![]() ![]() Select where count is greater than one : using JOINS See the below image ( figure 3) which shows data corresponding to customer_id=4. ![]() Though customer_id=4 also has more than one mode_of_shopping, still is not included in the results as mode_of_shopping is not distinct. In the output- figure 2, we can see that only customer_id -> 2, 3 and 5 are there in the result. The outer-query will then get all the data corresponding to customer_id, matching with customer_id in inner-query.The inner-query will get all the customer_id from customer_data table Grouped By customer_id and Having distinct mode_of_shopping > 1.The above query can be divided into two parts inner-query and outer-query.HAVING COUNT(DISTINCT mode_of_shopping) > 1) Observe the below query for the solution. Let us Get the details of the customers who had more than one distinct mode of shopping (who shopped online and at the shop). Syntax:- SELECT FROM GROUP BY HAVING COUNT This section will talk about select statements where the count is greater than one using the HAVING clause. Select where count is greater than one : using HAVING Clause We will see what got into the customer_data table by executing: SELECT * FROM customer_data INSERT INTO customer_table (customer_id,customer_name,customer_address,customer_level,mode_of_shopping) We will be creating the table customer_data and adding data to it. Select where count is greater than one : using Exists.Select where count is greater than one : using JOINS.Select where count is greater than one : using HAVING Clause.Scripting on this page enhances content navigation, but does not change the content in any way.In this article, we will be looking into the count() function with select statement and conditions. The following example calculates, for each employee in the employees table, the moving count of employees earning salaries in the range 50 less than through 150 greater than the employee's salary.ĬOUNT(*) OVER (ORDER BY salary RANGE BETWEEN 50 PRECEDINGĪND 150 FOLLOWING) AS mov_count FROM employees SELECT COUNT(DISTINCT manager_id) "Managers" FROM employees SELECT COUNT(commission_pct) "Count" FROM employees SELECT COUNT(*) "Allstars" FROM employees The following examples use COUNT as an aggregate function: See Also: "About SQL Expressions" for information on valid forms of expr and "Aggregate Functions" ![]()
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