最新的Cloudera Certification認證 CDP-3002考試題庫

問題1

How does Apache NiFi support schema inference during data flow management?

A. Through processors that automatically detect data formats and schemas

B. By enforcing static schemas for all data flows

C. By manually specifying schemas for each data source

D. Utilizing external schema repositories exclusively for schema management

正確答案: A

說明：（僅 VCESoft 成員可見）

問題2

Which tool or API is primarily used for monitoring and inspecting the performance of Spark applications in real-time?
A Spark History Server

A. Spark Web UI

B. Apache Ambari

C. Hadoop YARN ResourceManager UI

正確答案: C

說明：（僅 VCESoft 成員可見）

問題3

When creating a data pipeline in the Cloudera Data Engineering service, what is the primary file format used to define the pipeline steps and configuration?

A. YAML

B. Shell script

C. JSON

D. Python script

正確答案: A

說明：（僅 VCESoft 成員可見）

問題4

You're given a DataFrame containing information about flights, including columns "origin", "destination", and "delay_minutes". How can you find the top 5 origin airports with the most delayed flights on average?

A. Use Spark's machine learning library (MLIiB. for ranking and classification

B. Use groupBy and avg on "delay_minutes", then sort by the average in descending order and limit to top 5

C. Implement a custom function to calculate average delays for each origin and then sort and filter

D. Leverage Spark SQL's RANK function along with windowing to identify top 5 origins

正確答案: B

說明：（僅 VCESoft 成員可見）

問題5

In a PySpark application running on Kubernetes, you want to enable dynamic allocation of Executors. Which configuration setting is essential to turn on this feature?

A. 'spark.kubernetes.executor.dynamicAllocation'

B. 'spark.dynamicAllocation.enabled'

C. 'spark.kubernetes.dynamicAllocation.enabled'

D. 'spark.executor.instances'

正確答案: B

說明：（僅 VCESoft 成員可見）

問題6

When configuring a Spark job to run on Kubernetes within the Cloudera Data Engineering (CDE. service, which property is crucial for specifying the Docker image to be used by the executors?

A. spark.cde.container.image

B. spark.kubernetes.executor.container.image

C. spark.executor.image

D. spark.kubernetes.container.image

正確答案: B

說明：（僅 VCESoft 成員可見）

問題7

You encounter an error during the execution of your Airflow DAG. How can you identify the root cause of the issue and debug it effectively?

A. All of the above

B. Rely on the error message displayed on the Airflow UI, even if it's generic.

C. Inspect the code of failed tasks directly within the Airflow web Ul for potential issues.

D. Utilize Airflow logs (scheduler, worker) to analyze detailed error messages and stack traces.

正確答案: A

說明：（僅 VCESoft 成員可見）

問題8

You're working with an Airflow DAG that performs data quality checks on sensitive dat a. How can you ensure data security during the checks?

A. Implement data masking techniques to obfuscate sensitive information during the checks.

B. All of the above

C. Store sensitive data like thresholds and comparison values directly within the DAG code.

D. Utilize environment variables to store sensitive data and access them within the PythonOperator.

正確答案: A,D

問題9

You are deploying a Spark application in a Kubernetes environment. Your application is designed to process large datasets using Spark's data frame API. You have created a Docker image for your Spark application. Which of the following 'kubectl* commands should you use to deploy your Spark application onto the Kubernetes cluster?

A. 'kubectl expose deployment my-spark-app --type=LoadBalancer -port=808ff

B. 'kubectl create deployment my-spark-app --image=my-spark-app-image'

C. *kubectl apply -f spark-app.yamr

D. *kubectl config set-context -current -namespace=my-spark-app'

正確答案: C

說明：（僅 VCESoft 成員可見）

問題10

Your Airflow DAG encounters an error during the data transformation stage. What information can you access in the Airflow UI to troubleshoot the issue?

A. You need to manually inspect the code for potential issues.

B. The Airflow web server logs might contain relevant information about the error.

C. All of the above

D. The DAG run details page displays the task logs, providing insights into the specific error encountered.

正確答案: C

說明：（僅 VCESoft 成員可見）

問題11

When analyzing an Explain Plan, what does the presence of a large number of "Nested Loop Joins" indicate about a query's potential performance?

A. It suggests that the query is fully optimized for distributed execution

B. It guarantees optimal performance for all dataset sizes

C. It may indicate potential performance issues for large datasets due to the high computational cost

D. It implies that the data is perfectly partitioned for the query

正確答案: C

說明：（僅 VCESoft 成員可見）

問題12

You notice a significant performance overhead when persisting a large RDD to disk. What potential factors could contribute to this, and how can you mitigate them?

A. Inefficient serialization format for the RDD data

B. Insufficient disk space on the cluster nodes

C. All of the above

D. Using HDFS as the storage location instead of local disks

正確答案: C

說明：（僅 VCESoft 成員可見）

問題13

Which operator or feature in Apache Airflow can be used to dynamically adjust the schedule of data quality checks based on the volume of incoming data?

A. A custom PythonOperator that modifies the DAG's schedule interval

B. The ExternalTaskSensor to trigger data quality checks based on external events

C. The Scheduler component with dynamic DAG generation

D. The BranchPythonOperator to choose between different scheduling paths

正確答案: C

說明：（僅 VCESoft 成員可見）

問題14

How can you leverage Spark Streaming for real-time data processing and analytics?

A. Both A and B.

B. By implementing custom logic for data ingestion, transformation, and output.

C. By utilizing Structured Streaming with Kafka as the source and sink.

D. By defining a streaming DataFrame with a window function.

正確答案: A

說明：（僅 VCESoft 成員可見）

問題15

What command and parameters should be used to update an existing Spark job in the Cloudera Data Engineering (CDE. service to increase its executor memory using the CDE CLI?

A. cde spark submit -update -name my-spark-job -executor-memory 6G

B. cde job update -name my-spark-job --conf spark.executor.memory=6g

C. cde job config -name my-spark-job -set spark.executor.memory=6g

D. cde job run -edit my-spark-job -conf spark.executor.memory=6g

正確答案: B

說明：（僅 VCESoft 成員可見）

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