Harish Shan

Tamil Pedia - Privacy Policy

2025-01-04T00:11:00.004+05:30

PRIVACY POLICY

Last updated January 03, 2025

This Privacy Notice for Tamil Pedia ('we', 'us', or 'our'), describes how and why we might access, collect, store, use, and/or share ('process') your personal information when you use our services ('Services'), including when you:

Download and use our mobile application (Tamil Pedia), or any other application of ours that links to this Privacy Notice

Engage with us in other related ways, including any sales, marketing, or events

Questions or concerns? Reading this Privacy Notice will help you understand your privacy rights and choices. We are responsible for making decisions about how your personal information is processed. If you do not agree with our policies and practices, please do not use our Services.

SUMMARY OF KEY POINTS

This summary provides key points from our Privacy Notice, but you can find out more details about any of these topics by clicking the link following each key point or by using our table of contents below to find the section you are looking for.

What personal information do we process? When you visit, use, or navigate our Services, we may process personal information depending on how you interact with us and the Services, the choices you make, and the products and features you use. Learn more about personal information you disclose to us.

Do we process any sensitive personal information? Some of the information may be considered 'special' or 'sensitive' in certain jurisdictions, for example your racial or ethnic origins, sexual orientation, and religious beliefs. We do not process sensitive personal information.

Do we collect any information from third parties? We do not collect any information from third parties.

How do we process your information? We process your information to provide, improve, and administer our Services, communicate with you, for security and fraud prevention, and to comply with law. We may also process your information for other purposes with your consent. We process your information only when we have a valid legal reason to do so. Learn more about how we process your information.

In what situations and with which parties do we share personal information? We may share information in specific situations and with specific third parties. Learn more about when and with whom we share your personal information.

How do we keep your information safe? We have adequate organisational and technical processes and procedures in place to protect your personal information. However, no electronic transmission over the internet or information storage technology can be guaranteed to be 100% secure, so we cannot promise or guarantee that hackers, cybercriminals, or other unauthorised third parties will not be able to defeat our security and improperly collect, access, steal, or modify your information. Learn more about how we keep your information safe.

What are your rights? Depending on where you are located geographically, the applicable privacy law may mean you have certain rights regarding your personal information. Learn more about your privacy rights.

How do you exercise your rights? The easiest way to exercise your rights is by submitting a data subject access request, or by contacting us. We will consider and act upon any request in accordance with applicable data protection laws.

Want to learn more about what we do with any information we collect? Review the Privacy Notice in full.

TABLE OF CONTENTS

1. WHAT INFORMATION DO WE COLLECT?

2. HOW DO WE PROCESS YOUR INFORMATION?

3. WHEN AND WITH WHOM DO WE SHARE YOUR PERSONAL INFORMATION?

4. HOW LONG DO WE KEEP YOUR INFORMATION?

5. HOW DO WE KEEP YOUR INFORMATION SAFE?

6. DO WE COLLECT INFORMATION FROM MINORS?

7. WHAT ARE YOUR PRIVACY RIGHTS?

8. CONTROLS FOR DO-NOT-TRACK FEATURES

9. DO WE MAKE UPDATES TO THIS NOTICE?

10. HOW CAN YOU CONTACT US ABOUT THIS NOTICE?

11. HOW CAN YOU REVIEW, UPDATE, OR DELETE THE DATA WE COLLECT FROM YOU?

1. WHAT INFORMATION DO WE COLLECT?

Personal information you disclose to us

In Short: We collect personal information that you provide to us.

We collect personal information that you voluntarily provide to us when you express an interest in obtaining information about us or our products and Services, when you participate in activities on the Services, or otherwise when you contact us.

Sensitive Information. We do not process sensitive information.

All personal information that you provide to us must be true, complete, and accurate, and you must notify us of any changes to such personal information.

2. HOW DO WE PROCESS YOUR INFORMATION?

In Short: We process your information to provide, improve, and administer our Services, communicate with you, for security and fraud prevention, and to comply with law. We may also process your information for other purposes with your consent.

We process your personal information for a variety of reasons, depending on how you interact with our Services, including:

3. WHEN AND WITH WHOM DO WE SHARE YOUR PERSONAL INFORMATION?

In Short: We may share information in specific situations described in this section and/or with the following third parties.

We may need to share your personal information in the following situations:

Business Transfers. We may share or transfer your information in connection with, or during negotiations of, any merger, sale of company assets, financing, or acquisition of all or a portion of our business to another company.

4. HOW LONG DO WE KEEP YOUR INFORMATION?

In Short: We keep your information for as long as necessary to fulfil the purposes outlined in this Privacy Notice unless otherwise required by law.

We will only keep your personal information for as long as it is necessary for the purposes set out in this Privacy Notice, unless a longer retention period is required or permitted by law (such as tax, accounting, or other legal requirements).

When we have no ongoing legitimate business need to process your personal information, we will either delete or anonymise such information, or, if this is not possible (for example, because your personal information has been stored in backup archives), then we will securely store your personal information and isolate it from any further processing until deletion is possible.

5. HOW DO WE KEEP YOUR INFORMATION SAFE?

In Short: We aim to protect your personal information through a system of organisational and technical security measures.

We have implemented appropriate and reasonable technical and organisational security measures designed to protect the security of any personal information we process. However, despite our safeguards and efforts to secure your information, no electronic transmission over the Internet or information storage technology can be guaranteed to be 100% secure, so we cannot promise or guarantee that hackers, cybercriminals, or other unauthorised third parties will not be able to defeat our security and improperly collect, access, steal, or modify your information. Although we will do our best to protect your personal information, transmission of personal information to and from our Services is at your own risk. You should only access the Services within a secure environment.

6. DO WE COLLECT INFORMATION FROM MINORS?

In Short: We do not knowingly collect data from or market to children under 18 years of age.

We do not knowingly collect, solicit data from, or market to children under 18 years of age, nor do we knowingly sell such personal information. By using the Services, you represent that you are at least 18 or that you are the parent or guardian of such a minor and consent to such minor dependent’s use of the Services. If we learn that personal information from users less than 18 years of age has been collected, we will deactivate the account and take reasonable measures to promptly delete such data from our records. If you become aware of any data we may have collected from children under age 18, please contact us at __________.

7. WHAT ARE YOUR PRIVACY RIGHTS?

In Short: You may review, change, or terminate your account at any time, depending on your country, province, or state of residence.

Withdrawing your consent: If we are relying on your consent to process your personal information, which may be express and/or implied consent depending on the applicable law, you have the right to withdraw your consent at any time. You can withdraw your consent at any time by contacting us by using the contact details provided in the section 'HOW CAN YOU CONTACT US ABOUT THIS NOTICE?' below.

However, please note that this will not affect the lawfulness of the processing before its withdrawal nor, when applicable law allows, will it affect the processing of your personal information conducted in reliance on lawful processing grounds other than consent.

8. CONTROLS FOR DO-NOT-TRACK FEATURES

Most web browsers and some mobile operating systems and mobile applications include a Do-Not-Track ('DNT') feature or setting you can activate to signal your privacy preference not to have data about your online browsing activities monitored and collected. At this stage, no uniform technology standard for recognising and implementing DNT signals has been finalised. As such, we do not currently respond to DNT browser signals or any other mechanism that automatically communicates your choice not to be tracked online. If a standard for online tracking is adopted that we must follow in the future, we will inform you about that practice in a revised version of this Privacy Notice.

9. DO WE MAKE UPDATES TO THIS NOTICE?

In Short: Yes, we will update this notice as necessary to stay compliant with relevant laws.

We may update this Privacy Notice from time to time. The updated version will be indicated by an updated 'Revised' date at the top of this Privacy Notice. If we make material changes to this Privacy Notice, we may notify you either by prominently posting a notice of such changes or by directly sending you a notification. We encourage you to review this Privacy Notice frequently to be informed of how we are protecting your information.

10. HOW CAN YOU CONTACT US ABOUT THIS NOTICE?

If you have questions or comments about this notice, you may contact us by post at:

Tamil Pedia

153 N.K.Ganapathy Street,

Anna Nagar,

Kanchipuram, Tamil Nadu 631501

India

11. HOW CAN YOU REVIEW, UPDATE, OR DELETE THE DATA WE COLLECT FROM YOU?

Based on the applicable laws of your country, you may have the right to request access to the personal information we collect from you, details about how we have processed it, correct inaccuracies, or delete your personal information. You may also have the right to withdraw your consent to our processing of your personal information. These rights may be limited in some circumstances by applicable law. To request to review, update, or delete your personal information, please fill out and submit a data subject access request.

Virtual Reality

2019-08-10T23:32:00.000+05:30

The term "Virtual Reality"(Shortly called as VR) was first coined by an American computer scientist Jaron Lanier who founded VRL Research Inc in the 1980s to sell the first VR Goggles. Virtual Reality is an artificial environment that is created with software which creates a sensory experience of virtual presence in the simulated world. At present many industries started using VR as part of their applications. The VR was just fiction till the last decade, but today it becomes possible and affordable to everyone with the evolution and integration of the following technologies.

1. 360° Camera

We need a special camera which can capture 360° or at-least 190° since we have a maximum of 190° horizontal Field of View(FOV) by both of our two eyes, we have approximately 120° FOV for binocular vision(seen by both eyes together) and 135° FOV for vertical range of the visual fields. There are many 360° cameras available on the market and it does not require much technical knowledge to use this camera. The following are some popular 360° cameras currently available in the online market

Apart from the above expensive cameras, there are few apps(such as Google Street View and Cardboard Camera) available in both Andriod and iOS which will help us to capture 360° photos.
I have used Insta360 ONE X to capture my 360° Videos and Photos

2. Smartphone

A display device which can play video as binocular mode(side by side) and it should be placed 2" closer to our eyes, which means the device should not be more than 6.5" of screen size. Smart Phones with gyroscope sensor has the capability of tracking our head movement and play the video according. Moreover, the smartphone should have the VR media player to play the 360° video in Binocular mode.

3. VR Headset

If smartphones are 2" close to our eyes, we can't enjoy the VR experience, for that we need VR Headsets to see the video played by smartphones with the help of magnifying lenses to see the wide-angle. There are plenty of VR headsets are available in the market, Moreover Google has published the standard procedure to create our own(DIY) VR headsets in the name of Google Cardboard. The wide-angles of the VR headsets(maximum angle ability to experience the VR) are measured in FOV. The following are some popular VR headsets available in the online market

As already stated the evolution and integration of 360° camera, Smartphones with gyroscope and VR Headset made VR experience possible today. But in the Telugu (Indian Language) film "9 Nelalu" released in 2001, a scene is about VR in which it will describe how the VR experience is like.
In this particular scene, the hero returned home very late on his wedding day so that he cannot take his wife to the temple. But he will take his wife to the temple via VR, wearing a VR headset.

Find the link for the particular scene

DIY Simplified Google Cardboards Required Material:

Cardboard
Chart
Scale
Pen/Pencil
Staplers/Glue
Pair of the lens with 45mm focal length and 37mm diameter

Note: The 25mm diameter lenses were used in Google cardboard v1.0 but Google cardboard v2 uses 37mm diameter lenses. The diameter and the focal length of the lens matters, so be conscious while buying the lens.
I am using BAIRN ART 37mm Google Cardboard VR Lenses (Pack of 2) for this Google Cardboard
Let's note the following parameters and measurements for 6.3" Screen smart phones

Screen to lens distance: 45mm (same as focal length)
Inter lens diameter: 70mm
The thickness of the phone: 10mm
Phone Dimensions: 150mm x 73mm
Display Dimension: 140mm x 70mm

Now we are ready to draw the following diagram on the chart with the measurement as given below.

Where

The dimension of the side part is 80mm x 80mm as the phone size is 73mm, So derived the height of the side part as 80mm*80mm
The length of the top and bottom part of the cardboard should be 145mm as the phone dimension is 150mm x 73mm and screen dimension is 140mm x 70mm, so we derived the length of as 145mm (in between of 140mm and 150mm) and width as 80mm as same side part
Normal human face width is around 100mm so the curve length should be 125mm
The distance between pupils is 60mm so the inter lenses diameter as 70mm and lens center point should be at the middle of the cardboard.
Since the phone thickness is 10mm, we have given 15mm space for that

Draw the above diagram on the chart first to create the design template and cut the cardboard with the help of a template. Something like below but as per your phone measurement.

Once the cardboard is cut, fold the card as VR headset and glue it with glue or stapler, and place the lens card 45 mm away from the phone.

Now our simplified Google Cardboard(VR headset) is ready. Now we can darshan Athi Varadar via our Google Cardboard prepared and Google Cardboard app installed on our smartphone.

Athi Varadar

2019-08-01T22:20:00.005+05:30

Athi Varadar 360° Photo

Donar Pass View Free Darshan View

How to fix Kindle wrong time left in chapter book

2018-07-18T18:34:00.001+05:30

The most of kindle reader use the time left in chapter or time left in book options provided at left bottom of the page to estimate completing the book or the current chapter. But sometimes it was not accurate and displaying 5 min left in chapter instead of 30 min left in chapter. To fix this issue just type

;ReadingTimeReset

at search field and enter. Kindly refer the photo for the same.

Git

2018-07-03T20:16:00.000+05:30

Git is free and open source Distributed Version Control System (DVCS). Git was created by Linux Torvalds in 2005 for the development of Linux Kernel, with other kernel developers contributing to its initial development. Its current maintainer since 2005 is Junio Hamano.

Git is responsible for keeping track of changes to content usually source code files. It is designed to handle everything from small to very large projects with speed and efficiency. It provides mechanisms for sharing that content with others. It helps software developers to work simultaneously and maintaining history of every version.

This post will help to on board Git from basics to professional level.

Centralized Version Control System vs Distributed Version Control System

Centralized Version Control System uses a central server to store all files and enables team collaborations. It works on a single repository to which users can directly access a central server.

Repository Management

At Git, We manage our projects at repository. Git provides wide flexibility to manage our code. The following diagram represents the user repository strategy one of the most adopted method for managing repository.

Git User Strategy

At 'Git User Strategy' we will have a master remote repository which should have master branch, release branch and develop branch where master branch should contain live code, release branch should contain QA code and develop code will contain all the valid code merged from user remote repository.

Each user should fork from the master repository and create copy as user remote repository, Then they will clone from the user remote repository to their local machine and start working.

Create Organization & Repository

We need to create the master remote repository under organization at any of the Git platforms such as GitHub, BitBucket, GitLab, etc. All the below examples are bases on GitHub, so do sign up at GitHub and have a GitHub user account account ready.
Create organization from https://github.com/organizations/new where give some unique name for the organization from the created GitHub user account. Here "harishshanblogspot" is the organization name.

Creating Organization

Inviting organization members
Create master remote repository from the created organization. Here "example" is the master remote repository name.
Then all the users work on the project should fork from the master remote repository to create their user forked remote repository.

Once we have created the master remote repository and created forked user remote repository at GitHub. We can start working on our project from our local machine, The following example shows how to install Git, configure Git user account and start working on git commands from Windows.

Install Git at Windows

Download Git from https://git-scm.com/download/win
Run the downloaded Git setup for installing Git

While installing make sure the following configurations

To use Git commands from windows command prompt

To use OpenSSL Library for validating certificates

**Always use "Checkout windows-style, commit Unix-style line ending" to avoid CRLF issues while team is using different Operating-systems.

Concepts Of Git:

Repositories, Branches, Remotes, Committing, Pushing, Pulling, Merging, Rebasing, Reverting and Cherry-Picking

Concepts of GitHub:

Pull-Requests, Issues, Wiki, Forking, Remote Repositories, Gist

Simple Git Commands

git config

We need to configure the GitHub user account with user name and email address of created GitHub account. The following is the syntax for configuring user name and email, Where we need to replace the username and email-address with the created GitHub account.

git config --global user.name <username>
git config --global user.email <email-address>

git clone

Clone the created the project, the following is the example of 'git clone' command used to clone the repository at our local machine. This command can be executed at local machine git workspace directory where we want to clone the repository. Where git@github.com:harishshan/example.git is the user remote repository

git clone git@github.com:harishshan/example.git

git status

The 'git status' command will display the status and recommend us the next step.

git status

git add & git commit

The 'git add' command is used to add un-tracked modification/new file to staging from working area. This one helps us to segregate which changes are effective, we can ignore the rest of the changes are working area.

The syntax of 'git add' command for adding files by relative file path

git add <file1> <file2>

The following command can be used when we want to add all the changes from working directory to staging

git add .

The 'git commit' command is used to record our changes to the local repository. All the files added at staging area will be moved when we do 'git commit'. For each commit, git will return a unique commit id of length 40. Where -m parameter is mandatory used to mention the commit message

git commit -m "Commit Message"

git push

The 'git push' command is used to push the committed changes from the local machine repository to upstream. By default it will be pushed to origin remote repository and current branch.

git push

git pull

The 'git pull' command is used to pull the committed changes from the upstream to local machine repository. By default it will be pulled from the origin remote repository and current branch.

git pull

git remote

The 'git remote' command used to manage the remote repositories. The following command is used to list the remote repositories added for the current local repositories.

git remote -v

The following command is used to add the upstream remote repositories. We already cloned from the user remote repository and now we adding Master remote repository. Where git@github.com:harishshanblogspot/example.git is the Master remote repository. We can verify the added remote repositories using the 'git remote -v'.

git remote add parent git@github.com:harishshanblogspot/example.git

Git Use-cases

<<<<<<<<<<<<<<<Still Editing>>>>>>>>>>>>>>>

How to use Google Code Prettify

2017-07-16T21:18:00.001+05:30

This post is about how can we use Google Code Prettify to highlight the code which is displayed in my blog. Google Code Prettify is a simple lightweight embeddable java script library. Find the steps below for how to use Google Code Prettify.

Step 1: Add run_prettify.js script and any one of skin styles(sunburt

<script src="https://cdn.rawgit.com/google/code-prettify/master/loader/run_prettify.js?autoload=true&skin=sunburst&lang=css" defer=""></script>

Step 2: Use pre tag for representing our code as follows. The following is the example of html code highlighter.

<pre class="prettyprint lang-html linenums">
list of statements
</pre>

List of Skin Styles

List of built-in languages supported

bsh, c, cc, cpp, cs, csh, cyc, cv, htm, html, java, js, m, mxml, perl, pl, pm, py, rb, sh, xhtml, xml and xsl

List of additional language supported

Apollo, Basic, Clojure, CSS, Dart, Erlang, Go, Haskell, Lasso, Lisp, Scheme, LLVM, Logtal, Lua, MATLAB, MLs: F#, Ocaml,SML, Mumps, Nemerle, Pascal, Protocol buffers, R, S, RD, Rust, Scala, SQL, Swift, TCL, LaTeX, Visual Basic, VHDL, Wiki, XQ, YAML

For Reference: https://github.com/google/code-prettify

Base 64 Encode & Decode

2017-06-22T15:56:00.000+05:30

This post is about Base64 encoding and decoding. Base64 is a group of similar Binary-to-text encoding schemes that represent binary data in an ASCII string format by translating it into a radix-64 representation. The atob() and btoa() JavaScript methods, defined in the HTML5 draft specification, provide Base64 encoding and decoding functionality to web pages.

GitHub Link: https://github.com/harishshan/Tools/blob/master/Base64EncodeDecode.html

JSON Viewer

2017-06-22T15:49:00.002+05:30

This is a simple JSON viewer developed using JQuery. Find the JSON viewer blow and its source code at GitHub Link

Options: Collapse nodes Keys with quotes

GitHub Link:https://github.com/harishshan/Tools/blob/master/JSONViewer.html

How to create Dynamic Kafka Topic Through Java

2017-03-07T09:45:00.004+05:30

This is post is about how to create a Kafka topic dynamically through Java.In one of my project, we(me and my friend Jaya Ananthram) were required to create dynamic Kafka topic through Java. Since there is no documentation on Kafka official documentation we are struggled to create dynamic Kafka topic through Java. Then After a long search ,we found this solution for creating the Kafka topic through Java.

import java.util.Properties;
import kafka.admin.AdminUtils;
import kafka.utils.ZKStringSerializer$;
import kafka.utils.ZkUtils;
import org.I0Itec.zkclient.ZkClient;
import org.I0Itec.zkclient.ZkConnection;

public class KafkaTopicCreationInJava
{
    public static void main(String[] args) throws Exception {
        ZkClient zkClient = null;
        ZkUtils zkUtils = null;
        try {
            String zookeeperHosts = "localhost:2181";  
            // If multiple zookeeper then -> String zookeeperHosts = "192.168.1.1:2181,192.168.1.2:2181";
            int sessionTimeOutInMs = 15 * 1000; // 15 secs
            int connectionTimeOutInMs = 10 * 1000; // 10 secs

            zkClient = new ZkClient(zookeeperHosts, sessionTimeOutInMs, connectionTimeOutInMs, ZKStringSerializer$.MODULE$);
            zkUtils = new ZkUtils(zkClient, new ZkConnection(zookeeperHosts), false);

            String topicName = "testTopic";
            int noOfPartitions = 2;
            int noOfReplication = 3;
            Properties topicConfiguration = new Properties();

            AdminUtils.createTopic(zkUtils, topicName, noOfPartitions, noOfReplication, topicConfiguration);

        } catch (Exception ex) {
            ex.printStackTrace();
        } finally {
            if (zkClient != null) {
                zkClient.close();
            }
        }
    }
}

I am assuming both Zookeeper and Kafka are configured with default configuration at localhost and the service running. While creating ZkClient object, we must set ZkSerializer as ZKStringSerializer$.MODULE$, So that ZkClient will create a topic at Kafka. If we didn't mention ZkSerializer, the topic will not be properly created at Kafka. It will just create topic directories at Zookeepers and It will show that topic is created successfully. But by the time we try to push tuples, it will fail and throw Topic is not exists.

Note: The ZKStringSerializer$.MODULE$ will return the singleton ZKStringSerializer object.

Installing MS SQL Server on Ubuntu 16.04

2016-11-17T20:46:00.000+05:30

This post about installing the MS SQL Server on Ubuntu 16.04. MS SQL Server could be installed only on Windows, Now Microsoft released SQL Server 2017, which adds Linux support for these Linux platforms: Red Hat Enterprise Linux, SUSE Linux Enterprise Server, Ubuntu & Docker Engine. Find the steps below for installing MS SQL Server on Ubuntu 16.04

1. Login to sudo user

$sudo su

2.Install CURL (if curl is not already installed)

$sudo apt-get install curl

3.Register MS SQL Server repository

$curl https://packages.microsoft.com/keys/microsoft.asc | apt-key add
$curl https://packages.microsoft.com/config/ubuntu/16.04/mssql-server.list > /etc/apt/sources.list.d/mssql-server.list
$curl https://packages.microsoft.com/config/ubuntu/16.04/prod.list > /etc/apt/sources.list.d/msprod.list
sudo apt-get update

Note: mssql-server.list contains mssql-server and msprod.list contains mssql-tools
4. Install MS SQL server.

$sudo apt-get install -y mssql-server
$sudo /opt/mssql/bin/sqlservr-setup

Note: Do remember the password you have entered while installing the MS SQL server. Default username for the server is SA
5.Check the MS SQL Server service is running or not

$systemctl status mssql-server

6. Install MS SQL Tools

$sudo apt-get install mssql-tools

7. Connect the MS SQL Server via terminal using "sqlcmd" command and test some sample queries Syntax:

sqlcmd -S <hostname> -U <username> -P <password>

Example:

$sqlcmd -S localhost -U SA -P password
>CREATE DATABASE school;
>USE school
>CREATE DATABASE student(rollnumber INT, name VARCHAR(50));
>INSERT INTO student VALUES(1,'HARISH');
>SELECT * FROM school.student;
>QUIT

Brief Introduction to D3.js

2016-10-05T23:12:00.005+05:30

This post is the short notes about D3.js (Data Driven Documents) framework, It is a JavaScript framework mainly used to generate charts using HTML, DOM, Canvas and SVG. Reference: https://github.com/mbostock/d3/wiki/API-Reference

Select, Append, Text:

<script src="http://d3js.org/d3.v3.min.js"></script>
<script>
d3.select("body")
 .append("p")
 .style("color","red")
 .attr("allign","center")
 .text("Hello World");
</script>

Basic SVG Shape:

var canvas=d3.select("body")
 .append("svg")
 .attr("width",500)
 .attr("height",500);
var circle = canvas.append("circle")
 .attr("cx",250)
 .attr("cy",250)
 .attr("r", 50)
 .attr("fill","red");
var rect = canvas.append("rect")
 .attr("width",100)
 .attr("heiht",59);
                
var line = canvas.append("line")
 .attr("x1",0)
 .attr("y1",100)
 .attr("x2",400)
 .attr("y2",400)
 .attr("stroke","green")
 .attr("stroke-width",10);

Visualizing Data:

var dateArray = [20, 40, 50];
var canvas = d3.select("body")
 .append("svg")
 .attr("width",500)
 .attr("height",500);
var bars = canvas.selectAll("rect")
 .data(dateArray)
 .enter()
  .append("rect")
  .attr("width",function(d){
   return d * 10;
  })
  .attr("height",50)
  .attr("y",function(d, i){
   return i * 50
  });

Scales:

var width = 500;
var height = 500;
var widthscale = d3.scale.linear()
 .domain([0,60])
 .range([0, width]);
var color = d3.scale.linear()
 .domain([0,40])
 .range([red,blue]);
var dateArray = [20, 40, 50];
var canvas = d3.select("body")
 .append("svg")
 .attr("width",500)
 .attr("height",500);
var bars = canvas.selectAll("rect")
 .data(dateArray)
 .enter()
  .append("rect")
  .attr("width",function(d){
   return widthscale(d);
  })
  .attr("height",50)
  .attr("file", function(id){ return color(id})
  .attr("y",function(d, i){
   return i * 50
  });

Groups and Axes:

var axis = d3.svg.axis()
 .ticks(5)
 .scale(widthscale);
var canvas = d3.select("body")
 .append("svg")
 .attr("width",500)
 .attr("height",500)
 .append("g")
 .attr("transform","translate(20,0)")
 .call(axis);                
canvas.append("g")
 .attr("transform","translate(0,400)")
 .call(axis);

Enter, Update, Exit:

Dom elements < data elements(enter)
Dom elements > data elements(exit)
Dom elements = data elements(update)
var data = [10,20];
var canvas = d3.select("body")
 .append("svg")
 .attr("width",500)
 .attr("height",500);
var circle = canvas.append("circle")
 .attr("cx", 50)
 .attr("cy", 50)
 .attr("r",25);
var circle = canvas.selectAll("circle")
 .data(data)
 .attr("file","red")
 .enter()
  .append("circle")
  .attr("cx", 50)
  .attr("cy", 50)
  .attr("r",25)
  .attr("color","green");

Transitions:

var canvas = d3.select("body")
 .append("svg")
 .attr("width",500)
 .attr("height",500);
var circle = canvas.append("circle")
 .attr("cx", 50)
 .attr("cy", 50)
 .attr("r",25);
circle.transition()
 .duration(1500)
 .delay(2000)
 .attr("cx",150)
 .transition()
 .attr("cy",150)
 .each("end",function(){
  d3.select(this).attr("fill","red");
 });

Loading External Data:

mydata.json file : {{"name":"harish","age",25},{"name":"chitra","age":22},{"name":"Kutty","age":23}}
d3.json("mydata.json",function(data){
    var canvas = d3.select("body").append("svg")
  .attr("width",500)
  .attr("height",500);              
 canvas.selectAll("rect")
  .deta(data)
  .enter()
   .append("rect")
   .attr("width", function(d{
    return d.age * 10;
   })
   .attr("height",48)
   .attr("y",function(d,i){
    return i*50;                    
   })
   .attr("fill",""blue);
 canvas.select("text")
  .data(data)
  .enter()
   .append("text")
   .attr("fill","white)
   .attr("y",function(d,i){
    return i*50;
   })
   .text(function(d){
    return d.name;
   });
    })
})

mydata.csv

"name","age"
"Harish",25
"Chitra",22
"Kutty",23

Paths:

var canvas = d3.select("body").append("svg")
 .attr("width",500)
 .attr("height",500);
var data =[
 {x:10, y:20},
 {x:40, y:60},
 {x:50, y:70},
];
var group = canvas.append("g")
 .attr("transform","translate(100,100)");
var line = d3.svg.line()
 .x(function(d){
  return d.x;
 })
 .y(function(d){
  return d.y;
 };
group.selectAll("path")
 .data(data)
 .enter()
  .append("path")
  .attr("d", line)
  .attr("fill","none")
  .attr("stroke","#000")
  .attr("stroke-width",10);

