SQL syntax
The syntax of the SQL programming language is defined and maintained by ISO/IEC SC 32 as part of ISO/IEC 9075. This standard is not freely available. Despite the existence of the standard, SQL code is not completely portable among different database systems without adjustments.
Language elements
The SQL language is subdivided into several language elements, including:
- Keywords are words that are defined in the SQL language. They are either reserved (e.g. <syntaxhighlight lang="text" class="" style="" inline="1">SELECT</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">COUNT</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">YEAR</syntaxhighlight>), or non-reserved (e.g. <syntaxhighlight lang="text" class="" style="" inline="1">ASC</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">DOMAIN</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">KEY</syntaxhighlight>). List of SQL reserved words.
- Identifiers are names on database objects, like tables, columns and schemas. An identifier may not be equal to a reserved keyword, unless it is a delimited identifier. Delimited identifiers means identifiers enclosed in double quotation marks. They can contain characters normally not supported in SQL identifiers, and they can be identical to a reserved word, e.g. a column named <syntaxhighlight lang="text" class="" style="" inline="1">YEAR</syntaxhighlight> is specified as <syntaxhighlight lang="text" class="" style="" inline="1">"YEAR"</syntaxhighlight>.
- In MySQL, double quotes are string literal delimiters by default instead. Enabling the <syntaxhighlight lang="text" class="" style="" inline="1">ansi_quotes</syntaxhighlight> SQL mode enforces the SQL standard behavior. These can also be used regardless of this mode through backticks: <syntaxhighlight lang="text" class="" style="" inline="1">`YEAR`</syntaxhighlight>.
- Clauses, which are constituent components of statements and queries. (In some cases, these are optional.)[1]
- Expressions, which can produce either scalar values, or tables consisting of columns and rows of data
- Predicates, which specify conditions that can be evaluated to SQL three-valued logic (3VL) (true/false/unknown) or Boolean truth values and are used to limit the effects of statements and queries, or to change program flow.
- Queries, which retrieve the data based on specific criteria. This is an important element of SQL.
- Statements, which may have a persistent effect on schemata and data, or may control transactions, program flow, connections, sessions, or diagnostics.
- SQL statements also include the semicolon (";") statement terminator. Though not required on every platform, it is defined as a standard part of the SQL grammar.
- Insignificant whitespace is generally ignored in SQL statements and queries, making it easier to format SQL code for readability.
Operators
Operator | Description | Example |
---|---|---|
=
|
Equal to | <syntaxhighlight lang="sql" class="" style="" inline="1">Author = 'Alcott'</syntaxhighlight> |
<>
|
Not equal to (many dialects also accept != )
|
<syntaxhighlight lang="sql" class="" style="" inline="1">Dept <> 'Sales'</syntaxhighlight> |
>
|
Greater than | <syntaxhighlight lang="sql" class="" style="" inline="1">Hire_Date > '2012-01-31'</syntaxhighlight> |
<
|
Less than | <syntaxhighlight lang="sql" class="" style="" inline="1">Bonus < 50000.00</syntaxhighlight> |
>=
|
Greater than or equal | <syntaxhighlight lang="sql" class="" style="" inline="1">Dependents >= 2</syntaxhighlight> |
<=
|
Less than or equal | <syntaxhighlight lang="sql" class="" style="" inline="1">Rate <= 0.05</syntaxhighlight> |
<syntaxhighlight lang="sql" class="" style="" inline="1">[NOT] BETWEEN [SYMMETRIC]</syntaxhighlight> | Between an inclusive range. SYMMETRIC inverts the range bounds if the first is higher than the second. | <syntaxhighlight lang="sql" class="" style="" inline="1">Cost BETWEEN 100.00 AND 500.00</syntaxhighlight> |
<syntaxhighlight lang="sql" class="" style="" inline="1">[NOT] LIKE [ESCAPE]</syntaxhighlight> | Begins with a character pattern | <syntaxhighlight lang="sql" class="" style="" inline="1">Full_Name LIKE 'Will%'</syntaxhighlight> |
Contains a character pattern | <syntaxhighlight lang="sql" class="" style="" inline="1">Full_Name LIKE '%Will%'</syntaxhighlight> | |
<syntaxhighlight lang="sql" class="" style="" inline="1">[NOT] IN</syntaxhighlight> | Equal to one of multiple possible values | <syntaxhighlight lang="sql" class="" style="" inline="1">DeptCode IN (101, 103, 209)</syntaxhighlight> |
<syntaxhighlight lang="sql" class="" style="" inline="1">IS [NOT] NULL</syntaxhighlight> | Compare to null (missing data) | <syntaxhighlight lang="sql" class="" style="" inline="1">Address IS NOT NULL</syntaxhighlight> |
<syntaxhighlight lang="sql" class="" style="" inline="1">IS [NOT] TRUE</syntaxhighlight> or <syntaxhighlight lang="sql" class="" style="" inline="1">IS [NOT] FALSE</syntaxhighlight> | Boolean truth value test | <syntaxhighlight lang="sql" class="" style="" inline="1">PaidVacation IS TRUE</syntaxhighlight> |
<syntaxhighlight lang="sql" class="" style="" inline="1">IS NOT DISTINCT FROM</syntaxhighlight> | Is equal to value or both are nulls (missing data) | <syntaxhighlight lang="sql" class="" style="" inline="1">Debt IS NOT DISTINCT FROM - Receivables</syntaxhighlight> |
<syntaxhighlight lang="sql" class="" style="" inline="1">AS</syntaxhighlight> | Used to change a column name when viewing results | <syntaxhighlight lang="sql" class="" style="" inline="1">SELECT employee AS department1</syntaxhighlight> |
Other operators have at times been suggested or implemented, such as the skyline operator (for finding only those rows that are not 'worse' than any others).
