You have an analytics application that runs hundreds of queries on BigQuery every few minutes using BigQuery API. You want to find out how much time these queries take to execute. What should you do?
A.
Use Stackdriver Monitoring to plot slot usage.
B.
Use Stackdriver Trace to plot API execution time.
C.
Use Stackdriver Trace to plot query execution time.
D.
Use Stackdriver Monitoring to plot query execution times.
BigQuery automatically exports query execution metrics to Cloud Monitoring (formerly Stackdriver Monitoring).
Cloud Trace is used for tracing latency in distributed applications, not for monitoring BigQuery query performance.
You can use these metrics to plot query execution time, such as:
query.execution_time
query.count
Stackdriver Trace provides detailed traces of individual requests, including the time spent in each function and database query.
However, Stackdriver Monitoring doesn't provide detailed information about individual query execution times.
D. Use Stackdriver Monitoring to plot query execution times.
Stackdriver Monitoring (now part of Google Cloud's operations suite) provides capabilities to monitor BigQuery and create custom dashboards to visualize various metrics, including query execution times. You can track how long your queries take to run by plotting the query_execution_times metric in a custom dashboard.
The correct answer is C. Use Stackdriver Trace to plot query execution time. Stackdriver Trace is a distributed tracing system that allows you to profile and debug your application's performance. It allows you to trace requests across multiple services, and it provides a detailed breakdown of where time is being spent within your application. Since you want to find out how much time your queries take to execute, using Stackdriver Trace to plot query execution time would be the most appropriate approach.
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