This course covers advanced parallel job development techniques and performance and tuning in DataStage V11.7. In this course you will develop a deeper understanding of the DataStage architecture, including an 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.
Participants should have: IBM Infosphere DataStage Essentials course or equivalent, and at least one year of experience developing parallel jobs using DataStage.
3 Days/Lecture & Lab
Experienced DataStage developers seeking training in more advanced DataStage job techniques and who seek an understanding of the parallel framework architecture.
- Describe the parallel processing architecture
- Partitioning and collecting data
- Sorting data
- Buffering in parallel jobs
- Parallel framework data types
- Reusable components
- Balanced Optimization
- Unstructured stage
- Performance and Tuning Using Operations Console