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Hadoop Administration Course Certification Training

Hadoop Administration Training

Deep dive into Hadoop with practical examples and become an expert Hadoop Administrator

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Prerequisites for Hadoop Administration Course

Prerequisites and Eligibility
Prerequisites and Eligibility
  • 450K+
    Career Transformations
  • 250+
    Workshops Every Month
  • 100+
    Countries

Hadoop Administration Course Highlights

Course Highlights

Master Hadoop architecture, HDFS, and the Hadoop ecosystem

Master cluster configuration, management, and monitoring

Implement real-time data processing with Hadoop tools

Work on projects in banking, e-commerce, and other industries


Advance with a Hadoop certification

Learn Apache Hive, HBase, and Sqoop for efficient data handling

Apache Hadoop™ is an effective and dynamic data platform that simplifies and allows for the distributed processing of large data sets across clusters of computers and servers. Hadoop is the perfect choice for organizations that have to deal with the challenges involved in handling vast amounts of structured and unstructured data. The Hadoop framework is used for analyzing data and helping them to make informed business decisions that are based on the insights gleaned from the data.

This ever-increasing data and the need to analyze it for favorable business outcomes has in turn increased the demand for professionals skilled in Hadoop and data analysis. A Hadoop Administrator’s primary responsibility is to manage the deployment and maintenance of Hadoop clusters. In other words, a Hadoop admin ensures smooth operation of Hadoop clusters, problem mitigation, safety and improved performance. A training in Hadoop Administration will help prepare you for the demands of the industry. New innovations in technology have made it mandatory for IT professionals to be on par with the latest developments. A Hadoop Administrator training will ensure that there is no skill gap between what you know and what the industry wants, thus making you a valuable employee. Furthermore, the demand for data analysts has seen a meteoric rise in the past few years, thus making certified Hadoop Administrators a niche resource.

Benefits

Hadoop is the perfect solution for the challenges faced by vast amounts of unstructured data that are a goldmine when analyzed. Hadoop certification benefits not just the holder but also the organizations who hire them.

Why KnowledgeHut For Hadoop Administration Course

The KnowledgeHut Advantage

Instructor-led Live Classroom

Interact with instructors in real-time— listen, learn, question and apply. Our instructors are industry experts and deliver hands-on learning.

Curriculum Designed by Experts

Our courseware is always current and updated with the latest tech advancements. Stay globally relevant and empower yourself with the latest training!

Learn through Doing

Learn theory backed by practical case studies, exercises, and coding practice. Get skills and knowledge that can be applied effectively.

Mentored by Industry Leaders

Learn from the best in the field. Our expert mentors are all experienced professionals in the fields they teach.

Advance from the Basics

Learn concepts from scratch, and advance your learning through step-by-step guidance on tools and techniques.

Code Reviews by Professionals

Get detailed reviews and feedback on your final projects from professional developers with industry experience.

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Hadoop Administration Course Curriculum

Curriculum

1. Introduction to Big Data and Hadoop

Learning Objective :

Understanding what is Big Data and its solution for traditional Problems. You will learn about Hadoop and its core components and you will know how to read and write happens in HDFS. You will also know the roles and responsibilities of a Hadoop Administrator.

Topics :

  • Introduction to big data
  • Limitations of existing solutions
  • Common Big Data domain scenarios
  • Hadoop Architecture
  • Hadoop Components and Ecosystem
  • Data loading & Reading from HDFS
  • Replication Rules
  • Rack Awareness theory
  • Hadoop cluster Administrator: Roles and Responsibilities.

Hands-on:

Writing and Reading the Data from hdfs, how to submit the job in Hadoop 1.0 and YARN.

2. Hadoop Cluster and its Architecture

Learning Objectives:

Understanding different Configuration files and building Hadoop Multi Node Cluster. Differences in Hadoop 1.0 and Hadoop 2.0. You will also get to know the architecture of Hadoop 1.0 and Hadoop2.0(YARN).

Topics

  • Working of HDFS and its internals
  • Hadoop Server roles and their usage
  • Hadoop Installation and Initial configuration
  • Different Modes of Hadoop Cluster.
  • Deploying Hadoop in a Pseudo-distributed mode
  • Deploying a Multi-node Hadoop cluster
  • Installing Hadoop Clients
  • Understanding the working of HDFS and resolving simulated problems.
  • Hadoop 1 and its Core Components.
  • Hadoop 2 and its Core Components.

