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Development Development Tools Oozie

From 0 to 1: The Oozie Orchestration Framework

A first-principles guide to working with Workflows, Coordinators and Bundles in Oozie
Rating: 4.4 out of 54.4 (293 ratings)
3,913 students
Created by Loony Corn
Last updated 2/2018
English
English [Auto]
30-Day Money-Back Guarantee

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
Curated for the Udemy for Business collection

Course content

8 sections • 24 lectures • 4h 1m total length

  • Preview01:38

  • What is Oozie?
    Preview11:16
  • Oozie architectural components
    10:45

  • Installing Oozie on your machine
    16:28

  • Preview04:40
  • Preview06:12
  • Running our first Oozie Workflow MapReduce application
    11:15
  • The job.properties file
    08:45
  • The workflow.xml file
    12:06
  • A Shell action Workflow
    07:46
  • Control nodes, Action nodes and Global configurations within Workflows
    09:57

  • Running our first Coordinator application
    12:27
  • A time-triggered Coordinator definition
    08:52
  • Coordinator control mechanisms
    07:09
  • Data availability triggers
    10:03
  • Running a Coordinator which waits for input data
    06:11
  • Coordinator configuration to use data triggers
    15:25

  • Bundles and why we need them
    09:15
  • The Bundle kick-off time
    11:11

  • Hadoop Install Modes
    08:32
  • Hadoop Install Step 1 : Standalone Mode
    15:46
  • Hadoop Install Step 2 : Pseudo-Distributed Mode
    11:44

  • [For Linux/Mac OS Shell Newbies] Path and other Environment Variables
    08:25
  • Setting up a Virtual Linux Instance - For Windows Users
    15:58

Requirements

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

Description

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

Who this course is for:

  • 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

Instructor

Loony Corn
An ex-Google, Stanford and Flipkart team
Loony Corn
  • 4.2 Instructor Rating
  • 21,696 Reviews
  • 129,267 Students
  • 73 Courses

Loonycorn is us, Janani Ravi and Vitthal Srinivasan. Between us, we have studied at Stanford, been admitted to IIM Ahmedabad and have spent years  working in tech, in the Bay Area, New York, Singapore and Bangalore.

Janani: 7 years at Google (New York, Singapore); Studied at Stanford; also worked at Flipkart and Microsoft

Vitthal: Also Google (Singapore) and studied at Stanford; Flipkart, Credit Suisse and INSEAD too

We think we might have hit upon a neat way of teaching complicated tech courses in a funny, practical, engaging way, which is why we are so excited to be here on Udemy!

We hope you will try our offerings, and think you'll like them :-)

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