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Cloudera CDP-3002 Exam Syllabus Topics:
| Section | Weight | Objectives |
|---|---|---|
| Topic 1: CDP Platform Operations | 15% | - Cloudera Data Platform Architecture - Data Lake and Storage - Cluster Management and Monitoring - Cloudera Flow Management |
| Topic 2: Data Processing with Spark | 30% | - Spark Performance Optimization - Spark SQL and DataFrames - Spark Structured Streaming - Spark Core Concepts - DataFrame and Dataset APIs |
| Topic 3: Data Ingestion and Integration | 20% | - CDC (Change Data Capture) - Stream Data Ingestion - Data Federation - Data Transformation and ETL - Batch Data Ingestion |
| Topic 4: Data Quality and Governance | 15% | - Data Lineage - Data Validation and Cleansing - Access Control and Security - Data Catalog and Metadata |
| Topic 5: Data Pipeline Orchestration | 20% | - Pipeline Scheduling and Triggers - Error Handling and Retries - Apache Airflow on CDP - Workflow Dependencies |
Cloudera CDP Data Engineer - Certification Sample Questions:
1. Your Airflow DAG involves tasks that require access to specific resources like databases or external services. How can you ensure these resources are available and properly configured for the DAG execution?
A) Grant everyone access to all resources to avoid potential configuration issues.
B) Implement custom logic within each task to dynamically discover and connect to resources.
C) Hardcode connection details (credentials, URLs) directly within the DAG code.
D) Utilize Airflow connections to store and manage resource details securely.
2. In an Airflow DAG, you have tasks A, B, C, and D. Task A must complete before B and C can start, but B and C can run in parallel. Task D should only run once both B and C have completed. How do you set up these dependencies?
A) A]] B ]] C]] D
B) A.set_downstream([B, C]) and set_upstream([B, C])
C) A]] B, C]] D
D) [A ]] B, A]] C] and [B, C] ]] D
3. When deploying a packaged PySpark application using 'spark-submit', which option is used to include the packaged dependencies?
A) --jars
B) -files
C) --py-files
D) --packages
4. Which of the following is TRUE about using Explain Plans for performance tuning?
A) Explain Plans always show the actual runtime of a query
B) They can help identify operations that may become performance bottlenecks
C) They provide detailed network latency information
D) They are only useful for queries that involve joins
5. What challenge does schema inference aim to address when dealing with big data ecosystems?
A) Ensuring that all data is encrypted according to its inferred schema
B) The variety and complexity of data formats and structures
C) The need for large storage spaces to hold data schemas
D) Reducing the computational power required for data analysis
Solutions:
| Question # 1 Answer: D | Question # 2 Answer: D | Question # 3 Answer: C | Question # 4 Answer: B | Question # 5 Answer: B |
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