From 0 to 1: The Oozie Orchestration Framework
- 4 hours on-demand video
- 36 downloadable resources
- Full lifetime access
- Access on mobile and TV
- Certificate of Completion
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- Install and set up Oozie
- Configure Workflows to run jobs on Hadoop
- Configure time-triggered and data-triggered Workflows
- Configure data pipelines using Bundles
Run a simple MapReduce job using the command line. If you're comfortable running MR jobs you can simply skip this!
The attached zip files has a lot of MR examples, we just run the simplest one.
Workflows are basic Oozie building blocks, a brief introduction to how Workflows work
If you are unfamiliar with softwares that require working with a shell/command line environment, this video will be helpful for you. It explains how to update the PATH environment variable, which is needed to set up most Linux/Mac shell based softwares.
- 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
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
- 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