Arcs(Donut chart):

var data = [10,20,30];
var r = 300;
var color = d3.scale.ordinal()
 .range(["red","blue","orange"])
var canvas = d3.select("body").append("svg")
 .attr("width",500)
 .attr("height",500);
var group = canvas.append("g")
 .attr("transform","translate(100,100)");
var arc = d3.svg.arc()
 .innnerRadius(r-100)//innnerRadius(0) for piechart
 .outerRadius(r)
 
var pie = d3.layout.pie()
 value(function(d){
  return d;
 });
var arcs = group.selectAll("arc")
 .data(pie(data))
 .enter()
  .append("g")
  .attr("class","arc");
 
arcs.append("path")
 .attr("d",arc)
 .attr("fill", function(d){
  return color(d.data);
 });
arcs.append("text")
 .attr("transform", function(d){
  return "translate("+arc.centroid(d) +")";
 })
 .attr("text-anchor","middle")
 .attr("font-size",1.5em);
 .text(function(d){ 
  return d.data;
 });

Tree Layout:

{
    "name":"Shanmugam",
    "children" : [
        {
            "name":"Harish",
            "children":[
                {"name":"a"},
                {"name","b"},
                {"name","c"}
            ]
        },
        {
            "name":"chitra",
            "children":[
                {"name":"y"},
                {"name","z"}
            ]
        }
    ]
}

Just diagonal curve :

var canvas = d3.select("body").append("svg")
 .attr("width",500)
 .attr("height",500);
var diagonal = d3.svg.diagonal()
    .source({x:10, y:10})
    .target({x:300,y:300};

canvas.append("path")
 .attr("file","none")
 .attr("stroke","black")
 .attr("d", diagonal);

Full:

var canvas = d3.select("body").append("svg")
 .attr("width",500)
 .attr("height",500)
 .append("g")
 .attr("transform","translate(50,50)");
var tree = d3.layout.tree()
 .size([400,400]);
            
d3.json("mydata.json", function(data){
    var nodes = tree.nodes(data);
    var links = tree.links(nodes);
    var node = canvas.selectAll(.node)
  .data(nodes)
  .enter()
   .append("g")
   .attr("class","node")
   .attr("transform", funnction (d){
    return "translate(" + d.x +", "+ d.y + ")";
   })
    node.append("circle")
        .attr("r",5)
        .attr("fill","blue");
        
    node.append("text")
        .text(function(d){
            return d.name;
        });
    var diagonal = d3.svg.diagonal();
    //.projection(function (d) { reutrn [d.x, d.y]});
    canvas.selectAll(".link")
  .data(links)
  .enter()
   .append("path")
   .attr("class","link")
   .attr("fill","none")
   .attr("stroke","#ADADAD")
   .attr("d", diagonal);
})

Cluster Pack Bubble Layouts:

var canvas = d3.select("body").append("svg")
 .attr("width",500)
 .attr("height",500)
 .append("g")
 .attr("transform","translate(50,50)");
var pack = d3.layout.pack()
 .size([width, height-50])
 .padding(10);
d3.json("mydata.json", function(data){
    var nodes = pack.nodes(data);    
    var node = canvas.selectAll(".node")
        .data(nodes)
        .enter()
        .append("g")
            .attr("class","node")
            .attr("transform", function(d){
                return "translate[" + d.x+ ","+d.y +")";                
            })
    node.append("circle")
        .attr("r",function(d){
            return d.r;
        })
        .attr("stroke","#ADADAD")
        .attr("stroke-width", 5);
        
    node.apppend("text")
        .text(function(d){
            return d.childer ? "" : d.name;
        })
});
});

Histogram:

var width = 500, height = 500, padding= 50;
d3.csv("ages.csv",function(data){
    var map = data.map(function(i){
        return parseInt(i.age);
    })
    var histgram = d3.layout.histogram()
        .bins(7)(map)
    var y = d3.scale.linear()
  .domain([0, d3.max[histogram.data(function(i){return i.length;})])
  .range([0, height]);
            
    var x = d3.scale.linear()
  .domain([0,d3.max(map)])
  .range([0,width])
    var xAxis = d3.svg.axis()
  .scale(x)
  .orient("bottom");
    var canvas = d3.select("body").append("svg")
        .attr("width",500)
        .attr("height",500);
    var group = canvas.append("g")
        .attr("transform","translate[20,0]")
    var bars = canvas.selectAll(".bar")
        .data(histogram)
        .enter()
        .append("g")
    bars.append("rect")
        .attr("x", function(d){
            return d.x * 5;
        })
        .attr("y", 0)
        .attr("width", function(d){
            return d.dx * 5;
        })
        .attr("height", function(d){
            return d.dy *5;
        })
        .attr("fill","blue")
    bars.append("text")
        .attr("x", function(d){ return x[d.x})
        .attr("y", function(d){ return 500 - y[d.y];})
        .attr("dy",200px)
        .attr("fill", green)
        .attr("text-anchour","middle")
        .text(function(d){return d.y;})
});

A Brief Intro of Apache Storm

2015-04-21T23:29:00.004+05:30

This post is about Apache Storm and How to install Apache Storm 0.9.4 (latest version) on Windows 7 & Ubuntu 14.04.2 with an Hello World program.

Overview of Apache Storm

Apache Storm is a free and open source distributed system for real-time computation. Storm is implemented in Clojure & Storm APIs are written in Java by Nathan Marz & team at BackType. Storm is best for distributed processing where unbounded streams of real time data computation requires. In contrast to batch systems like Hadoop, which often introduce delay of hours, Storm allows us to process online data.Storm is extremely fast, with the ability to process over a million records per second per node on a cluster of modest size.

About Nathan Marz

Nathan Marz was the lead engineer on Twitter's Publisher Analytics team. Previously Nathan was the lead engineer of BackType which was acquired by Twitter in July of 2011. On march 2013 he left Twitter to start-up his own company He is a major believer in the power of open source and has authored some significant open source projects, including Cascalog, ElephantDB, and Storm. He writes a blog at http://nathanmarz.com.

A Brief History of Apache Storm

In 2010 Apache Storm was a nothing than an idea of Nathan Marz, But now storm has been adopted by many of the world's largest companies including Yahoo!, Twitter, Microsoft and many more. Before Storm, BackType built an analytic product to help businesses understand their impact on social media both historically and real time using Queues and Workers approach. Oftentimes these workers would send messages through another set of queues to another set of workers for further processing. Where most portion of code are for sending/receiving messages and serializing/deserializing messages and with small portion of actual business logic.

In December 2010, Nathan Marz realized the complexity of product and come up with idea of "Stream" as distributed abstraction with Top-level abstraction "Topology", a network of spouts and bolts. Spout produces brand new streams and Bolt takes in streams as input by subscribe to whatever streams they need to process and produces streams as output. The key insight is that spout and bolt are inherently parallel. Then he tested this abstraction against his test case and he wanted to validate large set of use cases, so he tweeted as

"I'm working on new kind of stream processing system. If this sounds interesting to you, ping me. I want to learn your use cases"

Most of people responded with their use-cases, Then he Initially started designing Storm with RabbitMQ for Intermediate messages. Then without intermediate messages, Nathan Marz developed an algorithm based on random numbers and XORs that would only require 20bytes to track each spout tuple to solve massage processing guarantee. Unlike Hadoop Zombie processes which would not shut down at idle, Storm never has this Zombie process issue and Storm has been designed to be "Process Fault-Tolerant". Storm has bean open sourced on July 2011 and graduated to a top-level Apache project on September 17th, 2014.

Storm Application

A Storm application is designed as a topology in the shape of DAG(Directed ACyclic Graph) with Spouts and Bolts acting as graph vertices. Edges on the graph are data stream between nodes.Here are some typical “prevent” and “optimize” use cases for Storm.

	“Prevent” Use Cases	“Optimize” Use Cases
Financial Services	Securities fraud Operational risks & compliance violations	Order routing Pricing
Telecom	Security breaches Network outages	Bandwidth allocation Customer service
Retail	Shrinkage Stock outs	Offers Pricing
Manufacturing	Preventative maintenance Quality assurance	Supply chain optimization Reduced plant downtime
Transportation	Driver monitoring Predictive maintenance	Routes Pricing
Web	Application failures Operational issues	Personalized content

Characteristics of Storm

Fast – bench-marked as processing one million 100 byte messages per second per node
Scaleable – with parallel calculations that run across a cluster of machines
Fault-tolerant – when workers die, Storm will automatically restart them. If a node dies, the worker will be restarted on another node.
Reliable – Storm guarantees that each unit of data (tuple) will be processed at least once or exactly once. Messages are only replayed when there are failures.
Easy to operate – standard configurations are suitable for production on day one. Once deployed, Storm is easy to operate

Use cases of Storm

Processing Streams (No need of intermediate Queues)
Continuous Computation
Distributed RPC

Spout

A Spout is a source of streams in a computation. Spout can read from queue like Kafka , can generate its own stream or read Twitter streaming.

Bolt

A bolt processes any number of input streams and produces any number of new output streams.Most of the logic of a computation goes into bolts, such as functions, filters, streaming joins, streaming aggregations, talking to databases, and so on.

Topology

A topology is a network of spouts and bolts, with each edge in the network representing a bolt subscribing to the output stream of some other spout or bolt. A topology is an arbitrarily complex multi-stage stream computation. Topologies run indefinitely when deployed.
A topology can have one spout and multiple bolt
A topology is arrangement of spout and bolt

Understanding Storm Architecture

Storm cluster has 3 sets of nodes

1. Nimbus Node

Uploads computations for execution
Distributes code across the cluster
Launches workers across the cluster
Monitors computations and reallocates workers as needed

2. Zookeeper nodes

Coordinates the storm cluster
Zookeeper is a distributed coordination service going to installed on each and every machine
Job tracker
When any failure, zookeeper will assist to nimbus and nimbus will re invoke to supervisor

3. Supervisor nodes

Communicates with nimbus through zookeeper, starts and stops workers according to signals from nimbus.
Supervisor actual execution happens at supervisor and only start and stop signals one set by nimbus
Task Tracker

Storm topology

The work is delegated to different types of components that are each responsible for a simple specific processing task
Input stream of a storm cluster is handled by a component called a spout
The spout pass the data to a component called a bolt which transforms it in some way
A boult either persists data in some sort of storage or pass it to some other bolt
Only one nimbus in a cluster, Single point of failure

Five Key abstractions help to understand how storm processes data

Tuple: An ordered list of elements eg: (7,5,6,9)
Stream: An unbounded sequence of tuples
Spouts: Source of streams in a computations
Bolts:Process input stream and produce output streams they can run functions filters aggregates or join data or talk to databases
Topology:overall calculation, represented visually as a network of spouts and bolts (as in the following diagram)

Nimbus

Distribute the code & lunch workers across the cluster
Real-time Analytics by Storm in Hadoop Framework
We can process the real time data with the help of queue streaming and Distributed Processing

How Apache Storm Works?

