What you'll learn

Commissioning & Decommissioning in Hadoop

Working of Namenodes

Setup the Environment on different OS

Basics to Start with an Introduction

Requirements

Core Java, Database Concepts etc.

Exposure of Linux OS

Description

Hadoop is an open-source framework that allows to store and process big data in a distributed environment across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage.This course provides a quick introduction to Big Data, MapReduce algorithm, and Hadoop Distributed File System.What Comes Under Big Data?Big data involves the data produced by different devices and applications. Given below are some of the fields that come under the umbrella of Big Data.Black Box Data − It is a component of helicopter, airplanes, and jets, etc. It captures voices of the flight crew, recordings of microphones and earphones, and the performance information of the aircraft.Social Media Data − Social media such as Facebook and Twitter hold information and the views posted by millions of people across the globe.Stock Exchange Data − The stock exchange data holds information about the ‘buy’ and ‘sell’ decisions made on a share of different companies made by the customers.Power Grid Data − The power grid data holds information consumed by a particular node with respect to a base station.Transport Data − Transport data includes model, capacity, distance and availability of a vehicle.Search Engine Data − Search engines retrieve lots of data from different databasesThis course has been prepared for professionals aspiring to learn the basics of Big Data Analytics using Hadoop Framework and become a Hadoop Developer. Software Professionals, Analytics Professionals, and ETL developers are the key beneficiaries of this course.Before you start proceeding with this course, we assume that you have prior exposure to Core Java, database concepts, and any of the Linux operating system flavors

Overview

Section 1: Module 1

Lecture 1 Metasave Command

Lecture 2 Dynamically Write Data with different Replication

Lecture 3 Rack Awareness

Lecture 4 Enabling Rack Awareness

Lecture 5 Default Rack

Lecture 6 Working of Secondary Namenode

Lecture 7 Secondary Namenode working in the Cluster Setup

Lecture 8 Shutting down the Namenode

Lecture 9 Manually talking to Namenode

Lecture 10 Safemode in Hadoop

Lecture 11 Using Namespace

Lecture 12 Commissioning and Decommissioning Nodes

Lecture 13 Setting for Commissioning Decommissioning

Hadoop Developer. Software Professionals, Analytics Professionals, and ETL developers etc.

https://www.filenext.com/3f99dwwoouex/Learn_Hadoop_in_a_Day_A_Big_Data_Course.rar.html