MySQL Performance – Why Integer Search String is Slower on Char Field?

MySQL

I'm using MySQL version 5.1 at my workplace.

I have a column my_cloumn char(10) in my_table.

I recently found that a process was taking longer, and the SQL that was responsible for this was below:

SELECT * FROM my_table WHERE my_column = 12345, which can take some 3 minutes running.

Now, editing and using quotes on the search string this way

SELECT * FROM my_table WHERE my_column = '12345'

retrieves the record in a matter of micro seconds.

I do not have access (direct or indirect) to have the code changed to pass the queries with the quotes (by either direct sql or specifying the correct data type in PDO), and currently may not be able to change the column whilst users are using the database. What I need most is how to explain the difference above.

Why is this faster with quotes and not without?

Best Answer

The quotes define the expression as a string, whereas without the single quote it is evaluated as a number. This means that MySQL is forced to perform a Type Conversion to convert the number to a CHAR to do a proper comparison.

As the doc above says,

For comparisons of a string column with a number, MySQL cannot use an index on the column to look up the value quickly. If str_col is an indexed string column, the index cannot be used when performing the lookup...

However, the inverse of that is not true and while the index can be used, using a string as a value causes a poor execution plan (as illustrated by jkavalik's sqlfiddle) where using where is used instead of the faster using index condition. The main difference between the two is that the former requires a row lookup and the latter can get the data directly from the index.

You should definitely modify the column data type (assuming it truly is only meant to contain numbers) to the appropriate data type ASAP, but make sure that no queries are actually using single quotes, otherwise you'll be back where you started.

FACTOR #1

For any given index, what is the key population? In other words, what is the cardinality (distinct count) of all tuples recorded in the index?

FACTOR #2

What storage engine are you using? Are all needed columns accessible from an index?

WHAT'S NEXT ???

Let's take a simple example: a table that holds two values (Male and Female)

Let create such a table with a test for index usage

USE test
DROP TABLE IF EXISTS mf;
CREATE TABLE mf
(
    id int not null auto_increment,
    gender char(1),
    primary key (id),
    key (gender)
) ENGINE=InnODB;
INSERT INTO mf (gender) VALUES
('M'),('M'),('M'),('M'),('M'),('M'),('M'),('M'),
('M'),('M'),('M'),('M'),('F'),('F'),('M'),('M'),
('M'),('M'),('M'),('M'),('M'),('M'),('M'),('M'),
('M'),('M'),('M'),('M'),('M'),('M'),('M'),('M'),
('F'),('M'),('M'),('M'),('M'),('M'),('M'),('M');
ANALYZE TABLE mf;
EXPLAIN SELECT gender FROM mf WHERE gender='F';
EXPLAIN SELECT gender FROM mf WHERE gender='M';
EXPLAIN SELECT id FROM mf WHERE gender='F';
EXPLAIN SELECT id FROM mf WHERE gender='M';

TEST InnoDB

mysql> USE test
Database changed
mysql> DROP TABLE IF EXISTS mf;
Query OK, 0 rows affected (0.00 sec)

mysql> CREATE TABLE mf
    -> (
    ->     id int not null auto_increment,
    ->     gender char(1),
    ->     primary key (id),
    ->     key (gender)
    -> ) ENGINE=InnoDB;
Query OK, 0 rows affected (0.07 sec)

mysql> INSERT INTO mf (gender) VALUES
    -> ('M'),('M'),('M'),('M'),('M'),('M'),('M'),('M'),
    -> ('M'),('M'),('M'),('M'),('F'),('F'),('M'),('M'),
    -> ('M'),('M'),('M'),('M'),('M'),('M'),('M'),('M'),
    -> ('M'),('M'),('M'),('M'),('M'),('M'),('M'),('M'),
    -> ('F'),('M'),('M'),('M'),('M'),('M'),('M'),('M');
Query OK, 40 rows affected (0.06 sec)
Records: 40  Duplicates: 0  Warnings: 0

mysql> ANALYZE TABLE mf;
+---------+---------+----------+----------+
| Table   | Op      | Msg_type | Msg_text |
+---------+---------+----------+----------+
| test.mf | analyze | status   | OK       |
+---------+---------+----------+----------+
1 row in set (0.00 sec)

mysql> EXPLAIN SELECT gender FROM mf WHERE gender='F';
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
| id | select_type | table | type | possible_keys | key    | key_len | ref   | rows | Extra                    |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
|  1 | SIMPLE      | mf    | ref  | gender        | gender | 2       | const |    3 | Using where; Using index |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
1 row in set (0.00 sec)

mysql> EXPLAIN SELECT gender FROM mf WHERE gender='M';
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
| id | select_type | table | type | possible_keys | key    | key_len | ref   | rows | Extra                    |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
|  1 | SIMPLE      | mf    | ref  | gender        | gender | 2       | const |   37 | Using where; Using index |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
1 row in set (0.00 sec)

mysql> EXPLAIN SELECT id FROM mf WHERE gender='F';
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
| id | select_type | table | type | possible_keys | key    | key_len | ref   | rows | Extra                    |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
|  1 | SIMPLE      | mf    | ref  | gender        | gender | 2       | const |    3 | Using where; Using index |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
1 row in set (0.00 sec)

mysql> EXPLAIN SELECT id FROM mf WHERE gender='M';
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
| id | select_type | table | type | possible_keys | key    | key_len | ref   | rows | Extra                    |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
|  1 | SIMPLE      | mf    | ref  | gender        | gender | 2       | const |   37 | Using where; Using index |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
1 row in set (0.00 sec)

mysql>

TEST MyISAM

mysql> USE test
Database changed
mysql> DROP TABLE IF EXISTS mf;
Query OK, 0 rows affected (0.00 sec)

mysql> CREATE TABLE mf
    -> (
    ->     id int not null auto_increment,
    ->     gender char(1),
    ->     primary key (id),
    ->     key (gender)
    -> ) ENGINE=MyISAM;
Query OK, 0 rows affected (0.05 sec)

mysql> INSERT INTO mf (gender) VALUES
    -> ('M'),('M'),('M'),('M'),('M'),('M'),('M'),('M'),
    -> ('M'),('M'),('M'),('M'),('F'),('F'),('M'),('M'),
    -> ('M'),('M'),('M'),('M'),('M'),('M'),('M'),('M'),
    -> ('M'),('M'),('M'),('M'),('M'),('M'),('M'),('M'),
    -> ('F'),('M'),('M'),('M'),('M'),('M'),('M'),('M');
Query OK, 40 rows affected (0.00 sec)
Records: 40  Duplicates: 0  Warnings: 0

mysql> ANALYZE TABLE mf;
+---------+---------+----------+----------+
| Table   | Op      | Msg_type | Msg_text |
+---------+---------+----------+----------+
| test.mf | analyze | status   | OK       |
+---------+---------+----------+----------+
1 row in set (0.00 sec)

mysql> EXPLAIN SELECT gender FROM mf WHERE gender='F';
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
| id | select_type | table | type | possible_keys | key    | key_len | ref   | rows | Extra                    |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
|  1 | SIMPLE      | mf    | ref  | gender        | gender | 2       | const |    3 | Using where; Using index |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
1 row in set (0.00 sec)

mysql> EXPLAIN SELECT gender FROM mf WHERE gender='M';
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
| id | select_type | table | type | possible_keys | key    | key_len | ref   | rows | Extra                    |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
|  1 | SIMPLE      | mf    | ref  | gender        | gender | 2       | const |   36 | Using where; Using index |
+----+-------------+-------+------+---------------+--------+---------+-------+------+--------------------------+
1 row in set (0.00 sec)

mysql> EXPLAIN SELECT id FROM mf WHERE gender='F';
+----+-------------+-------+------+---------------+--------+---------+-------+------+-------------+
| id | select_type | table | type | possible_keys | key    | key_len | ref   | rows | Extra       |
+----+-------------+-------+------+---------------+--------+---------+-------+------+-------------+
|  1 | SIMPLE      | mf    | ref  | gender        | gender | 2       | const |    3 | Using where |
+----+-------------+-------+------+---------------+--------+---------+-------+------+-------------+
1 row in set (0.00 sec)

mysql> EXPLAIN SELECT id FROM mf WHERE gender='M';
+----+-------------+-------+------+---------------+------+---------+------+------+-------------+
| id | select_type | table | type | possible_keys | key  | key_len | ref  | rows | Extra       |
+----+-------------+-------+------+---------------+------+---------+------+------+-------------+
|  1 | SIMPLE      | mf    | ALL  | gender        | NULL | NULL    | NULL |   40 | Using where |
+----+-------------+-------+------+---------------+------+---------+------+------+-------------+
1 row in set (0.00 sec)

mysql>

Analysis for InnoDB

When the data was loaded as InnoDB, please note that all four EXPLAIN plans used the gender index. The third and fourth EXPLAIN plans used the gender index even though the requested data was id. Why? Because id is in the PRIMARY KEY and all secondary indexes have reference pointers back to the PRIMARY KEY (via the gen_clust_index).

