Professional-Data-Engineer Online Training Materials | Professional-Data-Engineer Sample Questions Answers

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Google Certified Professional Data Engineer Exam Sample Questions (Q18-Q23):

NEW QUESTION # 18
You have an Apache Kafka cluster on-prem with topics containing web application logs. You need to replicate the data to Google Cloud for analysis in BigQuery and Cloud Storage. The preferred replication method is mirroring to avoid deployment of Kafka Connect plugins.
What should you do?

A. Deploy a Kafka cluster on GCE VM Instances with the PubSub Kafka connector configured as a Sink connector. Use a Dataproc cluster or Dataflow job to read from Kafka and write to GCS.
B. Deploy the PubSub Kafka connector to your on-prem Kafka cluster and configure PubSub as a Source connector. Use a Dataflow job to read from PubSub and write to GCS.
C. Deploy a Kafka cluster on GCE VM Instances. Configure your on-prem cluster to mirror your topics to the cluster running in GCE. Use a Dataproc cluster or Dataflow job to read from Kafka and write to GCS.
D. Deploy the PubSub Kafka connector to your on-prem Kafka cluster and configure PubSub as a Sink connector. Use a Dataflow job to read from PubSub and write to GCS.

Answer: C

Explanation:
Explanation/Reference:

NEW QUESTION # 19
When creating a new Cloud Dataproc cluster with the projects.regions.clusters.create operation, these four values are required: project, region, name, and ____.

A. zone
B. label
C. node
D. type

Answer: A

Explanation:
At a minimum, you must specify four values when creating a new cluster with the projects.regions.clusters.create operation:
The project in which the cluster will be created
The region to use
The name of the cluster
The zone in which the cluster will be created
You can specify many more details beyond these minimum requirements. For example, you can also specify the number of workers, whether preemptible compute should be used, and the network settings.

NEW QUESTION # 20
Your company is performing data preprocessing for a learning algorithm in Google Cloud Dataflow.
Numerous data logs are being are being generated during this step, and the team wants to analyze them.
Due to the dynamic nature of the campaign, the data is growing exponentially every hour.
The data scientists have written the following code to read the data for a new key features in the logs.
BigQueryIO.Read
.named("ReadLogData")
.from("clouddataflow-readonly:samples.log_data")
You want to improve the performance of this data read. What should you do?

A. Use of both the Google BigQuery TableSchemaand TableFieldSchemaclasses.
B. Specify the TableReferenceobject in the code.
C. Use .fromQueryoperation to read specific fields from the table.
D. Call a transform that returns TableRowobjects, where each element in the PCollectionrepresents
a single row in the table.

Answer: D

NEW QUESTION # 21
You are developing a software application using Google's Dataflow SDK, and want to use conditional, for loops and other complex programming structures to create a branching pipeline. Which component will be used for the data processing operation?

A. Sink API
B. Pipeline
C. PCollection
D. Transform

Answer: D

Explanation:
Explanation
In Google Cloud, the Dataflow SDK provides a transform component. It is responsible for the data processing operation. You can use conditional, for loops, and other complex programming structure to create a branching pipeline.
Reference: https://cloud.google.com/dataflow/model/programming-model

NEW QUESTION # 22
You are designing a system that requires an ACID-compliant database. You must ensure that the system requires minimal human intervention in case of a failure. What should you do?

A. Configure a Bigtable instance with more than one cluster.
B. Configure a Cloud SQL for PostgreSQL instance with high availability enabled.
C. Configure a BJgQuery table with a multi-region configuration.
D. Configure a Cloud SQL for MySQL instance with point-in-time recovery enabled.

Answer: B

Explanation:
The best option to meet the ACID compliance and minimal human intervention requirements is to configure a Cloud SQL for PostgreSQL instance with high availability enabled. Key reasons: Cloud SQL for PostgreSQL provides full ACID compliance, unlike Bigtable which provides only atomicity and consistency guarantees. Enabling high availability removes the need for manual failover as Cloud SQL will automatically failover to a standby replica if the leader instance goes down. Point-in-time recovery in MySQL requires manual intervention to restore data if needed. BigQuery does not provide transactional guarantees required for an ACID database. Therefore, a Cloud SQL for PostgreSQL instance with high availability meets the ACID and minimal intervention requirements best. The automatic failover will ensure availability and uptime without administrative effort.

NEW QUESTION # 23
......

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Professional-Data-Engineer Online Training Materials | Professional-Data-Engineer Sample Questions Answers

100% Pass 2025 Professional-Data-Engineer: Google Certified Professional Data Engineer Exam Fantastic Online Training Materials

Google Certified Professional Data Engineer Exam Sample Questions (Q18-Q23):

100% Pass Quiz 2025 Professional-Data-Engineer: Google Certified Professional Data Engineer Exam – Reliable Online Training Materials

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