CDP-3002 Exam Actual Questions & Exam CDP-3002 Objectives

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Cloudera CDP Data Engineer - Certification Exam Sample Questions (Q18-Q23):

NEW QUESTION # 18
You're designing a scalable and fault-tolerant Spark application for processing large-scale geospatial dat a. What additional considerations should you take into account beyond the general distributed processing principles?

A. Implement custom partitioning strategies based on geospatial coordinates
B. Leverage geospatial libraries like GeoSpark for efficient spatial operations
C. Choose a larger virtual machine size for Spark executors
D. Use a dedicated cluster specifically for geospatial processing tasks

Answer: A,B

Explanation:
While VM size A and dedicated clusters C might be relevant for scaling, focusing solely on these aspects doesn't address the specific needs of geospatial data. Leveraging libraries like GeoSpark provides optimized functions for spatial operations. Additionally, custom partitioning based on geospatial coordinates can improve query performance by ensuring relevant data is processed on the same nodes, reducing network overhead.

NEW QUESTION # 19
Why are partitioned tables beneficial in Hive for large datasets?

A. They decrease the security of the data.
B. They ensure that all data is stored in a single file, simplifying access.
C. They allow for faster query processing by scanning only relevant partitions.
D. They automatically encrypt data based on the partition key.

Answer: C

Explanation:
Partitioned tables are beneficial because they allow Hive to perform faster query processing by scanning only the relevant partitions of data rather than the entire dataset. This approach significantly reduces the amount of data read from disk during query execution, improving performance, especially with large datasets.

NEW QUESTION # 20
Your Airflow DAG includes tasks that can potentially fail due to various reasons. How can you handle such failures and ensure the overall workflow continues as intended?

A. Configure the DAG to automatically retry failed tasks a specific number of times.
B. All of the above
C. Utilize Airflow XCom to share information about failed tasks with downstream tasks for alternative processing.
D. Implement custom logic within each task to handle potential errors and retry failed tasks manually.

Answer: A,B

Explanation:
While option A might work for simple cases, it's not efficient for event-driven workflows. Option B highlights the use of Airflow sensors:Airflow Sensors: Allow the DAG to wait for specific conditions (e.g., a file to appear, a specific key in S3) before triggering, ensuring timely execution based on external events or data availability.

NEW QUESTION # 21
Your project involves integrating Spark with a NoSQL database, MongoDB. You need to write a DataFrame 'df into a MongoDB collection named 'orders'. Which PySpark code snippet correctly achieves this?

Answer: C

Explanation:
Option B is correct as it uses the official MongoDB Spark connector C com.mongodb.spark.sql') and specifies the URI correctly, pointing to the MongoDB collection.

NEW QUESTION # 22
When leveraging Spark's DataFrame API for caching, what implicit optimization does Spark perform to enhance processing efficiency?

A. Predicate pushdown and other logical optimizations before physical execution
B. Automatic conversion of all operations to map-reduce jobs
C. Automatic selection of the optimal storage level based on the DataFrame's size
D. Inlining of functions to reduce the overhead of JVM method calls

Answer: A

Explanation:
When leveraging Spark's DataFrame API, Spark performs several implicit optimizations, including predicate pushdown, where it moves filter operations closer to the data source, thereby reducing the amount of data shuffled or moved across the network. This optimization, part of the Catalyst optimizer's logical optimization phase, enhances processing efficiency by minimizing the data processed in subsequent stages of the query.

NEW QUESTION # 23
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CDP-3002 Exam Actual Questions & Exam CDP-3002 Objectives

Hot CDP-3002 Exam Actual Questions | Pass-Sure Cloudera Exam CDP-3002 Objectives: CDP Data Engineer - Certification Exam

Cloudera CDP Data Engineer - Certification Exam Sample Questions (Q18-Q23):

High Pass-Rate CDP-3002 Exam Actual Questions - Pass CDP-3002 Once - Fantastic Exam CDP-3002 Objectives

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