Cloudera CDP-3002 exam dumps - CDP Data Engineer - Certification Exam

  • Exam Code: CDP-3002
  • Exam Name: CDP Data Engineer - Certification Exam
  • Updated: Sep 16, 2026     Q & A: 320 Questions and Answers

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Cloudera CDP-3002 Exam Syllabus Topics:

SectionWeightObjectives
Topic 1: Data Pipeline Orchestration20%- Pipeline Scheduling and Triggers
- Workflow Dependencies
- Error Handling and Retries
- Apache Airflow on CDP
Topic 2: Data Processing with Spark30%- Spark SQL and DataFrames
- Spark Performance Optimization
- DataFrame and Dataset APIs
- Spark Core Concepts
- Spark Structured Streaming
Topic 3: Data Ingestion and Integration20%- Stream Data Ingestion
- Batch Data Ingestion
- CDC (Change Data Capture)
- Data Federation
- Data Transformation and ETL
Topic 4: CDP Platform Operations15%- Data Lake and Storage
- Cluster Management and Monitoring
- Cloudera Data Platform Architecture
- Cloudera Flow Management
Topic 5: Data Quality and Governance15%- Data Validation and Cleansing
- Data Lineage
- Access Control and Security
- Data Catalog and Metadata

Cloudera CDP Data Engineer - Certification Sample Questions:

Question #1

You have a PySpark application packaged as 'MyPySparkApp-0. I-py3-none-any.whl'. In your 'app.py', you utilize a function from an external library, 'numpy', listed in your 'requirements.txt'. How should you deploy this application to ensure 'numpy' is available at runtime?

  • A. Upload both 'app.py' and 'MyPySparkApp-0.1-py3-none-any.whl' and submit using 'spark-submit --py-files MyPySparkApp-0.1-py3-none- any.whl app.py'.
  • B. Upload 'app.py' only and submit using 'spark-submit app.py'.
  • C. Upload 'MyPySparkApp-0.1-py3-none-any.whl' only and submit using 'spark-submit --py-files MyPySparkApp-0.1-py3-none-any.whl'.
  • D. Upload 'app.py' and manually install 'numpy' on all nodes before submitting using 'spark-submit app.py'.
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Correct Answer: A  🗳️

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Question #2

When monitoring a PySpark application in Kubernetes, you notice that Executor pods are frequently restarting. What is the most likely cause of this issue?

  • A. Insufficient memory allocation for Executor pods.
  • B. Dynamic resource allocation is disabled.
  • C. Executor pods are not configured to restart upon failure.
  • D. Too many tasks assigned to each Executor.
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Correct Answer: A  🗳️

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Question #3

In the context of Cloudera's SQL engines, what does the presence of a "Broadcast Hash Join" in an Explain Plan suggest about query performance?

  • A. It suggests that the join operation might be a performance bottleneck for large datasets
  • B. It implies that no indexing is used in the join operation
  • C. It indicates an optimal use of network resources
  • D. It means that the query will execute faster than with any other join method
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Correct Answer: A  🗳️

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Question #4

Which of the following best describes the benefit of partition pruning in Spark SQL?

  • A. It increases the number of partitions to maximize parallelism.
  • B. It decreases the amount of data shuffled during join operations.
  • C. It dynamically adjusts partition sizes based on the query execution plan.
  • D. It selectively processes partitions that meet certain criteria, reducing 1/0.
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Correct Answer: D  🗳️

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Question #5

Why is it recommended to use the DataFrame API over RDDs for most data processing tasks in Spark?

  • A. DataFrames provide more fine-grained control over partitioning and parallelism.
  • B. DataFrames require less memory and compute resources compared to RDDs.
  • C. DataFrames automatically optimize queries using the Catalyst optimizer and Tungsten execution engine.
  • D. RDDs are deprecated and will be removed in future versions of Spark.
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Correct Answer: C  🗳️

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