Book Image

SAP Data Services 4.x Cookbook

Book Image

SAP Data Services 4.x Cookbook

Overview of this book

Want to cost effectively deliver trusted information to all of your crucial business functions? SAP Data Services delivers one enterprise-class solution for data integration, data quality, data profiling, and text data processing. It boosts productivity with a single solution for data quality and data integration. SAP Data Services also enables you to move, improve, govern, and unlock big data. This book will lead you through the SAP Data Services environment to efficiently develop ETL processes. To begin with, you’ll learn to install, configure, and prepare the ETL development environment. You will get familiarized with the concepts of developing ETL processes with SAP Data Services. Starting from smallest unit of work- the data flow, the chapters will lead you to the highest organizational unit—the Data Services job, revealing the advanced techniques of ETL design. You will learn to import XML files by creating and implementing real-time jobs. It will then guide you through the ETL development patterns that enable the most effective performance when extracting, transforming, and loading data. You will also find out how to create validation functions and transforms. Finally, the book will show you the benefits of data quality management with the help of another SAP solution—Information Steward.
Table of Contents (19 chapters)
SAP Data Services 4.x Cookbook
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
Index

Monitoring and analyzing dataflow execution


When you execute the job, Data Services populates relevant execution information into three log files: the trace, monitor, and error logs. In later chapters, we will take a closer look at the configuration parameters available at the job level in order to gather more detailed information regarding job execution. Meanwhile, in this recipe, we will spend some time analyzing the monitor log file, which logs processing information from inside the dataflow components.

Getting ready

For simplicity, we will use the second dataflow from the recipe Using the Table_Comparison transform created for detailed explanation of the flow of the data before and after it passes the Table_Comparison transform object:

Open the Table_Comparison transform editor in the workspace and change the comparison method to Cached comparison table:

We change this option to slightly change the behavior of the Data Services optimizer. Now, instead of comparing data row by row, executing...