big data had oop workshop
TRANSCRIPT
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Workshop: Big Data & Analytics Using Hadoop By
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Dymention Teknocrats Confidential
Contents
About Workshop ............................................................................................................................................. 3
Topics Covered ................................................................................................................................................ 4
Why should one attend? ................................................................................................................................. 5
Target Audience .............................................................................................................................................. 5
Prerequisites ................................................................................................................................................... 5
Contents & Schedule ....................................................................................................................................... 6
Contact Us ....................................................................................................................................................... 9
Facebook ......................................................................................................................................................... 9
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About Workshop
As data volumes increase at exponential speed in more and more application fields of science, the
challenges posed by handling Big Data gain an increasing importance. Large scientific experiments, such as
climate modeling, genome mapping, and high-energy physics simulations generate data volumes reachingpetabytes per year, further used for real-time or offline processing. Initially designed for powerful and
expensive supercomputers, such applications have seen an increasing adoption on clouds, exploiting their
elasticity and economical model.
However, running such applications in an efficient fashion on clouds is challenging. One such open
challenge is how to handle this data deluge. Sharing, disseminating and analyzing large data sets has
become a critical issue despite the deployment of petascale computing systems, and optical networking
speeds reaching up to 100 Gbps. While Map/Reduce covers a large fraction of the development space,
there are still many applications that are better served by other models and systems. In such a context, we
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need to embrace new programming models, scheduling schemes, hybrid infrastructures and scale out of
single datacenters to geographically distributed deployments in order to cope with these new challenges
effectively.
The Big Data workshop provides a platform for the dissemination of recent research efforts that explicitly
aim at addressing these challenges. It supports the presentation of advanced solutions for the efficient
management of Big Data in the context of Cloud computing, new development and deployment efforts in
running data-intensive computing workloads. In particular, we are interested in how the use of Cloud-based
technologies can meet the data intensive scientific challenges of HPC applications that are not well served
by the current supercomputers or grids, and are being ported to Cloud platforms. The goal of the workshopis to support the assessment of the current state, introduce future directions, and present architectures and
services for future Clouds supporting data intensive computing.
Topics Covered
What is Big Data and why Hadoop Hadoop Overview and Ecosystem Hadoop in action Hadoop Distributed file System - HDFS Using Pig
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Using HBase Map Reduce Architecture Developing Map Reduce Programs
Why should one attend?
Big Data and Hadoop professionals are in high demand, provide boost in employability Technology of today of tomorrow, will create a differentiator profile Command much higher salary Grow faster, get faster promotions in organization
Target Audience
It is imperative for everybody to understand Big Data concepts and hence will be very useful for Engineering
students, research scholar and professors alike.Prerequisites
Java Eclipse/Net Beans
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XML
Contents & ScheduleDay 1
Session Speaker Time Topic
1 10.00-
11.30 AM
What is Big Data and why Hadoop
1. Big Data characteristics
2. Challenges with traditional system
3. Computing in Cloud
4. RDBMS/SQL vs. Hadoop
TEA BREAK2 11.45-1.00
PM
3. Computing in Cloud
4. RDBMS/SQL vs. Hadoop
LUNCH BREAK
3 2:00 -3.30
PM
Hadoop Overview and Ecosystem
1. Architecture of Hadoop cluster
2. Virtual Machine Setup
TEA BREAK4 3.45-5.00
PM
Hadoop in action
1. Installing Hadoop
2. Configuring Hadoop
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Day 2
Session Speaker Time Topic
5 9:00-11:00
AM
Hadoop Distributed file System - HDFS
1. Name Node and Data Node
2. CLI
3. Hands-on exercise
TEA BREAK
6 11:15-1:00
PM
Using HBase
1. Data types and schemas
2. Intro to UDF
3. HBase vs. RDBMS
LUNCH BREAK7 2:00-3:00
PM
Using HBase
4. HBase Master and Region Servers
8 3:00-3:45
PM
Map Reduce Architecture
1. How does it work?
TEA BREAK9 4:00-5:00
PM
Map Reduce Architecture
2. The Mapper and Reducer Input
& Output Formats, Data Type
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10 2.00-3:45
PM
Developing Map Reduce Programs
1. Setting up development
environment
2. Creating Map Reduce programs
3. Hands-on Exercise11 4:00-5:00
PM
Analytics:
Discussing real life case study using Hadoop eco-system
Day 3
Session Speaker Time Topic
12 9.00-11AM Developing Map Reduce Programs
1. Setting up development environment
2. Creating Map Reduce programs
3. Hands-on ExerciseTEA BREAK
13 11.15-1:00
PM
Developing Map Reduce Programs
3. Hands-on Exercise
LUNCH BREAK
14 2:00-3:00
PM
Sqoop
Importing and exporting data from RDBMS
15 3:00-4:00
PM
Analytics:
Discussing real life case study using Hadoop eco-systemTEA BREAK
5 4:00-5PM Distribution of certificates and closing.
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Contact Us
Mahesh G.:
9901200400
Kanhiya Lal:
7259728800
Facebook
http://www.facebook.com/4thDTi
http://www.facebook.com/groups/4thDT/
Thank You
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