Chapter 6. Understanding Data Flows
In this chapter, we will cover:
- Splitting a stream into two or more streams based on a condition
- Merging rows from two streams with the same or different structure
- Comparing two streams and generating differences
- Generating all possible pairs formed from two datasets
- Joining two streams based on conditions
- Interspersing new rows in between existent rows
- Executing steps even when your stream is empty
- Processing rows differently based on the row number
The main purpose of Kettle transformations is to manipulate data in the form of a dataset; this task is done by the steps of the transformation.
When a transformation is launched, all its steps are started. During the execution, the steps work simultaneously ...