Grid and Cloud Computing Laboratory

Grid and Cloud Computing Laboratory

VII Semester of B.Tech

As per the curricullam and syllabus

of

Bharath Institute of Higher Education & Research

(Grid and Cloud Computing Laboratory)

PREPARED BY

Dr. S. Chakravarthi

Mr. A.V. Allin Geo

NEW EDITION

1

SCHOOL OF COMPUTING

DEPARTMENT OF COMPUTER SCIENCE & ENGINEERING

2

LAB MANUAL

SUBJECT NAME:

GRID AND CLOUD COMPUTING LABORATORY

SUBJECT CODE: BCS7L1

Regualtion R2015

(2015-2016)

3

BCS7L1 GRID AND CLOUD COMPUTING LABORATORY L T P C

Total Contact Hours - 30 0 0 3 2

Prerequisite –Distributed Computing, Operating Systems, Grid and Cloud Computing.

Lab Manual Designed by – Dept. of Computer Science and Engineering.

OBJECTIVES

Be exposed to tool kits for grid and cloud environment.

Be familiar with developing web services/Applications in grid framework

Learn to run virtual machines of different configuration.

COURSE OUTCOMES (COs)

CO1 Use the grid and cloud tool kits.

CO2 Design and implement applications on the Grid.

CO3 Design and Implement applications on the Cloud.

CO4 Connect Multiple System Using Zonal Server and JVishwa

CO5 Implement the Theorem using Naive Bayes Approach.

CO6 Implement the Virtual Machine.

MAPPING BETWEEN COURSE OUTCOMES & PROGRAM OUTCOMES

(3/2/1 INDICATES STRENGTH OF CORRELATION) 3- High, 2- Medium, 1-Low

COs PO1 PO2 PO3 PO4 PO5 PO6 PO7 PO8 PO9 PO10 PO11 PO12 PSO1 PSO2 PSO3

CO1 3 2 2 2 3 3 3

CO2 3 2 2 3 3 3

CO3 2 3 3

CO4 2 2 3 3 3

CO5 2 2 2 3 3

CO6 2 2 3 2 2 3 3

Category Professional Core (PC)

Approval 37th Meeting of Academic Council, May 2015

LIST OF EXPERIMENTS

1. Connecting Zonal Server with JVishwa. 2. Find the Prime Number for largest interval using Grid Computing. 3. Calculate the Matrix multiplication using Grid Computing. 4. Find procedure to run the virtual machine of different configuration. Check how

many virtual machines can be utilized at particular time Find the missing dataset using hadoop and map reduce.

5. Find procedure to attach virtual block to the virtual machine and check whether it holds the data even after the release of the virtual machine Classification using Naïve bayes approach.

6. Install a C++ compiler in the virtual machine and execute a sample program. 7. Show the virtual machine migration based on the certain condition from one

node to the other. 8. Find procedure to install storage controller and interact with it. 9. Write a word count program to demonstrate the use of Map and Reduce tasks.

4

BCS7L1-GRID AND CLOUD COMPUTING LABORATORY

LIST OF EXPERIMENTS

S.NO NAME OF THE EXPERIMENT

1 Connecting Zonal Server with JVishwa

2

Find the Prime Number for largest interval using Grid Computing.

3

Calculate the Matrix multiplication using Grid Computing.

4

Find procedure to run the virtual machine of different configuration. Check

how many virtual machines can be utilized at particular time Find the

missing dataset using hadoop and map reduce.

5 Find procedure to attach virtual block to the virtual machine and check

whether it holds the data even after the release of the virtual machine

Classification using Naïve bayes approach.

6 Install a C++ compiler in the virtual machine and execute a sample

program.

7 Show the virtual machine migration based on the certain condition from one

node to the other.

8 Find procedure to install storage controller and interact with it

9 Write a word count program to demonstrate the use of Map and Reduce

tasks

5

CONTENT

S.NO

NAME OF THE EXPERIMENT

PAGE NO

1 Connecting Zonal Server with JVishwa 5

2

Find the Prime Number for largest interval using Grid

Computing.

8

3

Calculate the using Grid Computing. 13

4

Find procedure to run the virtual machine of different

configuration. Check how many virtual machines can be

utilized at particular time Find the missing dataset using

hadoop and map reduce.

17

5 Find procedure to attach virtual block to the virtual machine

and check whether it holds the data even after the release of the

virtual machine Classification using Naïve bayes

approach.

21

6 Install a C++ compiler in the virtual machine and execute a

sample program.

24

7 Show the virtual machine migration based on the certain

condition from one node to the other.

27

8 Find procedure to install storage controller and interact with it.

28

9 Write a word count program to demonstrate the use of Map and

Reduce tasks.

30

6

Ex NO:1 CONNECTING ZONAL SERVER WITH JVISHWA

AIM:

Construction of uniform cluster in the grid using P2P middle ware

ALGORITHM:

1. Copy JVishwa and ZonalServer file into the bin of java folder.

2. Open the command prompt window and change the directory to the bin of java folder.

3. Execute the below command in the server machine “ java –jar ZonalServer.jar”

4. Give Zonal server id as 0.

5. Now the adjacency table has been created. And clients are yet to be connected.

6. In client machine open the command prompt window and change the directory as

same as server.

7. Find the IP address of the server machine and make a note.

8. Execute the below command in the server machine “java –jar jVishwa.jar (IP

Address of the server)”.

9. Now the client is connected to the server and the adjacency table had been

updated in the server machine.

10. Repeat the same process in other three client machines.

11. Now the server and client machine has been connected and ready for the

program execution.

SOURCE CODE:

1. Message on Server

JVishwa.ZonalServer.messaging.Add to Adjacency table

Row is inserted in the list

Adj Table

192.168.1.120

Column……….0

………………………

No of rows……..1

Jvishwa .messaging .joinmessage to ZonalServer

Error is here

Position is here

7

Reply send

Jvishwa.Zonal Server messaging Add to Adjacency Table

Row is inserted in the list

JVishwa .join messaging.AdjacencyTable

192.168.1.122 192.168.1.121 192.168.1.120

Column ……..2

192.168.1.122 192.168.1.121 192.168.1.120

Column …………….2

192.168.1.122 192.168.1.121 192.168.1.120

Column ………………2

192.168.1.122 192.168.1.121 192.168.1.120

Column…………………2

Number of rows….3

Jvishwa ZonalServer.messaging.Remove from .Adjacency Table

Jvishwa.messaging.Rep To Zonal Server

Jvishwa .join.messaging.Adjacency Table Req

Jvishwa .join.messaging.Adjacency Table Req

2. Grid Node Command

C:\Documents and Settings\Administrator> cd Desktop

C:\Documents and Settings\Administrator\desktop>java –jar JVishwa Jar 192.168.1.119

Message

Routing

Table-1

Neighbour-2

Leaf set-3

Other zonal nodes.ge use with caution will slow down system> Node id-

Message:::jVishwa.messaging.join rep to unstructured form::192.168.1.121 join request is receive

Local node id is…192..168.1.120 set size

is 0 Adding ….192.168.1.121

Message:::jVishwa.messaging join req To Unstructure from::192.168.1.122 Join req is received

Local node Id is 192.168.1.120 set size adding….192.168.1.122 is …1

3. Grid Node Command

C:\document and setting\Administrator>cd desktop

C:\document and setting\Administrator\desktop>java –jar jVishwa.jar 192.168.1.11

MESSAGE

Zonal server reply message is receiver local node id is 192.168.1.121 set size is adding….192.168.1.120

Sending 192.168.1.120

Size of vector is……..0

It took …..1016 milliseconds to join gri

Routing

Table-1

Neighbour-2

Leaf set-

Other Zone nodes-gc use with caution will slow down system> Node id-5

Node 192.168.1.120 joined

Local node id is ….192.168.1.121 set size is 1

Local node id is ….192.168.1.121 set size is 1

192.168.1.121.

192.168.1.122

4. Grid Node Command C:\Documents and Settings\Administrator> cd Desktop

8

C:\Documents and Settings\Administrator\desktop>java –jar JVishwa jar 192.168.1.119

Messag

Zonal Server reply message is received

Local Node id………………….192.168.1.122 Set Size is ………………0

Adding ………………192.168.1.121

Local Node id………………….192.168.1.122 Set Size is ………………1

Send 192.168.1.120

Sending the message to join req to unstructured 192.168.1.127 Size of vector is 0

It took -1531 milliseconds to join grid

Routing table – 1

Neighbour – 2

Leaf Set – 3

Other Zonal node - gc use with caution will slow down system> Node Id -5

192.168.1.122

192.168.1.126 192.168.1.12……………..

…………………………………………………

RESULT :

Thus the uniform cluster has been connected in the grid using P2P middleware

9

Ex. NO: 2 PRIME NUMBER

AIM:

To calculate the Prime number for huge interval using grid nodes.

ALGORITHM:

1. Connect the clients with server using grid in P2P middleware.

2. Copy the prime.java and paste it in the bin of the java folder.

3. Find the IP Address of the first client machine connected to the cluster and make a note.

4. In the Primeclient.java provide IP address of any one of the client node.

5. From the remote machine execute the Prime client program.

6. Now the work will be distributed to the clients equally and executed different interval in each

client.

7. This execution process can be monitored by server.

8. If any clients don’t respond, then that work will be shared by the other system.

SOURCE CODE:

import jvishwa.Context;

import jvishwa.Result;

import jvishwa.VishwaSubTask;

import java.util.Vector;

import java.io.FileInputStream;

import java.io.ObjectInputStream

import jvishwa.file.*;

import java.io.PrintStream;

import java.io.FileOutputStream;

public class Prime extends VishwaSubTask

{ Vector v; VishwaFile vfile=null;

//Constructor

public Prime() {

v=new Vector();

}

//calculation of prime public

void run(Context c) {

//Accessing the parameters from the context

int startpoint=Integer.parseInt((String)c.get("fromval")); int

endpoint=Integer.parseInt((String)c.get("toval")); //File Service for creating a file

FileService fileService=new FileService(this);

vfile=fileService.createFile("result");

10

PrintStream ps=null;

try {

ps=new PrintStream(new FileOutputStream(vfile));

}

catch(Exception e) {

e.printStackTrace();

}

//Calculation of prime

for(int i=startpoint;i<=endpoint;i++)

{ if(isPrime(i)) ps.println(i+"");

}

ps.close();

}

// Algorithm for calculation of prime private boolean isPrime(int n) {

int max=(int)Math.sqrt(n); for(int

div=2;div<=max;div++) {

if(n%div==0) return false;

}

return true;

}

//Aggregating the results...

public Result callback() { Result r=new

Result(); r.putFile(vfile);

return r;

}

//Deserialization method for getting the object public Object getObject(String fileName) {

try

{

FileInputStream fin=new FileInputStream(fileName); ObjectInputStream ois=new

ObjectInputStream(fin); Object o=ois.readObject();

ois.close(); return o;

}

catch(Exception e)

{


}

return null;

}

}

PRIMECLIENT

// prime numbers in a huge interval

import jvishwa.client.*;

import jvishwa.query.*;

import jvishwa.metric.*;

import jvishwa.task.SchedulerType;





import java.io.BufferedReader;

11

import java.io.File;



import java.io.InputStreamReader;

public class PrimeClient {

public static void main(String args[])

{

//Getting the instance of client manager

ClientManager manager=ClientManager.getInstance(); Metric

metric=new Metric();

Query query=new Query(metric); //Setting the

configuration parameters

query.setLowerBound(5);

query.setMemoryFractionValue(0.3);

query.setCPUFractionValue(0.7);

manager.setConditionType(ConditionType.DEFAULT_TYPE); manager.setMetric(metric);

manager.setQuery(query);

manager.setSurplusValue(0);

manager.setMinDonors(2);

manager.setMaxDonors(3);

manager.setReplicaSize(1);

manager.setSchedulerType(SchedulerType.DYNAMIC);

manager.setGridNodeIP("172.16.1.68");

try {

manager.initilize();

System.out.println("Press any key to start the execution...");

try

{

BufferedReader input = new BufferedReader(new InputStreamReader(System.in));

input.readLine();

}

catch(Exception e)

{


}} catch(Exception e)

System.exit(0);

}

SubTaskHandle handleSet[]=new SubTaskHandle[10];

Context context=null;

//Creating subtasks

for (i=1;i<=10;i++)

{

context=new Context();

context.put("fromval",i+"000000");

context.put("toval",i+1+"000000"); handleSet[i-1]=manager.execute(new Prime(),context);

}

//Waiting for all subtasks to

finish.manager.barrier();

//handleSet[i].waitSubTask()...Waiting for particular subtask to finish. try {

FileOutputStream fout=new FileOutputStream("sreedhar.txt"); PrintStream

ps=new PrintStream(fout);

12

//placing the results into the text file....

//int sum=0;

//int

content1=0;

for(int i=1;i<=10;i++) {

Result r=handleSet[i-1].getResult(); VishwaFile

vfile=r.getFile();

BufferedReader input = new BufferedReader(new InputStreamReader(new

FileInputStream(vfile)));

String content=null;

System.out.println("Compiling results from Sub-Task: "+(i-1));

ps.println("Compiling results from Sub-Task:"+String.valueOf(i-1));

while((content=input.readLine())!=null)

//content1=Integer.parseInt(content);

ps.print(content+",");

//sum=sum+content1;

input.close();

}

// ps.println("sum of prime no in the given range"+sum);

ps.close();

fout.close();

} catch(Exception e) {


}

//Closing the client manager

manager.close();

}

}

OUTPUT:

Compiling results from Sub-Task:0

100003,100019,100043,100049,100057……..199933,199961,199967,199999


200003,200009,200017,200023,200029,200033….299951,299969,299977,299983,299993


300007,300017,300023,300043,300073…..,399941,399953,399979,399983,399989


400009,400031,400033,400051……..499943,499957,499969,499973,499979


500009,500029,500041,500057,500069……599959,599983,599993,599999

13


600011,600043,600053,600071,600073…..699947,699953,699961,699967


700001,700027,700057,700067,700079…..799949,799961,799979,799991,799993,799999


800011,800029,800053,800057,800077,800083……899939,899971,899981


900001,900007,900019,900037,900061……999953,999959,999961,999979,999983 Compiling results from Sub-Task:9

1000003,1000033,1000037,1000039,1000081……1099927,1099933,1099957,1099961,1099997

RESULT :

Thus the prime number for huge interval has been calculated using grid node and the result

has been viewed.

14

Ex. NO: 3 MATRIX MULTIPLICATION

AIM:

To calculate the multiplication of integers for huge interval using grid nodes.

ALGORITHM:


2. Copy the Square.java and paste it in the bin of the java folder.


4. In the Squareclient.java provide the IP address of any one of the client machine

5. From the remote machine execute the Squareclient program.


client.

7. This execution process can be monitored by the server.

8. If any clients don’t respond, then that work will be shared by the other systems.

9. After the execution the results will be compiled and stored in the presentation machine.

SOURCE CODE :

import jvishwa.VishwaSubTask;







import java.io.ObjectInputStream;

public class Square extends VishwaSubTask { VishwaFile vfile = null; public void run(Context c) {


int startpoint = Integer.parseInt((String) c.get("fromval")); int endpoint = Integer.parseInt((String)

c.get("toval")); //File Service for creating a file

FileService fileService = new FileService(this); vfile = fileService.createFile("result");

PrintStream ps = null;

15

try {

ps = new PrintStream(new FileOutputStream(vfile));

}

catch (Exception e) { e.printStackTrace();

}

//Calculation of square

for (int i = startpoint; i <= endpoint; i++) {

ps.println(squareNum(i) + "");

}

ps.close();

}

public int squareNum(int num) { return num * num;

}

//Deserialization method for getting the object public Object getObject(String fileName)

{

try { FileInputStream fin = new FileInputStream(fileName); ObjectInputStream ois = new

ObjectInputStream(fin); Object o = ois.readObject();

ois.close();

return o;

} catch (Exception e) { e.printStackTrace();

}

return null;

}

//Aggregating the results... public Result callback() { Result r = new Result(); r.putFile(vfile);

return r;

}} SQUARE CLIENT: import jvishwa.client.*; import jvishwa.query.* import jvishwa.metric.*; import jvishwa.task.SchedulerType; import jvishwa.Result; import jvishwa.Context; import java.io.FileOutputStream; import java.io.PrintStream; import java.io.BufferedReader; import java.io.File; import java.io.FileInputStream; import jvishwa.file.*; import java.io.InputStreamReader; public class SquareClient { public static void main(String args[]) { ClientManager manager = ClientManager.getInstance(); Metric metric=new Metric(); Query query=new Query(metric);

//setting minimum and maximum grid nodes required query.setLowerBound(5);


query.setCPUFractionValue(0.7); manager.setConditionType(ConditionType.DEFAULT_TYPE);

manager.setMetric(metric);


16





//setting grid node



try {


System.out.println("Press any key to start the execution..."); try

{


input.readLine();

}

catch(Exception e)

{


}

} catch (Exception e) {


System.exit(0);

}

//System.out.println("Starting execution...");

SubTaskHandle handleSet[] = new SubTaskHandle[10];

Context context = null;

//Creating subtasks

for (int i = 0; i <= 9; i++) { context = new

Context(); context.put("fromval", i + "1");

context.put("toval", i + 1 + "0");

//pass parameter and get id of remote subtask

handleSet[i] = manager.execute(new Square(), context);

}

//wait for all remote subtasks to finish

manager.barrier();

try {

FileOutputStream fout = new FileOutputStream("squareresult1.txt"); PrintStream ps = new

PrintStream(fout);

//placing the results into the text file....

/*int sum=0;

int content1=0;*/

for (int i = 1; i <= 10; i++)

{

//get results from each subtask

Result r = handleSet[i - 1].getResult();

VishwaFile vfile = r.getFile();

BufferedReader input = new BufferedReader(new InputStreamReader(new FileInputStream(vfile)));

String content = null;

System.out.println("Compiling results from Sub-Task: " + (i - 1)); ps.println("Compiling results from

Sub-Task:" + String.valueOf(i - 1)); //placing the results into the text file....

while ((content = input.readLine()) != null) {

/*content1=Integer.parseInt(content);

ps.print(content1+",");

17

sum=sum+content1;*/

ps.print(content+",");

}

input.close();

}

//ps.println("sum of square no in the given range"+sum);

ps.close();

fout.close();

} catch (Exception e) { e.printStackTrace();

}

//Closing the client manager

manager.close();

}

}

OUTPUT:

Compiling results from Sub-Task:0 1,4,9,16,25,36,49,64,81,100










RESULT:

Thus the square number for huge interval has been calculated using grid node and the result

has been viewed.

18

Ex. NO: 4 MATRIX ADDITION

AIM :

To calculate the matrix addition for huge interval using grid nodes.

ALGORITHM:


2. Copy the Matrix.java and paste it in the bin of the java folder.


4. In the Matrixclient.java change the IP address of any one of the client node.

5. From the remote machine execute the Matrixclient program.


client.

