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Google Data Engineer Sample Questions:

1. Which of the following job types are supported by Cloud Dataproc (select 3 answers)?

A) Spark
B) YARN
C) Hive
D) Pig

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

3. You operate an IoT pipeline built around Apache Kafka that normally receives around 5000 messages per second. You want to use Google Cloud Platform to create an alert as soon as the moving average over 1 hour drops below 4000 messages per second. What should you do?

A) If that number falls below 4000, send an alert.
B) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
C) Set a fixed time window of 1 hour.Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
D) Use Cloud Scheduler to run a script every five minutes that counts the number of rows created in BigQuery in the last hour
E) Consume the stream of data in Cloud Dataflow using Kafka I
F) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to Cloud Bigtabl
G) Set a sliding time window of 1 hour every 5 minute
H) Compute the average when the window closes, and send an alert if the average is less than 4000 messages.
I) Use a Cloud Dataflow template to write your messages from Cloud Pub/Sub to BigQuer
J) Consume the stream of data in Cloud Dataflow using Kafka I
K) Use Cloud Scheduler to run a script every hour that counts the number of rows created in Cloud Bigtable in the last hour
L) Use Kafka Connect to link your Kafka message queue to Cloud Pub/Su
M) If that number falls below 4000, send an alert.

4. As your organization expands its usage of GCP, many teams have started to create their own projects. Projects are further multiplied to accommodate different stages of deployments and target audiences. Each project requires unique access control configurations. The central IT team needs to have access to all projects. Furthermore, data from Cloud Storage buckets and BigQuery datasets must be shared for use in other projects in an ad hoc way. You want to simplify access control management by minimizing the number of policies. Which two steps should you take? Choose 2 answers.

A) Introduce resource hierarchy to leverage access control policy inheritance.
B) Find all the active members who have access to these projects, and create a Cloud IAM policy to grant access to all these users.
C) Create distinct groups for various teams, and specify groups in Cloud IAM policies.
D) For each Cloud Storage bucket or BigQuery dataset, decide which projects need acces
E) Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.
F) Use Cloud Deployment Manager to automate access provision.

5. When a Cloud Bigtable node fails, is lost.

A) the last transaction
B) all data
C) the time dimension
D) no data

Solutions: