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Valid CDP-3002 Exam Questions, Test CDP-3002 Questions

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Cloudera CDP Data Engineer - Certification Exam Sample Questions (Q284-Q289):

NEW QUESTION # 284
You're designing a schema for an Iceberg table that will store time-series sensor dat a. Which of the following considerations is most important for optimal query performance and storage efficiency?

A. Partitioning the data by both sensor ID and timestamp.
B. Using nested structs to represent the complex structure of sensor readings.
C. Pre-aggregating sensor data at hourly intervals before inserting into the Iceberg table.
D. Normalizing sensor data across multiple tables to reduce redundancy.

Answer: A

NEW QUESTION # 285
How can you leverage Spark Streaming for real-time data processing and analytics?

A. By implementing custom logic for data ingestion, transformation, and output.
B. Both A and B.
C. By defining a streaming DataFrame with a window function.
D. By utilizing Structured Streaming with Kafka as the source and sink.

Answer: B

Explanation:
Spark Streaming offers two primary approaches: defining streaming DataFrames with window functions for micro-batching and utilizing Structured Streaming for end-to-end processing pipelines with sources like Kafka.

NEW QUESTION # 286
You need to design your Airflow DAG for data quality checks to be easily monitored and visualized. How can you achieve this?

A. Utilize Airflow XCom to share the outcome of the checks (success/failurE. with downstream tasks for further processing.
B. Leverage Airflow's built-in metrics and monitoring features like the Airflow web UI to track check execution and results.
C. Implement custom logic to send detailed logs about the check results to external monitoring tools.
D. All of the above

Answer: A,B,C

Explanation:
All options mentioned in D can be valuable for troubleshooting errors in data quality checks: Airflow UI: Task details page might display error messages or logs specific to the check. Airflow Logs: Scheduler and worker logs might provide additional context about the error and its origin. Custom Script Inspection: Examining the custom Python script used for the check can reveal potential errors within the logic itself.

NEW QUESTION # 287
Your team is integrating PySpark with a MySQL database. You need to read data from a table named 'employees'. Which of the following PySpark code snippets correctly accomplishes this task?

Answer: C

Explanation:
Option A is correct because it properly uses the JDBC format with all the necessary options including the URL, database table, and user credentials.

NEW QUESTION # 288
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)

A. Partitioning
B. Snapshots
C. Metadata tables
D. Manifest files
E. Iceberg table constraints (not yet fully supporteD.

Answer: C,D

NEW QUESTION # 289
......

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