For example, you might create a Rank transformation to identify the 50 highest paid employees in the company. You identify the SALARY column as the input/output port used to measure the ranks, and configure the transformation to filter out all rows except the top 50.

After the Rank transformation identifies all rows that belong to a top or bottom rank, it then assigns rank index values. In the case of the top 50 employees, measured by salary, the highest paid employee receives a rank index of 1. The next highest-paid employee receives a rank index of 2, and so on. When measuring a bottom rank, such as the 10 lowest priced products in the inventory, the Rank transformation assigns a rank index from lowest to highest. Therefore, the least expensive item would receive a rank index of 1.

If two rank values match, they receive the same value in the rank index and the transformation skips the next value. For example, if you want to see the top five retail stores in the country and two stores have the same sales, the return data might look similar to the following:

The RANKINDEX is an output port only. You can pass the rank index to another transformation in the mapping or directly to a target.