Book Image

jOOQ Masterclass

By : Anghel Leonard
Book Image

jOOQ Masterclass

By: Anghel Leonard

Overview of this book

jOOQ is an excellent query builder framework that allows you to emulate database-specific SQL statements using a fluent, intuitive, and flexible DSL API. jOOQ is fully capable of handling the most complex SQL in more than 30 different database dialects. jOOQ Masterclass covers jOOQ from beginner to expert level using examples (for MySQL, PostgreSQL, SQL Server, and Oracle) that show you how jOOQ is a mature and complete solution for implementing the persistence layer. You’ll learn how to use jOOQ in Spring Boot apps as a replacement for SpringTemplate and Spring Data JPA. Next, you’ll unleash jOOQ type-safe queries and CRUD operations via jOOQ’s records, converters, bindings, types, mappers, multi-tenancy, logging, and testing. Later, the book shows you how to use jOOQ to exploit powerful SQL features such as UDTs, embeddable types, embedded keys, and more. As you progress, you’ll cover trending topics such as identifiers, batching, lazy loading, pagination, and HTTP long conversations. For implementation purposes, the jOOQ examples explained in this book are written in the Spring Boot context for Maven/Gradle against MySQL, Postgres, SQL Server, and Oracle. By the end of this book, you’ll be a jOOQ power user capable of integrating jOOQ in the most modern and sophisticated apps including enterprise apps, microservices, and so on.
Table of Contents (26 chapters)
1
Part 1: jOOQ as a Query Builder, SQL Executor, and Code Generator
4
Part 2: jOOQ and Queries
11
Part 3: jOOQ and More Queries
16
Part 4: jOOQ and Advanced SQL
22
Part 5: Fine-tuning jOOQ, Logging, and Testing

Grouping sets

For those not familiar with grouping sets, let's briefly follow a scenario meant to quickly introduce and cover this notion. Consider the following screenshot:

Figure 13.24 – Two queries using a grouping set each

The groupBy(SALE.EMPLOYEE_NUMBER) construction from the left-hand side (respectively, groupBy(SALE.FISCAL_YEAR) from the right-hand side) is referred to as a grouping set. A grouping set can contain none (empty grouping set), one, or more columns. In our case, both grouping sets contain one column.

Getting a unified result set of these two result sets containing the aggregated data of both grouping sets can be done via the UNION ALL operator, as illustrated here:

Figure 13.25 – Union grouping sets

But, as you can see, even for only two grouping sets, this query is quite lengthy. Moreover, it needs to resolve two SELECT statements before combining their results into a single result set. Here...