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Cloudera CDP Data Engineer - Certification : CDP-3002
- Exam Code: CDP-3002
- Exam Name: CDP Data Engineer - Certification Exam
- Q & A: 320 Questions and Answers
About Cloudera CDP Data Engineer - Certification : CDP-3002 Exam
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Cloudera CDP-3002 Exam Syllabus Topics:
| Section | Objectives |
|---|---|
| Data Storage and Modeling | - Data lake architecture
|
| Data Governance and Security | - Security frameworks
|
| Data Ingestion and Integration | - Batch and streaming ingestion
|
| Data Processing and Transformation | - SQL analytics engines
|
| Platform Operations | - Cluster and workload management
|
Cloudera CDP Data Engineer - Certification Sample Questions:
Question #1
When optimizing join operations in a distributed data processing environment, why is it important to co-locate join keys?
- A. To increase the storage capacity required for join operations
- B. To enhance data encryption methods for secure joins
- C. To ensure data integrity by preventing data loss during network transmission
- D. To minimize data shuffle by ensuring related data is on the same node
Correct Answer: D 🗳️
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Question #2
After running a PySpark job, you want to analyze the performance and identify potential bottlenecks. Which tool should you use for this purpose?
- A. PySpark DataFrame API.
- B. Hadoop YARN ResourceManager.
- C. Spark Web I-Jl.
- D. PySpark SQL CLI.
Correct Answer: C 🗳️
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Question #3
What is the primary consideration when choosing the number of buckets in a Hive table?
- A. The number of nodes in the Hadoop cluster
- B. The total storage capacity of the HDFS cluster
- C. The expected distribution of data across the bucketing column
- D. The number of rows in each partition
Correct Answer: C 🗳️
Explanation: Only visible for TorrentVCE members. You can sign-up / login (it's free).
Question #4
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?
- A. Use the depends_on_past parameter in each data quality check task.
- B. Explicitly set task dependencies using the set_upstream or set_downstream methods.
- C. Implement each data quality check as a separate DAG.
- D. Use the SequentialExecutor for the Airflow environment.
Correct Answer: B 🗳️
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Question #5
Which strategy is most effective for managing schema evolution in a big data application that relies on schema inference?
- A. Manually updating the inferred schema for each data ingestion
- B. Integrating schema registry services that track and manage schema versions
- C. Completely disabling schema inference and relying on static schemas
- D. Using a single version of the schema for all data, regardless of changes
Correct Answer: B 🗳️
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