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Скачать или смотреть Converting Oracle-style Queries to JPQL in Spring Boot JPA: Using LIKE and Handling NULL Values

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  • 2025-10-06
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Converting Oracle-style Queries to JPQL in Spring Boot JPA: Using LIKE and Handling NULL Values
like and nvl in jpql query - springboot JPApostgresqlspring boothibernatespring data jpa
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Описание к видео Converting Oracle-style Queries to JPQL in Spring Boot JPA: Using LIKE and Handling NULL Values

Learn how to convert Oracle-style queries to JPQL in Spring Boot, including solutions for handling `NULL` values in a `LIKE` clause.
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This video is based on the question https://stackoverflow.com/q/67812236/ asked by the user 'F0cus' ( https://stackoverflow.com/u/3211648/ ) and on the answer https://stackoverflow.com/a/67821502/ provided by the user 'F0cus' ( https://stackoverflow.com/u/3211648/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Converting Oracle-style Queries to JPQL in Spring Boot JPA: A Step-by-Step Guide

When working with databases in Java applications, it's not uncommon to encounter challenges with query languages. In this post, we will explore how to convert an Oracle-style SQL query into JPQL (Java Persistence Query Language) using Spring Boot and JPA. We will specifically address the usage of the LIKE operator while elegantly handling NULL values. If you're new to JPA or facing similar issues, this guide is for you!

Understanding the Problem

You may find yourself needing to convert complex SQL queries into JPQL when working with Spring Boot. For example, consider the following Oracle SQL query that uses the LIKE operator alongside the NVL function:

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

In this query, NVL is used to replace NULL with the first_name itself, allowing for flexible searching. Translating this logic into JPQL can pose challenges, especially for new users who are still becoming familiar with the JPA framework.

The Solution

To achieve similar behavior in JPQL, we need to make a few adjustments. Here's how we can rewrite our query to effectively handle NULL values and utilize the LIKE operator.

JPQL Query Adjustment

Instead of using NVL, we can modify our JPQL to check for nulls directly in the WHERE clause. Here’s the revised JPQL query:

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

This query will allow a search to proceed if packageName is NULL, essentially ignoring the filter condition when there is no search term provided.

Controller Logic to Handle NULL Values

Additionally, you may wish to implement some logic in your controller to manage NULL inputs before they reach the repository layer. Here is how you can handle a potential NULL input cleanly:

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

The repoPackage.getPackageAll(search.getPackageName()) method will be invoked with a default value if no input is provided.

Repository Condition

In the repository layer, your where condition will leverage the logic we've discussed. Here’s how it would look:

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

This ensures that if packageName matches the default value, the query will proceed to search within the packageName field.

Summary

In this guide, we demonstrated how to convert an Oracle-style query to JPQL, incorporating the LIKE operator while effectively managing NULL values. By modifying both the JPQL query and implementing strategic checks in the controller, we ensure our application can gracefully handle various scenarios without throwing errors.

This approach promotes cleaner and more maintainable code — a critical consideration in software development. If you ever find yourself needing similar functionality, remember these patterns, and feel free to adapt them according to your specific needs!

Conclusion

Converting SQL queries to JPQL does not have to be an intimidating task. By understanding how to manipulate queries while managing special cases like NULL, you can enhance your application's querying capabilities. Embrace the power of JPQL and Spring Boot for a robust data handling experience!

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