Скачать или смотреть Solving the SQL Dilemma: Mastering NOT LIKE with Logical Operators

Learn how to effectively use `NOT LIKE` and `AND` statements in SQL queries to avoid unexpected outputs and get the results you need.
---
This video is based on the question https://stackoverflow.com/q/77811560/ asked by the user 'Daniel' ( https://stackoverflow.com/u/23239723/ ) and on the answer https://stackoverflow.com/a/77811608/ provided by the user 'Kazi Mohammad Ali Nur Romel' ( https://stackoverflow.com/u/8651601/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Using NOT LIKE and OR statement together producing FALSE output

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Understanding the SQL Issue: NOT LIKE and OR Confusion

SQL can sometimes be tricky, especially when dealing with logical operators like AND and OR. A common problem developers face is using the NOT LIKE statement in conjunction with OR, which can lead to unexpected results. In this guide, we will analyze a specific scenario where the combination of these operators produces false outputs, leaving you scratching your head instead of getting the results you expect.

Imagine you're querying a database to filter out certain names that contain specific keywords. However, instead of excluding these entries, your SQL query still returns results that shouldn't be there. This situation is not uncommon, and it often stems from how the logical operators interact in your SQL statement.

Let’s take a look at the problem, evaluate the provided SQL query, and discover how to fix it.

The Problem Query

Here is the SQL statement that raised the concern:

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

What's Going Wrong?

The issue arises from the use of the OR statement in conjunction with the NOT LIKE operator. Here’s why it doesn’t yield the desired results:

Understanding NOT LIKE: The NOT LIKE operator is used to exclude entries that match a given pattern. If any condition in an OR statement is true, the entire condition evaluates to true.

For example: If ld.lead_name contains 'automation', the condition ld.lead_name NOT LIKE 'automation%' would return false, but the other conditions like ld.lead_name NOT LIKE '%test%' would return true. Thus, because of the OR, the entire expression evaluates to true, resulting in unwanted outputs.

The Solution: Switch to AND

To achieve the desired filtering, you need to change your logical operator from OR to AND. This way, all conditions must be satisfied for a record to be included in the final result set. Here's the corrected query:

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

Explanation of the Fix

AND Logic: By replacing OR with AND, we've ensured that only entries that do not match any of the specified patterns will be included in the results.

Comprehensive Filtering: Now, all conditions must be met for an entry to be returned, which means that if any NOT LIKE condition evaluates to false, the entire WHERE clause will return false, effectively filtering out those entries we want to exclude.

Conclusion

Understanding the interactions of logical operators in SQL is crucial for writing effective queries that yield the expected results. By carefully choosing between AND and OR, you can avoid common pitfalls like the one discussed here.

So the next time you're faced with a filtering issue in SQL involving NOT LIKE, remember to evaluate the structure of your conditions and choose the appropriate logical operator to achieve the desired outcome.

With this knowledge, you can refine your SQL querying skills and tackle similar problems with confidence!