Consider we having a task like processing 2,00,000 lines text file on a machine, here to process a single record, it takes 6 seconds, so it will take(2,00,000*6) 12,00,000 seconds. Now we can see the real problem of long execution time.

How can we reduce the processing time? By creating two 1,00,000 lines text file and executing 2 processes, we can reduce the processing time to 6,00,000. So by parallel processing we can acheive this. But by doing more parallel processing on the single machine will not be effective. That is how distributed processing given solution to this problem by Running 10,000 lines text file on 20 machines, we can process the entire data in effecient time.

What is Lambda Architecture

Lambda architecture describes a system consisting of three layers: batch processing, speed (or real-time) processing, and a serving layer for responding to queries. Find more details at http://lambda-architecture.net

Installing Apache Storm on Windows 7

Storm installation is not actually required to run on Local standalone mode of Storm submission

Install Java, where note the java path does not contain any spaces
Install Zookeeper by downloading from its official website
Extract to c:\zookeeper
set PATH environment variable for zookeeper bin path
configure zoo.cfg
start zookeeper
Download storm and extract to storm at C:/storm
set PATH environment variable for Storm bin path
configure storm.yaml

For more reference on setting up storm cluster or installing storm on Ubuntu refer: https://storm.apache.org/documentation/Setting-up-a-Storm-cluster.html

Different Spouts

From DB
Queue
API
From text file

Different Tuple States

ASK-Storm fully processed
ACTIVATE-Deactivation to Activation
CLOSE-Spout Shutdown
DEACTIVATE-Deactivation
FAIL-Failed to process fully
NEXT TUPLE-request for next tuple emit to output collector
OPEN-Initialization

Install Hadoop 2.5.1 on Windows 7 - 64Bit Operating System

2014-10-06T23:57:00.006+05:30

This post is about installing Single Node Cluster Hadoop 2.5.1 (latest stable version) on Windows 7 Operating Systems.Hadoop was primarily designed for Linux platform. Hadoop supports for windows from its version 2.2, but we need prepare our platform binaries. Hadoop official website recommend Windows developers to use this build for development environment and not on production, since it is not completely tested success on Windows platform. This post describes the procedure for generating the Hadoop build for Windows platform.

Generating Hadoop Build For Windows Platform

Step 1:Install Microsoft Windows SDK 7.1

In my case, I have used Windows 7 64 bit Operating System. Download Microsoft Windows SDK 7.1 from Microsoft Official website and install it.
While installing Windows SDK,I have faced problem like C++ 2010 Redistribution is already installed. This problem will happen only if we have installed C++ 2010 Redistribution of higher version compared to the Windows SDK.
We can solve this issue by either not installing the C++ 2010 Redistribution by unchecked the Windows SDK on custom component selection or uninstalling from Control Panel and reinstalling the C++ 2010 Redistribution via Windows SDK again.

Step 2:Install Oracle Java JDK 1.7

I recommend everybody to download Oracle Java JDK7 and install JDK at C:\Java\ instead of default path C:\Programming Files\Java\. Since this default path contains invalid space character between “Programming” “Files”.
Now we need to configure JAVA_HOME Environment Variable with value “C:\Java\jdk1.7.0_51”. If we have already installed Java at it's default path (C:\Programming Files\Java\). We need to find its 8.3 pathname with the helpof “dir /X” command from its parent directory. The sample 8.3 pathname will look like "C:\PROGRA~1\Java\jdk1.7.0_51".
Finally we need to add Java bin path to PATH enviroment variable as “%JAVA_HOME%\bin”.

Step 3:Install Maven 3.2.1

Download latest Apache Maven from its official website and extract to C:\maven. Configure the M2_HOME Enviroment Variable with maven home directory path “C:\maven”.
Finally add the maven bin path to PATH Environment variable as “%M2_HOME%\bin".

Step 4: Install Protocol buffer 2.5.0

Download binary version of Protocol Buffer from it official website and extract it to “C:\protobuf” directory and add this path to PATH Environment Variable.

Step 5: Install Cygwin

Download the latest version of Cygwin from its official website and install at "C:\cygwin64" with ssh, sh packages.
Finally add the cygwin bin path to PATH environment variable.

Step 6: Install cmake 3.0.2

Download the latest cmake from its official website and install it normally.

Step 7: Configure “Platform” Environment Varibale.

Add the “Platform” environment variable with the value of either “x64” or “Win32” for buildin on 64-bit or 32-bit system.(Case-sensitive)

Step 8:Create Hadoop Build

Download the latest stable version of Hadoop source from its official website and extract it to “C:\hdc”. Now we can generate Hadoop Windows Build by executing the following command on Windows SDK Command Prompt.
```
mvn package -Pdist,native-win -DskipTests -Dtar
```
The above command will run for approx 30 min and output the Hadoop Windows build at C:\hdc\hadoop-dist\target” directory.

Configuring Hadoop for Single Node(Pseudo Distributed) Cluster

Step 1:Extract Hadoop

Copy the Hadoop Windows Build tar.gz file from “C:\hdc\hadoop-dist\target” and extract at “C:\hadoop”.

Step 2: Configure hadoop-env.cmd

Edit the “C:\hadoop\etc\hadoop\hadoop-env.cmd” file and add the following lines at the end of the file. The following lines will configure the Hadoop and Yarn Configuration Directories.
```
set HADOOP_PREFIX=c:\deploy
set HADOOP_CONF_DIR=%HADOOP_PREFIX%\etc\hadoop
set YARN_CONF_DIR=%HADOOP_CONF_DIR%
set PATH=%PATH%;%HADOOP_PREFIX%\bin
```

Step 3: Configure core-site.xml

Edit the “C:\hadoop\etc\hadoop\core-site.xml” file and configure the following property.

<configuration>
    <property>
        <name>fs.default.name</name>
        <value>hdfs://0.0.0.0:19000</value>
    </property>
</configuration>

Step 4: Configure hdfs-site.xml

Edit the “C:\hadoop\etc\hadoop\hdfs-site.xml” file and configure the following property.

<configuration>
    <property>
        <name>dfs.replication</name>
        <value>1</value>
    </property>
</configuration>

Step 5: Configure mapred-site.xml

Edit the “C:\hadoop\etc\hadoop\mapred-site.xml” file and configure the following property.

<configuration>
    <property>
        <name>mapred.job.tracker</name>
        <value>localhost:54311</value>
    </property>
</configuration>

Step 5: Create tmp directory

Create a tmp directory as “C:\tmp”, where “C:\tmp” is the default temperory directory for Hadoop.

Step 6: Execute hadoop-env.cmd

Execute the “C:\hadoop\etc\hadoop\hadoop-env.cmd” file from the Command Prompt to set the Environment Varibales.

Step 7: Format File System

Format the file sytem by executing the following command before first time usage.
```
%HADOOP_PREFIX%\bin\hdfs namenode -format
```

Step 8: Start HDFS

Execute the following command to start the HDFS.
```
%HADOOP_PREFIX%\sbin\start-dfs.cmd
```

Step 9: Check via Web-browser

Open the browser with address http://localhost:50070, this page will display the currently running nodes and we can browse the HDFS also on this portal.

Install Latest Hadoop 2.4.1 on Ubuntu 14.04

2014-09-27T14:47:00.002+05:30

This post is about Hadoop 2.4.1 (latest stable version) Single Node Cluster Installation on Ubuntu 14.04. The Hadoop Single Node Cluster Installation method are suitable only for beginners practicing. The Hadoop Multi Node Cluster is more suitable for production environment Since Hadoop is meant for distributed environment. The Multi Node Cluster Hadoop Installation steps are almost as same as Single Node Cluster Hadoop Installation with few configuration changes. My next post will cover the Multi Node Cluster Hadoop Installation.

The Hadoop installation requires the pre-require steps like installing Java & ssh, creating dedicated Linux user account, disabling IPv6, generating key-gen for user account. This pre-require steps requires for Hadoop node(s) communication by Secure Shell Protocol(ssh). Disable IPv6 requires since Hadoop doesn't support for IPv6.

Step 1: Install Oracle Java JDK7 on Ubuntu.

Step 2: Install SSH-Server

To install Open ssh server, execute the following command in terminal
```
sudo apt-get install openssh-server
```

Step 3: Create "hduser" user account under "hadoop" user group.

Execute the following command to create user group and user account. Give all required information while creating user account and give password as "hduser".
```
sudo addgroup hadoop
sudo adduser --ingroup hadoop hduser
sudo adduser hduser sudo
```

Step 4: Disable IPv6

Open the "/etc/sysctl.conf" file with gedit as sudo user.
```
sudo gedit /etc/sysctl.conf
```

Configure to disable the IPv6 by modifying/adding the following lines at last.

#disable ipv6
net.ipv6.conf.all.disable_ipv6 = 1
net.ipv6.conf.default.disable_ipv6 = 1
net.ipv6.conf.lo.disable_ipv6 = 1

Save & close the file then reboot the machine.
```
sudo shutdown -r now
```
Check the configuration
```
sudo sysctl -p
```

Step 5: Generate key-gen for hduser.

Execute the following command and give no password or key while generating key-gen

su - hduser
ssh-keygen -t rsa -P ""
cat $HOME/.ssh/id_rsa.pub >> $HOME/.ssh/authorized_keys

Now check the ssh for localhost
```
su - hduser
ssh localhost
```
If the above ssh is not working properly, we need to check and redo our Step 4 and Step 5 properly again.

Step 6: Download, Extract and Move Hadoop to hduser Home.

Execute the following commands on terminal to download Hadoop and extract to hduser home directory

su - hduser
cd /home/hduser/
wget http://apache.osuosl.org/hadoop/common/hadoop-2.4.1/hadoop-2.4.1.tar.gz
tar -zxvf hadoop-2.4.1.tar.gz
mv hadoop-2.4.1 hadoop

Step 7: Configure Environment Variable.

Open "$HOME/.bashrc" file with gedit as hduser.
```
gedit $HOME/.bashrc
```

Add/Modify the following Environment Variables.

export HADOOP_PREFIX=/home/hduser/hadoop
export JAVA_HOME=/usr/java/jdk1.7.0_51
export PATH=$PATH:$HADOOP_PREFIX/bin:$JAVA_HOME/bin
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_PREFIX/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_PREFIX/lib"

Save & Close the file then Execute the bash file:
```
exec bash
```
Check the Path environment variable:
```
$PATH
```

Step 8: Configure Hadoop Environment variable

Open "/home/hduser/hadoop/etc/hadoop/hadoop-env.sh" file with gedit as hduser.
```
gedit /home/hduser/hadoop/etc/hadoop/hadoop-env.sh
```
Add/Modify the following Environment Variable Path
```
export JAVA_HOME=/usr/java/jdk1.7.0_51
```
Save & Close the file

Step 9: Configure "core-site.xml" file for working temporary directory and name for File System.

Create a temp directory at hduser home
```
mkdir /home/hduser/tmp
```
Open "/home/hduser/hadoop/etc/hadoop/core-site.xml" flle with gedit as hduser
```
gedit /home/hduser/hadoop/etc/hadoop/core-site.xml
```

Add the following configurations in "core-site.xml" file. Then Save & Close the file

<configuration>
    <property>
        <name>hadoop.tmp.dir</name>
        <value>/home/hduser/tmp</value>
        <description>Base temporary directories</description>
    </property>
    <property>
        <name>fs.default.name</name>
        <value>hdfs://localhost:54310</value>
        <description>Default file system name</description>
    </property>
</configuration>

Step 10: Configure "hdfs-site.xml" file for data directory and replication.

Create a data direcotry directory
```
mkdir /home/hduser/tmp/dfs/data
```
Open "/home/hduser/hadoop/etc/hadoop/hdfs-site.xml" flle with gedit as hduser
```
gedit /home/hduser/hadoop/etc/hadoop/hdfs-site.xml
```

Add the following configurations in "hdfs-site.xml" file. Then Save & Close the file

<configuration>
    <property>
        <name>dfs.replication</name>
        <value>1</value>
    </property>
    <property>
        <name>dfs.data.dir</name>
        <value>/home/hduser/tmp/dfs/data</value>
    </property>
</configuration>

Step 11: Configure "mapred-site.xml" file for Host and Port number of Job Tracker.

Open "/home/hduser/hadoop/etc/hadoop/mapred-site.xml" file with gedit as hduser
```
gedit /home/hduser/hadoop/etc/hadoop/mapred-site.xml
```

Add the following configurations in "mapred-site.xml" file. Then Save & Close the file

<configuration>
 <property>
        <name>mapred.job.tracker</name>
        <value>localhost:54311</value>
        <description>Host,port for MapReduce Job Tracker</description>
    </property>
</configuration>

Step 12: Configure "yarn-site.xml" file for node manager and resource manager configurations.(Configuring yarn is optional)

Open "/home/hduser/hadoop/etc/hadoop/yarn-site.xml" file with gedit as hduser
```
gedit /home/hduser/hadoop/etc/hadoop/yarn-site.xml
```

Add the following configurations in "yarn-site.xml" file. Then Save & Close the file

<configuration>
    <property>
        <name>yarn.nodemanager.aux-services</name>
        <value>mapreduce_shuffle</value>
    </property>
    <property>
        <name>yarn.nodemanager.aux-services.mapreduce_shuffle.class</name>
        <value>org.apache.hadoop.mapred.ShuffleHandler</value>
    </property>
    <property>
        <name>yarn.resourcemanager.resource-tracker.address</name>
        <value>localhost:8025</value>
    </property>
    <property>
        <name>yarn.resourcemanager.scheduler.address</name>
        <value>localhost:8030</value>
    </property>
    <property>
        <name>yarn.resourcemanager.address</name>
        <value>localhost:8050</value>
    </property>
</configuration>

Step 13: Format namenode and start Hadoop dfs

Execute the following command to format namenode and to start HDFS

/home/hduser/hadoop/bin/hdfs namenode -format
/home/hduser/hadoop/sbin/start-dfs.sh

List Hadoop Nodes
```
jps
```
It will list all tasks running like NameNode, DataNode, SecondaryNameNode, JobTracker, TaskTracker

The Hadoop Installation is completed, Now we can use Hadoop.

WIFI hotspot on Windows

2014-09-25T01:11:00.002+05:30

This post is about creating our own WIFI hotspot on Windows Machine with out any software.

Only pre-requiest for creating WIFI hotspot is that our Windows machine should have incoming Internet via Ethernet or WIFI dongles,etc and a WIFI Device to share as hotspot. We can create our WIFI hotspot with simple windows commands by following the below steps:

Open control Panel, Go to Open Network and Sharing Center and click on Change Adapter Settings.
Go to Sharing Tab of the Ethernet properties and Enable the check-box of Allow other network users to connect through this computer's Internet connection.
Open notepad,type the following commands and save as batch file with filename as "hotspot-start.bat".

netsh wlan set hostednetwork mode=allow ssid=wifiname key=wifipassword
netsh wlan start hostednetwork

Open notepad, type the following commands and save as batch file with filename as "hotspot-stop.bat".

netsh wlan stop hostednetwork

Now we can start WIFI hotspot by executing hotspot-start.bat file and stoping by hotspot-stop.bat file.

Now enjoy the WIFI hotspot without any software and by simple commands.

Hadoop

2014-09-18T20:05:00.001+05:30

This post is about basic concepts of Big Data and Apache Hadoop framework. It is essential to know about Big Data for today's IT industry since Big Data technologies are getting more popular and powerful now a days.

Big Data:
Big Data is nothing but storing or processing LARGE quantity of data sets. Data can be

Structured Data (ex: RDBMS)
Semi Structured Data (ex: XML Files)
Unstructured Data (ex:Flat files)

Big data overcomes the challenges of traditional databases such as Volume, Velocity, Variety, Complex Data sets. 95% of Today's Data are created in the last three years so the state of data is changed a lot. Popular Companies such as Amazon, Google, Facebook, Twitter, Yahoo have realized the power of Big data and doing R&D on Big Data.

Apache Hadoop:

Apache Hadoop is an open source Big Data framework for distributed storage and distributed processing for very large data sets on computer clusters. Apache Hadoop is a Master-Slave Shared Nothing Architecture.

Apache Hadoop Core Contains

HDFS (Hadoop Distributed File System) is for Distributed Storage.

Map-Reduce (MR) is for Distributed Processing

Yarn is for Distributed Scheduling

Apache Hadoop was developed by Yahoo based on the white papers of Google MapReduce and Google File System.

The Design principles of Apache Hadoop are

To solve computation problem of large data sets Hadoop used large number of commodity hardware. Example:

Yahoo uses 45000 nodes of Hadoop Cluster
Facebook is having largest Hadoop cluster in the planet with 100PB
Twitter generates 400Million tweets a day.

Automatic Parallelization and Distribution.
Automatic Recovery and Fault Tolerance.
Clean and Simple By Map Reduce
By using large number of commodity hardware solved computation problem on large data sets.(ex:Yahoo uses more than 45000 machines with Hadoop Open Source of Map-Reduce)

Comparison of Apache Hadoop and Traditional RDBMS

Apache Hadoop	Traditional RDBMS
Schema on read	Schema on write
For Structure, Semi Structured & Un-Structured	Only for Structured

Hadoop Distributed File System (HDFS):
Hadoop Distributed File System (HDFS) is the Distributed storage area where data are stored for Hadoop processing. HDFS is a Master-Slave architecture where one device controls one or more slave devices.

Master contains Name-Node, Secondary-Name-Node, Job-Tracker.

Slave contains Data-Node, Task-Tracker.

Name-Node

Name Node controls all Data Nodes
Controller of File System operations such as file creation, deletion
Maintains File System Meta-information
Maintains memory map of the entire cluster

Manages Block Mapping which knows all information of data.

Monitors health

Most important node since It is the Single Point Of Failure (SPOF), (ie: if name node goes down, cluster goes down)

Secondary Name-Node

Snapshots (Backup) the Name Node for restoring.
It is not fail over for Name Node

Meta-Data backup on rebuild

No high availability

Data-Node

Stores Actual data and Replicated into 3 nodes by default.

Responsible for Block operations

Handles client requests by passing data to Name Node.

