![]() Avoid Using COUNT() in SQL When You Could Use EXISTS().Using Testcontainers to Generate jOOQ Code.The Many Different Ways to Fetch Data in jOOQ.10 SQL Tricks That You Didn't Think Were Possible.A Beginner's Guide to the True Order of SQL Operations.Say NO to Venn Diagrams When Explaining JOINs.Join 2,145 other subscribers Top Posts & Pages Don’t Miss out on Awesome SQL Power with FIRST_VALUE(), LAST_VALUE(), LEAD(), and LAG().Do You Really Understand SQL’s GROUP BY and HAVING clauses?. ![]() The Awesome PostgreSQL 9.4 / SQL:2003 FILTER Clause for Aggregate Functions.Common SQL Clauses and Their Equivalents in Java 8 Streams.How to use SQL PIVOT to Compare Two Tables in Your Database.SQL incompatibilities: NOT IN and NULL values.Read more articles about awesome SQL here: While JOIN operations are much more versatile, they are also more complex for the simple tasks that can be solved by UNION, INTERSECT, and EXCEPTĭid you like this article? It’s part of the Data Geekery SQL Training – a 1-day workshop helping you to get the most out of the awesome SQL language. Consider the following query, which we’ll run against the Sakila database:Ĭonclusion UNION, INTERSECT, and EXCEPT are very simple, yet very useful operations that can add a lot of value every now and then in your daily SQL tasks. The original Venn diagrams used FULL OUTER JOIN to model the “same” concept, although the two things are not strictly same. In the following example, we’ll see that we might be interested in all the different people from our database, given their first and last names, regardless if they’re customer or staff: It is often also referred to as “concatenation” of two sets of tuples, where the result is the concatenation of a set B to a set A. The UNION operation is the most well-known among these set operations. In the following sections, we’ll see that these operations match exactly the semantics of operations that can be illustrated by Venn diagrams, even if you will be able to “abuse” JOIN operations to achieve the same result. The true meaning of Venn diagrams is much better described by the operations When you join BOOK to AUTHOR, you will probably get a combination of every author ∈ AUTHOR with each book ∈ BOOK, such that for each combination (author, book), the author actually wrote the book. In a cartesian product between two sets A and B, the result is the multiplication of each set, meaning that each element a ∈ A is combined with each element b ∈ B to form a set of tuples (a, b). While these Venn diagrams are certainly useful to understand (and remember) SQL JOIN syntax, they’re not entirely accurate, because SQL JOIN is a special type of a cartesian product, the CROSS JOIN. When people talk about SQL JOIN, they often use Venn Diagrams to illustrate inclusion and exclusion of the two joined sets:
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