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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. What is the impact of caching intermediate data in Spark on iterative algorithms' performance?

A) It improves performance by reducing the need to recompute data in each iteration.
B) It decreases fault tolerance by storing data in volatile storage.
C) It significantly increases the execution time of each iteration.
D) It has no impact on performance but increases storage requirements.

2. Which strategy is most effective for managing schema evolution in a big data application that relies on schema inference?

A) Completely disabling schema inference and relying on static schemas
B) Integrating schema registry services that track and manage schema versions
C) Manually updating the inferred schema for each data ingestion
D) Using a single version of the schema for all data, regardless of changes

3. What Airflow feature allows you to template parts of your DAG to dynamically change based on the execution context?

A) XComs
B) PythonOperator
C) BranchOperator
D) Jinja Templating

4. In a PySpark application running on Kubernetes, if one of the Executors fails to execute a task due to a node failure, what action does the Spark Driver take?

A) It requests Kubernetes to allocate more resources to the failed Executor.
B) It pauses the application until the failed Executor is back online.
C) It immediately shuts down the entire application.
D) It reschedules the task on a different Executor.

5. Considering Hive's optimization mechanisms, under which scenario might partition pruning fail to improve query performance?

A) When querying data using the exact partition key in the WHERE clause
B) When querying data using a non-partition column as a filter
C) When the partitioned table contains a small number of partitions
D) When the table is partitioned on a column frequently used in query filters

Solutions: