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Understanding database model tuning

Database model tuning comes with one big stipulation. Find out what it is 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.

Understanding Database Model Tuning

The biggest problem with database model tuning is that it really must be done during the design phase, and preferably before any development is complete. This is the case as far as tables and their inter-relationships are concerned. Data warehouses are largely read-only and are not as restrictive with production-phase changes. Data warehouses are mostly read-only type environments. Read-only environments can take advantage of specialized database structures, which overlay, duplicate, and summarize data in tables. Materialized views are used extensively in data warehouses and even some OLTP databases. A materialized view allows for copying of table data, either as individual tables or joins. The result is a physical copy of data. Queries then execute against the materialized view copy, which is built based on the requirements of a single query or a group of queries. The result is better performance.

Tuning a database model is the most difficult and expensive option because SQL code depends on the structure of the underlying database model; extensive application code changes can result. The database model underpins and supports everything else. Changes to a database model can cause major application changes, obviously applying after development of application code. The point is that database model tuning changes (such as changes to underlying tables) can affect everything else. Changing everything from database model up is very expensive because everything is dependent on the database model. Everything must be changed. This is why it is so important to get the database model correct before development begins. Unfortunately, we don't live in an ideal world, but we can strive for it. Big changes to database model table structure can often result in what amounts to full rewrites of application software.

An effective way to performance-tune a database model after development is complete, is the creation of alternate indexing. Stored procedures can also help by compartmentalizing, speeding up and organizing what already exists.

When it comes to database model tuning, at the worst and most expensive end of the scale are normalization, denormalization, changes to referential integrity and table structure, and anything else that changes the basic table structure. At best, and with minimal intrusion on existing tables and relationships, alternate indexing, materialized views, clustering, and other such tricks, can help to enhance a database= model, without messing around with critical underlying table structure. Database objects such as materialized views and clustering help to circumvent table changes by creating copies and overlays of existing table structures, without affecting those existing tables, and obviously avoiding changes to any dependent application coding already written, tested, debugged, and in general use in a production environment. The down side to overlaying and copying is that there is a limit to how many things such as materialized views that can be created. Too much can hinder rather than help performance.

So, now you know why OLTP databases need less granularity, some denormalization, and small quantities of data. The same applies with the other extreme in that data warehouses need highly denormalized (simple) table structures to minimize table numbers in join queries, thus not severely impeding data warehouse reporting performance.

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

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