7. This execution process can be monitored in the server.

8. If any clients don’t respond, then that work will be shared by the other systems

9. After the execution the results will be compiled and stored in the presentation machine.

SOURCE CODE:


import jvishwa.Result; import jvishwa.VishwaSubTask;



import java.io.ObjectInputStream;




public class Matrix extends VishwaSubTask { Vector v; VishwaFile vfile=null; //Constructor public Matrix() { v=new Vector(); } //calculation of prime public

void run(Context c) {

//double A[],B[][];


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int taskidno = Integer.parseInt((String)c.get("taskid"));

System.out.println("##################Starting TASK: "+ taskidno +" --------##################");

int N = Integer.parseInt((String)c.get("order"));

double[] C = new double[N];

double[] A = new double[N];

double[][] B = new double[N][N];

for(int ti = 0; ti<N; ti++){

String rt= "R:"+String.valueOf(ti);

A[ti]= Double.parseDouble((String)c.get(rt));

}

for(int tj = 0; tj<N; tj++)

for(int tk=0;tk<N; tk++){

String rt=

"R:["+String.valueOf(tj)+"]["+String.valueOf(tk)+"]"; B[tj][tk]

= Double.parseDouble((String)c.get(rt)); //context.put(rt, ri);

}

A=(double[])c.get("firstmatrix");

// B=(double[][])c.get("secondmatrix");

System.out.println("populated the matrix**********************: "+ B);

//File Service for creating a file

FileService fileService=new FileService(this);

vfile=fileService.createFile("result");

PrintStream ps=null;

try {

ps=new PrintStream(new FileOutputStream(vfile));

}



}

//Calculation of prime

for (int j = 0; j < N; j++){

for (int k = 0; k < N; k++)

C[j] += A[j] * B[j][k];

System.out.println("c: " +C[j]);ps.println(String.valueOf(C[j]));

}

System.out.println("##################COMPLETED TASK: "+ taskidno +" --------

##################");

ps.close();

}

//Aggregating the results...

public Result callback() {

Result r=new Result();

r.putFile(vfile);

return r;

}

//Deserialization method for getting the object public Object getObject(String fileName) {

try

{

FileInputStream fin=new FileInputStream(fileName);

ObjectInputStream ois=new ObjectInputStream(fin);

Object o=ois.readObject();

ois.close();

return o;

20

}

catch(Exception e)

{


}

return null;

}

}

MATRIX CLIENT:

import jvishwa.client.*;

import jvishwa.query.*;

import jvishwa.metric.*;

import jvishwa.task.SchedulerType;





import java.io.BufferedReader;






public class MatrixClient {

public static void main(String args[]) {

int N=4;

//Getting the instance of client manager ClientManager

manager=ClientManager.getInstance(); Metric metric=new Metric();

Query query=new Query(metric);

//Setting the configuration parameters

query.setLowerBound(5);//20


query.setCPUFractionValue(0.7);

manager.setConditionType(ConditionType.DEFAULT_TYPE);

manager.setMetric(metric);






manager.setCustomClassPath(System.getProperty("user.dir"));



manager.setClassDirectory("/home/apkarthick/vishwa/MatrixMultiplication/");

//Generating matrix

double[][] A = new double[N][N]; double[][] B = new double[N][N];

double[][] C;for (int i = 0; i < N; i++)

for (int j = 0; j < N; j++)

A[i][j] = Math.random();

for (int i = 0; i < N; i++) for

21

(int j = 0; j < N; j++)

B[i][j] = Math.random();

System.out.println("matrix formed");

//Intilizing the grid with appliction requirements try {


System.out.println("Prees Any key to start the

execution..."); try

{


input.readLine();

}

catch(Exception e)

{


}

}



System.exit(0);

}

SubTaskHandle handleSet[]=new SubTaskHandle[N];

Context context=null;

//Creating subtasks

for(int i=0;i<N;i++)

{

context = new Context()

for(int ti = 0; ti<N; ti++){

String rt= "R:"+String.valueOf(ti);

double ri = A[i][ti]; context.put(rt,

String.valueOf(ri));

}

for(int tj = 0; tj<N; tj++)

for(int tk=0;tk<N; tk++){

String rt= "R:["+String.valueOf(tj)+"]["+String.valueOf(tk)+"]"; double ri = B[tj][tk];

context.put(rt, String.valueOf(ri));

}

// context.put("firstmatrix",A[i]);

// context.put("secondmatrix",B);

OUTPUT:-

Compiling results from Sub-Task:0 1.3110847180130507 0.45072657945777495

0.9328806887907788 0.0080678568628709


1.0333216991598813 0.5685121830127593


1.113233731808045 0.07265781176921086


1.892017828553201 0.647364140085597

RESULT:

Thus the matrix addition for huge interval has been calculated using grid node and the result

has been viewed.

