Discuss Google Associate Data Practitioner Exam Topic 2 Question 25

Your company is building a near real-time streaming pipeline to process JSON telemetry data from small appliances. You need to process messages arriving at a Pub/Sub topic, capitalize letters in the serial number field, and write results to BigQuery. You want to use a managed service and write a minimal amount of code for underlying transformations. What should you do?

AUse a Pub/Sub to BigQuery subscription, write results directly to BigQuery, and schedule a transformation query to run every five minutes.

BUse a Pub/Sub to Cloud Storage subscription, write a Cloud Run service that is triggered when objects arrive in the bucket, performs the transformations, and writes the results to BigQuery.

CUse the ''Pub/Sub to BigQuery'' Dataflow template with a UDF, and write the results to BigQuery.

DUse a Pub/Sub push subscription, write a Cloud Run service that accepts the messages, performs the transformations, and writes the results to BigQuery.

Suggested Answer: C

Using the 'Pub/Sub to BigQuery' Dataflow template with a UDF (User-Defined Function) is the optimal choice because it combines near real-time processing, minimal code for transformations, and scalability. The UDF allows for efficient implementation of custom transformations, such as capitalizing letters in the serial number field, while Dataflow handles the rest of the managed pipeline seamlessly.

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24 comments · newest first

Renea 2 days ago

B sounds complicated. I prefer less code.

Shantay 8 days ago

A is too slow with the five-minute schedule. Not real-time enough.

Melvin 13 days ago

I’m leaning towards D. Cloud Run seems flexible for transformations.

Lezlie 18 days ago

I think option C is the best. Dataflow templates are easy to use.

Edgar 23 days ago

D gives more control over the process. I like that.

Jerry 28 days ago

C is straightforward. UDFs can handle transformations easily.

Annelle 1 month ago

B is interesting, but I prefer managed services.

Rochell 1 month ago

A seems too manual. Scheduling queries is a hassle.

Genevive 1 month ago

I agree, but D sounds good too. Cloud Run is flexible.

Lorrine 2 months ago

I think option C is the best. Dataflow is powerful.

Antonio 2 months ago

I think B adds unnecessary complexity with Cloud Storage.

Caprice 2 months ago

Wait, can we really use a UDF in Dataflow like that?

Roosevelt 2 months ago

A is too slow with that 5-minute schedule.

Mariko 2 months ago

I disagree, D seems more flexible with the push subscription.

Arlette 2 months ago

Option C is the best choice for minimal code and real-time processing.

Galen 3 months ago

I agree, C is definitely the way to go for efficiency!

Merissa 3 months ago

A seems too slow with that 5-minute schedule.

Dorethea 3 months ago

Wait, can we really use a UDF in Dataflow? Sounds complicated!

Dana 3 months ago

I think D is more flexible with the push subscription.

Nettie 3 months ago

Option C is the best choice for minimal code and real-time processing.

Elina 4 months ago

I vaguely recall that using Cloud Storage might add unnecessary steps, so I think options A and B might not be the best fit for real-time processing.

Daryl 4 months ago

I’m leaning towards option D because it mentions a Cloud Run service, which we covered in our last session, but I’m unsure if it’s the most efficient choice.

Truman 4 months ago

I remember discussing the Pub/Sub to BigQuery subscription, but I feel like just writing results directly might not handle the transformations we need.

Brittani 5 months ago

I think option C sounds familiar since we practiced using Dataflow templates in class, but I'm not entirely sure about the UDF part.

Google Associate Data Practitioner Exam - Topic 2 Question 25 Discussion