Discuss Google Professional Cloud Architect (PR000213) Exam Topic 6 Question 100

Your company has a Google Cloud project that uses BigQuery for data warehousing on a pay-per-use basis. You want to monitor queries in real time to discover the most costly queries and which users spend the most. What should you do?

A1. Create a Cloud Logging sink to export BigQuery data access logs to Cloud Storage. 2. Develop a Dataflow pipeline to compute the cost of queries split by users.

B1. Create a Cloud Logging sink to export BigQuery data access logs to BigQuery.
2. Perform a BigQuery query on the generated table to extract the information you need.

C1. Activate billing export into BigQuery.
2. Perform a BigQuery query on the billing table to extract the information you need.

D1. In the BigQuery dataset that contains all the tables to be queried, add a label for each user that can launch a query.
2. Open the Billing page of the project.
3. Select Reports.
4. Select BigQuery as the product and filter by the user you want to check.

Suggested Answer: C

https://cloud.google.com/blog/products/data-analytics/taking-a-practical-approach-to-bigquery-cost-monitoring

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38 comments · newest first

Vilma 11 months ago

Wait, can you really track costs just by adding labels? That seems too easy!

Silvana 11 months ago

I agree with B, querying the logs directly is straightforward.

Avery 11 months ago

D seems a bit manual, not sure if it's the most efficient way.

Haydee 11 months ago

I think C is the best choice for tracking costs effectively.

Oren 12 months ago

Option B sounds solid, exporting logs to BigQuery is smart.

Chau 12 months ago

I think option A might be overcomplicating things with Dataflow. I remember we practiced simpler methods, but I can't remember if they were as effective for tracking costs.

Lenna 1 year ago

I feel like option D is a bit manual with all those steps. I can't recall if we covered how effective it is for real-time monitoring, though.

Lajuana 1 year ago

I remember discussing option C in our study group. Activating billing export to BigQuery seems like a straightforward way to analyze costs, but I wonder if it gives real-time insights.

Lang 1 year ago

I think option B sounds familiar because it involves exporting logs to BigQuery, which we practiced in class. But I'm not entirely sure if that's the best way to monitor costs in real time.

Tanja 1 year ago

I like the idea of using the billing export in option C. That seems like a straightforward way to get the cost information I need. I'll have to make sure I understand how to filter the data properly.

Johanna 1 year ago

Option A looks good to me. Exporting the logs to Cloud Storage and then using Dataflow to process them seems like a robust solution that will give me the real-time monitoring I need.

Nobuko 1 year ago

Hmm, I'm a bit confused. There are a few different options here, and I'm not sure which one is the best approach. I'll need to think this through carefully.

Altha 1 year ago

This seems like a straightforward question. I think option B is the way to go - exporting the BigQuery logs to a BigQuery table and then querying that table to get the information I need.

Jacki 2 years ago

Option C, huh? I guess they're really trying to squeeze every penny out of our BigQuery usage. Better keep those queries lean and mean!

Vallie 2 years ago

Option D? More like Option 'Doh!' Am I right? Someone's been drinking too much cloud Kool-Aid.

Art 2 years ago

↳ replying to Vallie

D) In the BigQuery dataset that contains all the tables to be queried, add a label for each user that can launch a query. Open the Billing page of the project. Select Reports. Select BigQuery as the product and filter by the user you want to check.

Bernardo 2 years ago

↳ replying to Vallie

C) Activate billing export into BigQuery. Perform a BigQuery query on the billing table to extract the information you need.

Shawnda 2 years ago

↳ replying to Vallie

B) Create a Cloud Logging sink to export BigQuery data access logs to BigQuery. Perform a BigQuery query on the generated table to extract the information you need.

Jaime 2 years ago

↳ replying to Vallie

A) Create a Cloud Logging sink to export BigQuery data access logs to Cloud Storage. Develop a Dataflow pipeline to compute the cost of queries split by users.

Arlene 2 years ago

I'd go with Option B. Keeping the logs in BigQuery just makes sense - no need to export them anywhere else. Efficient and straightforward.

Marvel 2 years ago

Option A gets my vote. Dataflow can crunch the numbers and give us the insights we need. Plus, Storage is much cooler than BigQuery, right?

Eric 2 years ago

Option D is way too complicated. Who has time to mess with all those labels and Billing reports? No thanks!

Quentin 2 years ago

↳ replying to Eric

B) 1. Create a Cloud Logging sink to export BigQuery data access logs to BigQuery. 2. Perform a BigQuery query on the generated table to extract the information you need.

Rosalind 2 years ago

↳ replying to Eric

A) 1. Create a Cloud Logging sink to export BigQuery data access logs to Cloud Storage. 2. Develop a Dataflow pipeline to compute the cost of queries split by users.

Ria 2 years ago

Option C looks good to me. Tapping into the billing data should give us the details we need on query costs and user activity.

Rasheeda 2 years ago

↳ replying to Ria

2. Perform a BigQuery query on the billing table to extract the information you need.

Beckie 2 years ago

↳ replying to Ria

C) 1. Activate billing export into BigQuery.

Deeanna 2 years ago

I'm not sure, I think option B could also work. Exporting BigQuery data access logs to BigQuery and performing a query on the generated table might provide the information we need.

Charolette 2 years ago

I think Option B is the way to go. Exporting the logs directly to BigQuery makes the data more accessible for querying.

Joesph 2 years ago

↳ replying to Charolette

Let's go with Option B then. It's a straightforward solution to analyze costly queries and user spending.

Katlyn 2 years ago

↳ replying to Charolette

I agree, it seems like the most efficient way to monitor queries and track user activity.

Paulina 2 years ago

↳ replying to Charolette

Option B is a good choice. Exporting logs to BigQuery will make it easier to extract the information we need.

Sabine 2 years ago

I agree with Lacey. Option A seems like the most efficient way to monitor queries in real time and identify the most costly queries and users.

Lacey 2 years ago

I think option A is the best choice because it involves exporting BigQuery data access logs to Cloud Storage and developing a Dataflow pipeline to compute the cost of queries split by users.

Lavonna 2 years ago

Option A seems the most comprehensive approach to monitoring BigQuery queries and costs in real-time.

Daisy 2 years ago

↳ replying to Lavonna

Yes, it would definitely help in identifying the most costly queries and which users are spending the most.

Oren 2 years ago

↳ replying to Lavonna

I agree, creating a Cloud Logging sink to export BigQuery data access logs to Cloud Storage and developing a Dataflow pipeline sounds efficient.

Gayla 2 years ago

↳ replying to Lavonna

Option A seems the most comprehensive approach to monitoring BigQuery queries and costs in real-time.

Google Professional Cloud Architect (PR000213) Exam - Topic 6 Question 100 Discussion