2. Query Optimizer
The query optimizer in SQL Server is cost-based. It includes:
1. Cost for using different resources (CPU and IO)
2. Total execution time
It determines the cost by using:
• Cardinality: The total number of rows processed at each level
of a query plan with the help of histograms , predicates and
constraint
• Cost model of the algorithm: To perform various operations
like sorting, searching, comparisons etc.
3. Statistics Analysis
• The query optimizer uses statistics to create query plans that
improve query performance
• A correct statistics will lead to high-quality query plan.
• The query optimizer determines when statistics might be out-
of-date by counting the number of data modifications since
the last statistics update and comparing the number of
modifications to a threshold.
4. Auto create statistics
• Default setting of auto create statistics is ON.
• It creates when:
• Clustered and non clustered Index is created
• Select query is executed.
• Auto create and updates applies strictly to
single-column statistics.
5. Why query 2 is performing better
• If we perform following operations on field of any table
in query predicate:
1. Using any system function or user defined function
2. Scalar operation like addition, multiplication etc.
3. Type casting
• In this situation sql server query optimizer is not able
to estimate correct cardinality using statistics.
6. To improve cardinality
• If possible, simplify expressions with constants in them.
• If possible, don't perform any operation on the any field of a
table in WHERE Clause, ON Clause, HAVING Clause
• Don't use local variables in WHERE Clause, ON Clause,
HAVING Clause.
• If there is any cross relationship among fields or there is a
complex expression in a field in a query predicates, it is better
to create a computed column and then create a non-clustered
index on it.
7. To improve cardinality
• If possible, don't update the value of parameters of a function
or stored procedure before using in sql statement
• Use OPTIMIZE FOR clause when you want to optimize
a sql query on the basis of specific parameter value.
• If you want to update the value parameter of a stored
procedure or a function create a similar procedure or function
and execute it form base procedure or function by passing the
updated value as a parameter.
• Create user defined multi column statistics if query predicates
have more than one fields of a table.
