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Cloudera CDP Data Engineer - Certification Sample Questions:

1. You need to update several rows in a large Iceberg table. Which of the following approaches would likely be the most efficient?

A) Employ Iceberg's time travel feature to revert to an older snapshot and reapply changes.
B) Use the Iceberg DELETE and INSERT operations together.
C) Read the entire table, make changes in Spark, and overwrite the table.
D) Use the Iceberg MERGE INTO syntax for row-level updates.

2. While working with Spark SQL, you encounter an error message stating "Unable to resolve table 'table_name"'. What could be the potential cause of this error?

A) All of the above
B) The Spark application doesn't have sufficient permissions to access the table
C) The table doesn't exist in the Hive metastore
D) The table schema is not compatible with Spark SQL

3. When creating a data pipeline in the Cloudera Data Engineering service, what is the primary file format used to define the pipeline steps and configuration?

A) YAML
B) Python script
C) Shell script
D) JSON

4. You need to process data stored in AWS S3 using SparkSQL. Which of the following options correctly reads a JSON file stored in S3 into a DataFrame and performs a SQL query on it?

A)

B)

C)

D)

5. Which Airflow feature allows you to template your tasks, enabling dynamic generation of task parameters such as table names for data quality checks?

A) XComs
B) Variables
C) Airflow Plugins
D) Jinja Templating

Solutions: