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Cloudera CDP Data Engineer - Certification Sample Questions:

1. 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) Use broadcast joins for small tables involved in the join operation
C) All of the above
D) Increase the number of Spark executors without any further optimization

2. Which strategy is most effective for managing schema evolution in a big data application that relies on schema inference?

A) Completely disabling schema inference and relying on static schemas
B) Integrating schema registry services that track and manage schema versions
C) Manually updating the inferred schema for each data ingestion
D) Using a single version of the schema for all data, regardless of changes

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

4. When using Cloudera's Command Line Interface (CLI), which of the following tasks can be performed?

A) Modifying the source code of Cloudera Manager.
B) Only data ingestion tasks can be automated.
C) Managing users and setting permissions on HDFS.
D) Cluster monitoring and diagnostics cannot be performed.

5. Which component of the Cloudera Data Engineering service is responsible for managing and scheduling data pipelines?

A) CDH Management Console
B) Cloudera Scheduler
C) Cloudera Manager
D) Cloudera Navigator

Solutions: