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SELECT FIRST 10 * from T : Ingres: SELECT FIRST 10 * FROM T order by a : Informix: SELECT SKIP 20 FIRST 10 * FROM T order by c, d : Informix (row numbers are filtered after order by is evaluated. SKIP clause was introduced in a v10.00.xC4 fixpack) SELECT TOP 10 * FROM T: MS SQL Server, SAP ASE, MS Access, SAP IQ, Teradata
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. The table statistics does not update The number of rows in the table is higher than before, but table statistics haven't been updated yet. The ...
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.
SQL was initially developed at IBM by Donald D. Chamberlin and Raymond F. Boyce after learning about the relational model from Edgar F. Codd [12] in the early 1970s. [13] This version, initially called SEQUEL (Structured English Query Language), was designed to manipulate and retrieve data stored in IBM's original quasirelational database management system, System R, which a group at IBM San ...
A common table expression, or CTE, (in SQL) is a temporary named result set, derived from a simple query and defined within the execution scope of a SELECT, INSERT, UPDATE, or DELETE statement. CTEs can be thought of as alternatives to derived tables ( subquery ), views , and inline user-defined functions.
The INTERSECT operator removes duplicate rows from the final result set. The INTERSECT ALL operator does not remove duplicate rows from the final result set, but if a row appears X times in the first query and Y times in the second, it will appear (,) times in the result set.
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If a query contains GROUP BY, rows from the tables are grouped and aggregated. After the aggregating operation, HAVING is applied, filtering out the rows that don't match the specified conditions. Therefore, WHERE applies to data read from tables, and HAVING should only apply to aggregated data, which isn't known in the initial stage of a query.