I just announced the new Spring 5 modules in REST With Spring:
Spring Boot allows us to import sample data into our database – mainly to prepare data for integration tests. Out of the box, there are two possibilities. We can use import.sql (Hibernate support) or data.sql (Spring JDBC support) files to load data.
However, sometimes we want to split one big SQL file into a few smaller ones, e.g., for better readability or to share some files with an init data between modules.
In this tutorial, we’ll show how to do it with both – Hibernate and Spring JDBC.
2. Hibernate Support
We can define files which contain sample data to load with a property spring.jpa.properties.hibernate.hbm2ddl.import_files. It can be set in the application.properties file inside the test resources folder.
This is in a case we want to load sample data just for JUnit tests. The value has to be a comma-separated list of files to import:
This configuration will load sample data from two files: import_active_users.sql and import_inactive_users.sql. Important to mention here is that we have to use prefix spring.jpa.properties to pass values (JPA configuration) to the EntityManagerFactory.
Next, we’ll show how we can do it with a Spring JDBC support.
3. Spring JDBC Support
The configuration for initial data and Spring JDBC support is very similar to Hibernate. We have to use the spring.datasource.data property:
Setting the value as above gives the same results as in the Hibernate support. However, a significant advantage of this solution is a possibility to define value using an Ant-style pattern:
The above value tells the Spring to search for all files with a name that matches import_*_users.sql pattern and import data which is inside.
In this short article, we showed how to configure Spring Boot application to load initial data from custom SQL files.
Finally, we showed two possibilities – Hibernate and Spring JDBC. They both work pretty well, and it’s up to the developer which one to chose.
As always, the complete code examples used in this article is available over on Github.