DataWeave is the primary transformation language in Mule. What is interesting about DataWeave is that it brings together features of XSLT (mapping), SQL (joinBy, splitBy, orderBy, groupBy, distinctBy operators), Streaming, Functional Programming (use of functions in DataWeave code) to make it a power-packed data...
Upgrade your Groovy Scripts in Mule with DSLDs
The groovy script transformer component is a very powerful piece of Mule. I use it for almost every message transformation that I need to make. Its XML and JSON libraries reduce message format conversion down to little more than building a map, while closures give you some powerful processing tools for handling...
A Groovy way to implement a JMS Request Response client using Camel
While working for one particular client we were under the particular constraint of not having access to the JMS management console (in this instance the ActiveMQ Console). So when it came time to test out integration workflows we needed a quick and easy way to call the SOAP over JMS services. The Deloitte Platform...
Part 1 of this series layed the foundation for some Groovy concepts and what makes the language suitable for data mapping tasks. With that in mind, lets dive into some of the advanced mapping features and some real world samples.
Introducing GroovyMap
There are 3 data transformation scenarios which we commonly...
ESB services involve working with a variety of different data formats and structures e.g. XML, JSON, CSV, spread sheets, key-value structures. Transformations between XML and other data structures are quite common when it comes to developing an ESB layer. Mule ESB provides a wide range of choices when it comes to...