Workflow on Hadoop Using Oozie__HadoopSummit2010
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Hadoop Summit 2010 - Developers Track Workflow on Hadoop Using Oozie Alejandro Abdelnur, Yahoo!
![Yahoo! Workflow Engine for Hadoop ,[object Object],Yahoo!](https://image.slidesharecdn.com/5ooziehadoopsummit2010-100630134430-phpapp02/85/Workflow-on-Hadoop-Using-Oozie__HadoopSummit2010-1-320.jpg)
![[object Object],[object Object],[object Object],Session Agenda](data:image/gif;base64,R0lGODlhAQABAIAAAAAAAP///yH5BAEAAAAALAAAAAABAAEAAAIBRAA7)
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Workflow on Hadoop Using Oozie__HadoopSummit2010
- 13. Use Cases: Data Pipelines WS f (5min) PH1 1:05 f (60min) PH1 1:10 PH1 1:15 PH1 2:00 LOG 1:05 LOG 1:10 LOG 1:15 LOG 2:00 PH2 2:00 01JAN 31DEC 01JAN 31DEC 1:05 1:10 2:00 1:15 2:00
- 15. Coordinator Input and Output Data PH1 1:05 f j (60min) PH1 1:10 PH1 1:15 PH1 2:00 PH2 2:00 01JAN 31DEC 2:00 ${current(0)} ${current(-11)} ${current(0)} ${current(-10)} ${current(-9)} f i (5min) f o (60min) IN Workflow OUT
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- Let me try to formalize things a bit A coordinator application can be parameterized, the locations of their inputs and outputs, special settings for the workflows jobs. They have a start and end date and a frequency, which also can be parameterized. On every frequency tick a workflow job is scheduled but the workflow is in WAITING state until all the INPUT is available A coordinator application defines all its input and an output. And they are normally related to the frequency and the time the workflow jobs are scheduled.
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