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Google Professional Machine Learning Engineer Exam - Topic 5 Question 8 Discussion

Actual exam question for Google's Professional Machine Learning Engineer exam
Question #: 8
Topic #: 5
[All Professional Machine Learning Engineer Questions]

You are developing a Kubeflow pipeline on Google Kubernetes Engine. The first step in the pipeline is to issue a query against BigQuery. You plan to use the results of that query as the input to the next step in your pipeline. You want to achieve this in the easiest way possible. What should you do?

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Suggested Answer: A

by Dalene at May 03, 2022, 04:48 AM

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Dorothea
4 months ago
A is just manual labor, not efficient at all.
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Mitsue
4 months ago
Surprised that D is even an option, seems like extra work!
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Toshia
4 months ago
C seems too complicated for a simple query.
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Christiane
4 months ago
Definitely agree with B! Using the API is straightforward.
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Katlyn
5 months ago
I think option B is the best choice for flexibility.
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Naomi
5 months ago
I'm a bit uncertain about the best option here. I think using the BigQuery console could work, but it doesn't seem to fit well with the pipeline automation.
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Bonita
5 months ago
I feel like option D could save a lot of time since it mentions using an existing component. I practiced something similar in a lab exercise.
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Gail
5 months ago
I remember practicing with the BigQuery API, but I'm not sure if writing a Python script is the easiest way to integrate it into Kubeflow.
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Shoshana
5 months ago
I think using the Kubeflow Pipelines DSL to create a custom component sounds like a solid approach, but it might take more time than just using an existing component.
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Nickie
5 months ago
The volume of waste could be an important limitation. All those data centers and servers consume a lot of energy and generate a ton of electronic waste. That's a big environmental concern with cloud computing.
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Alexis
5 months ago
Hmm, I'm a bit unsure about the class diagram question. I'll have to think that one through carefully.
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