PostgreSQL Full Text Search and Trigram Confusion

I'm a little bit confused with the whole concept of PostgreSQL, full text search and Trigram. In my full text search queries, I'm using tsvectors, like so:

SELECT * FROM articles
WHERE search_vector @@ plainto_tsquery('english', 'cat, bat, rat');

The problem is, this method doesn't account for misspelling. Then I started to read about Trigram and pg_trgm:

Looking through other examples, it seems like trigram is used or vectors are used, but never both. So my questions are: Are they ever used together? If so, how? Does trigram replace full text? Are trigrams more accurate? And how are trigrams on performance?


  • They serve very different purposes.

    • Full Text Search is used to return documents that match a search query of stemmed words.
    • Trigrams give you a method for comparing two strings and determining how similar they look.

    Consider the following examples:

    SELECT 'cat' % 'cats'; --true

    The above returns true because 'cat' is quite similar to 'cats' (as dictated by the pg_trgm limit).

    SELECT 'there is a cat with a dog' % 'cats'; --false

    The above returns false because % is looking for similarity between the two entire strings, not looking for the word cats within the string.

    SELECT to_tsvector('there is a cat with a dog') @@ to_tsquery('cats'); --true

    This returns true because tsvector transformed the string into a list of stemmed words and ignored a bunch of common words (stop words - like 'is' & 'a')... then searched for the stemmed version of cats.

    It sounds like you want to use trigrams to auto-correct your ts_query but that is not really possible (not in any efficient way anyway). They do not really know a word is misspelt, just how similar it might be to another word. They could be used to search a table of words to try and find similar words, allowing you to implement a "did you mean..." type feature, but this word require maintaining a separate table containing all the words used in your search field.

    If you have some commonly misspelt words/phrases that you want the text-index to match you might want to look at Synonym Dictorionaries