From 0 to 1: The Oozie Orchestration Framework
From 0 to 1: The Oozie Orchestration Framework, available at $64.99, has an average rating of 4.35, with 24 lectures, based on 586 reviews, and has 5203 subscribers.
You will learn about Install and set up Oozie Configure Workflows to run jobs on Hadoop Configure time-triggered and data-triggered Workflows Configure data pipelines using Bundles This course is ideal for individuals who are Yep! Engineers, analysts and sysadmins who are interested in big data processing on Hadoop or Nope! Beginners who have no knowledge of the Hadoop eco-system It is particularly useful for Yep! Engineers, analysts and sysadmins who are interested in big data processing on Hadoop or Nope! Beginners who have no knowledge of the Hadoop eco-system.
Enroll now: From 0 to 1: The Oozie Orchestration Framework
Summary
Title: From 0 to 1: The Oozie Orchestration Framework
Price: $64.99
Average Rating: 4.35
Number of Lectures: 24
Number of Published Lectures: 24
Number of Curriculum Items: 24
Number of Published Curriculum Objects: 24
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will 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
Who Should Attend
- 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
Target Audiences
- 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
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
Course Curriculum
Chapter 1: Introduction
Lecture 1: You, This Course and Us
Chapter 2: A Brief Overview Of Oozie
Lecture 1: What is Oozie?
Lecture 2: Oozie architectural components
Chapter 3: Oozie Install And Set Up
Lecture 1: Installing Oozie on your machine
Chapter 4: Workflows: A Directed Acyclic Graph Of Tasks
Lecture 1: Running MapReduce on the command line
Lecture 2: The lifecycle of a Workflow
Lecture 3: Running our first Oozie Workflow MapReduce application
Lecture 4: The job.properties file
Lecture 5: The workflow.xml file
Lecture 6: A Shell action Workflow
Lecture 7: Control nodes, Action nodes and Global configurations within Workflows
Chapter 5: Coordinators: Managing Workflows
Lecture 1: Running our first Coordinator application
Lecture 2: A time-triggered Coordinator definition
Lecture 3: Coordinator control mechanisms
Lecture 4: Data availability triggers
Lecture 5: Running a Coordinator which waits for input data
Lecture 6: Coordinator configuration to use data triggers
Chapter 6: Bundles: A Collection Of Coordinators For Data Pipelines
Lecture 1: Bundles and why we need them
Lecture 2: The Bundle kick-off time
Chapter 7: Installing Hadoop in a Local Environment
Lecture 1: Hadoop Install Modes
Lecture 2: Hadoop Install Step 1 : Standalone Mode
Lecture 3: Hadoop Install Step 2 : Pseudo-Distributed Mode
Chapter 8: Appendix
Lecture 1: [For Linux/Mac OS Shell Newbies] Path and other Environment Variables
Lecture 2: Setting up a Virtual Linux Instance – For Windows Users
Instructors
-
Loony Corn
An ex-Google, Stanford and Flipkart team
Rating Distribution
- 1 stars: 4 votes
- 2 stars: 15 votes
- 3 stars: 65 votes
- 4 stars: 224 votes
- 5 stars: 278 votes
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