Summary hadoop overview

Evolving Data Landscape: Big
Data Solutions - Hadoop
Ecosystem and Ongoing
Evolution
YARN Architecture and Components

 YARN Architecture
 ResourceManager
 NodeManager
 AppMaster
 YARN Components
 Scheduler
 Application Manager
Hadoop Distributed File System (HDFS)

 Understanding HDFS
 HDFS Overview
 HDFS Components
 Name Node
 Data Nodes
 Data Storage and Processing in Distributed
Systems
 HDFS Scalability and Commodity Hardware
 Data Storage with HDFS
 Configuring IP Address and Hostnames
 HDFS Web UI and Command-line Interfaces
 Data Replication and Scalability

,Hadoop MapReduce

 Introduction to MapReduce
 MapReduce Overview
 Data Processing in MapReduce
 MapReduce Programming Model
 MapReduce in Hadoop Version 1: Job Tracker and
Task Tracker
 Best Practices for MapReduce Development
 Processing Telecom Data with MapReduce
 Writing MapReduce Jobs for Common Use-cases
Setting Up and Configuring Hadoop

 Setting Up Network and IP Addresses
 Configuring Monitoring and Logging
 Setting Up NameNode and DataNodes
 Configuring a Hadoop cluster with two nodes
 Installing Essential Software
 Installing Java and Hadoop
 Creating a passwordless SSH setup
 Setting up root access and SSH connections
 HDFS Components: Name Node and Data Nodes
Volunteer Computing and Big Data
Challenges

 Volunteer Computing
 Big Data Challenges
Cloudera and Hortonworks Setup

,  Cloudera and Hortonworks Setup
Real-Time Insights: Big Data Analytics

 Unlocking Hidden Value from Data: The Power of
Big Data
 Cloud Architectures and Cluster Management
YARN: Yet Another Resource Negotiator

 Introducing YARN: Yet Another Resource
Negotiator
Managing Growing Data Volumes:
Distributed Storage Solutions

 Managing Growing Data Volumes: Distributed
Storage Solutions
Large-Scale Processing over Traditional
Databases

 Hadoop Ecosystem Evolution: Resources and
Scheduling
 Large-Scale Processing over Traditional
Databases
Hadoop Distributions

 Apache Hadoop Distributions
 Hadoop MapReduce: A Processing Model for Big
Data
MapReduce and YARN Components
Workflow

 Understanding MapReduce Components and
Workflow

,  Setting up root access and SSH connections
 Data Storage with HDFS
 Data Replication and Scalability
 Launching Hadoop Cluster Services
 Running MapReduce on a Hadoop Cluster
 Configuring IP Address and Hostnames
 Creating a passwordless SSH setup
 Configuring a Hadoop cluster with two nodes
 Setting Up Network and IP Addresses
 Configuring Monitoring and Logging
 Setting Up NameNode and DataNodes
 Installing Essential Software
 Installing Java and Hadoop
 HDFS Web UI and Command-line Interfaces
 HDFS Components: Name Node and Data Nodes
Writing MapReduce Jobs and YARN for
Common Use-cases

 Writing MapReduce Jobs for Common Use-cases
 Volunteer Computing and Big Data Challenges

Unlocking Hidden Value from
Data: The Power of Big Data -
Hadoop Ecosystem and Ongoing
Evolution
YARN Architecture and Components

 Yet Another Resource Negotiator (YARN) -
resource management layer for Hadoop