This web-based training course on Oozie functionality, administration and development, is available online to all individuals, institutions, corporates and enterprises in India (New Delhi NCR, Bangalore, Chennai, Kolkatta), US, UK, Canada, Australia, Singapore, United Arab Emirates (UAE), China and South Africa. No matter where you are located, you can enroll for any training with us - because all our training sessions are delivered online by live instructors using interactive, intensive learning methods.

Oozie is an open source project which aims to make the workflow in the Hadoop ecosystem much simpler and also create effective coordination between different jobs for convenience and ease of handling. Using projects of Oozie, different actions and jobs can be created along with the possible inter-dependencies between the jobs and further execute the actions depending on the fulfillment of the necessary dependencies. There are several components of Oozie which perform its numerous tasks such as Directed Acyclical graph which provides definition for the actions. Oozie is quite flexible when it comes to the types of tasks to be handled as the action nodes present in oozie can act as jobs for many platforms such as MapReduce, Java app or even Pig applications. The workflow process used in Oozie is a varied collection of various action types arranged as predefined by the DAG with reference to the sequence in which the actions are to be performed. The DAG is degined through a specific XML language known as hDPL which makes use of minimal amount of action nodes and flow control nodes in their structure.

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Course Details

This Apache Oozie Big Data online training course provides a clear and in-depth understanding of the entire Oozie structure and its workflow characteristics. The trainees will learn to run dependent data processing jobs in groups implement the required timing patterns for running them. Sufficient information will be provided about the work flow engine required to run DAGs of actions with coordinators such as cron job or scheduler. This Apache Oozie online training course also provides information about integrating the Hadoop stack supporting Hadoop MapReduce jobs with Apache Oozie. The trainees will learn to create multiple jobs attached to the single logical unit of labor and perform the actions related to DAG while supporting variables and functions. To successfully complete this course, it is advised that the trainees have a basic knowledge of data processing and Hadoop. Knowledge of JavaScript will be an added advantage in this course.

Introduction Of Oozie

  • Understanding the basics of Oozie
  • The architectural components of Oozie
  • Installation and Set Up of Oozie

Workflows: Understanding Directed Acyclic Graph Of Tasks

  • How to run MapReduce on the command line
  • Understanding the lifecycle of a Workflow
  • Creating and running our first Oozie Workflow MapReduce application
  • Working with the job.properties file
  • Working with the workflow.xml file
  • Developing Shell action Workflow
  • Working with Control nodes, Action nodes and Global configurations within Workflows

Managing Workflows with coordinators

  • Creating and running our first Coordinator application
  • Defining a time-triggered Coordinator
  • Mechanisms of Coordinator control
  • The various data availability triggers
  • How to run a Coordinator which waits for input data
  • Using data triggers for coordinator configuration

Using Bundles as a Collection Of Coordinators For Data Pipelines

  • Need and use of Bundles
  • The kick off time of Bundles

Installation of Hadoop in a Local Environment

  • The various modes of installing Hadoop
  • Setting up a Virtual Linux Instance (For Windows users)
  • Hadoop Standalone mode Install
  • Hadoop Pseudo-Distributed mode Install
Live Instructor-led & Interactive Online Sessions

Regular Course

Duration : 40 Hours

Capsule Course

Duration : 4-8 Hours

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Training Options


Weekdays- Cloud Based Training

Mon - Fri 07:00 AM - 09:00 AM(Mon, Wed, Fri)

Weekdays Online Lab

Mon - Fri 07:00 AM - 09:00 AM(Tue, Thur)


Weekend- Cloud Based Training

Sat-Sun 09:00 AM - 11:00 AM (IST)

Weekend Online Lab

Sat-Sun 11:00 AM - 01:00 PM

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