SQL has the <syntaxhighlight lang="text" class="" style="" inline="1">case</syntaxhighlight> expression, which was introduced in SQL-92. In its most general form, which is called a "searched case" in the SQL standard:
<syntaxhighlight lang="sql"> CASE WHEN n > 0
THEN 'positive' WHEN n < 0 THEN 'negative' ELSE 'zero'
END </syntaxhighlight>
SQL tests <syntaxhighlight lang="text" class="" style="" inline="1">WHEN</syntaxhighlight> conditions in the order they appear in the source. If the source does not specify an <syntaxhighlight lang="text" class="" style="" inline="1">ELSE</syntaxhighlight> expression, SQL defaults to <syntaxhighlight lang="text" class="" style="" inline="1">ELSE NULL</syntaxhighlight>. An abbreviated syntax called "simple case" can also be used:
<syntaxhighlight lang="sql"> CASE n WHEN 1
THEN 'One' WHEN 2 THEN 'Two' ELSE 'I cannot count that high'
END </syntaxhighlight>
This syntax uses implicit equality comparisons, with the usual caveats for comparing with NULL.
There are two short forms for special <syntaxhighlight lang="text" class="" style="" inline="1">CASE</syntaxhighlight> expressions: <syntaxhighlight lang="text" class="" style="" inline="1">COALESCE</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">NULLIF</syntaxhighlight>.
The <syntaxhighlight lang="text" class="" style="" inline="1">COALESCE</syntaxhighlight> expression returns the value of the first non-NULL operand, found by working from left to right, or NULL if all the operands equal NULL.
<syntaxhighlight lang="sql"> COALESCE(x1,x2) </syntaxhighlight> is equivalent to:
<syntaxhighlight lang="sql"> CASE WHEN x1 IS NOT NULL THEN x1
ELSE x2
END </syntaxhighlight>
The <syntaxhighlight lang="text" class="" style="" inline="1">NULLIF</syntaxhighlight> expression has two operands and returns NULL if the operands have the same value, otherwise it has the value of the first operand.
<syntaxhighlight lang="sql"> NULLIF(x1, x2) </syntaxhighlight>
is equivalent to <syntaxhighlight lang="sql"> CASE WHEN x1 = x2 THEN NULL ELSE x1 END </syntaxhighlight>
Comments
Standard SQL allows two formats for comments: <syntaxhighlight lang="text" class="" style="" inline="1">-- comment</syntaxhighlight>, which is ended by the first newline, and <syntaxhighlight lang="text" class="" style="" inline="1">/* comment */</syntaxhighlight>, which can span multiple lines.
Queries
The most common operation in SQL, the query, makes use of the declarative SELECT
statement. <syntaxhighlight lang="text" class="" style="" inline="1">SELECT</syntaxhighlight> retrieves data from one or more tables, or expressions. Standard <syntaxhighlight lang="text" class="" style="" inline="1">SELECT</syntaxhighlight> statements have no persistent effects on the database. Some non-standard implementations of <syntaxhighlight lang="text" class="" style="" inline="1">SELECT</syntaxhighlight> can have persistent effects, such as the <syntaxhighlight lang="text" class="" style="" inline="1">SELECT INTO</syntaxhighlight> syntax provided in some databases.[2]
Queries allow the user to describe desired data, leaving the database management system (DBMS) to carry out planning, optimizing, and performing the physical operations necessary to produce that result as it chooses.
