CDH

Cloudera Certified Administrator for Apache hadoop (CCA-500)
Number of Questions: 60 questions
Time Limit: 90 minutes
Passing Score: 70%
Language: English, Japanese
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 and MapReduce version 2 (MRv2) (17%)
•        Understand how upgrading a cluster from Hadoop 1 to Hadoop 2 affects cluster settings
•        Understand how to deploy MapReduce v2 (MRv2 / YARN), including all YARN daemons
•        Understand basic design strategy for MapReduce v2 (MRv2)
•        Determine how YARN handles resource allocations
•        Identify the workflow of MapReduce 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