- DataWeave 2.0 provides mapping capabilities
- Java and DataWeave can achieve the same mappings
- DataWeave mapping operator is less verbose than Java
DataWeave map operator
The DataWeave 2.0 (Mule 4) map operator shares similarities with the
map() method from Java’s
Mapping is a transformative operation
The idea of mapping is to transform each element of an array and output a new array of transformed elements. An expression is provided that performs the transformation. It is applied to each element in the array and collected into another new array.
Apply a mapping to an array in Java
In Java, a transformative expression is applied by passing it to the
map() method of the
Stream class. It is applied in turn to each element of the array and collected to a new
List. In the following code snippet the inline array is transformed into a stream so that mapping can be performed.
The transformation is performed by the lambda expression
e -> e.toUpperCase() where the variable
e represents each element in the array. The result of the transformation is added to a new
List using a collector
There is a ‘short cut’ expression that you can use in place of the explicit lambda expression. It is
String::toUpperCase, the above code would now look as follows.
Apply a mapping to an array in DataWeave
In DataWeave a transformative expression is applied to each element of an array and outputted to a new array containing these new transformed elements.
upper() function is applied to each element in the
pets array and transformed. Each transformed element is put into a new array. This new array is the output of this operation. The dollar ($) symbol represents each element in the array as the
map function iterates over the array. The
upper() function is a lambda function from the
dw::Core module. It is automatically imported into all DataWeave scripts.
DataWeave has been designed to transform data and does so in a performant way. The code is concise and easy to understand. As you can see Java is more verbose but provides much more capabilities than data transformation.
RESTful API design and RAML
There are five things to consider when designing a RESTful API. In this blog post I introduce those important aspects with examples to illustrate how to implement them in a API specification.
If you are designing a API using RAML you will want to include examples to ensure that the specification provides the high level of documentation that a modern API should. In this blog post I discuss four ways to specify examples in a RAML API specification.