Sends heartbeats to Name-Node with block report (default by every 3 sec.)
Job Tracker: Job tracker is the controller for all task tracker

Master-Slave Flow

Job-Client submits job to Job-Tracker
Job-Tracker talks to Name-Node,creates execution plan and submits work to Task-Tracker
Task-Tracker reports progress via heart beats, manages phases and updates states

Defult HDFS Block is 64MB
HDFS Properties

Large Data
N Times Replication
Failure is normal rather than exception
Fault Tolerence

HDFS Features

Rack awareness
Reliable Storage
High Throughput

Map-Reduce:

Map Reduce is Programming Paradigm.
A Execution Engine which uses Mappers and Reducers
Actually these are code for processing the Large Datasets.
Description on how Map-Reduce Works:

Let us consider our input data contains "Deer Bear River Car Car River Deer Car Bear".
Split Phase(hidden phase): Splits input into no of input splits.
Map Phase: Transforms the input split into Maps( key-value pair) based on user defined.
Shuffle & Sort(hidden phase): Moves map output to reducers and sorts them by the key.
Reduce Phase: Aggregate Map based on user defined code
Final Result: Determines how the file are parsed into the map/reduce pipeline and produces final result.

Hadoop Technology Stack:

Hadoop is collection of framework,the following are the popular Hadoop framework stack.

For Data Access

PIG: Hige-level data-flow scripting Language and execution framework
HIVE: Data-warehouse infrastructure allows SQL-like

For Data Storage

HBASE: Bigtable-like structured storage system, millions of columns and billions of rows
Cassendra: Scalable multi-master NO-SQL database with no single point of failure

For Interation, Visualization, Execution & Development

HCatalog: Meta table management
Lucene: Indexing tool for Searching tool with wildcard
Crunch: Used for Map-Reduce pipe lining with shuffle and sorting

For Data Serialization

Avro: Data serialization system
Thirft: multi language/ language-neutral making framework

For Data Intelligence

Mahout: Machine Learning & Data Mining tool mainly used for Business Intelligence

For Data Integration

Sqoop: Import and export data between RDBMS and Hadoop
Flame: Log Data collection system
Chukwa: Data collection system

For Management & Monitoring

Ambari: Web based tool for monitoring and managing
Zookeeper: High-performance coordination tool
Oozie: Schedule and workflow tool

The typical Hadoop Ecosystem may contain HDFS(Hadoop Distributed File System), HIVE, PIG, HBase, Zookeeper, Sqoop, Flame, Oozie. But it is completely depends upon individuals requirement and experience.

Preparing for Pirate Free

2014-09-18T17:59:00.001+05:30

This post is about how to make software piracy free world. I really want to write about this post is to make awareness on Software Piracy since it is illegal, that most people are unaware about it

What is Software Piracy?

Illegal usage, copy, distribute software without ownership or legal rights. So If we are using a paid software product without purchasing it means we are using it Illegally, the good thing is it does not hurt any person directly. There is no such a strict rules on pirated software usage on most of the countries. Most of us are still using pirated software even without aware that it is illegal.

There are Three options in our hand:

Let us continue with Microsoft Windows by purchasing licence from Online for cheap price
Once they are ready to buy software and gonna spend huge amount, they can consider Apples Mac Desktop or Laptop.
Best way is Linux obviously.

Why should we move towards Linux?

Now Linux has evolved a lot. It is not how, what we know Linux was 5 or 10 years before. It is more powerful now than Windows or Mac. People those who started to use Linux will love a lot. And It is FREE

Linux Beginners may face problem like which software should be used for particular task. On windows we are very familiar with the softwares. For example to do Document processing, Presentations, Spreed sheet works we use Microsoft Office, for images most people use Adobe Photoshop, for movies & songs we use VLC Media Player. The same software we can find by maximum 5 minute of Google search.

Let us stop this cheep activity of using pirated software. And let us enjoy pirate free software and make everyone feel good.

[Solution] WIFI Driver problem for HP 15-n011tu

2014-09-07T16:30:00.002+05:30

I have purchased an HP Pavilion 15-n011tu laptop recently with the operating system Ubuntu 12.04. The laptop is completely fine when I purchase,but after I upgraded to Ubuntu 14.04 version, only WIFI has stoped working. Even we can switch on or off the WIFI. This is a very common problem for all those who purchase HP laptop with Ubuntu OS, since HP is not supporting drivers for any Linux destro.

Solution 1: Solution for this problem is we can purchase Windows 7 or 8, since HP is providing driver support for Windows 8 (both 32 & 64 bit) and Windows 7(only 64 bit). Currently HP Windows drivers are available at the following URL address

http://h10025.www1.hp.com/ewfrf/wc/softwareCategory?cc=us&lc=en&product=5440120

Solution 2: But purchasing Windows OS is costly. Now a days, It is trend to migrating Windows to Linux for developers. In that case, Without WIFI or Internet any laptop is almost waste.

Please follow the following steps for Ubuntu Operating System.

Step 1:Open the terminal and type "lspci" you can find list PCI buses and devices connected to the system.

Step 2: Note your laptop WIFI model, My laptop WIFI Model is MEDIATEK Corp. MT7630e.

Step 3: If your laptop WIFI model is same as mine (MEDIATEK Corp. MT7630e), download the driver by Clicking Here. Once downloaded the driver, extract and copy files to /etc/ directory as /etc/MT7630E

[NOTE: if your WIFI model is different, you need to search for your WIFI model from Internet]

Step 4: Create Wifi.sh file under your home directory, then copy paste the following lines and save the file.

cp /etc/MT7630E/firmware/Wi-FI/MT7650E234.bin /lib/firmware
cd /etc/MT7630E/rt2x00
make clean
make
bash load.sh
exit

Step 5: For every restart of the laptop execute the Wifi.sh file as root

sudo ./Wifi.sh

Now WIFI will start working on your Ubuntu Operating System also. Thank You :-)

Install Spring Tool Suite on Ubuntu

2014-05-11T23:56:00.002+05:30

This post is about installing Spring Tool Suite (STS) on Ubuntu. The Spring Tool Suite is an Eclipse-based development environment that is customized for developing Spring applications.

Step 1:Download the latest Spring Tool Suite for Linux from STS official website: http://spring.io/tools/sts/all

Step 2:Extract into any folder which you prefer. My extracted Spring Tool Suite locations is /home/harishshan/springsource

Step 3:Create the Menu icon for quick access

sudo nano /usr/share/applications/STS.desktop

Step 4:Enter the following content

[Desktop Entry]
Name=SpringSource Tool Suite
Comment=SpringSource Tool Suite
Exec=/home/harishshan/springsource/sts-3.4.0-RELEASE/STS
Icon=/home/harishshan/springsource/sts-3.4.0-RELEASE/icon.xpm
StartupNotify=true
Terminal=false
Type=Application
Categories=Development;IDE;Java;

Step 5: Now you can check from Quick Menu by typing "Spring"

Database Replication Master Slave

2014-05-11T23:40:00.002+05:30

This post is about how to perform to Database Replication Slave to Master. I have used the Green Font to represent Master Server and Red Font to represent Slave Server.

Step 1:CHANGING MySQL CONFIGURATION
We need to add some extra configuration properties in the my.ini/my.cnf file. This step is must to perform replication.The following sub steps will describe in detail.

Open my.ini file for windows or my.cnf file for Linux
Search for [mysqld]
Add the following properties under [mysqld] section

server-id=1
log-bin=mysql-bin

save the my.ini file and Restart the mysql services
To check the result execute the following command in mysql console
```
show binary logs;
```
If it shows logs, Binary logging has been initiated and we can configure mirroring
Perform the same steps on slave database.

Step 2: CRATE USER AND GRANT RELICATION AND PREVILEGES

Create user

create user 'replication'@'%' identified by 'PASSWORD';

Grant replication

grant replication slave on *.* to 'replication'@'%';

Grant privileges

grant all privileges on *.* to 'replication'@'%' with grant option;

Perform the same steps on slave database with different password

Step 3: CHECKING MASTER STATUS

show master status;

Step 4:SETTING UP THE SLAVE

CHANGE MASTER TO
-> MASTER_HOST=’192.168.2.2′,
-> MASTER_PORT=3306,
-> MASTER_USER=’replication’,
-> MASTER_PASSWORD='PASSWORD',
-> MASTER_LOG_FILE=’mysql-bin.000019′,
-> MASTER_LOG_POS= 2186;

where

MASTER_HOST is IP address of Master
MASTER_LOG_FILE is credentials of master status (from Step 3)
MASTER_LOG_POS is credentials of master status (from Step 3)

Restart mysql from services on both master and slave

Step 5: CHECK MIRRORING

Go to slave database execute the following command

show slave status \G;

Output:

*************************** 1. row ***************************
Slave_IO_State: Waiting for master to send event
Master_Host: 10.195.2.60
Master_User: replication
Master_Port: 3306
Connect_Retry: 60
Master_Log_File: mysql-bin.000001
Read_Master_Log_Pos: 642
Relay_Log_File: India-Server-relay-bin.000003
Relay_Log_Pos: 409
Relay_Master_Log_File: mysql-bin.000001
Slave_IO_Running: Yes
Slave_SQL_Running: Yes
Replicate_Do_DB:
Replicate_Ignore_DB:
Replicate_Do_Table:
Replicate_Ignore_Table:
Replicate_Wild_Do_Table:
Replicate_Wild_Ignore_Table:
Last_Errno: 0
Last_Error:
Skip_Counter: 0
Exec_Master_Log_Pos: 642
Relay_Log_Space: 571
Until_Condition: None
Until_Log_File:
Until_Log_Pos: 0
Master_SSL_Allowed: No
Master_SSL_CA_File:
Master_SSL_CA_Path:
Master_SSL_Cert:
Master_SSL_Cipher:
Master_SSL_Key:
Seconds_Behind_Master: 0
Master_SSL_Verify_Server_Cert: No
Last_IO_Errno: 0
Last_IO_Error:
Last_SQL_Errno: 0
Last_SQL_Error:
Replicate_Ignore_Server_Ids:

Check Last_IO_Error,If it has error, do the steps provided in ERROR section
Else replication has been performed successfully and you can check executing commands from master to check its validity.

