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PROKODA GmbH | 05.02.2019

IBM KM404G - IBM InfoSphere Advanced DataStage - Parallel Framework v11.5

Seminare, Workshops
02.05.2018 - 04.05.2018
DE-20095 Hamburg


Key topics

1: Introduction to the parallel framework architecture

· Describe the parallel processing architecture

· Describe pipeline and partition parallelism

· Describe the role of the configuration file

· Design a job that creates robust test data

2: Compiling and executing jobs

· Describe the main parts of the configuration file

· Describe the compile process and the OSH that the compilation process generates

· Describe the role and the main parts of the Score

· Describe the job execution process

3: Partitioning and collecting data

· Understand how partitioning works in the Framework

· Viewing partitioners in the Score

· Selecting partitioning algorithms

· Generate sequences of numbers (surrogate keys) in a partitioned, parallel environment

4: Sorting data

· Sort data in the parallel framework

· Find inserted sorts in the Score

· Reduce the number of inserted sorts

· Optimize Fork-Join jobs

· Use Sort stages to determine the last row in a group

· Describe sort key and partitioner key logic in the parallel framework

5: Buffering in parallel jobs

· Describe how buffering works in parallel jobs

· Tune buffers in parallel jobs

· Avoid buffer contentions

6: Parallel framework data types

· Describe virtual data sets

· Describe schemas

· Describe data type mappings and conversions

· Describe how external data is processed

· Handle nulls

· Work with complex data

7: Reusable components

· Create a schema file

· Read a sequential file using a schema

· Describe Runtime Column Propagation (RCP)

· Enable and disable RCP

· Create and use shared containers

8: Balanced Optimization

· Enable Balanced Optimization functionality in Designer

· Describe the Balanced Optimization workflow

· List the different Balanced Optimization options.

· Push stage processing to a data source

· Push stage processing to a data target

· Optimize a job accessing Hadoop HDFS file system

· Understand the limitations of Balanced Optimizations

Voraussetzung: IBM InfoSphere DataStage Essentials course or equivalent and at least one year of experience developing parallel jobs using DataStage.

Preis: 2590,- € (zzgl. MwSt.) pro Teilnehmer.

Uhrzeit: Von 09:00 bis 16:00

Teilnehmergruppe: 3 bis 8

Dauer in Std: 24

Frühbucher: Preis: 2538.2 € bis zum 01.04.2018 reservieren.

Zur Veranstaltungsseite: https://www.prokoda.de/

Unternehmenseintrag: PROKODA GmbH

Eingestellt am: 05.02.2019 von: .

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