Overview
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Intermediate| English[Auto-generated] Real World Examples of Data Analysis in Hadoop
What is Hadoop
Hadoop is a free java based open source framework which is used for storing data and running applications on clusters of commodity hardware. This definition about Hadoop contains different terms and each has its own meaning. Here open source software means it is free to download and use. Framework in Hadoop means everything which you need to develop and run a software application. Hadoop has a massive storage area which breaks big data into blocks and stores in onto a cluster of commodity hardware. Hadoop processes huge amount of data using low cost computers and gives quick results.
What is Hadoop Used for?
Many companies are looking forward to use Hadoop as their big data platform because of its following uses
- Low storage cost – Hadoop requires only modest priced commodity hardware to store and combine data from various sources. This data can be archived and analyzed in the future
- Data warehouse and analytics store – Hadoop is mainly used to store large amount of raw data into enterprise data warehouse for performing various activities. Hadoop handles both structured and unstructured data
- Data lake – Hadoop is used to store huge amount of data without any constraints like other SQL based platform. Hadoop is a low cost platform which can process ETL and data quality jobs in parallel
- Sandbox – Hadoop is designed to deal with huge volume of data of different forms so it can run analytical algorithms. The sandbox approach of Hadoop helps to make innovations with minimum investment.
- Recommendation systems – One most important use of Hadoop is its web based recommendation system. Specially for social media sites like Facebook and LinkedIn, Hadoop is used to analyze real time data quickly and provide recommendations to the users before they leave the page.
Hadoop Advantages and Disadvantages
Hadoop is used widely by many of the organizations because of its different uses and benefits. The different benefits of Hadoop are listed below
- The first main reason why organizations use Hadoop is its quick processing power of really huge amount of data of any type. The data volumes and varieties keep changing constantly but Hadoop processes it all quickly.
- Hadoop has a distributed model system which processes the big data quickly. The more the number of computing nodes the more will be the processing power
- In Hadoop you need not pre process the data before storing it. You can store the raw data and use it later when you need it.
- The processing in Hadoop are protected against any hardware failure. If any node fails then the process is automatically redirected to the other nodes to make sure that the process does not fail.
- Hadoop stores multiple copies of data
- Hadoop has a open source framework which is free to use and is of low cost
- Hadoop requires only small amount of administration and it can easily multiply your system using nodes.
Hadoop Components
There are four main modules of Hadoop
- Hadoop Common – it is the library and utility centre of Hadoop
- Hadoop Distributed File System – This stores data from multiple machines
- MapReduce – This is a software programming model used to process large data sets
- Yet Another Resource Negotiator (YARN) – This is a resource management framework which is used to schedule and handle resource requests from distributed applications.
Course Objectives
At the end of this course you will be able to
- Know what is MapReduce and Hadoop
- Learn the real world applications of these two technologies
- Design, code and run a real example of MapReduce using real data
- Perform data analytics using Pig, Hive and YARN
- Work on a real life project on Big data analytics
Pre Requisites for taking this course
There are no specific pre requisites for taking up this Hadoop Course. But basic knowledge in core Java and SQL will help.
Target Audience for this course
The target audience of this course are
- Analytics Professional
- Data Warehouse Professional
- Project Managers
- Testing Professionals
- Software developers and
- Anyone who has a passion in learning Hadoop
Course Description
Section 1: Introduction
Hadoop is an open source software framework which is used as a popular data storage and analysis platform. Many large and successful organizations are using Hadoop to do powerful analysis of the data. Hadoop gives main two benefits to the organizations. It can store any kind of data and it can perform sophisticated analysis of the collected data easily and quickly. In this chapter you will learn about some real life examples of Hadoop in companies
- Analyze life threatening risks
Hadoop can be used in hospital to analyze the test results of patients and find out which patient is under more risk and need immediate treatment
- Find out warning signs of security breaches
Storing and analyzing data with the help of data will help to identify the problems before they arise.
- Prevent hardware failure
With the help of Hadoop you can collect all the information. Once you start collecting data with Hadoop you will know how much of the collected data will be useful and how much will go waste. You will also be able to determine what will happen if one system fails and how it would affect the entire network. By this way you can predict the problems even before they occur.
- Understand the mindset of the people
Hadoop will help you to know what your customers and prospects say about your company. The data you collect using Hadoop can help you to find out what people think of you and your competitors. By this way you can aim to improve your real time perception about your company.
- Know when to sell products
Hadoop cal also be used to analyze sales data using various factors. You can analyze sales data by particular week/day/time/hours
- Know your target customers
From the collected data you can know what your customers are expecting and where they are mostly located. Using this information you can run targeted ads and increase your conversion rate and sales.
- Server log files
Server log files can help you to identify and control the security. It will also give you a detailed insight about the usage statistics like which app is more popular and who are its main users.
Ratings Mapper
In this section you will learn about Map reduce computing, its two functions – mapper and reducer. You will also learn about parallel computing and its two main categories – Data Parallelism and Task Parallelism. This section also explains about Multiple Map Reduce Cycles and an example of how to compute average ratings per movie on the first map reduce cycle, ordered by rating on a second cycle.
Section 2: Ratings
Movie and Ratings Runner
This lesson contains a Hadoop program which explains the Movie Recommendation System. The program contains a real life dataset of various movies, its users and their ratings. It explains what is a recommendation system and the different algorithm procedures conducted to rate the movie.
Movie and Rating Calc Jar
A runnable jar in Hadoop is a zipped file that contains all the compiled source code as well as a manifest which tells Java which main class to be executed. This chapter explains how the jar command is used in Hadoop for Movie rating analysis.
Total Ratings By A User
MapReduce helps to find the highest rated movie each year. An example program is given in this chapter based on real life data
User Rating Reducer
This chapter explains how the user rating reducer and class function is defined in Hadoop along with few examples
Yarn Basic Tutorial
YARN is the architectural centre of Hadoop which provides a new approach to analytics. It allows multiple data processing engines to handle data that is stored in a single platform. It is the reason why organizations are following modern data architecture. In this chapter you will learn more about what is YARN and what it does. The four main features of YARN are explained in detail under this chapter
- Multi Tenancy
- Cluster Utilization
- Scalability
- Compatibility
Node Manager
The Node Manager is a part of YARN which takes care of each nodes in a Hadoop Cluster. The node manager helps to keep updated with the Resource manager. The several components of Node Manager are explained in detail in this lesson
- Node Status Updater
- Container Manager – RPC Server, Resource Localization Service, Containers Launcher, Aux Services, Containers Monitor, Log Handler
- Container Executor
- Node Health Checker Service
- Security – Application ACLs Manager, Container Token Secret Manager
- Web Server
- Container Launch
- Log Aggregation
FAQ’s General Questions
- Is the Hadoop course a right choice for professionals from Admin background ?
People with administration background can go for “Hadoop administration” course provided by educba. It will be a career progressing course. It will be more useful if you take up both Hadoop developer and Hadoop administration course sequentially.
- Is learning Hadoop a good career path ?
There is currently a big demand for professionals who are expert in Hadoop. This is because most of the organizations have started using Hadoop to maintain their data. As per a recent study the big data market is expected to have a sturdy growth across big data related infrastructure, software and services. Big Data related jobs like Information security analysts, management analysts and information security analysts continue to be in more demand.
- Is Java a pre requisite to learn Big data and Hadoop ?
You can become an expert in Hadoop irrespective of your education background. But a basic knowledge of Core Java and SQL might be helpful to learn Hadoop with ease. So Java is not a pre requisite for learning Hadoop. You can brush up your Java skills using a Java Introductory course offered by Educba.
- What are the major Big data job titles ?
Listed here are few of the Big data and Hadoop related job titles. This list will help you to look for Big data related jobs.
- Data Scientist
- Data Engineer
- Machine Learning Scientist
- Data Visualization Specialist
- Business Intelligence Solutions Architect
- Business Intelligence Specialist
- Analytics Manager
- Data Engineer
Testimonials
Sebastian
I had a wonderful experience in taking the Hadoop course from Educba. I loved the way the classes and content are organized. The course gave an effective introduction to all the tools in Hadoop. The course is a great overview of MapReduce in Hadoop. It explains what it does, how it works and where it can be used effectively. It is a best course for beginners as well as for professionals. Highly recommend to anyone who is looking for a Big data course.
Katie
I took this online course about Hadoop from Educba and I was greatly satisfied. The course contains material which was professionally prepared and it was easy to understand even for the beginners. The real time examples given in the course helped to understand the concepts clearly and it made the learning process easy. The course structure and flow of the content was great. Each section had enough examples to explain the concept. Good course for beginners who wanted to learn about MapReduce.
John
I took this course few months back and I am glad that I decided to choose this course on Hadoop from Educba. The course offers quality learning experience at affordable cost. The classes and the contents of the course were organized in a proper structure. Each section of the course was very neatly explained with few real time examples. The flow of the course from one section to another was interlinked which made the learning process easy. The real life examples made the concepts easy to understand and helped to solve the daily issues in workplace. Overall a good course on Hadoop and MapReduce. Highly recommended.
