Top 'n' results for each keyword - mysql

Question

I have a query to get the top 'n' users who commented on a specific keyword,
SELECT `user` , COUNT( * ) AS magnitude
FROM `results`
WHERE `keyword` = "economy"
GROUP BY `user`
ORDER BY magnitude DESC
LIMIT 5
I have approx 6000 keywords, and would like to run this query to get me the top 'n' users for each and every keyword we have data for. Assistance appreciated.

Answer 1

Since you haven't given the schema for results, I'll assume it's this or very similar (maybe extra columns):
create table results (
id int primary key,
user int,
foreign key (user) references <some_other_table>(id),
keyword varchar(<30>)
);
Step 1: aggregate by keyword/user as in your example query, but for all keywords:
create view user_keyword as (
select
keyword,
user,
count(*) as magnitude
from results
group by keyword, user
);
Step 2: rank each user within each keyword group (note the use of the subquery to rank the rows):
create view keyword_user_ranked as (
select
keyword,
user,
magnitude,
(select count(*)
from user_keyword
where l.keyword = keyword and magnitude >= l.magnitude
) as rank
from
user_keyword l
);
Step 3: select only the rows where the rank is less than some number:
select *
from keyword_user_ranked
where rank <= 3;
Example:
Base data used:
mysql> select * from results;
+----+------+---------+
| id | user | keyword |
+----+------+---------+
| 1 | 1 | mysql |
| 2 | 1 | mysql |
| 3 | 2 | mysql |
| 4 | 1 | query |
| 5 | 2 | query |
| 6 | 2 | query |
| 7 | 2 | query |
| 8 | 1 | table |
| 9 | 2 | table |
| 10 | 1 | table |
| 11 | 3 | table |
| 12 | 3 | mysql |
| 13 | 3 | query |
| 14 | 2 | mysql |
| 15 | 1 | mysql |
| 16 | 1 | mysql |
| 17 | 3 | query |
| 18 | 4 | mysql |
| 19 | 4 | mysql |
| 20 | 5 | mysql |
+----+------+---------+
Grouped by keyword and user:
mysql> select * from user_keyword order by keyword, magnitude desc;
+---------+------+-----------+
| keyword | user | magnitude |
+---------+------+-----------+
| mysql | 1 | 4 |
| mysql | 2 | 2 |
| mysql | 4 | 2 |
| mysql | 3 | 1 |
| mysql | 5 | 1 |
| query | 2 | 3 |
| query | 3 | 2 |
| query | 1 | 1 |
| table | 1 | 2 |
| table | 2 | 1 |
| table | 3 | 1 |
+---------+------+-----------+
Users ranked within keywords:
mysql> select * from keyword_user_ranked order by keyword, rank asc;
+---------+------+-----------+------+
| keyword | user | magnitude | rank |
+---------+------+-----------+------+
| mysql | 1 | 4 | 1 |
| mysql | 2 | 2 | 3 |
| mysql | 4 | 2 | 3 |
| mysql | 3 | 1 | 5 |
| mysql | 5 | 1 | 5 |
| query | 2 | 3 | 1 |
| query | 3 | 2 | 2 |
| query | 1 | 1 | 3 |
| table | 1 | 2 | 1 |
| table | 3 | 1 | 3 |
| table | 2 | 1 | 3 |
+---------+------+-----------+------+
Only top 2 from each keyword:
mysql> select * from keyword_user_ranked where rank <= 2 order by keyword, rank asc;
+---------+------+-----------+------+
| keyword | user | magnitude | rank |
+---------+------+-----------+------+
| mysql | 1 | 4 | 1 |
| query | 2 | 3 | 1 |
| query | 3 | 2 | 2 |
| table | 1 | 2 | 1 |
+---------+------+-----------+------+
Note that when there are ties -- see users 2 and 4 for keyword "mysql" in the examples -- all parties in the tie get the "last" rank, i.e. if the 2nd and 3rd are tied, both are assigned rank 3.
Performance: adding an index to the keyword and user columns will help. I have a table being queried in a similar way with 4000 and 1300 distinct values for the two columns (in a 600000-row table). You can add the index like this:
alter table results add index keyword_user (keyword, user);
In my case, query time dropped from about 6 seconds to about 2 seconds.

Answer 2

You can use a pattern like this (from Within-group quotas (Top N per group)):
SELECT tmp.ID, tmp.entrydate
FROM (
SELECT
ID, entrydate,
IF( #prev <> ID, #rownum := 1, #rownum := #rownum+1 ) AS rank,
#prev := ID
FROM test t
JOIN (SELECT #rownum := NULL, #prev := 0) AS r
ORDER BY t.ID
) AS tmp
WHERE tmp.rank <= 2
ORDER BY ID, entrydate;
+------+------------+
| ID | entrydate |
+------+------------+
| 1 | 2007-05-01 |
| 1 | 2007-05-02 |
| 2 | 2007-06-03 |
| 2 | 2007-06-04 |
| 3 | 2007-07-01 |
| 3 | 2007-07-02 |
+------+------------+