Cloudera CDP-3002 : CDP Data Engineer - Certification Exam

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Cloudera CDP Data Engineer - Certification Sample Questions:

1. You're working with a Spark application that processes sensitive dat
a. How can you ensure that persisted data remains secure even if accessed from unauthorized sources?

A) Implement custom access control mechanisms within your application
B) Encrypt the data before persisting it and decrypt it when needed
C) No additional security measures are needed, as Spark handles data security
D) Rely on Spark's lineage tracking to prevent unauthorized access

2. For scripting and automation purposes, how can Cloudera's CLI tools be integrated into administrative workflows?

A) Using exclusively manual CLI commands for each task without automation.
B) By creating custom plugins for web browsers to manage Cloudera services.
C) CLI tools cannot be integrated into administrative workflows; they are only for interactive use.
D) Incorporating CLI commands into shell scripts or automation tools like Ansible, Chef, or Puppet.

3. When performing a bucketed join between two tables, what must be true for the join to be executed as a map-side join, thereby maximizing performance?

A) Both tables must be partitioned, not bucketed, on the join columns.
B) Both tables must be bucketed on the join columns with the same number of buckets and the same hash function.
C) Both tables must be bucketed on the join columns with a different number of buckets.
D) Only one table needs to be bucketed, regardless of the bucket count.

4. A data analyst is performing a join operation in PySpark between a large DataFrame Clarge_df) and a much smaller DataFrame ('small_df). The process is very slow. What can the analyst do to optimize this join operation?

A) Utilize the 'broadcast' function in the join operation.
B) Increase the number of partitions in 'small_df'.
C) Apply before the join.
D) Use "key").

5. You're building a complex Airflow DAG with numerous tasks and dependencies. How can you improve the DAG's readability and maintainability?

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

Solutions: