Google Google Cloud Certified GCP-DE

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Google Data Engineer Sample Questions:

1. You work for a large fast food restaurant chain with over 400,000 employees. You store employee information in Google BigQuery in a Users table consisting of a FirstName field and a LastName field. A member of IT is building an application and asks you to modify the schema and data in BigQuery so the application can query a FullName field consisting of the value of the FirstName field concatenated with a space, followed by the value of the LastName field for each employee. How can you make that data available while minimizing cost?

A) Add a new column called FullName to the Users tabl
B) Create a view in BigQuery that concatenates the FirstName and LastName field values to produce the FullName.
C) Create a Google Cloud Dataproc job to process the CSV file and output a new CSV file containing the proper values for FirstName, LastName and FullNam G. Run a BigQuery load job to load the new CSV file into BigQuery.
D) Create a Google Cloud Dataflow job that queries BigQuery for the entire Users table, concatenates the FirstName value and LastName value for each user, and loads the proper values for FirstName, LastName, and FullName into a new table in BigQuery.
E) Run an UPDATE statement that updates the FullName column for each user with the concatenation of the FirstName and LastName values.
F) Use BigQuery to export the data for the table to a CSV fil

2. Which Google Cloud Platform service is an alternative to Hadoop with Hive?

A) Cloud Dataflow
B) BigQuery
C) Cloud Datastore
D) Cloud Bigtable

3. You are selecting services to write and transform JSON messages from Cloud Pub/Sub to BigQuery for a data pipeline on Google Cloud. You want to minimize service costs. You also want to monitor and accommodate input data volume that will vary in size with minimal manual intervention. What should you do?

A) Use Cloud Dataflow to run your transformation
B) Monitor the job system lag with Stackdrive
C) Monitor CPU utilization for the cluste
D) Configure the job to use non-default Compute Engine machine types when needed.
E) Use the diagnose command to generate an operational output archiv
F) Use Cloud Dataproc to run your transformation
G) Use the default autoscaling setting for worker instances.
H) Monitor the total execution time for a sampling of job
I) Use Cloud Dataproc to run your transformation
J) Resize the number of worker nodes in your cluster via the command line.
K) Use Cloud Dataflow to run your transformation
L) Locate the bottleneck and adjust cluster resources.

4. You are designing the database schema for a machine learning-based food ordering service that will predict what users want to eat. Here is some of the information you need to store:
The user profile: What the user likes and doesn't like to eat
The user account information: Name, address, preferred meal times
The order information: When orders are made, from where, to whom
The database will be used to store all the transactional data of the product. You want to optimize the data schem a. Which Google Cloud Platform product should you use?

A) BigQuery
B) Cloud Datastore
C) Cloud Bigtable
D) Cloud SQL

5. All Google Cloud Bigtable client requests go through a front-end server they are sent to a Cloud Bigtable node.

A) once
B) after
C) only if
D) before

Solutions: