IBM InfoSphere Advanced DataStage - Parallel Framework v11.5

Course Description

In DataStage v11.5, this course is intended to introduce advanced parallel task building approaches. You will gain a deeper grasp of the DataStage architecture in this course, as well as the runtime and development environments for the platform. This will provide you the ability to create parallel jobs that are reliable, less prone to errors, reusable, and performance-optimized.

Prerequisites

Having completed an IBM InfoSphere DataStage Essentials course or its equivalent, and having at least one year of experience using DataStage to create parallel jobs

Target Audience

Experienced DataStage developers looking to learn more sophisticated DataStage job skills and gain a grasp of the architecture of the parallel framework

Learning Objectives

Please refer to course overview

Content Outline

  • Describing the parallel processing architecture
  • Describing pipeline and partition parallelism
  • Describing the role of the configuration file
  • Designing a job that creates robust test data
  • Describing the main parts of the configuration file
  • Describing the compile process and the OSH that the compilation process generates
  • Describing the role and the main parts of the Score
  • Describing the job execution process
  • Understanding how partitioning works in the Framework
  • Viewing partitioners in the Score
  • Selecting partitioning algorithms
  • Generating sequences of numbers (surrogate keys) in a partitioned, parallel environment
  • Sorting data in the parallel framework
  • Finding inserted sorts in the Score
  • Reducing the number of inserted sorts
  • Optimizing Fork-Join jobs
  • Using Sort stages to determine the last row in a group
  • Describing sort key and partitioner key logic in the parallel framework
  • Describing how buffering works in parallel jobs
  • Tuning buffers in parallel jobs
  • Avoiding buffer contentions
  • Describing virtual data sets
  • Describing schemas
  • Describing data type mappings and conversions
  • Describing how external data is processed
  • Handling nulls
  • Working with complex data
  • Creating a schema file
  • Reading a sequential file using a schema
  • Describing Runtime Column Propagation (RCP)
  • Enabling and disabling RCP
  • Creating and using shared containers
  • Enabling Balanced Optimization functionality in Designer
  • Describing the Balanced Optimization workflow
  • Listing the different Balanced Optimization options.
  • Pushing stage processing to a data source
  • Pushing stage processing to a data target
  • Optimizing a job accessing Hadoop HDFS file system
  • Understanding the limitations of Balanced Optimizations 

FAQs

An ETL tool, IBM InfoSphere DataStage is a component of IBM InfoSphere and the IBM Information Platforms Solutions family. It is offered in a variety of variants, including the Server Edition, the Enterprise Edition, and the MVS Edition, and it uses a graphical notation to design data integration solutions. Client-server architecture is used. Both Windows and Unix can be used to deploy the servers.

It is a potent data integration tool that is widely used in Data Warehousing projects to get the data ready for report generating.

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