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Hadoop & Big Data Administration

Hadoop & Big Data Administration

hadoop

Course Id: 1024

[wptab name=’About’]

Hadoop is a free, Java-based programming framework that supports the processing of large data sets in a distributed computing environment. It is part of the Apache project sponsored by the Apache Software Foundation. Hadoop is composed of four core components—Hadoop Common, Hadoop Distributed File System (HDFS), MapReduce and YARN.

Hadoop Common
A module containing the utilities that support the other Hadoop components.

MapReduce
A framework for writing applications that process large amounts of structured and unstructured data in parallel across a cluster of thousands of machines, in a reliable, fault-tolerant manner.

HDFS
A file system that provides reliable data storage and access across all the nodes in a Hadoop cluster. It links together the file systems on many local nodes to create a single file system.

Yet Another Resource Negotiator (YARN)
The next-generation MapReduce, which assigns CPU, memory and storage to applications running on a Hadoop cluster. It enables application frameworks other than MapReduce to run on Hadoop, opening up a wealth of possibilities.

Hadoop is supplemented by an ecosystem of Apache open-source projects that extend the value of Hadoop and improve its usability.


 

[/wptab]

[wptab name=’Syllabus’]

Hadoop Course Syllabus


The Case for Apache Hadoop
> Why Hadoop?
> Core Hadoop Components
> Fundamental Concepts
HDFS
> HDFS Features
> Writing and Reading Files
> NameNode Memory Considerations
> Overview of HDFS Security
> Using the Namenode Web UI
> Using the Hadoop File Shell
Getting Data into HDFS
> Ingesting Data from External Sources with
Flume
> Ingesting Data from Relational Databases
with Sqoop
> REST Interfaces
> Best Practices for Importing Data
YARN and MapReduce
> What Is MapReduce?
> Basic MapReduce Concepts
> YARN Cluster Architecture
> Resource Allocation
> Failure Recovery
> Using the YARN Web UI
> MapReduce Version 1
Planning Your Hadoop Cluster
> General Planning Considerations
> Choosing the Right Hardware
> Network Considerations
> Configuring Nodes
> Planning for Cluster Management

Hadoop Installation and Initial
Configuration
> Deployment Types
> Installing Hadoop
> Specifying the Hadoop Configuration
> Performing Initial HDFS Configuration
> Performing Initial YARN and MapReduce
Configuration
> Hadoop Logging
Installing and Configuring Hive, Impala,
and Pig
> Hive
> Impala
> Pig
Hadoop Clients
> What is a Hadoop Client?
> Installing and Configuring Hadoop Clients
> Installing and Configuring Hue
> Hue Authentication and Authorization
Cloudera Manager
> The Motivation for Cloudera Manager
> Cloudera Manager Features
> Express and Enterprise Versions
> Cloudera Manager Topology
> Installing Cloudera Manager
> Installing Hadoop Using Cloudera Manager
> Performing Basic Administration Tasks
Using Cloudera Manager
Advanced Cluster Configuration
> Advanced Configuration Parameters
> Configuring Hadoop Ports
> Explicitly Including and Excluding Hosts
> Configuring HDFS for Rack Awareness
> Configuring HDFS High Availability

Hadoop Security
> Why Hadoop Security Is Important
> Hadoop’s Security System Concepts
> What Kerberos Is and How it Works
> Securing a Hadoop Cluster with Kerberos
Managing and Scheduling Jobs
> Managing Running Jobs
> Scheduling Hadoop Jobs
> Configuring the FairScheduler
> Impala Query Scheduling
Cluster Maintenance
> Checking HDFS Status
> Copying Data Between Clusters
> Adding and Removing Cluster Nodes
> Rebalancing the Cluster
> Cluster Upgrading
Cluster Monitoring and Troubleshooting
> General System Monitoring
> Monitoring Hadoop Clusters
> Common Troubleshooting Hadoop Clusters
> Common Misconfigurations
Conclusion

[/wptab]

[wptab name=’Duration’]

  • Regular classes – 4 weeks
  • Weekend Classes – 6 weeks
  • Customized Fast Track option is available as well. Call 9731012185 now to customize according to your requirement

[/wptab]

[wptab name=’Trainer’]

  • Experienced IT professionals
  • Having hands on practical knowledge
  • With experience of training large batches in both offline and online mode

[/wptab]

[wptab name=’Placement’]

The following services are available on demand as add-on to this course

  • Resume Preparation
  • Mock interviews
  • Job opportunity leads and suggestions

[/wptab]

[wptab name=’Mode’]

  • Online Self Paced Training (SPT) with Videos and Documents
  • Online Instructor Led Training (ILT)

About the course:


Study9 provides a robust job market focused Hadoop training. Our Hadoop course is designed with the right mix of basic and advanced topics to get one started in the domain and enable a person to get a good job in this competitive market. Our Hadoop trainers are experienced professionals with hands on knowledge of Hadoop projects. The Hadoop course content is designed with keeping the current job market’s demands in mind.Our Hadoop training course is value for money and tailor made for our students.

About Study9 Training Method


The Study9 Hadoop training courses are completely online training courses. The online Hadoop training is given using advanced training softwares to make the students comfortable with the online training. The student and teacher can talk over VOIP software, they can share each others screens, share Hadoop course contents and concerns during the class through chat window and even can see each other using Webcams. The time tested proven online Hadoop training methodologies adopted by study9 are of the most advanced ones in India. The student will feel at ease with the Hadoop training mode. And we are so confident on that, we offer a moneyback if the student is not satisfied with first Hadoop Training class.

The cloud based Hadoop training course contents are accessible from anywhere in the world. Study9 provides access for each student to an online Learning Management System that holds all the slides and videos that are part of the Hadoop training courses. The students can access them from their Laptop, Mobile, Tablets etc. The students will also give Hadoop training exams on this Learning Management System and our expert Hadoop trainers will rate their papers and provide certifications on successful completion of these Hadoop training exams.

The best part of this online Hadoop training approach is that it does not require one to waste time by travelling to a particular Hadoop training center. And the timings are flexible so that if someday the student has problems in taking the morning Hadoop training class he/she can fix an alternate time in the evening in discussion with Hadoop trainer. On need basis our Hadoop trainers can take a class in late night as well. On request basis missed Hadoop training class sessions can even be given as video lectures to the student for them to go through to be prepared for the next class.

[/wptab]

[wptab name=’Cost’]

[/wptab]
[wptab name=’Register’]

Schedule: Weekdays (1 hr /day), Weekends (2.5 hrs /day)  and Fast Track options available
[/wptab]

[end_wptabset]


 

 

 

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