If you have MyISAM tables that you want to convert to InnoDB for better reliability and scalability, review the following guidelines and tips before making the conversion.

Reduce Memory Usage for MyISAM, Increase Memory Usage for InnoDB

As you transition away from MyISAM tables, lower the value of the key_buffer_size configuration option to free memory no longer needed for caching results. Increase the value of the innodb_buffer_pool_size configuration option, which performs a similar role of allocating cache memory for InnoDB tables. The InnoDB buffer pool caches both table data and index data, so it does double duty in speeding up lookups for queries and keeping query results in memory for reuse. For guidance regarding buffer pool size configuration, see Section 8.12.4.1, “How MySQL Uses Memory”.

On a busy server, run benchmarks with the Query Cache turned off. The InnoDB buffer pool provides similar benefits, so the Query Cache might be tying up memory unnecessarily.

Watch Out for Too-Long Or Too-Short Transactions

Because MyISAM tables do not support transactions, you might not have paid much attention to the autocommit configuration option and the COMMIT and ROLLBACK statements. These keywords are important to allow multiple sessions to read and write InnoDB tables concurrently, providing substantial scalability benefits in write-heavy workloads.

While a transaction is open, the system keeps a snapshot of the data as seen at the beginning of the transaction, which can cause substantial overhead if the system inserts, updates, and deletes millions of rows while a stray transaction keeps running. Thus, take care to avoid transactions that run for too long:

The preceding tips save memory and disk space that can be wasted during too-long transactions. When transactions are shorter than they should be, the problem is excessive I/O. With each COMMIT, MySQL makes sure each change is safely recorded to disk, which involves some I/O.

Don't Worry Too Much About Deadlocks

You might see warning messages referring to “deadlocks” in the MySQL error log, or the output of SHOW ENGINE INNODB STATUS. Despite the scary-sounding name, a deadlock is not a serious issue for InnoDB tables, and often does not require any corrective action. When two transactions start modifying multiple tables, accessing the tables in a different order, they can reach a state where each transaction is waiting for the other and neither can proceed. MySQL immediately detects this condition and cancels (rolls back) the “smaller” transaction, allowing the other to proceed.

Your applications do need error-handling logic to restart a transaction that is forcibly cancelled like this. When you re-issue the same SQL statements as before, the original timing issue no longer applies: either the other transaction has already finished and yours can proceed, or the other transaction is still in progress and your transaction waits until it finishes.

If deadlock warnings occur constantly, you might review the application code to reorder the SQL operations in a consistent way, or to shorten the transactions.

For more information, see Section 14.8.5, “Deadlocks in InnoDB”.

Plan the Storage Layout

To get the best performance from InnoDB tables, you can adjust a number of parameters related to storage layout.

When you convert MyISAM tables that are large, frequently accessed, and hold vital data, investigate and consider the innodb_file_per_table and innodb_file_format configuration options, and the ROW_FORMAT and KEY_BLOCK_SIZE clauses of the CREATE TABLE statement.

During your initial experiments, the most important setting is innodb_file_per_table. When this setting is enabled, new InnoDB tables are implicitly created in file-per-table tablespaces. In contrast with the InnoDB system tablespace, file-per-table tablespaces allow disk space to be reclaimed by the operating system when a table is truncated or dropped. File-per-table tablespaces also support the Barracuda file format and associated features such as table compression and off-page storage for long variable-length columns. For more information, see Section 14.10.4, “InnoDB File-Per-Table Tablespaces”.

Converting an Existing Table

To convert a non-InnoDB table to use InnoDB use ALTER TABLE:

ALTER TABLE table_name ENGINE=InnoDB;

Cloning the Structure of a Table

You might make an InnoDB table that is a clone of a MyISAM table, rather than doing the ALTER TABLE conversion, to test the old and new table side-by-side before switching.

Create an empty InnoDB table with identical column and index definitions. Use show create table table_name\G to see the full CREATE TABLE statement to use. Change the ENGINE clause to ENGINE=INNODB.

Transferring Existing Data

To transfer a large volume of data into an empty InnoDB table created as shown in the previous section, insert the rows with INSERT INTO innodb_table SELECT * FROM myisam_table ORDER BY primary_key_columns.

You can also create the indexes for the InnoDB table after inserting the data. Historically, creating new secondary indexes was a slow operation for InnoDB, but now you can create the indexes after the data is loaded with relatively little overhead from the index creation step.

