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Cloudera CDP Data Engineer - Certification Sample Questions:

1. A PySpark application is facing performance issues due to uneven distribution of data across the nodes. Which approach would best help in resolving this issue?

A) Apply 'df.coalesce(Y to reduce the number of partitions.
B) Employ to redistribute data based on a key.
C) Convert the DataFrame to an RDD and then back to a DataFrame.
D) Use 'df.collect()'.

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

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

3. Which of the following is a benefit of using RESTful APIs with Cloudera Manager for cluster management?

A) Direct database access to Cloudera Manager's underlying storage mechanism.
B) Increased network latency and overhead.
C) The ability to integrate with continuous integration/continuous deployment (CI/CD. pipelines.
D) Reduced compatibility with industry-standard tools and protocols.

4. In Apache Airflow, what is the purpose of setting max_active_runs in a DAG's configuration?

A) To specify the maximum number of DAG runs that can be executed in parallel.
B) To control the number of retries for a failed task.
C) To determine the maximum number of DAG files that can be parsed at any given time.
D) To limit the number of task instances that can run concurrently within the DAG.

5. You are deploying a Spark application in a Kubernetes environment. Your application is designed to process large datasets using Spark's data frame API. You have created a Docker image for your Spark application. Which of the following 'kubectl* commands should you use to deploy your Spark application onto the Kubernetes cluster?

A) 'kubectl create deployment my-spark-app --image=my-spark-app-image'
B) 'kubectl expose deployment my-spark-app --type=LoadBalancer -port=808ff
C) *kubectl apply -f spark-app.yamr
D) *kubectl config set-context -current -namespace=my-spark-app'

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