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Google Professional Data Engineer Exam - Topic 6 Question 77 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 77
Topic #: 6
[All Professional Data Engineer Questions]

You need to look at BigQuery data from a specific table multiple times a day. The underlying table you are querying is several petabytes in size, but you want to filter your data and provide simple aggregations to downstream users. You want to run queries faster and get up-to-date insights quicker. What should you do?

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Suggested Answer: B

Materialized views are precomputed views that periodically cache the results of a query for increased performance and efficiency. BigQuery leverages precomputed results from materialized views and whenever possible reads only changes from the base tables to compute up-to-date results. Materialized views can significantly improve the performance of workloads that have the characteristic of common and repeated queries. Materialized views can also optimize queries with high computation cost and small dataset results, such as filtering and aggregating large tables. Materialized views are refreshed automatically when the base tables change, so they always return fresh data. Materialized views can also be used by the BigQuery optimizer to process queries to the base tables, if any part of the query can be resolved by querying the materialized view.Reference:

Introduction to materialized views

Create materialized views

BigQuery Materialized View Simplified: Steps to Create and 3 Best Practices

Materialized view in Bigquery


by Jani at Feb 07, 2024, 06:56 AM

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Bettyann
4 months ago
Limiting columns is a must for faster queries!
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Andrew
4 months ago
Wait, can materialized views really handle petabytes?
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Maryann
4 months ago
Running scheduled queries seems outdated.
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Alethea
4 months ago
I think caching queries is a good option too.
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Ena
4 months ago
Materialized views are super efficient for this!
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Cyril
5 months ago
Running a scheduled query like in option A sounds practical, but I wonder if it would really provide the up-to-date insights we need.
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Moira
5 months ago
I practiced a similar question where limiting columns helped improve performance, so option D might be worth considering too.
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Dorothy
5 months ago
I'm not entirely sure, but I remember something about cached queries in option C being useful for speeding up repeated queries.
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Alecia
5 months ago
I think option B, creating a materialized view, could be the best choice since it precomputes the results and speeds up queries.
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Marshall
5 months ago
Option D looks like the easiest solution to me. Limiting the columns should help reduce the amount of data being pulled, which should make the queries faster.
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Angelyn
5 months ago
Hmm, I'm a bit unsure about this one. I'm trying to decide between running a scheduled query or creating a materialized view. I'll need to think it through a bit more.
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Jesusa
5 months ago
This seems like a straightforward question. I think I'll go with option B and create a materialized view to speed up the queries.
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Niesha
5 months ago
I'm confident that option A is the way to go here. Running a scheduled query to pull the data at regular intervals is a simple and effective solution.
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Alease
5 months ago
Hmm, I'm a bit unsure about this one. I know Lean focuses on flow and value, but I can't quite recall the specific term they use. I'll have to think this through carefully.
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Tenesha
5 months ago
This question is asking how to avoid repeating the business logic for determining high value opportunities. I think the key is to centralize that logic in one place so it can be reused.
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Wayne
6 months ago
I'm not entirely sure if "polynomial solutions" is the right term. Didn't we talk about NP-hard problems in relation to cryptography?
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Marshall
6 months ago
Okay, let's see. The question mentions that the organization supports access to social networking sites, so I don't think that's the issue. I'm leaning towards either the People Pane being turned off or the Navigation Pane being turned off.
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Sherron
6 months ago
Wait, I'm a bit confused. Doesn't the DSSS signal have to match between the access point and the hosts? I'm not sure if that's the best approach.
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Ming
6 months ago
Hmm, I'm a little unsure about this one. I know variable costs are supposed to change with activity, but I'm not totally clear on the wording of the question. I'll have to think it through carefully.
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Kasandra
2 years ago
Limiting the query columns might also help in getting quicker insights.
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Antonio
2 years ago
What about using a cached query instead? Would that work as well?
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Lezlie
2 years ago
I agree, a materialized view would definitely improve query performance.
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Chun
2 years ago
I think creating a materialized view would help speed up the query.
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Nina
2 years ago
You know, I was about to suggest the column limiting option, but after hearing you all, I think the materialized view is the way to go. It's like having a personal assistant for your data - they do all the heavy lifting so you can just sit back and enjoy the results.
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Asha
2 years ago
Ooh, good point. I was thinking about the cached query option, but a materialized view is probably more robust. Plus, it'll free up our time to focus on other important tasks instead of waiting for those massive queries to run.
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Buffy
2 years ago
I agree, a materialized view seems like the way to go. With a table that size, we need to be proactive about optimizing our queries. And B gives us the added benefit of keeping the data fresh without having to run a full query every time.
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Rodney
2 years ago
I agree, a materialized view seems like the way to go. With a table that size, we need to be proactive about optimizing our queries. And B gives us the added benefit of keeping the data fresh without having to run a full query every time.
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Bernardine
2 years ago
B) Create a materialized view based off of the query being run.
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Jeffrey
2 years ago
A) Run a scheduled query to pull the necessary data at specific intervals daily.
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Kerry
2 years ago
Hmm, this is a tricky one. The table is massive, so we need to be smart about how we access the data. A scheduled query could work, but it might not give us the most up-to-date insights. I'm leaning towards option B - creating a materialized view. That way, we can preload the data we need and get faster results.
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