If you have UNIQUE constraints on secondary keys, you can speed up a table import by turning off the uniqueness checks temporarily during the import operation:

SET unique_checks=0;
... import operation ...
SET unique_checks=1;

For big tables, this saves disk I/O because InnoDB can use its change buffer to write secondary index records as a batch. Be certain that the data contains no duplicate keys. unique_checks permits but does not require storage engines to ignore duplicate keys.

To get better control over the insertion process, you might insert big tables in pieces:

INSERT INTO newtable SELECT * FROM oldtable
   WHERE yourkey > something AND yourkey <= somethingelse;

After all records have been inserted, you can rename the tables.

During the conversion of big tables, increase the size of the InnoDB buffer pool to reduce disk I/O, to a maximum of 80% of physical memory. You can also increase the sizes of the InnoDB log files.

Storage Requirements

If you intend to make several temporary copies of your data in InnoDB tables during the conversion process, it is recommended that you create the tables in file-per-table tablespaces so that you can reclaim the disk space when you drop the tables. As mentioned previously, when the innodb_file_per_table option is enabled, newly created InnoDB tables are implicitly created in file-per-table tablespaces.

Whether you convert the MyISAM table directly or create a cloned InnoDB table, make sure that you have sufficient disk space to hold both the old and new tables during the process. InnoDB tables require more disk space than MyISAM tables. If an ALTER TABLE operation runs out of space, it starts a rollback, and that can take hours if it is disk-bound. For inserts, InnoDB uses the insert buffer to merge secondary index records to indexes in batches. That saves a lot of disk I/O. For rollback, no such mechanism is used, and the rollback can take 30 times longer than the insertion.

In the case of a runaway rollback, if you do not have valuable data in your database, it may be advisable to kill the database process rather than wait for millions of disk I/O operations to complete. For the complete procedure, see Section 14.23.2, “Forcing InnoDB Recovery”.

Carefully Choose a PRIMARY KEY for Each Table

The PRIMARY KEY clause is a critical factor affecting the performance of MySQL queries and the space usage for tables and indexes. Perhaps you have phoned a financial institution where you are asked for an account number. If you do not have the number, you are asked for a dozen different pieces of information to “uniquely identify” yourself. The primary key is like that unique account number that lets you get straight down to business when querying or modifying the information in a table. Every row in the table must have a primary key value, and no two rows can have the same primary key value.

Here are guidelines for the primary key, followed by more detailed explanations.

Consider adding a primary key to any table that does not already have one. Use the smallest practical numeric type based on the maximum projected size of the table. This can make each row slightly more compact, which can yield substantial space savings for large tables. The space savings are multiplied if the table has any secondary indexes, because the primary key value is repeated in each secondary index entry. In addition to reducing data size on disk, a small primary key also lets more data fit into the buffer pool, speeding up all kinds of operations and improving concurrency.

If the table already has a primary key on some longer column, such as a VARCHAR, consider adding a new unsigned AUTO_INCREMENT column and switching the primary key to that, even if that column is not referenced in queries. This design change can produce substantial space savings in the secondary indexes. You can designate the former primary key columns as UNIQUE NOT NULL to enforce the same constraints as the PRIMARY KEY clause, that is, to prevent duplicate or null values across all those columns.

If you spread related information across multiple tables, typically each table uses the same column for its primary key. For example, a personnel database might have several tables, each with a primary key of employee number. A sales database might have some tables with a primary key of customer number, and other tables with a primary key of order number. Because lookups using the primary key are very fast, you can construct efficient join queries for such tables.

If you leave the PRIMARY KEY clause out entirely, MySQL creates an invisible one for you. It is a 6-byte value that might be longer than you need, thus wasting space. Because it is hidden, you cannot refer to it in queries.

Application Performance Considerations

The extra reliability and scalability features of InnoDB do require more disk storage than equivalent MyISAM tables. You might change the column and index definitions slightly, for better space utilization, reduced I/O and memory consumption when processing result sets, and better query optimization plans making efficient use of index lookups.

If you do set up a numeric ID column for the primary key, use that value to cross-reference with related values in any other tables, particularly for join queries. For example, rather than accepting a country name as input and doing queries searching for the same name, do one lookup to determine the country ID, then do other queries (or a single join query) to look up relevant information across several tables. Rather than storing a customer or catalog item number as a string of digits, potentially using up several bytes, convert it to a numeric ID for storing and querying. A 4-byte unsigned INT column can index over 4 billion items (with the US meaning of billion: 1000 million). For the ranges of the different integer types, see Section 11.2.1, “Integer Types (Exact Value) - INTEGER, INT, SMALLINT, TINYINT, MEDIUMINT, BIGINT”.

Understand Files Associated with InnoDB Tables

InnoDB files require more care and planning than MyISAM files do.