LEAD (Transact-SQL)
Applies to: 
SQL Server
Azure SQL Database
Azure SQL Managed Instance
Azure Synapse Analytics
Analytics Platform System (PDW)
SQL analytics endpoint in Microsoft Fabric
Warehouse in Microsoft Fabric
Accesses data from a subsequent row in the same result set without the use of a self-join starting with SQL Server 2012 (11.x). LEAD provides access to a row at a given physical offset that follows the current row. Use this analytic function in a SELECT statement to compare values in the current row with values in a following row.
Transact-SQL syntax conventions
Syntax
LEAD ( scalar_expression [ , offset ] [ , default ] ) [ IGNORE NULLS | RESPECT NULLS ]
OVER ( [ partition_by_clause ] order_by_clause )
Arguments
scalar_expression
The value to be returned based on the specified offset. It's an expression of any type that returns a single (scalar) value. scalar_expression can't be an analytic function.
offset
The number of rows forward from the current row from which to obtain a value. If not specified, the default is 1. offset can be a column, subquery, or other expression that evaluates to a positive integer or can be implicitly converted to bigint. offset can't be a negative value or an analytic function.
default
The value to return when offset is beyond the scope of the partition. If a default value isn't specified, NULL is returned. default can be a column, subquery, or other expression, but it can't be an analytic function. default must be type-compatible with scalar_expression.
[ IGNORE NULLS | RESPECT NULLS ]
Applies to: SQL Server 2022 (16.x) and later versions, Azure SQL Database, Azure SQL Managed Instance, Azure SQL Edge
IGNORE NULLS - Ignore NULL values in the dataset when computing the first value over a partition.
RESPECT NULLS - Respect NULL values in the dataset when computing first value over a partition. RESPECT NULLS is the default behavior if a NULLS option isn't specified.
There was a bug fix in SQL Server 2022 CU4 related to IGNORE NULLS in LAG and LEAD.
For more information on this argument in Azure SQL Edge, see Imputing missing values.
OVER ( [ partition_by_clause ] order_by_clause )
partition_by_clause divides the result set produced by the
FROMclause into partitions to which the function is applied. If not specified, the function treats all rows of the query result set as a single group.order_by_clause determines the order of the data before the function is applied.
When partition_by_clause is specified, it determines the order of the data in each partition. The order_by_clause is required. For more information, see SELECT - OVER Clause.
Return types
The data type of the specified scalar_expression. NULL is returned if scalar_expression is nullable or default is set to NULL.
LEAD is nondeterministic. For more information, see Deterministic and Nondeterministic Functions.
Examples
The Transact-SQL code samples in this article use the AdventureWorks2022 or AdventureWorksDW2022 sample database, which you can download from the Microsoft SQL Server Samples and Community Projects home page.
A. Compare values between years
The query uses the LEAD function to return the difference in sales quotas for a specific employee over subsequent years. Because there's no lead value available for the last row, the default of zero (0) is returned.
USE AdventureWorks2022;
GO
SELECT BusinessEntityID,
YEAR(QuotaDate) AS SalesYear,
SalesQuota AS CurrentQuota,
LEAD(SalesQuota, 1, 0) OVER (ORDER BY YEAR(QuotaDate)) AS NextQuota
FROM Sales.SalesPersonQuotaHistory
WHERE BusinessEntityID = 275 AND YEAR(QuotaDate) IN ('2005', '2006');
Here's the result set.
BusinessEntityID SalesYear CurrentQuota NextQuota
---------------- ----------- --------------------- ---------------------
275 2005 367000.00 556000.00
275 2005 556000.00 502000.00
275 2006 502000.00 550000.00
275 2006 550000.00 1429000.00
275 2006 1429000.00 1324000.00
275 2006 1324000.00 0.00
B. Compare values within partitions
The following example uses the LEAD function to compare year-to-date sales between employees. The PARTITION BY clause is specified to partition the rows in the result set by sales territory. The LEAD function is applied to each partition separately and computation restarts for each partition. The ORDER BY clause specified in the OVER clause orders the rows in each partition before the function is applied. The ORDER BY clause in the SELECT statement orders the rows in the whole result set. Because there's no lead value available for the last row of each partition, the default of zero (0) is returned.
USE AdventureWorks2022;
GO
SELECT TerritoryName, BusinessEntityID, SalesYTD,
LEAD (SalesYTD, 1, 0) OVER (PARTITION BY TerritoryName ORDER BY SalesYTD DESC) AS NextRepSales
FROM Sales.vSalesPerson
WHERE TerritoryName IN (N'Northwest', N'Canada')
ORDER BY TerritoryName;
Here's the result set.
TerritoryName BusinessEntityID SalesYTD NextRepSales
----------------------- ---------------- --------------------- ---------------------
Canada 282 2604540.7172 1453719.4653
Canada 278 1453719.4653 0.00
Northwest 284 1576562.1966 1573012.9383
Northwest 283 1573012.9383 1352577.1325
Northwest 280 1352577.1325 0.00
C. Specify arbitrary expressions
The following example demonstrates specifying various arbitrary expressions and ignoring NULL values in the LEAD function syntax.
