Cloudera hadoop certification

4/11/2015 Cloudera Hadoop Certification | Hadoop Online Training
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Certifications Exams from Cloudera,
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Terminology.
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CCD-410 Cloudera Certified Developer for
Apache Hadoop (CCDH)
CCB-400 Cloudera Certified Specialist in
Apache HBase
CCA-500 Cloudera Certified Administrator for
Apache Hadoop (CCAH)
CCA-505 Cloudera Certified Administrator for
Apache Hadoop (CCAH) CDH5 Upgrade Exam
Exam Code: CCD-410
Individuals who achieve Cloudera Certified Developer
for Apache Hadoop (CCDH) accreditation have
demonstrated their technical knowledge, skill, and
ability to write, maintain, and optimize Apache Hadoop
Cloudera Certified Developer for Apache
Hadoop (CCDH)
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Exam Code: CCD-410
Number of Questions: 50 - 55 live questions
Time Limit: 90 minutes
Passing Score: 70%
Language: English, Japanese
Price: USD $295, AUD $300, EUR €215, GBP £185, JPY
¥28,500
Hands-On Hadoop
Through instructor-led discussion and interactive,
hands-on exercises, participants will navigate the
Hadoop ecosystem, learning topics such as:
The internals of MapReduce and HDFS and
how to write MapReduce code
Best practices for Hadoop development,
debugging, and implementation of
workflows and common algorithms
How to leverage Hive, Pig, Sqoop, Flume,
Oozie, and other Hadoop ecosystem
projects
Creating custom components such as
WritableComparables and InputFormats to
manage complex data types
Writing and executing joins to link data sets
in MapReduce
Advanced Hadoop API topics required for
real-world data analysis
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Hadoop Content or Topics
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Cloudera Certified Administrator for Apache Hadoop
(CCAH)
Individuals who achieve Cloudera Certified
Administrator for Apache Hadoop (CCAH) accreditation
have demonstrated their technical knowledge, skill,
and ability to configure, deploy, maintain, and secure
an Apache Hadoop cluster.
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CCAH CDH 5 Exam
Audience: Administrators who want to certify on CDH 5
Exam Code: CCA-500
Number of Questions: 60 questions
Passing Score: 70%
Language: English, Japanese (forthcoming)
¥28,500
CCAH CDH 5 Upgrade Exam
Audience: Cloudera Certified Administrators who want
to upgrade their certification from a previous version
of CDH to CDH 5
Exam Code: CCA-505
Passing Score: 70%
Language: English, Japanese (forthcoming)
¥12,500
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
Environment,Hadoop File
sys...
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Describe file read and write paths
Identify the commands to manipulate files
in the Hadoop File System Shell
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.
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
2. YARN and MapReduce version 2 (MRv2) (17%)
3. Hadoop Cluster Planning (16%)
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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
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
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
4. Hadoop Cluster Installation and Administration (25%)
5. Resource Management (10%)
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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
Download Cloudera Administrator Training for Apache
Hadoop Topics
Know the Methods Used by HBase Specialists
Individuals who achieve Cloudera Certified Specialist in
Apache HBase (CCSHB) accreditation have
demonstrated their technical knowledge, skill, and
ability working with Apache HBase.
Exam Code: CCB-400
Passing Score: 69%
Language: English, Japanese
¥28,500
Download Cloudera Training for Apache HBase Topics
The use cases and usage occasions for
HBase, Hadoop, and RDBMS
6. Monitoring and Logging (15%)
Cloudera Certified Specialist in Apache HBase
(CCSHB)
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Using the HBase shell to directly manipulate
HBase tables
Designing optimal HBase schemas for
efficient data storage and recovery
How to connect to HBase using the Java API,
configure the HBase cluster, and administer
an HBase cluster
Best practices for identifying and resolving
performance bottlenecks
Main Topics:
Core HBase Concepts
Recognize the fundamental characteristics of Apache
HBase and its role in a big data ecosystem. Identify
differences between Apache HBase and a traditional
RDBMS. Describe the relationship between Apache
HBase and HDFS. Given a scenario, identify application
characteristics that make the scenario an appropriate
application for Apache HBase.
Data Model
Describe how an Apache HBase table is physically
stored on disk. Identify the differences between a
Column Family and a Column Qualifier. Given a data
loading scenario, identify how Apache HBase will
version the rows. Describe how Apache HBase cells
store data. Detail what happens to data when it is
deleted.
Architecture
Identify the major components of an Apache HBase
cluster. Recognize how regions work and their benefits
under various scenarios. Describe how a client finds a
row in an HBase table. Understand the function and
purpose of minor and major compactions. Given a
region server crash scenario, describe how Apache
HBase fails over to another region server. Describe
RegionServer splits.
Schema Design
Describe the factors to be considered with creating
Column Families. Given an access pattern, define the
row keys for optimal read performance. Given an
access pattern, define the row keys for locality.

API
Describe the functions and purpose of the
HBaseAdmin class. Given a table and rowkey, use the
get() operation to return specific versions of that row.
Describe the behavior of the checkAndPut() method.
Administration
Recognize how to create, describe, and access data in
tables from the shell. Describe how to bulk load data
into Apache HBase. Recognize the benefits of managed
region splits.
Prove Your Expertise at the Highest Level
Required Exams
DS700 - Descriptive and Inferential Statistic
DS701 - Unsupervised Machine Learning
DS702 - Supervised Machine Learning
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report that informs you of your overall score and
how you scored on each section of the test. From
this score report, you will know which areas of the
test you need to study before scheduling to take
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Cloudera hadoop certification

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Cloudera hadoop certification