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Business Intelligence/IBMIBM InfoSphere Advanced DataStage - Advanced Data Processing V9.1Réf. : ZL1_KM403

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Objectifs pédagogiques

Objectifs : - Describe the parallel processing architecture
- Describe pipeline and partition parallelism
- Describe the role and elements of the DataStage configuration file
- Describe the compile process and how it is represented in the OSH
- Describe the runtime job execution process and how it is depicted in the
Score
- Describe how data partitioning and collecting works in the parallel framework
- List and select partitioning and collecting algorithms
- Describe sorting in the parallel framework
- Describe optimization techniques for sorting
- Describe sort key and partitioner key logic in the parallel framework
- Describe buffering in the parallel framework
- Describe optimization techniques for buffering
- Describe and work with parallel framework data types and elements,
including virtual data sets and schemas
- Describe the function and use of Runtime Column Propagation (RCP) in
DataStage parallel jobs
- Create reusable job components using shared containers
- Describe the function and use of Balanced Optimization
- Optimize DataStage parallel jobs using Balanced Optimization

Pré-requis

Prérequis : You should have :
- DataStage Essentials course or equivalent and at least one year of
experience developing parallel jobs using DataStage.

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