Free CDP-3002 Questions for Cloudera CDP-3002 Exam

Question #1

Your team is integrating PySpark with a MySQL database. You need to read data from a table named 'employees'. Which of the following PySpark code snippets correctly accomplishes this task?

A.

B.

C.

D.

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Correct Answer: C Vote an answer

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Question #2

You're using Iceberg for streaming data ingestion. A critical use case requires exactly-once processing guarantees. Which considerations are most important for achieving this? (Choose two)

A. Enabling Iceberg's transactional writes

B. Using a data format like JSON, which is less prone to corruption than Parquet.

C. Disabling Iceberg's snapshot isolation feature.

D. Carefully configuring the streaming source to handle retries and failures

E. Leveraging a CDC (Change Data Captur tool integrated with Iceberg.

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Correct Answer: A,D Vote an answer

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Question #3

How does Spark achieve fault tolerance during distributed processing?

A. null

B. By replicating data across all nodes in the cluster

C. By restarting failed tasks on different nodes

D. By implementing automatic checkpointing of intermediate results

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Correct Answer: A Vote an answer

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Question #4

Why are partitioned tables beneficial in Hive for large datasets?

A. They decrease the security of the data.

B. They ensure that all data is stored in a single file, simplifying access.

C. They allow for faster query processing by scanning only relevant partitions.

D. They automatically encrypt data based on the partition key.

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Correct Answer: C Vote an answer

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Question #5

Your Airflow DAG includes data quality checks that involve comparing data against predefined thresholds or reference datasets. How can you handle potential failures during these checks and ensure the pipeline doesn't proceed with unreliable data?

A. Configure the DAG to automatically retry failed tasks associated with the data quality checks.

B. All of the above

C. Use the BranchPythonOperator to check the success of the data quality checks and conditionally branch the DAG execution based on the outcome.

D. Implement custom logic within the PythonOperator to raise exceptions upon failed checks and trigger downstream tasks to handle the error.

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Correct Answer: B,C Vote an answer

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Question #6

In Apache Airflow, which strategy allows for the dynamic generation of tasks within a DAG based on external data sources, such as a list of database tables?

A. Implementing a PythonOperator that generates other tasks at runtime

B. Utilizing the @dag decorator with dynamic input parameters

C. Employing the TaskFlow API with dynamic task mapping

D. Using the Variable class to store and retrieve the list of tables

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Correct Answer: C Vote an answer

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Question #7

What is the impact of query vectorization in Cloudera's Optimization Framework?

A. It improves query performance by processing batches of rows together

B. It slows down query execution by adding complexity

C. It encrypts query results for security

D. It enables the execution of SQL commands

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Correct Answer: A Vote an answer

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Question #8

Which of the following is a benefit of using RESTful APIs with Cloudera Manager for cluster management?

A. The ability to integrate with continuous integration/continuous deployment (CI/CD. pipelines.

B. Reduced compatibility with industry-standard tools and protocols.

C. Increased network latency and overhead.

D. Direct database access to Cloudera Manager's underlying storage mechanism.

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Correct Answer: A Vote an answer

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Question #9

How can you prevent backfilling for a specific DAG in Apache Airflow?
A Set catchup=False in the DAG's arguments.

A. Use schedule interval=None.

B. Define is backfill=False in the DAG definition.

C. Set max active runs=1.

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Correct Answer: C Vote an answer

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Question #10

You are deploying a Spark application on Kubernetes, which requires access to a web I-Jl. You decide to expose it using a Kubernetes service. Which type of service would you typically use to expose the Spark IJI to external traffic?

A. ClusteriP

B. ExternalName

C. LoadBalancer

D. NodePort

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Correct Answer: D Vote an answer

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Question #11

You encounter an error message stating "Failed to find persisted data for RDD" in your Spark application. What are the potential causes and how can you troubleshoot them?

A. Spark encountered a network issue and couldn't access the persisted data

B. The RDD was never persisted, or the storage level was set incorrectly

C. All of the above

D. The data might have been corrupted or deleted from the storage location

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Correct Answer: C Vote an answer

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Question #12

What mechanism does Airflow provide to retry failed tasks?

A. Airflow Scheduler's automatic rerun feature

B. The on failure callback function in DAG definitions

C. The retry_delay and retries parameters in task definitions

D. Manual intervention and rerun via the Airflow Webserver

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Correct Answer: C Vote an answer

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Question #13

While working with Spark SQL, you encounter an error message stating "Unable to resolve table 'table_name"'. What could be the potential cause of this error?

A. The table schema is not compatible with Spark SQL

B. All of the above

C. The Spark application doesn't have sufficient permissions to access the table

D. The table doesn't exist in the Hive metastore

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Correct Answer: B Vote an answer

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Free CDP-3002 Questions for Cloudera CDP Data Engineer - Certification CDP-3002 Exam as PDF & Practice Test Engine

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