How to Create a Table Using "With" Clause in Sql

I'm attempting to create a persistent table using the WITH clause however, I'm getting an error.

For context the answer that I currently find is

CREATE TABLE my_table
AS 
WITH my_tables_data AS ( 
   SELECT another_table.data1 AS some_value 
   FROM another_table
) 
SELECT * 
FROM some_data; 

However, I am getting an error

Msg 319, Level 15, State 1, Line 5 Incorrect syntax near the keyword 'with'. If this statement is a common table expression, an xmlnamespaces clause or a change tracking context clause, the previous statement must be terminated with a semicolon.

My code is

CREATE TABLE SalesOrdersPerYear  
WITH t1 AS (
    -- Define the CTE expression name and column list.  
    WITH Sales_CTE (SalesPersonID, BaseSalary)  
    AS  
    -- Define the CTE query.  
    (  
        SELECT SALES_PERSON.SALES_PERSON_ID, SALES_PERSON.BASE_SALARY  
        FROM SALES_PERSON  
        WHERE SALES_PERSON_ID IS NOT NULL  
    )  
    -- Define the outer query referencing the CTE name.  
    SELECT SalesPersonID, BaseSalary AS TotalSales  
    FROM Sales_CTE   
    ORDER BY SalesPersonID, BaseSalary;  
)

Would anyone be able to provide some guidance on this?

Many thanks in advance!

7

2 Answers

This is not valid syntax for sql server. you can either create a table using CREATE TABLE and specifying the column names and types, or you can do a SELECT INTO statement including data.

Approach 1 : Create the table and then populate:

CREATE TABLE SalesOrdersPerYear 
( SalesPersonID int, BaseSalary float)
;

WITH Sales_CTE (SalesPersonID, BaseSalary)  
AS  
(  
    SELECT SALES_PERSON.SALES_PERSON_ID, SALES_PERSON.BASE_SALARY  
    FROM SALES_PERSON  
    WHERE SALES_PERSON_ID IS NOT NULL 
)  
insert into SalesOrdersPerYear  
SELECT SalesPersonID, BaseSalary AS TotalSales  
FROM Sales_CTE   
ORDER BY SalesPersonID, BaseSalary;  

Approach 2 - all in one step

WITH Sales_CTE (SalesPersonID, BaseSalary)  
AS  
(  
    SELECT SALES_PERSON.SALES_PERSON_ID, SALES_PERSON.BASE_SALARY  
    FROM SALES_PERSON  
    WHERE SALES_PERSON_ID IS NOT NULL 
)  
select  SalesPersonID, BaseSalary AS TotalSales  
into SalesOrdersPerYear
FROM Sales_CTE   
ORDER BY SalesPersonID, BaseSalary;  

Use approach 1 when you need to specify more about the table (primary keys, indexes, foregin keys etc.

Use approach 2 for things that are more temporary. (you would normally use a temporary table such as #SalesOrdersPerYear here).

Either way, the data is now stored in your table, and you can use it again.

Using temporary tables:

-- Check for existence and drop first to avoid errors if it already exists.
if OBJECT_ID('tempdb..#SalesOrdersPerYear') is not null
    drop table #SalesOrdersPerYear

WITH Sales_CTE (SalesPersonID, BaseSalary)  
AS  
(  
    SELECT SALES_PERSON.SALES_PERSON_ID, SALES_PERSON.BASE_SALARY  
    FROM SALES_PERSON  
    WHERE SALES_PERSON_ID IS NOT NULL 
)  
select  SalesPersonID, BaseSalary AS TotalSales  
into #SalesOrdersPerYear
FROM Sales_CTE   
ORDER BY SalesPersonID, BaseSalary;  

You could also define it as a table variable, which is a bit of a cross between the approaches:

declare @SalesOrdersPerYear table
( SalesPersonID int, BaseSalary float)
;

WITH Sales_CTE (SalesPersonID, BaseSalary)  
AS  
(  
    SELECT SALES_PERSON.SALES_PERSON_ID, SALES_PERSON.BASE_SALARY  
    FROM SALES_PERSON  
    WHERE SALES_PERSON_ID IS NOT NULL 
)  
insert into @SalesOrdersPerYear  
SELECT SalesPersonID, BaseSalary AS TotalSales  
FROM Sales_CTE   
ORDER BY SalesPersonID, BaseSalary;  

This option will only persist with this batch, and does not need dropping - just like any other variable.

4
CREATE VIEW AS my_view
AS 
WITH my_tables_data AS ( 
   SELECT another_table.data1 AS some_value 
   FROM another_table
) 

SELECT * 
FROM some_data; 

CREATE TABLE my_table AS 
SELECT * FROM my_view;
2

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David Miller

David Miller

Executive Financial & Market Analyst

David Miller brings 15 years of experience in global economics, personal finance strategy, and market dynamics. He specializes in turning complex economic trends into actionable insights for everyday readers.

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