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Google Professional Data Engineer Exam - Topic 3 Question 33 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 33
Topic #: 3
[All Professional Data Engineer Questions]

Given the record streams MJTelco is interested in ingesting per day, they are concerned about the cost of Google BigQuery increasing. MJTelco asks you to provide a design solution. They require a single large data table called tracking_table. Additionally, they want to minimize the cost of daily queries while performing fine-grained analysis of each day's events. They also want to use streaming ingestion. What should you do?

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Suggested Answer: B

by Marguerita at May 06, 2022, 09:54 PM

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Mariko
5 months ago
Not sure if this will really minimize costs in the long run...
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Trinidad
6 months ago
Partitioning is definitely the way to go!
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Lashawnda
6 months ago
Wait, why not just use a DATE column instead of TIMESTAMP?
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Paris
6 months ago
I disagree, sharded tables (Option C) could be more manageable.
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Olga
6 months ago
Option B is the best choice for cost efficiency!
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Barrett
6 months ago
I vaguely recall that using a DATE column might not be as efficient for querying as a TIMESTAMP. I’m leaning towards option B, but I’m not completely confident.
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Merissa
6 months ago
I'm not entirely sure, but I think sharded tables could lead to more complexity. Option C feels risky for daily queries.
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Ernestine
6 months ago
I remember we discussed partitioned tables in class, and they seem to help with cost management. I think option B might be the right choice.
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Ty
6 months ago
I practiced a similar question where partitioning was emphasized for cost efficiency. Option B sounds familiar, but I'm hesitant about the TIMESTAMP vs. DATE debate.
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Blondell
6 months ago
Alright, I think I've got a handle on this. Let me walk through it one more time to double-check my understanding before submitting my answer.
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Nieves
7 months ago
Ah, I remember learning about this in class. I'm pretty confident the correct answer is C - using the import/export utilities. That's the method we discussed for migrating repository data during upgrades.
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