Other answers clarified that trigram similarity is based on alphanumeric characters only. That's why all your examples match 100 %.
You may still be able to make use of a trigram GiST or GIN index and establish your desired sort order with additional
ORDER BY expressions. For your demonstrated case:
SELECT my_column, similarity('$ Hello', my_column) AS sml
WHERE my_column % '$ Hello'
ORDER BY sml DESC
, my_column <> '$ Hello' -- !
The boolean expression
my_column <> '$ Hello' evaluates to
NULL - with this sort order. So the exact match (considering all characters) comes first. And this query can still use a trigram index. A trigram GiST index would (still) even support a "nearest neighbor" (KNN) search with
You can do more, depends on your exact use case and requirements. Example:
ORDER BY sml DESC
, my_column <> '$ Hello'
, my_column !~ '\$ Hello' -- note $ escaped with \$
, levenshtein(my_column , '$ Hello')
Within the same trigram similarity, this sorts exact matches first, then strings containing the exact phrase. And within each subgroup matches the shorter Levenshtein distance first. Alphabetical as final tiebreaker. Related:
Last but not least, you tagged full text search. But your example is based on trigram similarity (provided by the additional module
pg_trgm), which is a largely different concept with completely separate infrastructure and operators. You may want actual full text search instead (and phrase search with that?):
But punctuation characters are considered noise and stripped in FTS all the same. Same "problem".
ts_debug() shows how your text search configuration classifies identified tokens in a given string (
simple configuration in the example).
SELECT * FROM ts_debug('simple', '? Hello %&/( 123');
It starts with the "default" parser (currently the only one), parsing all these as noise to begin with ...