Google Professional Data Engineer Question 260
Select 3Google Cloud PlatformYou are managing a Google Cloud project that processes large datasets with BigQuery. Recently, your team has started receiving quota limit errors when running queries. Upon investigation, you discover that the queries are failing due to the 'Bytes Billed per Query' limit being exceeded. What steps should you take to troubleshoot and resolve this issue?
- A
Review the query to optimize it and reduce the amount of data scanned.
- B
Increase the 'Bytes Billed per Query' quota in the Google Cloud Console.
- C
Request a quota increase by submitting a support ticket to Google Cloud Support.
- D
Switch to a flat-rate pricing model to avoid per-query billing limits.
- E
Use partitioned tables or clustered tables to reduce the amount of data scanned by queries.
Show answer and explanation
Correct answers: A, C, E
Explanation
When troubleshooting quota limit errors, it is important to first optimize the queries to reduce the data scanned. If the issue persists, a quota increase request can be submitted to Google Cloud Support. Additionally, leveraging partitioned or clustered tables can help improve query efficiency and prevent such errors. While pricing models like flat-rate may help manage costs, they do not directly resolve quota issues.
- A. Correct.
Optimizing the query to reduce the amount of data scanned can help stay within the quota limits. This involves techniques like using SELECT statements with specific fields, filtering data using WHERE clauses, or leveraging table partitions.
- B. Incorrect.
There is no option to directly increase the 'Bytes Billed per Query' quota in the Google Cloud Console. Quota increases must be requested via a support ticket.
- C. Correct.
Submitting a support ticket to request a quota increase is a valid step when troubleshooting quota issues. Google Cloud Support can help with raising specific limits.
- D. Incorrect.
Switching to a flat-rate pricing model is a pricing strategy, not a direct solution to resolving quota errors. It does not address the immediate issue with the query exceeding the 'Bytes Billed per Query' limit.
- E. Correct.
Using partitioned tables or clustered tables can help reduce the amount of data that queries scan, thereby preventing the quota from being exceeded. This is an effective optimization technique.