Support of joins

The SQL engine of 4D extends the support of joins.

Join operations may be inner or outer, implicit or explicit. Implicit inner joins are support via the SELECT command. You can also generate explicit inner and outer joins using the SQL JOIN keyword.

Note: The current implementation of joins in the 4D SQL engine does not include:

• natural joins.
• the USING construct on inner joins.

Join operations are used to make connections between the records of two or more tables and combine the result in a new table, called a join. 

You generate joins via SELECT statements that specify the join conditions. With explicit joins, these conditions can be complex but they must always be based on an equality comparison between the columns included in the join. For example, it is not possible to use the >= operator in an explicit join condition. Any type of comparison can be used in an implicit join.
Internally, equality comparisons are carried out directly by the 4D engine, which ensures rapid execution. 

Note: Usually, in the database engine, the table order is determined by the order specified during the search. However, when you use joins, the order of the tables is determined by the list of tables. In the following example:
SELECT * FROM T1 RIGHT OUTER JOIN T2 ON T2.depID = T1.depID;
... the order of the tables is T1 then T2 (as they appear in the list of tables) and not T2 then T1 (as they appear in the join condition).

An inner join is based on a comparison to find matches between two columns. For example, if we consider the three following tables:

• Employees
  

  name	depID	cityID
  Alan	10	30
  Anne	11	39
  Bernard	10	33
  Mark	12	35
  Martin	15	30
  Philip	NULL	33
  Thomas	10	NULL

• Departments
  

  depID	depName
  10	Program
  11	Engineering
  NULL	Marketing
  12	Development
  13	Quality

• Cities
  

  cityID	cityName
  30	Paris
  33	New York
  NULL	Berlin

Note: The example structure above will be used throughout this chapter. 

Here is an example of an implicit inner join:

In 4D, you can also use the JOIN keyword to specify an explicit inner join:

You can insert this query into 4D code as follows:

Here are the results of this join:

Note that neither the employees named Philip or Martin nor the Marketing or Quality departments appear in the resulting join because:

• Philip does not have a department associated with his name (NULL value),
• The department ID associated with Martin’s name does not exist in the Departments table,
• There is no employee associated with the Quality department (ID 13),
• The Marketing department does not have an ID associated with it (NULL value).

A cross or Cartesian join is an inner join for which no WHERE nor ON clauses have been specified. It consists in associating each row of one table with each row of another table.
The result of a cross join is the Cartesian product of the tables, containing a x b rows, where a is the number of rows in the first table and b is the number of rows in the second table. This product represents every possible combination formed by the concatenation of the rows of both tables. 

Each of the following syntaxes are equivalent:

Here is an example of 4D code with a cross join:

Here is the result of this join with our example database:

Note: For performance reasons, cross joins should be used with precaution.

You can now generate outer joins with 4D. With outer joins, it is not necessary for there to be a match between the rows of joined tables. The resulting table contains all the rows of the tables (or of at least one of the joined tables) even if there are no matching rows. This means that all the information of a table can be used, even if the rows are not completely filled in between the different joined tables. 

There are three types of outer joins, specified using the LEFT, RIGHT and FULL keywords. LEFT and RIGHT are used to indicate the table (located to the left or right of the JOIN keyword) where all the data must be processed. FULL indicates a bilateral outer join.

Note: Only explicit outer joins are supported by 4D.

The result of a left outer join (or left join) always contains all the records for the table located to the left of keyword even if the join condition does not find a matching record in the table located to the right. This means that for each row in the left table where the search does not find any matching row in the right table, the join will still contain this row but it will have NULL values in each column of the right table. In other words, a left outer join returns all the rows of the left table plus any of those of the right table that match the join condition (or NULL if none match). Note that if the right table contains more than one row that matches the join predicate for a single row of the left table, the values of the left table will be repeated for each distinct row of the right table. 

Here is an example of 4D code with a left outer join:

Here is the result of this join with our example database (additional rows shown in red):

A right outer join is the exact opposite of a left outer join. Its result always contains all the records of the table located to the right of the JOIN keyword even if the join condition does not find any matching record in the left table. 

Here is an example of 4D code with a right outer join:

Here is the result of this join with our example database (additional rows shown in red):

A full outer join simply combines together the results of a left outer join and a right outer join. The resulting join table contains all the records of the left and right tables and fills in the missing fields on each side with NULL values. 

Here is an example of 4D code with a full outer join:

Here is the result of this join with our example database (additional rows shown in red):

It is possible to combine several joins in the same SELECT statement. It is also possible to mix implicit or explicit inner joins and explicit outer joins.

Here is an example of 4D code with multiple joins:

Here is the result of this join with our example database: