What are the top SQL performance tuning practices for mission-critical systems?

1 Understand your data and queries

The first step in SQL performance tuning is to understand your data and queries. You need to know the size, structure, and distribution of your data, as well as the frequency, complexity, and purpose of your queries. This will help you identify the most critical and problematic queries, as well as the potential areas for improvement. You can use tools such as query analyzers, execution plans, and performance monitors to collect and analyze data and query metrics.

2 Use indexes wisely

Indexes are data structures that can speed up the retrieval of data from tables by creating pointers to specific rows or columns. However, indexes also have a cost: they consume disk space, memory, and CPU cycles, and they need to be updated whenever the data changes. Therefore, you need to use indexes wisely and avoid over-indexing or under-indexing your tables. You should create indexes only on the columns that are frequently used in queries, especially in the WHERE, JOIN, and ORDER BY clauses. You should also choose the appropriate index type and size for your data and queries.

3 Optimize your queries

Optimizing your queries is essential for SQL performance tuning. You can optimize your queries by following general guidelines, such as expressing the query logic in the simplest and most direct way, avoiding unnecessary or redundant operations, using joins instead of correlated subqueries or nested loops, filtering and predicating to limit the number of rows and columns returned, using query hints or optimizer hints to influence the query execution plan, and relying on stored procedures, views, or user-defined functions to encapsulate and reuse common query logic.

4 Tune your database parameters

Your database parameters can have a significant impact on your SQL performance, as they are responsible for managing and allocating resources such as memory, disk, cache, and concurrency. You can tune these parameters to suit your workload, data volume, and system configuration. For example, you can adjust the buffer pool size to control the amount of memory allocated to store data pages in memory; the log file size to manage the disk space allocated to store transaction logs; the cache size to determine the amount of memory allocated to store frequently accessed data or metadata; the locking level to define the granularity of locking applied to data; and the isolation level to determine the degree of concurrency and consistency allowed for transactions.

5 Monitor and test your performance

The last practice for SQL performance tuning is to monitor and test your performance regularly. You need to measure and compare your performance before and after applying any changes, such as creating or dropping indexes, optimizing queries, or tuning parameters. You also need to monitor your performance over time and under different scenarios, such as peak load, stress, or failure. You can use tools such as benchmarks, profilers, or load testers to simulate and evaluate your performance. You should also establish performance baselines and thresholds, and set up alerts or notifications for any deviations or anomalies.

6 Here’s what else to consider

This is a space to share examples, stories, or insights that don’t fit into any of the previous sections. What else would you like to add?