Deal of The Day! Hurry Up, Grab the Special Discount - Save 25% - Ends In 00:00:00 Coupon code: SAVE25
Welcome to Pass4Success

- Free Preparation Discussions
Mail Us support@pass4success.com
Location US
Mob_nav_barsMENU

Google Professional Data Engineer Exam - Topic 4 Question 60 Discussion

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?
C) Cluster table data by create_date location_id and device_version
A) Partition table data by create_date, location_id and device_version
B) Partition table data by create_date cluster table data by tocation_id and device_version
D) Cluster table data by create_date, partition by location and device_version

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?

Show Suggested Answer Hide Answer
Suggested Answer: C

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

Limited Time Offer

25%

Off

Get Premium Professional Data Engineer Questions as Interactive Web-Based Practice Test or PDF

Contribute your Thoughts:

0/2000 characters
Submit Cancel
Jolanda
10 months ago
C doesn't seem efficient for large datasets, though.
upvoted 0 times
...
Sophia
10 months ago
B is definitely the way to go, it balances everything nicely!
upvoted 0 times
...
Sherron
10 months ago
Wait, can we really cluster by multiple fields like that?
upvoted 0 times
...
Adelaide
11 months ago
I disagree, A might be more straightforward.
upvoted 0 times
...
Mickie
11 months ago
B seems like the best option for optimizing both cost and performance.
upvoted 0 times
...
Kate
11 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.
upvoted 0 times
...
Tarra
11 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.
upvoted 0 times
...
Shawana
11 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.
upvoted 0 times
...
Alexis
11 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.
upvoted 0 times
...
Murray
11 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.
upvoted 0 times
...
Rozella
11 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.
upvoted 0 times
...

Save Cancel