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Professional Data Engineer Exam (Professional-Data-Engineer) - Google Cloud Exam Questions

Last updated on June 20, 2026

97% Exam Compliance
384 Total Questions
1
Question
You are designing a messaging system by using Pub/Sub to process clickstream data with an event- driven consumer app that relies on a push subscription. You need to configure the messaging system that is reliable enough to handle temporary downtime of the consumer app. You also need the messaging system to store the input messages that cannot be consumed by the subscriber. The system needs to retry failed messages gradually, avoiding overloading the consumer app, and store the failed messages after a maximum of 10 retries in a topic. How should you configure the Pub/Sub subscription?
Options
A Use immediate redelivery as the subscription retry policy, and configure dead lettering to a different topic with maximum delivery attempts set to 10.
B Use exponential backoff as the subscription retry policy, and configure dead lettering to the same source topic with maximum delivery attempts set to 10.
C Increase the acknowledgement deadline to 10 minutes.
D Use exponential backoff as the subscription retry policy, and configure dead lettering to a different topic with maximum delivery attempts set to 10.
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2
Question
When you design a Google Cloud Bigtable schema it is recommended that you _________.
Options
A Create schema designs that are based on a relational database design
B Avoid schema designs that require atomicity across rows
C Avoid schema designs that are based on NoSQL concepts
D Create schema designs that require atomicity across rows
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3
Question
You are designing a pipeline that publishes application events to a Pub/Sub topic. You need to
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4
Question
You are developing an application that uses a recommendation engine on Google Cloud. Your solution should display new videos to customers based on past views. Your solution needs to generate labels for the entities in videos that the customer has viewed. Your design must be able to provide very fast filtering suggestions based on data from other customer preferences on several TB of dat
Options
A Build and train a classification model with Spark MLlib to generate labels. Build and train a second classification model with Spark MLlib to filter results to match customer preferences. Deploy the models using Cloud Dataproc. Call the models from your application.
B Build an application that calls the Cloud Video Intelligence API to generate labels. Store data in Cloud Bigtable, and filter the predicted labels to match the user’s viewing history to generate preferences.
C Build and train a complex classification model with Spark MLlib to generate labels and filter the results.
Deploy the models using Cloud Dataproc. Call the model from your application.
D Build an application that calls the Cloud Video Intelligence API to generate labels. Store data in Cloud SQL, and join and filter the predicted labels to match the user’s viewing history to generate preferences.
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5
Question
To give a user read permission for only the first three columns of a table, which access control method would you use?
Options
A Predefined role
B Authorized view
C Primitive role
D It's not possible to give access to only the first three columns of a table.
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