Developer Transformation Guide

10.4.0
- 10.5.2
- 10.5
- 10.4.1

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Expressions in Transformations

You can enter expressions in the

Expression Editor

in some transformations. Expressions modify data or test whether data matches conditions.

Create expressions that use transformation language functions. Transformation language functions are SQL-like functions that transform data.

Enter an expression in a port that uses the value of data from an input or input/output port. For example, you have a transformation with an input port IN_SALARY that contains the salaries of all the employees. You might use the values from the IN_SALARY column later in the mapping. You might also use the transformation to calculate the total and average salaries. The Developer tool requires you to create a separate output port for each calculated value.

The following table lists the transformations in which you can enter expressions:

Transformation	Expression	Return Value
Aggregator	Performs an aggregate calculation based on all data passed through the transformation. Alternatively, you can specify a filter for records in the aggregate calculation to exclude certain kinds of records. For example, you can find the total number and average salary of all employees in a branch office using this transformation.	Result of an aggregate calculation for a port.
Expression	Performs a calculation based on values within a single row. For example, based on the price and quantity of a particular item, you can calculate the total purchase price for that line item in an order.	Result of a row-level calculation for a port.
Filter	Specifies a condition used to filter rows passed through this transformation. For example, if you want to write customer data to the BAD_DEBT table for customers with outstanding balances, you could use the Filter transformation to filter customer data.	TRUE or FALSE, based on whether a row meets the specified condition. The Data Integration Service passes rows that return TRUE through this transformation. The transformation applies this value to each row that passes through it.
Joiner	Specifies an advanced condition used to join unsorted source data. For example, you can concatenate first name and last name master ports and then match them with the full name detail port.	TRUE or FALSE, based on whether the row meets the specified condition. Depending on the type of join selected, the Data Integration Service either adds the row to the result set or discards the row.
Rank	Sets the conditions for rows included in a rank. For example, you can rank the top 10 salespeople who are employed with the organization.	Result of a condition or calculation for a port.
Router	Routes data into multiple transformations based on a group expression. For example, use this transformation to compare the salaries of employees at three different pay levels. You can do this by creating three groups in the Router transformation. For example, create one group expression for each salary range.	TRUE or FALSE, based on whether a row meets the specified group expression. The Data Integration Service passes rows that return TRUE through each user-defined group in this transformation. Rows that return FALSE pass through the default group.
Update Strategy	Flags a row for update, insert, delete, or reject. You use this transformation when you want to control updates to a target, based on some condition you apply. For example, you might use the Update Strategy transformation to flag all customer rows for update when the mailing address has changed. Or, you might flag all employee rows for reject for people who no longer work for the organization.	Numeric code for update, insert, delete, or reject. The transformation applies this value to each row passed through it.