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Cloudera CDP-3002 Exam Syllabus Topics:

Cloudera CDP Data Engineer - Certification Sample Questions:

1. 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)

2. What is the primary purpose of the Cost-Based Optimizer (CBO) in the context of Cloudera's Optimization Framework?

A) To minimize the amount of data processed
B) To distribute data evenly across the cluster
C) To decide the best execution plan based on the cost of operations
D) To choose the data storage format

3. You are deploying a Spark application on Kubernetes and need to specify the amount of memory allocated to each Executor. In your PySpark code, which configuration setting will you use?

A) 'spark.executor.memory'
B) 'spark.executor.instances'
C) 'spark.driver.memory'
D) 'spark.executor.memoryoverhead'

4. What is a primary benefit of schema-on-read compared to schema-on-write in big data processing frameworks?

A) It significantly reduces the computational overhead during data ingestion.
B) It allows for greater flexibility in data formats and structures at the time of analysis.
C) It requires all data to conform to a rigid schema before storage.
D) It mandates manual intervention for each data read operation.

5. Your Spark application encounters performance issues when reading data from a large Hive table. What potential optimization techniques can you explore?

A) Increase the number of Spark executors without further optimization
B) Use a different file format for the Hive table, like CSV, for faster parsing
C) Implement custom data compression logic within Spark for improved storage efficiency
D) Leverage partition pruning to only read relevant data from the table

Solutions: