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Data Mapper mediator is a data mapping solution that can be integrated into a mediation sequence. It converts and transforms one data format to another, or changes the structure of the data in a message. It provides a WSO2 Developer Studio-based tool to create a graphical mapping configuration and generates the files required to execute this graphical mapping configuration by the WSO2 Data Mapper engine.

WSO2 Data Mapper is an independent component that does not depend on any other WSO2 product. However, other products can use the Data Mapper to achieve/offer data mapping capabilities. Data Mapper Mediator is the intermediate component you need for that, which gives the data mapping capability into the ESB profile of WSO2 EI.

Data Mapper mediator finds the configuration files from the Registry and configures the Data Mapper Engine with the input message type (XML/JSON/CSV) and output message type (XML/JSON/CSV). Then it takes the request message from the ESB profile message flow and uses the configured Data Mapper Engine to execute the transformation and adds the output message to the ESB profile message flow.

The Data Mapper mediator is a content-aware mediator.


You need to install the WSO2 EI Tooling to use the Data Mapper mediator. For instructions on installing this WSO2 EI Tooling Plugin, see Installing WSO2 EI Tooling.


<datamapper config="gov:datamapper/FoodMapping.dmc" inputSchema="gov:datamapper/FoodMapping_inputSchema.json" inputType="XML" outputSchema="gov:datamapper/FoodMapping_outputSchema.json" outputType="XML"/> 

UI configuration 

Ui configuration of the Data Mapper mediator  

The parameters available for configuring the Data Mapper mediator are as follows.

Parameter nameDescription
Mapping ConfigurationThe file, which contains the script file that is used to execute the mapping. You need to create a mapping configuration file using the Dev Studio-based Tooling plugin, and store it either in the Configuration Registry or Governance Registry, to select and upload it from here.
Input SchemaJSON schema, which represents the input message format. You need to create an input schema file using the Dev Studio-based Tooling plugin, and store it either in the Configuration Registry or Governance Registry to select and upload it from here.
Output SchemaJSON schema, which represents the output message format. You need to create an output schema file using the Dev Studio-based Tooling plugin, and store it either in the Configuration Registry or Governance Registry to select and upload it from here.
Input TypeExpected input message type (XML/JSON/CSV)
Output TypeTarget output message type (XML/JSON/CSV)


You can configure the mediator using XML. Click switch to source view in the Mediator window.

Components of Data Mapper

WSO2 Data Mapper consists of two components. They are Data Mapper Tooling and Data Mapper Engine.

Data Mapper Tooling 

Data Mapper Tooling component is the interface used to create configuration files that are required by the Data Mapper Engine to execute the mapping. Following three configuration files are needed by the Data Mapper engine. 

  • Input schema file
  • Output schema file
  • Mapping configuration file

These three files are generated by the Data Mapper Tool and saved in a Registry Resource project, which you deploy in a WSO2 server as shown in the example below.

generated configuration files

The .datamapper and .datamapper_diagram files as shown in the example above contain meta data related to the Data Mapper diagram. They are ignored when you deploy the project to a server to be used by the Data Mapper Engine. Only the two schema files and the .dmc (Data Mapper Configuration) get deployed.

Input and output schema files

Input and output schema files are custom-defined JSON schemas that define the input/output format of input/output messages. The Data Mapper tool generates them when loading the input and output files as shown below.

You can also create the input and output JSON Schemas manually using the Data Mapper Diagram Editor. For instructions, see Creating a JSON Schema Manually.

select load input option

select input format

You can load the following input/output message formats:

When loading a sample input XML file, you cannot have the default namespace (i.e. without a prefix in the namespace element). Also, you need to use the same prefix in all occurrences that refer to the same namespace within one XML file. For example, see the use of the prefix axis2ns11 in the example below.