Hands-on:

Creating Pseudo and Fully Distributed Hadoop Cluster. Changing different configuration Properties while submitting the Jobs and different hdfs admin commands.

3. Hadoop Cluster Administration and Understanding Different Processing Frameworks on Hadoop

Learning Objectives:

Understanding the various properties of Namenode, Data node, and Secondary Namenode. You will also learn how to add and decommission the data node to the cluster. You will also learn Various Processing frameworks in Hadoop and its Architecture in the context of Hadoop administrator and schedulers.

Topics:

  • Properties of NameNode, DataNode and Secondary Namenode
  • OS Tuning for Hadoop Performance
  • Understanding Secondary Namenode
  • Log Files in Hadoop
  • Working with Hadoop distributed cluster
  • Decommissioning or commissioning of nodes
  • Different Processing Frameworks
  • Understanding MapReduce
  • Spark and its Features
  • Application Workflow in YARN
  • YARN Metrics
  • YARN Capacity Scheduler and Fair Scheduler
  • Understanding Schedulers and enabling them.

Hands-on:

Changing the configuration files of Secondary Namenode. Add and remove the data nodes in a Distributed Cluster. And also Changes Schedulers in run time while submitting the jobs to YARN.

4. Hadoop Cluster Administration and Maintenance

Learning Objectives:

You will learn regular Cluster Administration tasks like balancing data in the cluster, protecting data by enabling trash, attempting a manual failover, creating backup within or across clusters

Topics:

  • Namenode Federation in Hadoop
  • HDFS Balancer
  • High Availability in Hadoop
  • Enabling Trash Functionality
  • Checkpointing in Hadoop
  • DistCP and Disk Balancer.

Hands-on:

Works with Cluster Administration and Maintenance tasks. Runs DistCP and HDFS Balancer Commands to get even distribution of the data.

5. Backup, Recovery, And Maintenance

Learning Objectives:

You will learn how to take Backup and recovery of data in master and slaves. You will also learn about allocating Quota to the master and slaves files.

Topics:

  • Key Admin commands like DFSADMIN
  • Safemode
  • Importing Check Point
  • MetaSave command
  • Data backup and recovery
  • Backup vs Disaster recovery
  • Namespace count quota or space quota
  • Manual failover or metadata recovery.

Hands-on:

Do regular backup using MetaSave commands. You will also run commands to do data Recovery using Checkpoints.

6. Hadoop 2.0 Cluster: Planning and Management

Learning Objective:

You will understand about Cluster Planning and Managing, what are the aspects you need to think about when planning a setup of a new cluster.

Topics :

  • Planning a Hadoop 2.0 cluster
  • Cluster sizing
  • Hardware
  • Network and Software considerations
  • Popular Hadoop distributions
  • Workload and usage patterns
  • Industry recommendations.

Hands-on:

Setting up a new Cluster and scaling Dynamically. Login to different Hadoop distributions online.

7. Hadoop Security and Cluster Monitoring

Learning Objectives:

You will get to know about the Hadoop cluster monitoring and security concepts. You will also learn how to secure a Hadoop cluster with Kerberos.

Topics :

  • Monitoring Hadoop Clusters
  • Authentication & Authorization
  • Nagios and Ganglia
  • Hadoop Security System Concepts
  • Securing a Hadoop Cluster With Kerberos
  • Common Misconfigurations
  • Overview on Kerberos
  • Checking log files to understand Hadoop clusters for troubleshooting.

Hands-on:

Monitor the cluster and also authorization of Hadoop resource by granting tickets using Kerberos.

8. Hadoop 2.0 With High Availability And Upgrading

Learning Objectives:

You will learn how to configure Hadoop2 with high availability and upgrading. You will also learn how to work with the Hadoop ecosystem.

Topics :

  • Configuring Hadoop 2 with high availability
  • Upgrading to Hadoop 2
  • Working with Sqoop
  • Understanding Oozie
  • Working with Hive.
  • Working with Pig.

Hands-on:

Login to the Hive and Pig shell with their respective commands. You will also schedule OOZIE Job.

