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CCA-500 PDF + Testing Engine



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  • Exam Name: Cloudera Certified Administrator for Apache Hadoop (CCAH)
  • Last Update: 08-Dec-2023
  • Questions and Answers: 60
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CCA-500 Questions and Answers

Question # 1

You are running a Hadoop cluster with a NameNode on host mynamenode. What are two ways to determine available HDFS space in your cluster?


Run hdfs fs –du / and locate the DFS Remaining value


Run hdfs dfsadmin –report and locate the DFS Remaining value


Run hdfs dfs / and subtract NDFS Used from configured Capacity


Connect to http://mynamenode:50070/dfshealth.jsp and locate the DFS remaining value

Question # 2

Which three basic configuration parameters must you set to migrate your cluster from MapReduce 1 (MRv1) to MapReduce V2 (MRv2)? (Choose three)


Configure the NodeManager to enable MapReduce services on YARN by setting the following property in yarn-site.xml:




Configure the NodeManager hostname and enable node services on YARN by setting the following property in yarn-site.xml:




Configure a default scheduler to run on YARN by setting the following property in mapred-site.xml:




Configure the number of map tasks per jon YARN by setting the following property in mapred:




Configure the ResourceManager hostname and enable node services on YARN by setting the following property in yarn-site.xml:




Configure MapReduce as a Framework running on YARN by setting the following property in mapred-site.xml:


Question # 3

You are migrating a cluster from MApReduce version 1 (MRv1) to MapReduce version 2 (MRv2) on YARN. You want to maintain your MRv1 TaskTracker slot capacities when you migrate. What should you do/


Configure yarn.applicationmaster.resource.memory-mb and yarn.applicationmaster.resource.cpu-vcores so that ApplicationMaster container allocations match the capacity you require.


You don’t need to configure or balance these properties in YARN as YARN dynamically balances resource management capabilities on your cluster


Configure and mapred.tasktracker.reduce.tasks.maximum ub yarn-site.xml to match your cluster’s capacity set by the yarn-scheduler.minimum-allocation


Configure yarn.nodemanager.resource.memory-mb and yarn.nodemanager.resource.cpu-vcores to match the capacity you require under YARN for each NodeManager

Question # 4

A user comes to you, complaining that when she attempts to submit a Hadoop job, it fails. There is a Directory in HDFS named /data/input. The Jar is named j.jar, and the driver class is named DriverClass.

She runs the command:

Hadoop jar j.jar DriverClass /data/input/data/output

The error message returned includes the line:

PriviligedActionException as:training (auth:SIMPLE) cause:org.apache.hadoop.mapreduce.lib.input.invalidInputException:

Input path does not exist: file:/data/input

What is the cause of the error?


The user is not authorized to run the job on the cluster


The output directory already exists


The name of the driver has been spelled incorrectly on the command line


The directory name is misspelled in HDFS


The Hadoop configuration files on the client do not point to the cluster

Question # 5

Your cluster is configured with HDFS and MapReduce version 2 (MRv2) on YARN. What is the result when you execute: hadoop jar SampleJar MyClass on a client machine?


SampleJar.Jar is sent to the ApplicationMaster which allocates a container for SampleJar.Jar


Sample.jar is placed in a temporary directory in HDFS


SampleJar.jar is sent directly to the ResourceManager


SampleJar.jar is serialized into an XML file which is submitted to the ApplicatoionMaster

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