Data transformation is the process of converting data or information from one format to another, usually from the format of a source system into the required format of a new destination system. MuleSoft has developed “DataWeave” - a new language and module for querying and transforming data. DataWeave is a full-featured and fully native framework for querying and transforming data on Anypoint Platform.

In today’s enterprise infrastructure, system and application integration is more and more frequently a mission critical concern. There are number of Enterprise Service Bus (ESB) products available in the market today. These products can help you remove basic dependencies between applications by eliminating the need for one application to be aware of the other's location, but connectivity is not the only issue. In reality, most systems do not speak same language so Data transformation is one of the most important topic in Integration space.

Data transformation is the process of converting data or information from one format to another, usually from the format of a source system into the required format of a new destination system. MuleSoft has developed “DataWeave” - a new language and module for querying and transforming data. DataWeave is a full-featured and fully native framework for querying and transforming data on Anypoint Platform. Fully integrated with the graphical interface of Anypoint Studio and DataSense, DataWeave makes even the most complex data integration simple.

The DataWeave language supports a variety of transformations, from simple one-to-one mappings to more elaborate mappings including normalization, grouping, joins, deduplication, pivoting and filtering. It also supports XML, JSON, CSV, Java and EDI out of the box. The DataWeave Language is a powerful template engine that allows you to transform data to and from any kind of format (XML, CSV, JSON, Pojos, Maps, etc). It is fully integrated with Anypoint Studio, making on-ramp and continued development easy. It includes full integration with DataSense, allowing payload-aware development with auto-completion, auto-scaffolding of transforms, and live previews.

Let’s learn little bit more about the basics of this elegant and lightweight expression language. DataWeave files are divided into two main sections: 1) The Header, which defines directives (optional) and 2) The Body, which describes the output structure. Both sections are delimited by a separator, which is not required if no header is present. The separator consists of three dashes: "---".

 

Header

The DataWeave header contains the directives, these define high level information about your transformation. The structure of the Header is a sequence of lines, each with its own Directives. Through directives you can define:

  • DataWeave version

  • Input types and sources

  • Output type

  • Namespaces to import into your transform

  • Constants that can be referenced throughout the body

  • Functions that can be called throughout the body

 

Body

The body contains the expression that generates the output structure. Regardless of the types of the input and output, the data model for the output is always described in the standard DataWeave language, and this model that the transform executes. The data model of the produced output can consist of three different types of data:

  • Objects: represented as collection of key value pairs

  • Arrays: represented as a sequence of comma separated values

  • Simple literals

 

Let’s take a look at a simple example to understand more about DataWeave. In this example, we will first transform JSON input data to Java object and finally Java object to XML format.

Step 1. Import JSON Schema

Employee JSON Schema
{
  "title": "Employee Schema",
  "type": "object",
  "properties": {
    "emp_id": {
      "type": "integer"
    },
    "first_name": {
      "type": "string"
    },
    "last_name": {
      "type": "string"
    },
    "preferred_first_name": {
      "type": "string"
    },
    "preferred_last_name": {
      "type": "string"
    },"dob": {
      "type": "string"
    },
    "active": {
      "type": "string"
    },
    "addresses": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "address_line1": {
            "type": "string"
          },
          "address_line2": {
            "type": "string"
          },
          "city": {
            "type": "string"
          },
          "state": {
            "type": "string"
          },
          "zip_code": {
            "type": "string"
          },
          "country": {
            "type": "string"
          }
        },
        "required": [
          "address_line1",
          "city",
          "state",
          "zip_code",
          "country"
        ]
      }
    },
    "contacts": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "home": {
            "type": "string"
          },
          "cell": {
            "type": "string"
          },
          "fax": {
            "type": "string"
          },
          "primary_email": {
            "type": "string"
          },
          "secondary_email": {
            "type": "string"
          }
        }
      }
    }
  },
  "required": [
    "emp_id",
    "first_name",
    "last_name",
    "dob",
    "active"
  ]
}

Step 2. Import XML Schema

Employee XML Schema
<?xml version="1.0" encoding="UTF-8"?>
<schema xmlns="http://www.w3.org/2001/XMLSchema" xmlns:tns="http://www.example.org/xml_schema_employee/"
  targetNamespace="http://www.example.org/xml_schema_employee/">
  <element name="Employee" type="tns:Employee"></element>
  <complexType name="Employee">
    <sequence>
      <element name="empId" type="integer" maxOccurs="1" minOccurs="1">
      </element>
      <element name="firstName" type="string" maxOccurs="1"
        minOccurs="1">
      </element>
      <element name="middleName" type="string" maxOccurs="1"
        minOccurs="0">
      </element>
      <element name="lastName" type="string" maxOccurs="1"
        minOccurs="1">
      </element>
      <element name="preferredFullName" type="string" maxOccurs="1"
        minOccurs="0">
      </element>
      <element name="dateOfBirth" type="string" maxOccurs="1"
        minOccurs="1">
      </element>
      <element name="isActive" type="boolean" maxOccurs="1"
        minOccurs="1">
      </element>
      <element name="address" type="tns:Address" maxOccurs="unbounded"
        minOccurs="0">
      </element>
      <element name="contact" type="tns:Contact" maxOccurs="unbounded"
        minOccurs="0">
      </element>
    </sequence>
  </complexType>
  <complexType name="Address">
    <sequence>
      <element name="line1" type="string" maxOccurs="1" minOccurs="1">
      </element>
      <element name="line2" type="string" maxOccurs="1" minOccurs="0">
      </element>
      <element name="city" type="string" maxOccurs="1" minOccurs="1">
      </element>
      <element name="state" type="string" maxOccurs="1" minOccurs="1">
      </element>
      <element name="zip" type="string" maxOccurs="1" minOccurs="1">
      </element>
      <element name="country" type="string" maxOccurs="1"
        minOccurs="1"></element>
    </sequence>
  </complexType>
    <complexType name="Contact">
      <sequence>
        <element name="home" type="string" maxOccurs="1"
          minOccurs="0">
        </element>
        <element name="mobile" type="string" maxOccurs="1"
          minOccurs="0">
        </element>
        <element name="fax" type="string" maxOccurs="1"
          minOccurs="0">
        </element>
        <element name="email" type="tns:Email" maxOccurs="1"
          minOccurs="0">
        </element>
      </sequence>
    </complexType>
    <complexType name="Email">
      <sequence>
        <element name="primary" type="string" maxOccurs="1"
          minOccurs="0">
        </element>
        <element name="secondary" type="string" maxOccurs="1" minOccurs="0"></element>
      </sequence>
    </complexType>
</schema>

Step 3. Create Java Classes

Employee.java
import java.io.Serializable;
import java.util.ArrayList;
import java.util.Date;
import java.util.List;

public class Employee implements Serializable {

  private static final long serialVersionUID = 830974489967994125L;
  private Integer employeeId;
  private String firstName;
  private String middleName;
  private String lastName;
  private String preferredFullName;
  private Date dateOfBirth;
  private boolean active;
  private List<Address> addresses;
  private List<Contact> contacts;
  public Integer getEmployeeId() {
    return employeeId;
  }
  public void setEmployeeId(Integer employeeId) {
    this.employeeId = employeeId;
  }
  public String getFirstName() {
    return firstName;
  }
  public void setFirstName(String firstName) {
    this.firstName = firstName;
  }
  public String getMiddleName() {
    return middleName;
  }
  public void setMiddleName(String middleName) {
    this.middleName = middleName;
  }
  public String getLastName() {
    return lastName;
  }
  public void setLastName(String lastName) {
    this.lastName = lastName;
  }
  public Date getDateOfBirth() {
    return dateOfBirth;
  }
  public void setDateOfBirth(Date dateOfBirth) {
    this.dateOfBirth = dateOfBirth;
  }
  public boolean isActive() {
    return active;
  }
  public void setActive(boolean active) {
    this.active = active;
  }  
  public String getPreferredFullName() {
    return preferredFullName;
  }
  public void setPreferredFullName(String preferredFullName) {
    this.preferredFullName = preferredFullName;
  }
  public List<Address> getAddresses() {
    if (addresses == null) {
      addresses = new ArrayList<Address>();
    }
    return addresses;
  }  
  public void setAddresses(List<Address> addresses) {
    this.addresses = addresses;
  }
  public List<Contact> getContacts() {
    if (contacts == null) {
      contacts = new ArrayList<Contact>();
    }
    return contacts;
  }  
  public void setContacts(List<Contact> contacts) {
    this.contacts = contacts;
  }
}
Contact.java
import java.io.Serializable;

public class Contact implements Serializable {

    private static final long serialVersionUID = 8191183310915009265L;
    private String homePhone;
    private String cellPhone;
    private String fax;
    private Email email;

    public String getHomePhone() {
        return homePhone;
    }
    public void setHomePhone(String homePhone) {
        this.homePhone = homePhone;
    }
    public String getCellPhone() {
        return cellPhone;
    }
    public void setCellPhone(String cellPhone) {
        this.cellPhone = cellPhone;
    }
    public String getFax() {
        return fax;
    }
    public void setFax(String fax) {
        this.fax = fax;
    }
    public Email getEmail() {
        return email;
    }
    public void setEmail(Email email) {
        this.email = email;
    }
}
Address.java
import java.io.Serializable;

public class Address implements Serializable {

    private static final long serialVersionUID = -4178015379362625254L;
    private String line1;
    private String line2;
    private String city;
    private String state;
    private String zipCode;
    private String country;

    public String getLine1() {
        return line1;
    }
    public void setLine1(String line1) {
        this.line1 = line1;
    }
    public String getLine2() {
        return line2;
    }
    public void setLine2(String line2) {
        this.line2 = line2;
    }
    public String getCity() {
        return city;
    }
    public void setCity(String city) {
        this.city = city;
    }
    public String getState() {
        return state;
    }
    public void setState(String state) {
        this.state = state;
    }
    public String getZipCode() {
        return zipCode;
    }
    public void setZipCode(String zipCode) {
        this.zipCode = zipCode;
    }
    public String getCountry() {
        return country;
    }
    public void setCountry(String country) {
        this.country = country;
    }
}
Email.java
import java.io.Serializable;

public class Email implements Serializable {

    private static final long serialVersionUID = 6412135990330505529L;
    private String primary;
    private String secondary;

    public String getPrimary() {
        return primary;
    }
    public void setPrimary(String primary) {
        this.primary = primary;
    }
    public String getSecondary() {
        return secondary;
    }
    public void setSecondary(String secondary) {
        this.secondary = secondary;
    }
}

Step 4. Write Mule Flow in Anypoint Studio

Step 5. Write XML to Java Transformation

DW Transformation (XML to Java)
%dw 1.0
%output application/java
---
{
  active: payload.active as :boolean,
  addresses: payload.addresses map ((address , indexOfAddress) -> {
    city: address.city,
    country: address.country,
    line1: address.address_line1,
    line2: address.address_line2,
    state: address.state,
    zipCode: address.zip_code
  }),
  contacts: payload.contacts map ((contact , indexOfContact) -> {
    cellPhone: contact.cell,
    email: {
      primary: contact.primary_email,
      secondary: contact.secondary_email
    },
    fax: contact.fax,
    homePhone: contact.home
  }),
  dateOfBirth: payload.dob as :date { format: "yyyyMMdd"},
  employeeId: payload.emp_id,
  firstName: payload.first_name,
  lastName: payload.last_name,
  preferredFullName: payload.preferred_first_name ++ " " ++ payload.preferred_last_name
} as :object {
  class : "com.appnovation.dataweave.example.Employee"
} 

Step 6. Write Java to Json Transformation

DW Transformation (Java to XML)
%dw 1.0
%output application/xml
%namespace ns0 http://www.example.org/xml_schema_employee/
---
{
  ns0#Employee: {
    empId: payload.employeeId,
    firstName: payload.firstName,
    middleName: payload.middleName,
    lastName: payload.lastName,
    preferredFullName: payload.preferredFullName,
    dateOfBirth: payload.dateOfBirth as :string,
    isActive: payload.active,
    (payload.contacts map ((contact , indexOfContact) -> {
      contact: {
        mobile: contact.cellPhone,
        home: contact.homePhone,
        fax: contact.fax,
        email: {
          primary: contact.email.primary,
          secondary: contact.email.secondary
        }
      }
    })),
    (payload.addresses map ((address , indexOfAddress) -> {
      address: {
        line1: address.line1,
        line2: address.line2,
        city: address.city,
        state: address.state,
        zip: address.zipCode,
        country: address.country
      }
    }))
  }
}  

Step 7. Input and Output

Input Data (JSON Format)
{
  "emp_id": 112233,
  "first_name": "Sagar",
  "last_name": "Chaudhari",
  "dob": "19860307",
  "preferred_first_name": "Sagar",
  "preferred_last_name": "Chaudhari",
  "active": true,
  "addresses": [
    {
      "address_line1": "120 Spanish",
      "address_line2": "A",
      "city": "San Francisco",
      "state": "California",
      "zip": "94100",
      "country": "USA"
    },
    {
      "address_line1": "120 Encanto",
      "address_line2": "B",
      "city": "St Louis",
      "state": "Missouri",
      "zip_code": "63001",
      "country": "USA"
    }
  ],
  "contacts": [
    {
      "home": "111-111-1111",
      "cell": "222-222-2222",
      "fax": "333-333-3333",
      "primary_email": "a@primary.com",
      "secondary_email": "b@secondary.com"
    },
    {
      "home": "555-555-5555"
    }
  ]
} 
Output Data (XML Format)
<?xml version='1.0' encoding='UTF-8' ?>
<ns0:Employee xmlns:ns0="http://www.example.org/xml_schema_employee/">
    <empId>112233</empId>
    <firstName>Sagar</firstName>
    <middleName xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:nil="true"/>
    <lastName>Chaudhari</lastName>
    <preferredFullName>Sagar Chaudhari</preferredFullName>
    <dateOfBirth>1986-03-07T00:00:00</dateOfBirth>
    <isActive>true</isActive>
    <contact>
        <mobile>222-222-2222</mobile>
        <home>111-111-1111</home>
        <fax>333-333-3333</fax>
        <email>
            <primary>a@primary.com</primary>
            <secondary>b@secondary.com</secondary>
        </email>
    </contact>
    <contact>
        <mobile xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:nil="true"/>
        <home>555-555-5555</home>
        <fax xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:nil="true"/>
        <email>
            <primary xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:nil="true"/>
            <secondary xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:nil="true"/>
        </email>
    </contact>
    <address>
        <line1>120 Spanish</line1>
        <line2>A</line2>
        <city>San Francisco</city>
        <state>California</state>
        <zip xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:nil="true"/>
        <country>USA</country>
    </address>
    <address>
        <line1>120 Encanto</line1>
        <line2>B</line2>
        <city>St Louis</city>
        <state>Missouri</state>
        <zip>63001</zip>
        <country>USA</country>
    </address>
</ns0:Employee>

 

References 

http://mulesoft.github.io/data-weave/

https://www.mulesoft.com/integration-solutions/dataweave-integration

https://docs.mulesoft.com/mule-user-guide/v/3.7/dataweave-reference-documentation

https://docs.mulesoft.com/mule-user-guide/v/3.7/dataweave-tutorial

 

Advantages

  • Mapping and transforming with DataWeave eliminates error-prone custom code

  • Rules, lookups, and editing capabilities enable advanced transformations

  • DataSense™ discovers end-point meta-data for intelligent design

  • Delivers both batch and real-time event-driven data integration capabilities

  • Supports XML, JSON, CSV, POJOs, Excel, and more

 

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