A Dozen SQL Rules of Thumb, Part 3

Today we pick up our three-part series of SQL rules of thumb (ROTs) with the third and final installment… You can think of these rules as general guiding principles you should follow as your write SQL statements… and we start off today’s post with rule #9…

Rule 9: Know What Works Best

The flexibility of SQL allows the same process to be coded in multiple ways. However, one way of coding usually provides better performance than the others. The DBA should understand the best way to code SQL for each DBMS in use. Furthermore, the DBA should provide information on proper query formulation for performance to the application development staff.

Keep in mind that these rules are DBMS-specific. By that I mean, one way of writing SQL might perform well on SQL Server but not on Oracle, which performs better with a different form of SQL returning the same data.

Rule 10: Issue Frequent COMMITs

When coding programs to run as batch transactions, it is important to issue regular SQL COMMIT statements. The COMMIT statement hardens modifications to the database. When a COMMIT is issued, locks on the modified database objects and data can be released. If you write programs that make a lot of changes, but do not issue periodic COMMITs, then you will be locking data and negatively impacting concurrent access to the data. I call this Bachelor Programming Syndrome (you know, fear of committing).

An additional consideration for Oracle DBAs is the impact of a COMMIT on the rollback segments. Rollback segments are used by Oracle to store completed transactions before the changes are actually written to the table. When you issue a COMMIT in Oracle, not only is the data finalized to the table but the contents of the rollback segment are removed, too. Oracle rollback segments are used to store before images of the data in case transactions are rolled back before changes are committed.

As a DBA you must ensure that application developers issue enough COMMIT statements to minimize the impact of locking on availability and (for Oracle) to keep rollback segments to a manageable size.

Rule 11: Beware of Code Generators

Beware of application code generators and similar tools that automatically create SQL. Many of these tools use gateways that require each SQL statement to be recompiled and optimized each time it is requested. However, some gateways provide a caching mechanism to store compiled and optimized SQL on the server. Such a cache can be help to improve performance for frequently recurring SQL statements.

Additionally, many code generators create accurate SQL, but not necessarily efficient SQL. So you might need to tweak the SQL that is generated (if that is even possible).

Rule 12: Consider Stored Procedures

Performance degradation due to repeated network traffic can be minimized by using a stored procedure because only a single request is needed to execute it. Within the stored procedure, multiple SQL statements can be issued, and the results processed and sent to the requesting program or user. Without the stored procedure, each of the multiple SQL statements, as well as all of the results, would have to be sent across the network. Additionally, SQL in stored procedures may perform better than the same SQL outside of the stored procedure if the DBMS parses and compiles the statements before run time.


These twelve SQL rules of thumb across three blog posts provide a sound basis for SQL development. Of course, they offer high-level guidance and are not the only things that you need to be aware of, and follow, as you strive to build efficient database applications.

So start here, but expand your knowledge base and keep learning about how you can write effective and efficient SQL for your database applications!



About craig@craigsmullins.com

I'm a strategist, researcher, and consultant with nearly three decades of experience in all facets of database systems development.
This entry was posted in DBA, performance, SQL. Bookmark the permalink.

One Response to A Dozen SQL Rules of Thumb, Part 3

  1. Pingback: A Database Performance Tuning Primer | Data and Technology Today

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