About this course

Course code TPZL1_KM402
Duration 3 Days

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.

Prerequisites

You should have:

  • taken DataStage Essentials course or equivalent
  • and at least one year of experience developing parallel jobs using DataStage

Delegates will learn how to

  • 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

Outline

  • 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

3 Days

Duration
Training delivered by an IBM Global Training Provider
Delivery Method

Delivery method

Classroom

Face-to-face learning in the comfort of our quality nationwide centres, with free refreshments and Wi-Fi.

Find dates and prices

Online booking is currently not available for this course, to find out more please call us on 0345 074 7998 or email us at info@qa.com to discuss how we can help.

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