MySQL 5.7 Reference Manual Including MySQL NDB Cluster 7.5 and NDB Cluster 7.6
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 (PRIMARY KEY
,
UNIQUE
, INDEX
, and
FULLTEXT
) are stored in
B-trees. Exceptions: Indexes
on spatial data types use R-trees; MEMORY
tables also support hash
indexes; InnoDB
uses inverted lists
for FULLTEXT
indexes.
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 8.3.8, “Comparison of B-Tree and Hash Indexes”.
MySQL uses indexes for these operations:
To find the rows matching a WHERE
clause
quickly.
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)
,
(col1, col2)
, and (col1, col2,
col3)
. For more information, see
Section 8.3.5, “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,
VARCHAR
and
CHAR
are considered the same
if they are declared as the same size. For example,
VARCHAR(10)
and
CHAR(10)
are the same size, but
VARCHAR(10)
and
CHAR(15)
are not.
For comparisons between nonbinary string columns, both
columns should use the same character set. For example,
comparing a utf8
column with a
latin1
column 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 1
in the numeric column, it might compare equal to any number
of values in the string column such as
'1'
, ' 1'
,
'00001'
, or '01.e1'
.
This rules out use of any indexes for the string column.
To find the MIN()
or
MAX()
value for a specific
indexed column key_col
. This is
optimized by a preprocessor that checks whether you are
using WHERE
on all key
parts that occur before key_part_N
=
constant
key_col
in the index. In this case, MySQL does a single key lookup
for each MIN()
or
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
) FROMtbl_name
WHEREkey_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 key_part1
,
key_part2
DESC
, the key is
read in reverse order. See
Section 8.2.1.14, “ORDER BY Optimization”, and
Section 8.2.1.15, “GROUP BY Optimization”.
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:
SELECTkey_part3
FROMtbl_name
WHEREkey_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 8.2.1.20, “Avoiding Full Table Scans” for details.