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Introduction and Overview of BigData, Hadoop, Distributed Computing - BigData Community
1. FEARLESS engineering Acharya institute of technology, Bengaluru. Grand Welcome to the world of, “bigdata_community”
2. FEARLESS engineering Acharya institute of technology, Bengaluru.
Introduction to bigdata and installation of single-node apache hadoop cluster
Presented By, Mahantesh C. Angadi Nagarjuna DN Manoj PT Under the Guidance of, Prof. Manjunath tN Prof. Amogh pk Dept. of ISE AIT, Bengaluru Session-1: 24 March 2014
3. FEARLESS engineering Contents
Purpose of This Talk
Introduction
Terminologies
Cloud Computing
BigData
Traditional Approaches to Solve BigData Problems
Hadoop and its Characteristics
Architecture of Hadoop
4. FEARLESS engineering Contents
Why Only Hadoop?
Advantages of Hadoop
Limitations of Hadoop
Job Opportunities in BigData & Hadoop
Conclusion
References
5. FEARLESS engineering Purpose of This talk
To understand the terminologies
To introduce you to BigData and Hadoop
To be able to clearly differentiate between Cloud, BigData, Hadoop
Traditional approaches to handle BigData
Characteristics of Hadoop
Explain how Hadoop works?
Get friendly with MapReduce and HDFS
6. FEARLESS engineering continued…
Get aware about Hadoop Ecosystem
Advantages and Limitations of Hadoop
Job opportunities in Hadoop
Conclusion
7. FEARLESS engineering introduction
Today We Live in the Data Age.
Due to Internet of Things (IoT), the speed of ingestion of data is keeps on increasing and increasing.
So, the World is getting more “Hungrier and Hungrier for Data”
10. FEARLESS engineering Cloud computing
“Computing may someday be organized as a public utility, just as the telephone system is organized as a public utility” - John McCarthy, 1961
The word “Cloud” is first time used in a technical perspective by HP and Compaq people.
Cloud Computing is a Utility Computing that involves a large number of computers connected through a communication network such as the Internet, provides services based-on-demand.
11. FEARLESS engineering utility computing
Utility computing is the packaging of computing resources, such as computation, storage and services, as a metered service.
This model has the advantage of a low or no initial cost to acquire computer resources;
12. FEARLESS engineering Distributed computing
Distributed computing refers to the use of distributed systems to solve computational problems.
Here a problem will be divided into many no. of small tasks, each of which is solved by one or more computers, which communicate with each other by passing messages.
Parallel Computing is a form of computation in which many calculations are carried out simultaneously, operating on the principle that large problems can often be divided into smaller ones, which are then solved concurrently.
13. FEARLESS engineering Why bigdata deserves our attention?
Everyday we create 2.5 quintillions bytes of data, 90% this data is unstructured.
90% of the data in the World today has been created in the last two years alone.
By the end of 2015, CISCO estimates that global Internet traffic will reach 4.8 Zettabytes a year.
BigData would create 4.4. million jobs by 2015.
There is a shortage of 140,000-190,000 BigData professionals in the United States alone…!
15. FEARLESS engineering what is bigdata…?
BigData is the any amount of data that is structured and/or unstructured data which is beyond the storage and processing capabilities of a single physical machine and traditional database techniques.
Data that has extra large Volume, comes from Variety of sources, Variety of formats and comes at us with a great Velocity is normally refers to as BigData.
18. FEARLESS engineering Rise of bigdata adoption
Data Scientist is the Hottest job of 21st Century…! - Harvard Business Review Magazine
Positions such as Data Scientist, Data Analytics were doesn’t exist few years ago.
Today Companies are fighting to recruit these specialists.
The market is not Growing at the rate it wants to grow:- Because skills shortage is looming, so they increase Salaries up…!
Data Scientists take huge amounts of data & attempt to pull useful “Business Insights” from that raw data.
21. FEARLESS engineering Characteristics of Storage area network (san)
SAN can be visualize as, one massive storage that can give us Infinite Storage.
Moving Data to Computational Nodes.
It has multiple Application Servers.
Programs run on each Application Server.
All the data is stored in one SAN.
Before Execution, each server Gets the data from SAN.
After Execution, each server Writes the output to SAN.
