A Cloudera Certified Administrator for Apache Hadoop (CCAH) certification proves that you have demonstrated your technical knowledge, skills, and ability to configure, deploy, maintain, and secure an Apache Hadoop cluster.
Cloudera Certified Administrator for Apache Hadoop (CCA-500)
Number of Questions: 60 questions
Time Limit: 90 minutes
Passing Score: 70%
Language: English, Japanese
Price: NOT AVAILABLE
Exam Sections and Blueprint
1. HDFS (17%)
Describe the function of HDFS daemons
Describe the normal operation of an Apache Hadoop cluster, both in data storage and in data processing
Identify current features of computing systems that motivate a system like Apache Hadoop
Classify major goals of HDFS Design
Given a scenario, identify appropriate use case for HDFS Federation
Identify components and daemon of an HDFS HA-Quorum cluster
Analyze the role of HDFS security (Kerberos)
Determine the best data serialization choice for a given scenario
Describe file read and write paths
Identify the commands to manipulate files in the Hadoop File System Shell
2. YARN (17%)
Understand how to deploy core ecosystem components, including Spark, Impala, and Hive
Understand how to deploy MapReduce v2 (MRv2 / YARN), including all YARN daemons
Understand basic design strategy for YARN and Hadoop
Determine how YARN handles resource allocations
Identify the workflow of job running on YARN
Determine which files you must change and how in order to migrate a cluster from MapReduce version 1 (MRv1) to MapReduce version 2 (MRv2) running on YARN
3. Hadoop Cluster Planning (16%)
Principal points to consider in choosing the hardware and operating systems to host an Apache Hadoop cluster
Analyze the choices in selecting an OS
Understand kernel tuning and disk swapping
Given a scenario and workload pattern, identify a hardware configuration appropriate to the scenario
Given a scenario, determine the ecosystem components your cluster needs to run in order to fulfill the SLA
Cluster sizing: given a scenario and frequency of execution, identify the specifics for the workload, including CPU, memory, storage, disk I/O
Disk Sizing and Configuration, including JBOD versus RAID, SANs, virtualization, and disk sizing requirements in a cluster
Network Topologies: understand network usage in Hadoop (for both HDFS and MapReduce) and propose or identify key network design components for a given scenario
4. Hadoop Cluster Installation and Administration (25%)
Given a scenario, identify how the cluster will handle disk and machine failures
Analyze a logging configuration and logging configuration file format
Understand the basics of Hadoop metrics and cluster health monitoring
Identify the function and purpose of available tools for cluster monitoring
Be able to install all the ecoystme components in CDH 5, including (but not limited to): Impala, Flume, Oozie, Hue, Cloudera Manager, Sqoop, Hive, and Pig
Identify the function and purpose of available tools for managing the Apache Hadoop file system
5. Resource Management (10%)
Understand the overall design goals of each of Hadoop schedulers
Given a scenario, determine how the FIFO Scheduler allocates cluster resources
Given a scenario, determine how the Fair Scheduler allocates cluster resources under YARN
Given a scenario, determine how the Capacity Scheduler allocates cluster resources
6. Monitoring and Logging (15%)
Understand the functions and features of Hadoop’s metric collection abilities
Analyze the NameNode and JobTracker Web UIs
Understand how to monitor cluster daemons
Identify and monitor CPU usage on master nodes
Describe how to monitor swap and memory allocation on all nodes
Identify how to view and manage Hadoop’s log files
Interpret a log file
Disclaimer: These exam preparation pages are intended to provide information about the objectives covered by each exam, related resources, and recommended reading and courses. The material contained within these pages is not intended to guarantee a passing score on any exam. Cloudera recommends that a candidate thoroughly understand the objectives for each exam and utilize the resources and training courses recommended on these pages to gain a thorough understand of the domain of knowledge related to the role the exam evaluates..
QUESTION 1
You have installed a cluster running HDFS and MapReduce version 2 (MRv2) on YARN. You have
no afs.hosts entry()ies in your hdfs-alte.xml configuration file. You configure a new worker node by
setting fs.default.name in its configuration files to point to the NameNode on your cluster, and you
start the DataNode daemon on that worker node.
What do you have to do on the cluster to allow the worker node to join, and start storing HDFS blocks?
A. Nothing; the worker node will automatically join the cluster when the DataNode daemon is started.
B. Without creating a dfs.hosts file or making any entries, run the command hadoop dfsadmin –refreshHadoop on the NameNode
C. Create a dfs.hosts file on the NameNode, add the worker node’s name to it, then issue the command hadoop dfsadmin –refreshNodes on the NameNode
D. Restart the NameNode
Answer: D
QUESTION 2
Assuming a cluster running HDFS, MapReduce version 2 (MRv2) on YARN with all settings at
their default, what do you need to do when adding a new slave node to a cluster?
A. Nothing, other than ensuring that DNS (or /etc/hosts files on all machines) contains am entry for the new node.
B. Restart the NameNode and ResourceManager deamons and resubmit any running jobs
C. Increase the value of dfs.number.of.needs in hdfs-site.xml
D. Add a new entry to /etc/nodes on the NameNode host.
E. Restart the NameNode daemon.
Answer: B
QUESTION 3
You have a 20 node Hadoop cluster, with 18 slave nodes and 2 master nodes running HDFS High
Availability (HA). You want to minimize the chance of data loss in you cluster. What should you do?
A. Add another master node to increase the number of nodes running the JournalNode which increases the number of machines available to HA to create a quorum
B. Configure the cluster’s disk drives with an appropriate fault tolerant RAID level
C. Run the ResourceManager on a different master from the NameNode in the order to load share HDFS metadata processing
D. Run a Secondary NameNode on a different master from the NameNode in order to load provide automatic recovery from a NameNode failure
E. Set an HDFS replication factor that provides data redundancy, protecting against failure
Answer: C
QUESTION 4
You decide to create a cluster which runs HDFS in High Availability mode with automatic failover, using Quorum-based Storage. What is the purpose of ZooKeeper in such a configuration?
A. It manages the Edits file, which is a log changes to the HDFS filesystem.
B. It monitors an NFS mount point and reports if the mount point disappears
C. It both keeps track of which NameNode is Active at any given time, and manages the Edits file, which is a log of changes to the HDFS filesystem
D. It only keeps track of which NameNode is Active at any given time
E. Clients connect toZoneKeeper to determine which NameNode is Active
Answer: D
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