Free Google Professional-Data-Engineer Exam Questions

Become Google Certified with updated Professional-Data-Engineer exam questions and correct answers

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Total 472 Questions | Updated On: Nov 24, 2025

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Question 1

Your weather app queries a database every 15 minutes to get the current temperature. The frontend is powered by Google App Engine and server millions of users. How should you design the frontend to respond to a database failure?

A : ue a command to restart the database servers.

B : try the query with exponential backoff, up to a cap of 15 minutes.

C : try the query every second until it comes back online to minimize staleness of data.

D : duce the query frequency to once every hour until the database comes back online.

Answer: B

Question 2

Your company is currently setting up data pipelines for their campaign. For all the Google Cloud Pub/Sub streaming data, one of the important business requirements is to be able to periodically identify the inputs and their timings during their campaign. Engineers have decided to use windowing and transformation in Google Cloud Dataflow for this purpose. However, when testing this feature, they find that the Cloud Dataflow job fails for the all streaming insert. What is the most likely cause of this problem?

A : ey have not assigned the timestamp, which causes the job to fail

B : ey have not set the triggers to accommodate the data coming in late, which causes the job to fail

C : ey have not applied a global windowing function, which causes the job to fail when the pipeline is created

D : ey have not applied a non-global windowing function, which causes the job to fail when the pipeline is created

Answer: C

Question 3

You are running a Dataflow streaming pipeline, with Streaming Engine and Horizontal Autoscaling enabled.

You have set the maximum number of workers to 1000. The input of your pipeline is Pub/Sub messages with

notifications from Cloud Storage One of the pipeline transforms reads CSV files and emits an element for

every CSV line. The Job performance is low. the pipeline is using only 10 workers, and you notice that the

autoscaler is not spinning up additional workers. What should you do to improve performance?

A : Use Dataflow Prime, and enable Right Fitting to increase the worker resources

B : Update the job to increase the maximum number of workers.

C : Enable Vertical Autoscaling to let the pipeline use larger workers.

D : Change the pipeline code, and introduce a Reshuffle step to prevent fusion.

Answer: D

Question 4

You stream order data by using a Dataflow pipeline, and write the aggregated result to Memorystore. You

provisioned a Memorystore for Redis instance with Basic Tier. 4 GB capacity, which is used by 40 clients for

read-only access. You are expecting the number of read-only clients to increase significantly to a few hundred

and you need to be able to support the demand. You want to ensure that read and write access availability is

not impacted, and any changes you make can be deployed quickly. What should you do?

A : Create multiple new Memorystore for Redis instances with Basic Tier (4 GB capacity) Modify theDataflow pipeline and new clients to use all instances

B : Create a new Memorystore for Redis instance with Standard Tier Set capacity to 4 GB and read replicato No read replicas (high availability only). Delete the old instance.

C : Create a new Memorystore for Memcached instance Set a minimum of three nodes, and memory pernode to 4 GB. Modify the Dataflow pipeline and all clients to use the Memcached instance Delete theold instance.

D : Create a new Memorystore for Redis instance with Standard Tier Set capacity to 5 GB and createmultiple read replicas Delete the old instance.

Answer: D

Question 5

You work for a manufacturing plant that batches application log files together into a single log file once a day at 2:00 AM. You have written a Google Cloud Dataflow job to process that log file. You need to make sure the log file in processed once per day as inexpensively as possible. What should you do?

A : ange the processing job to use Google Cloud Dataproc instead

B : nually start the Cloud Dataflow job each morning when you get into the office.

C : eate a cron job with Google App Engine Cron Service to run the Cloud Dataflow job.

D : nfigure the Cloud Dataflow job as a streaming job so that it processes the log data immediately.

Answer: C

Page: 1 / 95

Total 472 Questions | Updated On: Nov 24, 2025

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