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Cloudera CCA175 Exam Dumps

Certification Exams

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Number Of Questions

96

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Description

Status: RETIRED
Exam Name: CCA Spark and Hadoop Developer
Exam Code: CCA175
Related Certification(s): Cloudera Certified Associate Certification
Certification Provider: Cloudera
Number of CCA175 practice questions in our database: 96 
Expected CCA175 Exam Topics, as suggested by Cloudera :

  • Module 1: Understand the fundamentals of querying datasets in Spark/ Write the results back into HDFS using Spark
  • Module 2: Write queries that calculate aggregate statistics/ Load data from HDFS for use in Spark applications
  • Module 3: Use meta store tables as an input source or an output sink for Spark applications/ Filter data using Spark
  • Module 4: Generate reports by using queries against loaded data/ Produce ranked or sorted data
  • Module 5: Perform standard extract, transform, load (ETL) processes on data using the Spark API/ Join disparate datasets using Spark
  • Module 6: Use Spark SQL to interact with the meta store programmatically in your applications/ Read and write files in a variety of file formats

Description

Status: RETIRED
Exam Name: CCA Spark and Hadoop Developer
Exam Code: CCA175
Related Certification(s): Cloudera Certified Associate Certification
Certification Provider: Cloudera
Number of CCA175 practice questions in our database: 96 
Expected CCA175 Exam Topics, as suggested by Cloudera :

  • Module 1: Understand the fundamentals of querying datasets in Spark/ Write the results back into HDFS using Spark
  • Module 2: Write queries that calculate aggregate statistics/ Load data from HDFS for use in Spark applications
  • Module 3: Use meta store tables as an input source or an output sink for Spark applications/ Filter data using Spark
  • Module 4: Generate reports by using queries against loaded data/ Produce ranked or sorted data
  • Module 5: Perform standard extract, transform, load (ETL) processes on data using the Spark API/ Join disparate datasets using Spark
  • Module 6: Use Spark SQL to interact with the meta store programmatically in your applications/ Read and write files in a variety of file formats

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Q1. Problem Scenario 96 : Your spark application required extra Java options as below. -XX:+PrintGCDetails-XX:+PrintGCTimeStamps Please replace the XXX values correctly ./bin/spark-submit --name "My app" --master local[4] --conf spark.eventLog.enabled=talse --conf XXX hadoopexam.jar

A.Solution XXX: Mspark.executoi\extraJavaOptions=-XX:+PrintGCDetails -XX:+PrintGCTimeStamps' Notes: ./bin/spark-submit \ --class --master \ --deploy-mode \ -conf = \ ... # other options \ [application-arguments] Here, conf is used to pass the Spark related contigs which are required for the application to run like any specific property(executor memory) or if you want to override the default property which is set in Spark-default.conf.

B. Solution XXX: Mspark.executoi\extraJavaOptions=-XX:+PrintGCDetails -XX:+PrintGCTimeStamps' Notes: ./bin/spark-submit \ \ [application-arguments] Here, conf is used to pass the Spark related contigs which are required for the application to run like any specific property(executor memory) or if you want to override the default property which is set in Spark-default.conf.

Correct Answer: A

Q2. Problem Scenario 94 : You have to run your Spark application on yarn with each executor 20GB and number of executors should be 50.Please replace XXX, YYY, ZZZ export HADOOP_CONF_DIR=XXX ./bin/spark-submit \ -class com.hadoopexam.MyTask \ xxx\ -deploy-mode cluster \ # can be client for client mode YYY\ 222 \ /path/to/hadoopexam.jar \ 1000

A.Solution XXX: -master yarn YYY : -executor-memory 20G ZZZ: -num-executors 50

B. Solution XXX: -master yarn YYY : -executor-memory 40G ZZZ: -num-executors 80

Correct Answer: A

Q3. Problem Scenario 92 : You have been given a spark scala application, which is bundled in jar named hadoopexam.jar. Your application class name is com.hadoopexam.MyTask You want that while submitting your application should launch a driver on one of the cluster node. Please complete the following command to submit the application. spark-submit XXX -master yarn \ YYY SSPARK HOME/lib/hadoopexam.jar 10

A.Solution XXX: -class com.hadoopexam.MyTask

B. Solution XXX: -class com.hadoopexam.MyTask YYY : --deploy-mode cluster

Correct Answer: B

Q4. Problem Scenario 94 : You have to run your Spark application on yarn with each executor 20GB and number of executors should be 50.Please replace XXX, YYY, ZZZ export HADOOP_CONF_DIR=XXX ./bin/spark-submit \ -class com.hadoopexam.MyTask \ xxx\ -deploy-mode cluster \ # can be client for client mode YYY\ 222 \ /path/to/hadoopexam.jar \ 1000

A.Solution XXX: -master yarn YYY : -executor-memory 20G ZZZ: -num-executors 50

B. Solution XXX: -master yarn YYY : -executor-memory 40G ZZZ: -num-executors 80

Correct Answer: A

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