MySQL GROUP BY optimization - optimization

Question

This question is a more specific version of a previous question I asked
Table
CREATE TABLE Test4_ClusterMatches
(
`match_index` INT UNSIGNED,
`cluster_index` INT UNSIGNED,
`id` INT NOT NULL AUTO_INCREMENT,
`tfidf` FLOAT,
PRIMARY KEY (`cluster_index`,`match_index`,`id`)
);
The query I want to run
mysql> explain SELECT `match_index`, SUM(`tfidf`) AS total
FROM Test4_ClusterMatches WHERE `cluster_index` IN (1,2,3 ... 3000)
GROUP BY `match_index`;
The Problem with the query
It uses temporary and filesort so its to slow+----+-------------+----------------------+-------+---------------+---------+---------+------+-------+-----------------------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+----------------------+-------+---------------+---------+---------+------+-------+-----------------------------------------------------------+
| 1 | SIMPLE | Test4_ClusterMatches | range | PRIMARY | PRIMARY | 4 | NULL | 51540 | Using where; Using index; Using temporary; Using filesort |
+----+-------------+----------------------+-------+---------------+---------+---------+------+-------+-----------------------------------------------------------+
With the current indexing the query would need to sort by cluster_index first to eliminate the use of temporary and filesort, but doing so gives the wrong results for sum(tfidf).
Changing the primary key to
PRIMARY KEY (`match_index`,`cluster_index`,`id`)
Doesn't use file sort or temp tables but it uses 14,932,441 rows so it is also to slow
+----+-------------+----------------------+-------+---------------+---------+---------+------+----------+--------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+----------------------+-------+---------------+---------+---------+------+----------+--------------------------+
| 1 | SIMPLE | Test5_ClusterMatches | index | NULL | PRIMARY | 16 | NULL | 14932441 | Using where; Using index |
+----+-------------+----------------------+-------+---------------+---------+---------+------+----------+--------------------------+
Tight Index Scan
Using tight index scan by running the search for just one index
mysql> explain SELECT match_index, SUM(tfidf) AS total
FROM Test4_ClusterMatches WHERE cluster_index =3000
GROUP BY match_index;Eliminates the temporary tables and filesort.
+----+-------------+----------------------+------+---------------+---------+---------+-------+------+--------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+----------------------+------+---------------+---------+---------+-------+------+--------------------------+
| 1 | SIMPLE | Test4_ClusterMatches | ref | PRIMARY | PRIMARY | 4 | const | 27 | Using where; Using index |
+----+-------------+----------------------+------+---------------+---------+---------+-------+------+--------------------------+ I'm not sure if this can be exploited with some magic sql-fu that I haven't come across yet?
Question
How can I change my query so that it use 3,000 cluster_indexes, avoids using temporary and filesort without it needing to use 14,932,441 rows?
Update
Using the table
CREATE TABLE Test6_ClusterMatches
(
match_index INT UNSIGNED,
cluster_index INT UNSIGNED,
id INT NOT NULL AUTO_INCREMENT,
tfidf FLOAT,
PRIMARY KEY (id),
UNIQUE KEY(cluster_index,match_index)
);
The query below then gives 10 rows in set (0.41 sec) :)
SELECT `match_index`, SUM(`tfidf`) AS total FROM Test6_ClusterMatches WHERE
`cluster_index` IN (.....)
GROUP BY `match_index` ORDER BY total DESC LIMIT 0,10;
but its using temporary and filesort
+----+-------------+----------------------+-------+---------------+---------------+---------+------+-------+----------------------------------------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+----------------------+-------+---------------+---------------+---------+------+-------+----------------------------------------------+
| 1 | SIMPLE | Test6_ClusterMatches | range | cluster_index | cluster_index | 5 | NULL | 78663 | Using where; Using temporary; Using filesort |
+----+-------------+----------------------+-------+---------------+---------------+---------+------+-------+----------------------------------------------+
I'm wondering if theres anyway to get it faster by eliminating the using temporary and using filesort?

Answer 1

I had a quick look and this is what I came up with - hope it helps...
SQL Table
drop table if exists cluster_matches;
create table cluster_matches
(
cluster_id int unsigned not null,
match_id int unsigned not null,
...
tfidf float not null default 0,
primary key (cluster_id, match_id) -- if this isnt unique add id to the end !!
)
engine=innodb;
Test Data
select count(*) from cluster_matches
count(*)
========
17974591
select count(distinct(cluster_id)) from cluster_matches;
count(distinct(cluster_id))
===========================
1000000
select count(distinct(match_id)) from cluster_matches;
count(distinct(match_id))
=========================
6000
explain select
cm.match_id,
sum(tfidf) as sum_tfidf,
count(*) as count_tfidf
from
cluster_matches cm
where
cm.cluster_id between 5000 and 10000
group by
cm.match_id
order by
sum_tfidf desc limit 10;
id select_type table type possible_keys key key_len ref rows Extra
== =========== ===== ==== ============= === ======= === ==== =====
1 SIMPLE cm range PRIMARY PRIMARY 4 290016 Using where; Using temporary; Using filesort
runtime - 0.067 seconds.
Pretty respectable runtime of 0.067 seconds but I think we can make it better.
Stored Procedure
You will have to forgive me for not wanting to type/pass in a list of 5000+ random cluster_ids !
call sum_cluster_matches(null,1); -- for testing
call sum_cluster_matches('1,2,3,4,....5000',1);
The bulk of the sproc isnt very elegant but all it does is split a csv string into individual cluster_ids and populate a temp table.
drop procedure if exists sum_cluster_matches;
delimiter #
create procedure sum_cluster_matches
(
in p_cluster_id_csv varchar(65535),
in p_show_explain tinyint unsigned
)
proc_main:begin
declare v_id varchar(10);
declare v_done tinyint unsigned default 0;
declare v_idx int unsigned default 1;
create temporary table tmp(cluster_id int unsigned not null primary key);
-- not every elegant - split the string into tokens and put into a temp table...
if p_cluster_id_csv is not null then
while not v_done do
set v_id = trim(substring(p_cluster_id_csv, v_idx,
if(locate(',', p_cluster_id_csv, v_idx) > 0,
locate(',', p_cluster_id_csv, v_idx) - v_idx, length(p_cluster_id_csv))));
if length(v_id) > 0 then
set v_idx = v_idx + length(v_id) + 1;
insert ignore into tmp values(v_id);
else
set v_done = 1;
end if;
end while;
else
-- instead of passing in a huge comma separated list of cluster_ids im cheating here to save typing
insert into tmp select cluster_id from clusters where cluster_id between 5000 and 10000;
-- end cheat
end if;
if p_show_explain then
select count(*) as count_of_tmp from tmp;
explain
select
cm.match_id,
sum(tfidf) as sum_tfidf,
count(*) as count_tfidf
from
cluster_matches cm
inner join tmp on tmp.cluster_id = cm.cluster_id
group by
cm.match_id
order by
sum_tfidf desc limit 10;
end if;
select
cm.match_id,
sum(tfidf) as sum_tfidf,
count(*) as count_tfidf
from
cluster_matches cm
inner join tmp on tmp.cluster_id = cm.cluster_id
group by
cm.match_id
order by
sum_tfidf desc limit 10;
drop temporary table if exists tmp;
end proc_main #
delimiter ;
Results
call sum_cluster_matches(null,1);
count_of_tmp
============
5001
id select_type table type possible_keys key key_len ref rows Extra
== =========== ===== ==== ============= === ======= === ==== =====
1 SIMPLE tmp index PRIMARY PRIMARY 4 5001 Using index; Using temporary; Using filesort
1 SIMPLE cm ref PRIMARY PRIMARY 4 vldb_db.tmp.cluster_id 8
match_id sum_tfidf count_tfidf
======== ========= ===========
1618 387 64
1473 387 64
3307 382 64
2495 373 64
1135 373 64
3832 372 57
3203 362 58
5464 358 67
2100 355 60
1634 354 52
runtime 0.028 seconds.
Explain plan and runtime much improved.

Answer 2

If the cluster_index values in the WHERE condition are continuous, then instead of IN use:
WHERE (cluster_index >= 1) and (cluster_index <= 3000)
If the values are not continuous then you can create a temporary table to hold the cluster_index values with an index and use an INNER JOIN to the temporary table.