What Are Joins?

Imagine you want to cook a delicious recipe. You step into your kitchen, which contains:

• Utensils

• Spices

• A fridge full of vegetables and fruits

To make the recipe, you need to combine information from all these sources. Using only one, like spices, won't give you the complete picture. This is where JOINS come in:

• JOINS are like the method you use to combine these resources into a single recipe.

• They combine rows from two or more tables based on a common feature.

Example

• Table 1: Vegetables

• Table 2: Utensils

You want to check if you have both "brinjal" in the vegetables table and a "steel bowl" in the utensils table to prepare brinjal curry. Using a JOIN, you can combine data from these tables into one complete report.

In Short:

JOINS bring related data together, just like connecting puzzle pieces to see the whole picture.

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Why Use SQL Joins?

SQL JOINS allow you to combine data from multiple tables using relationships between them. For example:

• In a library database, you have three tables:

  • Books: Contains book information.

  • Authors: Contains author details.

  • Borrowed: Tracks borrowed books.

Use Cases

1. Match Books with Authors: See who wrote each book.

2. Combine Borrowed Data: Identify which author's books are borrowed most frequently.

By merging tables, JOINS provide complete and meaningful insights without duplicating data.

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Where to Use SQL JOINS?

SQL JOINS are typically used in the SELECT statement of a query.

Steps:

1. Start with the FROM Clause: Specify the first table.

2. Use the JOIN Keyword: Connect the first table to another.

3. Optionally Specify the JOIN Type: By default, it’s an INNER JOIN.

4. Define the Relationship with ON: Specify the common feature between tables (e.g., books.book_id = authors.book_id).

5. Optionally Add a WHERE Clause: Filter combined data further.

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Types of JOINS

There are four main types of SQL JOINS:

1. Inner Join

2. Outer Join (with subtypes: Left, Right, and Full)

3. Cross Join

4. Natural Join

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1) Inner Join

An inner join returns only the rows with matching values in both tables.

Example:

Imagine your college is hosting:

• A Fest (Table 1: Students registered for the fest).

• A DJ Night (Table 2: Students registered for the DJ night).

You want to find students who registered for both events. An inner join will help you do this.

SQL Syntax:

SELECT
    f.fruit_name, f.quantity AS fruit_quantity,
    v.veg_name, v.quantity AS veg_quantity
FROM
    Fruits f
INNER JOIN
    Vegetables v
ON
    f.fruit_name = v.veg_name;

Result:

This query returns rows where the fruit_name column in the Fruits table matches the veg_name column in the Vegetables table.

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2) Outer Join

Outer joins include data even if there isn’t a match. Subtypes are:

a) Left Outer Join

• Returns all rows from the left table and matching rows from the right table. Unmatched rows in the right table return NULL.

SQL Syntax:

SELECT
    f.fruit_name, f.quantity AS fruit_quantity,
    v.veg_name, v.quantity AS veg_quantity
FROM
    Fruits f
LEFT JOIN
    Vegetables v
ON
    f.fruit_name = v.veg_name;

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b) Right Outer Join

• Returns all rows from the right table and matching rows from the left table. Unmatched rows in the left table return NULL.

SQL Syntax:

SELECT
    f.fruit_name, f.quantity AS fruit_quantity,
    v.veg_name, v.quantity AS veg_quantity
FROM
    Fruits f
RIGHT JOIN
    Vegetables v
ON
    f.fruit_name = v.veg_name;

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c) Full Outer Join

• Returns all rows from both tables. Unmatched rows return NULL for missing values.

SQL Syntax:

SELECT
    f.fruit_name, f.quantity AS fruit_quantity,
    v.veg_name, v.quantity AS veg_quantity
FROM
    Fruits f
FULL OUTER JOIN
    Vegetables v
ON
    f.fruit_name = v.veg_name;

Real-World Analogy:

You want to know:

• Who registered for only the Fest.

• Who registered for only the DJ Night.

• Who registered for both events.

A full outer join gives you all this information.

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3) Cross Join

A cross join returns the Cartesian product of two tables. This means every row in the first table is combined with every row in the second table.

SQL Syntax:

SELECT
    f.fruit_name, v.veg_name
FROM
    Fruits f
CROSS JOIN
    Vegetables v;

Real-World Analogy:

Imagine pairing every guest at a party with every available dish. If there are 5 guests and 3 dishes, you’ll create 15 combinations.

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4) Natural Join

A natural join automatically combines rows from tables based on columns with the same name. It doesn’t require an ON clause.

SQL Syntax:

SELECT
    fruit_name, quantity
FROM
    Fruits
NATURAL JOIN
    Vegetables;

Note:

While convenient, NATURAL JOIN can lead to unexpected results if tables have unrelated columns with the same name. It’s rarely used in practice.

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Key Takeaways:

• Inner Join: This is for matching rows in both tables.

• Outer Joins: For including unmatched rows.

• Cross Join: For all possible combinations.

• Natural Join: For automatic column matching (use cautiously).

Practice Exercise:

1. Create two tables: Students and Courses.

2. Write queries to find:

   • Students enrolled in a specific course (Inner Join).

   • All students, whether or not they’ve enrolled in a course (Left Join).

   • All courses, whether or not they have students enrolled (Right Join).

   • All possible combinations of students and courses (Cross Join).

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Conclusion

We explored SQL Joins, which combine data from multiple tables to derive insights. Key takeaways:

• What Joins are

• Why use Joins

• How to use Joins

• Types of Joins (Inner, Outer, Cross, Natural)

Mastering SQL Joins unlocks the potential of relational databases, enabling data-driven decisions and impactful analyses. 🚀

Closing Thoughts:

JOINS are the backbone of relational databases. By understanding and practising them, you can unlock the full potential of SQL to analyze and manage complex datasets effectively.