Relevance ranking can impose a significant computational cost in the context of affected search operations (that is, operations where relevance ranking is actually enabled).
You can minimize the performance impact of relevance ranking in your implementation by making module substitutions when appropriate, and by ordering the modules you do select sensibly within your relevance ranking strategy.
Because of the linear cost of relevance ranking in the size of the result set, the actual cost of relevance ranking depends heavily on the set of ranking modules used. In general, modules that do not perform text evaluation introduce significantly lower computational costs than text-matching-oriented modules.
In order to maximize the performance of your relevance ranking strategy, consider a less expensive way to get similar results. For example, replacing Exact with Phrase may improve performance in some cases with relatively little impact on results.
Relevance ranking modules are only evaluated as needed. When higher-priority ranking modules determine the order of records, lower-priority modules do not need to be calculated. This can have a dramatic impact on performance when higher-cost modules have a lower priority than a lower-cost module.
While you have the freedom to order modules as you like, for best performance, make sure that the cheaper modules are placed before the more expensive ones in your strategy.