Course details
This course is designed to introduce advanced parallel job development techniques in DataStage V9.1. In this course you will develop a deeper understanding of the DataStage architecture, including a deeper understanding of the DataStage development and runtime environments. This will enable you to design parallel jobs that are robust, less subject to errors, reusable, and optimized for better performance.
Target Audience:
This advanced course is for experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek an understanding of the parallel framework architecture.
Prerequisites:
You should have:
- taken DataStage Essentials course or equivalent
- and at least one year of experience developing parallel jobs using DataStage
Content:
- Unit 1 - Introduction to the Parallel Framework Architecture
- Unit 2 - Compilation and Execution
- Unit 3 - Partitioning and Collecting Data
- Unit 4 - Sorting Data
- Unit 5 - Buffering in Parallel Jobs
- Unit 6 - Parallel Framework Data Types
- Unit 7 - Reusable components
- Unit 8 - Balanced Optimization
Course Location
About Global Knowledge Egypt
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