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SQL Query Performance Analysis

            Statistics
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.
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.
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.
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.
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.
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.
Tools

• Sql query profiler

• Database Tuning Advisor

• Resource Governor
THANK YOU

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Statistics

  • 1. SQL Query Performance Analysis Statistics
  • 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.
  • 8. Tools • Sql query profiler • Database Tuning Advisor • Resource Governor