InnoDB table has a special index called
the clustered index
where the data for the rows is stored. Typically, the clustered
index is synonymous with the
primary key. To get the
best performance from queries, inserts, and other database
operations, you must understand how InnoDB uses the clustered
index to optimize the most common lookup and DML operations for
When you define a
PRIMARY KEY on your
InnoDB uses it as the clustered
index. Define a primary key for each table that you create.
If there is no logical unique and non-null column or set of
columns, add a new
column, whose values are filled in automatically.
If you do not define a
PRIMARY KEY for
your table, MySQL locates the first
UNIQUE index where all the key columns
NOT NULL and
InnoDB uses it as the clustered index.
If the table has no
PRIMARY KEY or
InnoDB internally generates a hidden
clustered index on a synthetic column containing row ID
values. The rows are ordered by the ID that
InnoDB assigns to the rows in such a
table. The row ID is a 6-byte field that increases
monotonically as new rows are inserted. Thus, the rows
ordered by the row ID are physically in insertion order.
Accessing a row through the clustered index is fast because the
index search leads directly to the page with all the row data.
If a table is large, the clustered index architecture often
saves a disk I/O operation when compared to storage
organizations that store row data using a different page from
the index record. (For example,
one file for data rows and another for index records.)
All indexes other than the clustered index are known as
InnoDB, each record in a secondary index
contains the primary key columns for the row, as well as the
columns specified for the secondary index.
InnoDB uses this primary key value to search
for the row in the clustered index.
If the primary key is long, the secondary indexes use more space, so it is advantageous to have a short primary key.