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Cloudera CDP Data Engineer - Certification Sample Questions:

1. You're working with a large dataset that needs to be partitioned and processed in chunks to improve efficiency. How can you achieve this using Airflow operators?

A) Implement a custom Python script to handle partitioning and then use the BashOperator to execute the script within the DAG.
B) Use the Split Operator to divide the data into smaller subsets and chain them with downstream processing tasks.
C) Configure the source system to provide the data pre-partitioned for efficient processing.
D) Leverage the File transform operator to partition the data based on specific criteria within the operator itself.

2. You need to optimize the performance of a Spark query that involves joining data from multiple Hive tables. What strategies can you employ to improve efficiency?

A) Pre-partition tables based on the join columns for faster data co-location
B) Increase the number of Spark executors without any further optimization
C) All of the above
D) Use broadcast joins for small tables involved in the join operation

3. You need to design a DAG that can be easily paused, resumed, or skipped based on specific conditions. How can you achieve this functionality?

A) Implement custom logic within each task to check for pause or skip conditions.
B) Configure the DAG to run continuously without any manual intervention.
C) Leverage Airflow XCom to share information about the desired action (pause, resume, skip) between tasks.
D) Utilize Airflow pools to dynamically control the execution of tasks based on resource availability.

4. You are working on a project that involves processing large datasets stored in HDFS. You need to read a CSV file into a DataFrame using PySpark. Which of the following code snippets correctly achieves this?

A)

B)

C)

D)

5. When would it be advantageous to use both partitioning and bucketing on a Hive table?

A) When dealing with large datasets that require efficient querying and data sampling
B) When data needs to be stored in a single file for archival purposes
C) When managing small datasets to reduce complexity
D) When data security is a primary concern

Solutions: