An SQL JOIN clause combines records from two or more tables in a database.[1] It creates a set that can be saved as a table or used as is. A JOIN is a means for combining fields from two tables by using values common to each. ANSI standard SQL specifies four types of JOINs: INNER, OUTER, LEFT, and RIGHT. In special cases, a table (base table, view, or joined table) can JOIN to itself in a self-join.
A programmer writes a JOIN predicate to identify the records for joining. If the evaluated predicate is true, the combined record is then produced in the expected format, a record set or a temporary table, for example.
Novices should beware that the default JOIN in many systems is the inner join (this can be confusing because join ... on can seem to imply an ordering, but it is actually the join that applies to the table names, and the on that applies to the criteria; join is itself ambiguous between order-independence and order-dependence).
all subsequent explanations on join types in this article make use of the following two tables. The rows in these tables serve to illustrate the effect of different types of joins and join-predicates. In the following tables, Department.DepartmentID is the primary key, while Employee.DepartmentID is a foreign key.
Note: The "Marketing" Department currently has no listed employees. Also, employee "John" has not been assigned to any Department yet.
An inner join is the most common join operation used in applications, and represents the default join-type. Inner join creates a new result table by combining column values of two tables (A and B) based upon the join-predicate. The query compares each row of A with each row of B to find all pairs of rows which satisfy the join-predicate. When the join-predicate is satisfied, column values for each matched pair of rows of A and B are combined into a result row. The result of the join can be defined as the outcome of first taking the Cartesian product (or cross-join) of all records in the tables (combining every record in table A with every record in table B) - then return all records which satisfy the join predicate. Actual SQL implementations normally use other approaches like a Hash join or a Sort-merge join where possible, since computing the Cartesian product is very inefficient.
SQL specifies two different syntactical ways to express joins: "explicit join notation" and "implicit join notation".
The "explicit join notation" uses the JOIN keyword to specify the table to join, and the ON keyword to specify the predicates for the join, as in the following example:
SELECT * FROM employee INNER JOIN department ON employee.DepartmentID = department.DepartmentID
The "implicit join notation" simply lists the tables for joining (in the FROM clause of the SELECT statement), using commas to separate them. Thus, it specifies a cross-join, and the WHERE clause may apply additional filter-predicates (which function comparably to the join-predicates in the explicit notation).
The following example shows a query which is equivalent to the one from the previous example, but this time written using the implicit join notation:
SELECT * FROM employee, department WHERE employee.DepartmentID = department.DepartmentID
The queries given in the examples above will join the Employee and Department tables using the DepartmentID column of both tables. Where the DepartmentID of these tables match (i.e. the join-predicate is satisfied), the query will combine the LastName, DepartmentID and DepartmentName columns from the two tables into a result row. Where the DepartmentID does not match, no result row is generated.
Thus the result of the execution of either of the two queries above will be:
Employee.LastName Employee.DepartmentID Department.DepartmentName Department.DepartmentIDNote: Programmers should take special care when joining tables on columns that can contain NULL values, since NULL will never match any other value (or even NULL itself), unless the join condition explicitly uses the IS NULL or IS NOT NULL predicates.
Notice that the employee "John" and the department "Marketing" do not appear in the query execution results. Neither of these has any matching records in the respective other table: "John" has no associated department, and no employee has the department ID 35. Thus, no information on John or on Marketing appears in the joined table. Depending on the desired results, this behavior may be a subtle bug. Outer joins may be used to avoid it.
One can further classify inner joins as equi-joins, as natural joins, or as cross-joins (see below).
An equi-join, also known as an equijoin, is a specific type of comparator-based join, or theta join, that uses only equality comparisons in the join-predicate. Using other comparison operators (such as <) disqualifies a join as an equi-join. The query shown above has already provided an example of an equi-join:
SELECT * FROM employee INNER JOIN department ON employee.DepartmentID = department.DepartmentID
SQL provides an optional shorthand notation for expressing equi-joins, by way of the USING construct (Feature ID F402):
SELECT * FROM employee INNER JOIN department USING (DepartmentID)
The USING construct is more than mere syntactic sugar, however, since the result set differs from the result set of the version with the explicit predicate. Specifically, any columns mentioned in the USING list will appear only once, with an unqualified name, rather than once for each table in the join. In the above case, there will be a single DepartmentID column and no employee.DepartmentID or department.DepartmentID.
