In SQL, aggregate functions are used to calculate a set of values and return a single value. There are 5 types of SQL aggregate functions: We often use aggregate functions with the GROUP BY and HAVING clauses of the SELECT statement. What is an Aggregate Function in SQL?Īn aggregate function in SQL returns one value after calculating multiple values of a column. An aggregate function ignores NULL values when it performs the calculation, except for the count function. SQL provides many aggregate functions that include avg, count, sum, min, max, etc. Monitoring PostgreSQL with Navicat Monitor 3.An aggregate function in SQL performs a calculation on multiple values and returns a single value.Trace Queries on your PostgreSQL Instances with Navicat Monitor 3.Viewing PostgreSQL Instance Details in Navicat Monitor 3.A Quick Guide to Naming Conventions in SQL - Part 2.A Quick Guide to Naming Conventions in SQL - Part 3.Selecting Distinct Values From a Relational Database.Implement Audit Trail Logging Using Triggers.Multi-Version Concurrency Control in PostgreSQL.A Guide to MySQL Foreign Key Constraints.More than a way to count NULL and non-NULL values, when combined with other SQL function such as IF() and SUM(), these can be utilized to compile all sorts of statistics on your data! In today's blog, we learned how to combine NULLs with the SQL Count() function to achieve a variety of objectives. Here is the query and results in Navicat: Conclusion SELECT count(IF(country = 'Australia', 1, NULL)) as Australia_Count,Ĭount(IF(country = 'Germany', 1, NULL)) as Germany_Count,Ĭount(IF(country = 'Canada' OR country = 'USA', 1, NULL)) as North_America_Count,Ĭount(IF(country like 'F%', 1, NULL)) as F_Countries_Count,Ĭount(IF(creditLimit between 200000, 1, NULL)) as CreditLimit_Range_Count, The COUNTs then tabulate each row where the IFs evaluate to 1, i.e., where the predicate is true: If the predicate is false, it evaluates to the false-value, or NULL, as seen in the statement below. If the predicate is true, IF evaluates to the true-value, or 1 in the query below. That fact that the COUNT(Expression) version of the Count() function ignores Null expressions can be extremely helpful in compiling statistics about table data, especially when combined with other functions such as the SQL IF() function, which is basically the SQL equivalent of the Ternary Operator: Here is the above SELECT statement in Navicat Premium's Query Designer, along with the results:Īs expected, the addressLine2_Count and Null_addressLine2_Rows results add up to the All_Rows count. This query uses the Count() function in three ways to show all table rows, the number of populated addressLine2 rows and Nulls:ĬOUNT(addressLine2) AS addressLine2_Count,ĬOUNT(*) - COUNT(addressLine2) AS Null_addressLine2_Rows Hence, it's not required for all addresses, as we can see in this sample of table data: The addressline2 field contains additional address details that are not part of the street name and number. Here is that table in Navicat Premium's Table Designer: We'll run this query against the customers table of the MySQL classicmodels Sample Database. Now that we know how to count null, non-null, and all rows in a table, let's see an example. And that is by subtracting the non-NULL fields from the Total fields, like so: These two separate uses of Count() provide an important clue as to how we can obtain a count of NULL values for a specific column. Hence, if you provide a column name that allows NULL values, then Count() will return all rows that have a non-null value. The Count() function comes in two flavors: COUNT(*) returns all rows in the table, whereas COUNT(Expression) ignores Null expressions. In today's blog, we'll learn how to combine NULLs with the SQL Count() function to achieve a variety of objectives. That article also described how to allow NULLs in your database tables and how to reference them in queries. Null Values and the SQL Count() Function by Robert Gravelleīack in March of 2020, the The NULL Value and its Purpose in Relational Database Systems article presented the NULL value and its special meaning in relational databases.
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