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Summary: Discover how SQL Server determines which statistics take precedence and understand the nuances of query recompilation. Gain insights to improve your database performance.
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Understanding SQL Server Statistics Precedence and Query Recompilation

SQL Server relies on statistics to optimize query performance. These statistics help the SQL Server query optimizer make informed decisions about query execution plans. This guide will explore which SQL Server statistics take precedence and help you grasp the concept of query recompilation.

SQL Server Statistics

SQL Server uses statistics to understand the distribution of data within tables. These statistics guide the SQL Server query optimizer in selecting the best query execution plan. Here are a few key concepts related to SQL Server statistics:

Auto-Created and User-Created Statistics

Auto-Created Statistics: SQL Server can automatically create statistics on columns involved in predicates (e.g., WHERE clauses) when those columns are not already associated with existing statistics.

User-Created Statistics: As a database administrator or developer, you can create statistics manually using the CREATE STATISTICS statement.

Which Statistics Take Precedence?

When SQL Server encounters multiple applicable statistics, it needs to determine which ones to use. The precedence of statistics can significantly impact query performance. Here’s how SQL Server decides:

Statistics on Indexes: Statistics that are part of an index generally take precedence over auto-created or manually created column statistics. Indexed statistics are often more comprehensive as they reflect the order and distribution of index keys.

Most Recently Updated Statistics: Among available statistics, the most recently updated ones are likely to be more accurate. SQL Server tends to prioritize these.

Cardinality and Selectivity: SQL Server's query optimizer evaluates the cardinality (the uniqueness of data values) and selectivity when choosing statistics. Statistics that provide better insight into data distribution typically take precedence.

Query Recompilation

What is Query Recompilation?

Query recompilation refers to the process where SQL Server invalidates an existing query execution plan and generates a new one. This is often necessary to ensure that the query uses up-to-date statistics and data distributions have changed.

When Does Query Recompilation Occur?

Statistics Updates: When statistics are updated significantly, it might trigger a recompilation to ensure the query plan is optimized based on the latest data distribution.

Schema Changes: Changes to the schema, such as altering table structures or indexed views, can cause query recompilation.

Configuration Changes: Modifying server configurations related to query optimization can lead to recompilation.

Impact of Recompilation

While query recompilation helps in maintaining optimal performance, it can also introduce some overhead. Frequent recompilations may lead to increased CPU utilization and execution time.

Managing Statistics and Recompilation

Here are some best practices for managing statistics and handling recompilation:

Regularly Update Statistics: Schedule regular updates for statistics using the UPDATE STATISTICS statement to ensure they remain accurate.

Monitor and Tune: Utilize SQL Server's built-in monitoring tools to analyze query performance and adjust statistics updates accordingly.

Minimize Unnecessary Recompilations: Ensure changes to schema and configuration are deliberate and necessary to reduce the frequency of query recompilations.

Conclusion

Understanding which SQL Server statistics take precedence and grasping the concept of query recompilation is crucial for optimizing your database's performance. Accurate statistics play a vital role in helping the SQL Server query optimizer make efficient decisions. By managing statistics thoughtfully and being mindful of recompilations, you can significantly enhance query performance in your database environment.