A query includes a list of columns to include in the final result, normally immediately following the <syntaxhighlight lang="text" class="" style="" inline="1">SELECT</syntaxhighlight> keyword. An asterisk ("*
") can be used to specify that the query should return all columns of the queried tables. <syntaxhighlight lang="text" class="" style="" inline="1">SELECT</syntaxhighlight> is the most complex statement in SQL, with optional keywords and clauses that include:
- The
FROM
clause, which indicates the table(s) to retrieve data from. The <syntaxhighlight lang="text" class="" style="" inline="1">FROM</syntaxhighlight> clause can include optionalJOIN
subclauses to specify the rules for joining tables. - The
WHERE
clause includes a comparison predicate, which restricts the rows returned by the query. The <syntaxhighlight lang="text" class="" style="" inline="1">WHERE</syntaxhighlight> clause eliminates all rows from the result set where the comparison predicate does not evaluate to True. - The
GROUP BY
clause projects rows having common values into a smaller set of rows.[clarification needed] <syntaxhighlight lang="text" class="" style="" inline="1">GROUP BY</syntaxhighlight> is often used in conjunction with SQL aggregation functions or to eliminate duplicate rows from a result set. The <syntaxhighlight lang="text" class="" style="" inline="1">WHERE</syntaxhighlight> clause is applied before the <syntaxhighlight lang="text" class="" style="" inline="1">GROUP BY</syntaxhighlight> clause. - The
HAVING
clause includes a predicate used to filter rows resulting from the <syntaxhighlight lang="text" class="" style="" inline="1">GROUP BY</syntaxhighlight> clause. Because it acts on the results of the <syntaxhighlight lang="text" class="" style="" inline="1">GROUP BY</syntaxhighlight> clause, aggregation functions can be used in the <syntaxhighlight lang="text" class="" style="" inline="1">HAVING</syntaxhighlight> clause predicate. - The
ORDER BY
clause identifies which column[s] to use to sort the resulting data, and in which direction to sort them (ascending or descending). Without an <syntaxhighlight lang="text" class="" style="" inline="1">ORDER BY</syntaxhighlight> clause, the order of rows returned by an SQL query is undefined. - The
DISTINCT
keyword[3] eliminates duplicate data.[4] - The <syntaxhighlight lang="text" class="" style="" inline="1">OFFSET</syntaxhighlight> clause specifies the number of rows to skip before starting to return data.
- The <syntaxhighlight lang="text" class="" style="" inline="1">FETCH FIRST</syntaxhighlight> clause specifies the number of rows to return. Some SQL databases instead have non-standard alternatives, e.g. <syntaxhighlight lang="text" class="" style="" inline="1">LIMIT</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">TOP</syntaxhighlight> or <syntaxhighlight lang="text" class="" style="" inline="1">ROWNUM</syntaxhighlight>.
The clauses of a query have a particular order of execution,[5] which is denoted by the number on the right hand side. It is as follows:
SELECT <columns> |
5. |
FROM <table> |
1. |
WHERE <predicate on rows> |
2. |
GROUP BY <columns> |
3. |
HAVING <predicate on groups> |
4. |
ORDER BY <columns> |
6. |
OFFSET |
7. |
FETCH FIRST |
8. |
The following example of a <syntaxhighlight lang="text" class="" style="" inline="1">SELECT</syntaxhighlight> query returns a list of expensive books. The query retrieves all rows from the Book table in which the price column contains a value greater than 100.00. The result is sorted in ascending order by title. The asterisk (*) in the select list indicates that all columns of the Book table should be included in the result set.
<syntaxhighlight lang="sql"> SELECT *
FROM Book WHERE price > 100.00 ORDER BY title;
</syntaxhighlight>
The example below demonstrates a query of multiple tables, grouping, and aggregation, by returning a list of books and the number of authors associated with each book.
<syntaxhighlight lang="sql"> SELECT Book.title AS Title,
count(*) AS Authors FROM Book JOIN Book_author ON Book.isbn = Book_author.isbn GROUP BY Book.title;
</syntaxhighlight>
Example output might resemble the following:
Title Authors ---------------------- ------- SQL Examples and Guide 4 The Joy of SQL 1 An Introduction to SQL 2 Pitfalls of SQL 1
Under the precondition that isbn is the only common column name of the two tables and that a column named title only exists in the Book table, one could re-write the query above in the following form:
<syntaxhighlight lang="sql"> SELECT title,
count(*) AS Authors FROM Book NATURAL JOIN Book_author GROUP BY title;
</syntaxhighlight>
However, many[quantify] vendors either do not support this approach, or require certain column-naming conventions for natural joins to work effectively.
