Databricks Data Engineer Professional Question 6
Select 3You are tasked with setting up a Databricks cluster for a production workload that involves processing large volumes of data using Delta Lake. The workload requires high availability and auto-scaling based on the data processing needs. Additionally, you need to log cluster events and monitor the cluster's performance. Which combination of Databricks features should you use to meet these requirements?
- A
Enable autoscaling for the cluster.
- B
Configure instance pools for efficient resource management.
- C
Enable cluster logging and set up a destination for logs.
- D
Use a shared job cluster to minimize costs.
- E
Enable high concurrency mode for the cluster.
Show answer and explanation
Correct answers: A, B, C
Explanation
To meet the requirements of a production workload, you need to ensure that the cluster can scale dynamically, manage resources efficiently, and provide logging for monitoring and troubleshooting. Autoscaling and instance pools address the scaling and resource management needs, while enabling cluster logging ensures operational visibility. High concurrency mode and shared job clusters are not optimal choices for this scenario.
- A. Correct.
Enabling autoscaling ensures that the cluster can scale up or down based on workload demands, which is critical for handling large volumes of data efficiently.
- B. Correct.
Instance pools allow for efficient management of resources by reducing cluster startup times and reusing instances, which is important in a production environment.
- C. Correct.
Enabling cluster logging and setting up a destination for logs ensures that you can monitor the cluster’s performance and troubleshoot issues effectively, which is essential for production workloads.
- D. Incorrect.
A shared job cluster is more suited for short-lived jobs and does not offer the flexibility required for a production workload requiring high availability and monitoring.
- E. Incorrect.
High concurrency mode is designed for serving multiple users or queries simultaneously but is not directly relevant to the auto-scaling, high availability, and logging requirements of this scenario.