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Big Data and Hadoop

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Updated On 02 Feb, 19

Overview

Introduction to Big Data & Hadoop - Big Data Learning Paths - Hadoop Tutorial for Beginners - Hadoop MapReduce Tutorial - Big Data - Hadoop - Introduction to MapReduce - MapReduce Programming Tutorial - Fundamentals of Hadoop MapReduce - Understanding Hadoop MapReduce - Hadoop Tutorial - What is Big Data - Big Data Explained - Hadoop & MapReduce - MapReduce Tutorial - Hadoop distributed cache - Advanced mapreduce - What is Big Data? - Why Learn Hadoop ? - Hadoop 2.0 Features - What is Hadoop - Hadoop Tutorial for Beginners - Hadoop Tutorial - What is Hadoop - Hadoop Basics - Hadoop for Beginners - Hadoop for Data Warehousing Professional - De-Identify Mapreduce Code - Mapreduce Tutorial - What is Hive - Why Hive - Apache Hive Tutorial - Understanding Concepts of Advanced Hive - Hive Scripting - Apache Hive Tutorial - Introduction to Apache Hive - Understanding Hive Commands in Apache Hadoop - Hive Data Model - Introduction to Sqoop - Demo on Hadoop Flume - Intro To Hadoop Developer Training - Cloudera - Introduction to Hadoop Zookeeper - Introduction to HBase - Intro To Hadoop Developer Training - Hadoop installation on ubuntu - TDD Using Pig Unit - Demo - Hadoop Pig Tutorial - What is Pig Unit & Why Unit Test Pig - Hadoop Pig Tutorial - What is Big data - Why learn Hadoop - Big data and Hadoop Tutorial - Learn Hadoop - What is HBase - Why Hbase - Hbase Tutorial - What is Oozie in Hadoop - Introduction to Advanced MapReduce - Advanced MapReduce Programming Tutorial - Hadoop Distributed Cache - Advanced Mapreduce Tutorial - Combiner & Partitioner in Hadoop - Hadoop Mapreduce Tutorial - Learn Hadoop - Debugging using MRUnit Testig Framework - Hadoop Tutorial for Beginners - Joins in Hadoop Mapreduce - Mapside Joins - Reduce Side Joins - Hadoop Mapreduce - Tutorial - Setup Pig on cloudera - Pig Installation Tutorial - What is Pig and Why Pig | Pig Explained - Hadoop Pig Tutorial - Demonstrating Word Count Example Using Pig Grunt Shell - Hadoop Pig Tutorial - Hbase Architecture - Pig vs Hive ? - Hadoop Vs Traditional Database Systems - Hadoop Data Warehouse - Hadoop and ETL - Hadoop Data Mining - Big Data Tutorial - Hadoop Training - Big Data Training - What is Hadoop? - Hadoop 1.x Arch Challenges - Hadoop 2.0 Architecture - YARN - Hadoop Jobs - Introduction to Hadoop Ecosystem - Introduction to Hdfs - Demo on big data applications - Demo on Hadoop Technology

Includes

Lecture 3: Big Data and Hadoop 2 | Hadoop Tutorial 2 |Big Data Tutorial 2 |Hadoop Tutorial for Beginners - 2

4.1 ( 11 )


Lecture Details

httpwww.edureka.cobig-data-and-hadoop?utm_source=youtube&utm_medium=referral&utm_campaign=big-data-hadoop-2

This is Part 1 of 10 Module Big Data and Hadoop course. The 3hr Interactive live class covers What is Big Data, What is Hadoop and Why Hadoop? You will understand How Hadoop solves the problem of Big Data with the existing Data Warehouse solutions based on traditional databases. You will also understand the details of Hadoop Architecture the Hadoop Distributed File System ( HDFS) and MapReduce framework. The Tutorial covers in detail about Name Node, Data Nodes, Secondary Name Node. It goes into the details of concepts like Rack Awareness, Data Replication, Reading and Writing on HDFS.

Start your Hadoop Journey with edureka!
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How it Works?

1. This is a 10-Module Instructor led Online Course. We have added 2 additional modules of 3-Hour each to cover Advance MapReduce and New Features in Hadoop 2.0 such as YARN, NameNode High Availability, HDFS Federation.
2. We have a 3-hour Live and Interactive Sessions.
3. We have 4 hours of Practical Work in each module involving Lab Assignments, Case Studies and Projects every week which can be done at your own pace. We can also provide you Remote Access to Our Hadoop Cluster for doing Practicals.
4. We have a 24x7 One-on-One LIVE Technical Support to help you with any problems you might face or any clarifications you may require during the course.
5. At the end of the training you will have to undergo a 2-hour LIVE Practical Exam based on which we will provide you a Grade and a Verifiable Certificate!
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About the Course

Big Data and Hadoop training course is designed to provide knowledge and skills to become a successful Hadoop Developer. In-depth knowledge of concepts such as Hadoop Distributed File System, Setting up the Hadoop Cluster, MapReduce, Advanced MapReduce, PIG, HIVE, HBase, Zookeeper, SQOOP, YARN, Hadoop 2.0 etc. will be covered in the course.
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Course Objectives

After the completion of the Hadoop Course at Edureka, you should be able to Master the concepts of Hadoop Distributed File System. Understand Cluster Setup and Installation. Understand MapReduce, Advance MapReduce and Functional programming. Understand How Pig is tightly coupled with MapReduce. Learn how to use Hive, How you can load data into HIVE and query data from Hive. Implement HBase, MapReduce Integration, Advanced Usage and Advanced Indexing. Have a good understanding of ZooKeeper service and Sqoop. Develop a working Hadoop Architecture.
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Who should go for this course?

This course is designed for developers with some programming experience (preferably Java) who are looking forward to acquire a solid foundation of Hadoop Architecture. Existing knowledge of Hadoop is not required for this course.
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Why Learn Hadoop?

BiG Data! A Worldwide Problem?

According to Wikipedia, "Big data is collection of data sets so large and complex that it becomes difficult to process using on-hand database management tools or traditional data processing applications." In simpler terms, Big Data is a term given to large volumes of data that organizations store and process. However, It is becoming very difficult for companies to store, retrieve and process the ever-increasing data. If any company gets hold on managing its data well, nothing can stop it from becoming the next BIG success!

The problem lies in the use of traditional systems to store enormous data. Though these systems were a success a few years ago, with increasing amount and complexity of data, these are soon becoming obsolete. The good news is - Hadoop, which is not less than a panacea for all those companies working with BIG DATA in a variety of applications and has become an integral part for storing, handling, evaluating and retrieving hundreds of terabytes, and even petabytes of data.
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Some of the top companies using Hadoop

The importance of Hadoop is evident from the fact that there are many global MNCs that are using Hadoop and consider it as an integral part of their functioning, such as companies like Yahoo and Facebook! On February 19, 2008, Yahoo! Inc. established the worlds largest Hadoop production application. The Yahoo! Search Webmap is a Hadoop application that runs on over 10,000 core Linux cluster and generates data that is now widely used in every Yahoo! Web search query.

Opportunities for Hadoopers!

Opportunities for Hadoopers are infinite - from a Hadoop Developer, to a Hadoop Tester or a Hadoop Architect, and so on. If cracking and managing BIG Data is your passion in life, then think no more and Join Edurekas Hadoop Online course and carve a niche for yourself! Happy Hadooping!

Please write back to us at hadoopsales@edureka.co or call us at +91-8880862004 for more information.
httpwww.edureka.cobig-data-and-hadoop

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Sam

Excellent course helped me understand topic that i couldn't while attendinfg my college.

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Dembe

Great course. Thank you very much.

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