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

5 months ago

Surprised that B isn't considered a value!

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Ming

5 months ago

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

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Junita

6 months ago

Wait, aren't there other values in B?

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Arthur

6 months ago

Totally agree, A and D are correct.

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Emilio

6 months ago

A and D are the values!

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Tiera

6 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

7 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

7 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

7 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

7 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

7 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

7 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

7 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

7 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

7 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

7 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

7 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

7 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

12 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

10 months ago

C) [0, 1]

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Geoffrey

10 months ago

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

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Lorrie

11 months ago

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

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Jarod

1 year 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

11 months ago

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

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Mozell

11 months ago

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

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Rashida

12 months ago

I agree, B and C are the correct answers.

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Kenny

1 year 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

11 months ago

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

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Caren

11 months ago

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

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Louisa

11 months ago

Definitely, the other options have too many zeros.

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Dyan

11 months ago

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

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Paola

11 months ago

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

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Odette

11 months ago

I think B and C are the correct answers.

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Amira

12 months ago

I think B and C are the correct answers.

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Nana

1 year 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

12 months ago

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

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Stephaine

1 year ago

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

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Scot

1 year ago

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

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Ashleigh

12 months ago

So, the correct answers are B and C.

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Joanne

1 year ago

Sparse vectors have mostly zero values.

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Nathalie

1 year ago

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

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Jettie

1 year ago

I think B and C are the correct answers.

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Kenneth

1 year 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

1 year ago

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

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Jesusa

1 year ago

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

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Titus

1 year ago

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

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