Efficient indexing for performance

Some databases allow different types of indexing. Get an overview of index types and efficient indexing in this book excerpt?

The following tip was excerpted from Chapter 8, 'Building Fast-Performing Data Models,' from the book "Beginning Database Design" by Gavin Powell, courtesy of WROX Publishing. Click here for the complete collection of book excerpts.

Efficient Indexing for Performance

Most important, always be more circumspect about creating an index rather than not creating an index. Many databases get so convoluted and mixed up with over-indexing that, after long periods of time, no one knows who created what --and why. Never be afraid of not creating an index. It follows that you should not always assume that an existing index should exist, simply because it does exist.

Types of Indexes

Some databases allow different types of indexing. In relational databases, one index type is most commonly used. That index type is usually some form of binary tree index (BTree). Other index types are nearly always rare and only applicable in specialized cases. Be aware of the needs of, and consequences for, using special types of indexing such as ISAM, hash, or bitmap indexing.

Different database engines use index structures and methods in different ways. Some examples are warranted here. Where one database engine allows creation of separate physical ISAM indexes, another database may use an ISAM algorithm to access a BTree index. Some databases allow creation of hash indexes as separate physical structures; others only allow application of hashing algorithms to all fields in an entire table. Some database engines allow creation of BTree indexes both as an index, and as a sorting sequence on an entire table. The table itself, and all its fields, become a BTree index (known as a clustered index or an index organized table).

They have very specialized applications and are not commonly used. Also, be aware that these less commonly used index types are often subject to overflow when changes are made to source tables. In reality, unusual types of indexes can often be subject to performance-crippling forms of overflow. Overflow is where an index has its performance created index structure completely diverted from and partially undone, by data changes to tables. Most of these unusual types of indexes are more often that not for read-only type environments, and should generally be implemented and applied with great care and forethought beforehand.

Database administrators should always keep a watchful eye on indexing in a database. Of course, there is never really available time, but when an application is released it is always best to re-examine all indexing. Quite often, developers will create many indexes, sometimes each creating their own sets of indexes, for the same application. The result is over-indexing. Too many indexes on a table create a performance problem. Effectively, executing a table change command (INSERT, UPDATE, or DELETE) on a table executes the same command on all of its indexes in addition to just the table. For example, inserting a single record into a table with four indexes comprises five changes to the database.

The above tip was excerpted from Chapter 8, 'Building Fast-Performing Data Models,' from the book "Beginning Database Design" by Gavin Powell, courtesy of WROX Publishing. Click here for the complete collection of book excerpts.

This was first published in April 2006
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