Join (SQL)

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.

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).

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.

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 an SQL query author cannot modify and which cause inner joins to omit data with no indication of an error.

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.

[2][3][4] A function in an SQL Where clause can result in the database ignoring relatively compact table indexes.

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.

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.

An equi-join is a specific type of comparator-based join, that uses only equality comparisons in the join-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.

[6] The result of the natural join is the set of all combinations of tuples in R and S that are equal on their common attribute names.

For an example consider the tables Employee and Dept and their natural join: This can also be used to define composition of relations.

For example, the composition of Employee and Dept is their join as shown above, projected on all but the common attribute DeptName.

The natural join is arguably one of the most important operators since it is the relational counterpart of logical AND.

In particular, the natural join allows the combination of relations that are associated by a foreign key.

More formally the semantics of the natural join are defined as follows: where Fun is a predicate that is true for a relation r if and only if r is a function.

Thus an existing query could produce different results, even though the data in the tables have not been changed, but only augmented.

Real world databases are commonly designed with foreign key data that is not consistently populated (NULL values are allowed), due to business rules and context.

It is common practice to modify column names of similar data in different tables and this lack of rigid consistency relegates natural joins to a theoretical concept for discussion.

In many database environments the column names are controlled by an outside vendor, not the query developer.

A natural join assumes stability and consistency in column names which can change during vendor mandated version upgrades.

Neither provides any functionality that the other does not, so right and left outer joins may replace each other as long as the table order is switched.

For example, can also be written as Much work in database-systems has aimed at efficient implementation of joins, because relational systems commonly call for joins, yet face difficulties in optimising their efficient execution.

The choices become more complex as the number of tables involved in a query increases, with each table having different characteristics in record count, average record length (considering NULL fields) and available indexes.

A query optimizer has two basic freedoms: Many join-algorithms treat their inputs differently.

One can classify query-plans involving joins as follows:[12] These names derive from the appearance of the query plan if drawn as a tree, with the outer join relation on the left and the inner relation on the right (as convention dictates).

However, it is defined on the Inventory table, even though the columns Part_Type and Supplier_State are "borrowed" from Supplier and Part respectively.

For example, in MySQL the command STRAIGHT_JOIN reads the tables in exactly the order listed in the query.