PHP and MySQL powered blogging platform

If I am creating a blog system and I would like to incorporate 'tags' into my blogposts. These tags function in a way that is similar to what you see here, as they help to categorize posts with similar topics.

My plan is to store the tags in the database as a comma-separated string of words (words without spaces). However, I am unsure about how I would search for all posts that contain both tag A and tag B.

I prefer not to use a simple solution that works well with a small database by retrieving all data and scanning it using a PHP loop. This method would not be suitable for a large database with hundreds or thousands of posts. Even though I do not anticipate having many blogposts, I want the system to be robust and efficient, saving processing time on PHP scripts by obtaining accurate results directly from the database.

Imagine if my table had a structure like this (it's actually slightly more complex)

blogposts:
id   | title         | content_html                  | tags
0    | "hello world" | "<em>hello world!</em>"       | "hello,world,tag0"
1    | "bye world"   | "<strong>bye world!</strong>" | "bye,world,tag1,tag2"
2    | "hello you"   | "hello you! :&gt;"            | "hello,tag3,you"

How could I select all posts that have both "hello" and "world" within their tags? I am aware of the LIKE statement, which allows you to search for substrings, but can it be used effectively with multiple substrings?

Answer №1

Indexing a field of CSV values and finding unique values in SQL can be challenging. To solve this issue, it is recommended to set up additional tables and make adjustments to the existing table structure.

New table structures:

- blogposts:

id | title | content_html

- tags:

id | tag_name

- taxonomy table:

id | blogpost_id | tag_id

When adding a tag to a blog post, a new record should be inserted into the taxonomy table. When querying data, you can join these tables to retrieve relevant information using a query similar to this:

SELECT `tag_name` FROM `blogposts` INNER JOIN `blogposts_taxonomy` ON
`blogposts`.`id`=`blogposts_taxonomy`.`blogpost_id` INNER JOIN `blogpost_tags` ON
`blogposts_taxonomy`.`tag_id`=`blogpost_tags`.`id` WHERE `blogposts`.`id` = someID;

//UPDATE

Establishing an N:M relationship between tables provides flexibility during application development. For instance, if you wish to search for blogposts tagged as "php," you can execute the following query:

SELECT `id`,`html_content` FROM `blogposts` INNER JOIN `blogposts_taxonomy` ON
`blogposts`.`id`=`blogposts_taxonomy`.`blogpost_id` INNER JOIN `blogposts_tags` ON
`blogposts_taxonomy`.`tag_id`=`blogposts_tags`.`id` WHERE `blogposts_tags`.`tag_name`="php";

This query will return all blogposts associated with the "php" tag.

Cheers

Answer №2

If you are considering storing data in this format, the FIND_IN_SET mysql function can be very helpful.

You may need to use the function multiple times in the where clause.

However, performance may suffer with this approach - it is recommended to have a linked table structure for a one-to-many relationship as it is a much better solution. If you have a large number of similar tags, a many-to-many relationship could be implemented using a 'post2tag' table.

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