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DataWeave function chaining for Java programmers

In this article, you will learn how to use method chaining in DataWeave with reference to Java 8 lambda expressions and how to convert from Java Streams into DataWeave chaining.  Java 8 introduced the Stream API, which is used to process…
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DataWeave: Generating XML

In this blog post, I will show you how to generate XML output from a JSON data source while avoiding some of the most common pitfalls and explain how to use encoding, namespaces, fields, and attributes. Sample JSON data Throughout this article,…
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DataWeave lambdas for Java programmers

In Mule 4, DataWeave is everywhere: every listener and processor can be configured with it. Because most Mule users already know Java well, this article will help Java developers to easily use DataWeave by rewriting their lambdas expressions. First,…
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Round-up: The 7 most popular blog posts from 2017

This year, we published over 215 blog posts spanning a wide variety of topics––from why messaging queues suck to why ESB-led integration is no longer an adequate approach for organizations. Check out the top 7 most popular blog posts…
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HowTo – Invoke Java/Groovy logic in DataWeave

When building DataWeave transformations for your Mule application, you will run into situations in which you will need to invoke external logic that may be encapsulated in a Java POJO, Groovy, Python, Ruby script, or really any lookup that uses…
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HowTo – Perform date arithmetic with DataWeave

When integration involves different applications, systems, or databases, we face a common challenge: how do we bridge between data formats and how can we provide interoperability for fields that store dates and date/time values?  I recently…
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HowTo – Implement logic handling in DataWeave

Logic handling using DataWeave is essential for simple mediums and highly complex transformations, in which the mapping requirements necessitate generating outputs based on values provided in the input payload.  This could be as simple…
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How to Apply DataWeave to the Real-world: Looping (Part 3)

So far in this 3-part series, we have looked at variables (Part 1) and functions (Part 2) in order to leverage them to our advantage. In this third and final part of the real-world DataWeave series, we will look at another common problem area,…
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How to Apply DataWeave to the Real-world: Functions (Part 2)

In the first part of this series we tackled the issue of defining and also using variables within DataWeave as opposed to using the legacy set “Variable” module. Today, I need to raise the topic of functions in DataWeave as a key…
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How to Apply DataWeave to the Real-world: Variables (Part 1)

Over the last few years at MuleSoft, I have had the opportunity to work with many different customers covering a wide range of use cases, inevitably requiring data transformations of one sort or another. I have observed some recurring patterns…