CREATE TABLE T (a INT, b INT, c INT);
GO
INSERT INTO T VALUES (1, 1, -3), (2, 2, 4), (3, 1, NULL), (4, 3, 1), (5, 2, NULL), (6, 1, 5);
SELECT b, c,
LEAD(2 * c, b * (SELECT MIN(b) FROM T), -c / 2.0) IGNORE NULLS OVER (ORDER BY a) AS i
FROM T;
Here's the result set.
b c i
----------- ----------- -----------
1 5 -2
2 NULL NULL
3 1 0
1 NULL 2
2 4 2
1 -3 8
D. Use IGNORE NULLS to find non-NULL values
The following sample query demonstrates using the IGNORE NULLS argument.
The IGNORE NULLS argument is used with both LAG and LEAD to demonstrate substitution of NULL values for preceding or next non-NULL values.
- If the preceding row contained
NULLwithLAG, then the current row uses the most recent non-NULLvalue. - If the next row contains a
NULLwithLEAD, then the current row uses the next available non-NULLvalue.
DROP TABLE IF EXISTS #test_ignore_nulls;
CREATE TABLE #test_ignore_nulls (column_a int, column_b int);
GO
INSERT INTO #test_ignore_nulls VALUES
(1, 8),
(2, 9),
(3, NULL),
(4, 10),
(5, NULL),
(6, NULL),
(7, 11);
SELECT column_a, column_b,
[Previous value for column_b] = LAG(column_b) IGNORE NULLS OVER (ORDER BY column_a),
[Next value for column_b] = LEAD(column_b) IGNORE NULLS OVER (ORDER BY column_a)
FROM #test_ignore_nulls
ORDER BY column_a;
--cleanup
DROP TABLE #test_ignore_nulls;
column_a column_b Previous value for column_b Next value for column_b
------------ ----------- ------------------------------ ------------------------
1 8 NULL 9
2 9 8 10
3 NULL 9 10
4 10 9 11
5 NULL 10 11
6 NULL 10 11
7 11 10 NULL
E. Use RESPECT NULLS to keep NULL values
The following sample query demonstrates using the RESPECT NULLS argument, which is the default behavior if not specified, as opposed to the IGNORE NULLS argument in the previous example.
- If the preceding row contained
NULLwithLAG, then the current row uses the most recent value. - If the next row contains a
NULLwithLEAD, then the current row uses the next value.
DROP TABLE IF EXISTS #test_ignore_nulls;
CREATE TABLE #test_ignore_nulls (column_a int, column_b int);
GO
INSERT INTO #test_ignore_nulls VALUES
(1, 8),
(2, 9),
(3, NULL),
(4, 10),
(5, NULL),
(6, NULL),
(7, 11);
SELECT column_a, column_b,
[Previous value for column_b] = LAG(column_b) RESPECT NULLS OVER (ORDER BY column_a),
[Next value for column_b] = LEAD(column_b) RESPECT NULLS OVER (ORDER BY column_a)
FROM #test_ignore_nulls
ORDER BY column_a;
--Identical output
SELECT column_a, column_b,
[Previous value for column_b] = LAG(column_b) OVER (ORDER BY column_a),
[Next value for column_b] = LEAD(column_b) OVER (ORDER BY column_a)
FROM #test_ignore_nulls
ORDER BY column_a;
--cleanup
DROP TABLE #test_ignore_nulls;
column_a column_b Previous value for column_b Next value for column_b
1 8 NULL 9
2 9 8 NULL
3 NULL 9 10
4 10 NULL NULL
5 NULL 10 NULL
6 NULL NULL 11
7 11 NULL NULL
Examples: Azure Synapse Analytics and Analytics Platform System (PDW)
A. Compare values between quarters
The following example demonstrates the LEAD function. The query obtains the difference in sales quota values for a specified employee over subsequent calendar quarters. Because there's no lead value available after the last row, the default of zero (0) is used.
-- Uses AdventureWorks
SELECT CalendarYear AS Year,
CalendarQuarter AS Quarter,
SalesAmountQuota AS SalesQuota,
LEAD(SalesAmountQuota, 1, 0) OVER (ORDER BY CalendarYear, CalendarQuarter) AS NextQuota,
SalesAmountQuota - LEAD(SalesAmountQuota, 1, 0) OVER (ORDER BY CalendarYear, CalendarQuarter) AS Diff
FROM dbo.FactSalesQuota
WHERE EmployeeKey = 272 AND CalendarYear IN (2001, 2002)
ORDER BY CalendarYear, CalendarQuarter;
Here's the result set.
Year Quarter SalesQuota NextQuota Diff
---- ------- ---------- --------- -------------
2001 3 28000.0000 7000.0000 21000.0000
2001 4 7000.0000 91000.0000 -84000.0000
2001 1 91000.0000 140000.0000 -49000.0000
2002 2 140000.0000 7000.0000 7000.0000
2002 3 7000.0000 154000.0000 84000.0000
2002 4 154000.0000 0.0000 154000.0000