The USING clause is supported by MySQL, Oracle, PostgreSQL, SQLite, DB2/400 and Firebird in version 2.1 or higher.
A natural join offers a further specialization of equi-joins. The join predicate arises implicitly by comparing all columns in both tables that have the same column-name in the joined tables. The resulting joined table contains only one column for each pair of equally-named columns....
The above sample query for inner joins can be expressed as a natural join in the following way:
SELECT * FROM employee NATURAL JOIN department
As with the explicit USING clause, only one DepartmentID column occurs in the joined table, with no qualifier:
A cross join, cartesian join or product provides the foundation upon which all types of inner joins operate. A cross join returns the cartesian product of the sets of records from the two joined tables. Thus, it equates to an inner join where the join-condition always evaluates to True or where the join-condition is absent from the statement. In other words, a cross join combines every row in B with every row in A. The number of rows in the result set will be the number of rows in A times the number of rows in B.
Thus, if A and B are two sets, then the cross join is written as A × B.
The SQL code for a cross join lists the tables for joining (FROM), but does not include any filtering join-predicate.
Example of an explicit cross join:
SELECT * FROM employee CROSS JOIN department
Example of an implicit cross join:
SELECT * FROM employee, department;
The cross join does not apply any predicate to filter records from the joined table. Programmers can further filter the results of a cross join by using a WHERE clause.
An outer join does not require each record in the two joined tables to have a matching record. The joined table retains each record—even if no other matching record exists. Outer joins subdivide further into left outer joins, right outer joins, and full outer joins, depending on which table(s) one retains the rows from (left, right, or both).
(In this case left and right refer to the two sides of the JOIN keyword.)
No implicit join-notation for outer joins exists in standard SQL.
The result of a left outer join (or simply left join) for table A and B always contains all records of the "left" table (A), even if the join-condition does not find any matching record in the "right" table (B). This means that if the ON clause matches 0 (zero) records in B, the join will still return a row in the result—but with NULL in each column from B. This means that a left outer join returns all the values from the left table, plus matched values from the right table (or NULL in case of no matching join predicate). If the left table returns one row and the right table returns more than one matching row for it, the values in the left table will be repeated for each distinct row on the right table.
For example, this allows us to find an employee's department, but still shows the employee(s) even when their department does not exist (contrary to the inner-join example above, where employees in non-existent departments are excluded from the result).
Example of a left outer join, with the additional result row italicized:
SELECT * FROM employee LEFT OUTER JOIN department ON employee.DepartmentID = department.DepartmentID
A right outer join (or right join) closely resembles a left outer join, except with the treatment of the tables reversed. Every row from the "right" table (B) will appear in the joined table at least once. If no matching row from the "left" table (A) exists, NULL will appear in columns from A for those records that have no match in B.
A right outer join returns all the values from the right table and matched values from the left table (NULL in case of no matching join predicate).
For example, this allows us to find each employee and his or her department, but still show departments that have no employees.
Example right outer join, with the additional result row italicized:
SELECT * FROM employee RIGHT OUTER JOIN department ON employee.DepartmentID = department.DepartmentID
In practice, explicit right outer joins are rarely used, since they can always be replaced with left outer joins (with the table order switched) and provide no additional functionality. The result above is produced also with a left outer join:
SELECT * FROM department LEFT OUTER JOIN employee ON employee.DepartmentID = department.DepartmentID
A full outer join combines the results of both left and right outer joins. The joined table will contain all records from both tables, and fill in NULLs for missing matches on either side.
For example, this allows us to see each employee who is in a department and each department that has an employee, but also see each employee who is not part of a department and each department which doesn't have an employee.
Example full outer join:
SELECT * FROM employee FULL OUTER JOIN department ON employee.DepartmentID = department.DepartmentID
Some database systems (like MySQL) do not support this functionality directly, but they can emulate it through the use of left and right outer joins and unions. The same example can appear as follows:
SELECT * FROM employee LEFT JOIN department ON employee.DepartmentID = department.DepartmentID UNION SELECT * FROM employee RIGHT JOIN department ON employee.DepartmentID = department.DepartmentID WHERE employee.DepartmentID IS NULL