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
and YEAR
), or non-reserved (e.g. ASC
, DOMAIN
and KEY
). List of SQL reserved words.YEAR
is specified as "YEAR"
. ansi_quotes
SQL mode enforces the SQL standard behavior. These can also be used regardless of this mode through backticks: `YEAR`
.Operator | Description | Example |
---|---|---|
= | Equal to | Author='Alcott' |
<> | Not equal to (many dialects also accept != ) | Dept<>'Sales' |
> | Greater than | Hire_Date>'2012-01-31' |
< | Less than | Bonus<50000.00 |
>= | Greater than or equal | Dependents>=2 |
<= | Less than or equal | Rate<=0.05 |
[NOT]BETWEEN[SYMMETRIC] | Between an inclusive range. SYMMETRIC inverts the range bounds if the first is higher than the second. | CostBETWEEN100.00AND500.00 |
[NOT]LIKE[ESCAPE] | Begins with a character pattern | Full_NameLIKE'Will%' |
Contains a character pattern | Full_NameLIKE'%Will%' | |
[NOT]IN | Equal to one of multiple possible values | DeptCodeIN(101,103,209) |
IS[NOT]NULL | Compare to null (missing data) | AddressISNOTNULL |
IS[NOT]TRUE orIS[NOT]FALSE | Boolean truth value test | PaidVacationISTRUE |
ISNOTDISTINCTFROM | Is equal to value or both are nulls (missing data) | DebtISNOTDISTINCTFROM-Receivables |
AS | Used to change a column name when viewing results | SELECTemployeeASdepartment1 |
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:
CASEWHENn>0THEN'positive'WHENn<0THEN'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:
CASEnWHEN1THEN'One'WHEN2THEN'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
.
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:
CASEWHENx1ISNOTNULLTHENx1ELSEx2END
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
CASEWHENx1=x2THENNULLELSEx1END
Standard SQL allows two formats for comments: -- comment
, which is ended by the first newline, and /* comment */
, which can span multiple lines.
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]
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
clause, which indicates the table(s) to retrieve data from. The FROM
clause can include optional JOIN
subclauses to specify the rules for joining tables. WHERE
clause includes a comparison predicate, which restricts the rows returned by the query. The WHERE
clause eliminates all rows from the result set where the comparison predicate does not evaluate to True. GROUP BY
clause projects rows having common values into a smaller set of rows.[ clarification needed ]GROUP BY
is often used in conjunction with SQL aggregation functions or to eliminate duplicate rows from a result set. The WHERE
clause is applied before the GROUP BY
clause. HAVING
clause includes a predicate used to filter rows resulting from the GROUP BY
clause. Because it acts on the results of the GROUP BY
clause, aggregation functions can be used in the HAVING
clause predicate. 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 ORDER BY
clause, the order of rows returned by an SQL query is undefined.DISTINCT
keyword [3] eliminates duplicate data. [4] OFFSET
clause specifies the number of rows to skip before starting to return data.FETCH FIRST
clause specifies the number of rows to return. Some SQL databases instead have non-standard alternatives, e.g. LIMIT
, TOP
or 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> | 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 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*FROMBookWHEREprice>100.00ORDERBYtitle;
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.
SELECTBook.titleASTitle,count(*)ASAuthorsFROMBookJOINBook_authorONBook.isbn=Book_author.isbnGROUPBYBook.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:
SELECTtitle,count(*)ASAuthorsFROMBookNATURALJOINBook_authorGROUPBYtitle;
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.
SELECTisbn,title,price,price*0.06ASsales_taxFROMBookWHEREprice>100.00ORDERBYtitle;
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:
SELECTisbn,title,priceFROMBookWHEREprice<(SELECTAVG(price)FROMBook)ORDERBYtitle;
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.
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):
SELECTb.isbn,b.title,b.price,sales.items_sold,sales.company_nmFROMBookbJOIN(SELECTSUM(Items_Sold)Items_Sold,Company_Nm,ISBNFROMBook_SalesGROUPBYCompany_Nm,ISBN)salesONsales.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.
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]
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]
The Data Manipulation Language (DML) is the subset of SQL used to add, update and delete data:
INSERTINTOexample(column1,column2,column3)VALUES('test','N',NULL);
UPDATE
modifies a set of existing table rows, e.g.:UPDATEexampleSETcolumn1='updated value'WHEREcolumn2='N';
DELETE
removes existing rows from a table, e.g.:DELETEFROMexampleWHEREcolumn2='N';
MERGE
is used to combine the data of multiple tables. It combines the INSERT
and UPDATE
elements. It is defined in the SQL:2003 standard; prior to that, some databases provided similar functionality via different syntax, sometimes called "upsert".MERGEINTOtable_nameUSINGtable_referenceON(condition)WHENMATCHEDTHENUPDATESETcolumn1=value1[,column2=value2...]WHENNOTMATCHEDTHENINSERT(column1[,column2...])VALUES(value1[,value2...])
Transactions, if available, wrap DML operations:
START TRANSACTION
(or BEGIN WORK
, or BEGIN TRANSACTION
, depending on SQL dialect) marks the start of a database transaction, which either completes entirely or not at all.SAVE TRANSACTION
(or SAVEPOINT
) saves the state of the database at the current point in transactionCREATETABLEtbl_1(idint);INSERTINTOtbl_1(id)VALUES(1);INSERTINTOtbl_1(id)VALUES(2);COMMIT;UPDATEtbl_1SETid=200WHEREid=1;SAVEPOINTid_1upd;UPDATEtbl_1SETid=1000WHEREid=2;ROLLBACKtoid_1upd;SELECTidfromtbl_1;
COMMIT
makes all data changes in a transaction permanent. ROLLBACK
discards all data changes since the last COMMIT
or ROLLBACK
, leaving the data as it was prior to those changes. Once the COMMIT
statement completes, the transaction's changes cannot be rolled back.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.
STARTTRANSACTION;UPDATEAccountSETamount=amount-200WHEREaccount_number=1234;UPDATEAccountSETamount=amount+200WHEREaccount_number=2345;IFERRORS=0COMMIT;IFERRORS<>0ROLLBACK;
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
creates an object (a table, for example) in the database, e.g.:CREATETABLEexample(column1INTEGER,column2VARCHAR(50),column3DATENOTNULL,PRIMARYKEY(column1,column2));
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.:ALTERTABLEexampleADDcolumn4INTEGERDEFAULT25NOTNULL;
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).TRUNCATETABLEexample;
DROP
deletes an object in the database, usually irretrievably, i.e., it cannot be rolled back, e.g.:DROPTABLEexample;
Each column in an SQL table declares the type(s) that column may contain. ANSI SQL includes the following data types. [14]
CHARACTER(n)
(or CHAR(n)
): fixed-width n-character string, padded with spaces as neededCHARACTER VARYING(n)
(or VARCHAR(n)
): variable-width string with a maximum size of n charactersCHARACTER LARGE OBJECT(n [ K | M | G | T ])
(or CLOB(n [ K | M | G | T ])
): character large object with a maximum size of n [ K | M | G | T ] charactersNATIONAL CHARACTER(n)
(or NCHAR(n)
): fixed width string supporting an international character setNATIONAL CHARACTER VARYING(n)
(or NVARCHAR(n)
): variable-width NCHAR
stringNATIONAL CHARACTER LARGE OBJECT(n [ K | M | G | T ])
(or NCLOB(n [ K | M | G | T ])
): national character large object with a maximum size of n [ K | M | G | T ] charactersFor 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.
BINARY(n)
: Fixed length binary string, maximum length n.BINARY VARYING(n)
(or VARBINARY(n)
): Variable length binary string, maximum length n.BINARY LARGE OBJECT(n [ K | M | G | T ])
(or BLOB(n [ K | M | G | T ])
): binary large object with a maximum length 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.
BOOLEAN
The BOOLEAN
data type can store the values TRUE
and FALSE
.
INTEGER
(or INT
), SMALLINT
and BIGINT
FLOAT
, REAL
and DOUBLE PRECISION
NUMERIC(precision, scale)
or 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.))
DATE
: for date values (e.g. 2011-05-03
).TIME
: for time values (e.g. 15:51:36
).TIME WITH TIME ZONE
: the same as TIME
, but including details about the time zone in question.TIMESTAMP
: This is a DATE
and a TIME
put together in one variable (e.g. 2011-05-03 15:51:36.123456
).TIMESTAMP WITH TIME ZONE
: the same as TIMESTAMP
, but including details about the time zone in question.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
.)
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 secondsThe Data Control Language (DCL) authorizes users to access and manipulate data. Its two main statements are:
GRANT
authorizes one or more users to perform an operation or a set of operations on an object.REVOKE
eliminates a grant, which may be the default grant.Example:
GRANTSELECT,UPDATEONexampleTOsome_user,another_user;REVOKESELECT,UPDATEONexampleFROMsome_user,another_user;
Structured Query Language (SQL) is a domain-specific language used to manage data, especially in a relational database management system (RDBMS). It is particularly useful in handling structured data, i.e., data incorporating relations among entities and variables.
In the relational model of databases, a primary key is a designated attribute (column) that can reliably identify and distinguish between each individual record in a table. The database creator can choose an existing unique attribute or combination of attributes from the table to act as its primary key, or create a new attribute containing a unique ID that exists solely for this purpose.
A foreign key is a set of attributes in a table that refers to the primary key of another table, linking these two tables. In the context of relational databases, a foreign key is subject to an inclusion dependency constraint that the tuples consisting of the foreign key attributes in one relation, R, must also exist in some other relation, S; furthermore that those attributes must also be a candidate key in S.
Transact-SQL (T-SQL) is Microsoft's and Sybase's proprietary extension to the SQL used to interact with relational databases. T-SQL expands on the SQL standard to include procedural programming, local variables, various support functions for string processing, date processing, mathematics, etc. and changes to the DELETE and UPDATE statements.
In database systems, isolation is one of the ACID transaction properties. It determines how transaction integrity is visible to other users and systems. A lower isolation level increases the ability of many users to access the same data at the same time, but also increases the number of concurrency effects users might encounter. Conversely, a higher isolation level reduces the types of concurrency effects that users may encounter, but requires more system resources and increases the chances that one transaction will block another.
A join clause in the Structured Query Language (SQL) combines columns from one or more tables into a new table. The operation corresponds to a join operation in relational algebra. Informally, a join stitches two tables and puts on the same row records with matching fields : INNER
, LEFT OUTER
, RIGHT OUTER
, FULL OUTER
and CROSS
.
The SQL SELECT statement returns a result set of rows, from one or more tables.
An SQL INSERT statement adds one or more records to any single table in a relational database.
In computer science, the Boolean is a data type that has one of two possible values which is intended to represent the two truth values of logic and Boolean algebra. It is named after George Boole, who first defined an algebraic system of logic in the mid 19th century. The Boolean data type is primarily associated with conditional statements, which allow different actions by changing control flow depending on whether a programmer-specified Boolean condition evaluates to true or false. It is a special case of a more general logical data type—logic does not always need to be Boolean.
A user-defined function (UDF) is a function provided by the user of a program or environment, in a context where the usual assumption is that functions are built into the program or environment. UDFs are usually written for the requirement of its creator.
In SQL, null or NULL is a special marker used to indicate that a data value does not exist in the database. Introduced by the creator of the relational database model, E. F. Codd, SQL null serves to fulfil the requirement that all true relational database management systems (RDBMS) support a representation of "missing information and inapplicable information". Codd also introduced the use of the lowercase Greek omega (ω) symbol to represent null in database theory. In SQL, NULL
is a reserved word used to identify this marker.
Oracle Database provides information about all of the tables, views, columns, and procedures in a database. This information about information is known as metadata. It is stored in two locations: data dictionary tables and a metadata registry.
A WHERE
clause in SQL specifies that a SQL Data Manipulation Language (DML) statement should only affect rows that meet specified criteria. The criteria are expressed in the form of predicates. WHERE
clauses are not mandatory clauses of SQL DML statements, but can be used to limit the number of rows affected by a SQL DML statement or returned by a query. In brief SQL WHERE clause is used to extract only those results from a SQL statement, such as: SELECT
, INSERT
, UPDATE
, or DELETE
statement.
A relational database management system uses SQL MERGE
statements to INSERT
new records or UPDATE
existing records depending on whether condition matches. It was officially introduced in the SQL:2003 standard, and expanded in the SQL:2008 standard.
Gadfly is a relational database management system written in Python. Gadfly is a collection of Python modules that provides relational database functionality entirely implemented in Python. It supports a subset of the standard RDBMS Structured Query Language (SQL).
In relational database management systems, a unique key is a candidate key. All the candidate keys of a relation can uniquely identify the records of the relation, but only one of them is used as the primary key of the relation. The remaining candidate keys are called unique keys because they can uniquely identify a record in a relation. Unique keys can consist of multiple columns. Unique keys are also called alternate keys. Unique keys are an alternative to the primary key of the relation. In SQL, the unique keys have a UNIQUE
constraint assigned to them in order to prevent duplicates. Alternate keys may be used like the primary key when doing a single-table select or when filtering in a where clause, but are not typically used to join multiple tables.
SQL:1999 was the fourth revision of the SQL database query language. It introduced many new features, many of which required clarifications in the subsequent SQL:2003. In the meanwhile SQL:1999 is deprecated.
A hierarchical query is a type of SQL query that handles hierarchical model data. They are special cases of more general recursive fixpoint queries, which compute transitive closures.
In a SQL database query, a correlated subquery is a subquery that uses values from the outer query. Because the subquery may be evaluated once for each row processed by the outer query, it can be slow.
In relational databases, the log trigger or history trigger is a mechanism for automatic recording of information about changes inserting or/and updating or/and deleting rows in a database table.
Although the UNIQUE argument is identical to DISTINCT, it is not an ANSI standard.
[...] the keyword DISTINCT [...] eliminates the duplicates from the result set.