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APACHE HADOOP Administrator

Prerequisites

Prior knowledge of Apache Hadoop is not required. Unix/Linux administration knowledge will be helpful.

Associated Certification(s):

Upon completion of the course, attendees can go for CCAH or HDP Administrator. Certification is a great differentiator; it helps establish you as a leader in the field, providing employers and customers with tangible evidence of your skills and expertise.

Course Objectives

This four-day administrator training course for Apache Hadoop provides participants with a comprehensive understanding of all the steps necessary to operate and maintain a Hadoop cluster. From installation and configuration through load balancing and tuning. This training course is the best preparation for the real-world challenges faced by Hadoop administrators.

Course Content

Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, learning topics such as:

  • The internals of YARN, MapReduce, and HDFS
  • Determining the correct hardware and infrastructure for your cluster
  • Proper cluster configuration and deployment to integrate with the data center
  • How to load data into the cluster from dynamically-generated files using Flume and from RDBMS using Sqoop
  • Configuring the FairScheduler to provide service-level agreements for multiple users of a cluste
  • Best practices for preparing and maintaining Apache Hadoop in production
  • Troubleshooting, diagnosing, tuning, and solving Hadoop issues

Course Outline

Introduction

The Case for Apache Hadoop

  • Why Hadoop?
  • Core Hadoop Components
  • Fundamental Concepts

HDF

  • HDFS Features
  • Writing and Reading Files
  • NameNode Memory Considerations
  • Overview of HDFS Security> Using the Namenode Web UI
  • Using the Hadoop File Shell

Getting Data into HDFS

  • Ingesting Data from External Sources with
  • Flume
  • Ingesting Data from Relational Databases with Sqoop
  • Best Practices for Importing Data

YARN and MapReduce

  • What Is MapReduce?
  • Basic MapReduce Concepts
  • YARN Cluster Architecture
  • Resource Allocation
  • Failure Recovery
  • Using the YARN Web UI
  • MapReduce Version 1 Planning Your Hadoop Cluster
  • General Planning Considerations
  • Choosing the Right Hardware
  • Network Considerations
  • Configuring Nodes
  • Planning for Cluster Management Hadoop Installation and Initial Configuration
  • Deployment Types
  • Installing Hadoop
  • Specifying the Hadoop Configuration
  • Performing Initial HDFS Configuration
  • Performing Initial YARN and MapReduce Configuration
  • Hadoop Logging

Installing and Configuring Hive, Impala, and Pig

  • Hive
  • Impala
  • Pig Hadoop Clients
  • What is a Hadoop Client?
  • Installing and Configuring Hadoop Clients
  • Installing and Configuring Hue
  • Hue Authentication and Authorization Cloudera Manager / APACHE Ambari
  • The Motivation for Cloudera Manager /Apache Ambari
  • Cloudera Manager/ Apache Ambari Features
  • Express and Enterprise Versions
  • Cloudera Manager / Apache Ambari Topology
  • Installing Cloudera Manager / Apache Ambari
  • Installing Hadoop Using Cloudera Manager / Apache Ambari
  • Performing Basic Administration Tasks Using Cloudera Manager / Apache Ambari

Advanced Cluster Configuration

  • Configuring Hadoop Ports
  • Explicitly Including and Excluding Hosts
  • Configuring HDFS for Rack Awareness
  • Configuring HDFS High Availability Hadoop Security
  • Why Hadoop Security Is Important
  • Hadoop’s Security System Concepts
  • What Kerberos Is and How it Works Cluster Maintenance
  • Checking HDFS Status
  • Copying Data Between Clusters
  • Adding and Removing Cluster Nodes
  • Rebalancing the Cluster
  • Cluster Upgrading

Cluster Monitoring and Troubleshooting

  • General System Monitoring
  • Monitoring Hadoop Clusters
  • Common Troubleshooting Hadoop Clusters
  • Common Misconfigurations
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Agilitics Pte. Ltd. is a reknowned Big Data Analytics firm headquartered in Singapore with operations in mulitple countries. They are expert of big data and belive and spreading the knowledging for betterment of the Big Data community and generating bigger and better talent pool for industry.
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