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

Actual exam question for Google's Professional Cloud Architect (PR000213) exam
Question #: 100
Topic #: 6
[All Professional Cloud Architect (PR000213) Questions]

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?

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Suggested Answer: C

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


by Tegan at Jan 11, 2025, 12:22 PM

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Vilma
6 months ago
Wait, can you really track costs just by adding labels? That seems too easy!
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Silvana
6 months ago
I agree with B, querying the logs directly is straightforward.
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Avery
6 months ago
D seems a bit manual, not sure if it's the most efficient way.
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Haydee
7 months ago
I think C is the best choice for tracking costs effectively.
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Oren
7 months ago
Option B sounds solid, exporting logs to BigQuery is smart.
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Chau
7 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.
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Lenna
7 months 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.
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Lajuana
7 months 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.
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Lang
8 months 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.
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Tanja
8 months 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.
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Johanna
8 months 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.
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Nobuko
8 months 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.
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Altha
8 months 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.
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Jacki
1 year 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!
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Vallie
1 year ago
Option D? More like Option 'Doh!' Am I right? Someone's been drinking too much cloud Kool-Aid.
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Art
1 year ago
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.
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Bernardo
1 year ago
C) Activate billing export into BigQuery. Perform a BigQuery query on the billing table to extract the information you need.
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Shawnda
1 year ago
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.
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Jaime
1 year ago
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.
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Arlene
1 year 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.
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Marvel
1 year 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?
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Eric
1 year ago
Option D is way too complicated. Who has time to mess with all those labels and Billing reports? No thanks!
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Quentin
1 year ago
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.
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Rosalind
1 year ago
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.
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Ria
1 year 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.
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Rasheeda
1 year ago
2. Perform a BigQuery query on the billing table to extract the information you need.
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Beckie
1 year ago
C) 1. Activate billing export into BigQuery.
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Deeanna
1 year 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.
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Charolette
1 year ago
I think Option B is the way to go. Exporting the logs directly to BigQuery makes the data more accessible for querying.
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Joesph
1 year ago
Let's go with Option B then. It's a straightforward solution to analyze costly queries and user spending.
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Katlyn
1 year ago
I agree, it seems like the most efficient way to monitor queries and track user activity.
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Paulina
1 year ago
Option B is a good choice. Exporting logs to BigQuery will make it easier to extract the information we need.
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Sabine
1 year 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.
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Lacey
1 year 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.
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Lavonna
1 year ago
Option A seems the most comprehensive approach to monitoring BigQuery queries and costs in real-time.
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Daisy
1 year ago
Yes, it would definitely help in identifying the most costly queries and which users are spending the most.
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Oren
1 year ago
I agree, creating a Cloud Logging sink to export BigQuery data access logs to Cloud Storage and developing a Dataflow pipeline sounds efficient.
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Gayla
1 year ago
Option A seems the most comprehensive approach to monitoring BigQuery queries and costs in real-time.
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