It is one of a processing stage and as the name suggests, used to perform sort operations. Some of the stages in Datastage requires sorted input data like Join and Merge stage as some stages like Aggregator uses less memory space with the presorted input.
The Row Generator stage is a Development/Debug stage. The Row Generator stage produces a set of mock data fitting the specified metadata. This is useful where you want to test your job but have no real data available to process.
Transformer stage allows us to create transformations to apply to our data. These transformations can be simple or complex and can be applied to individual columns in our data. Transformations are specified using a set of functions.
It is a one of the Processing stage and as the name suggests helps in creating a copy. It can have one input link and n number of output links which helps to create multiple copies of input data. Copy Stage also helps to make a backup for data while performing another operation on that data.
The Merge stage is one of a processing stage. It can have any number of input links, a single output link, and the same number of reject links as there are update input links. Merge stage combines a master dataset with one or more update datasets based on the key columns.
The Filter stage is one of the processing stages and filters out records of the input data as per the specified Conditions. It supports one input link and n number of output links. All the data which don’t satisfy the condition can be passed to an output link.
Aggregator stage is one of a processing stage in Datastage and is used to perform aggregate functions such as MAX, SUM, COUNT etc by grouping and summary operations.