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Google Data Engineer Sample Questions:

1. You have developed three data processing jobs. One executes a Cloud Dataflow pipeline that transforms data uploaded to Cloud Storage and writes results to BigQuery. The second ingests data from on-premises servers and uploads it to Cloud Storage. The third is a Cloud Dataflow pipeline that gets information from third-party data providers and uploads the information to Cloud Storage. You need to be able to schedule and monitor the execution of these three workflows and manually execute them when needed. What should you do?

A) Use Stackdriver Monitoring and set up an alert with a Webhook notification to trigger the jobs.
B) Set up cron jobs in a Compute Engine instance to schedule and monitor the pipelines using GCP API calls.
C) Create a Direct Acyclic Graph in Cloud Composer to schedule and monitor the jobs.
D) Develop an App Engine application to schedule and request the status of the jobs using GCP API calls.

2. What Dataflow concept determines when a Window's contents should be output based on certain criteria being met?

A) Windows
B) Sessions
C) OutputCriteria
D) Triggers

3. You are operating a Cloud Dataflow streaming pipeline. The pipeline aggregates events from a Cloud Pub/Sub subscription source, within a window, and sinks the resulting aggregation to a Cloud Storage bucket. The source has consistent throughput. You want to monitor an alert on behavior of the pipeline with Cloud Stackdriver to ensure that it is processing dat a. Which Stackdriver alerts should you create?

A) An alert based on a decrease of instance/storage/used_bytes for the source and a rate of change increase of subscription/num_undelivered_messages for the destination
B) An alert based on an increase of subscription/num_undelivered_messages for the source and a rate of change decrease of instance/storage/used_bytes for the destination
C) An alert based on an increase of instance/storage/used_bytes for the source and a rate of change decrease of subscription/num_undelivered_messages for the destination
D) An alert based on a decrease of subscription/num_undelivered_messages for the source and a rate of change increase of instance/storage/used_bytes for the destination

4. You are planning to migrate your current on-premises Apache Hadoop deployment to the cloud. You need to ensure that the deployment is as fault-tolerant and cost-effective as possible for long-running batch jobs. You want to use a managed service. What should you do?

A) Change references in scripts from hdfs:// to gs://
B) Install Hadoop and Spark on a 10-node Compute Engine instance group with standard instance
C) Use a standard persistent disk and 50% preemptible worker
D) Deploy a Cloud Dataproc cluste
E) Use an SSD persistent disk and 50% preemptible worker
F) Install the Cloud Storage connector, and store the data in Cloud Storag
G) Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
H) Deploy a Cloud Dataproc cluste
I) Store data in Cloud Storage, and change references in scripts from hdfs:// to gs://
J) Install Hadoop and Spark on a 10-node Compute Engine instance group with preemptible instances.Store data in HDF
K) Change references in scripts from hdfs:// to gs://

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) 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) Use Cloud Deployment Manager to automate access provision.
D) Only use service accounts when sharing data for Cloud Storage buckets and BigQuery datasets.
E) Introduce resource hierarchy to leverage access control policy inheritance.
F) Create distinct groups for various teams, and specify groups in Cloud IAM policies.

Solutions: