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Cloudera CDP Data Engineer - Certification Sample Questions:

1. In the context of Cloudera's SQL engines, what does the presence of a "Broadcast Hash Join" in an Explain Plan suggest about query performance?

A) It implies that no indexing is used in the join operation
B) It means that the query will execute faster than with any other join method
C) It suggests that the join operation might be a performance bottleneck for large datasets
D) It indicates an optimal use of network resources

2. How can you secure your data pipelines within the Cloudera Data Engineering service to ensure data privacy and compliance?

A) Implement encryption for data at rest and in transit but ignore user access control.
B) Employ a layered security approach combining access control, encryption, and audit logging.
C) Utilize Cloudera Manager security features without additional configuration within the Data Engineering service.
D) Rely solely on access control lists (ACLs) defined on individual data assets.

3. You are designing a data pipeline that involves ingesting data from multiple sources, performing data transformations using Spark, and storing the results in a data lake. How would you leverage the Cloudera Data Engineering service to ensure efficient and fault-tolerant execution?

A) Utilize separate Spark jobs for each data source and transformation step.
B) Implement custom logic within the YAML configuration file to manage data flow and error handling.
C) Design the pipeline with stages and steps, leveraging Spark operators for transformations and utilizing retries and error handling mechanisms.
D) Develop a single Spark job containing all transformation logic.

4. When deploying a Spark application in Kubernetes, what is the purpose of specifying the '-conf spark.kubernetes.driver.pod.name=spark-driver-pod' in the 'spark-submit' command?

A) To assign a specific node for the Driver pod.
B) To name the Executor pods.
C) To define the Docker image for the Driver pod.
D) To specify the name of the Spark Driver pod.

5. In the context of big data processing, what is a potential downside of relying heavily on schema inference?

A) Enhanced data security and compliance
B) Increased data storage efficiency
C) Potential performance overhead due to the dynamic analysis of data structure
D) Reduced flexibility in handling different data types

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