SQL Server LAG function overview and examples

The LAG() function in SQL Server is used to access data from a previous row within the same result set. It provides a way to look back at the previous row’s value and compare it with the current row’s value. Compare with Lead function, The LEAD function is used to retrieve the value from the next row in a query result set.


LAG (scalar_expression [,offset] [,default_value]) 
OVER ([PARTITION BY partition_expression, ... ] 
ORDER BY order_expression [ASC | DESC], ... )
  • scalar_expression: The expression to be returned from the previous row.
  • offset: An optional argument that specifies the number of rows to move back from the current row. The default value is 1.
  • default_value: An optional argument that specifies a default value to return if the offset is beyond the first row.

Example 1 

SELECT ProductName, Sales, 
  LAG(Sales) OVER (ORDER BY Sales) AS PrevSales
FROM SalesTable

In this example, the query returns the ProductName, Sales, and the previous row’s Sales value. The LAG() function is used to access the previous row’s value and compare it with the current row’s value. The result set is ordered by Sales.

Example 2

SELECT EmployeeName, Salary, 
  LAG(Salary, 2, 0) OVER (ORDER BY Salary) AS Prev2ndSalary
FROM EmployeeTable

In this example, the query returns the EmployeeName, Salary, and the second previous row’s Salary value. The LAG() function is used to access the second previous row’s value and compare it with the current row’s value. The result set is ordered by Salary, and the offset argument is set to 2, which specifies that the function should move two rows back from the current row. The default_value argument is set to 0, which specifies a default value to return if the offset is beyond the first row.

SQL Server Lead function overview and examples

Lead function is available from SQL Server 2012. Lead function can accesses data from a subsequent row in the same result set without self-join. Use this function in a Select statement can compare values in the current row with values in the following row.


LEAD ( scalar_expression [ ,offset ] , [ default ] )   
    OVER ( [ partition_by_clause ] order_by_clause )

scalar_expression the value to be compared and returned between the select result set

offset the number of rows forward from the current, the lead function will fetch the value based on this number.

default the default value returned from the lead function when reached last row of the select result set.

OVER ( [ partition_by_clause ] order_by_clause ) used to divide the result rows by partition_by_clause then order the result set by order_by_clause, the number of offset will be calculated based on the order_by result sets.

Demo data used in the following Example:

Example 1 Lead function with offset 1 and without a default value

In this example, we will calculate the price_to value for each records, the records will be grouped by PublicationSource and ordered by price_from. the first row’s price_to will be second rows price_from. before SQL Server 2012, we need to use self-join to do this logic. but since SQL Server 2012 , the new function LEAD can do this job as well.

SELECT ID,PublicationSource,PriceFrom
,LEAD(PriceFrom,1)OVER(PARTITION BY PublicationSource ORDER BY PriceFrom) price_to 
FROM #demo
ORDER BY PublicationSource,PriceFrom 

From the above output, we can see that the Lead function gets the value from the next row of the select result set and return NULL if no subsequent row is available be cause the offset is 1 and default value haven’t provide in the code.

Example 1 Lead function with offset 2 and without a default value

SELECT ID,PublicationSource,PriceFrom
,LEAD(PriceFrom,2)OVER(PARTITION BY PublicationSource ORDER BY PriceFrom) price_to
FROM #demo
ORDER BY PublicationSource,PriceFrom

From the above output, we can see that the Lead function gets the value from the second row of current data in the select result set and return NULL if no subsequent row is available

How to use Git in Visual Studio Code

Before change code in dev branch, you need to ensure you had the latest change of the master branch.

  1. Check your current local branch by using ‘git branch‘.
  2. Use ‘git checkout master‘ to switch your current branch if you are not on the master branch
  3. Use ‘git pull‘ to get latest update from the master remote repository. This command will download the latest changes from the remote repository and merge them with your local master branch.
  4. Use ‘git checkout dev‘ to switch your branch from local master to local dev
  5. Use ‘git merge master‘ to merge the changes from master branch into your local dev branch

Now, local dev branch’s code is updated to the same as master remote repository then you can start your new code change in dev branch.

  1. Before you change start code change, always use ‘git branch‘ to check what’s your current branch. then start your code change
  2. Once you finished your code change, use ‘git status’ to check the status of your local repository. This will show you which files have been modified or added and which files are ready to be committed.
  3. Use ‘git add <file>’ to stage the changes your want to commit. or You can stage all changes by using ‘git add .
  4. Use ‘git commit -m “commit message” ‘ to commit changes with a message describing the changes made.
  5. Use ‘git push‘ to upload your commits to remote repository. this command sends your local commits to remote repository and make them available to others.
  6. a merge request should automatically created after ‘git push’ is done. this merge request will try to merge dev branch changes to master branch.

TRANSLATE and REPLACE function in SQL Server

TRANSLATE and REPLACE are both SQL Server functions that can be used to replace characters in a string, but they have some key differences:

  • REPLACE function replaces all occurrences of a specific string or character with another string or character. It takes three arguments: the source string, the string or character to be replaced, and the replacement string or character.
    REPLACE(string_expression, string_pattern, string_replacement)
  • TRANSLATE function replaces multiple characters at once. It takes three arguments: the source string, the set of characters to be replaced, and the set of replacement characters. Each character in the first set is replaced by the corresponding character in the second set. If a character in the first set is not found in the second set, it is removed.
    TRANSLATE(string_expression, string_pattern, string_replacement)
    SELECT TRANSLATE('2*[3+4]/{7-2}', '[]{}', '()()') –out put 2*(3+4)/(7-2)

The main difference between the two is that REPLACE can replace one or more specific characters or substrings in a string, while TRANSLATE can replace multiple characters at once. TRANSLATE can be useful when you need to replace multiple characters in a string at once, while REPLACE is useful when you need to replace a specific substring or character.

