Book Image

Learning Informatica PowerCenter 10.x - Second Edition

By : Rahul Malewar
Book Image

Learning Informatica PowerCenter 10.x - Second Edition

By: Rahul Malewar

Overview of this book

Informatica PowerCenter is an industry-leading ETL tool, known for its accelerated data extraction, transformation, and data management strategies. This book will be your quick guide to exploring Informatica PowerCenter’s powerful features such as working on sources, targets, transformations, performance optimization, scheduling, deploying for processing, and managing your data at speed. First, you’ll learn how to install and configure tools. You will learn to implement various data warehouse and ETL concepts, and use PowerCenter 10.x components to build mappings, tasks, workflows, and so on. You will come across features such as transformations, SCD, XML processing, partitioning, constraint-based loading, Incremental aggregation, and many more. Moreover, you’ll also learn to deliver powerful visualizations for data profiling using the advanced monitoring dashboard functionality offered by the new version. Using data transformation technique, performance tuning, and the many new advanced features, this book will help you understand and process data for training or production purposes. The step-by-step approach and adoption of real-time scenarios will guide you through effectively accessing all core functionalities offered by Informatica PowerCenter version 10.x.
Table of Contents (20 chapters)
Title Page
Credits
About the Author
Acknowledgement
About the Reviewer
www.PacktPub.com
Customer Feedback
Preface

Working on partitioning


Before we discuss partitioning, make a note that partitioning is a high availability feature that you need to purchase separately from Informatica. If you enable high availability features, you can make use of the partitioning functionality.

By default, a mapping containing source, target, and transformations has a single partition. A single partition means that a single record can flow from the source to target at a time. By adding multiple partitions, you logically divide the mapping into multiple sections-each section can pass a record at a time. So if you make three partitions in the mapping, three records can pass through the mapping, making your runtime reduced by one third. When you add a partition at any stage of the mapping, the integration service adds partitions at other stages of the mapping. You need to make sure that you have sufficient memory space and system capacity to handle the processing of multiple records at a time.

If you have 1,000 records to...