Hadoop Overview

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Course Objectives

Become Hadoop Spark expert by learning core Big Data technologies and gain hands-on knowledge of Hadoop and Spark along with their eco-system components like HDFS, Map-Reduce, Sqoop, core Spark, Spark RDDs, Apache Spark SQL, and Spark Streaming through this Spark Hadoop course.

Target Audience

  • Software developers, Project Managers and architects
  • BI, ETL and Data Warehousing Professionals
  • Mainframe and testing Professionals
  • Business analysts and Analytics professionals
  • DBAs and DB professionals
  • Professionals willing to learn Data Science techniques
  • Any graduate focusing to build career in Big Data

Training Outline

The Case for Apache Hadoop
  • Why Hadoop?
  • Fundamental Concepts
  • Core Hadoop Components
Hadoop Cluster Installation
  • Rationale for a Cluster Management Solution
  • Cloudera Manager Features
  • Cloudera Manager Installation
  • Hadoop (CDH) Installation
The Hadoop Distributed File System (HDFS)
  • HDFS Features
  • Writing and Reading Files
  • NameNode Memory Considerations
  • Overview of HDFS Security
  • Web UIs for HDFS
  • Using the Hadoop File Shell
MapReduce and Spark on YARN
  • The Role of Computational Frameworks
  • YARN: The Cluster Resource Manager
  • MapReduce Concepts
  • Apache Spark Concepts
  • Running Computational Frameworks on YARN
  • Exploring YARN Applications Through the Web UIs, and the Shell
  • YARN Application Logs
Hadoop Configuration and Daemon Logs
  • Cloudera Manager Constructs for Managing Configurations
  • Locating Configurations and Applying Configuration Changes
  • Managing Role Instances and Adding Services
  • Configuring the HDFS Service
  • Configuring Hadoop Daemon Logs
  • Configuring the YARN Service
Getting Data Into HDFS
  • Ingesting Data from External Sources with Flume
  • Ingesting Data from Relational Databases with Sqoop
  • REST Interfaces
  • Introduction to Kafka & Use Cases
  • Best Practices for Importing Data
Planning Your Hadoop Cluster
  • General Planning Considerations
  • Choosing the Right Hardware
  • Virtualization Options*
  • Network Considerations
  • Configuring Nodes
Hadoop Clients Including Hue
  • What Are Hadoop Clients?
  • Installing and Configuring Hadoop Clients
  • Installing and Configuring Hue
  • Hue Authentication and Authorization
Hadoop Security
  • Why Hadoop Security Is Important
  • Hadoop’s Security System Concepts
  • What Kerberos Is and how it Works
  • Securing a Hadoop Cluster with Kerberos
  • Other Security Concepts
Managing Resources
  • Configuring cgroups with Static Service Pools
  • The Fair Scheduler
  • Configuring Dynamic Resource Pools
  • YARN Memory and CPU Settings
  • Impala Query Scheduling

Prerequisite

As such no prior knowledge of any technology is required to learn Big Data Spark and Hadoop.