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  1. Home
  2. Cloudera Certification
  3. CDP-3002 Exam
  4. Cloudera.CDP-3002.v2025-09-26.q117 Dumps
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Question 76

You're working with a large dataset that needs to be partitioned and processed in chunks to improve efficiency. How can you achieve this using Airflow operators?

Correct Answer: A
The Split Operator is specifically designed to split data into smaller chunks and trigger downstream tasks for each partition, making it ideal for handling large datasets efficiently.
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Question 77

Which of the following is a best practice for organizing tasks within a DAG in Apache Airflow?

Correct Answer: A
Organizing tasks into groups with similar functionalities using SubDAGs is considered a best practice. It enhances the readability and maintainability of the DAG by logically separating different parts of the workflow, making it easier to understand, debug, and scale.
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Question 78

What is the impact of query vectorization in Cloudera's Optimization Framework?

Correct Answer: C
Query vectorization improves performance by allowing multiple rows to be processed together as a batch, instead of one row at a time. This reduces CPU usage and improves throughput for query operations-Explain Plans
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Question 79

You're implementing a data quality process for Iceberg tables in CDP Which of the following Iceberg features can help you enforce constraints and detect data anomalies? (Choose two)

Correct Answer: A,B
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Question 80

What is the recommended way to handle dependencies between data quality checks in Apache Airflow to ensure that checks are performed in a specific sequence?

Correct Answer: B
Explicitly setting task dependencies using set_upstream, set_downstream, or the bitshift operators (]] and [[) in your DAG definition file is the recommended way to manage the sequence of data quality checks. This approach ensures that tasks are executed in the correct order, based on their dependencies.
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