Data Processing Functions
MapForce Data Conversion:
- Data processing functions convert data on the fly
- Mathematical calculations
- Boolean, date, time, number, or string conversion
- Programmatic string and dateTime parsing
- Specialized node, sequence, edifact, and db functions
- Supports filters, conditions, parameters, and variables
- Database functions in SQL or SQL/XML
- Data mapping debugger gives deep insight into the exact inner workings of data mapping functions
Functions for Data Conversion
MapForce® 2017 delivers powerful, flexible support for defining custom data processing functions between source and target files.
Data mapping MapForce provides an extensible library of data processing functions for filtering and manipulating data according to the needs of your data mapping project. A variety of conversion functions are provided to parseTo save time and leverage work you’ve already completed and tested, you can even import existing data conversion code or an XSLT 1.0 or 2.0 file for use as a function library. MapForce also includes a unique visual function builder for defining custom functions that combine multiple operations.
MapForce can handle the most advanced conversion scenarios thanks to a comprehensive data mapping function library, which allows you to define rules based on conditions, Boolean logic, string operations, mathematical computations, SQL and SQL/XML statements, or any user-defined function. You can even use an existing Web service to look up or process data in any mapping.
MapForce includes a comprehensive function library for building advanced data processing functions to perform any type of computational operation needed to comply with the content model of the target.
Many of the built-in functions, such as concat, add, multiply, etc., support an unlimited number of parameters, making it easy to perform mathematical manipulations and combine multiple parameters. Aggregate functions allow you to perform computations on groups of data, including count, sum, min, average, join-string, and others. Conversion functions are provided to conveniently parse complex data types.
Functions in the core library are generalized and not specific to any type of output. Using these core functions, you can create XSLT 1.0/2.0, XQuery, Java, C++, or C# data conversion code by simply selecting the language(s) you require.
Intermediate variables are a special type of component that store an intermediate mapping result for further processing and can be used to solve various advanced mapping problems. An intermediate variable is equivalent to a regular (non-inline) user-defined function, and is a structural component without an instance file.
Filters and Conditions
Inserting filters and conditions into a mapping allows you to select data from the source based on Boolean conditions.
The if-else condition in MapForce is equivalent to a switch statement in many programming languages, enabling you to easily control the flow of data in your mapping projects by matching a value to a selected criterion.
MapForce supports transformation input parameters, allowing outside parameters to affect mapping transformations. The transformation input parameters can be passed to the main mapping function created by the MapForce code generator in Java, C#, or C++.
Grouping enables users to combine source data in groups for output and then apply processing instructions to those groups, essentially transforming flat data into a hierarchical structure.
Grouping functions include: group-by, group-adjacent, group-starting-with, and group-ending-with.
More Data Integration Tools:
MapForce is available in 32-bit and 64-bit versions. Learn about the advantages of choosing the 64-bit data mapping tool when you have a 64-bit operating system.