Query Optimization:-Query Optimization is the method of practicing the most efficient way to quickly extract data from the database through queries SQL at optimal performance. We can achieve the same result by writing different SQL queries. But it's important to use the best query when performance is critical. The main goal of query optimization is to retrieve data quickly. Query optimization helps reduce execution speed and saves time in data extraction and is cost-effective. Most databases, once created and loaded with data, as well as their subsequent use, will reduce the speed of data extraction. The time required to execute the query and return results increases as the amount of data increases in the database, resulting in longer wait times for the application and the user. Sometimes the waiting time to run the query can last for hours or days and can also cause a blocking issue in the database. A query or SQL statement can be executed in different ways, such as index scans, full table scans, nested loops, and hash joins. It can process more queries in the same amount of time because: Each query will take less time than non-optimized queries. Query optimizer being an important module of a DBMS has a greater impact on the performance of the database. It analyzes a number of candidate plans generated for a given query that have an equivalent result but have different resource costs. It selects the least expensive effective plan from these candidates. Although much work has been done on query optimization, estimating cardinality to manage optimization time and efficiently estimating costs with respect to server state remain challenging problems. Different query processing methods...... middle of paper ...... there is no need to sort the results to distinguish the results. 8) Denormalization is also an optimization technique used to speed up query performance (it combines multiple tables into a single table so that table joins are reduced). Typically, developers are responsible for writing appropriate code, but the database administrator has the primary responsibility for ensuring that SQL is optimal. Developers and QA testers can test the application thoroughly, but the application may not scale well when exposed to real, demanding production environment conditions. As a result, database administrators must scramble to find solutions to a poorly performing SQL statement once the code is executed in the production environment. In many cases, we will encounter performance issues on a production environment that was designed and coded a long time ago. Try to fix the SQL statements first if possible.