22

ExNo:5 STORING & ACCESSING FILES IN TO DROPBOX

AIM:

Write a Program in Storing & Accessing Files In To Dropbox

Algorithm: STEP 1: Make sure you’ve installed the desktop app on your computer STEP 2: Drag and drop files into the Dropbox folder. That’s it!

STEP 3: Sign in to dropbox.com STEP 4: Click the blue Upload file button at the top of the window.

On Windows or Mac

1. Install the Dropbox desktop app if you haven’t already.

2. Open your Dropbox folder, and find the file or folder you’d like to share.

3. Right-click on the file and select Copy Dropbox Link. The link will be copied

automatically. Just paste it wherever you’d like.

https://www.dropbox.com/install

https://www.dropbox.com/install

23

Work on files together

Collaborate on presentations and docs — without emailing files back and forth. Just create a shared

folder and add other people to it. When you edit a file in a shared folder, everyone instantly gets the

latest version on their devices.

Set up a shared folder

On dropbox.com

Sign in to dropbox.com, and click on the Sharing tab on the left side of the window.

Choose New shared folder at the top of the window, select I’d like to create and share a new folder, then

click Next.

Enter a name for your shared folder, then click Next.

24

RESULT:

Thus the Storing & Accessing Files In To Dropbox,executed and the output was verified

successfully.

25

Ex no:6 IMPLEMENTATION OF PARA-VIRTUALIZATION USING VM WARE’S

WORKSTATION/ ORACLE’S VIRTUAL BOX

AIM:

Implementation of Virtual Box for Virtualization of any OS.

ALGORITHM:

Host operating system (host OS). This is the operating system of the physical computer on

which Virtual Box was installed. There are versions of Virtual Box for Windows, Mac OS X, Linux and

Solaris hosts.

Guest operating system (guest OS).This is the operating system that is running inside the virtual

machine. Theoretically, Virtual Box can run any x86 operating system (DOS, Windows, OS/2, FreeBSD, Open

BSD), but to achieve near-native performance of the guest code on your machine, we had to go through a lot of

optimizations that are specific to certain operating systems. So while your favorite operating system may run as a

guest, we officially support and optimize for a select few (which, however, include the most common ones).

Virtual machine (VM). This is the special environment that Virtual Box creates for your guest operating

system while it is running. In other words, you run your guest operating system "in" a VM. Normally, a VM will

be shown as a window on your computers desktop, but depending on which of the various frontends of

VirtualBox you use, it can be displayed in full screen mode or remotely on another computer. In a more abstract

way, internally, Virtual Box thinks of a VM as a set of parameters that determine its behavior. They include

hardware settings (how much memory the VM should have, what hard disks Virtual Box should virtualize

through which container files, what CDs are mounted etc.) as well as state information (whether the VM

is currently running, saved, its snapshots etc.). These settings are mirrored in the Virtual Box Manager window as

well as the VBoxManage command line program;

Guest Additions. This refers to special software packages which are shipped with VirtualBox but designed to

be installed inside a VM to improve performance of the guest OS and to add extra features.

Starting Virtual Box:

After installation, you can start VirtualBox as follows:

On a Windows host, in the standard "Programs" menu, click on the item in the "VirtualBox"

group. On Vista or Windows 7, you can also type "VirtualBox" in the search box of the "Start"

menu.

On a Mac OS X host, in the Finder, double-click on the "VirtualBox" item in the "Applications"

folder.

On a Linux or Solaris host, depending on your desktop environment, a "VirtualBox" item may

have been placed in either the "System" or "System Tools" group of your "Applications" menu.

Alternatively, you can type VirtualBox in a terminal.

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This window is called the "VirtualBox Manager". On the left, you can see a pane that will later list all

your virtual machines. Since you have not created any, the list is empty. A row of buttons above it

allows you to create new VMs and work on existing VMs, once you have some. The pane on the right

displays the properties of the virtual machine currently selected, if any. Again, since you don't have any

machines yet, the pane displays a welcome message.

Creating your first virtual machine:

Click on the "New" button at the top of the VirtualBox Manager window. A wizard will pop up to guide

you through setting up a new virtual machine (VM)

Running your virtual machine: To start a virtual machine, you have several options:

Double-click on its entry in the list within the Manager window or

select its entry in the list in the Manager window it and press the "Start" button at the top or

for virtual machines created with VirtualBox 4.0 or later, navigate to the "VirtualBox VMs"

folder in your system user's home directory, find the subdirectory of the machine you want to

start and double-click on the machine settings file (with a .vbox file extension). This opens up a

new window, and the virtual machine which you selected will boot up. Everything which would

normally be seen on the virtual system's monitor is shown in the window. In general, you can use

the virtual machine much like you would use a real computer. There are couple of points worth

mentioning however.

Saving the state of the machine: When you click on the "Close" button of your virtual machine

window (at the top right of the window, just like you would close any other window on your system),

VirtualBox asks you whether you want to "save" or "power off" the VM. (As a shortcut, you can also

press the Host key together with "Q".)

