Structured Query Language, or SQL, is known for its ability to interact with databases seamlessly. One basic fundamental of SQL is the retrieval of records from different tables. And here’s where joins come into picture. You can use joins to retrieve records from two or more tables that share a common column, making it possible to work with multiple tables and extract useful information.

In SQL, before learning joins, it is crucial to understand the concept of Database Normalization. Some tables have information, while others only contain some, creating a multi-table framework. A simple table will hold required information, but sometimes this information will be split between multiple tables, and joins will allow you to bring these partial tables together.

What Is a Join?

The term “join” in SQL refers to the act of two or more tables joining together into one table with the help of their associated tables. It is Allen’s dream to be able to have data from several tables in one sight without having to reference a table in another. Joins can generally be implemented on link conditions that contain common column values in both tables.

A join in SQL simply is a way of combining tables by means of merging the rows of each joined table that satisfies the join conditions specified. Typically, such conditions consist of column values that are to be compared and are used to relate the tables involved. This is what renders joins as one of the fundamental pillars of relational databases – providing an avenue through which related information that is stored in separate tables can be retrieved.

Types of Joins

SQL supports multiple types of joins. Each of them specifies the rules of how two or more tables will be joined, based on the condition of their match. These types are:

1. INNER JOIN:

INNER JOIN is the most widely used type of join. It gives back only those rows for which there is a corresponding row in both tables being joined. If some columns do not match when being compared, those rows will be left out in the result set. In other words, an INNER JOIN writes select statements which return only the records where both tables have common rows that satisfy the join criteria.

2. LEFT JOIN (or LEFT OUTER JOIN):

The LEFT JOIN complements the operation of the right join in that it returns all the rows from the left table with the rows that match in the right-side table. In this case, if the right table contains no matching row, NULL will be returned for the columns fetched from it. This kind of join is appropriate when it is necessary to return all rows from the left table regardless of whether there is any data in the left table that matches any data in the right table.

3. RIGHT JOIN (or RIGHT OUTER JOIN):

The RIGHT JOIN works similarly to the LEFT JOIN, except that it preserves all the rows from the right table along with the rows that correspond in the left table. In the absence of such a match, the columns that are selected from the left table would be populated with NULL values. This join is applied whenever one wants to include all the rows from the right table before performing the join irrespective of whether there are matching rows in the left table or not.

4. FULL JOIN (or FULL OUTER JOIN):

The FULL JOIN retrieves every row from both tables regardless of whether or not they have a corresponding row in the other table. Both tables will be completely used in this operation; if any of their columns match, then the relevant row will be taken into consideration; otherwise, NULL values will be written in the tables where there isn’t any match. Such joins should be used when we want to have all records regardless of matches available in the tables.

5. CROSS JOIN:

The CROSS JOIN simply makes a combination of all rows of the two tables. On a technical note, it is also referred to as the Cartesian product of the two tables because it returns every possible combination of rows of the two tables. Every row of the first table is united with all rows of the second table. Although this might be useful in specific situations, it is not used too often because it might return an extremely large result set especially if both tables have a considerable amount of rows - which is not going to be very useful most of the time.

6. SELF JOIN:

The concept of SELF JOIN is quite basic because it describes the act of joining a particular table with itself. This is necessary when comparisons between rows of the same table are needed. In a self-join, two aliases of the same table are used as if they were two different tables.

Summary of Join Operations in One Paragraph

Consider customer data and order details maintained in two tables as an example of a table join. For instance, the customer table could have records about customers that include CustomerID, Name, Email, whereas the order table could include OrderID, CustomerID, OrderDate, and so forth. The tables have a relationship on CustomerID.

Let’s say you want to get a list of customers together with their order records. In this manner, you could use a JOIN so as to link the two tables on the matching CustomerID identifier. As a result, you will have a result set where each customer and their orders are provided in the same set.

By using an `INNER JOIN`, we would only see in the results the customers that have placed any orders. On the other hand, by using a `LEFT JOIN`, we would also see customers that have not placed any orders, but their order details would be `NULL`.

Understanding Why Joins are Important in SQL

Joins are essential for the retrieval of information stored in relational databases as it allows you to collect and retrieve information that is stored in two or more tables. It enables you to construct sophisticated queries that contain various elements such as customers, orders, and products, among others. Without these links, it would be cumbersome as you would have to work with a lot of datasets, combine them manually which isn’t only time consuming but also might yield errors.

For example, in the case of an online store the application database might use separate tables for Customers, Orders, and Products. In this case, the join statements will allow easy access to information about what products the customer bought, how many of those products they bought, and how much money they spent all in one single statement.