ts_rank functions use the term frequency within that document. not a global term frequency (which is why u need a separate index like what elasticsearch does).

this is important, cos if a word is too common, its considered less significant for a document match. When we calculate IDF, it will be very low for the most occurring words such as stop words (“is” is present in almost all of the documents, and tf-idf will give a very low value to that word).

there's someone who implemented this, its pretty cool. but definitely performance takes a hit versus a separate elasticsearch cluster. https://codebots.com/crud/How-to-efficiently-search-text-usi...