Adventures in Machine Learning

Mastering SQL Set Operators: Union Union All Except and Intersect

Set Operators in SQL: Understanding Union,

Union All, Except, and Intersect

Are you struggling with the vast amount of data stored in your database? Do you need to answer complex queries that require merging or eliminating data from multiple tables?

If you answered “yes” to any of these questions, then it’s time to learn about SQL set operators. These operators provide a powerful way to combine or exclude data from multiple tables, helping you answer complex queries with ease.

In this article, we will explore four of the most commonly used SQL set operators: Union,

Union All, Except, and Intersect. By the end of this article, you will have a solid understanding of how to use these operators in your SQL queries.

SQL Set Operators

SQL set operators are used to combine or exclude data from two or more tables. These operators are used to answer complex queries that require data from multiple tables to be merged or eliminated.

Set operators are commonly used in SQL SELECT statements, JOIN statements, and subqueries.

Union

Union is an SQL set operator that combines data from two or more tables and returns a single result set. The

Union operator is used to combine rows from two or more tables into a single result set, eliminating any duplicate rows.

The primary keyword used to implement the

Union operator is “UNION”. For example, suppose you have two tables named “celebrities” and “politicians”.

You can use the

Union operator to combine rows from both tables as follows:

SELECT * FROM celebrities

UNION

SELECT * FROM politicians;

In the above example, the SELECT statement selects all the rows from “celebrities” and “politicians”. The

Union operator combines the rows from both tables and eliminates any duplicate rows.

Union All

Union All is another SQL set operator that combines data from two or more tables and returns a single result set. The

Union All operator is used to combine rows from two or more tables into a single result set, including any duplicate rows. The primary keyword used to implement the

Union All operator is “UNION ALL”. For example, using the same “celebrities” and “politicians” tables, you can use the

Union All operator to combine rows from both tables as follows:

SELECT * FROM celebrities

UNION ALL

SELECT * FROM politicians;

In the above example, the SELECT statement selects all the rows from “celebrities” and “politicians”. The

Union All operator combines the rows from both tables, including any duplicate rows.

Except

The

Except operator is an SQL set operator that returns the records from the first table that are not present in the second table. The primary keyword used to implement the

Except operator is “EXCEPT” or “MINUS”.

For example, suppose you have two tables named “celebrities” and “politicians”. You can use the

Except operator to eliminate all the rows from “politicians” that also exist in “celebrities” as follows:

SELECT * FROM celebrities

EXCEPT

SELECT * FROM politicians;

In the above example, the SELECT statement selects all the rows from “celebrities” and eliminates any row that also exists in “politicians”.

Intersect

The

Intersect operator is an SQL set operator that returns the common records from two tables. The primary keyword used to implement the

Intersect operator is “INTERSECT”.

For example, suppose you have two tables named “celebrities” and “politicians”. You can use the

Intersect operator to select only the rows that exist in both tables as follows:

SELECT * FROM celebrities

INTERSECT

SELECT * FROM politicians;

In the above example, the SELECT statement selects all the rows that exist in both “celebrities” and “politicians”.

Understanding Venn Diagrams

Venn diagrams are graphical representations of set theory concepts. A Venn diagram consists of overlapping circles that represent sets.

Each circle represents a set, and the overlapping portion between the circles represents the intersection of the two sets. The non-overlapping portion of each circle represents the complement of the set.

Venn diagrams can be used to illustrate set operations such as Union, Except, and Intersect.

Union Illustrated with Venn Diagram

The

Union of two sets is represented by a Venn diagram as follows:

Image credit: By Mate2code – Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=96520458

In the above diagram, A and B are two sets. The shaded region represents the

Union of A and B.

The

Union of A and B includes all the elements that are in either A or B or both.

Except Illustrated with Venn Diagram

The

Except of two sets is represented by a Venn diagram as follows:

Image credit: By Sdcowriter – Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=46608298

In the above diagram, A and B are two sets. The shaded region represents the

Except of A and B.

The

Except of A and B includes all the elements that are in A but not in B.

Intersect Illustrated with Venn Diagram

The

Intersect of two sets is represented by a Venn diagram as follows:

Image credit: By Sdcowriter – Own work, CC BY-SA 4.0, https://commons.wikimedia.org/w/index.php?curid=46608292

In the above diagram, A and B are two sets. The shaded region represents the

Intersect of A and B.

The

Intersect of A and B includes all the elements that are in both A and B.

Conclusion

SQL set operators are powerful tools that allow you to combine or exclude data from multiple tables. Union,

Union All, Except, and

Intersect are some of the commonly used SQL set operators.

Venn diagrams can be used to visualize these set operations. By understanding SQL set operators and Venn diagrams, you can write SQL queries that answer complex questions with ease.

Using SQL Set Operators: Examples of Union,

Union All, Except, and Intersect

In the previous section, we explored SQL set operators and their implementation using primary keywords. This section will provide examples of using SQL set operators in real-world scenarios.

We will use the same tables, “celebrities” and “politicians”, for our examples. We will start with examples of using the

Union operator, followed by the difference between

Union All and Union. Finally, we will provide examples of using the

Except and

Intersect operators.

