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Join (SQL) - Wikipedia. A SQLjoin clause combines columns from one or more tables in a relational database. It creates a set that can be saved as a table or used as it is.

A JOIN is a means for combining columns from one (self- table) or more tables by using values common to each. ANSI- standard SQL specifies five types of JOIN: INNER, LEFT OUTER, RIGHT OUTER, FULL OUTER and CROSS. As a special case, a table (base table, view, or joined table) can JOIN to itself in a self- join. A programmer declares a JOIN statement to identify rows for joining. If the evaluated predicate is true, the combined row is then produced in the expected format, a row set or a temporary table. Sample tables. For example, a Department may be associated with a number of Employees.

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Joining separate tables for Department and Employee effectively creates another table which combines the information from both tables. 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 the Department. How To Install Tie Rods 98 Chevy Truck Video more.

IDcolumn of the Department table (which can be designated as Department. Department. ID) is the primary key, while Employee. Department. ID is a foreign key. Employee table. Last. Name. Department. IDRafferty. 31. Jones.

Heisenberg. 33. Robinson. Smith. 34. Williams. NULLDepartment table.

Department. IDDepartment. Name. 31. Sales. 33. Engineering. 34. Clerical.

Marketing. Note: In the Employee table above, the employee . Also, note that no employees are assigned to the . CREATETABLEdepartment 2 ( 3 Department. IDINTPrimarykey, 4 Department. Name. VARCHAR(2. 0) 5 ); 6 7 CREATETABLEemployee 8 ( 9 Last. Name. VARCHAR(2. 0),1. Department. IDINTreferencesdepartment(Department.

ID)1. 1 ); 1. 2 1. INSERTINTOdepartment. VALUES(3. 1,'Sales'); 1. INSERTINTOdepartment. VALUES(3. 3,'Engineering'); 1. INSERTINTOdepartment. VALUES(3. 4,'Clerical'); 1.

INSERTINTOdepartment. VALUES(3. 5,'Marketing'); 1. INSERTINTOemployee. VALUES('Rafferty',3. INSERTINTOemployee.

VALUES('Jones',3. INSERTINTOemployee. VALUES('Heisenberg',3. INSERTINTOemployee. VALUES('Robinson',3. INSERTINTOemployee. VALUES('Smith',3.

INSERTINTOemployee. VALUES('Williams',NULL); Cross join. In other words, it will produce rows which combine each row from the first table with each row from the second table. The results of a cross join can be filtered by using a WHERE clause which may then produce the equivalent of an inner join. In the SQL: 2. 01.

F4. 01, . 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 by matching non- NULL values, 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 rows in the tables (combining every row in table A with every row in table B) and then returning all rows which satisfy the join predicate.

Actual SQL implementations normally use other approaches, such as hash joins or sort- merge joins, since computing the Cartesian product is slower and would often require a prohibitively large amount of memory to store. SQL specifies two different syntactical ways to express joins: the .

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 is equivalent to the previous one, but this time using implicit join notation: SELECT*FROMemployee,department. WHEREemployee. Department.

ID=department. Department. ID; The queries given in the examples above will join the Employee and Department tables using the Department. ID column of both tables. Where the Department. ID of these tables match (i. Where the Department.

ID does not match, no result row is generated. Thus the result of the execution of the query above will be: Employee. Last. Name. Employee. Department. IDDepartment. Department. Name.

Department. Department. IDRobinson. 34. Clerical.

Jones. 33. Engineering. Smith. 34. Clerical. Heisenberg. 33. Engineering.

Rafferty. 31. Sales. The employee . Neither of these has any matching rows in the other respective table: . Depending on the desired results, this behavior may be a subtle bug, which can be avoided by replacing the inner join with an outer join. Programmers should take special care when joining tables on columns that can contain NULL values, since NULL will never match any other value (not even NULL itself), unless the join condition explicitly uses a combination predicate that first checks that the joins columns are NOT NULL before applying the remaining predicate condition(s).

The Inner join can only be safely used in a database that enforces referential integrity or where the join columns are guaranteed not to be NULL. Many transaction processing relational databases rely on Atomicity, Consistency, Isolation, Durability (ACID) data update standards to ensure data integrity, making inner joins an appropriate choice. However transaction databases usually also have desirable join columns that are allowed to be NULL. Many reporting relational database and data warehouses use high volume Extract, Transform, Load (ETL) batch updates which make referential integrity difficult or impossible to enforce, resulting in potentially NULL join columns that a SQL query author cannot modify and which cause inner joins to omit data with no indication of an error. The choice to use an inner join depends on the database design and data characteristics.

A left outer join can usually be substituted for an inner join when the join columns in one table may contain NULL values. Any data column that may be NULL (empty) should never be used as a link in an inner join, unless the intended result is to eliminate the rows with the NULL value. If NULL join columns are to be deliberately removed from the result set, an inner join can be faster than an outer join because the table join and filtering is done in a single step.

Conversely, an inner join can result in disastrously slow performance or even a server crash when used in a large volume query in combination with database functions in an SQL Where clause. The database may read and inner join the selected columns from both tables before reducing the number of rows using the filter that depends on a calculated value, resulting in a relatively enormous amount of inefficient processing. When a result set is produced by joining several tables, including master tables used to look up full text descriptions of numeric identifier codes (a Lookup table), a NULL value in any one of the foreign keys can result in the entire row being eliminated from the result set, with no indication of error. A complex SQL query that includes one or more inner joins and several outer joins has the same risk for NULL values in the inner join link columns.

A commitment to SQL code containing inner joins assumes NULL join columns will not be introduced by future changes, including vendor updates, design changes and bulk processing outside of the application's data validation rules such as data conversions, migrations, bulk imports and merges. One can further classify inner joins as equi- joins, as natural joins, or as cross- joins.

Equi- join. 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*FROMemployee. JOINdepartment. ONemployee. Department. ID=department. Department. ID; We can write equi- join as below,SELECT*FROMemployee,department. WHEREemployee. Department.

ID=department. Department. ID; If columns in an equi- join have the same name, SQL- 9.