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14.2.13. InnoDB Table and Index Structures

MySQL stores its data dictionary information for tables in .frm files in database directories. This is true for all MySQL storage engines. But every InnoDB table also has its own entry in the InnoDB internal data dictionary inside the tablespace. When MySQL drops a table or a database, it has to delete both an .frm file or files, and the corresponding entries inside the InnoDB data dictionary. This is the reason why you cannot move InnoDB tables between databases simply by moving the .frm files.

Every InnoDB table has a special index called the clustered index where the data for the rows is stored. If you define a PRIMARY KEY on your table, the index of the primary key is the clustered index.

If you do not define a PRIMARY KEY for your table, MySQL picks the first UNIQUE index that has only NOT NULL columns as the primary key and InnoDB uses it as the clustered index. If there is no such index in the table, InnoDB internally generates a clustered index where the rows are ordered by the row 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 row data is on the same page where the index search leads. If a table is large, the clustered index architecture often saves a disk I/O when compared to the traditional solution. (In many database systems, data storage uses a different page from the index record.)

In InnoDB, the records in non-clustered indexes (also called secondary indexes) contain the primary key value for the row. InnoDB uses this primary key value to search for the row from the clustered index. Note that if the primary key is long, the secondary indexes use more space.

InnoDB compares CHAR and VARCHAR strings of different lengths such that the remaining length in the shorter string is treated as if padded with spaces.


 
 
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