Indexes are used to find rows with specific column values quickly. Without an index, MySQL must begin with the first row and then read through the entire table to find the relevant rows. The larger the table, the more this costs. If the table has an index for the columns in question, MySQL can quickly determine the position to seek to in the middle of the data file without having to look at all the data. This is much faster than reading every row sequentially.
Most MySQL indexes (
FULLTEXT) are stored in
B-trees. Exceptions: Indexes
on spatial data types use R-trees;
tables also support hash
InnoDB uses inverted lists
In general, indexes are used as described in the following
discussion. Characteristics specific to hash indexes (as used in
MEMORY tables) are described in
Section 8.3.9, “Comparison of B-Tree and Hash Indexes”.
MySQL uses indexes for these operations:
To find the rows matching a
To eliminate rows from consideration. If there is a choice between multiple indexes, MySQL normally uses the index that finds the smallest number of rows (the most selective index).
If the table has a multiple-column index, any leftmost prefix of the index can be used by the optimizer to look up rows. For example, if you have a three-column index on
(col1, col2, col3), you have indexed search capabilities on
(col1, col2), and
(col1, col2, col3). For more information, see Section 8.3.6, “Multiple-Column Indexes”.
To retrieve rows from other tables when performing joins. MySQL can use indexes on columns more efficiently if they are declared as the same type and size. In this context,
CHARare considered the same if they are declared as the same size. For example,
CHAR(10)are the same size, but
For comparisons between nonbinary string columns, both columns should use the same character set. For example, comparing a
utf8column with a
latin1column precludes use of an index.
Comparison of dissimilar columns (comparing a string column to a temporal or numeric column, for example) may prevent use of indexes if values cannot be compared directly without conversion. For a given value such as
1in the numeric column, it might compare equal to any number of values in the string column such as
'01.e1'. This rules out use of any indexes for the string column.
To find the
MAX()value for a specific indexed column
key_col. This is optimized by a preprocessor that checks whether you are using
WHEREon all key parts that occur before
key_colin the index. In this case, MySQL does a single key lookup for each
MAX()expression and replaces it with a constant. If all expressions are replaced with constants, the query returns at once. For example:
SELECT MIN(key_part2),MAX(key_part2) FROM tbl_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 index (for example,
ORDER BY). If all key parts are followed by
DESC, the key is read in reverse order. (Or, if the index is a descending index, the key is read in forward order.) See Section 184.108.40.206, “ORDER BY Optimization”, Section 220.127.116.11, “GROUP BY Optimization”, and Section 8.3.13, “Descending Indexes”.
In some cases, a query can be optimized to retrieve values without consulting the data rows. (An index that provides all the necessary results for a query is called a covering index.) If a query uses from a table only columns that are included in some index, the selected values can be retrieved from the index tree for greater speed:
SELECT key_part3 FROM tbl_name WHERE key_part1=1
Indexes are less important for queries on small tables, or big tables where report queries process most or all of the rows. When a query needs to access most of the rows, reading sequentially is faster than working through an index. Sequential reads minimize disk seeks, even if not all the rows are needed for the query. See Section 18.104.22.168, “Avoiding Full Table Scans” for details.