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.
<syntaxhighlight lang="sql"> SELECT isbn,
title, price, price * 0.06 AS sales_tax FROM Book WHERE price > 100.00 ORDER BY title;
</syntaxhighlight>
Subqueries
Queries can be nested so that the results of one query can be used in another query via a relational operator or aggregation function. A nested query is also known as a subquery. While joins and other table operations provide computationally superior (i.e. faster) alternatives in many cases, the use of subqueries introduces a hierarchy in execution that can be useful or necessary. In the following example, the aggregation function <syntaxhighlight lang="text" class="" style="" inline="1">AVG</syntaxhighlight> receives as input the result of a subquery:
<syntaxhighlight lang="sql"> SELECT isbn,
title, price FROM Book WHERE price < (SELECT AVG(price) FROM Book) ORDER BY title;
</syntaxhighlight>
A subquery can use values from the outer query, in which case it is known as a correlated subquery.
Since 1999 the SQL standard allows <syntaxhighlight lang="text" class="" style="" inline="1">WITH</syntaxhighlight> clauses for subqueries, i.e. named subqueries, usually called common table expressions (also called subquery factoring). CTEs can also be recursive by referring to themselves; the resulting mechanism allows tree or graph traversals (when represented as relations), and more generally fixpoint computations.
Derived table
A derived table is the use of referencing an SQL subquery in a FROM clause. Essentially, the derived table is a subquery that can be selected from or joined to. The derived table functionality allows the user to reference the subquery as a table. The derived table is sometimes referred to as an inline view or a subselect.
In the following example, the SQL statement involves a join from the initial "Book" table to the derived table "sales". This derived table captures associated book sales information using the ISBN to join to the "Book" table. As a result, the derived table provides the result set with additional columns (the number of items sold and the company that sold the books):
<syntaxhighlight lang="sql"> SELECT b.isbn, b.title, b.price, sales.items_sold, sales.company_nm FROM Book b
JOIN (SELECT SUM(Items_Sold) Items_Sold, Company_Nm, ISBN FROM Book_Sales GROUP BY Company_Nm, ISBN) sales ON sales.isbn = b.isbn
</syntaxhighlight>
Null or three-valued logic (3VL)
The concept of Null allows SQL to deal with missing information in the relational model. The word <syntaxhighlight lang="text" class="" style="" inline="1">NULL</syntaxhighlight> is a reserved keyword in SQL, used to identify the Null special marker. Comparisons with Null, for instance equality (=) in WHERE clauses, results in an Unknown truth value. In SELECT statements SQL returns only results for which the WHERE clause returns a value of True; i.e., it excludes results with values of False and also excludes those whose value is Unknown.
Along with True and False, the Unknown resulting from direct comparisons with Null thus brings a fragment of three-valued logic to SQL. The truth tables SQL uses for AND, OR, and NOT correspond to a common fragment of the Kleene and Lukasiewicz three-valued logic (which differ in their definition of implication, however SQL defines no such operation).[6]
|
|
|
|
There are however disputes about the semantic interpretation of Nulls in SQL because of its treatment outside direct comparisons. As seen in the table above, direct equality comparisons between two NULLs in SQL (e.g. <syntaxhighlight lang="text" class="" style="" inline="1">NULL = NULL</syntaxhighlight>) return a truth value of Unknown. This is in line with the interpretation that Null does not have a value (and is not a member of any data domain) but is rather a placeholder or "mark" for missing information. However, the principle that two Nulls aren't equal to each other is effectively violated in the SQL specification for the <syntaxhighlight lang="text" class="" style="" inline="1">UNION</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">INTERSECT</syntaxhighlight> operators, which do identify nulls with each other.[7] Consequently, these set operations in SQL may produce results not representing sure information, unlike operations involving explicit comparisons with NULL (e.g. those in a <syntaxhighlight lang="text" class="" style="" inline="1">WHERE</syntaxhighlight> clause discussed above). In Codd's 1979 proposal (which was basically adopted by SQL92) this semantic inconsistency is rationalized by arguing that removal of duplicates in set operations happens "at a lower level of detail than equality testing in the evaluation of retrieval operations".[6] However, computer-science professor Ron van der Meyden concluded that "The inconsistencies in the SQL standard mean that it is not possible to ascribe any intuitive logical semantics to the treatment of nulls in SQL."[7]
