The free webinar on Big Data & Hadoop titled " When not to use Hadoop " conducted by Edureka on 11th December 2014

1. www.edureka.co/big-data-and-hadoop
When not to use Hadoop
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2. www.edureka.co/big-data-and-hadoop
Slide2
Objectives
At the end of this module, you will be able to…
Understand When not to use Hadoop
»Real Time Analytics
»Not a Replacement
»Dataset Size
»Complexity
»Security
Understand When to use Hadoop
»Huge Unstructured Datasets
»Response Time is Not an Issue
»Future Planning
»Multiple Frameworks for Big Data
»Lifetime Data Availability

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Hadoop Mania

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When Not To Use Hadoop

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If you want to do some Real Time Analytics, where you are expecting the result quickly, Hadoop should not be used directly
Hadoop works on Batch processing, hence the response time is high
Day1
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Input
Data
Processing
Data
Input
Data
Processing
Data
Input
Data
Processing
Data
Input Data
Processing Data using MR
Time Lag
Real Time Analytics

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Real Time Analytics –Accepted Way
Streaming Data
Storing

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14 sec
0.6 sec
Real Time Analytics –Accepted Way (Contd.)

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Hadoop is not a replacement for your existing data processing infrastructure
After processing the data in Hadoop you need to send the output to relational database technologies for BI, decision support, reporting etc.
It is not going to replace your database, but your database isn’t likely to replace Hadoop either
Different tools for different jobs
Not a Replacement for Existing Infrastructure

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Hadoop framework is not recommendable for small structured datasets as you have other tools available in the market which can do this work quite easily and at a fast pace than Hadoop like MS excel, RDBMS etc.
For a small data analytics, Hadoop can be costlier than other tools
Merge all the small files into one
Multiple Smaller Datasets –Accepted Way

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www.edureka.co/big-data-and-hadoop
Multiple Smaller Datasets –Accepted Way4225284
EachfileofxMB
Slow Execution –10400 ms4225284
Alltheabovefilesmergedintoonefile(9xMB)
Fast Execution –6140 ms
Same Output
Same Input

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Unless you have a better understanding of the Hadoop framework, its not suggested to use Hadoop for production
Learning Hadoop and its eco-system tools and deciding which technology suits your need is again a different level of complexity
Novice Hadoopers

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Many enterprises -especially within the highly regulated industries dealing with sensitive data -aren’t able to move as quick as they would like, towards implementing Big Data projects and Hadoop
“Example Health-care data used by Insurance companies to calculate premium”
Where Security is the Primary Concern?
They don’t have to hesitate though, as many of the security and compliance challenges are being continuously worked upon and can be surmountable (for example, by using Apache Accumulo on top of Hadoop).

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Where Security is the Primary Concern –Accepted way
Healthcare Data
Hadoop Analytic Integration
Healthcare Data
Hadoop Analytic Integration

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When To Use Hadoop

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Your have different types of data: structured, semi-structured and unstructured
The data set is huge in size i.e. several Terabytes or Petabytes
You are not in a hurry for Answers
Data Size and Data Diversity

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To implement Hadoop on your data you should first understand the level of complexity of data and the rate in which it is going to grow
So we need a cluster planning, it may begin with building a small or medium cluster in your industry as per data (in GBs or few TBs ) available at present and scale up your cluster in future depending on the growth of your data
Future Planning

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Hadoop can be integrated with multiple analytic tools to get the best out of it, like M-Learning, R , Python, Spark, MongoDB etc.
Multiple Frameworks for Big Data

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When you want your data to be live and running forever, it can be achieved using Hadoop’s scalability
Lifetime Data Availability

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20. LIVE Online Class
Class Recording in LMS
24/7 Post Class Support
Module Wise Quiz
Project Work
Verifiable Certificate
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How it Works?

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Module 1
»Understanding Big Data and Hadoop
Module 2
»Hadoop Architecture and HDFS
Module 3
»Hadoop MapReduce Framework -I
Module 4
»Hadoop MapReduce Framework -II
Module 5
»Advance MapReduce
Course Topics
Module 6
»PIG
Module 7
»HIVE
Module 8
»Advance HIVE and HBase
Module 9
»Advance HBase
Module 10
»Oozie and Hadoop Project

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Questions
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