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Deleting all rows from a table can be very time-consuming. Some DBMS [clarification needed] offer a TRUNCATE TABLE command that works a lot quicker, as it only alters metadata and typically does not spend time enforcing constraints or firing triggers. DELETE only deletes the rows. For deleting a table entirely the DROP command can be used.
For example, no two persons can have the same social security number. Set-Membership constraints: The values for a column come from a set of discrete values or codes. For example, a person's sex may be Female, Male or Non-Binary. Foreign-key constraints: This is the more general case of set membership. The set of values in a column is defined ...
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 ...
In SQL, NULL is a reserved word used to identify this marker. A null should not be confused with a value of 0. A null indicates a lack of a value, which is not the same as a zero value. For example, consider the question "How many books does Adam own?" The answer may be "zero" (we know that he owns none) or "null" (we do not know how many he owns).
The DROP statement is distinct from the DELETE and TRUNCATE statements, in that DELETE and TRUNCATE do not remove the table itself. For example, a DELETE statement might delete some (or all) data from a table while leaving the table itself in the database, whereas a DROP statement removes the entire table from the database.
SQL Server has limitations on row size if attempting to change the storage format of a column: the total contents of all atomic-datatype columns, sparse and non-sparse, in a row that contain data cannot exceed 8016 bytes if that table contains a sparse column for the data to be automatically copied over.
The programming model becomes what a SQL statement would be like with multiple WHERE clauses. The combination of list-aware subjects and objects plus a pipeline approach can yield extremely expressive queries spanning many different domains of data. Here is a more comprehensive example that illustrates the pipeline using some syntax shortcuts.
MS-DOS, for example, used a simple File Allocation Table (FAT). The FAT has an entry for each disk block, [note 1] and that entry identifies whether its block is used by a file and if so, which block (if any) is the next disk block of the same file. So, the allocation of each file is represented as a linked list in the table.