Hello,
I am trying to identify how best to handle the situation where a controlled
vocabulary needs to be searched on using full text search.
I have a list of brand names that have, what FTS deems, blank characters in
them that I need to search against. E.g. (+)people, D&G, 100% Design.
These particular combinations are proving to be difficult so I would like
to do a replacement at index and query time
(+)people, +people -> pluspeople
100% Design -> 100percent Design
D&G, D & G, DG -> DandG
Running these through the default parser means I get a much reduced lexemes
that won't be exact enough.
alias | description | token | dictionaries | dictionary |
lexemes
-----------+-----------------+-------+----------------+--------------+---------
asciiword | Word, all ASCII | d | {english_stem} | english_stem | {d}
blank | Space symbols | & | {} | |
asciiword | Word, all ASCII | g | {english_stem} | english_stem | {g}
(3 rows)
alias | description | token | dictionaries | dictionary |
lexemes
-----------+-----------------+--------+----------------+--------------+---------
blank | Space symbols | ( | {} | |
blank | Space symbols | +) | {} | |
asciiword | Word, all ASCII | people | {english_stem} | english_stem |
{peopl}
Can I achieve this with FTS and dictionaries or would I need a custom
parser? Any other ideas on how a search like this could work?
I have considered using the actual text column in the query to try and
match the exact term using ilike and pg_trgm. So for a user query of 'D&G
dresses' the select could be:
select * from test where text_val @@ plainto_tsquery('english','d&g
dresses') and lex ilike'%d&g%';
but there would be some horrible query mangling to find all words that have
the blank tokens and use them in multiple ilike comparisons.
Thanks
Sumit
