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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. Which Spark configuration parameter should be increased to improve performance when dealing with large broadcast variables?

A) 'spark.driver.memory'
B) 'spark.broadcast.blockSize'
C) 'spark.default.parallelism'
D) 'spark.executor.memory'

2. In Apache Airflow, what is a DAG?

A) A visualization tool for monitoring pipeline execution
B) A programming language used for creating data pipelines
C) A type of operator used for executing Python functions
D) A collection of tasks with directional dependencies

3. You're developing a Spark application with multiple stages, and you want to ensure that later stages only start processing after all data from the previous stage is complete. How can you achieve this dependency management in Spark?

A) Set appropriate configuration for spark.sql.shuffe.partitions
B) Implement custom logic to track completion of each stage
C) Leverage Spark's lineage tracking and stage boundaries
D) Use explicit rdd.persist() calls in each stage

4. You want to debug an issue within your Spark application that interacts with Hive tables. What tools and techniques can you employ for effective debugging?

A) Leverage Spark's web UI and Hive logs for general error messages
B) Implement unit tests for individual Spark operations within your application
C) Use Spark's Lineage Viewer to visualize data flow and identify potential errors
D) Print debug statements throughout the code to inspect intermediate data

5. How does partition pruning contribute to query performance in the Cloudera Data Platform?

A) By encrypting data at rest
B) By increasing the number of partitions
C) By removing unnecessary data replication
D) By selecting only relevant partitions for query execution

Solutions: