clusters. For further details, refer to: Choosing the cluster type for the job.
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When creating a job in Databricks, which statement inaccurately describes the difference between using an existing all-purpose cluster and a new job cluster?
A
If you opt for a new job cluster during job creation, the cluster is terminated once the last task utilizing it is finished.
B
Selecting a terminated all-purpose cluster requires the job owner to have at least 'Can Restart' permissions for the job to execute successfully.
C
A new job cluster is the preferred choice for updating a dashboard every 30 minutes.
D
In the event of a job cluster failure during job execution, a replacement job cluster is automatically generated.
E
Choosing a new job cluster means the cluster is initiated when the first task of the job begins.