Analysis for MyISAM

When the data was loaded as MyISAM, please note that the first three EXPLAIN plans used the gender index. In the fourth EXPLAIN plan, the Query Optimizer decided not to use an index at all. It opted for a full table scan instead. Why?

Regardless of DBMS, Query Optimizers operate on a very simple rule-of-thumb: If an index is being screened as a candidate to be used for performing the lookup and Query Optimizer computes that it must lookup more than 5% of the total number of rows in the table:

a full index scan is done if all needed columns for retrieval are in the selected index
a full table scan otherwise

CONCLUSION

If you do not have proper covering indexes, or if the key population for any given tuple is more than 5% of the table, six things must happen:

Come to the realization that you must profile the queries
Find all WHERE, GROUP BY, and ORDER BY` clauses from those Queries
Formulate indexes in this order
- WHERE clause columns with static values
- GROUP BY columns
- ORDER BY columns
Avoid Full Table Scans (Queries lacking a sensible WHERE clause)
Avoid Bad Key Populations (or at least cache those Bad Key Populations)
Decide on the best MySQL Storage Engine (InnoDB or MyISAM) for the Tables

I have written about this 5% rule of thumb in the past:

May 07, 2012 : MySQL EXPLAIN doesn't show 'use index' for FULLTEXT
Mar 22, 2012 : Why does MySQL choose this execution plan?
Mar 09, 2012 : index not being used
Jan 18, 2012 : MySQL status variable Handler_read_rnd_next is growing a lot
Dec 27, 2011 : MySQL - fastest way to ALTER TABLE for InnoDB
Jul 29, 2011 : MySQL Query Optimization : Indexing and Pagination
Jul 12, 2011 : MySQL very slow query when changing one WHERE field despite no index/key

UPDATE 2012-11-14 13:05 EDT

I took a look back at your question and at the original SO post. Then, I thought about my Analysis for InnoDB I mentioned before. It coincides with the person table. Why?

For both tables mf and person

Storage Engine is InnoDB
Primary Key is id
Table access is by secondary index
If table was MyISAM, we would see a completely different EXPLAIN plan

Now, look at the query from the SO question : select * from person order by age\G. Since there is no WHERE clause, you explicitly demanded a full table scan. The default sort order of the table would be by id (PRIMARY KEY) because of its auto_increment and the gen_clust_index (aka Clustered Index) is ordered by internal rowid. When you ordered by the index, keep in mind that InnoDB secondary indexes have the rowid attached to each index entry. This produces the internal need for full row access each time.

Setting up ORDER BY on an InnoDB table can be a rather daunting task if you ignore these facts about how InnoDB indexes are organized.

Going back to that SO query, since you explicitly demanded a full table scan, IMHO the MySQL Query Optimizer did the correct thing (or at least, chose the path of least resistance). When it comes to InnoDB and the SO query, it is far easier to perform a full table scan and then some filesort rather than doing a full index scan and a row lookup via the gen_clust_index for each secondary index entry.

I am not an advocate of using Index Hints because it ignores the EXPLAIN plan. Notwithstanding, if you really know your data better than InnoDB, you will have to resort to Index Hints, especially with queries that have no WHERE clause.

UPDATE 2012-11-14 14:21 EDT

According to the book Understanding MySQL Internals

enter image description here

Page 202 Paragraph 7 says the following:

The data is stored in a special structure called a clustered index, which is a B-tree with the primary key acting as the key value, and the actual record (rather than a pointer) in the data part. Thus, each InnoDB table must have a primary key. If one is not supplied, a special row ID column not normally visible to the user is added to act as a primary key. A secondary key will store the value of the primary key that identifies the record. The B-tree code can be found in innobase/btr/btr0btr.c.

This is why I stated earlier : it is far easier to perform a full table scan and then some filesort rather than doing a full index scan and a row lookup via the gen_clust_index for each secondary index entry. InnoDB is going to do a double index lookup every time. That sounds kind of brutal, but that's just the facts. Again, take into consideration the lack of WHERE clause. This, in itself, is the hint to the MySQL Query Optimizer to do a full table scan.

MySQL Performance – Why Simple SELECTs on InnoDB Are 100x Slower Than on MyISAM

YOUR QUERY

SELECT post.postid, post.attach FROM newbb_innopost AS post WHERE post.threadid = 51506;

At first glance, that query should only touches 1.1597% (62510 out of 5390146) of the table. It should be fast given the key distribution of threadid 51506.

REALITY CHECK

No matter which version of MySQL (Oracle, Percona, MariaDB) you use, none of them can fight to one enemy they all have in common : The InnoDB Architecture.

InnoDB Architecture

CLUSTERED INDEX

Please keep in mind that the each threadid entry has a primary key attached. This means that when you read from the index, it must do a primary key lookup within the ClusteredIndex (internally named gen_clust_index). In the ClusteredIndex, each InnoDB page contains both data and PRIMARY KEY index info. See my post Best of MyISAM and InnoDB for more info.

REDUNDANT INDEXES

You have a lot of clutter in the table because some indexes have the same leading columns. MySQL and InnoDB has to navigate through the index clutter to get to needed BTREE nodes. You should reduced that clutter by running the following:

ALTER TABLE newbb_innopost
    DROP INDEX threadid,
    DROP INDEX threadid_2,
    DROP INDEX threadid_visible_dateline,
    ADD INDEX threadid_visible_dateline_index (`threadid`,`visible`,`dateline`,`userid`)
;

Why strip down these indexes ?

The first three indexes start with threadid
threadid_2 and threadid_visible_dateline start with the same three columns
threadid_visible_dateline does not need postid since it's the PRIMARY KEY and it's embedded

BUFFER CACHING

The InnoDB Buffer Pool caches data and index pages. MyISAM only caches index pages.

Just in this area alone, MyISAM does not waste time caching data. That's because it's not designed to cache data. InnoDB caches every data page and index page (and its grandmother) it touches. If your InnoDB Buffer Pool is too small, you could be caching pages, invalidating pages, and removing pages all in one query.

TABLE LAYOUT

You could shave of some space from the row by considering importthreadid and importpostid. You have them as BIGINTs. They take up 16 bytes in the ClusteredIndex per row.

You should run this

SELECT importthreadid,importpostid FROM newbb_innopost PROCEDURE ANALYSE();

This will recommend what data types these columns should be for the given dataset.

CONCLUSION

MyISAM has a lot less to contend with than InnoDB, especially in the area of caching.

While you revealed the amount of RAM (32GB) and the version of MySQL (Server version: 10.0.12-MariaDB-1~trusty-wsrep-log mariadb.org binary distribution, wsrep_25.10.r4002), there are still other pieces to this puzzle you have not revealed

The InnoDB settings
The Number of Cores
Other settings from my.cnf

If you can add these things to the question, I can further elaborate.

UPDATE 2014-08-28 11:27 EDT

You should increase threading

innodb_read_io_threads = 64
innodb_write_io_threads = 16
innodb_log_buffer_size = 256M

I would consider disabling the query cache (See my recent post Why query_cache_type is disabled by default start from MySQL 5.6?)

query_cache_size = 0

I would preserve the Buffer Pool

innodb_buffer_pool_dump_at_shutdown=1
innodb_buffer_pool_load_at_startup=1

Increase purge threads (if you do DML on multiple tables)

innodb_purge_threads = 4

Best Answer

Related Solutions

Must an Index Cover All Selected Columns for ORDER BY in MySQL?

FACTOR #1

FACTOR #2

WHAT'S NEXT ???

TEST InnoDB

TEST MyISAM

Analysis for InnoDB

Analysis for MyISAM

CONCLUSION

UPDATE 2012-11-14 13:05 EDT

UPDATE 2012-11-14 14:21 EDT

MySQL Performance – Why Simple SELECTs on InnoDB Are 100x Slower Than on MyISAM

YOUR QUERY

REALITY CHECK

CLUSTERED INDEX

REDUNDANT INDEXES

BUFFER CACHING

TABLE LAYOUT

CONCLUSION

UPDATE 2014-08-28 11:27 EDT

GIVE IT A TRY !!!

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