9. Cloudera Manager And Cluster Setup

Learning Objectives:

You will see how to work with CDH and its administration tool Cloudera Manager. You will also learn ecosystem administration and its optimization.

Topics:

  • Cloudera Manager and cluster setup
  • Hive administration
  • HBase architecture
  • HBase setup
  • Hadoop/Hive/Hbase performance optimization.
  • Pig setup and working with a grunt.

Hands-on:

Install CDH and works with Cloudera Manager. Install new parcel in CDH machine.

What You'll Learn in the Hadoop Administration Course

Learning Objectives
1
Build Powerful Applications

Understand how to use Apache Hadoop™ software to build powerful applications to analyze Big Data.

2
Hadoop Distributed File System (HDFS)

Learn about Hadoop Distributed File System (HDFS) and its role in web-scale big data analytics.

3
Cluster Management in Hadoop

Let’s see what is cluster management in Hadoop and how to set up, manage and monitor Hadoop cluster.

4
Apache Hive installation

Know the basics of Apache Hive, how to install Hive, run HiveQL queries to create tables, & so on.

5
Running scripts

Learn more on Apache Sqoop, how to run scripts to transfer data between Hadoop & relational databases.

6
Apache HBase

Know the basics of Apache HBase, how to perform real-time read/write access to your Big Data.

Who can attend the Hadoop Administration Course

Who This Course Is For?
  • DevOps Engineers
  • Architects
  • Project Managers
  • Linux / Unix Administrators
  • Database Administrators
  • Windows Administrators
  • Infrastructure Administrators
  • System Administrators
  • Analytics Professionals
  • Senior IT professionals
  • Data Management Professionals
  • Testing and Mainframe professionals
  • Business Intelligence Professionals
Who Should Attend

Hadoop Administration Course FAQs

Frequently Asked Questions
Hadoop Administration

1. What exactly does a Hadoop Administrator do?

A Hadoop administrator administers and manages the set of Hadoop clusters. A Hadoop administrator’s responsibilities include setting up Hadoop clusters, backup, recovery and maintenance of the clusters. Good knowledge of Hadoop architecture is required to become a Hadoop administrator. Some of the key responsibilities of a Hadoop Administrator are:

  • Takes care of the day-to-day running of Hadoop Clusters.
  • Makes sure that Hadoop cluster is running all the time.
  • Responsible for managing and reviewing Hadoop log files.
  • Responsible for capacity planning and estimating the requirements.
  • Implementation of ongoing Hadoop infrastructure.
  • Cluster maintenance along with the creation and removal of nodes.
  • Keeping an eye on Hadoop cluster security and connectivity.
  • Tuning the performance of Hadoop clusters.
  • Managing and reviewing the log files of Hadoop.

2. How does Hadoop work?

Hadoop mainly consists of three layers:

  • HDFS (Hadoop Distributed File System): the place where all the data is stored,
  • Application layer (on which the MapReduce engine sits): to process the stored data, and
  • YARN: which allocates the resources to various slaves. All of these are operating on Master and Slave nodes.

3. Is Hadoop a framework or a programming language?

Hadoop is an open-source framework written in Java that enables the distributed processing of large datasets. Hadoop is not a programming language.

4. What is the difference between a Hadoop developer and an administrator?

Hadoop developers are needed to develop or program applications whereas administrators are required to run those applications. Let’s see how Hadoop developer and administrator differ from each other in terms of roles and responsibilities:

A few responsibilities of Hadoop Administrator:

  • Installing Hadoop in a Linux environment
  • Runningand maintaininga Hadoop cluster
  • Ensuringthat a Hadoop cluster is running all the time
  • Creation and removal of a new node in a cluster environment
  • Implementingand administeringHadoop infrastructure continuously

A few responsibilities of Hadoop developer:

  • To load data using ETL tools from various platforms into the Hadoop platform
  • Deciding a file format that would be most effective for a task
  • Cleaning data using user-defined functions or streaming API based on the requirements
  • Definingthe job flow in Hadoop
  • Maintaining, scheduling, and managinglog files.

5. What are the different components of the Hadoop ecosystem?

Following is a list of different components of the Hadoop ecosystem:

  • HDFS
  • MapReduce
  • YARN
  • Hive
  • Apache Pig
  • Apache HBase
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