Indexes are used to find rows with specific column values fast. Without an index MySQL has to start with the first record and then read through the whole table to find the relevant rows. The bigger the table, the more this costs. If the table has an index for the columns in question, MySQL can quickly get a position to seek to in the middle of the datafile without having to look at all the data. If a table has 1000 rows, this is at least 100 times faster than reading sequentially. Note that if you need to access almost all 1000 rows, it is faster to read sequentially, because that minimises disk seeks.
All MySQL indexes (PRIMARY KEY, UNIQUE, and INDEX) are stored in B-trees. Strings are automatically prefix- and end-space compressed. See CREATE INDEX.
Indexes are used in the following ways:
To quickly find the rows that match a WHERE clause.
To retrieve rows from other tables when performing joins.
To find the MAX() or MIN() value for a specific indexed column. This is optimized by a preprocessor that checks if you are using WHERE key_part_# = constant on all key parts < N. In this case MySQL will do a single key lookup and replace the MIN() expression with a constant. If all expressions are replaced with constants, the query will return at once:
SELECT MIN(key_part2),MAX(key_part2) FROM table_name where key_part1=10
To sort or group a table if the sorting or grouping is done on a leftmost prefix of a usable key (for example, ORDER BY key_part_1,key_part_2 ). The key is read in reverse order if all key parts are followed by DESC. See ORDER BY optimisation.
In some cases a query can be optimized to retrieve values without consulting the datafile. If all used columns for some table are numeric and form a leftmost prefix for some key, the values may be retrieved from the index tree for greater speed:
SELECT key_part3 FROM table_name WHERE key_part1=1
Suppose you issue the following SELECT statement:
mysql> SELECT * FROM tbl_name WHERE col1=val1 AND col2=val2;
If a multiple-column index exists on col1 and col2, the appropriate rows can be fetched directly. If separate single-column indexes exist on col1 and col2, the optimizer tries to find the most restrictive index by deciding which index will find fewer rows and using that index to fetch the rows.
If the table has a multiple-column index, any leftmost prefix of the index can be used by the optimizer to find rows. For example, if you have a three-column index on (col1, col2, col3), you have indexed search capabilities on (col1), (col1, col2), and (col1, col2, col3).
MySQL can't use a partial index if the columns don't form a leftmost prefix of the index. Suppose you have the SELECT statements shown here:
mysql> SELECT * FROM tbl_name WHERE col1=val1; mysql> SELECT * FROM tbl_name WHERE col2=val2; mysql> SELECT * FROM tbl_name WHERE col2=val2 AND col3=val3;
If an index exists on (col1, col2, col3), only the first of the preceding queries uses the index. The second and third queries do involve indexed columns, but (col2) and (col2, col3) are not leftmost prefixes of (col1, col2, col3).
MySQL also uses indexes for LIKE comparisons if the argument to LIKE is a constant string that doesn't start with a wildcard character. For example, the following SELECT statements use indexes:
mysql> SELECT * FROM tbl_name WHERE key_col LIKE "Patrick%"; mysql> SELECT * FROM tbl_name WHERE key_col LIKE "Pat%_ck%";
In the first statement, only rows with "Patrick" <= key_col < "Patricl" are considered. In the second statement, only rows with "Pat" <= key_col < "Pau" are considered.
The following SELECT statements will not use indexes:
mysql> SELECT * FROM tbl_name WHERE key_col LIKE "%Patrick%"; mysql> SELECT * FROM tbl_name WHERE key_col LIKE other_col;
In the first statement, the LIKE value begins with a wildcard character. In the second statement, the LIKE value is not a constant.
MySQL 4.0 does another optimization on LIKE. If you use ... LIKE "%string%" and string is longer than 3 characters, MySQL will use the Turbo Boyer-Moore algorithm to initialize the pattern for the string and then use this pattern to perform the search quicker.
Searching using column_name IS NULL will use indexes if column_name is an index.
MySQL normally uses the index that finds the smallest number of rows. An index is used for columns that you compare with the following operators: =, >, >=, <, <=, BETWEEN, or a LIKE with a pattern that begins with a non-wildcard prefix like 'something%'.
Any index that doesn't span all AND levels in the WHERE clause is not used to optimize the query. In other words: To be able to use an index, a prefix of the index must be used in every AND group.
The following WHERE clauses use indexes:
... WHERE index_part1=1 AND index_part2=2 AND other_column=3 ... WHERE index=1 OR A=10 AND index=2 /* index = 1 OR index = 2 */ ... WHERE index_part1='hello' AND index_part_3=5 /* optimized like "index_part1='hello'" */ ... WHERE index1=1 AND index2=2 OR index1=3 AND index3=3; /* Can use index on index1 but not on index2 or index 3 */
These WHERE clauses do not use indexes:
... WHERE index_part2=1 AND index_part3=2 /* index_part_1 is not used */ ... WHERE index=1 OR A=10 /* Index is not used in both AND parts */ ... WHERE index_part1=1 OR index_part2=10 /* No index spans all rows */
Note that sometime MySQL will not use an index, even if one is available. One instance of this is when use of the index would require MySQL to access more than 30% of the rows in the table. (In this case a table scan is probably much faster, as it will require many fewer seeks.) However, if such a query uses LIMIT to only retrieve part of the rows, MySQL will use an index anyway, as it can much more quickly find the few rows to return in the result.