To combine rows from two or more tables based on a related column between them, what specific Structured Query Language (SQL) clause would an expert use?

The specific Structured Query Language (SQL) clause an expert would use to combine rows from two or more tables based on a related column between them is the `JOIN` clause. A `JOIN` clause is fundamental for retrieving data from multiple `tables` and presenting it as a single, unified `result set`. A `table` is an organized collection of related data, structured into `rows` and `columns`. A `row` (also known as a record) represents a single, complete entry of data, while a `column` (or field) represents a specific attribute or piece of information within that entry.

The core of combining tables with `JOIN` relies on a `related column`, which acts as a common field or link between the tables. Typically, this related column is a `PRIMARY KEY` in one table and a `FOREIGN KEY` in another. A `PRIMARY KEY` is a column or set of columns that uniquely identifies each row within its table, ensuring no two rows are identical. A `FOREIGN KEY` is a column in one table that references the primary key of another table, thereby establishing a direct, referential link between the two. This link ensures data consistency across the database.

The `ON` clause is an essential component of the `JOIN` statement, as it specifies the condition that dictates how rows from the joined tables should be matched. This condition typically involves an equality comparison between the related columns in each table, for example, `TableA.ColumnX = TableB.ColumnY`.

There are several types of `JOIN` operations, each designed for specific data retrieval needs:

1. INNER JOIN: This is the most frequently used `JOIN`. It returns only the rows where there is a direct match in both tables based on the condition specified in the `ON` clause. Any rows that do not have a corresponding match in the other table are excluded from the final result. For instance, to combine information about customers and their orders, where `CustomerID` is the related column between a `Customers` table and an `Orders` table, one would write: `SELECT Customers.CustomerName, Orders.OrderID FROM Customers INNER JOIN Orders ON Customers.CustomerID = Orders.CustomerID;` This query would only show customers who have placed at least one order and their respective order IDs.

2. LEFT JOIN (or LEFT OUTER JOIN): This join returns all rows from the "left" table (the first table specified in the `FROM` clause) and the matching rows from the "right" table. If a row in the left table has no match in the right table, `NULL` values are returned for all columns belonging to the right table in that row.

3. RIGHT JOIN (or RIGHT OUTER JOIN): This join returns all rows from the "right" table and the matching rows from the "left" table. If a row in the right table has no match in the left table, `NULL` values are returned for all columns belonging to the left table in that row.

4. FULL OUTER JOIN: This join returns all rows when there is a match in either the left or the right table. It effectively combines the results of both `LEFT JOIN` and `RIGHT JOIN`. If a row from one table has no matching rows in the other, the columns from the non-matching table will contain `NULL` values.

5. CROSS JOIN: This join produces the Cartesian product of the rows from the joined tables. It combines every row from the first table with every row from the second table. Unlike other `JOIN` types, a `CROSS JOIN` typically does not use an `ON` clause because it does not rely on a related column for matching; it simply generates all possible combinations.