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Save the machine state: With this option, VirtualBox "freezes" the virtual machine by

completely saving its state to your local disk. When you start the VM again later, you will find

that the VM continues exactly where it was left off. All your programs will still be open, and

your computer resumes operation. Saving the state of a virtual machine is thus in some ways

similar to suspending a laptop computer (e.g. by closing its lid).

Send the shutdown signal. This will send an ACPI shutdown signal to the virtual machine,

which has the same effect as if you had pressed the power button on a real computer. So long as

the VM is running a fairly modern operating system, this should trigger a proper shutdown

mechanism from within the VM.

Manager window discards a virtual machine's saved state. This has the same effect as powering

it off, and the same warnings apply.

Importing and exporting virtual machines

VirtualBox can import and export virtual machines in the industry-standard Open Virtualization

Format (OVF). OVF is a cross-platform standard supported by many virtualization products which

allows for creating ready-made virtual machines that can then be imported into a virtualizer such

as VirtualBox. VirtualBox makes OVF import and export easy to access and supports it from the

Manager window as well as its command-line interface. This allows for packaging so-called

virtual appliances: disk images together with configuration settings that can be distributed easily.

This way one can offer complete ready-to-use software packages (operating systems with

applications) that need no configuration or installation except for importing into VirtualBox.

They can come in several files, as one or several disk images, typically in the widely-used

VMDK format (see Section 5.2,Disk image files (VDI, VMDK, VHD, HDD)‖) and a textual

description file in an XML dialect with an .ovf extension. These files must then reside in the

same directory for Virtual Box to be able to import them.

Alternatively, the above files can be packed together into a single archive file, typically with an

.ova extension. (Such archive files use a variant of the TAR archive format and can therefore be

unpacked outside of Virtual Box with any utility that can unpack standard TAR files.)

Select "File" -> "Export appliance". A different dialog window shows up that allows you to combine

several virtual machines into an OVF appliance. Then, select the target location where the target files

should be stored, and the conversion process begins. This can again take a while.

RESULT:

Thus we have studied use of Multiple OS using Virtual Box by virtualization.

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Ex no:7 IMPLEMENTATION OF VIRTUAL MACHINE MIGRATION BASED ON THE

CERTAIN CONDITION FROM ONE NODE TO THE OTHER

AIM:

To show the virtual machine migration based on the certain condition from one node to the other.

ALGORITHM:

Existing images can be cloned to a new one. This is useful to make a backup of an Image before you

modify it, or to get a private persistent copy of an image shared by other user.

To clone an image, execute

$ oneimage clone Ubuntu new_image

Listing Available Images

You can use the oneimage list command to check the available images in the

repository.

$ oneimage list

ID USER GROUP NAME DATASTORE SIZE TYPE PER STAT RVMS

0 oneuser1 users Ubuntu default 8M OS No rdy 0

To get complete information about an image, use oneimage show, or list images

continuously with oneimage top.

RESULT:

Thus the Implementation of virtual machine migration based on the certain condition from one node to

the other has been verified and executed successfully.

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Exno:8 Find procedure to install storage controller and interact with it

AIM:

To find the procedure to install storage controller and interact with it.

ALGORITHM:

Storage controller will be installed as Swift and Cinder components when installing open stack. The

ways to interact with the storage will be done through portal.

Open Stack Object Storage (swift) is used for redundant, scalable data storage using clusters of

standardized servers to store petabytes of accessible data. It is a long-term storage system for large

amounts of static data which can be retrieved and updated.

Open Stack Object Storage provides a distributed, API-accessible storage platform that can be

integrated directly into an application or used to store any type of file, including VM images, backups,

archives, or media files. In the OpenStack dashboard, you can only manage containers and objects.

In OpenStack Object Storage, containers provide storage for objects in a manner similar to a Windows

folder or Linux file directory, though they cannot be nested. An object in OpenStack consists of the file

to be stored in the container and any accompanying metadata.

Create a container

Log in to the dashboard

1. Select the appropriate project from the drop down menu at the top left.

2. On the Project tab, open the Object Store tab and click Containers category.

3. Click Create Container.

4. In the Create Container dialog box, enter a name for the container, and then click Create

Container.

You have successfully created a container.

Upload an object

1. Log in to the dashboard.



4. Select the container in which you want to store your object.

5. Click Upload Object.

The Upload Object To Container: <name> dialog box appears. <name> is the name of the

container to which you are uploading the object.

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6. Enter a name for the object.

7. Browse to and select the file that you want to upload.

8. Click Upload Object.

You have successfully uploaded an object to the container.

Manage an object

To edit an object

1. Log in to the dashboard.



4. Select the container in which you want to store your object.

5. Click the menu button and choose Edit from the dropdown list.

The Edit Object dialog box is displayed.