ERROR

ERROR#1 -> Can occur if operation is performed directly on slave instead of master.
ERROR#2 -> Can occur if there is a problem in network.
For ERROR#1 drop the replication user, flush the binary logs and restart the mysql server on both master and slave servers.

drop user 'replication'@'%';
flush binary logs;

Now proceed the same procedure again from Step 1

Note: If two servers are not of same architecture(i.e One server is of 64 bit and another is of 32 bit machine). We should select only 64 bit machine for Master and 32 bit machine for Slave.

Schedule Task on Ubuntu Using Cron Jobs

2014-05-11T23:03:00.003+05:30

This article is about the Cron Job and how to schedule task on Ubuntu machine using Cron jobs. The cron is a time-based job scheduler in Unix-like computer operating systems.

The word "Crontab" is derived from chronos (Time in Greeks) and tab stands for table. Crontab is useful for scheduling the task automatically run at regular interval as the background process. Crontabs are useful for taking backups, synchronizing files, etc.

Before doing all other stuffs, first we will change the default editor to nano editor by typing the following command in terminal.

export EDITOR="nano"

To schedule new /edit crontab entries for specific time

crontab -e

This will open the nano editor with the default commented scheduling with five stars to allow our task scheduling. we can schedule our tasks here as follows

* * * * * /home/harishshan/example.sh

This will execute the example.sh for every minute. The following is an easy way to remember the crontab format

* * * * * command to be executed
- - - - -
| | | | |
| | | | ----- Day of week (0 - 7) (Sunday=0 or 7)
| | | ------- Month (1 - 12)
| | --------- Day of month (1 - 31)
| ----------- Hour (0 - 23)
------------- Minute (0 - 59)

If you leave star(asterisk), it means every.If you leave ?, it means any.

Examples:

Schedule	Crontab Syntax
Daily 10AM	0 10 * * *
October 12th 12.20 PM	20 12 12 10 *
5 After 4 Every Sunday	5 4 * * 0
Every 15 minutes	/15 * * *
Every Friday 1 AM	0 1 * *5

To list crontab entries

crontab -l

To list scheduled cron jobs of a particular user

crontab -u root -l

To remove all crontab entry

crontab -r

To prompt before deleting crontab

crontab -i -r

Note: By default crontab saves the output in user's mailbox which we configured as MAILTO in the crontab

MAILTO="yourname@yourdomain.com"

Instead you can configure to output to separate logfile like as follows

* * * * * /home/harishshan/example.sh >> /var/log/example_log.log 2>&1

Where

/var/log/example_log.log represents log file
1 represents STDOUT
2 represents STDERR

How to Install Java on Ubuntu

2014-04-29T23:19:00.001+05:30

This article is about installing the Oracle Java JDK7 (Java Development Kit 7) on the Ubuntu Operating System.

Everybody knows that Sun Java was migrated to Oracle Java with Open source licence. Similarly IBM and Open source community has their own standard Java JDK. I personally prefer Oracle's Java JDK, Since majority of the cooperates uses Oracle JDK,I also recommend Ubuntu Java beginners to start with Oracle JDK. So don't confuse while downloading/Installing Oracle Java JDK.The following steps will guide you to install Oracle JDK in Ubuntu in a very easy manner.

To install Oracle JDK in Ubuntu, Advanced Package Tools (apt) provides the many providers for oracle. The webupd8team provider provides the following command to install the Oracle JDK.

To install Oracle JDK 7, execute the following commands in the terminal.

sudo apt-get install python-software-properties
sudo add-apt-repository ppa:webupd8team/java
sudo apt-get update
sudo apt-get install oracle-java7-installer

By executing the above command in the terminal, we installed Java in Ubuntu, But we still need to set the environment variables. To set the JAVA_HOME environment variable, execute the following commands in the terminal.

sudo update-alternatives --config java

This will return the installed java version in the system.

There are 1 choices for the alternative java (providing /usr/bin/java).
Selection   Path                                       Priority   Status
-----------------------------------------------------------------------------
  *0        /usr/lib/jvm/java-7-oracle/jre/bin/java    1062       auto mode 
   1        /usr/lib/jvm/java-7-oracle/jre/bin/java    1062       manual mode

Press enter to keep the current choice[*], or type selection number:

Now copy the path from your preferred installation and then edit /etc/environment file by the command

sudo nano /etc/environment

This will open the environment file in nano editor, in the opened file add the following line

JAVA_HOME="/usr/lib/jvm/java-7-oracle

After adding this line, press ctrl+o and enter to save the file and ctrl+X to close the file. Finally we installed the Oracle JDK 7 in the Ubuntu Operating system.

Transfer Bulk Data via Torrent file

2014-04-29T00:06:00.002+05:30

This article is all about the Torrent File Transfer Mechanism and its features. How to optimize Torrent client and how to create our own Torrent file for transferring bulk data instead downloading Movies and Software from other Torrent sites.

What is Torrent?

Torrent is the protocol for distributing files. It uses Peer-to-Peer data transmission. Its advantage over plain HTTP is that when multiple downloads of the same file happen concurrently, the downloaders upload to each other, making it possible for the file source to support very large numbers of downloaders, with only a modest increase in its load.Torrent's peer protocol can operate over TCP or uTP.

Torrent is created by Bram cohen in 2001 and now handled by BitTorrent.inc company

Torrent file distribution consists of these entities:

An ordinary web server
A static 'metainfo' file
A Torrent tracker
An 'original' downloader
The end user web browsers
The end user downloaders

Torrent Files

Torrent files are also known as metainfo files which are bencoded dictionaries which contains metadata like name, piece length, pieces, length, path and announce URL for trackers

Trackers

Tracker GET requests have the following keys:

info_hash- Bencoded form of info values
peer_id-Random generated id at the start of new download
ip-Trackers machines IP address
port-Port number for listening on peer
uploaded-Total amount uploaded so far
downloaded- Total amount downloaded so for
left-Remaining amount has to download
event-Announcement events such as started, completed, stopped(empty)

How Torrent Network works?

Seed is the user or computer that has a file can be downloaded. There are also so-called leechers/peers. Leechers are the users or computers who want to download the file. When one leecher has managed to download the files 100% of the seed, then the leecher's role will change to seed. Therefore torrent source files are not fixated on single sources.

Advantage of Torrent

It will be very faster when the files are being download by many users. But normal download will fail s to serve if number of downloaders increases.
By downloading via torrent, the same file can be downloaded from many sources.
The leecher can become seeder once the download complete to serve other leecher.
It consume less CPU utilization compared to normal download.
It allows to transfer files with anyone, anywhere.

Tips to optimize Torrent Client[Some Popular Torrent Client Softwares are BitTorrent, uTorrent, Vuze, qBittorrent.]

Go to Options-> setup guide -> uncheck the bandwith
Go to Options-> Preferences -> Advanced -> Change "net.max_halfopen" value to 50 by selecting the line, modifying the value at the bottom to 50 and clicking Set.
At the same Advanced screen, Change "bt.transp_disposition" value to 255 by selecting the line, modifying the value at the bottom to 255 and clicking Set.
More Peers means more speed, To get more peers, right-click the entry on the list of peers , and click Update Tracker.
Increase the number of connections by Options -> Preferences -> Bandwidth -> Number of Connections. Experiment by increasing the number of global/max connections in steps of 25
Increase the speed of particular torrent by setting the download limit to unlimited and upload limit to very less.

How to transfer files via Torrent file.

Step 1: Create Built-in Tracker

a) Open the utorrent Software->Options->Preferences

b) Go to Connections and set the port number which is opened/unused

c) Then go to BitTorrent and set the IP/Hostname to report to tracker: [as your sender IP address]

d) And go the Advanced and set true for bt.enable_tracker and save the setting

Step 2:Create Torrent file

a) Click File->Create New Torrent

b) Select Source which you want to transfer

c) Give the Torrent Properties Tracker values as "http://[Sender IP Address][Port]/announce"

where Port and Sender IP Address are we already configured in tracker

d) Delete if any other trackers found other than our tracker.

e) Give tick Start Seeding and Private torrent. and press Create

Now this will create a .torrent extension file

Step 3:Download the file from any other system like as normal as we download movies using .torrent file.

Command Prompt Full Screen on Windows 8/7

2013-11-13T17:40:00.002+05:30

In Windows 8/7 and Vista we could not open full screen Command Prompt. It makes more trouble especially for the Developers who majorly work on the command prompt. By following the simple steps we can open our Windows Vista / 7 / 8 Operating System Command Prompt in full screen.

Full Screen Command Prompt
Step 1: Open the command prompt by typing "cmd" in the Windows Run.

Step 2: Right click on the title bar of the command prompt and select "default" option to open the "Console Window Properties".

Step 3:Open the Layout tab and change the Screen Buffer Size as Width:1500 and Height: 500 and change the Window Size as Width: 168 and Height: 55 and press OK.

Step 4: Close the current command prompt and open the command Prompt using Step 1 and enjoy the full screen Command Prompt in Windows Vista / 7 / 8.

Read Java Properties File

2013-11-02T23:16:00.000+05:30

The properties files are generally used as configuration file for java programs.In Java, there is a special class for manipulating properties file called java.util.Properites. Properties are configuration values managed as key and value pairs since it is basically a Hashtable that can be saved/loaded from stream. In each pair, both key and value are String values.

Example Program for Reading Properties File

ReadProperties.java

import java.util.Properties;
import java.io.FileInputStream;
class ReadProperties {
  public static void main(String arg[]) {
    try {
      Properties properties=new Properties();
      properties.load(new FileInputStream("D:\\config.properties"));
      System.out.println("Message from Properties file: "+ properties.getProperty("message"));   
    }
    catch(Exception e) {
      e.printStackTrace();
    }
  }
}

config.properties

message=All The Best

Output:

Message from Properties file: All The Best