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Google Professional Data Engineer Exam - Topic 5 Question 107 Discussion

Actual exam question for Google's Professional Data Engineer exam
Question #: 107
Topic #: 5
[All Professional Data Engineer Questions]

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

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Suggested Answer: B

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Howard
2 months ago
C seems a bit off, isn’t clustering usually for performance?
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Rosendo
2 months ago
I think B makes more sense for clustering.
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Domitila
2 months ago
A is the best option for optimizing cost and performance!
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Chandra
3 months ago
D sounds confusing, can you really partition by locationed?
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Elke
3 months ago
Wait, what’s the difference between partitioning and clustering again?
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Laurena
3 months ago
I thought clustering was more about how the data is physically stored, so maybe option C is the right approach?
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Raylene
3 months ago
I feel like option B might be the best choice since it combines both partitioning and clustering, but I'm a bit confused about the order.
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Daryl
4 months ago
I remember a practice question where clustering helped with query performance, but I can't recall the exact details.
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Laura
4 months ago
I think partitioning by create_date makes sense, but I'm not sure if I should cluster by location_id or device_version.
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Mendy
4 months ago
Option C looks promising to me - clustering the data by all three attributes could provide good performance for a wide range of queries. I'll need to do some research on the pros and cons of clustering versus partitioning to make a final decision.
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Yolando
4 months ago
I'm a bit confused by the difference between partitioning and clustering. Can someone explain that to me in simple terms? I want to make sure I understand the concepts before choosing an answer.
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Keith
4 months ago
I'm leaning towards option B - partitioning by create_date and then clustering by location_id and device_version. That way, I can take advantage of both partitioning and clustering to optimize the data structure.
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Alaine
5 months ago
Partitioning by create_date, location_id, and device_version seems like a good approach to improve query performance, but I'm not sure if it's the most cost-effective.
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Detra
5 months ago
Hmm, this is a tricky one. I'll need to think carefully about the trade-offs between partitioning and clustering to optimize for both cost and performance.
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Becky
8 months ago
This question is making my head spin like a data-driven tornado. Time to grab a cup of coffee and think it through again.
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Loren
8 months ago
Option B all the way! Partitioning and clustering, it's like a dance of optimization. Now, if only I could get my boss to understand the importance of this...
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Monroe
7 months ago
I agree, it really does make a difference in cost and performance.
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Glenn
7 months ago
Option B all the way! Partitioning and clustering, it's like a dance of optimization.
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Portia
8 months ago
Option D? Really? Clustering by create_date and then partitioning by location_id and device_version? Sounds like a recipe for disaster if you ask me.
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Alva
8 months ago
A) Partition table data by create_date, location_id and device_version
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Daniel
8 months ago
C) Cluster table data by create_date location_id and device_version
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Madonna
8 months ago
B) Partition table data by create_date cluster table data by location_Id and device_version
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Roselle
8 months ago
A) Partition table data by create_date, location_id and device_version
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Patria
9 months ago
I prefer option D, clustering table data by create_date and partitioning by location_id and device_version can help with query optimization.
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Madelyn
9 months ago
Hmm, this is a tough one. I'm going to have to go with Option C. Clustering all three columns seems like the simplest approach, and it might be good enough for most use cases.
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Gerardo
8 months ago
I agree, clustering by all three columns seems like a good balance between cost and performance.
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Erick
8 months ago
I think Option C is the best choice too. It simplifies the structure and should help with performance.
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Aretha
9 months ago
I think option C makes the most sense, clustering table data by create_date, location_id, and device_version can provide both cost and performance benefits.
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Lizette
9 months ago
I disagree, I believe option B is more efficient because clustering table data by location_id and device_version can improve performance.
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Pamella
10 months ago
I'm leaning towards Option A. Partitioning by all three columns should provide the best overall optimization, even if it's a bit more complicated to set up.
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Wade
8 months ago
User 3: Option A does seem like the most comprehensive approach. It's worth the extra effort for better optimization.
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Shawnda
8 months ago
User 2: I agree, it may be a bit more work to set up, but it should optimize both cost and performance.
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Joni
9 months ago
User 1: I think Option A is the way to go. Partitioning by all three columns seems like the best choice.
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Keshia
10 months ago
I think option A is the best choice because partitioning by create_date, location_id, and device_version can help optimize queries.
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Thea
10 months ago
Option B seems like the way to go. Partitioning by create_date and then clustering by location_id and device_version sounds like a good strategy to optimize both cost and performance.
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Olen
10 months ago
Partitioning by create_date and then clustering by location_id and device_version sounds like a good strategy to optimize both cost and performance.
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Vi
10 months ago
Option B seems like the way to go.
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