SQL Ranking Functions

SQL provides 4 ranking functions:

RANK — Returns the rank of each row within the partition of a result set. The rank of a row is one plus the number of ranks that come before the row in question.

DENSE_RANK –This function returns the rank of each row within a result set partition, with no gaps in the ranking values. The rank of a specific row is one plus the number of distinct rank values that come before that specific row.

ROW_NUMBER — Numbers the output of a result set. More specifically, returns the sequential number of a row within a partition of a result set, starting at 1 for the first row in each partition.

NTILE — Distributes the rows in an ordered partition into a specified number of groups. The groups are numbered, starting at one. For each row, NTILE returns the number of the group to which the row belongs.


The following example shows the four ranking functions used in the same query. For function-specific examples, see each ranking function.

SELECT p.FirstName, p.LastName  
    ,ROW_NUMBER() OVER (ORDER BY a.PostalCode) AS "Row Number"  
    ,RANK() OVER (ORDER BY a.PostalCode) AS Rank  
    ,DENSE_RANK() OVER (ORDER BY a.PostalCode) AS "Dense Rank"  
    ,NTILE(4) OVER (ORDER BY a.PostalCode) AS Quartile  
FROM Sales.SalesPerson AS s   
    INNER JOIN Person.Person AS p   
        ON s.BusinessEntityID = p.BusinessEntityID  
    INNER JOIN Person.Address AS a   
        ON a.AddressID = p.BusinessEntityID  
WHERE TerritoryID IS NOT NULL AND SalesYTD <> 0;  
FirstNameRow NumberRankDense RankQuartileSalesYTDPostalCode

How to handle error or exceptions in SQL Stored Procedures


Once stored procedures deployed to production server, there is no easy way to safely debug or reproduce or tracking issues if we haven’t had a proper error and exception handling logic.

In this article, we’ll give one of example to catch the errors and save related information to table for issue debugging.

Handling errors using TRY…CATCH

Here’s how the syntax looks like. It’s pretty simple to get the hang of. We have two blocks of code:

     --function logic
     --error handling logic

The code BEGIN TRY and END TRY is our function logic code that we want to monitor for an error. So, if an error would have happened inside this TRY statement, the CATCH statement will be triggered and then we need to handle those errors inside of CATCH statement . We can try to report the error, log the error, or event fix the error. But in this article, we are going to demo how to log the error, so we know can when it happened, who did it and other useful stuff. We even have access to some special data only available inside the CATCH statement:

  • ERROR_NUMBER – Returns the internal number of the error
  • ERROR_STATE – Returns the information about the source
  • ERROR_SEVERITY – Returns the information about anything from informational errors to errors user of DBA can fix, etc.
  • ERROR_LINE – Returns the line number at which an error happened on
  • ERROR_PROCEDURE – Returns the name of the stored procedure or function
  • ERROR_MESSAGE – Returns the most essential information and that is the message text of the error

The script below is as simple as it gets:

-- Basic example of TRY...CATCH
-- Generate a divide-by-zero error  
    1 / 0 AS Error;
    ERROR_NUMBER() AS ErrorNumber,
    ERROR_STATE() AS ErrorState,
    ERROR_SEVERITY() AS ErrorSeverity,
    ERROR_PROCEDURE() AS ErrorProcedure,
    ERROR_LINE() AS ErrorLine,
    ERROR_MESSAGE() AS ErrorMessage;

This is an example of how it looks and how it works. The only thing we’re doing in the BEGIN TRY is dividing 1 by 0, which will cause an error. If we execute the script from above, this is what we get:

Basic SQL Server try catch script executed in Management Studio that returns an error

From left to right, we got ErrorNumber, ErrorState, ErrorSeverity; there is no procedure in this case (NULL), ErrorLine, and ErrorMessage.

Now, let’s create a table called DB_Errors, which can be used to store tracking data:

         (ErrorID        INT IDENTITY(1, 1),
          UserName       VARCHAR(100),
          ErrorNumber    INT,
          ErrorState     INT,
          ErrorSeverity  INT,
          ErrorLine      INT,
          ErrorProcedure VARCHAR(MAX),
          ErrorMessage   VARCHAR(MAX),
          ErrorDateTime  DATETIME)

Now, let’s modify a custom stored procedure from the database and put an error handler in there:

ALTER PROCEDURE dbo.AddSale @employeeid INT,
@productid INT,
@quantity SMALLINT,
SET @saleid = NEWID()
SELECT @saleid,@productid,@employeeid,@quantity

Altering this stored procedure simply wraps error handling in this case around the only statement inside the stored procedure. If we call this stored procedure and pass some valid data, here’s what happens:

Script for inserting valid data through a stored procedure into Sales table

A quick Select statement indicates that the record has been successfully inserted:

Script for validating if data is inserted successfully into the table

However, if we call the above-stored procedure one more time, passing the same parameters, the results grid will be populated differently:

Script for inserting invalid data that would cause raise error SQL state

This time, we got two indicators in the results grid:

0 rows affected – this line indicated that nothing actually went into the Sales table

1 row affected – this line indicates that something went into our newly created logging table

So, what we can do here is look at the errors table and see what happened. A simple Select statement will do the job:

Script for retrieving data from the errors table

Here we have all the information we set previously to be logged, only this time we also got the procedure field filled out and of course the SQL Server “friendly” technical message that we have a violation:

Violation of PRIMARY KEY constraint ‘PK_Sales_1′. Cannot insert duplicate key in object’ Sales.Sales’. The duplicate key value is (20).

So in this way, we have tracking what the error happened and then can fix issue based on the error information which make our issue tracking and fixing task more easily.