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From 0 To 1: The Oozie Orchestration Framework
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.99 GB | Duration: 4h 1m
A first-principles guide to working with Workflows, Coordinators and Bundles in Oozie
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz
Language: English | Size: 1.99 GB | Duration: 4h 1m
A first-principles guide to working with Workflows, Coordinators and Bundles in Oozie
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
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
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