 Sample input XML file
<?xml version="1.0" encoding="utf-8"?>
<soapenv:Envelope xmlns:soapenv="">
    <axis2ns11:LimitInfoHeader xmlns:axis2ns11="">
            <axis2ns11:type>API REQUESTS</axis2ns11:type>
    <axis2ns11:records xmlns:axis2ns11="" xmlns:xsi="" xsi:type="sf:sObject">
    <sf:type xmlns:sf="">Account</sf:type>
    <sf:Id xmlns:sf="">001E0000002SFO2IAO</sf:Id>
    <sf:CreatedDate xmlns:sf="">2011-03-15T00:15:00.000Z</sf:CreatedDate>
    <sf:Id xmlns:sf="">001E0000002SFO2IAO</sf:Id>
    <sf:Name xmlns:sf="">WSO2</sf:Name>
  • XML: to load a sample XML file
  • JSON: to load a sample JSON file
  • CSV: to load a sample CSV file with column names as the first record
  • XSD: to load an XSD file, which is an actual schema for XML files
  • JSONSCHEMA: to load a WSO2 Data Mapper JSON schema
  • CONNECTOR: to use Data Mapper with WSO2 EI Connectors. Connectors will contain JSON schemas for each operation that defines the message formats to which it will respond and expect. Therefore, when you integrate connectors in a project this Connector option searches through the workspace and find the available Connectors. Then, you can select the respective Connector in the operation, so that the related JSON schema will be loaded for the Data Mapper by the tool.
Mapping configuration file

This is a JavaScript file generated by looking at the diagram you draw in the Data Mapper Diagram Editor by connecting input elements to output elements. Every operation you define in the diagram gets converted to a JavaScript operation.

Data Mapper Engine

You need the following information to configure the Data Mapper Engine:

  • Input message type
  • Output message type
  • Input schema Java Scripting API
  • Output schema
  • Mapping configuration

At the runtime, the Data Mapper Engine gets the input message and the runtime variable map object and outputs the transformed message. The Data Mapper Engine uses the Java Scripting API, t o execute the mapping configuration. Therefore, if your runtime is JAVA 7, it uses the Rhino JS Engine and if your runtime is JAVA 8, it uses the Nashorn JS engine.

When you use JAVA 7, there are several limitations in the Rhino engine that directly affects the Data mapper Engine. There are several functions that Rhino does not support. For example, String object functions like startsWith() and endsWith(). Therefore, the Rhino engine may have limitations in executing those when using custom functions and operators.

Using product-specific runtime variables

Also, the Data Mapper engine allows you to use runtime product-specific variables in the mapping. The intermediate component should construct a map object containing runtime product-specific variables and send it to the Data Mapper Engine, thereby, when the mapping happens in the Data Mapper Engine, these variables become available.

For example, the Data Mapper mediator provides properties like  axis2/transport/synapse/axis2client/operation/.. In the Data Mapper diagram, you can use the  Property operator  and define the scope and the property name and use it in the mapping. Then, the Data Mapper mediator will identify the required properties to execute the mapping and populate a map with the required properties and will send it to the Data Mapper Engine. 

Data Mapper element and attribute types

Following are the element and attribute types that are supported by the Data Mapper.

  • {} - represents object elements
  • [] - represents array elements
  • <> - represents primitive field values
  • A - represents XML attribute values

Data Mapper operations

The operations palette placed in the left-hand side of the WSO2 Data Mapping Diagram Editor displays the operations that the Data Mapper supports as shown below.

You can drag and drop these operations to the Editor area. There are six categories of operations as follows:

  • Links
  • Common
  • Arithmetic
  • Conditional
  • Boolean
  • Type Conversion
  • String

DataMapperLink.gif   Data Mapping Link:  maps elements with other operators and elements.


Constant Constant: defines String, number or boolean constant values.

CustomFunction Custom Function: defines custom functions to use in the mapping.

Properties Properties: uses product-specific runtime variables.

GlobalVariable Global Variable: instantiates global variables that you can access from anywhere. 

Compare Compare: compares two inputs in the mapping.


Add Add: adds two numbers.

Subtract Subtract: subtracts two or more numbers.

Multiply Multiply: multiplies two or more numbers.

Divide Divide: divides two numbers.

Celi Ceiling: derives the ceiling value of a number (closest larger integer value).

Floor Floor: derives the floor value of a number (closest lower integer value).

Round Round: derives the nearest integer value.

SetPrecision Set Precision: formats a number into a specified length.

AbsoluteValue Absolute Value: derives the absolute value of a rational number.

Min Min: derives the minimum number from given inputs

Max Max: derives the maximum number from given inputs


IfElse   IfElse:  uses a condition and selects one input from given two.


AND AND: performs the boolean AND operation on inputs. 

OR OR: performs the boolean OR operation on inputs.

NOT NOT: performs the boolean NOT operation on inputs.

Type conversion

StringToNumber StringToNumber: converts a String value to number (“0” -> 0).

StringToBoolean StringToBoolean: converts a String value to boolean (“true” -> true).

ToString ToString: converts a number or a boolean value to String.


Concat Concat: concatenates two or more Strings.

Split Split: splits a String by a matching String value.

UpperCase Uppercase: converts a String to uppercase letters.

LowerCase Lowercase: converts a String to lowercase letters.

StringLength String Length: gets the length of the String.

StartsWith StratsWith: checks whether a String starts with a specific value. (This is not supported in Java 7.)

EndsWith EndsWith: checks whether String ends with a specific value. (This is not supported in Java 7.)

Substring Substring: extracts a part of the String value.

Trim Trim: removes white spaces from the beginning and end of a String.

Replace Replace: replaces the first occurrence of a target String with another.

Match Match – check whether the input match with a (JS) Regular Expression


Example 1 - Creating a  SOAP payload with namespaces

This example creates a Salesforce login SOAP payload using a JSON payload. The login payload consists of XML namespaces. Even though the JSON payload does not contain any namespace information, the output JSON schema will be generated with XML namespace information using the provided SOAP payload.  

example one Data mapper diagram

The sample input JSON payload is as follows.


The sample output XML is as follows.

<soapenv:Envelope xmlns:urn="" xmlns:soapenv="">

Example 2 - Mapping  SOAP header elements 

This example demonstrates how to map SOAP header elements along with SOAP body elements to create a certain SOAP payload, by creating a Salesforce convertLead SOAP payload using a JSON payload. The Convert Lead SOAP payload needs mapping SOAP header information.
E.g. <urn:sessionId>QwWsHJyTPW.1pd0_jXlNKOSU</urn:sessionId>

example two

The sample input JSON payload is as follows.

   "opportunityName":"Partner Opportunity",

The sample output XML is as follows.

<?xml version="1.0" encoding="utf-8"?>  
<soapenv:Envelope xmlns:urn="" xmlns:soapenv="">
     <urn:convertLead >
        <urn:leadConverts> <!-- Zero or more repetitions -->
           <urn:opportunityName>Partner Opportunity</urn:opportunityName>

Example 3 - Mapping primitive types

This example demonstrates how you can map an XML payload with integer, boolean etc. values, into a JSON payload with required primitive types,  by specifying the required primitive type in the JSON schema.

example three mapping

The sample input XML payload is as follows.

<?xml version="1.0" encoding="UTF-8" ?>

The sample output JSON is as follows.

    "name" : "app_name",
    "version" : "version",
    "manifest_version" : 2,
    "description" : "description_text",
    "container" : "GOOGLE_DRIVE",
    "api_console_project_id" : "YOUR_APP_ID",
    "gdrive_mime_types": {
      "": [
          "type": ["image/png", "image/jpeg", "image/gif", "application/",
          "href": "http://your_web_url/",
          "title" : "Open",
          "disposition" : "window"
    "icons": {
      "128": "icon_128.png"
    "app" : {
      "launch" : {
      "web_url" : ""

Example 4 - Mapping XML to CSV

This example demonstrates how you can map an XML payload to CSV format.

example four mapping

The  sample in put XML payload is as follows.

<?xml version="1.0"?>
<PurchaseOrder PurchaseOrderNumber="001">
    <Name>James Yee</Name>
    <Street>Downtown Bartow</Street>
    <City>Old Town</City>
    <Name>Elen Smith</Name>
    <Street>123 Maple Street</Street>
    <City>Mill Valley</City>
 <DeliveryNotes>Please leave packages in shed by driveway.</DeliveryNotes>

The  sample out put CSV is as follows.

James Yee,Downtown Bartow,Old Town,PA,95819,USA
Ellen Smith,123 Maple Street,Mill Valley,CA,10999,USA

Example 5 - Mapping XSD to JSON

This example demonstrates how you can map an XSD payload to JSON format.

example 5 mapping

The  sample in put XSD payload is as follows.

<xs:schema attributeFormDefault="unqualified" elementFormDefault="qualified" xmlns:xs="">
  <xs:element name="books">
        <xs:element name="book">
              <xs:element type="xs:string" name="id"/>
              <xs:element type="xs:string" name="author"/>
              <xs:element type="xs:string" name="title"/>
              <xs:element type="xs:float" name="price"/>

The  sample out put JSON is as follows.

  "books": {
    "book": {
      "id": "001",
      "author": "Writer",
      "title": "Great book on nature",
      "price": "44.95"


For a sample that demonstrates how to use the Data Mapper mediator, see:

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