From 0 to 1 The Oozie Orchestration Framework

A first-principles guide to working with Workflows, Coordinators and Bundles in Oozie
From 0 to 1 The Oozie Orchestration Framework
File Size :
2.00 GB
Total length :
4h 1m



Loony Corn


Last update




From 0 to 1 The Oozie Orchestration Framework

What you’ll learn

Install and set up Oozie
Configure Workflows to run jobs on Hadoop
Configure time-triggered and data-triggered Workflows
Configure data pipelines using Bundles

From 0 to 1 The Oozie Orchestration Framework


Students should have basic knowledge of the Hadoop eco-system and should be able to run MapReduce jobs on Hadoop


Prerequisites: Working with Oozie requires some basic knowledge of the Hadoop eco-system and running MapReduce jobs
Taught by a team which includes 2 Stanford-educated, ex-Googlers  and 2 ex-Flipkart Lead Analysts. This team has decades of practical experience in working with large-scale data processing jobs. 

Oozie is like the formidable, yet super-efficient admin assistant who can get things done for you, if you know how to ask
Let’s parse that 
formidable, yet super-efficient: Oozie is formidable because it is entirely written in XML, which is hard to debug when things go wrong. However, once you’ve figured out how to work with it, it’s like magic. Complex dependencies, managing a multitude of jobs at different time schedules, managing entire data pipelines are all made easy with Oozie
get things done for you: Oozie allows you to manage Hadoop jobs as well as Java programs, scripts and any other executable with the same basic set up. It manages your dependencies cleanly and logically. 
if you know how to ask: Knowing the right configurations parameters which gets the job done, that is the key to mastering Oozie
What’s Covered: 
Workflow Management: Workflow specifications, Action nodes, Control nodes, Global configuration, real examples with MapReduce and Shell actions which you can run and tweak
Time-based and data-based triggers for Workflows: Coordinator specification, Mimicing simple cron jobs, specifying time and data availability triggers for Workflows, dealing with backlog, running time-triggered and data-triggered coordinator actions
Data Pipelines using Bundles: Bundle specification, the kick-off time for bundles, running a bundle on Oozie


Section 1: Introduction

Lecture 1 You, This Course and Us

Section 2: A Brief Overview Of Oozie

Lecture 2 What is Oozie?

Lecture 3 Oozie architectural components

Section 3: Oozie Install And Set Up

Lecture 4 Installing Oozie on your machine

Section 4: Workflows: A Directed Acyclic Graph Of Tasks

Lecture 5 Running MapReduce on the command line

Lecture 6 The lifecycle of a Workflow

Lecture 7 Running our first Oozie Workflow MapReduce application

Lecture 8 The file

Lecture 9 The workflow.xml file

Lecture 10 A Shell action Workflow

Lecture 11 Control nodes, Action nodes and Global configurations within Workflows

Section 5: Coordinators: Managing Workflows

Lecture 12 Running our first Coordinator application

Lecture 13 A time-triggered Coordinator definition

Lecture 14 Coordinator control mechanisms

Lecture 15 Data availability triggers

Lecture 16 Running a Coordinator which waits for input data

Lecture 17 Coordinator configuration to use data triggers

Section 6: Bundles: A Collection Of Coordinators For Data Pipelines

Lecture 18 Bundles and why we need them

Lecture 19 The Bundle kick-off time

Section 7: Installing Hadoop in a Local Environment

Lecture 20 Hadoop Install Modes

Lecture 21 Hadoop Install Step 1 : Standalone Mode

Lecture 22 Hadoop Install Step 2 : Pseudo-Distributed Mode

Section 8: Appendix

Lecture 23 [For Linux/Mac OS Shell Newbies] Path and other Environment Variables

Lecture 24 Setting up a Virtual Linux Instance – For Windows Users

Yep! Engineers, analysts and sysadmins who are interested in big data processing on Hadoop,Nope! Beginners who have no knowledge of the Hadoop eco-system

Course Information:

Udemy | English | 4h 1m | 2.00 GB
Created by: Loony Corn

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