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In SQL procedures, a cursor makes it possible to define a result set (a set of data rows) and perform complex logic on a row by row basis. By using the same mechanics, a SQL procedure can also define a result set and return it directly to the caller of the SQL procedure or to a client application.
Major DBMSs, including SQLite, [5] MySQL, [6] Oracle, [7] IBM Db2, [8] Microsoft SQL Server [9] and PostgreSQL [10] support prepared statements. Prepared statements are normally executed through a non-SQL binary protocol for efficiency and protection from SQL injection, but with some DBMSs such as MySQL prepared statements are also available using a SQL syntax for debugging purposes.
Example (using Python and SQLite): cursor.execute("SELECT * FROM users WHERE username = ? ... which then return the results. Stored procedures also require variable binding, which further enhances ...
A function is a subprogram written to perform certain computations. A scalar function returns only one value (or NULL), whereas a table function returns a (relational) table comprising zero or more rows, each row with one or more columns. Functions must return a value (using the RETURN keyword), but for stored procedures this is not mandatory.
Cursor-for loops automatically open a cursor, read in their data and close the cursor again. As an alternative, the PL/SQL programmer can pre-define the cursor's SELECT-statement in advance to (for example) allow re-use or make the code more understandable (especially useful in the case of long or complex queries).
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 ...
The next program uses a function pointer to invoke one of two functions (sin or cos) indirectly from another function (compute_sum, computing an approximation of the function's Riemann integration). The program operates by having function main call function compute_sum twice, passing it a pointer to the library function sin the first time, and ...
In addition, this approach requires high engineering efforts to implement flattening algorithms into a database engine. A general computational approach is to directly execute the nested loop by iterating all tuples of the correlated columns from the outer query block and executing the subquery as many times as the number of outer-loop tuples. [9]