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.
The SQL language is subdivided into several language elements, including:
SELECT
COUNT
YEAR
ASC
DOMAIN
KEY
"YEAR"
ansi_quotes
`YEAR`
=
Author = 'Alcott'
<>
!=
Dept <> 'Sales'
>
Hire_Date > '2012-01-31'
<
Bonus < 50000.00
>=
Dependents >= 2
<=
Rate <= 0.05
[NOT] BETWEEN [SYMMETRIC]
Cost BETWEEN 100.00 AND 500.00
[NOT] LIKE [ESCAPE]
Full_Name LIKE 'Will%'
Full_Name LIKE '%Will%'
[NOT] IN
DeptCode IN (101, 103, 209)
IS [NOT] NULL
Address IS NOT NULL
IS [NOT] TRUE
IS [NOT] FALSE
PaidVacation IS TRUE
IS NOT DISTINCT FROM
Debt IS NOT DISTINCT FROM - Receivables
AS
SELECT employee AS department1
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 case expression, which was introduced in SQL-92. In its most general form, which is called a "searched case" in the SQL standard:
case
CASE WHEN n > 0 THEN 'positive' WHEN n < 0 THEN 'negative' ELSE 'zero' END
SQL tests WHEN conditions in the order they appear in the source. If the source does not specify an ELSE expression, SQL defaults to ELSE NULL. An abbreviated syntax called "simple case" can also be used:
WHEN
ELSE
ELSE NULL
CASE n WHEN 1 THEN 'One' WHEN 2 THEN 'Two' ELSE 'I cannot count that high' END
This syntax uses implicit equality comparisons, with the usual caveats for comparing with NULL.
There are two short forms for special CASE expressions: COALESCE and NULLIF.
CASE
COALESCE
NULLIF
The COALESCE 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.
COALESCE(x1,x2)
is equivalent to:
CASE WHEN x1 IS NOT NULL THEN x1 ELSE x2 END
The NULLIF expression has two operands and returns NULL if the operands have the same value, otherwise it has the value of the first operand.
NULLIF(x1, x2)
is equivalent to
CASE WHEN x1 = x2 THEN NULL ELSE x1 END
Standard SQL allows two formats for comments: -- comment, which is ended by the first newline, and /* comment */, which can span multiple lines.
-- comment
/* comment */
The most common operation in SQL, the query, makes use of the declarative SELECT statement. SELECT retrieves data from one or more tables, or expressions. Standard SELECT statements have no persistent effects on the database. Some non-standard implementations of SELECT can have persistent effects, such as the SELECT INTO syntax provided in some databases.[2]
SELECT INTO
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 SELECT keyword. An asterisk ("*") can be used to specify that the query should return all columns of the queried tables. SELECT is the most complex statement in SQL, with optional keywords and clauses that include:
*
FROM
JOIN
WHERE
GROUP BY
HAVING
ORDER BY
DISTINCT
OFFSET
FETCH FIRST
LIMIT
TOP
ROWNUM
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>
FROM <table>
WHERE <predicate on rows>
GROUP BY <columns>
HAVING <predicate on groups>
ORDER BY <columns>
The following example of a SELECT 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.
SELECT * FROM Book WHERE price > 100.00 ORDER BY title;
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.
SELECT Book.title AS Title, count(*) AS Authors FROM Book JOIN Book_author ON Book.isbn = Book_author.isbn GROUP BY Book.title;
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:
SELECT title, count(*) AS Authors FROM Book NATURAL JOIN Book_author GROUP BY title;
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.
SELECT isbn, title, price, price * 0.06 AS sales_tax FROM Book WHERE price > 100.00 ORDER BY title;
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 AVG receives as input the result of a subquery:
AVG
SELECT isbn, title, price FROM Book WHERE price < (SELECT AVG(price) FROM Book) ORDER BY title;
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 WITH 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.
WITH
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):
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
The concept of Null allows SQL to deal with missing information in the relational model. The word NULL 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.
NULL
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. NULL = NULL) 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 UNION and INTERSECT 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 WHERE 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]
NULL = NULL
UNION
INTERSECT
Additionally, because SQL operators return Unknown when comparing anything with Null directly, SQL provides two Null-specific comparison predicates: IS NULL and IS NOT NULL 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 <row value expression> IS DISTINCT FROM <row value expression> infixed comparison operator, which returns TRUE unless both operands are equal or both are NULL. Likewise, IS NOT DISTINCT FROM is defined as NOT (<row value expression> IS DISTINCT FROM <row value expression>). SQL:1999 also introduced BOOLEAN 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]
IS NULL
IS NOT NULL
<row value expression> IS DISTINCT FROM <row value expression>
NOT (<row value expression> IS DISTINCT FROM <row value expression>)
BOOLEAN
The Data Manipulation Language (DML) is the subset of SQL used to add, update and delete data:
INSERT
INSERT INTO example (column1, column2, column3) VALUES ('test', 'N', NULL);
UPDATE
UPDATE example SET column1 = 'updated value' WHERE column2 = 'N';
DELETE
DELETE FROM example WHERE column2 = 'N';
MERGE
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 ...])
Transactions, if available, wrap DML operations:
START TRANSACTION
BEGIN WORK
BEGIN TRANSACTION
SAVE TRANSACTION
SAVEPOINT
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;
COMMIT
ROLLBACK
COMMIT and ROLLBACK terminate the current transaction and release data locks. In the absence of a START TRANSACTION 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.
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;
The Data Definition Language (DDL) manages table and index structure. The most basic items of DDL are the CREATE, ALTER, RENAME, DROP and TRUNCATE statements:
CREATE
ALTER
RENAME
DROP
TRUNCATE
CREATE TABLE example( column1 INTEGER, column2 VARCHAR(50), column3 DATE NOT NULL, PRIMARY KEY (column1, column2) );
ALTER TABLE example ADD column4 INTEGER DEFAULT 25 NOT NULL;
TRUNCATE TABLE example;
DROP TABLE example;
Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following data types.[14]
CHARACTER(n)
CHAR(n)
CHARACTER VARYING(n)
VARCHAR(n)
CHARACTER LARGE OBJECT(n [ K | M | G | T ])
CLOB(n [ K | M | G | T ])
NATIONAL CHARACTER(n)
NCHAR(n)
NATIONAL CHARACTER VARYING(n)
NVARCHAR(n)
NCHAR
NATIONAL CHARACTER LARGE OBJECT(n [ K | M | G | T ])
NCLOB(n [ K | M | G | T ])
For the CHARACTER LARGE OBJECT and NATIONAL CHARACTER LARGE OBJECT data types, the multipliers K (1 024), M (1 048 576), G (1 073 741 824) and T (1 099 511 627 776) can be optionally used when specifying the length.
CHARACTER LARGE OBJECT
NATIONAL CHARACTER LARGE OBJECT
K
M
G
T
BINARY(n)
BINARY VARYING(n)
VARBINARY(n)
BINARY LARGE OBJECT(n [ K | M | G | T ])
BLOB(n [ K | M | G | T ])
For the BINARY LARGE OBJECT data type, the multipliers K (1 024), M (1 048 576), G (1 073 741 824) and T (1 099 511 627 776) can be optionally used when specifying the length.
BINARY LARGE OBJECT
The BOOLEAN data type can store the values TRUE and FALSE.
TRUE
FALSE
INTEGER
INT
SMALLINT
BIGINT
FLOAT
REAL
DOUBLE PRECISION
NUMERIC(precision, scale)
DECIMAL(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 CEILING and FLOOR to round numerical values. (Popular vendor specific functions are TRUNC (Informix, DB2, PostgreSQL, Oracle and MySQL) and ROUND (Informix, SQLite, Sybase, Oracle, PostgreSQL, Microsoft SQL Server and Mimer SQL.))
CEILING
FLOOR
TRUNC
ROUND
DATE
2011-05-03
TIME
15:51:36
TIME WITH TIME ZONE
TIMESTAMP
2011-05-03 15:51:36.123456
TIMESTAMP WITH TIME ZONE
The SQL function EXTRACT 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 CURRENT_DATE, CURRENT_TIMESTAMP, LOCALTIME, or LOCALTIMESTAMP. (Popular vendor specific functions are TO_DATE, TO_TIME, TO_TIMESTAMP, YEAR, MONTH, DAY, HOUR, MINUTE, SECOND, DAYOFYEAR, DAYOFMONTH and DAYOFWEEK.)
EXTRACT
CURRENT_DATE
CURRENT_TIMESTAMP
LOCALTIME
LOCALTIMESTAMP
TO_DATE
TO_TIME
TO_TIMESTAMP
MONTH
DAY
HOUR
MINUTE
SECOND
DAYOFYEAR
DAYOFMONTH
DAYOFWEEK
YEAR(precision)
YEAR(precision) TO MONTH
MONTH(precision)
DAY(precision)
DAY(precision) TO HOUR
DAY(precision) TO MINUTE
DAY(precision) TO SECOND(scale)
HOUR(precision)
HOUR(precision) TO MINUTE
HOUR(precision) TO SECOND(scale)
MINUTE(precision)
MINUTE(precision) TO SECOND(scale)
The Data Control Language (DCL) authorizes users to access and manipulate data. Its two main statements are:
GRANT
REVOKE
Example:
GRANT SELECT, UPDATE ON example TO some_user, another_user; REVOKE SELECT, UPDATE ON example FROM some_user, another_user;
Although the UNIQUE argument is identical to DISTINCT, it is not an ANSI standard.
[...] the keyword DISTINCT [...] eliminates the duplicates from the result set.