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- SQL AND DATABASE RULES
- NAMING CONVENTIONS
- DECLARING VARIABLES
- SELECT STATEMENTS
- WILDCARD CHARACTERS
- NOT EQUAL OPERATORS
- DERIVED TABLES
- SQL BATCHES
- ANSI-STANDARD JOIN CLAUSES
- STORED PROCEDURES NAMING CONVENTION
- USING VIEWS
- TEXT DATA TYPES
- INSERT STATEMENTS
- ACCESSING TABLES
- STORED PROCEDURE RETURNING VALUES
- OBJECT CASE
- T-SQL VARIABLES
- OFFLOAD TASKS
- CHECK FOR RECORD EXISTENCE
- OBJECT OWNER
- UPSERT STATEMENTS
- DATETIME COLUMNS
- MEASURE QUERY PERFORMANCE
All T-SQL Keywords must be upper case.
All declared variable names must be Camel Case while all stored procedure names, function names, trigger names, Table names and Columns names in query must be Pascal Case.
All view names must start with the letter ‘v’ followed by the name of the view in Pascal Case
SELECT * FROM Employee WHERE ID = 2
DECLARE @minSalary int
CREATE PROCEDURE GetEmployees
If you are creating a table belonging to a specific module, make sure to append a 3 character prefix before the name of each table, example:
Note that all table names must be singular.
When creating columns, make sure to append a ‘_F’ to the end of each column you intend to use as a flag. If there are exactly two statuses for the flag, use ‘bit’ data type, if there are 3 or more statuses, use ‘char(1)’ data type. If the column is foreign key reference, append ‘_FK’ to the end of the column name. This makes it easy to distinguish flag and foreign key columns:
CREATE TABLE Employee(
ID INT IDENTITY NOT NULL PRIMARY KEY,
Always declare variables at the top of your stored procedure and set their values directly after declaration. If your database runs on SQL Server 2008, you can declare and set the variable on the same line. Take a look at the following statement under SQL 2000/SQL 2005 and the second statement under SQL 2008. Standard programming language semantics are added in SQL 2008 for short assignment of values:
DECLARE @i int
SET @i = 1
SET @i = @i + 1
DECLARE @i int = 1
SET @i +=1
Do not use SELECT * in your queries. Always write the required column names after the SELECT statement. This technique results in reduced disk I/O and better performance:
SELECT CustomerID, CustomerFirstName, City From Customer
If you need to write a SELECT statement to retrieve data from a single table, don’t SELECT the data from a view that points to multiple tables. Instead, SELECT the data from the table directly, or from a view that only contains the table you are interested in. If you SELECT the data from the multi-table view, the query will experience unnecessary overhead, and performance will be hindered.
Try to avoid server side cursors as much as possible. Always stick to a ‘set-based approach’ instead of a ‘procedural approach’ for accessing and manipulating data. Cursors can often be avoided by using SELECT statements instead.
If a cursor is unavoidable, use a WHILE loop instead. A WHILE loop is always faster than a cursor. But for a WHILE loop to replace a cursor you need a column (primary key or unique key) to identify each row uniquely.
Try to avoid wildcard characters at the beginning of a word while searching using the LIKE keyword, as that result in an index scan, which defeats the purpose of an index. The following statement results in an index scan, while the second statement results in an index seek:
SELECT EmployeeID FROM Locations WHERE FirstName LIKE '%li'
SELECT EmployeeID FROM Locations WHERE FirsName LIKE 'a%i'
Not Equal Operators
Avoid searching using not equals operators (<> and NOT) as they result in table and index scans.
Use ‘Derived tables’ wherever possible, as they perform better. Consider the following query to find the second highest salary from the Employees table:
SELECT MIN(Salary) FROM Employees WHERE EmpID IN (SELECT TOP 2 EmpID FROM Employees ORDER BY Salary Desc)
The same query can be re-written using a derived table, as shown below, and it performs twice as fast as the above query:
SELECT MIN(Salary) FROM (SELECT TOP 2 Salary FROM Employees ORDER BY Salary DESC)
This is just an example, and your results might differ in different scenarios depending on the database design, indexes, volume of data, etc. So, test all the possible ways a query could be written and go with the most efficient one.
Use SET NOCOUNT ON at the beginning of your SQL batches, stored procedures and triggers in production environments.
