How Can I Join Tables Without a Direct Foreign Key Relationship?

Join tables with foreign key relationships through a third table

Problem Description

Data is often stored in multiple tables, with relationships defined by foreign keys. However, sometimes two tables may not have a direct foreign key relationship, but they can still be joined through a third table. This question demonstrates how to perform such a join to extract specific information from multiple tables.

Solution

Contrary to the assumption that foreign keys are required for table joins, foreign keys are not required. Instead, tables can be joined based on predicates defined for each table.

To join tables that lack direct foreign key relationships, follow these steps:

1. Determine the appropriate table to join based on the desired output.
2. Combine tables using the CROSS JOIN or INNER JOIN operators.
3. Use the WHERE clause to add additional conditions to filter the connected data.

Detailed explanation

Statements and tables:

Each table has a predicate that defines the rows it contains. For example, the Species table contains rows where the species name corresponds to its wood type and maximum height.

Query predicate:

queries also have predicates based on FROM, WHERE and other clauses. Table aliases allow column renaming and facilitate join conditions.

Join table:

CROSS JOIN and INNER JOIN use AND to combine predicates. UNION uses OR, while EXCEPT uses AND NOT to combine predicates. The ON and WHERE clauses can be used to specify additional join conditions.

Selection table:

To choose the right table, consider the desired output and identify the table that contains the necessary columns. Join them based on the predicate they share.

Foreign keys and queries:

Foreign keys do not affect query execution. They enforce integrity constraints but do not restrict connections. Queries are evaluated against table predicates.

Example query:

To extract the forest name, species name and wood type of the "ARCTIC" regional forest:

<code class="language-sql">SELECT Forest.Fo_name, Species.Sp_name, Species.Sp_woodtype
FROM Forest
INNER JOIN Tree ON Forest.Fo_name = Tree.Tr_forest
INNER JOIN Species ON Tree.Tr_species = Species.Sp_name
WHERE Forest.Fo_loc='ARCTIC'
ORDER BY Forest.Fo_name, Species.Sp_name;</code>

This query effectively joins the Tr_species, Tr_forest and Forest tables via the Species and Tree columns and filters the results based on the Fo_loc column. The output is sorted by forest and species name.

Note: The example query has been corrected from the description to ensure logical correctness and to be able to join the three tables. The ON Tree.Tr_species=Tree.Tr_forest condition in the original example is wrong because it is trying to join two different columns within a table. The corrected query uses the correct join conditions.

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