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D- reasons:
1.-Cloud Audit Logs maintains audit logs for admin activity, data access and system events. BIGQUERY is automatically send to cloud audit log functionality.
2.- In the filter you can filter relevant BigQuery Audit messages, you can express filters as part of the export
https://cloud.google.com/logging/docs/audit
https://cloud.google.com/bigquery/docs/reference/auditlogs#ids
https://cloud.google.com/bigquery/docs/reference/auditlogs#auditdata_examples
D is the right as you can get the monthly view of the query usage across all the users and projects for auditing purpose. C does need appropriate permission to see the detail level data. Monthly view is tough to get directly from the bq ls or bq show commands.
reason:
https://cloud.google.com/logging/docs/audit#data-access
Data Access audit logs—except for BigQuery Data Access audit logs—are disabled by default because audit logs can be quite large. If you want Data Access audit logs to be written for Google Cloud services other than BigQuery, you must explicitly enable them
I finally decide to go with Option D over B because we or the auditor might not have access to the metadata. In fact, in our project, not all of us had access to query this view.
"To get the permission that you need to query the INFORMATION_SCHEMA.JOBS view, ask your administrator to grant you the BigQuery Resource Viewer"
https://cloud.google.com/bigquery/docs/information-schema-jobs#required_role.
(And not because of the wordings "Table" instead of "view" - don't think an architect exam will try to assess your memory of whether it is a table or a view or your understanding of the difference between a table and a view).
C - bq show: To view job details (https://cloud.google.com/bigquery/docs/managing-jobs#view_job_details_2)
bq ls: To list jobs (https://cloud.google.com/bigquery/docs/managing-jobs#list_jobs)
So D is the correct one.
JOBS system table does exist and it contains exactly the info we need: one record for each job executed by users (query is one of the type of the jobs)
D. Use Cloud Audit Logging to view Cloud Audit Logs, and create a filter on the query operation to get the required information.
Cloud Audit Logging records activities and API calls in Google Cloud services, including BigQuery. You can use Cloud Audit Logging to view logs and filter them based on specific operations, such as queries in BigQuery. By filtering on the query operation, you can gather the required information about how many queries each user ran in the last month, which is essential for audit purposes.
A is not possible.
B is possible if VIEW is used instead of TABLE in the description. I use this view to get this information regularly.
C. I have no cloud how this can be right answer.
D. Only possible as per text descriptions.
The correct answer is D. Use Cloud Audit Logging to view Cloud Audit Logs, and create a filter on the query operation to get the required information.
Google Cloud's Cloud Audit Logging service allows you to view, search, and export audit logs for your Google Cloud projects. These audit logs contain information about the actions that are performed in your project, including queries that are run in BigQuery.
To see how many queries each user ran in the last month, you can use Cloud Audit Logging to view the Cloud Audit Logs for your BigQuery project. Then, you can create a filter on the query operation to see only the queries that were run. You can also create a filter on the user field to see the queries that were run by each user. This will allow you to see the number of queries that were run by each user in the last month, which can be useful for audit purposes.
Option A, connecting Google Data Studio to BigQuery and creating a dimension for the users and a metric for the amount of queries per user, is a valid method of visualizing data, but it would not provide the specific information about the number of queries that were run by each user in the last month.
Option B, executing a query on the JOBS table to get the required information, is not a viable option because the JOBS table does not contain information about the user who ran the query.
Option C, using the 'bq show' and 'bq ls' commands to list job information, is not a viable option because these commands do not provide information about the user who ran the query.
Option A: Why would this not provide correct information? You could show the content of the JOBS view. :
SELECT
user_email,
CAST(creation_time as DATE) as date,
count(*) as queries_per_day
FROM
`region-eu`.INFORMATION_SCHEMA.JOBS
WHERE
creation_time BETWEEN TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 45 DAY) AND CURRENT_TIMESTAMP()
AND job_type = 'QUERY'
group by user_email, CAST(creation_time as DATE)
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