How to SELECT Rows Starting with Multiple Values in MySQL Using C#

Описание: Learn how to effectively query rows in MySQL that match prefixes stored in a separate table using C-. This guide explores using JOIN instead of subqueries for successful results.
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Selecting Rows Starting with Multiple Prefixes: A Practical Guide

Do you need to pull data from a MySQL database where you want to select rows based on prefixes stored in another table? If so, you've come to the right place! In this post, we'll explore a common scenario faced by developers using C- and MySQL and provide a solution using the JOIN operation.

The Problem

Imagine you have two tables: table_1 containing authors and their details, and table_2 that has a list of prefixes. Your goal is to select all authors whose names begin with any prefix specified in table_2.

Here’s the structure of the tables:

table_1:

[[See Video to Reveal this Text or Code Snippet]]

table_2:

[[See Video to Reveal this Text or Code Snippet]]

When you attempt to use a subquery to fetch these prefixes, you might encounter the error: Error Code: 1242. Subquery returns more than 1 row. This is because the subquery is returning multiple rows which cannot concatenate into a single value as intended.

The Solution: Using JOIN

Why Use JOIN?

Instead of relying on subqueries, a more effective approach is to employ the JOIN operation. By doing so, you efficiently connect the two tables based on the condition of matching prefix values, allowing for a straightforward selection of authors who meet the criteria.

The SQL Query

Here’s how you can write the SQL query using JOIN:

[[See Video to Reveal this Text or Code Snippet]]

Breaking Down the Query

FROM table_1 AS t1: This indicates that we’re selecting data starting from table_1, and we’re aliasing it as t1 for brevity.

JOIN table_2 AS t2: We join table_2 (aliased as t2) to gain access to its PreFix data.

ON t1.aut_name LIKE CONCAT(t2.PreFix, '%'): This ON clause specifies that we want to include only those records from table_1 where the author’s name starts with any prefix from table_2. The LIKE operator combined with CONCAT checks for matches.

Building the Tables

For those who want to replicate this example, here are the DDL (Data Definition Language) and DML (Data Manipulation Language) statements to create and populate the tables:

[[See Video to Reveal this Text or Code Snippet]]

Conclusion

Using JOIN instead of subquerying can significantly simplify your queries, especially in cases where you're dealing with multiple values. In this guide, you learned how to effectively select authors whose names start with prefixes stored in another table, avoiding common pitfalls associated with subqueries.

Try implementing this approach in your applications and feel the difference it makes in your data querying processes.