listread wrote:
Chris,
I just assumed that everyone on this list was using MySQL... That's
what we're using (v. 5.1.45 GA) with InnoDB as the engine.
Most people are but there are lots of types of databases out there :)
(I just read your tutorial at http://www.designmagick.com/article/16/
It was very helpful - I look forward to checking out more of your
articles.)
If it is just as efficient to use multiple separate indexes, that would
make index building less complicated on our large db.
It is, though wildcard searches can't always use indexes.
If you do
field like 'abcdef%';
then an index can potentially be used because the db (mysql or
otherwise) can look at the start of the string to see if it matches. The
longer the string the more likely an index can be used (eg doing field
like 'a%' probably won't use an index, it'll end up being quicker to
scan the actual data).
If you do
field like '%abcdef%';
then an index can't be used since abcdef could appear anywhere in the
string.
Without a large dataset, it hard to truly test a system and if you have
a large dataset, like we do, it takes quite a while to build indexes.
Definitely, it's the best way to test and also the hardest since
rebuilding the db takes so long.
Our project is a petition signature validation suite. Since many of the
handwritten names and addresses on petition sheets are difficult to
read, the user needs to be able to do some fuzzy searching. Sometimes
it's easier to read the address than it is the name. The zip code is
usually easy to read. We almost always need to use LIKE queries, since
some part of the name or address is typically hard to read. (We try to
use as many of the leading characters as we can and wildcard the
remaining.)
I'd suggest fulltext but that won't work with innodb, only myisam. You
could do something like keep the addresses and names in a separate
myisam table just for searching, though that means a whole new import
process and also means you'd end up having to do two queries (maybe a
subquery or join, you'd have to test) - one do to full text search and
one to get the rest of the data based on the result of the first.
What do your queries end up looking like?
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