Solr is not limited to finding relevant results for a user's search. Providing the end user with selection of the most relevant results, that are sorted, is important as well. We will be doing this using SQL to find relevant matching pattern results and sorting them into columns in either ascending or descending order. Similarly, Solr also does sorting of the result set retrieved based on the search pattern, with a score that would match the relevancy strength in the dataset.

Ranked results is very important, primarily because the volume of data that search engine platforms have to dig through is huge. If there is no control on ranked results, then the result set would be filled with no relevancy and would have so much data that it wouldn't be feasible to display it either. The other important aspect is user experience. All of us are now used to expecting a search engine to provide relevant results using limited keywords. We are getting restless, aren't we? But we expect a search engine platform to not get annoyed and provide us relevant ranked results with few keywords. Hold on, we are not talking of Google search here! So for users like us, Solr can help address such situations by providing higher rankings based on various criteria: fields, terms, document name, and a few more. The ranking of the dataset can vary based on many factors, but a higher ranking would generally be based on the relevancy of the search pattern. With this, we can also have criteria such as gender; with the rankings of certain documents being at the top.