Additionally, because SQL operators return Unknown when comparing anything with Null directly, SQL provides two Null-specific comparison predicates: <syntaxhighlight lang="text" class="" style="" inline="1">IS NULL</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">IS NOT NULL</syntaxhighlight> test whether data is or is not Null.[8] SQL does not explicitly support universal quantification, and must work it out as a negated existential quantification.[9][10][11] There is also the <syntaxhighlight lang="text" class="" style="" inline="1"><row value expression> IS DISTINCT FROM <row value expression></syntaxhighlight> infixed comparison operator, which returns TRUE unless both operands are equal or both are NULL. Likewise, IS NOT DISTINCT FROM is defined as <syntaxhighlight lang="text" class="" style="" inline="1">NOT (<row value expression> IS DISTINCT FROM <row value expression>)</syntaxhighlight>. SQL:1999 also introduced <syntaxhighlight lang="text" class="" style="" inline="1">BOOLEAN</syntaxhighlight> type variables, which according to the standard can also hold Unknown values if it is nullable. In practice, a number of systems (e.g. PostgreSQL) implement the BOOLEAN Unknown as a BOOLEAN NULL, which the standard says that the NULL BOOLEAN and UNKNOWN "may be used interchangeably to mean exactly the same thing".[12][13]
Data manipulation
The Data Manipulation Language (DML) is the subset of SQL used to add, update and delete data:
<syntaxhighlight lang="sql"> INSERT INTO example
(column1, column2, column3) VALUES ('test', 'N', NULL);
</syntaxhighlight>
UPDATE
modifies a set of existing table rows, e.g.:
<syntaxhighlight lang="sql"> UPDATE example
SET column1 = 'updated value' WHERE column2 = 'N';
</syntaxhighlight>
DELETE
removes existing rows from a table, e.g.:
<syntaxhighlight lang="sql"> DELETE FROM example
WHERE column2 = 'N';
</syntaxhighlight>
MERGE
is used to combine the data of multiple tables. It combines the <syntaxhighlight lang="text" class="" style="" inline="1">INSERT</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">UPDATE</syntaxhighlight> elements. It is defined in the SQL:2003 standard; prior to that, some databases provided similar functionality via different syntax, sometimes called "upsert".
<syntaxhighlight lang="sql">
MERGE INTO table_name USING table_reference ON (condition) WHEN MATCHED THEN UPDATE SET column1 = value1 [, column2 = value2 ...] WHEN NOT MATCHED THEN INSERT (column1 [, column2 ...]) VALUES (value1 [, value2 ...])
</syntaxhighlight>
Transaction controls
Transactions, if available, wrap DML operations:
- <syntaxhighlight lang="text" class="" style="" inline="1">START TRANSACTION</syntaxhighlight> (or <syntaxhighlight lang="text" class="" style="" inline="1">BEGIN WORK</syntaxhighlight>, or <syntaxhighlight lang="text" class="" style="" inline="1">BEGIN TRANSACTION</syntaxhighlight>, depending on SQL dialect) marks the start of a database transaction, which either completes entirely or not at all.
- <syntaxhighlight lang="text" class="" style="" inline="1">SAVE TRANSACTION</syntaxhighlight> (or <syntaxhighlight lang="text" class="" style="" inline="1">SAVEPOINT</syntaxhighlight>) saves the state of the database at the current point in transaction
<syntaxhighlight lang="postgresql"> CREATE TABLE tbl_1(id int);
INSERT INTO tbl_1(id) VALUES(1); INSERT INTO tbl_1(id) VALUES(2);
COMMIT;
UPDATE tbl_1 SET id=200 WHERE id=1;
SAVEPOINT id_1upd;
UPDATE tbl_1 SET id=1000 WHERE id=2;
ROLLBACK to id_1upd;
SELECT id from tbl_1;
</syntaxhighlight>
COMMIT
makes all data changes in a transaction permanent.ROLLBACK
discards all data changes since the last <syntaxhighlight lang="text" class="" style="" inline="1">COMMIT</syntaxhighlight> or <syntaxhighlight lang="text" class="" style="" inline="1">ROLLBACK</syntaxhighlight>, leaving the data as it was prior to those changes. Once the <syntaxhighlight lang="text" class="" style="" inline="1">COMMIT</syntaxhighlight> statement completes, the transaction's changes cannot be rolled back.
<syntaxhighlight lang="text" class="" style="" inline="1">COMMIT</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">ROLLBACK</syntaxhighlight> terminate the current transaction and release data locks. In the absence of a <syntaxhighlight lang="text" class="" style="" inline="1">START TRANSACTION</syntaxhighlight> or similar statement, the semantics of SQL are implementation-dependent. The following example shows a classic transfer of funds transaction, where money is removed from one account and added to another. If either the removal or the addition fails, the entire transaction is rolled back.
