It’s typical for many applications, including web applications, to read and write to a database. JDBC operations are significantly simplified when using Spring JdbcTemplates and Kotlin’s language features. For example, it’s easy to one line read and insert operations into a database. This post goes through a sample web application that inserts a user into a database table and then prints a list of all users stored in the database.

Interacting with the Database

Our first order of business is to create a database schema. This is the SQL script that we will use to generate our database.

DROP TABLE IF EXISTS USERS;

CREATE TABLE USERS (
  id INTEGER IDENTITY,
  first_name VARCHAR(50),
  last_name VARCHAR(50),
  email VARCHAR(50),
  phone VARCHAR(50),
)

Now we will define a database that maps to the information held in our database. Kotlin’s data classes are ideal for this sort of task.

//Define a data class that maps to both our
//form and database table
data class User(var firstName: String = "",
                var lastName: String = "",
                var email: String = "",
                var phone: String = "")

There isn’t anything special about our User class. It’s only job is to carry information from the view to the database and back from the database to the view. Now that we have a database table and a transfer object, we need to configure our datasource so that Spring can connect our application to our database. We will define a configuration class that will define some Spring beans for us.

@Configuration
class Configuration {

    //First configure a data source that
    //generates an embedded db
    @Bean(name = arrayOf("dataSource"))
    fun dataSource(): DataSource {

        //This will create a new embedded database and run the schema.sql script
        return EmbeddedDatabaseBuilder()
                .setType(EmbeddedDatabaseType.HSQL)
                .addScript("schema.sql")
                .build()
    }

    //Create a JdbcTemplate Bean that connects to our database
    @Bean
    fun jdbcTemplate(@Qualifier("dataSource") dataSource: DataSource): JdbcTemplate {
        return JdbcTemplate(dataSource)
    }
}

The first bean, dataSource, returns an EmbeddedDatabaseBuilder object that does the work of creating an embedded database, setting it’s dialect, and running our schema.sql script to create the database definition. At this point, our database is fully ready when the build() method is called.

The next bean is a JdbcTemplate object. We create a bean definition for it so that we can inject instances of this object into our repository classes later on. The JdbcTemplate requires a DataSource object, which happens to point at our embedded database. Now let’s define a repository class that will actually work with our JdbcTemplate.

@Repository
class IndexRepository(@Autowired var jdbcTemplate: JdbcTemplate) {


    fun addUser(user: User) {
        //We can use SimpleJdbcInsert to insert a value into our table
        //The becomes super concise when combined with Kotlins apply and mapOf functions
        SimpleJdbcInsert(jdbcTemplate).withTableName("USERS").apply {
            setGeneratedKeyName("id")
            execute(
                    mapOf("first_name" to user.firstName,
                            "last_name" to user.lastName,
                            "email" to user.email,
                            "phone" to user.phone))
        }
    }

    //This allows us to query the Users table and return a list of users
    //This is one method call to jdbcTemplate with a lambda expression which makes the code
    //incredibly concise
    fun allUsers(): List = jdbcTemplate.query("SELECT FIRST_NAME, LAST_NAME, EMAIL, PHONE FROM USERS",
            { rs: ResultSet, _: Int ->
                User(rs.getString("first_name"), rs.getString("last_name"), rs.getString("email"), rs.getString("phone"))
            })
}

@Respository is a Spring sterotype annotation that marks our IndexRepository as a class that is intended to interact with the datasource. Spring provides two other stereotype annotations, @Controller and @Service, that are typically used to mark seperations in the application. @Controller is intended to interact with the view, while @Respository works with datasource. @Service should contain business logic. When developers follow this pattern, the application maintains loose coupling which makes it easy to maintain and test code.

Since IndexController is marked with @Repository, it makes sense to inject JdbcTemplate into this class so that it can work with the database. We have two methods in this class: addUser and allUsers. We’ll take each function on its own.

The addUser(user : User) method performs an insert into the database. We create an instance of SimpleJdbcInsert and pass our JdbcTemplate object into this class. The following call to withTable(“USERS”) specifies which table we are inserting a record into. Since our primary key is generated automatically by the database, we can use SimpleJdbcInsert.setGeneratedKeyName(“id”) to assign a primary key. Finally we use the execute() function to actually perform the insertion into the database. The execute() takes a map where the key is the name of the column in the database and the value is what we are inserting into the column.

There is some Kotlin magic that helps keep the code concise. For one, we are chaining our calls to setGeneratedKeyName() and execute() inside of the apply() function. We can also leverage Kotlin’s mapOf() function to generate a Map on the fly as opposed to creating a map object and populating it with values ahead of time.

The allUsers() function queries the database. In this case, we can call the query method from the jdbcTemplate object. The query() method requires two parameters. The first parameter is the query that is sent to the database. The second method is a an instance of RowMapper, which is a single abstract method (SAM) class. Since RowMapper has only one method, we can use a lambda expression to provide an implementation of RowMapper.

The RowMapper’s job is to transform the results of the database query into a User object. It provides with two objects that help with this job. The first is the good old JDBC ResetSet object and the other object is an Int that represents the row number. We only use the ResultSet in this example. The ResultSet interface has a getString() method that takes the name of the column and outputs the value stored in that column. Using getString(), we can populate each field of a User object and return it. RowMapper will handle the details of building a list and returning the List to the caller.

Web Portion

The remaining part of the application is a Spring MVC application. We aren’t going to spend a lot of time on this portion but are including it for After the @Repository tier (covered above), we have a service class that handles the business logic between the @Controller and the @Repository. In our case, it’s really boring because all our @Service class is doing is acting as a wrapper for our @Repository class, but in the real world, there is generally more application code located in this class.

@Service
class IndexService(
    //Inject IndexRepository here
    @Autowired var indexRepository: IndexRepository) {

    fun addUser(user: User) {
        indexRepository.addUser(user)
    }

    fun allUsers(): List {
        return indexRepository.allUsers()
    }
}

We also have a @Controller class that handles HTTP GET and POST requests.

@Controller
@RequestMapping("/")
class IndexController(@Autowired var indexService: IndexService) {

    @RequestMapping(method = arrayOf(RequestMethod.GET))
    fun doGet(model: Model): String {
        model.addAttribute("user", User())
        model.addAttribute("allUsers", indexService.allUsers())
        return "index"
    }

    @RequestMapping(method = arrayOf(RequestMethod.POST))
    fun doPost(model: Model, user: User): String {
        indexService.addUser(user)

        model.addAttribute("user", User())
        model.addAttribute("allUsers", indexService.allUsers())
        return "index"
    }
}

And finally the view…

Conclusion

Kotlin greatly enchances the already excellent JDBC abilities offered by Spring Boot. As was demonstrated in this post, developers can start with definining a data class that holds all of the data in a single row in a database table. When it comes to actually perform inserts or queries from the database, Kotlin’s mapOf(), apply, and to functions cut down on any additional verbosity that might still remain from using JDBC Template. As always, Spring makes it super simple to spring up a web application that interfaces with a database.

You can grab the source for this example from my GitHub page or view the Video tutorial on YouTube.