Suppose I have two columns, keywords and content. I have a fulltext index across both. I want a row with foo in the keywords to have more relevance than a row with foo in the content. What do I need to do to cause MySQL to weight the matches in keywords higher than those in content?
I'm using the "match against" syntax.
SOLUTION:
Was able to make this work in the following manner:
SELECT *,
CASE when Keywords like '%watermelon%' then 1 else 0 END as keywordmatch,
CASE when Content like '%watermelon%' then 1 else 0 END as contentmatch,
MATCH (Title, Keywords, Content) AGAINST ('watermelon') AS relevance
FROM about_data
WHERE MATCH(Title, Keywords, Content) AGAINST ('watermelon' IN BOOLEAN MODE)
HAVING relevance > 0
ORDER by keywordmatch desc, contentmatch desc, relevance desc
Create three full text indexes
Then, your query:
SELECT id, keyword, content,
MATCH (keyword) AGAINST ('watermelon') AS rel1,
MATCH (content) AGAINST ('watermelon') AS rel2
FROM table
WHERE MATCH (keyword,content) AGAINST ('watermelon')
ORDER BY (rel1*1.5)+(rel2) DESC
The point is that rel1
gives you the relevance of your query just in the keyword
column (because you created the index only on that column). rel2
does the same, but for the content
column. You can now add these two relevance scores together applying any weighting you like.
However, you aren't using either of these two indexes for the actual search. For that, you use your third index, which is on both columns.
The index on (keyword,content) controls your recall. Aka, what is returned.
The two separate indexes (one on keyword only, one on content only) control your relevance. And you can apply your own weighting criteria here.
Note that you can use any number of different indexes (or, vary the indexes and weightings you use at query time based on other factors perhaps ... only search on keyword if the query contains a stop word ... decrease the weighting bias for keywords if the query contains more than 3 words ... etc).
Each index does use up disk space, so more indexes, more disk. And in turn, higher memory footprint for mysql. Also, inserts will take longer, as you have more indexes to update.
You should benchmark performance (being careful to turn off the mysql query cache for benchmarking else your results will be skewed) for your situation. This isn't google grade efficient, but it is pretty easy and "out of the box" and it's almost certainly a lot lot better than your use of "like" in the queries.
I find it works really well.