MySQL looking up more rows than needed (indexing issue) In our MySQL 5.5 database, we have following InnoDB table with 30M+ rows:

+----------------+-------------+-----------------+--------+
| participant_id | question_id | given_answer_id | status |
+----------------+-------------+-----------------+--------+
|       500      |      12     |        25       |    0   |
+----------------+-------------+-----------------+--------+


The combination participant_id + question_id + given_answer_id is unique.

At the moment we have following keys:

PRIMARY KEY (in this order)


participant_id
question_id
given_answer_id


INDEX KEY


question_id


For this table, we have two kinds of select queries in our application:

[...] WHERE participant_id = x AND question_id = y AND given_answer_id = z;


and

[...] WHERE question_id = x;


Normally, every participant_id has between 0 and &lt;100 rows with different question_ids. The other way around, every question_id can have unlimited (usually not more than 100 000) rows with different participant_ids. The first query is executed way more often than the second one.

When we execute following query, it shows us that 32096 rows where looked up:

EXPLAIN SELECT * FROM example WHERE question_id = 500;

+----+-------------+-----------+------+---------------+-------------+---------+-------+-------+-------+
| id | select_type | table     | type | possible_keys | key         | key_len | ref   | rows  | Extra |
+----+-------------+-----------+------+---------------+-------------+---------+-------+-------+-------+
| 1  | SIMPLE      | example   | ref  | question_id   | question_id | 8       | const | 32096 |       |
+----+-------------+-----------+------+---------------+-------------+---------+-------+-------+-------+


Whereas, when we execute the same query without EXPLAIN only 18732 rows are returned.

What indexes do we need on this table in order to prevent this overhead but still performing for both kinds of queries?



Here's is the code to create this table:


CREATE TABLE `example` (
    `participant_id` BIGINT(20) UNSIGNED NOT NULL,
    `question_id` BIGINT(20) UNSIGNED NOT NULL,
    `given_answer_id` BIGINT(20) UNSIGNED NOT NULL,
    `status` TINYINT(3) UNSIGNED NOT NULL DEFAULT '0',
    PRIMARY KEY (`participant_id`, `question_id`, `given_answer_id`),
    INDEX `question_id` (`question_id`)
)
ENGINE=InnoDB;
Your indexes are fine for the two types of queries you mentioned.
This query will be satisfied by traversing the clustered index on the primary key...
[...] WHERE participant_id = x AND question_id = y AND given_answer_id = z;

...and this one is satisfied by the index on 'question_id':
[...] WHERE question_id = x;

The output of EXPLAIN SELECT is not telling you what you think it is telling you, because the value shown in rows is an estimate of the number of rows the server will need to consider, not the actual rows it will examine.  For InnoDB these are based on index statistics.

rows
The rows column indicates the number of rows MySQL believes it must examine to execute the query.
For InnoDB tables, this number is an estimate, and may not always be exact.
— http://dev.mysql.com/doc/refman/5.5/en/explain-output.html#explain_rows

The optimizer gathers information about different possible query plans, and chooses the one with the lowest cost.  The information shown in EXPLAIN is the information the optimizer gathered about the plan it selected.
When type is ref and key is not NULL, this means that the name listed in the key column is the name of the index that the optimizer has chosen to use to find the desired rows, so your query plan looks exactly as it should.
Note, sometimes you will see Using index in the Extra column and a lot of people assume that this means an index is being used, or that no index is being used when that doesn't appear, but that's not correct, either.  Using index describes a special case called a &quot;covering index&quot; -- it does not indicate whether an index is being used to locate the rows of interest.
It's possible that running ANALYZE [LOCAL] TABLE would cause the numbers in rows shown by EXPLAIN to differ, but this is a simple query and selecting this index is an obvious choice for the optimizer to make, so ANALYZE TABLE is unlikely to make any actual difference in performance.
It is possible, however, that your overall performance might see some marginal improvement with an occasional OPTIMIZE [LOCAL] TABLE, because you are not inserting rows in primary key order (as would be the case with an auto_increment primary key)... but on large tables this can be time-consuming because it rebuilds a new copy of the table... but, again, I wouldn't expect any significant change.