Back To Base (Make SQL Great Again)

I have to admit upfront that my brain is somehow incompatible with JPA. Every time I try to use JPA, I will somehow wind up fighting weird issues, be it LazyInitializationException with Hibernate, or weird sequence generator preallocation issues with EclipseLink. I don’t know what to use merge() for; I lack the mean to reattach a bean and overwrite its values from the database. I don’t want to bore you to death with all of the nitty-gritty details; all the reasons are summed in Issue #3 Remove JPA. I think that the number 1 reason of why JPA is incompatible with me is that

JPA is built around the idea that the Java classes, not the database, is the source of truth.

My way of thinking is the other way around: I think that the database (and not the JPA) is the source of truth. This way of thinking is however incompatible with the very core of the JPA technology and makes it impossible to use JPA for me.

The Source Of Truth

To allow Java beans to be the source of truth, JPA defines certain techniques and requires Hibernate to sync Java beans with the database behind the scenes. That is unfortunately a non-trivial issue which cannot be done automatically in certain cases, and that’s why JPA abstraction suffers from the following issues:

  • Hibernate must track changes done to the bean, in order to sync them to the underlying database. That is done by intercepting all calls to setters, which can only be done by runtime class enhancement (for every entity Hibernate creates a class which extends that entity, overrides all setters and injects some Hibernate core class which is notified of changes). Such class can hardly be called a POJO since passing that class around will start throwing LazyInitializationException like hell. That is the black magic, pure and evil.
  • It intentionally lacks the method to reattach a bean and overwrite its contents with the database contents - this goes against the idea of having Java class the source of truth.
  • By abstracting joins into Collections, it causes the programmers to unintentionally write code which suffers from the 1+N loading issues.

Since I’m very bullheaded, instead of trying to attune my mind towards JPA I explored the different approach: let’s step back and make the database the source of truth again.

Database As The Source Of Truth

Having Database as the source of truth means that the data in your bean may be obsolete the moment it leaves the database (since there might be somebody else already modifying that thing). The optimistic/pessimistic locking is the way around that, and to have the most recent data you will need to requery from the database.

The bean can now ditch all of its sync capabilities and become just a snapshot: a sample of the state of the database row at some particular time. Changes to the bean properties will no longer be propagated automatically to the database, but need to be done explicitly by the developer. The developer is once again in charge.

There - I have solved the whole detached/managed/lazy initialization exception nonsense for you :-)

The beans are once again POJOs with getters and setters, simply populated from the database by reading the data from the JDBC ResultSet and calling bean’s setters.

That can be achieved by a simple reflection. Moreover, no runtime enhancement is needed since the bean will never track changes; to save changes we will need to issue the INSERT/UPDATE statement. Also, since there’s no runtime enhancement, the bean is really a POJO and can be actually made serializable and passed around in the app freely, which means that you don’t need DTOs anymore.

The Vaadin-on-Kotlin Persistency Layer: vok-orm

There is a very handy library called JDBI which maps JDBC ResultSet to Java POJOs. This idea forms the very core of vok-db. To explain the data retrieving capabilities of the vok-db library, let’s begin by implementing a simple function which finds a bean by its ID.

vok-orm: Data Retrieval From Scratch

The findById() function will simply issue a select SQL statement which selects a single row, then passes it to JDBI to populate the bean with the contents of that row:

fun <T : Any> Connection.findById(clazz: Class<T>, id: Any): T? =
        createQuery("select * from ${clazz.databaseTableName} where id = :id")
                .addParameter("id", id)

The function is rather simple: it is actually nothing more but a simple Kotlin reimplementation of the very first example in the JDBI. The JDBI API will do nothing more but create a JDBC PreparedStatement, run it, create instances of clazz using the zero-arg constructor, populate the bean with data and return the first one. Using this approach it is easy to implement more of the finders, such as findAll(clazz: Class<T>), findBySQL(clazz: Class<T>, where: String). However, let’s focus on the findById() for now.

To obtain the JDBI’s Connection (which is a wrapper of JDBC’s connection), we simply poll the HikariCP connection pool and use the db{} method to start+commit the transaction for us. This will allow us to retrieve beans from the database easily, simply by calling the following statement from anywhere of your code, be it a background thread, or a Vaadin button click listener:

val person: Person = db { connection.findById(, 25L) }

This is nice, but we can do better. In the dependency injection world, for every bean there is a Repository or DAO class which defines such finder methods and fetches instances of that particular bean. However, we have no DI and therefore we do not have to have a separate class injected somewhere, just for the purpose of accessing a database. We are free to attach those finders right where they belong: as factory methods of the Person class:

class Person {
  companion object {
    fun findById(id: Long): Person? = db { connection.findById(, id) }

This will allow us to write the finder code even more concise:

val person = Person.findById(25L)

Yet, adding those pesky findById() (and all other finder methods such as findAll()) manually to every bean is quite a tedious process. Is there perhaps some easier, more automatized way to add those methods to every bean? Yes there is, by the means of mixins and companion objects.

As a first attempt, we will define a Dao interface as follows:

interface Dao<T> {
  fun findById(clazz: Class<T>, id: Any): T? = db { connection.findById(clazz, id) }

Remember that the companion object is just a regular object, and as such it can implement interfaces?

class Person {
  companion object : Dao<Person>

This allows us to call the finder method as follows:

val person = Person.findById(, 25L)

Not bad, but the is somewhat redundant. Is there a way to force Kotlin to fill it for us? Yes, by the means of extension methods and reified type parameters:

interface Dao<T> {}
inline fun <ID: Any, reified T : Entity<ID>> Dao<T>.findById(id: ID): T? = db { con.findById(, id) }

Now the finder code is perfect:

val person = Person.findById(25L)

vok-db follows this idea and provides the Dao interface for you, along with several of utility methods for your convenience. By the means of extension methods, you can define your own global finder methods, or you can simply attach finder methods to your beans as you see fit.

You can even define an extension property on Dao which produces Vaadin’s DataProvider, fetching all instances of that particular bean. Luckily, you don’t have to do that since vok-db already provides one for you.

Next up, data modification.

vok-db: Data Modification

Unfortunately JDBI doesn’t support persisting of the data, so we will have to do that ourselves. Luckily, it’s very simple: all we need to do is to generate a proper insert or update SQL statement:

interface Entity<ID: Any> : Serializable {
    fun save() {
        db {
            if (id == null) {
                // not yet in the database, insert
                val fields = meta.persistedFieldDbNames - meta.idDbname
                con.createQuery("insert into ${meta.databaseTableName} (${fields.joinToString()}) values (${ { ":$it" }.joinToString()})")
                id = con.key as ID
            } else {
                val fields = meta.persistedFieldDbNames - meta.idDbname
                con.createQuery("update ${meta.databaseTableName} set ${ { "$it = :$it" }.joinToString()} where ${meta.idDbname} = :${meta.idDbname}")

Simply by having your beans implement the Entity interface, you will gain the ability to save and/or create database rows:

data class Person(override var id: Long, var name: String): Entity<Long> {
  companion object : Dao<Person>

val person = Person.findById(25L) = "Duke Leto Atreides"

Pure simplicity:


Written on February 8, 2018