Setup Hadoop in distributed mode

This tutorial explains How to Setup and configure Hadoop on Multiple machines, i.e. Installation of Hadoop in Distributed Mode. In the cluster setup there is one master and 2 slaves will be configured. During the deployment all the pre-requisites will be installed. Hadoop installation is done on Amazon cloud (AWS).
Follow following video tutorial for the installation and configuration of Hadoop 1 in distributed mode  (real cluster mode)on Amazon Cloud:

In this video following topics has been covered:
 - Installation and configuration of Hadoop 1.x or Cloudera CDH3Ux in Distributed mode (on multiple node cluster).
 - Launch 3 instances on AWS (Amazon Cloud), on which we will setup the real cluster. One instance will act as Master and rest all the instances will act as slaves.
 - Prerequisites for hadoop Installation.
   -- Installation of Java.
   -- Setup of password-less ssh.
 - Important configurations properties.
 - Setup Configuration in core-site.xml, hdfs-site.xml, map-red-site.xml.
 - Format name-node.
 - Start hadoop services: NameNode, DataNode, secondary-namenode, JobTracker, TaskTracker.
 - Setup environment variables for  Hadoop,
 - Submit Map-Reduce Job.

Big Data Training First Session - Hadoop Training First Class Recording

This video covers: 
 - Introduction to Big Data
 - What is the need of Big Data
 - Essence of Big Data
 - 4Vs of Big Data Volume, Velocity, Variety, Veracity
 - Problems with conventional systems like RDBMS and OS file-system
 - Introduction to Hadoop
 - Introduction to HDFS
 - Introduction to MapReduce
 - Real life Big Data use cases
 - Future of Big Data & Hadoop
 - Careers in Big Data & Hadoop
 - Job Roles in Big Data & Hadoop like: Hadoop Analyst, Hadoop Developer, Hadoop Admin, etc.
 - How DataFlair will help you in making your career in Big Data.



About Big Data - Hadoop Training Course:
An online course designed by Hadoop Experts to provide in-depth knowledge and practical skills in the field of Big Data and Hadoop to make you successful Big Data and Hadoop Developer.

Big Data and Hadoop training course is designed to provide knowledge and skills to make you employable in Big Data industry. In-depth knowledge of concepts such as Hadoop Distributed File System, Map-Reduce, Hadoop Cluster- Single and multi node, Hadoop 2.0, Flume, Sqoop, PIG, Hive, Hbase, Zookeeper, Oozie etc. will be covered in the course.


Course Objectives:
After the completion of the ‘Big Data and Hadoop’ Course you should be able to:

1. Master the concepts of Hadoop Distributed File System and MapReduce framework
2. Setup a Hadoop on single and multi node Cluster
3. Understand Data Loading Techniques using Sqoop and Flume
4. Program in MapReduce (Both MRv1 and MRv2)
5. Learn to write Complex MapReduce programs
6. Program in YARN (MRv2)
7. Perform Data Analytics using Pig and Hive
8. Implement HBase, MapReduce Integration, Advanced Usage and Advanced Indexing
9. Have a good understanding of ZooKeeper service
10. New features in Hadoop 2.0 — YARN, HDFS Federation, NameNode High Availability
11. Implement best Practices for Hadoop Development and Debugging
12. Implement a Hadoop Project
13. Work on a Real Life Project on Big Data Analytics and gain Hands on Project Experience

Please contact us for more details: 
http://data-flair.com/
http://data-flair.com/course/big-data-and-hadoop/
Email us: info@data-flair.com
Phone: +91-8451097879

Deep Dive into Map-Reduce Data Flow | Big Data Training

This video covers: Basics of MapReduce, DataFlow in MapReduce, Basics of Input Split, Mapper, Intermediate output, Data Shuffling, Principle behind Shuffling, Reducer, Wordcount in Map-Reduce, etc.




About Big Data - Hadoop Training Course:
An online course designed by Hadoop Experts to provide indepth knowledge and practical skills in the field of Big Data and Hadoop to make you successful Hadoop Developer.

Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Hadoop Cluster- Single and multi node, Hadoop 2.0, Flume, Sqoop, Map-Reduce, PIG, Hive, Hbase, Zookeeper, Oozie etc. will be covered in the course.


Course Objectives:

After the completion of the ‘Big Data and Hadoop’ Course you should be able to:

1. Master the concepts of Hadoop Distributed File System and MapReduce framework
2. Setup a Hadoop on single and multi node Cluster
3. Understand Data Loading Techniques using Sqoop and Flume
4. Program in MapReduce (Both MRv1 and MRv2)
5. Learn to write Complex MapReduce programs
6. Program in YARN (MRv2)
7. Perform Data Analytics using Pig and Hive
8. Implement HBase, MapReduce Integration, Advanced Usage and Advanced Indexing
9. Have a good understanding of ZooKeeper service
10. New features in Hadoop 2.0 — YARN, HDFS Federation, NameNode High Availability
11. Implement best Practices for Hadoop Development and Debugging
12. Implement a Hadoop Project
13. Work on a Real Life Project on Big Data Analytics and gain Hands on Project Experience

Please contact us for more details: info@data-flair.com, +91-8451097879.