If your application makes several database requests to perform related updates, combining the statements into a stored routine can help performance. Similarly, if your application computes a single result based on several column values or large volumes of data, combining the computation into a UDF (user-defined function) can help performance. The resulting fast database operations are then available to be reused by other queries, applications, and even code written in different programming languages. See Section 20.2, “Using Stored Routines” and Adding Functions to MySQL for more information.

To fix any compression issues that occur with ARCHIVE tables, use OPTIMIZE TABLE. See Section 15.5, “The ARCHIVE Storage Engine”.

If possible, classify reports as “live” or as “statistical”, where data needed for statistical reports is created only from summary tables that are generated periodically from the live data.

If you have data that does not conform well to a rows-and-columns table structure, you can pack and store data into a BLOB column. In this case, you must provide code in your application to pack and unpack information, but this might save I/O operations to read and write the sets of related values.

With Web servers, store images and other binary assets as files, with the path name stored in the database rather than the file itself. Most Web servers are better at caching files than database contents, so using files is generally faster. (Although you must handle backups and storage issues yourself in this case.)

If you need really high speed, look at the low-level MySQL interfaces. For example, by accessing the MySQL InnoDB or MyISAM storage engine directly, you could get a substantial speed increase compared to using the SQL interface.

Similarly, for databases using the NDBCLUSTER storage engine, you may wish to investigate possible use of the NDB API (see MySQL NDB Cluster API Developer Guide).

Replication can provide a performance benefit for some operations. You can distribute client retrievals among replicas to split up the load. To avoid slowing down the source while making backups, you can make backups using a replica. See Chapter 17, Replication.