Google Professional Data Engineer Exam - Topic 4 Question 102 Discussion

Actual exam question for Google's Professional Data Engineer exam

Question #: 102
Topic #: 4

[All Professional Data Engineer Questions]

Which of these are examples of a value in a sparse vector? (Select 2 answers.)

A[0, 5, 0, 0, 0, 0]

B[0, 0, 0, 1, 0, 0, 1]

C[0, 1]

D[1, 0, 0, 0, 0, 0, 0]

Show Suggested Answer

Suggested Answer: C

To re-encrypt all of your CMEK-protected Cloud Storage data after a key has been exposed, and to ensure future writes are protected with a new key, creating a new Cloud KMS key and a new Cloud Storage bucket is the best approach. Here's why option C is the best choice:

Re-encryption of Data:

By creating a new Cloud Storage bucket and copying all objects from the old bucket to the new bucket while specifying the new Cloud KMS key, you ensure that all data is re-encrypted with the new key.

This process effectively re-encrypts the data, removing any dependency on the compromised key.

Ensuring CMEK Protection:

Creating a new bucket and setting the new CMEK as the default ensures that all future objects written to the bucket are automatically protected with the new key.

This reduces the risk of objects being written without CMEK protection.

Deletion of Compromised Key:

Once the data has been copied and re-encrypted, the old key can be safely deleted from Cloud KMS, eliminating the risk associated with the compromised key.

Steps to Implement:

Create a New Cloud KMS Key:

Create a new encryption key in Cloud KMS to replace the compromised key.

Create a New Cloud Storage Bucket:

Create a new Cloud Storage bucket and set the default CMEK to the new key.

Copy and Re-encrypt Data:

Use the gsutil tool to copy data from the old bucket to the new bucket while specifying the new CMEK key:

gsutil -o 'GSUtil:gs_json_api_version=2' cp -r gs://old-bucket/* gs://new-bucket/

Delete the Old Key:

After ensuring all data is copied and re-encrypted, delete the compromised key from Cloud KMS.

Cloud KMS Documentation

Cloud Storage Encryption

Re-encrypting Data in Cloud Storage

by Elfriede at Jan 25, 2025, 07:03 PM

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Mabel

3 months ago

Surprised that B isn't considered a value!

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Ming

3 months ago

I thought C had a value too, but I guess not.

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Junita

3 months ago

Wait, aren't there other values in B?

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Arthur

4 months ago

Totally agree, A and D are correct.

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Emilio

4 months ago

A and D are the values!

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Tiera

4 months ago

I’m pretty confident that option B has two non-zero values, which makes it less sparse. I think A and D might be the right answers.

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Layla

4 months ago

I feel like option C is definitely a sparse vector since it only has one non-zero value. I’m torn between A and D for the second choice.

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Santos

4 months ago

I remember practicing with similar questions, and I think option A has a non-zero value, but it still feels like it might not qualify as sparse.

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Kristin

5 months ago

I think a sparse vector should have mostly zeros, so maybe options B and D? But I'm not entirely sure.

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Rory

5 months ago

I think the key here is to look for the options with the fewest non-zero values. A and D seem to fit that criteria, so I'll go with those.

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France

5 months ago

I'm a bit unsure about this one. I know sparse vectors have mostly zeros, but I'm not sure exactly how to identify the valid examples. I'll need to think it through carefully.

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Stefan

5 months ago

I'm pretty confident that A and D are examples of valid sparse vector values. The other options have too many non-zero elements to be considered sparse.

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Britt

5 months ago

Okay, let me see here. A sparse vector is one with mostly zero values, so I'm looking for the options that have a lot of zeros and just a few non-zero values.

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Doyle

5 months ago

Hmm, this looks like a question about sparse vectors. I'll need to think carefully about which options represent valid values in a sparse vector.

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Man

5 months ago

I'm feeling a little lost here. Can someone remind me what the key characteristics of a sparse vector are? I want to make sure I understand this properly before answering.

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Kristin

5 months ago

Okay, I've got this. The sparse vectors will be the ones with mostly zeros and just a few non-zero values. I'll select the options that fit that description.

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Chaya

5 months ago

Hmm, I'm a bit unsure about this one. I need to think carefully about what defines a sparse vector and make sure I select the right examples.

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Levi

5 months ago

This looks like a straightforward question about sparse vectors. I'll focus on identifying the vectors that have non-zero values in only a few positions.

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Glory

9 months ago

This question is as sparse as the vectors themselves. B and C are the obvious choices, unless you're a dense person.

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Ling

8 months ago

C) [0, 1]

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Geoffrey

8 months ago

B) [0, 0, 0, 1, 0, 0, 1]

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Lorrie

9 months ago

A) [0, 5, 0, 0, 0, 0]

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Jarod

10 months ago

I'm going to go with B and C. Anything with more than two non-zero elements is just showing off.

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Buddy

8 months ago

I think B and C are the most efficient examples of a value in a sparse vector.

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Mozell

9 months ago

Yeah, anything with more than two non-zero elements is unnecessary.

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Rashida

9 months ago

I agree, B and C are the correct answers.

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Kenny

10 months ago

This question is so easy, even a kindergartener could get it right. B and C are the clear winners here.

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Annamae

8 months ago

It's a simple question, but important to understand sparse vectors.

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Caren

9 months ago

Definitely, B and C are the examples of values in a sparse vector.

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Louisa

9 months ago

Definitely, the other options have too many zeros.

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Dyan

9 months ago

I agree, they both have non-zero values at specific indices.

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Paola

9 months ago

I agree, B and C both have values in sparse vector.

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Odette

9 months ago

I think B and C are the correct answers.

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Amira

9 months ago

I think B and C are the correct answers.

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Nana

10 months ago

I'm going with B and D. Those two options have the fewest non-zero elements, which is the key characteristic of a sparse vector.

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Raymon

9 months ago

Yes, B and D have the fewest non-zero elements, making them examples of sparse vectors.

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Stephaine

10 months ago

I agree, B and D are the correct choices for sparse vectors.

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Scot

11 months ago

Definitely B and C. A and D are too dense to be considered sparse vectors.

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Ashleigh

10 months ago

So, the correct answers are B and C.

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Joanne

10 months ago

Sparse vectors have mostly zero values.

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Nathalie

10 months ago

A and D have too many non-zero values to be sparse vectors.

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Jettie

10 months ago

I think B and C are the correct answers.

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Kenneth

11 months ago

I think B and C are the correct answers. A and D have too many zeros, which doesn't align with the definition of a sparse vector.

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Martin

11 months ago

I'm not sure. Can you explain why A and C are considered sparse vectors?

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Jesusa

11 months ago

I agree with Titus. A and C have non-zero values at specific indices, making them sparse vectors.

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Titus

11 months ago

I think A and C are examples of values in a sparse vector.

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