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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. Which Airflow component is responsible for executing task instances in a distributed manner?

A) Webserver
B) Scheduler
C) Executor
D) Worker

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

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

3. What impact does the Spark configuration parameter spark.network.timeout have on Spark streaming applications?

A) It specifies the timeout for network operations such as data shuffle and broadcast.
B) It sets the timeout for Akka-based network operations, crucial for Spark streaming's stability.
C) It determines the timeout for connections between executors and the Spark driver, impacting task retries and executor loss detection.
D) It controls the maximum time a Spark streaming application will wait for data before timing out.

4. You're working with a large Spark DataFrame and need to perform an aggregation operation (e.g., can you improve the performance of the aggregation? SUM, COUNT). How

A) Use Spark SQL's built-in aggregation functions like SUM and COUNT
B) Increase the number of Spark executors without further optimization
C) All of the above
D) Leverage partitioning techniques to group relevant data together

5. You have a DataFrame containing sales data with columns "product_id", "customer id", and "amount". How can you efficiently calculate the total sales per customer?

A) Utilize spark SQL's GROUP BY and SUM functions
B) Implement a custom function to group and sum the sales
C) Leverage Spark's machine learning library (MLIiB. for aggregation
D) Use a loop to iterate through the DataFrame and accumulate the sales for each customer

Solutions: