Summary
The problem is that field
is not a good candidate for indexing, due to the nature of b-trees.
Explanation
Let's suppose you have a table that has the results of 500,000 coin tosses, where the toss is either 1
(heads) or 0
(tails):
CREATE TABLE toss (
id int NOT NULL AUTO_INCREMENT,
result int NOT NULL DEFAULT '0',
PRIMARY KEY ( id )
)
select result, count(*) from toss group by result order by result;
+--------+----------+
| result | count(*) |
+--------+----------+
| 0 | 250290 |
| 1 | 249710 |
+--------+----------+
2 rows in set (0.40 sec)
If you want to select one toss (at random) where the toss was tails, then you need to search through your table, picking a random starting place.
select * from toss where result != 1 limit 123456, 1;
+--------+--------+
| id | result |
+--------+--------+
| 246700 | 0 |
+--------+--------+
1 row in set (0.06 sec)
explain select * from toss where result != 1 limit 123456, 1;
+----+-------------+-------+------+---------------+------+---------+------+--------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+------+---------------+------+---------+------+--------+-------------+
| 1 | SIMPLE | toss | ALL | NULL | NULL | NULL | NULL | 500000 | Using where |
+----+-------------+-------+------+---------------+------+---------+------+--------+-------------+
You see that you're basically searching sequentially through all of the rows to find a match.
If you create an index on the toss
field, then your index will contain two values, each with roughly 250,000 entries.
create index foo on toss ( result );
Query OK, 500000 rows affected (2.48 sec)
Records: 500000 Duplicates: 0 Warnings: 0
select * from toss where result != 1 limit 123456, 1;
+--------+--------+
| id | result |
+--------+--------+
| 246700 | 0 |
+--------+--------+
1 row in set (0.25 sec)
explain select * from toss where result != 1 limit 123456, 1;
+----+-------------+-------+-------+---------------+------+---------+------+--------+-------------+
| id | select_type | table | type | possible_keys | key | key_len | ref | rows | Extra |
+----+-------------+-------+-------+---------------+------+---------+------+--------+-------------+
| 1 | SIMPLE | toss | range | foo | foo | 4 | NULL | 154565 | Using where |
+----+-------------+-------+-------+---------------+------+---------+------+--------+-------------+
Now you're searching fewer records, but the time to search increased from 0.06 to 0.25 seconds. Why? Because sequentially scanning an index is actually less efficient than sequentially scanning a table, for indexes with a large number of rows for a given key.
Let's look at the indexes on this table:
show index from toss;
+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| Table | Non_unique | Key_name | Seq_in_index | Column_name | Collation | Cardinality | Sub_part | Packed | Null | Index_type | Comment |
+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
| toss | 0 | PRIMARY | 1 | id | A | 500000 | NULL | NULL | | BTREE | |
| toss | 1 | foo | 1 | result | A | 2 | NULL | NULL | | BTREE | |
+-------+------------+----------+--------------+-------------+-----------+-------------+----------+--------+------+------------+---------+
The PRIMARY index is a good index: there are 500,000 rows, and there are 500,000 values. Arranged in a BTREE, you can quickly identify a single row based on the id.
The foo index is a bad index: there are 500,000 rows, but only 2 possible values. This is pretty much the worst possible case for a BTREE -- all of the overhead of searching the index, and still having to search through the results.