22. FEARLESS engineering Problems with Storage area network (san)
Huge dependency between networks
Huge bandwidth demand
Scaling up and scaling down is not a smooth process
Partial failures are also difficult to handle
A lot of processing power is spent on Transferring the Data
Data Synchronization is required during exchange
23. FEARLESS engineering moore’s law continued… Moore’s Law:
“The number of Transistors per silicon chip, that can be placed in a Processor will double approximately every two years, for half the cost.”
It is named after Gordon Moore, the founder of Intel.
24. FEARLESS engineering hadoop
Inspired by Google.
Google is originated in the year 1998.
They faced serious challenge in early 2000 to handle the BigData.
In 2004 Google related two papers: - GFS: Google File System - MapReduce: A Programming Model
25. FEARLESS engineering what is hadoop…?
Apache Hadoop is an open-source software framework, used to manage BigData.
Its built and used by a global community of contributors and users.
It’s not only a tool, it’s a Framework of tools.
Moving computation is cheaper than moving data.
Most important Hadoop sub-projects: i. HDFS: Hadoop Distributed File System ii. MapReduce: A Programming Model
27. FEARLESS engineering why the name hadoop…? “Hadoop“ is simply the name of a stuffed toy ELEPHANT that belonged to the son of its creator “DOUG CUTTING”.
28. FEARLESS engineering
Scalable– New nodes can be added without changing data formats.
Cost-effective– It parallelly processes huge datasets on large clusters of commodity computers.
Efficient and Flexible- It is schema-less, and can absorb any type of data, from any number of sources.
Fault-tolerant and Reliable- It handles failures of nodes easily because od Replication.
Easy to use- It uses simple Map and Reduce functions to process the data.
It is developed in Java but it can support Python & others too.
Characteristics of hadoop
34. FEARLESS engineering Hadoop Distributed File System
Pioneered by Google File System (GFS)
It consists of three major components -
i. Name Node
•It is responsible for the distribution of the data throughout the Hadoop cluster.
ii. Secondary Name Node (Backup Node)
•It regularly contacts Name Node and maintains an up to date snapshots of Name Node's directory information.
iii. Data Node
•It responsible to store the chunk of data that is assigned to it by the Name Node.
35. FEARLESS engineering Mapreduce
Pioneered by Google, Popularized by Yahoo (Apache).
It consists of two major components – i. Job Tracker
•It is responsible for scheduling the task to slave nodes.
•So it consults the Name Node and assigns the task to the nodes which has the data on which task would be performed. ii. Task Tracker
•It has the actual logic to perform the task, so it performs Map and Reduce functions on the data assigned to it by Master Node.
42. FEARLESS engineering Advantages of hadoop
Moving Computation is far better than Moving Data
Runs on commodity hardware
It’s a Master/Slave architecture
It handles all types of node failures by live Heartbeats
It handles assigning tasks to nodes
It has Rack awareness between nodes
So, Programmers only need to concentrate on getting business values from BigData
43. FEARLESS engineering limitations of hadoop
Do you think Hadoop is a “Golden_Bullet” that can solve all kinds of problems…? - The answer is NO…!!!
Not suitable, if data is too small.
Not suitable, if there is a dependency between the data.
Not suitable, if Job cannot be divided into small chunks.
Not suitable, to process real-time and stream-based processing.
44. FEARLESS engineering Closer home AADHAR – Government of India’s UIDAI project is considered as one of the largest BigData project in the World...!
45. FEARLESS engineering Closer home
Feb 14th 2011 – IBM’s Super Computer “WATSON” built using BigData Technology.
Its not online & its process like a Human Brain…!
46. FEARLESS engineering Job opportunities Roles and Profiles:
Hadoop Administrator Pre-req: Networking, Admin
Hadoop Developer Pre-req: Programming Expertise Preferably Java/Python
Data Scientist and Data Analytics Pre-req: Mathematics, Statistical Background Scripting languages like Perl etc.
47. FEARLESS engineering Conception about bigdata “BigData is like Teen_Age_Sex: Everyone talks about it, nobody really knows how to do it…??? Everyone thinks that everyone else is doing it, so everyone claims they are doing it…!!! But anyone who actually tries this will be Terrible at it...!!! ” -Dan Ariely, Behavioral Economics Guru.
48. FEARLESS engineering conclusion
•Big Data brings new and exciting opportunities to companies who utilize the platforms available.
•In this Information Era, BigData technology has got its own importance for businesses.
•It has got lot of opportunities in the upcoming days.