Cloudera CDP Data Engineer - Certification : CDP-3002

  • Exam Code: CDP-3002
  • Exam Name: CDP Data Engineer - Certification Exam
  • Updated: Sep 10, 2026
  • Q & A: 320 Questions and Answers

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About Cloudera CDP Data Engineer - Certification : CDP-3002 Exam

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Cloudera CDP-3002 Exam Syllabus Topics:

SectionObjectives
Topic 1: Data Governance and Security- Security frameworks
  • 1. Authentication and authorization in CDP
    • 2. Ranger / Sentry policies
      - Data governance
      • 1. Data lineage and auditing
        • 2. Metadata management
          Topic 2: Platform Operations- Cluster and workload management
          • 1. Resource management and scheduling
            • 2. Monitoring and troubleshooting
              Topic 3: Data Ingestion and Integration- Data movement and pipelines
              • 1. Data flow orchestration
                • 2. ETL/ELT workflows
                  - Batch and streaming ingestion
                  • 1. Data ingestion patterns in CDP
                    • 2. Apache NiFi / Kafka ingestion concepts
                      Topic 4: Data Processing and Transformation- Spark processing
                      • 1. Distributed processing concepts
                        • 2. Spark SQL and DataFrames
                          - SQL analytics engines
                          • 1. Data transformation best practices
                            • 2. Hive / Impala query optimization
                              Topic 5: Data Storage and Modeling- Data modeling
                              • 1. Schema design for analytics
                                • 2. Dimensional modeling concepts
                                  - Data lake architecture
                                  • 1. HDFS / cloud object storage concepts
                                    • 2. Partitioning and file formats (Parquet, ORC)

                                      Cloudera CDP Data Engineer - Certification Sample Questions:

                                      Question 1

                                      You're working with an Airflow DAG that performs data quality checks on sensitive dat a. How can you ensure data security during the checks?

                                      A. Implement data masking techniques to obfuscate sensitive information during the checks.
                                      B. All of the above
                                      C. Store sensitive data like thresholds and comparison values directly within the DAG code.
                                      D. Utilize environment variables to store sensitive data and access them within the PythonOperator.


                                      Question 2

                                      You are setting up a Spark Driver pod in Kubernetes and need to specify resource requests and limits. Which of the following configurations ensures that the Spark Driver has at least 1 CPU and 1 Gi of memory but can use up to 2 CPUs and 2 Gi of memory if available?

                                      A. Option D
                                      B. Option A
                                      C. Option B
                                      D. Option C


                                      Question 3

                                      What does setting the Spark configuration parameter 'spark.sql.shuffle.partitions' impact?
                                      A The default level of parallelism for joins and aggregations

                                      A. The memory allocation for executor instances
                                      B. The serialization format of data
                                      C. The compression codec used for shuffle files


                                      Question 4

                                      How does the Cloudera Optimization Framework leverage columnar storage formats for query performance improvement?

                                      A. By reducing network traffic through columnar data replication
                                      B. By encrypting data stored in columnar formats
                                      C. By allowing more efficient data scans and operations on compressed data
                                      D. By enabling more efficient compression and encoding schemes


                                      Question 5

                                      What is the recommended way to handle dependencies between data quality checks in Apache Airflow to ensure that checks are performed in a specific sequence?

                                      A. Use the depends_on_past parameter in each data quality check task.
                                      B. Explicitly set task dependencies using the set_upstream or set_downstream methods.
                                      C. Implement each data quality check as a separate DAG.
                                      D. Use the SequentialExecutor for the Airflow environment.


                                      Solutions:

                                      Question 1
                                      Answer: A,D
                                      Question 2
                                      Answer: C
                                      Question 3
                                      Answer: B
                                      Question 4
                                      Answer: C
                                      Question 5
                                      Answer: B

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