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A GROUP BY statement in SQL specifies that a SQL SELECT statement partitions result rows into groups, based on their values in one or several columns. Typically, grouping is used to apply some sort of aggregate function for each group. [1] [2] The result of a query using a GROUP BY statement contains one row for
The SELECT statement has many optional clauses: SELECT list is the list of columns or SQL expressions to be returned by the query. This is approximately the relational algebra projection operation. AS optionally provides an alias for each column or expression in the SELECT list. This is the relational algebra rename operation.
The input and output domains may be the same, such as for SUM, or may be different, such as for COUNT. Aggregate functions occur commonly in numerous programming languages, in spreadsheets, and in relational algebra. The listagg function, as defined in the SQL:2016 standard [2] aggregates data from multiple rows into a single concatenated string.
SQL includes operators and functions for calculating values on stored values. SQL allows the use of expressions in the select list to project data, as in the following example, which returns a list of books that cost more than 100.00 with an additional sales_tax column containing a sales tax figure calculated at 6% of the price.
When query processed SELECT COUNT(*), nulls existed in the column The query is counting the number of null columns in a typical index. However, SELECT COUNT(*) can't count the number of null columns. The query is unselective The number of return rows is too large and takes nearly 100% in the whole table. These rows are unselective.
SELECT DeptID, SUM (SaleAmount) FROM Sales WHERE SaleDate = '2000-01-01' GROUP BY DeptID HAVING SUM (SaleAmount) > 1000 Referring to the sample tables in the Join example , the following query will return the list of departments which have more than 1 employee:
T1 = SUMMARY(EMP, GROUP(DEPTNUM), EMPS=COUNT, SALSUM=SUM(SALARY)) T2 = JOIN(T1, DEPT) T3 = SELECT(T2, SALSUM > BUDGET) Note the "natural join" on the common column, DEPTNUM. Although some SQL dialects support natural joins, for familiarity, the example will show only a "traditional" join. Here is the equivalent SQL for comparison:
In SQL, a window function or analytic function [1] is a function which uses values from one or multiple rows to return a value for each row. (This contrasts with an aggregate function, which returns a single value for multiple rows.) Window functions have an OVER clause; any function without an OVER clause is not a window function, but rather ...