There are many good reasons for partitioning the data in your database into smaller, separate tables. The reasons include: improved performance, reduced backup windows, better data protection and support for special needs of a particular set of users with their own data set.
Partitioning lets you work with a smaller group of records or locate a data set in an appropriate location or on the best server to suit your needs. Although you essentially partition your data in memory anytime you create a view, that set of records competes for I/O with the larger set of records. So although you can achieve a greater degree of normalization by minimizing the number of tables, there are advantages to be had when you de-normalize your tables.
Most database designers learn quickly that heavily used static data sets are candidates for isolation in a lookup file. Lookup files work best when they are narrow and long (a vertical partition) and especially when they operate against an index. Lookup files work less well for data placed into a wide and shallow table (horizontal partition). Creation of lookup files lets you isolate records that have high transaction traffic, which also lets you protect this data and locate the data in one or more locations. As a rule, heavily accessed data is most susceptible to corruption due to software errors, hardware errors like disk hot spots or user errors.
Heavily accessed data that changes frequently is also a good candidate for partitioning.
Barrie Sosinsky is president of consulting company Sosinsky and Associates (Medfield MA). He has written extensively on a variety of computer topics. His company specializes in custom software (database and Web related), training and technical documentation.
This was first published in March 2005