TEXT fields are a nightmare. For you and for your server. It is slow to retrieve, and if you are doing searches on it, be prepared, things are going to get bumpy.
If you use MySQL with a MyISAM engine, this may not be an issue for you, you can create a
FULLTEXT index, your only problem is if you want to add a new column, an alter table can take forever, since MySQL creates a new table and copies the old data to the new table. For those who uses MySQL with an InnoDB engine, prepare because, you’ll have more issues. Indexes can’t be
FULLTEXT and if you do need an index you must inform the length of it. It defeats the purpose of you doing the search in that field.
The observation above is only true for MySQL 5.5 or below, since version 5.6 MySQL does support
FULLTEXTindexes on InnoDB – thanks Davey Shafik for the correction.
My TEXT field is not searchable, I just use it to store a big string
In that case you will only have trouble when it comes the time to add a new column or index to that table. As I said, when executing an
ALTER TABLE statement, MySQL will create a new table with the new modifications and reinsert the data. Once I did this in a huge table with a TEXT field, it took 2 days. So, be careful.
Maintenance can be an issue too and I had problems in the past with MyISAM corrupting table and losing a lot of data. In the new versions of MySQL things seems to have changed, I think since the 5.1 version I didn’t face that again.
Why the statement
LIKE is so slow?
Take this table as example:
CREATE TABLE `options` ( `id` INT, `user_id` INT, `value` TEXT, `created` DATETIME ) DEFAULT CHARSET=utf8;
Well, one of the first things we learn when programming is that reading from the hard disk is costly while reading from the memory is super fast. For every row stored in a table like the one above, the field
value will not be stored inline like the
id value. It will store a reference to a file containing the actual data, MySQL stores 4MB of data into a TEXT field.
Having that in mind, every time you use a
LIKE statement you are reading from your server disk, which is pretty slow (you can have a super server with high IOPS, but this is not the case for the majority). Unless you use the MyISAM engine and create a
FULLTEXT index into the
ALTER TABLE `options` ADD FULLTEXT INDEX `ix_value` (`value` ASC);
Making the search fast
You will need to index the data through one of the services in an extra step of the table insert. One thing for sure, the search will be FAST!
Making the retrieval fast (no search)
Storing in the database
If you don’t want to add another layer, you can achieve a compromise by removing the TEXT field from the table and adding it to a second one.
It would look like this:
CREATE TABLE `options` ( `id` INT, `user_id` INT, `created` DATETIME )Engine=InnoDB DEFAULT CHARSET=utf8; CREATE TABLE `options_text` ( `option_id` INT, `value` TEXT ) Engine=MyISAM DEFAULT CHARSET=utf8;
That way you can create a
FULLTEXT index in the table and still be able to work with better data consistency provided by InnoDB. You can use InnoDB engine on the second table too, but it is not needed unless you want to use the constraint in the foreign keys.
To retrieve it, a
INNER JOIN or
LEFT JOIN between the two tables:
SELECT `options`.`id` AS id, `options`.`user_id` AS user_id, `options`.`created` AS created, `options_text`.`value` AS value FROM `options` INNER JOIN `options_text` ON `options`.`id` = `options_text`.`option_id`
Don’t be fooled, the search into
options_text will still be slow, but it will be better than if it all were stored in the same table.
There is not a right way of doing this, you must consider all the implications of either approach and see what works better for you.
Keep this in mind: the first two proposed ideas need to add an extra step in the CRUD operations, and only you know how problematic can be to mess with that in a legacy application, for example. You won’t have much trouble to implement with a clean code.
I recommend you read more about BLOB and TEXT fields performance and storage in this article from Peter Zaitsev in the Percona blog.