This query is not equivalent because it produces NULL when order_type = 'purchase', and hence it will not be counted by the COUNT() function.ĭ: COUNT(CASE WHEN order_type = 'purchase' then 1 ELSE 0 END) The options that are not logically equivalent are:Ĭ: COUNT(CASE WHEN order_type = 'purchase' then NULL END) These queries are equivalent because they also produce non-null values for each row where order_type = 'purchase', and hence will be counted by the COUNT() function. Given this understanding, the logically equivalent options to COUNT(CASE WHEN order_type = 'purchase' then 1 END) are: The COUNT() function then counts the number of rows that do not have a NULL value generated by the case statement. The case statement inside the COUNT() function generates a value for each row in the dataset. In SQL, the COUNT() function only considers non-null values. D: COUNT(CASE WHEN order_type = 'purchase' then 1 ELSE 0 END).C: COUNT(CASE WHEN order_type = 'purchase' then NULL END).B: COUNT(CASE WHEN order_type = 'purchase' then 2 END).A: COUNT(CASE WHEN order_type = 'purchase' then 0 END).Which of the following is logically equivalent to the query above? (Focus specifically on: COUNT(CASE WHEN order_type = 'purchase' then 1 END) ). On the other hand, if it is not of type purchase, we can tag it as 0. This can be expressed by tagging the result as 1. From how we coded the query, we only count a row if it has the order_type of ‘purchase’. In this query, we utilize the COUNT (CASE WHEN.) statement to count the number of purchases within the “orders” table. Consider the following code snippet: SELECT COUNT ( CASE WHEN order_type = 'purchase' then 1 ELSE 0 END ) FROM ORDERS To understand the usage of SQL’s COUNT (CASE WHEN.) in practical scenarios, let’s take a look at the statement in action.
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