Page 75 - B.Tech IT Curriculum and Syllabus R2017 - REC

Department of IT, REC

LIST OF EXPERIMENTS

1. Install, configure and run Hadoop and HDFS.
2. Implement word count/frequency programs using MapReduce.
3. Implement a MapReduce program to process a weather dataset.
4. Implement Linear and Logistic Regression.
5. Implement SVM/Decision tree classification techniques.
6. Implement clustering techniques – Hierarchical and K-Means.
7. Visualize data using any plotting framework.
8. Implement an application that stores big data in Hbase/MongoDB/Pig using Hadoop/R.
9. Install, Deploy & Configure Apache Spark Cluster. Run Apache Spark applications using
Scala.

TOTAL: 60 PERIODS
OUTCOMES:
At the end of the course, the student should be able to:
1. Process big data using Hadoop framework.
2. Build and apply linear and logistic regression models.
3. Perform data analysis with machine learning methods.
4. Perform graphical data analysis.
5. Create applications for big data analytics.

LAB EQUIPMENT FOR A BATCH OF 30 STUDENTS:
Hardware: PC with 8 GB RAM, i3 Processor
Software: Hadoop, R package, Hbase, MongoDB

CS17711 CLOUD COMPUTING LABORATORY L T P C
0 0 4 2
OBJECTIVES:
The student should be made to:
● Learn and understand Virtualization and run VMs of different configuration.
● Be familiar with current cloud technologies by creating applications and deploying it in public
cloud.
● Learn to set up an enterprise level cloud infrastructure.
● To understand the programming models for distributed cloud management.
● To understand the issues and solutions by simulating a cloud data centre.
Virtualization:
1. Find procedure to run the virtual machine of different configuration using virt-manager.
2. Virtualize a machine and check how many virtual machines can be utilized at a particular
time.
3. Create a VM Clone and attach virtual block to the cloned virtual machine and check whether
it holds the data even after the release of the virtual machine.
4. Create a Snapshot of a VM at a given point in time and test the snapshot by restoring the VM
to that time. (Note: Testing can be done by installing an application and then restore it.)
5. Perform Storage Virtualization by Installing a Storage controller and interact with it using
open-source network-attached storage (NAS) software.
Public Cloud:
1. Develop a simple application to understand the concept of PAAS using GAE/Amazon Elastic
Beanstalk/IBM Blue Mix and launch it.
2. Test how a SaaS applications scales in response to demand.

Curriculum and Syllabus | B.Tech. Information Technology | R2017 Page 75