This suppresses messages like ‘(1 row(s) affected)’ after executing INSERT, UPDATE, DELETE and SELECT statements. This improves the performance of stored procedures by reducing network traffic.
ANSI-Standard Join Clauses
Use the more readable ANSI-Standard Join clauses instead of the old style joins. With ANSI joins, the WHERE clause is used only for filtering data. Whereas with older style joins, the WHERE clause handles both the join condition and filtering data. The first of the following two queries shows the old style join, while the second one show the new ANSI join syntax:
SELECT a.au_id, t.title FROM titles t, authors a, titleauthor ta WHERE
a.au_id = ta.au_id AND
ta.title_id = t.title_id AND
t.title LIKE '%Computer%'
SELECT a.au_id, t.title
FROM authors a
INNER JOIN titleauthor ta
a.au_id = ta.au_id
INNER JOIN titles t
ta.title_id = t.title_id WHERE t.title LIKE '%Computer%'
Stored Procedures Naming Convention
Do not prefix your stored procedure names with “sp_”. The prefix sp_ is reserved for system stored procedure that ship with SQL Server. Whenever SQL Server encounters a procedure name starting with sp_, it first tries to locate the procedure in the master database, then it looks for any qualifiers (database, owner) provided, then it tries dbo as the owner.
So you can really save time in locating the stored procedure by avoiding the “sp_” prefix.
Views are generally used to show specific data to specific users based on their interest. Views are also used to restrict access to the base tables by granting permission only on views. Yet another significant use of views is that they simplify your queries.
Incorporate your frequently required, complicated joins and calculations into a view so that you don’t have to repeat those joins/calculations in all your queries. Instead, just select from the view.
Text Data Types
Try not to use TEXT or NTEXT data types for storing large textual data.
The TEXT data type has some inherent problems associated with it and will be removed from future version of Microsoft SQL Server.
For example, you cannot directly write or update text data using the INSERT or UPDATE
Statements. Instead, you have to use special statements like READTEXT, WRITETEXT and UPDATETEXT.
There are also a lot of bugs associated with replicating tables containing text columns.
So, if you don’t have to store more than 8KB of text, use CHAR(8000) or VARCHAR(8000) data types instead.
In SQL 2005 and 2008, you can use VARCHAR(max) for storing unlimited amount of textual data.
Always use a column list in your INSERT statements. This helps in avoiding problems when the table structure changes (like adding or dropping a column).
Always access tables in the same order in all your stored procedures and triggers consistently. This helps in avoiding deadlocks. Other things to keep in mind to avoid deadlocks are:
1. Keep your transactions as short as possible. Touch as few data as possible during a transaction.
2. Never, ever wait for user input in the middle of a transaction.
3. Do not use higher level locking hints or restrictive isolation levels unless they are absolutely needed.
4. Make your front-end applications deadlock-intelligent, that is, these applications should be able to resubmit the transaction incase the previous transaction fails with error 1205.
5. In your applications, process all the results returned by SQL Server immediately so that the locks on the processed rows are released, hence no blocking.
Stored Procedure Returning Values
Make sure your stored procedures always return a value indicating their status. Standardize on the return values of stored procedures for success and failures.
The RETURN statement is meant for returning the execution status only, but not data. If you need to return data, use OUTPUT parameters.
If your stored procedure always returns a single row result set, consider returning the result set using OUTPUT parameters instead of a SELECT statement, as ADO handles output parameters faster than result sets returned by SELECT statements.
Always be consistent with the usage of case in your code. On a case insensitive server, your code might work fine, but it will fail on a case sensitive SQL Server if your code is not consistent in case.
For example, if you create a table in SQL Server or a database that has a case-sensitive or binary sort order; all references to the table must use the same case that was specified in the CREATE TABLE statement.
If you name the table as ‘MyTable’ in the CREATE TABLE statement and use ‘mytable’ in the SELECT statement, you get an ‘object not found’ error.
Though T-SQL has no concept of constants (like the ones in the C language), variables can serve the same purpose. Using variables instead of constant values within your queries improves readability and maintainability of your code. Consider the following example:
SELECT OrderID, OrderDate FROM Orders WHERE OrderStatus IN (5,6)
The same query can be re-written in a mode readable form as shown below:
DECLARE @ORDER_DELIVERED, @ORDER_PENDING
SELECT @ORDER_DELIVERED = 5, @ORDER_PENDING = 6
SELECT OrderID, OrderDate FROM Orders
WHERE OrderStatus IN (@ORDER_DELIVERED, @ORDER_PENDING)
Offload tasks, like string manipulations, concatenations, row numbering, case conversions, type conversions etc., to the front-end applications if these operations are going to consume more CPU cycles on the database server.
