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Anypoint Platform Development: DataWeave

Advance your DataWeave skills beyond those taught in Development: Fundamentals to build complex transformations. Skills Gained Write generalized and reusable transformations using variables,...

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$1,800 USD
Course Code DEX480
Duration 2 days
Available Formats Classroom, Virtual

Advance your DataWeave skills beyond those taught in Development: Fundamentals to build complex transformations.

Skills Gained

  • Write generalized and reusable transformations using variables, functions, DataWeave modules.
  • Use the DataWeave Playground to test and author DataWeave code.
  • Build complex transformations from smaller testable steps.
  • Build more robust and testable functions and expressions using strong typing, match operators, error handling, and logging.
  • Create, transform, filter, combine, shuffle, select from, and reduce complex data structures that include nested arrays, objects, and arrays of objects.
  • Recursively replace or format every element or a list of elements in a nested schema.
  • Reduce arrays to other data structures or data types and calculate key performance indicators.

Who Can Benefit

This course is for Mule 4 developers or architects who want to advance their DataWeave skills beyond those taught in the Anypoint Platform Development: Fundamentals course so that they can build complex transformations.

Prerequisites

  • Experience developing Mule 4 applications as demonstrated by one of the following: A current MuleSoft Certified Developer - Level 1 certification, Completion of the Anypoint Platform Development: Fundamentals course, or Completion of the Anypoint Platform Development: Mule 4 for Mule 3 Users course
  • A basic knowledge of functional programming
  • Note: If you are new to functional programming, read An introduction to functional programming in JavaScript.

Course Details

Setup Requirements

  • A computer with at least 8-16 GB available RAM (16 highly recommended), 2GHz CPU, and 10GB available storage
  • Internet access to port 80 (with > 5Mbps download and > 2Mbps upload)
  • Anypoint Studio 7.14.0 or later with embedded Mule runtime
  • Advanced REST Client (or any other REST client application)

Course Outline

Applying DataWeave fundamentals

  • Review and apply DataWeave fundamentals as learned in the Anypoint Platform Development: Fundamentals course
  • Set example input to preview DataWeave results in Anypoint Studio
  • Chain together two argument functions by using infix notation
  • Filter, order, and group elements of an object or array
  • Retype DataWeave expressions in the middle of code execution

Organizing an reusing DataWeave code

  • Organize DataWeave code into variables and functions
  • Enclose variables and functions in do statement scopes
  • Pass functions and lambda expressions as arguments to other DataWeave functions
  • Create and use reusable DataWeave modules

Writing more defensive and more robust DataWeave

  • Write more defensive DataWeave expressions that filter and route data based upon conditions
  • Write more robust functions using a match operator to test for data types
  • Handle and raise errors
  • Log from inside DataWeave expressions

Constructing arrays and objects

  • Add components to and remove elements from arrays and objects
  • Construct objects from lists of DataWeave expressions by using object constructor curly braces { }
  • Troubleshoot common issues when using object constructor curly braces { }

Iteratively mapping and joining arrays and objects

  • Combine objects and arrays into nested data structures by using map and mapObject functions
  • Extract an array of keys and/or values from an object by using the pluck function
  • Extract an array of keys and/or values from an object by using the DataWeave core Arrays module functions
  • Conditionally join together two nested schema by using the join function

Updating inside nested data structures

  • Conditionally update and mask parts of nested data structures
  • Format and transform nested data structures by using recursive functions

Reducing data from arrays

  • Conditionally test, count, and sum up elements of an array by using the DataWeave core Arrays module
  • Reduce and accumulate array elements to other output types by using the reduce function
  • Calculate key performance indicators from input collections by using the reduce function
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