Chapter 5. Transforming data with Mule
In this chapter
- Message transformation principles
- Common transformers from Mule Core
- JMS and XML transformers
- Writing custom transformers
Nowadays, every application understands XML and uses interoperable data structures, right? If you replied yes, be informed that you live in Wonderland, and sooner or later, you’ll awake to a harsh reality! If, like most of us, you answered no, then you know why data transformation is such a key feature of an ESB.
We’re still far away from a world of unified data representation, if we ever reach that point. Unifying data is a tremendous effort. For public data models, it takes years of work by international committees to give birth to complete and complex standards. In large corporations, internal working groups or governance bodies also struggle to establish custom unified data representations. In the meantime, the everyday life of a software developer working on integration projects is fraught with data transformation challenges.
In this chapter, you’ll learn how Mule can help you with your data transformation needs. We’ll first discuss the way transformers behave and how you can work with them. We’ll then review the usage of a few existing transformers that illustrate the diversity and capacities of Mule:
- Core transformers— General-purpose transformers from the core library of Mule
- XML transformers— Specialized transformers from the XML module
- JMS transformers— Transport-specific transformers for JMS