For example, we cannot display in the output because it is not included in the GROUP BY clause. In the result set, we cannot use the non-aggregated columns in the SELECT statement. For this purpose, we use the SUM() and GROUP BY function as shown below. Let’s say we want to know the total orders value by location (City).
It has a column that specifies the customer city of where the order was placed. In this article, we will focus on exploring the SQL PARTITION BY clause.
Row or Range: You can further limit the rows in a partition by specifying the start and endpoints. Order By: This arranges the rows in ascending or descending order for the partition window. Partition By: This divides the rows or query result set into small partitions. The Window function uses the OVER() clause, and it can include the following functions: In this case, the Window function combined with the aggregate function helps achieve the desired output. Sometimes, we require aggregated values over a small set of rows. These functions operate on an entire table and return single aggregated data using the GROUP BY clause. Understanding the Window functionĭatabase users use aggregate functions such as MAX(), MIN(), AVERAGE() and COUNT() for performing data analysis. 
In this article, we will explore when and how to use the SQL PARTITION BY clause and compare it to using the GROUP BY clause.
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