Sql Server Query Parameterization


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This session talks all about SQL Server Query Parameterization. Covers various topics like Query Tuning, Adhoc Query, Execution Plan, Query Optimizer, Parameter Sniffing, Indexes etc. etc.

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Sql Server Query Parameterization

  1. 1. SQL Server Query Parameterization  Query Tuning Ritesh Kumar Skype: mfs_ritesh Blog: http://exacthelp.blogspot.com/
  2. 2. INDEX  Adhoc Query  Predicates Order  Execution Plan  Query Optimizer  Parameter Sniffing  Indexes  Statistics  Database Engine Tuning Advisor
  3. 3. Adhoc Query q Any non-parameterized queries are called addhoc queries. For example : q SELECT MsgID, Severity FROM SqlMessage WHERE MsgID = 100 q In sql server if we execute a sql query it goes through two steps just like any other programming languages: q Compilation q Execution
  4. 4. Properties Of Addhoc Queries q Case sensitive q Space sensitive q Parameter sensitive  q Sql server treats two same sql queries of different parameters as a two different sql statements. For example: q SELECT MsgID, Severity FROM SqlMessage WHERE MsgID = 1 q SELECT MsgID, Severity FROM SqlMessage WHERE MsgID = 2
  5. 5. Effect Of Faulty C# Code  Sql server has took extra n * (Compilation time) ms to display records  Extra time to insert records in cached plans.  Sql server has to frequently fire a job to delete the cached plan since it will reach the max limit very soon.  It will not only decrease the performance of this sql query but all sql queries of other applications since this faulty code will force to delete cached query plans of other sql statements.
  6. 6. Predicates Order q Does order of predicates matters in WHERE clause? q WHERE vcLanguage = 'English' AND ntAge = 12 q WHERE ntAge = 12 AND vcLanguage = 'English'
  7. 7. Execution Plan
  8. 8. Query Optimizer
  9. 9. Query Optimizer The query optimizer in SQL Server is cost-based. It includes: q Cost for using different resources (CPU and IO) q 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.
  10. 10. Parameter Sniffing  Sql server generates execution paln according to the first parameter  This execution plan may bad for other parameters.   Solution:  Create multiples stored procedures.  Use optimizer for query hints.
  11. 11. What Is An Index ? q Index is a way to organize data to make searching, sorting and grouping faster. q we need indexing when : q WHERE, ON, HAVING clause (Searching) q ORDER BY clause (Sorting) q GROUP BY clause (Grouping) etc.
  12. 12. Table Scan SELECT * FROM Student WHERE RollNo = 111 Time complexity of table scan is : O(n) RollNo Name Country Age 101 Greg UK 23 102 Sachin India 21 103 Akaram Pakistan 22 107 Miyabi China 18 108 Marry Russia 27 109 Scott USA 31 110 Benazir Banglades 17 111 Miyabi Japan 24 112 Rahul India 27 113 Nicolus France 19
  13. 13. Types Of Index q Table without any index is called Heap q There are two type of index: q Clustered index q Non-Clustered index
  14. 14. Clustered Index  When we create a clustered index on any table physical organization of table is changed.  Now data of table is stored as a balanced tree(B tree). CREATE UNIQUE [CLUSTERED] INDEX <Name> ON <ObjectName>( <ColumnName>  [ASC | DESC ] [ ,...n ] )
  15. 15. Types Of Scanning  Table scan: It is very slow can and it is used only if table has not any clustered index.  Index scan: It is also slow scan. It is used when table has clustered index and either in WHERE clause non-key columns are present or query has not been covered (will discuss later) or both.  Index Seek: It is very fast. Our goal is to achieve this.
  16. 16. Clustered Index  If we create table with primary key, sql server automatically creates clustered index on that table  A table can have only one clustered index .  Physical order of rows of table is same as logical order of key columns of clustered index.
  17. 17. Terms Of Execution Plan  Predicate: It is condition in WHERE clause which is either nonkey column or column which has not been covered.  Object: It is name of source from where it getting the data. It can be name of table, Clustered index or non-clustered index  Output list: It is name of the columns which is getting from object.  Seek Predicate: It is condition in WHERE clause which is either key column or fully covered.
  18. 18. Non-Clustered Index  It is logical organization of data of table. A non-clustered index can be of two types. q Heap q Based on clustered index.  If table has clustered index then leaf node of non-clustered index keeps the key columns of clustered index.  If the table has not any clustered index then leaf node of nonclustered index keeps RID which unique of each row of table.
  19. 19. Based On Clustered Index
  20. 20. Based On Heap
  21. 21. Covering Of Queries   We can specify maximum 16 column names. Sum of size of the columns cannot be more than 900 bytes.  All columns must belong to same table.  Data type of columns cannot be ntext, text, varchar (max), nvarchar (max), varbinary (max), xml, or image  It cannot be non-deterministic computed column.
  22. 22. 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-ofdate by counting the number of data modifications since the last statistics update and comparing the number of modifications to a threshold.
  23. 23. 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 singlecolumn statistics.
  24. 24. Why Query 2 Is Performing Better q If we perform following operations on field of any table in query predicate: q Using any system function or user defined function q Scalar operation like addition, multiplication etc. q Type casting q In this situation sql server query optimizer is not able to estimate correct cardinality using statistics.
  25. 25. 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.
  26. 26. 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.
  27. 27. SQL Server Tools  Sql query profiler  Database Tuning Advisor  Client Statistics  Resource Governor  Data Collections
  28. 28. THANK YOU