Databricks Data Engineer Professional Question 222
Select 4You have been tasked with monitoring a streaming job in Databricks that processes real-time data from a Kafka source. The job has been experiencing intermittent delays, and your team wants to identify the root cause. Which of the following steps can help you effectively monitor and troubleshoot the performance of the streaming job?
- A
Enable structured streaming metrics in the Spark UI to monitor the processing rates and latency of the streaming job.
- B
Use the Databricks REST API to retrieve the cluster event logs for identifying resource bottlenecks.
- C
Set up a Delta Live Tables pipeline to automatically optimize the streaming job's query plan.
- D
Check the query progress logs to analyze the input and processing rates of the streaming job.
- E
Use Ganglia metrics to assess the cluster's CPU and memory utilization.
Show answer and explanation
Correct answers: A, B, D, E
Explanation
Monitoring and troubleshooting streaming jobs in Databricks requires a combination of tools and techniques. Structured streaming metrics in the Spark UI, query progress logs, and Ganglia metrics provide insights into the job's performance and cluster resource usage. Additionally, the Databricks REST API can be used to access cluster logs and events to further diagnose issues. However, Delta Live Tables are not relevant for optimizing existing streaming jobs.
- A. Correct.
Enabling structured streaming metrics in the Spark UI provides detailed information on processing rates, input rates, and latency, which are crucial for monitoring streaming jobs.
- B. Correct.
The Databricks REST API can be used to fetch cluster logs and events, which can help identify resource-related issues like memory or CPU bottlenecks.
- C. Incorrect.
Delta Live Tables are useful for simplifying ETL pipelines, but they do not directly optimize or monitor existing structured streaming jobs.
- D. Correct.
Query progress logs contain valuable details about input rates, batch processing times, and state operation metrics, which are essential for diagnosing streaming performance issues.
- E. Correct.
Ganglia metrics help monitor the overall resource utilization of the cluster, providing insights into potential bottlenecks affecting the job's performance.