Opportunities in Big Data Hadoop

Watch the exclusive recording of Big Data Session conducted By DataFlair

Are you Ready to Migrate your Career in the Latest upcoming Technology Big Data

Visit: http://data-flair.com/course/big-data-and-hadoop-training/

How Big Data is the Biggest Buzz Word

What is Big Data

Big data is a buzzword, or catch-phrase, used to describe a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques.

What leaders say About Big Data:

Big Data is the new Oil
 - Gartner

Hadoop will grow at CAGR of 58%, will reach $50 billion by 2020

 - Experfy

Big Data market will be growing 6 times faster than the overall IT market

 - IDC

Why learn Big Data?

It is no secret that the data content in the world is growing exponentially. For last two decades, IT communities have been grappling with the issue of managing the glut of data. Google has been at the forefront of this problem and came up with a framework which is now widely known as Big Data & Hadoop. This framework fundamentally changes the traditional approaches – which are no longer coping with the volumes of data being generated today.

This video Tutorial covers Following Topics:

 - Why Big Data is biggest Buzz Word
 - Basics of Big Data & Hadoop
 - Essence of Big Data (volume, velocity, variety, veracity of Big Data)
 - Problems with conventional systems like RDBMS and OS file-system
 - Introduction of Hadoop & Hadoop ecosystem
 - Real time Hadoop use cases
 - Future of Hadoop & Careers in Hadoop
 - Job Roles in Hadoop like: Hadoop Analyst, Hadoop Developer, Hadoop Admin, Hadoop Architect etc.
 - How DataFlair will help you in making your career in Big Data.

Are you Ready to Migrate your Career in the Latest upcoming Technology Big Data

Visit: http://data-flair.com/course/big-data-and-hadoop-training/

Big Data Hadoop Tutorial For Beginners

Why learn Big Data Hadoop?

We create 2.5 quintillion bytes of data every day. So much that 90% of the data in the world today has been created in the last two years alone (Source: IBM). These extremely large datasets are hard to deal with using legacy systems such as RDBMS as data exceed the storage and processing capacity of database. The legacy systems are becoming obsolete.
According to Gartner: “Big Data is new Oil”. Big Data is all about finding the needle of value in a haystack of Structured, Semi-structured and Un-structured data. Hadoop (the Solution of All Big Data Problems) has become the most important component in the data stack, which enables rapid processing of data at petabyte scale. Hadoop is expected to be at the core of more than half of all analytics software within the next two years.

Watch the exclusive recording of Big Data Live Session

In this tutorial, you will be gaining knowledge on:
- Basics of Big Data & Hadoop
- Introduction to Big Data
- Why Big Data
- Essence of Big Data-volume, velocity, variety, veracity
- Problems with conventional systems like RDBMS and OS file-system
- Introduction of Hadoop
- Introduction of Map-Reduce and HDFS
- Real time Hadoop use cases
- Introduction of Hadoop ecosystem
- Future of Hadoop
- Careers in Hadoop
- Job Roles in Hadoop like: Hadoop Analyst, Hadoop Developer, Hadoop Admin, etc.

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.

Install Cloudera Hadoop with YARN on Ubuntu

Objective:

This tutorial describes how to install and configure a single-node Hadoop cluster on Ubuntu OS. Single Node Hadoop cluster is also called as Hadoop Pseudo-Distributed Mode. The tutorial is very simple and to the point, so that you can install Hadoop in 10 Min. Once the installation is done you can perform Hadoop Distributed File System (HDFS) and Hadoop Map-Reduce operations.

Recommended Platform:

• OS: Linux is supported as a development and production platform. You can use Ubuntu 14.04 or later (you can also use other Linux flavors like: CentOS, Redhat, etc.)
• Hadoop: Cloudera Distribution for Apache hadoop CDH5.x (you can use Apache hadoop 2.x)

Prerequisites:

Install Java 7 (Recommended Oracle Java)

Install Python Software Properties

$sudo apt-get install python-software-properties

Add Repository

$sudo add-apt-repository ppa:webupd8team/java

Update the source list

$sudo apt-get update

Install Java

$sudo apt-get install oracle-java7-installer

Configure SSH

Install Open SSH Server-Client

$sudo apt-get install openssh-server openssh-client

Generate Key Pairs

$ssh-keygen -t rsa -P ""

3.2.3 Configure password-less SSH

$cat $HOME/.ssh/id_rsa.pub >> $HOME/.ssh/authorized_keys

Check by SSH to localhost

$ssh localhost

Install Hadoop

Download Hadoop

http://archive.cloudera.com/cdh5/cdh/5/hadoop-2.5.0-cdh5.3.2.tar.gz

Untar Tar ball

$tar xzf hadoop-2.5.0-cdh5.3.2.tar.gz

Note: All the required jars, scripts, configuration files, etc. are available in HADOOP_HOME directory (hadoop-2.5.0-cdh5.3.2)

Read Complete Post >>

Apache Spark - the Second Generation Big Data Technology

This tutorial covers: Introduction to Spark – Why, what and Features, Understanding Spark Key Terms, RDDs, Spark Ecosystem, Shark, Spark Streaming, MLLib, GraphX, SparkR, Data flow in Spark, Spark Examples with Demo, Fault tolerance in Spark, Spark Use Cases, Spark streaming, Spark Sql, Behavior with Not Enough RAM, Organizations Using Spark



http://data-flair.com/
Email us: info@data-flair.com
Phone: +91-8451097879

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

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

Introduction to HDFS | Hadoop Distributed File System Tutorial

http://data-flair.com/course/big-data-and-hadoop/
Email us: info@data-flair.com
Phone: 8451097879

This video covers: Basics of Hadoop Distributed File System HDFS, Introduction to HDFS, HDFS Architecture, HDFS Nodes, NameNode and DataNode Daemons, HDFS Features, Fault tolerance, High Availability, Reliable Data Storage, Replication, Blocks, File Read Operation, File Write Operation, Rack Awareness, Scalability, Real time Hadoop use cases, 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.

DataFlair Student Review of Hadoop Training

http://data-flair.com/
Email us: info@data-flair.com
Phone: 8451097879

This Video Contains: Feedback about DataFlair from our students.

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, 8451097879.

Learn Big Data with real life use-cases

http://data-flair.com/course/big-data-and-hadoop/

Email us: info@data-flair.com

Phone: +91-8451097879



This video covers: Basics of Big Data & Hadoop, Introduction to Big Data, Why Big Data, essence of Big Data, volume, velocity, variety, veracity of Big Data, Problems with conventional systems like RDBMS and OS file-system, Introduction of Hadoop, Introduction of Map-Reduce, Introduction of HDFS, Real time Hadoop use cases.



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.

Hadoop Map Reduce Training Video

http://data-flair.com/course/big-data-and-hadoop/

Email us: info@data-flair.com

Phone: 8451097879



This video covers: MapReduce Concepts, What is Map, Map Task, Mapper, What is Reduce, Reduce Task, Reducer, Map & Reduce together, MR Job, Task, Split the job into tasks, Map-Reduce flow, Map-Reduce daemons, Job Tracker, Task Tracker, 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.