Скачать или смотреть How to Run Postgres String Functions on a Column Created in the Same Query

Discover how to execute Postgres string functions in the same query with step-by-step guidance tailored for effective database management.
---
This video is based on the question https://stackoverflow.com/q/68992206/ asked by the user 'refriedjello' ( https://stackoverflow.com/u/3645278/ ) and on the answer https://stackoverflow.com/a/68992384/ provided by the user 'Laurenz Albe' ( https://stackoverflow.com/u/6464308/ ) 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: Run Postgres string function on column created in same query

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.
---
Running Postgres String Functions on a Column Created in the Same Query

Working with database queries often raises challenges, especially when handling string functions in PostgreSQL. One common issue is how to run a series of string functions on a column that you define within the same query. If you're using Postgres 11, this guide will guide you through the process of resolving this issue effectively.

The Problem: Understanding Your Needs

Imagine you have a source table called labels, structured simply as follows:

descr12345_orange23456B_yellow34567C_blueYou want to create a view that returns additional processed columns such as id, rate, and name based on the descr column. Your expected output would resemble this:

descridratename12345_orange12345orange23456B_yellow23456Byellow34567C_blue34567CblueTo achieve this, you need to extract specific components from the descr string. Here's where things can get tricky: The values might not always be in a consistent format. For example, the rate value might sometimes be absent, which adds complexity to your string extraction.

The Solution: Using Subqueries or CTEs

To correctly execute multiple string functions on the same dataset, you can utilize subqueries (or Common Table Expressions, CTEs). Let's break down how to implement this effectively.

Option 1: Subquery Method

You can utilize a subquery to first create a temporary set of data, where you compute the id and then use that in your main query to derive the rate. Here’s how to do it:

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

Explanation:

The inner query (SELECT labels.descr, SPLIT_PART(labels.descr, '_', 1) as id FROM labels) extracts the id by splitting the string, which is then referenced in the outer query to retrieve the rate.

Option 2: CTE (Common Table Expression) Method

Alternatively, you can use a CTE, which can make your SQL more readable and easier to manage:

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

Explanation:

The CTE defined at the beginning allows you to construct an intermediate result set (subq), making it accessible in the subsequent SELECT statement. This approach enhances organization and clarity in your SQL code.

Conclusion: Why the Original Query Fails

In your original attempt, the query resulted in an error stating that the column id does not exist. This happens because the SQL engine processes the query in stages, meaning that it does not recognize the new alias (id) from the previous section until you refer to it in a way that is defined beforehand (like in a subquery or CTE).

By using either of the methods described above, you can effectively manage string operations on the same dataset in a query.



This guidance not only helps in resolving the specific issue at hand but also improves your understanding of managing complex queries in PostgreSQL. Don’t hesitate to reach out if you have further questions or need assistance with SQL!