Terribly slow SQL query with COUNT and GROUP BY on two columns

I'm archiving this web forum, which normally gets purged about once a week. So I'm screen scraping it, and storing it into my database (PostgreSQL).

I also do a little analysis on the data, with some graphs for users to enjoy, like what time of day is the forum most active, and so forth.

So I have a posts table, like so:

   Column   |            Type
------------+------------------------------
 id         | integer
 body       | text
 created_at | timestamp without time zone
 topic_id   | integer
 user_name  | text
 user_id    | integer

And I now want to have a post count for each user, for my little top 10 posters table.

I came up with this:

SELECT user_id, user_name, count(*)
FROM posts
GROUP BY user_id, user_name
ORDER BY count DESC LIMIT 10

Which turns out to be very slow. 9 seconds, with just about 300 000 rows in the posts table at the moment.

It takes only half a sec开发者_如何学JAVAond, if I group on just one column, but I need both.

I'm rather new to relational databases, and SQL, so I'm not quite sure if this is right, or just how am I doing it wrong?

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There's probably only one user with a particular ID, so max(user_name) should equal user_name. Then you can group on a single column, which your post indicates works faster:

SELECT user_id, max(user_name), count(*)
FROM posts
GROUP BY user_id

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also could use having count > 0 so you only return true