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Google GCP-DE Exam Syllabus Topics:

Google Data Engineer Sample Questions:

Question 1

You are planning to use Google's Dataflow SDK to analyze customer data such as displayed below. Your project requirement is to extract only the customer name Passing Certification Exams Made Easy visit - https://www.2PassEasy.com from the data source and then write to an output PCollection.
Tom,555 X street Tim,553 Y street Sam, 111 Z street
Which operation is best suited for the above data processing requirement?

A. Source API
B. ParDo
C. Data extraction
D. Sink API

Question 2

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 temporary table in Cloud Spanner that will act as a buffer for new data
B. Use a larger instance type for your Cloud Dataflow workers
C. Create a temporary table in Cloud Bigtable that will act as a buffer for new data
D. Change the zone of your Cloud Dataflow pipeline to run in us-central1
E. 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
F. Increase the number of max workers
G. 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

Question 3

Cloud Dataproc is a managed Apache Hadoop and Apache service.

A. Blaze
B. Fire
C. Spark
D. Ignite

Question 4

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

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

Question 5

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

Solutions: