Which component would you use for joining multiple sources in a mapping?

The Joiner Transformation is the appropriate component for joining multiple sources in a mapping because it is explicitly designed to combine data from two or more sources based on a related column. This transformation facilitates the merging of records from different data sets, allowing for complex integrations where data elements from separate sources need to be analyzed or reported together.

When using the Joiner Transformation, you can perform various types of joins—such as inner, outer, or full outer joins—depending on the requirements of the mapping. This flexibility allows you to specify which records to pull based on matching keys, thus making it essential for scenarios where data integration involves multiple datasets that must be related to one another.

On the other hand, while the Source Qualifier Transformation is responsible for reading data from a particular source and transforming it into a format suitable for the target, it does not perform join operations among multiple sources. Similarly, the Router Transformation is used to route data into multiple paths based on specified conditions, but does not merge them. Lastly, the Aggregator Transformation is meant for performing calculations on groups of data, like sums or averages, but does not facilitate joining datasets. Thus, for the specific task of joining multiple sources, the Joiner Transformation is the most fitting component.