6. Browse to and select the file that you want to upload.

7. Click Update Object

RESULT:

Thus the Implementation to find the procedure to install storage controller and interaction has been

executed successfully

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ExNo:9 WRITE A WORD COUNT PROGRAM TO DEMONSTRATE THE USE OF MAP &

REDUCE TASKS.

AIM:

To write a word count program to demonstrate the use of Map and Reduce tasks.

ALGORITHM:

1. Splitting – The splitting parameter can be anything, e.g. splitting by space, comma, semicolon,

or even by a new line (‘\n’).

2. Mapping – as explained above.

3. Intermediate splitting – the entire process in parallel on different clusters. In order to group them

in “Reduce Phase” the similar KEY data should be on the same cluster.

4. Reduce – it is nothing but mostly group by phase.

5. Combining – The last phase where all the data (individual result set from each cluster) is

combined together to form a result.

6. Open Eclipse> File > New > Java Project >( Name it – MRProgramsDemo) > Finish.

7. Right Click > New > Package ( Name it - PackageDemo) > Finish.

8. Right Click on Package > New > Class (Name it - WordCount).

9. Add Following Reference Libraries:

10. Right Click on Project > Build Path> Add External

11. /usr/lib/hadoop-0.20/hadoop-core.jar

12. Usr/lib/hadoop-0.20/lib/Commons-cli-1.2.jar

SOURCE CODE

package PackageDemo;

import java.io.IOException;

import org.apache.hadoop.conf.Configuration;

import org.apache.hadoop.fs.Path;

import org.apache.hadoop.io.IntWritable;

import org.apache.hadoop.io.LongWritable;

import org.apache.hadoop.io.Text;

import org.apache.hadoop.mapreduce.Job;

import org.apache.hadoop.mapreduce.Mapper;

import org.apache.hadoop.mapreduce.Reducer;

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import org.apache.hadoop.mapreduce.lib.input.FileInputFormat;

import org.apache.hadoop.mapreduce.lib.output.FileOutputFormat;

import org.apache.hadoop.util.GenericOptionsParser;

public class WordCount {

public static void main(String [] args) throws Exception

{

Configuration c=new Configuration();

String[] files=new GenericOptionsParser(c,args).getRemainingArgs();

Path input=new Path(files[0]);

Path output=new Path(files[1]);

Job j=new Job(c,"wordcount");

j.setJarByClass(WordCount.class);

j.setMapperClass(MapForWordCount.class);

j.setReducerClass(ReduceForWordCount.class);

j.setOutputKeyClass(Text.class);

j.setOutputValueClass(IntWritable.class);

FileInputFormat.addInputPath(j, input);

FileOutputFormat.setOutputPath(j, output);

System.exit(j.waitForCompletion(true)?0:1);

}

public static class MapForWordCount extends Mapper<LongWritable, Text, Text, IntWritable>{

public void map(LongWritable key, Text value, Context con) throws IOException,

InterruptedException

{

String line = value.toString();

String[] words=line.split(",");

for(String word: words )

{

Text outputKey = new Text(word.toUpperCase().trim());

IntWritable outputValue = new IntWritable(1);

con.write(outputKey, outputValue);

}

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}

}

public static class ReduceForWordCount extends Reducer<Text, IntWritable, Text, IntWritable>

{

public void reduce(Text word, Iterable<IntWritable> values, Context con) throws IOException,

InterruptedException

{

int sum = 0;

for(IntWritable value : values)

{

sum += value.get();

}

con.write(word, new IntWritable(sum));

}

}

}

The above program consists of three classes:

Driver class (Public, void, static, or main; this is the entry point).

The Map class which extends the public class

Mapper<KEYIN,VALUEIN,KEYOUT,VALUEOUT> and implements the Map function.

The Reduce class which extends the public class

Reducer<KEYIN,VALUEIN,KEYOUT,VALUEOUT> and implements the Reduce

function.

Make a jar file

Right Click on Project> Export> Select export destination as Jar File > next> Finish

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To move this into Hadoop directly, open the terminal and enter the following commands:

[training@localhost ~]$ hadoop fs -put wordcountFile wordCountFile

Run the jar file:

[training@localhost ~]$ hadoop jar MRProgramsDemo.jar PackageDemo.WordCount

wordCountFile MRDir1

RESULT:

[training@localhost ~]$ hadoop fs -ls MRDir1

Found 3 items

-rw-r--r-- 1 training supergroup 0 2016-02-23 03:36 /user/training/MRDir1/_SUCCESS

drwxr-xr-x - training supergroup 0 2016-02-23 03:36 /user/training/MRDir1/_logs

-rw-r--r-- 1 training supergroup 20 2016-02-23 03:36 /user/training/MRDir1/part-r-00000

[training@localhost ~]$ hadoop fs -cat MRDir1/part-r-00000

BUS 7

CAR 4

TRAIN 6