For a long time, PDI developers used to ask, can I run a Job inside a transformation? The answer was definitely a no. In order to solve the requirement, the solution was to create jobs and transformations nested in complex ways. Now you can avoid all that unnecessary work by looping jobs in an easier way. There is a Job Executor step—analogous to the Transformation Executor that you know—that can easily be configured to loop over the rows in a dataset.
The Job Executor is a PDI step that allows you to execute a Job several times simulating a loop. The executor receives a dataset, and then executes the Job once for each row or a set of rows of the incoming dataset.
To understand how this works, we will build a very simple example. The Job that we will execute will have two parameters: a folder and a file. It will create the folder, and then it will create an empty file inside the new folder. Both the name of the folder and the name of the...