This Hortonworks (HDP) Hadoop Administration training program provides online training on the popular skills required for a successful career in Hadoop administration data engineering. Master the art of creating and managing Hadoop cluster using HDP management console called "Ambari". Also learn how to configure High availability of Namenode and ResourceManager, how to run Balancer tool, how to take up the back up and snapshot , how to create secure cluster using kerbros and Ranger.
Learning Objectives - In this module, you will understand day to day Cluster Administration tasks such as adding and Removing Data Nodes, NameNode recovery, configuring Backup and Recovery in Hadoop, Diagnosing the Node Failures in the Cluster, Hadoop Upgrade etc.
Topics -Configure Rack awareness, Setting up Hadoop Backup, whitelist and blacklist data nodes in a cluster, setup quota's, upgrade Hadoop cluster, copy data across clusters using distcp, Diagnostics and Recovery, Cluster Maintenance
Learning Objectives - In this module, you will understand basics of Hadoop security, Managing security with Kerberos, HDFS Federation setup and Log Management. You will also understand HDFS High Availability using Quorum Journal Manager (QJM).
Topics -Configuring HDFS Federation, Basics of Hadoop Platform Security, Securing the Platform, Configuring Kerberos
Data Loading : Here we will learn different data loading options available in Hadoop and will look into details about Flume and Sqoop to demonstrate how to bring various kind of files such as Web server logs , stream data, RDBMS, twetter ‘s tweet into HDFS.
• Configuration management
• YARN Architecture
• YARN Node Configuration
• Memory Consumption parameters
• Performance tuning of MR and YARN
• Logging and troubleshooting YARN Jobs
• YARN Capacity Scheduler
• YARN Isolation
Learning Objectives - In this module, you will understand Planning and Managing a Hadoop Cluster, Hadoop Cluster Monitoring and Troubleshooting, Analysing logs, and Auditing. You will also understand Scheduling and Executing MapReduce Jobs, and different Schedulers.
Topics -Planning the Hadoop Cluster, Cluster Size, Hardware and Software considerations, Managing and Scheduling Jobs, types of schedulers in Hadoop, Configuring the schedulers and run MapReduce jobs, Cluster Monitoring and Troubleshooting
Learning Objectives - In this module, you will understand Secondary NameNode setup and check pointing, HDP3.1 New Features, HDFS High Availability, YARN framework, and MRv2
Topics -Configuring Secondary NameNode, HDP3.1, YARN framework, MRv2, HDP3.1 Cluster setup, Deploying HDP3.1 in pseudo-distributed mode, deploying a multi-node HDP3.1 cluster
Hadoop cluster Installation Using Hortonworks Data Patform Distribution in AWS cloud
• Hadoop Installation
• Hadoop Configuration properties
• Hadoop Installation and Initial Configuration
• Deploying Hadoop in pseudo-distributed mode in local machine
• Mutinode Cluster setup on AWS Cloud
• Deploying a multi-node Hadoop cluster on AWS Cloud
• Add and Remove Cluster Nodes
• Zookeeper Configuration
Learning Objectives - After this module, you will understand Multiple Hadoop Server roles such as NameNode and DataNode, and MapReduce data processing. You will also understand the HDP 3.1 Cluster setup and configuration, Setting up Hadoop Clients using HDP3.1, and important Hadoop configuration files and parameters.
Topics -Hadoop server roles and their usage, Rack Awareness, Anatomy of Write and Read, Replication Pipeline, Data Processing, Hadoop Installation and Initial Configuration, Deploying Hadoop in pseudo-distributed mode, deploying a multi-node Hadoop cluster, Installing Hadoop Clients
HDFS Lab: Understanding How blocks are created in HDFS and physical location of the blocks
HDFS Configuration properties walkthrough
Interfacing HDFS through Command line and Browser
Namenode UI
HDFS Shell commands to write ,read, delete files/directories. export data from HDFS to local file system.
Learning Objectives - In this module, you will understand what is Big Data and Apache Hadoop, How Hadoop solves the Big Data problems, Hadoop Cluster Architecture, Introduction to MapReduce framework, Hadoop Data Loading techniques, and Role of a Hadoop Cluster Administrator.
Topics -Introduction to Big Data, Hadoop Architecture, MapReduce Framework, A typical Hadoop Cluster, Data Loading into HDFS, Hadoop Cluster Administrator: Roles and Responsibilities
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Let our experts clear your doubts
A real time project will be provided.
Mukesh has overall 15 years of industry experience, started his career as Software project engineer and worked in different roles such as Project Lead, Software Architect and Enterprise Architect for over 12 years. In the last 3 years, he hasworked as professional consultant and cooperate trainer for conducting workshop and training programs in the area of Big Data Analytics and helping client’s migrating their data platform and applications to Big Data platform to leverage the scalability and cost effectiveness of these platforms.
Attend one complete batch.
Complete one project and one simulation test with a minimum score of 80%.
Online Self-Learning:
Complete 85% of the course.
Complete one project and one simulation test with a minimum score of 80%.
Tech Eureka's Blended Learning model brings classroom learning experience online with its world-class LMS. It combines instructor-led training, self-paced learning and personalized mentoring to provide an immersive learning experience
We offer 24/7 support through email, chat, and calls. We also have a dedicated team that provides on-demand assistance through our community forum. What’s more, you will have lifetime access to the community forum, even after completion of your course with us
Techeureka has Flexi-pass that lets you attend classes to blend in with your busy schedule and gives you an advantage of being trained by world-class faculty with decades of industry experience combining the best of online classroom training and self-paced learning
With Flexi-pass, Techeureka gives you access to as many as 15 sessions for 90 days
This Course will conducted by Mr Mukesh Kumar who has trained 15,000 people and conducted more than 500 batches of Big data training.
Contact us using the form on the right of any page on our website, or select the Live Chat link. Our customer service representatives can provide you with more details.
Payments can be made using any of the following options. You will be emailed a receipt after the payment is made.
Yes, you can cancel your enrollment if necessary. We will refund the course price after deducting an administration fee. To learn more, you can view our Refund Policy.
We offer a flexible set of options:
To run Hadoop, your system must fulfill the following requirements:
We will help you to set up a Virtual Machine with local access. For this training we will provide AWS instance to create a cluster.
Hadoop is one of the leading edge technological frameworks that is being widely used for big data. To learn Hadoop Administration, you just need to unix commands. Our extensive course on Hadoop Administrator will help prepare you for your future in big data.
Big data refers to massive data sets which gets generated are stored by different IT application and products of the organizations; the goal is to leverage big data to make insightful organizational decisions. These data sets contain both structured and unstructured data which are very complex and huge that they can't be handled using traditional techniques. Hadoop is an open-source framework that allows you to efficiently store and process big data in a parallel and distributed