If you are DBA you already know the topic. By the way you may see many SQL code example which show how statistic is important for Oracle Cost-based Optimizer (CBO) in performance topic.
As I said, statistics play a crucial role in Oracle Database for query optimization and performance tuning.
Let us see some reasons why statistics are important for us:
Query Optimization:
The Oracle optimizer uses statistics to determine the most efficient execution plan for a given SQL query. Statistics provide information about the distribution, density, and selectivity of data within tables and indexes. By analyzing these statistics, the optimizer can make informed decisions on which access paths, join methods, and other optimization techniques to use when executing a query. Accurate statistics lead to better execution plans and improved query performance.
Cost-Based Optimization:
Oracle’s optimizer uses a cost-based approach to determine the optimal execution plan. Statistics help estimate the cost of various execution plans by providing information about the data distribution and cardinality. With accurate statistics, the optimizer can estimate the number of rows returned by each operation, the size of intermediate result sets, and the overall cost of different execution plans. This allows the optimizer to choose the plan with the lowest cost, resulting in efficient query execution.
Index Selection:
Statistics on indexes help the optimizer decide whether to use an index or perform a full table scan. By analyzing the index statistics, the optimizer can estimate the selectivity of index scans and determine if using an index would be beneficial in terms of reducing I/O and improving query performance. Accurate statistics help the optimizer make informed decisions on index usage and avoid unnecessary index scans.
Plan Stability:
When statistics are accurate and up-to-date, the execution plans generated by the optimizer tend to be stable and consistent. This means that the same query will consistently produce the same execution plan, leading to predictable and reliable performance. In contrast, outdated or missing statistics can result in suboptimal plans or plan instability, causing variations in query performance and hindering the ability to tune and optimize the database.
Automatic Maintenance:
Oracle provides mechanisms for automatic statistics gathering, such as the Automatic Optimizer Statistics Collection feature. This feature automates the process of collecting and maintaining statistics for tables, indexes, and other database objects. By enabling automatic statistics collection, you ensure that the optimizer has the most up-to-date statistics available, reducing the need for manual intervention and helping to maintain optimal query performance.
In summary, statistics are essential in Oracle Database as they enable the optimizer to make informed decisions about query execution plans, select appropriate access paths, and estimate the cost of different operations. Accurate and up-to-date statistics contribute to efficient query optimization, improved performance, and better overall database management.
