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Cloudera CDP-3002 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Data Quality and Governance | 15% | - Access Control and Security - Data Validation and Cleansing - Data Lineage - Data Catalog and Metadata |
| CDP Platform Operations | 15% | - Cluster Management and Monitoring - Cloudera Data Platform Architecture - Data Lake and Storage - Cloudera Flow Management |
| Data Pipeline Orchestration | 20% | - Pipeline Scheduling and Triggers - Apache Airflow on CDP - Error Handling and Retries - Workflow Dependencies |
| Data Ingestion and Integration | 20% | - Batch Data Ingestion - Data Federation - Data Transformation and ETL - CDC (Change Data Capture) - Stream Data Ingestion |
| Data Processing with Spark | 30% | - DataFrame and Dataset APIs - Spark Structured Streaming - Spark Core Concepts - Spark SQL and DataFrames - Spark Performance Optimization |
Cloudera CDP Data Engineer - Certification Sample Questions:
1. Your Airflow DAG involves sending notifications upon successful completion of the entire pipeline. How can you achieve this functionality?
A) Use the Email Operator to send an email notification upon successful DAG run completion.
B) Utilize Airflow variables to store notification details and access them within the final task.
C) Implement a custom notification script within the final task of the DAG.
D) Configure the Airflow web UI to send alerts based on DAG run status.
2. In the context of caching data for reuse in Spark, how does the Tungsten project contribute to enhancing memory management and execution efficiency?
A) By optimizing Spark's internal memory management and data processing operations
B) By providing a graphical interface for memory management
C) By rewriting Spark operations in a lower-level language for direct memory access
D) By enforcing strict data typing to reduce runtime type checking overhead
3. How can you dynamically generate tasks in Apache Airflow?
A) By using Python loops to create tasks during DAG parsing
B) By defining a Python function inside the DAG file
C) By using the Jinja templating engine
D) By using the Variable feature to store dynamic configurations
4. Your ETL pipeline processes sensitive dat
a. How can you ensure data security within Airflow?
A) Grant everyone access to the Airflow web UI to monitor and manage the pipeline.
B) Implement encryption for sensitive data at rest and in transit.
C) Use environment variables to store sensitive credentials for accessing data sources.
D) Store passwords and other sensitive data directly within your Airflow code.
5. How does setting the "priority_weight" parameter in Airflow tasks influence the scheduler's behavior?
A) It influences the order in which tasks are selected for execution across multiple DAGs competing for resources.
B) It sets a fixed time slot during which the task must be executed, overriding the scheduler's automatic timing.
C) It allocates more CPIJ and memory resources to tasks with higher priority weights.
D) It determines the order in which tasks are executed within the same DAG.
Solutions:
| Question # 1 Answer: A | Question # 2 Answer: A | Question # 3 Answer: A | Question # 4 Answer: B | Question # 5 Answer: A |





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