Скачать или смотреть How to Replace Values in JSON in Redshift

Struggling with replacing values in JSON stored in Amazon Redshift? This guide provides a step-by-step solution using SQL functions, tailored for JSON manipulation.
---
This video is based on the question https://stackoverflow.com/q/65023078/ asked by the user 'S M' ( https://stackoverflow.com/u/8594194/ ) and on the answer https://stackoverflow.com/a/65023144/ provided by the user 'Gordon Linoff' ( https://stackoverflow.com/u/1144035/ ) 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: How can I replace values in JSON in Redshift?

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.
---
How to Replace Values in JSON in Redshift: A Comprehensive Guide

Handling JSON data in a database can be quite challenging, especially when it comes to making specific alterations! Many users of Amazon Redshift encounter the need to modify JSON data stored in their tables, and this can include tasks like replacing values contained in JSON structures.

In this guide, we will tackle a particular problem: how to replace street names and house numbers with ‘--’ in a JSON column. Let’s break it down step by step.

Understanding the Problem

The JSON Structure

Imagine you have a column containing address information in JSON format that looks like this:

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

Your goal is to modify this JSON to replace all house_no and street_name values with --, resulting in this updated format:

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

Storing JSON in Redshift

In Amazon Redshift, JSON is often stored as a VARCHAR column. This means we need to use specific SQL functions to parse and manipulate this text-based structure effectively.

The Solution: Using regexp_replace()

The primary tool we need in this case is the regexp_replace() function. This function allows us to perform a regex based replacement directly on the JSON string. Let’s dive into how to utilize this effectively.

Steps to Replace Values in JSON

Identify the Function:
You will need to use regexp_replace() twice:

To replace the house_no values.

To replace the street_name values.

Write the SQL Query:
Here’s the SQL query you can use:

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

Explanation of the SQL Query

Outer regexp_replace():

This one targets the street_name values.

It looks for the pattern that matches the field name followed by its string value and replaces it with "street_name":"--".

Inner regexp_replace():

This replaces the house_no values in a similar way.

It targets any numeric values that follow the house_no field.

Global vs Local Replacement

It's essential to note that in Redshift, regexp_replace() functions already apply a global replacement by default. This means that all occurrences are replaced without needing additional parameters, which is the case in many other database systems.

Conclusion

Replacing values within JSON in Amazon Redshift might seem complex, but with the right usage of regexp_replace(), it can be done simply and effectively. Armed with the above query, you can easily convert your JSON columns to reflect the changes you need.

By following the steps outlined here, you’ve learned how to modify address information in JSON format, making your data more manageable according to your requirements. Let us know how your experience goes, or if you have further questions regarding JSON handling in Redshift!