Also try to do basic validations in the front-end itself during data entry. This saves unnecessary network roundtrips.
Check for record Existence
If you need to verify the existence of a record in a table, don’t use SELECT COUNT (*) in your Transact-SQL code to identify it, which is very inefficient and wastes server resources. Instead, use the Transact-SQL IF EXITS to determine if the record in question exits, which is much more efficient. For example:
Here’s how you might use COUNT(*):
IF (SELECT COUNT(*) FROM table_name WHERE column_name = 'xxx')
Here’s a faster way, using IF EXISTS:
IF EXISTS (SELECT * FROM table_name WHERE column_name = 'xxx')
The reason IF EXISTS is faster than COUNT(*) is because the query can end immediately when the text is proven true, while COUNT(*) must count go through every record, whether there is only one, or thousands, before it can be found to be true.
For best performance, all objects that are called from within the same stored procedure should all be owned by the same owner, preferably dbo. If they are not, then SQL Server must perform name resolution on the objects if the object names are the same but the owners are different. When this happens, SQL Server cannot use a stored procedure “in-memory plan” over, instead, it must re-compile the stored procedure, which hinders performance.
There are a couple of reasons, one of which relates to performance. First, using fully qualified names helps to eliminate any potential confusion about which stored procedure you want to run, helping to prevent bugs and other potential problems. But more importantly, doing so allows SQL Server to access the stored procedures execution plan more directly, and in turn, speeding up the performance of the stored procedure. Yes, the performance boost is very small, but if your server is running tens of thousands or more stored procedures every hour, these little time savings can add up.
SQL Server 2008 introduces Upsert statements which combine insert, update, and delete statements in one ‘Merge’ statement.
Always use the Merge statement to synchronize two tables by inserting, updating, or deleting rows in one table based on differences found in the other table
MERGE table1 AS target
) AS source (ID,Name)
target.Table2ID = source.ID
WHEN NOT MATCHED AND target.Name IS NULL THEN
WHEN NOT MATCHED THEN
INSERT (name, Table2ID)
VALUES(name + ' not matched', source.ID)
WHEN MATCHED THEN
SET target.name = source.name + ' matched'
Always use ‘datetime2’ data type in SQL 2008 instead of the classic ‘datetime’. Datetime2 offers optimized data storage by saving 1 additional byte from the classic datetime. It has a larger date range, a larger default fractional precision, and optional user-specified precision.
If your column is supposed to store the date only portion, use the ‘date’ date type while if you want to store the time portion, use the ‘time’ data type. Below is a list of examples of these new data types look like:
time 12:35:29. 1234567
smalldatetime 2007-05-08 12:35:00
datetime 2007-05-08 12:35:29.123
datetime2 2007-05-08 12:35:29. 1234567
datetimeoffset 2007-05-08 12:35:29.1234567 +12:15
Measure Query Performance
Always use statistics time feature to measure your important query and stored procedure’s performance. Use statistics time to optimize your queries Take a look at this example:
SET STATISTICS TIME ON
EXEC GetMedicalProcedures 1,10
SET STATISTICS TIME OFF
The below information will be displayed in the Messages tab:
SQL Server parse and compile time:
CPU time = 6 ms, elapsed time = 6 ms.
SQL Server Execution Times:
CPU time = 24 ms, elapsed time = 768 ms.
(10 row(s) affected)
SQL Server Execution Times:
CPU time = 0 ms, elapsed time = 125 ms.
SQL Server Execution Times:
CPU time = 16 ms, elapsed time = 131 ms.
This provides a good estimation of how long the query took to be executed, showing the CPU time (processing time) and elapsed time (CPU + I/O).
Create indexes on tables that have high querying pressure using select statements. Be careful not to create an index on tables that are subject to real-time changes using CRUD operations.
An index speeds up a select clause if the indexed column is included in the query, especially if it is in the WHERE clause. However, the same index slows down an insert statement whether or not the indexed column is included in the query. This downside occurs because indexes readjust and update statistics every time the table structure is changed. So use indexes wisely for optimizing tables having high retrieval rate and low change rate.