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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

1. Which of the following is NOT one of the three main types of triggers that Dataflow supports?

A) Trigger based on element size in bytes
B) Trigger based on element count
C) Trigger based on time
D) Trigger that is a combination of other triggers

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

3. The YARN ResourceManager and the HDFS NameNode interfaces are available on a Cloud Dataproc cluster .

A) master node
B) application node
C) conditional node
D) worker node

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

5. You are running a pipeline in Cloud Dataflow that receives messages from a Cloud Pub/Sub topic and writes the results to a BigQuery dataset in the EU. Currently, your pipeline is located in europe-west4 and has a maximum of 3 workers, instance type n1-standard-1. You notice that during peak periods, your pipeline is struggling to process records in a timely fashion, when all 3 workers are at maximum CPU utilization. Which two actions can you take to increase performance of your pipeline? (Choose two.)

A) Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Bigtable to BigQuery
B) Create a new step in your pipeline to write to this table first, and then create a new pipeline to write from Cloud Spanner to BigQuery
C) Create a temporary table in Cloud Bigtable that will act as a buffer for new data
D) Use a larger instance type for your Cloud Dataflow workers
E) Create a temporary table in Cloud Spanner that will act as a buffer for new data
F) Change the zone of your Cloud Dataflow pipeline to run in us-central1
G) Increase the number of max workers

Solutions: