Environment Setup for Hadoop Installation. (Tutorial 4)

Hadoop - Environment Setup for Hadoop Installation.

Hadoop is supported by Linux System So We install the Linux System.
If you are using other than linux , then download the VirtualBox software in it and install linux in virtual box.

We need to set up linux using ssh i.e. Secure Shell So folow the given Steps:

Step 1: Creating Different User for Hadoop.

Create the seperate user for hadoop to isolate Hadoop file System from Unix file System.

>> Open the root using "su".
>> Create new user from root account using command "useradd <username>".
>> Now you can open the exixting user using the command "su <username>".

Example :

Step 2: Key Generation and SSH Setup.

It is required to do different operations such as starting , stopping on a cluster . To authenticate different user of Hadoop , iy=t is required to provide public/private key pair for a Hadoop user and share it with different users.

Commands are used for generating a key value pair:
>> Copy the Public key from id_rsa.pub to authrazed_keys,
>> Provide the owner with read and write permissions.

Example:

Step 3: Installing the Java.

Java is the main prerequisite for Hadoop . Follows the given Step to install Java.

1. Download the JDK Latest Version (Click Here for jump JDK download )

2. Extract the JDK latest version using the following Command

     

3. Change the location to "/usr/local/". so that it is available for all users. 

4. Now set the PATH and JAVA_HOME variables.

   Now aplly all changes into the current running System.

>> $ source ~/.bashrc.

5. Use the given commands to configure java alternatives:

6. Now Verify the Java - Version  using command java version.

All Requirements for Hadoop Installation are Done.

Links to Tutorial 1. http://firstengineer1.blogspot.in/2016/03/introduction-to-hadoop.html
2. http://firstengineer1.blogspot.in/2016/03/lets-start-with-hadoop.html
3. http://firstengineer1.blogspot.in/2016/04/how-does-hadoop-work-tutorial-3.html

How Does Hadoop Work? (Tutorial 3)

How Does Hadoop Work?

Stage 1

A user/application can submit a job to the Hadoop (a hadoop job client) for required process by specifying the following items:

1. The location of the input and output files in the distributed file system.
2. The java classes in the form of jar file containing the implementation of map and reduce functions.
3. The job configuration by setting different parameters specific to the job.

Stage 2

The Hadoop job client then submits the job (jar/executable etc) and configuration to the JobTracker which then assumes the responsibility of distributing the software/configuration to the slaves, scheduling tasks and monitoring them, providing status and diagnostic information to the job-client.

Stage 3

The TaskTrackers on different nodes execute the task as per MapReduce implementation and output of the reduce function is stored into the output files on the file system.

Advantages of Hadoop

• Hadoop framework allows the user to quickly write and test distributed systems. It is efficient, and it automatic distributes the data and work across the machines and in turn, utilizes the underlying parallelism of the CPU cores.
• Hadoop does not rely on hardware to provide fault-tolerance and high availability (FTHA), rather Hadoop library itself has been designed to detect and handle failures at the application layer.
• Servers can be added or removed from the cluster dynamically and Hadoop continues to operate without interruption.
• Another big advantage of Hadoop is that apart from being open source, it is compatible on all the platforms since it is Java based.

Lets Start With Hadoop.

           HADOOP AND ITS ARCHITECTURE

Introduction and Big Data:
Click Here

Hadoop is an open source framework (OOF) written in java.  It allows to distributed processing of large amount of data across clusters of computers using simple programming models. A Hadoop frame-worked application works in an environment that provides distributed storage and computation across clusters of computers. Hadoop is designed to scale up from single server to thousands of machines, each offering local computation and storage.

Hadoop Architecture:

It has 4 level Architecture or we can say that it has four modules. 

1     1. Hadoop Common: This part of programming module . it consists of Java         Libraries and utilities required by other hadoop modules. These                     libraries provides file Management or File system and OS and it also             contain required java files and script which are required to start                     hadoop.

       2. Hadoop YARN: This is a framework used to manage the cluster                       resources and job scheduling.

       3. Hadoop Distributed File System (HDFS): It is system used to manage             data in hadoop . it based on the google file system and provides a                   distributed file system that is designed to run thousands of small                   computer machines in a reliable, fault-tolerant manner.

       4. Hadoop MapReduce: It is based on YARN for parallel processing of               large amount of data. It is software framework which process big                   amount of data in parallel on large cluster of commodity hardware in a         reliable, fault-tolerant manner.

        

       Hadoop Architecture Diagram

       

       

       

Introduction to Hadoop.

HADOOP:

Hadoop is an open-source framework that gives the functionality of storing and processing the big data in a distributed environment across the clusters of computer by using simple programming models.

Big Data:

It is collection of large amount of data that cannot processes using traditional computing tecgniques. Big Data is not merely a data, rather it has become a complete subject, which involve various tools, techniques and frameworks.

Big data involve the data produced by different devices and applications. Given below are some of the field that come under the umbrella of big data.

§        1. Black Box Data: It is component of helicopters, airplanes and jets etc. It capture voices of                   the flight crew , recordings of microphones and earphones.

§      2. Social Media Data: The stock exchange data holds information about the buy and sell                       decision made on a share of different companies made by the customers.

§      3. Power Grid Data: The power grid data holds information consumed by a particular                            node with respect to a base station.

§       4. Transport Data : Transport data includes Model , capacity , distance and availability of                      a vechicle.

§       5.  Search Engine data : Search engines retrieve lots of data from different databases.