<syntaxhighlight lang="plpgsql"> START TRANSACTION;
UPDATE Account SET amount=amount-200 WHERE account_number=1234; UPDATE Account SET amount=amount+200 WHERE account_number=2345;
IF ERRORS=0 COMMIT; IF ERRORS<>0 ROLLBACK; </syntaxhighlight>
Data definition
The Data Definition Language (DDL) manages table and index structure. The most basic items of DDL are the <syntaxhighlight lang="text" class="" style="" inline="1">CREATE</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">ALTER</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">RENAME</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">DROP</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">TRUNCATE</syntaxhighlight> statements:
CREATE
creates an object (a table, for example) in the database, e.g.:
<syntaxhighlight lang="sql"> CREATE TABLE example(
column1 INTEGER, column2 VARCHAR(50), column3 DATE NOT NULL, PRIMARY KEY (column1, column2)
); </syntaxhighlight>
ALTER
modifies the structure of an existing object in various ways, for example, adding a column to an existing table or a constraint, e.g.:
<syntaxhighlight lang="sql"> ALTER TABLE example ADD column4 INTEGER DEFAULT 25 NOT NULL; </syntaxhighlight>
TRUNCATE
deletes all data from a table in a very fast way, deleting the data inside the table and not the table itself. It usually implies a subsequent COMMIT operation, i.e., it cannot be rolled back (data is not written to the logs for rollback later, unlike DELETE).
<syntaxhighlight lang="sql"> TRUNCATE TABLE example; </syntaxhighlight>
DROP
deletes an object in the database, usually irretrievably, i.e., it cannot be rolled back, e.g.:
<syntaxhighlight lang="sql"> DROP TABLE example; </syntaxhighlight>
Data types
Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following data types.[14]
- Character strings and national character strings
CHARACTER(n)
(orCHAR(n)
): fixed-width n-character string, padded with spaces as neededCHARACTER VARYING(n)
(orVARCHAR(n)
): variable-width string with a maximum size of n charactersCHARACTER LARGE OBJECT(n [ K | M | G | T ])
(orCLOB(n [ K | M | G | T ])
): character large object with a maximum size of n [ K | M | G | T ] charactersNATIONAL CHARACTER(n)
(orNCHAR(n)
): fixed width string supporting an international character setNATIONAL CHARACTER VARYING(n)
(orNVARCHAR(n)
): variable-widthNCHAR
stringNATIONAL CHARACTER LARGE OBJECT(n [ K | M | G | T ])
(orNCLOB(n [ K | M | G | T ])
): national character large object with a maximum size of n [ K | M | G | T ] characters
For the <syntaxhighlight lang="text" class="" style="" inline="1">CHARACTER LARGE OBJECT</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">NATIONAL CHARACTER LARGE OBJECT</syntaxhighlight> data types, the multipliers <syntaxhighlight lang="text" class="" style="" inline="1">K</syntaxhighlight> (1 024), <syntaxhighlight lang="text" class="" style="" inline="1">M</syntaxhighlight> (1 048 576), <syntaxhighlight lang="text" class="" style="" inline="1">G</syntaxhighlight> (1 073 741 824) and <syntaxhighlight lang="text" class="" style="" inline="1">T</syntaxhighlight> (1 099 511 627 776) can be optionally used when specifying the length.
- Binary
BINARY(n)
: Fixed length binary string, maximum length n.BINARY VARYING(n)
(orVARBINARY(n)
): Variable length binary string, maximum length n.BINARY LARGE OBJECT(n [ K | M | G | T ])
(orBLOB(n [ K | M | G | T ])
): binary large object with a maximum length n [ K | M | G | T ].
For the <syntaxhighlight lang="text" class="" style="" inline="1">BINARY LARGE OBJECT</syntaxhighlight> data type, the multipliers <syntaxhighlight lang="text" class="" style="" inline="1">K</syntaxhighlight> (1 024), <syntaxhighlight lang="text" class="" style="" inline="1">M</syntaxhighlight> (1 048 576), <syntaxhighlight lang="text" class="" style="" inline="1">G</syntaxhighlight> (1 073 741 824) and <syntaxhighlight lang="text" class="" style="" inline="1">T</syntaxhighlight> (1 099 511 627 776) can be optionally used when specifying the length.
