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Hadoop Administration
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Hadoop Administration Training

Learn ways to implement, manage the ongoing administration of a Hadoop cluster and to build powerful applications to analyse Big Data

Online & Classroom | Latest & Accredited Courseware | 100+ hrs of assignments

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Modes of Delivery

Key Features

Instructor Led Live online training
24 Hours total immersive Hands-on training sessions
Get mentored by an industry expert
Complete your own project by course completion
Log into the sessions from anywhere

Description

It has been predicted that Hadoop would be adopted by most of the Fortune 2000 organizations by 2020. This is not a surprise given that Big Data drives business intelligence and Hadoop can help analyse Big Data and aid in business development. As organizations are racing towards exploring the benefits of Hadoop, they are on the lookout for qualified, professional Hadoop specialists who have the technical expertise to manage Hadoop clusters in a development or production environment. Zeolearn’s course on Hadoop Administration introduces you to the fundamental concepts of Apache Hadoop™ and Hadoop cluster. Through hands on exercises and practice sessions you will learn to configure, deploy and maintain a Hadoop cluster, and to confidently navigate the Hadoop ecosystem. By the end of this session you will learn how to configure backup options, diagnose and recover node failures, and address any challenges related to Big Data and cloud services.

Here’s what you will learn!

  • Implement and manage the ongoing administration of a Hadoop cluster
  • Build powerful applications to analyse Big Data and learn to manage and monitor the Hadoop cluster
  • Ensure performance tuning of Hadoop clusters and Hadoop MapReduce routines

Is this course right for you?

System administrators, DBAs, Software architects, IT Managers, System Administrators and even students who want to learn about Hadoop will benefit from this course.

What do you need to be familiar with?

  • Basic knowledge of Linux
  • Knowledge of algorithms and computer science technicalities will also help

 

Curriculum

  1. Hadoop cluster architecture
  2. Data loading into HDFS
  3. Roles and Responsibilities of a Hadoop Cluster Administrator
  1. Hadoop server roles and their usage
  2. Rack awareness
  3. Write and Read
  4. Replication Pipeline
  5. Data Processing
  6. Hadoop Installation and Initial Configuration
  7. Deploying Hadoop in pseudo-distributed mode
  8. Deploying a multi-node Hadoop cluster
  9. Installing Hadoop Clients
  1. Selecting the appropriate hardware
  2. Designing a scalable cluster
  3. Building the cluster
    • Installing the Hadoop daemons
    • Optimizing the network architecture
  4. Managing and scheduling jobs
  5. Types of schedulers in Hadoop
  6. Configuring the schedulers and run MapReduce jobs
  7. Cluster monitoring and troubleshooting
  1. How to manage hardware failures
  2. Securing Hadoop clusters
  3. Configuring Hadoop backup
  4. Distcp to copy data
  5. Cluster maintenance
  6. Configuring HDFS Federation
  7. Basics of Hadoop Platform Security
  8. Securing the Platform
  9. Configuring Kerberos
  1. Isolating single points of failure
  2. Maintaining High Availability
  3. Triggering manual failover
  4. Automating failover with Zookeeper
  5. Extending HDFS resources
  6. Managing the namespace volumes
  7. Critiquing the YARN architecture
  8. Identifying the new daemons
  1. Starting and stopping Hadoop daemonso Monitoring HDFS status
  2. Adding and removing data nodes
  3. Managing MapReduce jobs
  4. Tracking progress with monitoring tools
  5. Commissioning and decommissioning compute nodes
  1. Oozie
  2. Hcatalog/Hive Administration
  3. HBase Architecture
  4. HBase setup
  5. HBase and Hive Integration
  6. HBase performance optimization

Frequently Asked Questions

Apache Hadoop™ is a dynamic platform that aids in distributed processing of large data sets across clusters of computers and servers. That makes it a vital technology in this era of Big Data analytics and processing. You can be an integral part of the data value chain, setting up and maintaining complex data sets while also enabling high-value analytics.Our course will teach you how to use Apache Hadoop™ and perform an administrator’s responsibilities of setting up, deploying and managing Hadoop clusters. With in-depth courseware and expert guidance from our faculty you will learn to tackle everyday problems and steer your career on the success path.
After completing our course, you will be able to:
  • Understand the concept of Hadoop Distributed File System (HDFS)
  • Build powerful applications using Apache Hadoop™ and analyse Big Data
  • Setup, manage and monitor Hadoop cluster
  • Understand how to deal with hardware failures and ensure data safety and recovery by implementing solutions
  • Get a fundamental understanding of Pig scripting language
  • To install Hive, run HiveQL queries to create tables, load data etc
  • Use Apache Sqoop to transfer data between Hadoop and relational databases
  • Use HBase to perform real-time read/write access to Big Data
Towards the end of the course, all participants will be required to work on a project to get hands on familiarity with the concepts learnt. You will build a Hadoop cluster, with full support from your mentors and use this Hadoop implementation to solve Big Data problems. This project, which can also be a live industry project, will be reviewed by our instructors and industry experts. On successful completion, you will be awarded a certificate.
Classes are held on weekdays and weekends. You can check available schedules and choose the batch timings which are convenient for you.
You may be required to put in 10 to 12 hours of effort every week, including the live class, self study and assignments.
  • Your classes will be held online. All you need is a windows computer with good internet connection to attend your classes online. A headset with microphone is recommended.
  • You may also attend these classes from your smart phone or tablet. 
Don’t worry, you can always access your class recording or opt to attend the missed session again in any other live batch.

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