Mastering Variable Mapping in Informatica Taskflow

Mastering Variable Mapping in Informatica Taskflow

Table of Contents

1. Introduction
2. Understanding Mapping Variables
3. Differences between Mapping Variables and Parameters
4. Setting Up a Mapping Variable
5. Using Mapping Variables in a Session
6. Use Case: Splitting Table Records
   • 6.1 Mapping Implementation Overview
   • 6.2 Creating the Mapping
   • 6.3 Configuring the Mapping Variables
   • 6.4 Implementing the Splitting Logic
   • 6.5 Creating the Target Tables
   • 6.6 Mapping Task and Task Flow
7. Conclusion
8. FAQs

Introduction

In this article, we will discuss the concept of mapping variables in Informatica PowerCenter. Mapping variables allow us to pass in/out values across a session using the task loop. Unlike mapping parameters, mapping variables can be changed during a session run, providing us with more flexibility in our workflows.

Understanding Mapping Variables

Mapping variables are values that can be dynamically changed during the execution of a session. They allow us to store temporary values that can be used in various transformations or tasks. These variables can be shared across different parts of the workflow, making them a powerful tool in Informatica PowerCenter.

Differences between Mapping Variables and Parameters

Mapping variables and parameters may seem similar at first, but there are key differences between them. Parameters are constants and cannot be changed during a session run, while variables can be dynamically modified. Parameters are defined at the mapping level, while variables are defined at the workflow level.

Setting Up a Mapping Variable

To Create a mapping variable, we need to define it in the mapping or workflow properties. We can set an initial default value for the variable, which will be used if no other value is assigned. Mapping variables can have various data types, such as integer, STRING, or date.

Using Mapping Variables in a Session

Once we have defined a mapping variable, we can use it in different parts of our session. We can assign values to the variable using expressions, functions, or by retrieving values from a source or target table. These values can then be used in transformations, conditions, or tasks during the session run.

Use Case: Splitting Table Records

To illustrate the use of mapping variables, we will discuss a use case on splitting table records. Let's consider an example where we have an employee table with 16 records in the source. Our goal is to pass these records to two target tables, equally divided with 8 records in each table.

6.1 Mapping Implementation Overview

In this section, we will provide an overview of the mapping implementation for splitting table records. We will discuss the different transformations involved and their purpose in achieving the desired outcome.

6.2 Creating the Mapping

To begin, we need to create a mapping that will handle the splitting of the table records. We will define the mapping variables, set the initial values, and configure the necessary transformations to achieve the desired result.

6.3 Configuring the Mapping Variables

In this step, we will configure the mapping variables used in the mapping. We will set the default values and ensure they are properly assigned throughout the session run. This ensures that the variables are updated with the correct values when executing the mapping.

6.4 Implementing the Splitting Logic

With the mapping variables set, we can now implement the logic to split the table records equally between the two target tables. We will use transformations like Aggregator and Expression to calculate the record count and determine the distribution of records.

6.5 Creating the Target Tables

Before proceeding, we need to create the target tables where the split records will be loaded. We will define the necessary table structures and ensure they are compatible with the incoming data from the mapping.

6.6 Mapping Task and Task Flow

To execute the mapping, we will create a mapping task and incorporate it into a task flow. We will define the connections between tasks and ensure that the mapping variables are correctly assigned and used throughout the workflow.

Conclusion

Mapping variables are a powerful feature in Informatica PowerCenter that allow us to dynamically change values during a session run. They provide flexibility in our workflows and enable us to handle complex tasks efficiently. By understanding the concepts and implementing mapping variables effectively, we can streamline our data integration processes and achieve desired results.

FAQs

Q: Can we change mapping variable values during a session run?

A: Yes, mapping variables can be changed during a session run. This allows us to adapt to dynamic requirements and perform different actions Based on changing conditions.

Q: Are mapping variables the same as mapping parameters?

A: No, mapping variables and parameters are different. Mapping parameters are constants and cannot be changed during a session run, while variables can be dynamically modified.

Q: What data types can be used for mapping variables?

A: Mapping variables can have various data types, including integer, string, date, or any other supported data type in Informatica PowerCenter.

Q: Can mapping variables be shared across different parts of a workflow?

A: Yes, mapping variables can be shared across different parts of a workflow, allowing us to pass values between transformations, tasks, or even Sessions. This enables us to efficiently manage and manipulate data throughout the workflow.

Q: How can mapping variables be used to split table records?

A: Mapping variables can be used to calculate the Record count and distribute records between different targets. By assigning specific values to the variables and implementing the necessary logic, we can achieve the desired splitting of table records.