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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. Which feature of Apache Avro facilitates dynamic schema inference during data serialization and deserialization?

A) Embedded schema within data files
B) Manual schema declaration
C) Strong data typing
D) Schema versioning via external services

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 C
B) Option A
C) Option B
D) Option D

3. How does Airflow handle task dependencies?

A) By manually triggering tasks in the correct order
B) By using the ExternalTaskSensor to pause execution until an external condition is met
C) By specifying dependencies through the depends_on_past parameter in task definitions
D) By using the set_upstream() or set_downstream() methods, or the bitshift operators (]] and [[)

4. You're building a large and complex ETL pipeline with numerous tasks and dependencies. What are some best practices to ensure its maintainability and understandability?

A) All of the above
B) Implement extensive logging within each task to capture detailed execution information.
C) Use clear and descriptive names for tasks, operators, variables, and DAG comments throughout the code.
D) Break down the pipeline into smaller, modular sub-DAGs with well-defined functionalities.

5. You're working with a large dataset stored in multiple Parquet files across different HDFS directories. How can you efficiently load and process this data using Spark, ensuring data locality and minimizing shuffle operations?

A) Implement a custom function to read each Parquet file individually
B) Leverage Spark SQL catalogs and partition discovery
C) Use spark.read.parquet("/path/to/data/") with recursive directory listing
D) Directly load all files using spark.read.parquet("/path/to/data/")

Solutions: