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Google Professional Data Engineer Exam - Topic 4 Question 60 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 60
Topic #: 4
[All Professional Data Engineer Questions]

You are collecting loT sensor data from millions of devices across the world and storing the data in BigQuery. Your access pattern is based on recent data tittered by location_id and device_version with the following query:

You want to optimize your queries for cost and performance. How should you structure your data?

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Suggested Answer: C

by Paris at Oct 22, 2022, 09:33 AM

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Jolanda
4 months ago
C doesn't seem efficient for large datasets, though.
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Sophia
4 months ago
B is definitely the way to go, it balances everything nicely!
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Sherron
4 months ago
Wait, can we really cluster by multiple fields like that?
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Adelaide
4 months ago
I disagree, A might be more straightforward.
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Mickie
4 months ago
B seems like the best option for optimizing both cost and performance.
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Kate
5 months ago
I believe clustering by location_id and device_version could help with query performance, but I’m not entirely sure if that’s the right choice for this scenario.
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Tarra
5 months ago
I’m a bit confused about whether to cluster or partition first. I feel like I’ve seen similar questions, but I can’t recall the best approach.
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Shawana
5 months ago
I think option B sounds familiar; it seems like a good way to optimize for both cost and performance based on our practice questions.
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Alexis
5 months ago
I remember we discussed partitioning and clustering in class, but I'm not sure if I should prioritize one over the other here.
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Murray
5 months ago
Okay, I think I've got this. If an individual end user can't access a business application, that's likely a P1 issue since it's impacting a user's ability to do their job. I'll go with A - Yes.
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Rozella
5 months ago
I'm pretty confident that option B is the right answer here. Modular inputs and HEC seem like the recommended way to ingest data on clustered indexers.
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