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Well, firts of all, sorry by my english. I try to do a query in a table that the users can include some text, like a blog page. The users can design the content in a html format. In my table it is stored like this:

Estadísticas<br />
<table border="0">
<tbody>
<tr>
<td>Columna 1</td>
<td>Columna 2</td>
</tr>
<tr>
<td>Columna 3<br /></td>
<td>Columna 4<br /></td>
</tr>
</tbody>
</table>

I must serch in that content all that user's want. The field 'texto' (that I'm using for it) is a longtext field and the table is innodb. I can't use full text search, 'cause it is only for myisam tables. I made the query as:

"SELECT * FROM texto WHERE texto like '%$variable%'"

but the query is very, very slow, an it take an eternity. The table has a 849 records, that's isn't big. If I write the same query in a phpmyadmin also take a very, very long time. But there are big records in this field, some records have the video html, tables, images, but it's just that, text like the above.

What I can do??? How can improve the performance of the query??? I appreciate all your help. Thanks a lot. And again, sorry for my english.

Anibal Mauricio
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1 Answers1

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Unfortunately you can't get more from the structure you have - any clustered or non-clustered index won't be able to handle like '%...' query. The best solution would be probably to export your data to some full-text search engine (eg. SOLR) and use this engine to fulfill users queries. If it's not possible than another solution would be to create a tokens table that will play a role of a text index:

create table tokens(
  token varchar(100) not null,
  docid int not null references testdo(id),
  constraint PK_tokens primary key (token, docid)
);

where docid references your data table (I named it testdo).

Then you need to fill the tokens table by splitting users blog posts by some common html expressions, eg.:

insert ignore into tokens values
('Estad', 1),
('Columna 1', 1),
('Columna 2', 1),
('Estad', 1);

Notice ignore keyword which will silently ignore any duplicates that may come. With tokens table filled with data you may modify your query to something like:

select * from testdo d 
  inner join tokens t on t.docid = d.id where t.token like 'Col%'

which should execute much faster as it's using indexes and key-lookups.

PS. You may improve the tokens table by adding a count column which will keep a number of occurrences of a given word in a document. You may then order the results by this column and make the them even more relevant to the search term.

Sebastian
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