The SQL Server Query Optimizer is responsible for generating an optimal execution plan to execute a query based on database schema, query logic, and statistics. The Cardinality Estimator is a component of the Query Optimizer that estimates the number of rows returned by a query. To optimize the Query Optimizer and Cardinality Estimator for better query performance, there are several best practices to follow:
1. Use up-to-date statistics: Accurate and current statistics help the Query Optimizer to generate optimal execution plans. Hence, it is recommended to keep statistics updated by enabling auto-update statistics or manual statistics updates.
2. Consider using the latest compatibility level of your database: Compatibility level determines the Query Optimizer version and behavior. Using the latest compatible level ensures that the database uses the latest Query Optimizer version.
3. Avoid using non-SARGable expressions in WHERE clauses: Non-SARGable expressions such as functions, calculations, and type conversions inhibit the use of an index and result in scan operations that increase query execution time. Therefore, it is recommended to use SARGable expressions in WHERE clauses.
4. Use appropriate index types: Indexes improve query performance by reducing the number of rows accessed during query execution. Clustered indexes are recommended for queries that sort and group data while non-clustered indexes are recommended for queries that filter data.
5. Avoid overusing JOIN and UNION operators: Overusing JOIN and UNION operators require the Query Optimizer to consider multiple execution plans, which results in slower query performance. Hence, it is recommended to use the appropriate JOIN and UNION operators that improve query performance.
6. Avoid using the NOLOCK hint: The NOLOCK hint allows for dirty reads, which can return inconsistent data due to uncommitted changes. It is recommended to use READ_COMMITTED isolation level instead.
7. Optimize queries by understanding query execution plans: Understanding query execution plans helps identify inefficiencies that can be optimized in the query or schema.
8. Partition large tables: Partitioning large tables distribute data across multiple file groups, making data retrieval faster and improving query performance.
9. Use appropriate hardware resources: Proper hardware resources such as CPU, RAM, and I/O resources play a vital role in query performance. Therefore, it is essential to use appropriate hardware resources to optimize the Query Optimizer and Cardinality Estimator.
To summarize, optimizing the SQL Server Query Optimizer and Cardinality Estimator involves using up-to-date statistics, using the latest compatibility level, using SARGable expressions in WHERE clauses, using appropriate index types, avoiding overusing JOIN and UNION operators, avoiding using the NOLOCK hint, optimizing queries, partitioning large tables, and using appropriate hardware resources.