Example of using

Union

Suppose we have two tables named “celebrities” and “politicians”, containing the following records:

Table: Celebrities

| Id | Name |

|—-|—————–|

| 1 | Leonardo DiCaprio|

| 2 | Jennifer Lawrence|

| 3 | Angelina Jolie |

| 4 | Brad Pitt |

Table: Politicians

| Id | Name |

|—-|—————–|

| 1 | Barack Obama |

| 2 | Donald Trump |

| 3 | Hillary Clinton |

| 4 | Joe Biden |

We want to combine the data from both tables into a single result set, eliminating any duplicate records. We can use the

Union operator to accomplish this as follows:

SELECT * FROM celebrities

UNION

SELECT * FROM politicians;

The result of the above SQL query would be:

| Id | Name |

|—-|—————–|

| 1 | Leonardo DiCaprio|

| 2 | Jennifer Lawrence|

| 3 | Angelina Jolie |

| 4 | Brad Pitt |

| 1 | Barack Obama |

| 2 | Donald Trump |

| 3 | Hillary Clinton |

| 4 | Joe Biden |

This result set eliminates any duplicate records from both tables.

Union All vs.

Union

Union All and

Union have a key difference that can affect query performance.

Union eliminates duplicate records, while

Union All includes all records from both tables, including duplicates. Therefore,

Union All can result in a larger result set than Union. Let’s consider the following example:

Table: celebrities

| Id | Name |

|—-|—————–|

| 1 | Leonardo DiCaprio|

| 2 | Jennifer Lawrence|

| 3 | Angelina Jolie |

| 4 | Brad Pitt |

Table: politicians

| Id | Name |

|—-|—————–|

| 1 | Barack Obama |

| 2 | Donald Trump |

| 3 | Barack Obama |

| 4 | Joe Biden |

We want to combine the data from both tables into a single result set, including duplicates.

We can use the

Union All operator as follows:

SELECT * FROM celebrities

UNION ALL

SELECT * FROM politicians;

The result of the above SQL query would be:

| Id | Name |

|—-|—————–|

| 1 | Leonardo DiCaprio|

| 2 | Jennifer Lawrence|

| 3 | Angelina Jolie |

| 4 | Brad Pitt |

| 1 | Barack Obama |

| 2 | Donald Trump |

| 3 | Barack Obama |

| 4 | Joe Biden |

Compared to the

Union operator, the

Union All operator returns the duplicate records from both tables. However, since

Union All does not eliminate duplicates, it performs faster than the

Union operator. Example of using

Except

Suppose we have two tables named “celebrities” and “politicians”, containing the following records:

Table: Celebrities

| Id | Name |

|—-|—————–|

| 1 | Leonardo DiCaprio|

| 2 | Jennifer Lawrence|

| 3 | Angelina Jolie |

| 4 | Brad Pitt |

Table: Politicians

| Id | Name |

|—-|—————–|

| 1 | Barack Obama |

| 2 | Donald Trump |

| 3 | Hillary Clinton |

| 4 | Joe Biden |

We want to select all the records from “celebrities” that are not present in “politicians”.

We can use the

Except operator to accomplish this as follows:

SELECT * FROM celebrities

EXCEPT

SELECT * FROM politicians;

The result of the above SQL query would be:

| Id | Name |

|—-|—————–|

| 1 | Leonardo DiCaprio|

| 2 | Jennifer Lawrence|

| 3 | Angelina Jolie |

| 4 | Brad Pitt |

This result set eliminates all the records that exist in “politicians” table. Example of using

Intersect

Suppose we have two tables named “celebrities” and “politicians”, containing the following records:

Table: Celebrities

| Id | Name |

|—-|—————–|

| 1 | Leonardo DiCaprio|

| 2 | Jennifer Lawrence|

| 3 | Angelina Jolie |

| 4 | Brad Pitt |

Table: Politicians

| Id | Name |

|—-|—————–|

| 1 | Barack Obama |

| 2 | Donald Trump |

| 3 | Hillary Clinton |

| 4 | Joe Biden |

We want to select all the records that exist in both “celebrities” and “politicians”.

We can use the

Intersect operator to accomplish this as follows:

SELECT * FROM celebrities

INTERSECT

SELECT * FROM politicians;

The result of the above SQL query would be an empty result set since there are no records that exist in both “celebrities” and “politicians”.

Conclusion

SQL set operators, including Union,

Union All, Except, and Intersect, provide powerful tools for combining and excluding data from multiple tables. These operators are widely used to answer complex queries that require merging or eliminating data from multiple tables.

Using SQL set operators, we can write SQL queries that answer complex questions with ease. In this article, we have provided examples of using SQL set operators in real-world scenarios.

By understanding the differences between

Union All and Union, and the uses of

Except and

Intersect operators, we can write efficient SQL queries that return accurate and useful data. In this article, we have explored SQL set operators and how to use them to combine or exclude data from multiple tables.

We have covered four commonly used SQL set operators, Union,

Union All, Except, and Intersect, and provided examples of their implementation in real-world scenarios. We have also illustrated these set operations with Venn diagrams to provide a clear understanding of how they work.

Understanding SQL set operators is critical for anyone who works with databases as they provide powerful tools for answering complex queries. Remembering the differences between

Union All and Union, and the uses of

Except and

Intersect operators are essential to writing efficient SQL queries that return accurate and useful data. By mastering these concepts, we can unlock the full potential of our databases and make more informed decisions.

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