• Use views and stored procedures instead of heavy-duty queries.This can reduce network traffic, because your client will send toserver only stored procedure or view name (perhaps with someparameters) instead of large heavy-duty queries text. This can be usedto facilitate permission management also, because you can restrictuser access to table columns they should not see.
• Try to use constraints instead of triggers, whenever possible.Constraints are much more efficient than triggers and can boostperformance. So, you should use constraints instead of triggers,whenever possible.
• Use table variables instead of temporary tables.Table variables require less locking and logging resources thantemporary tables, so table variables should be used whenever possible.The table variables are available in SQL Server 2000 only.
• Try to use UNION ALL statement instead of UNION, whenever possible.The UNION ALL statement is much faster than UNION, because UNION ALLstatement does not look for duplicate rows, and UNION statement doeslook for duplicate rows, whether or not they exist.
• Try to avoid using the DISTINCT clause, whenever possible.Because using the DISTINCT clause will result in some performancedegradation, you should use this clause only when it is necessary.
• Try to avoid using SQL Server cursors, whenever possible.SQL Server cursors can result in some performance degradation incomparison with select statements. Try to use correlated sub-query orderived tables, if you need to perform row-by-row operations.
• Try to avoid the HAVING clause, whenever possible.The HAVING clause is used to restrict the result set returned by theGROUP BY clause. When you use GROUP BY with the HAVING clause, theGROUP BY clause divides the rows into sets of grouped rows andaggregates their values, and then the HAVING clause eliminatesundesired aggregated groups. In many cases, you can write your selectstatement so, that it will contain only WHERE and GROUP BY clauseswithout HAVING clause. This can improve the performance of your query.
• If you need to return the total table's row count, you can usealternative way instead of SELECT COUNT(*) statement.Because SELECT COUNT(*) statement make a full table scan to return thetotal table's row count, it can take very many time for the largetable. There is another way to determine the total row count in atable. You can use sysindexes system table, in this case. There isROWS column in the sysindexes table. This column contains the totalrow count for each table in your database. So, you can use thefollowing select statement instead of SELECT COUNT(*): SELECT rowsFROM sysindexes WHERE id = OBJECT_ID('table_name') AND indid < 2 So,you can improve the speed of such queries in several times.
• Include SET NOCOUNT ON statement into your stored procedures to stop the message indicating the number of rows affected by a T-SQL statement.This can reduce network traffic, because your client will not receivethe message indicating the number of rows affected by a T-SQL statement.
• Try to restrict the queries result set by using the WHERE clause.This can results in good performance benefits, because SQL Server willreturn to client only particular rows, not all rows from the table(s).This can reduce network traffic and boost the overall performance ofthe query.
• Use the select statements with TOP keyword or the SET ROWCOUNTstatement, if you need to return only the first n rows.This can improve performance of your queries, because the smallerresult set will be returned. This can also reduce the traffic betweenthe server and the clients.
• Try to restrict the queries result set by returning only theparticular columns from the table, not all table's columns.This can results in good performance benefits, because SQL Server willreturn to client only particular columns, not all table's columns.This can reduce network traffic and boost the overall performance ofthe query.
1.Indexes
2.avoid more number of triggers on the table
3.unnecessary complicated joins
4.correct use of Group by clause with the select list
5 In worst cases Denormalization
