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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

Question 1

You have historical data covering the last three years in BigQuery and a data pipeline that delivers new data to BigQuery daily. You have noticed that when the Data Science team runs a query filtered on a date column and limited to 30-90 days of data, the query scans the entire table. You also noticed that your bill is increasing more quickly than you expected. You want to resolve the issue as cost-effectively as possible while maintaining the ability to conduct SQL queries. What should you do?

A. Re-create the tables using DD
B. Write an Apache Beam pipeline that creates a BigQuery table per data
C. Partition the tables by a column containing a TIMESTAMP or DATE Type.
D. Modify your pipeline to maintain the last 30-90 days of data in one table and the longer history in a different table to minimize full table scans over the entire history.
E. Recommend that the Data Science team use wildcards on the table name suffixes to select the data they need.
F. Recommend that the Data Science team export the table to a CSV file on Cloud Storage and use Cloud Datalab to explore the data by reading the files directly.

Question 2

You have a data stored in BigQuery. The data in the BigQuery dataset must be highly available. You need to define a storage, backup, and recovery strategy of this data that minimizes cost. How should you configure the BigQuery table?

A. In the event of an emergency, use the backup copy of the table.
B. In the event of an emergency, use the backup copy of the table.
C. Create a scheduled query to make copies of the data to tables suffixed with the time of the backu
D. Set the BigQuery dataset to be multi-regional
E. Set the BigQuery dataset to be regiona
F. In the event of an emergency, use a point-in-time snapshot to recover the data.
G. Create a scheduled query to make copies of the data to tables suffixed with the time of the backup
H. Set the BigQuery dataset to be multi-regional
I. Set the BigQuery dataset to be regiona
J. In the event of an emergency, use a point-in-time snapshot to recover the data.

Question 3

What are the minimum permissions needed for a service account used with Google Dataproc?

A. Execute to Google Cloud Storage; write to Google Cloud Logging
B. Read and write to Google Cloud Storage; write to Google Cloud Logging
C. Execute to Google Cloud Storage; execute to Google Cloud Logging
D. Write to Google Cloud Storage; read to Google Cloud Logging

Question 4

You have a data pipeline with a Cloud Dataflow job that aggregates and writes time series metrics to Cloud Bigtable. This data feeds a dashboard used by thousands of users across the organization. You need to support additional concurrent users and reduce the amount of time required to write the dat a. Which two actions should you take? (Choose two.)

A. Modify your Cloud Dataflow pipeline to use the Flatten transform before writing to Cloud Bigtable
B. Increase the number of nodes in the Cloud Bigtable cluster
C. Modify your Cloud Dataflow pipeline to use the CoGroupByKey transform before writing to Cloud Bigtable
D. Increase the maximum number of Cloud Dataflow workers by setting maxNumWorkers in PipelineOptions
E. Configure your Cloud Dataflow pipeline to use local execution

Question 5

You are building a new data pipeline to share data between two different types of applications: jobs generators and job runners. Your solution must scale to accommodate increases in usage and must accommodate the addition of new applications without negatively affecting the performance of existing ones. What should you do?

A. Create an API using App Engine to receive and send messages to the applications
B. Create a table on Cloud SQL, and insert and delete rows with the job information
C. Create a table on Cloud Spanner, and insert and delete rows with the job information
D. Use a Cloud Pub/Sub topic to publish jobs, and use subscriptions to execute them

Solutions: