PROFESSIONAL-DATA-ENGINEER · Question #150
PROFESSIONAL-DATA-ENGINEER Question #150: Real Exam Question with Answer & Explanation
The correct answer is C: 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. Explanation/Reference: The recommendation requires filtering based on several TB of data, therefore BigTable is the recommended option vs Cloud SQL which is limited to 10TB.
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 data. What should you do?
Options
- ABuild and train a complex classification model with Spark MLlib to generate labels and filter the results.
- BBuild 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
- CBuild 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
- DBuild 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
Explanation
Explanation/Reference: The recommendation requires filtering based on several TB of data, therefore BigTable is the recommended option vs Cloud SQL which is limited to 10TB.
Community Discussion
No community discussion yet for this question.