CCA500 (Multiple Choice) Exam has been retired by Cloudera. It has been replaced by their CCA131 : CCA Administrator Exam . HadoopExam is in process of creating material for this certification exam and will be launched around 15th of August. Hence, please subscribe here to get the Alert for this material release. However, CCA500 material will always be available to buy in case you want to learn or test your skills.
200 Practice Questions for Cloudera CDH5 (CCA500 & CCA505) Certification Practice Questions + Revision Notes of 28 PagesCCA-500 and CCA-505 Certification Simulator Just Reading the Book and online material is not enough to clear Hadoop Administrator Certification. At some point you are going to have to ask yourself: "Am I ready to take the Hadoop Certification Exam?" Here is the secret to answering this question and passing the exam on your first try: Practice - practice - practice! The Hadoop Exam Simulator offers you the opportunity to take 4 sample Hadoop Exams before heading out for the real thing. Be ready to succeed on exam day!
Bullet Points How Practice Questions are updated (Never Outdated) 1. Almost all questions are covered from Hadoop Admin actual exam question pools (Similar or Same Questions). 2. Our expert regularly update the questions as per the real exam. 3. All Practice Questions are included. 4. Always updated and correct/incorrect answers explanation 5. Record of 100% success ratio. 6. All possible exam questions are included in 200 Practice questions, so you would easily clear the exam in first attempt 7. Best revision notes (You will nowhere find it), revise whole syllabus in just 2 Hrs.
Exhaustive explanation to all required questions
Benefits/Features
Note : This product is tested only on Windows Operating System Tag
:
Cloudera Administrator
exam CCA500 and CCA500 Dumps |
CCA–500 and 505 Exam Sections and Blueprint
Notes: Hadoop ecosystem items are no longer treated separately as their own section and are integrated throughout the exam. Both CCA–500 and CCA–505 share the same proportion of items per section.
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
Practice... Practice .. Practice ...
_______________________________________________________________________________________________________________________
Click to View What Learners Say about us : Testimonials
We have training subscriber from TCS, IBM, INFOSYS, ACCENTURE, APPLE, HEWITT, Oracle , NetApp , Capgemini etc.