To Batch-Write to a File

In this procedure, a database connector retrieves data from two tables. Mule feeds this data into Transform Message inside the Batch Commit. In Transform Message, DataWeave maps the data from a Java.util.HashMap to the CSV format. A file connector writes the resulting CSV file to disk. A logger component writes processing details to the console.

This procedure uses a MySQL sample database, which you can import. Download the SQL script using the following URL:

The script creates the company database that has tables named employees and roles.

  1. In Studio, create a new project, and drag connectors onto the canvas as follows:

    • Drag Poll onto the canvas.

    • Drag and put Processor Chain inside Poll.

    • Drag and put Database inside Processor Chain.

    • Drag Batch Step onto the canvas in the process section.

    • Drag and put Batch Commit inside Batch Step.

    • Drag and put Transform and File inside Batch Commit.

    • Put Logger in the on complete section of Batch Step, as shown in the following screenshot:

      batch task components
  2. In Database properties, click Add add, and set the following options:

    • Host: The name of the host running MySQL.

    • Port: 3306

    • User and Password: Your database user name and password.

    • Database: company

    • MySQL Driver: Browse to the location of and select the driver that is compatible with your database.

      Test and save the settings.

  3. In Database properties, set options according to the following table:

    Parameter Value



    Query Type


    Parameterized SQL Statement

    SELECT no, first_name, last_name, role FROM employees INNER JOIN roles ON = roles.emp_no

  4. Double-click Transform Message to open its configuration.

    Datasense should build the input side of your transform. If not, to instruct DataWeave to process the MySQL data, right-click Payload on the left and click Set Metadata.

    set metadata
  5. In Select Metadata Type, define the metadata as type Map, comprised of type List<Element>. Add the names and data types of the employees table database:

    • first_name, String

    • last_name, String

    • no, Integer

    • role, String

      The Transform Message configuration appears as follows.


      The resulting DataWeave code is auto-generated:

      %dw 1.0
      %output application/csv
      payload map ((payload01 , indexOfPayload01) -> {
      	column_0: payload01.first_name,
      	column_1: payload01.last_name,
      	column_3: payload01.role
  6. Configure the File connector to save the CSV file to your file system.

  7. Configure the Logger to output the following message at log level INFO.

    Total Records exported: #[message.payload.getLoadedRecords()], Failed Records: #[message.payload.getFailedRecords()], Processing time: #[message.payload.getElapsedTimeInMillis()]
  8. Run the app, and check that the results appear in the file on your file system. Check the console and verify that logged messages appear as expected. For example:

    INFO 2017-08-14 09:42:47,170 [batch-job-myprojectBatch-work-manager.02] org.mule.api.processor.LoggerMessageProcessor: Total Records exported: 100, Failed Records: 0, Processing time: 516

  9. In the properties editor, click Terminate stop app to stop the app from running every ten minutes.