- Boolean
- <syntaxhighlight lang="text" class="" style="" inline="1">BOOLEAN</syntaxhighlight>
The <syntaxhighlight lang="text" class="" style="" inline="1">BOOLEAN</syntaxhighlight> data type can store the values <syntaxhighlight lang="text" class="" style="" inline="1">TRUE</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">FALSE</syntaxhighlight>.
- Numerical
- <syntaxhighlight lang="text" class="" style="" inline="1">INTEGER</syntaxhighlight> (or <syntaxhighlight lang="text" class="" style="" inline="1">INT</syntaxhighlight>), <syntaxhighlight lang="text" class="" style="" inline="1">SMALLINT</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">BIGINT</syntaxhighlight>
- <syntaxhighlight lang="text" class="" style="" inline="1">FLOAT</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">REAL</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">DOUBLE PRECISION</syntaxhighlight>
NUMERIC(precision, scale)
orDECIMAL(precision, scale)
DECFLOAT(precision
)
For example, the number 123.45 has a precision of 5 and a scale of 2. The precision is a positive integer that determines the number of significant digits in a particular radix (binary or decimal). The scale is a non-negative integer. A scale of 0 indicates that the number is an integer. For a decimal number with scale S, the exact numeric value is the integer value of the significant digits divided by 10S.
SQL provides the functions <syntaxhighlight lang="text" class="" style="" inline="1">CEILING</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">FLOOR</syntaxhighlight> to round numerical values. (Popular vendor specific functions are <syntaxhighlight lang="text" class="" style="" inline="1">TRUNC</syntaxhighlight> (Informix, DB2, PostgreSQL, Oracle and MySQL) and <syntaxhighlight lang="text" class="" style="" inline="1">ROUND</syntaxhighlight> (Informix, SQLite, Sybase, Oracle, PostgreSQL, Microsoft SQL Server and Mimer SQL.))
- Temporal (datetime)
- <syntaxhighlight lang="text" class="" style="" inline="1">DATE</syntaxhighlight>: for date values (e.g. <syntaxhighlight lang="text" class="" style="" inline="1">2011-05-03</syntaxhighlight>).
- <syntaxhighlight lang="text" class="" style="" inline="1">TIME</syntaxhighlight>: for time values (e.g. <syntaxhighlight lang="text" class="" style="" inline="1">15:51:36</syntaxhighlight>).
- <syntaxhighlight lang="text" class="" style="" inline="1">TIME WITH TIME ZONE</syntaxhighlight>: the same as <syntaxhighlight lang="text" class="" style="" inline="1">TIME</syntaxhighlight>, but including details about the time zone in question.
- <syntaxhighlight lang="text" class="" style="" inline="1">TIMESTAMP</syntaxhighlight>: This is a <syntaxhighlight lang="text" class="" style="" inline="1">DATE</syntaxhighlight> and a <syntaxhighlight lang="text" class="" style="" inline="1">TIME</syntaxhighlight> put together in one variable (e.g. <syntaxhighlight lang="text" class="" style="" inline="1">2011-05-03 15:51:36.123456</syntaxhighlight>).
- <syntaxhighlight lang="text" class="" style="" inline="1">TIMESTAMP WITH TIME ZONE</syntaxhighlight>: the same as <syntaxhighlight lang="text" class="" style="" inline="1">TIMESTAMP</syntaxhighlight>, but including details about the time zone in question.
The SQL function <syntaxhighlight lang="text" class="" style="" inline="1">EXTRACT</syntaxhighlight> can be used for extracting a single field (seconds, for instance) of a datetime or interval value. The current system date / time of the database server can be called by using functions like <syntaxhighlight lang="text" class="" style="" inline="1">CURRENT_DATE</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">CURRENT_TIMESTAMP</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">LOCALTIME</syntaxhighlight>, or <syntaxhighlight lang="text" class="" style="" inline="1">LOCALTIMESTAMP</syntaxhighlight>. (Popular vendor specific functions are <syntaxhighlight lang="text" class="" style="" inline="1">TO_DATE</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">TO_TIME</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">TO_TIMESTAMP</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">YEAR</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">MONTH</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">DAY</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">HOUR</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">MINUTE</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">SECOND</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">DAYOFYEAR</syntaxhighlight>, <syntaxhighlight lang="text" class="" style="" inline="1">DAYOFMONTH</syntaxhighlight> and <syntaxhighlight lang="text" class="" style="" inline="1">DAYOFWEEK</syntaxhighlight>.)
- Interval (datetime)
YEAR(precision)
: a number of yearsYEAR(precision) TO MONTH
: a number of years and monthsMONTH(precision)
: a number of monthsDAY(precision)
: a number of daysDAY(precision) TO HOUR
: a number of days and hoursDAY(precision) TO MINUTE
: a number of days, hours and minutesDAY(precision) TO SECOND(scale)
: a number of days, hours, minutes and secondsHOUR(precision)
: a number of hoursHOUR(precision) TO MINUTE
: a number of hours and minutesHOUR(precision) TO SECOND(scale)
: a number of hours, minutes and secondsMINUTE(precision)
: a number of minutesMINUTE(precision) TO SECOND(scale)
: a number of minutes and seconds
Data control
The Data Control Language (DCL) authorizes users to access and manipulate data. Its two main statements are:
- <syntaxhighlight lang="text" class="" style="" inline="1">GRANT</syntaxhighlight> authorizes one or more users to perform an operation or a set of operations on an object.
- <syntaxhighlight lang="text" class="" style="" inline="1">REVOKE</syntaxhighlight> eliminates a grant, which may be the default grant.
Example:
<syntaxhighlight lang="sql"> GRANT SELECT, UPDATE
ON example TO some_user, another_user;
REVOKE SELECT, UPDATE
ON example FROM some_user, another_user;
</syntaxhighlight>
Notes
References
- ^ ANSI/ISO/IEC International Standard (IS). Database Language SQL—Part 2: Foundation (SQL/Foundation). 1999.
- ^ "Transact-SQL Reference". SQL Server Language Reference. SQL Server 2005 Books Online. Microsoft. 2007-09-15. Retrieved 2007-06-17.
- ^
SAS 9.4 SQL Procedure User's Guide. SAS Institute. 2013. p. 248. ISBN 9781612905686. Retrieved 2015-10-21.
Although the UNIQUE argument is identical to DISTINCT, it is not an ANSI standard.
- ^
Leon, Alexis; Leon, Mathews (1999). "Eliminating duplicates - SELECT using DISTINCT". SQL: A Complete Reference. New Delhi: Tata McGraw-Hill Education (published 2008). p. 143. ISBN 9780074637081. Retrieved 2015-10-21.
[...] the keyword DISTINCT [...] eliminates the duplicates from the result set.
- ^ "What Is The Order Of Execution Of An SQL Query? - Designcise.com". www.designcise.com. 29 June 2015. Retrieved 2018-02-04.
- ^ 6.0 6.1 Hans-Joachim, K. (2003). "Null Values in Relational Databases and Sure Information Answers". Semantics in Databases. Second International Workshop Dagstuhl Castle, Germany, January 7–12, 2001. Revised Papers. Lecture Notes in Computer Science. Vol. 2582. pp. 119–138. doi:10.1007/3-540-36596-6_7. ISBN 978-3-540-00957-3.
- ^ 7.0 7.1 Ron van der Meyden, "Logical approaches to incomplete information: a survey" in Chomicki, Jan; Saake, Gunter (Eds.) Logics for Databases and Information Systems, Kluwer Academic Publishers ISBN 978-0-7923-8129-7, p. 344
- ^ ISO/IEC. ISO/IEC 9075-2:2003, "SQL/Foundation". ISO/IEC.
- ^ Negri, M.; Pelagatti, G.; Sbattella, L. (February 1989). "Semantics and problems of universal quantification in SQL". The Computer Journal. 32 (1): 90–91. doi:10.1093/comjnl/32.1.90. Retrieved 2017-01-16.
- ^ Fratarcangeli, Claudio (1991). "Technique for universal quantification in SQL". ACM SIGMOD Record. 20 (3): 16–24. doi:10.1145/126482.126484. S2CID 18326990. Retrieved 2017-01-16.
- ^ Kawash, Jalal (2004) Complex quantification in Structured Query Language (SQL): a tutorial using relational calculus; Journal of Computers in Mathematics and Science Teaching ISSN 0731-9258 Volume 23, Issue 2, 2004 AACE Norfolk, Virginia. Thefreelibrary.com
- ^ C. Date (2011). SQL and Relational Theory: How to Write Accurate SQL Code. O'Reilly Media, Inc. p. 83. ISBN 978-1-4493-1640-2.
- ^ ISO/IEC 9075-2:2011 §4.5
- ^ "ISO/IEC 9075-1:2016: Information technology – Database languages – SQL – Part 1: Framework (SQL/Framework)".
External links
- "Definition of SQL grammar", ISO_IEC_9075-2(E)_Foundation.bnf.xml (Backus–Naur form XML), ISO Standards Maintenance Portal.
- "Online SQL Formating Utility", Online SQL Formatter Utility.
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