Cloudera CDP-3002 Exam Questions - Guaranteed Success

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Cloudera CDP Data Engineer - Certification Exam Sample Questions (Q86-Q91):

NEW QUESTION # 86
You want to track changes to an Iceberg table over time for auditing purposes. Which combination of Iceberg features would best support this?

A. Metadata tables and time travel
B. Snapshots and partition evolution
C. Snapshots and manifest lists
D. Hidden partitioning and Iceberg audit logs

Answer: A

Explanation:
C). The REMOVE ORPHAN FILES procedure is specifically designed to identify and remove files that are no longer referenced in the Iceberg metadata, which often occurs due to corruption.

NEW QUESTION # 87
What are the potential consequences of persisting all intermediate RDDs in Spark with the MEMORY ONLY storage level?

A. Improved performance due to faster data access
B. Increased risk of application crashes due to memory exhaustion
C. All intermediate data will be automatically persisted to disk
D. No impact on the application, as Spark manages memory efficiently

Answer: B

Explanation:
While MEMORY_ONLY provides faster access, persisting all data in memory can lead to memory exhaustion B, potentially causing application crashes. Spark manages memory, but it's essential to consider available memory and data size when choosing the storage level.

NEW QUESTION # 88
What impact does the Spark configuration parameter spark.network.timeout have on Spark streaming applications?

A. It determines the timeout for connections between executors and the Spark driver, impacting task retries and executor loss detection.
B. It sets the timeout for Akka-based network operations, crucial for Spark streaming's stability.
C. It controls the maximum time a Spark streaming application will wait for data before timing out.
D. It specifies the timeout for network operations such as data shuffle and broadcast.

Answer: A

Explanation:
The spark.network.timeout configuration parameter specifies the timeout for network operations, including connections between executors and the Spark driver. It is crucial for detecting network issues, executor loss, and for controlling task retries in a distributed environment. This setting is particularly important in Spark streaming applications where maintaining a stable connection and promptly detecting failures is essential for continuous data processing. Options A and C describe aspects of network operations but do not capture the full scope of this parameter's impact on streaming applications. Option B is misleading as it suggests a direct control over data waiting time, which is not the primary purpose of this parameter.

NEW QUESTION # 89
What is the impact of query vectorization in Cloudera's Optimization Framework?

A. It enables the execution of SQL commands
B. It improves query performance by processing batches of rows together
C. It slows down query execution by adding complexity
D. It encrypts query results for security

Answer: B

Explanation:
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

NEW QUESTION # 90
You want to write the results of a Spark DataFrame operation to a Parquet file for efficient storage and retrieval. What approach can you achieve this efficiently?

A. Use Spark SQL's CREATE TABLE statement with the Parquet format specified
B. Use the DataFrame.write.text() method and specify the output format as Parquet
C. Convert the DataFrame to a temporary table and then use HiveQL commands to write to Parquet
D. Leverage the DataFrame.write.parquet() method with appropriate options

Answer: D

Explanation:
While text files A are not efficient for Parquet, option B involves unnecessary steps. Spark DataFrames provide a dedicated method write.parquet() C for efficient Parquet file generation. Option D is mainly used for creating Hive tables, not DataFrames within Spark.

NEW QUESTION # 91
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Cloudera CDP-3002 Exam Questions - Guaranteed Success

100% Pass CDP-3002 - Perfect CDP Data Engineer - Certification Exam Practice Braindumps

Cloudera CDP Data Engineer - Certification Exam Sample Questions (Q86-Q91):

2025 Cloudera Efficient CDP-3002 Practice Braindumps

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