Announcing Krush – idiomatic persistence layer for Kotlin, based on Exposed

We’ve released a persistence library for Kotlin, you can find it on our Github. It’s a JPA-to-Exposed SQL DSL generator.

TL;DR

We’ve released a persistence library for Kotlin, you can find it on our Github. It’s a JPA-to-Exposed SQL DSL generator.

The state of persistence in Kotlin

One of the key decisions that helped Kotlin gain massive popularity was to reuse Java ecosystem instead of inventing it’s own. This means that you can safely use Kotlin as a primary language for a project developed using any popular Java stack like Spring Boot and built with Java build tool like Maven. What this also means is that natural choice for persistence layer in Kotlin is Spring Data with JPA 3 with Hibernate as an implementation.

However, JPA, which highly relies on mutable objects and dirty checking, may not look like pure Kotlin, which tries to embrace functional programming and immutability. The official Spring JPA guide for Kotlin uses mutable classes and properties which is not really idiomatic for Kotlin where you want to use immutable data classes whenever it’s possible.

There are some other options, which can be used safely with Kotlin and data classes, like Spring Data JDBC — interesting approach based on pure JDBC, embracing DDD and aggregate root concepts or Micronaut Data JDBC — if you’re not tied to Spring ecosystem. But they’re both relatively new, not mature yet and miss another idiomatic Kotlin feature — a DSL for making SQL queries.

DSL for SQL queries

Another thing that made Kotlin really powerful and popular is its ability to construct Domain Specific Languages using features like property reference, operators, infix and extension functions. For example, for Android development there is excellent anko library for constructing complex view layouts for Android apps. In Spring/JPA the default approach to SQL queries are query methods, where you use special naming convention of methods in repository interfaces. The method names are parsed at runtime to provide required SQL queries and mapping. The naming convention is supported by IntelliJ Idea and other IDEs and works well in simple cases, but may be not flexible enough when you want complex queries e.g. with some conditions based on dynamic filters. If you want to use a true, type-safe, composable and idiomatic Kotlin SQL DSL, you can try to use other libraries, like Requery or Exposed.

Requery

Requery is a lightweight persistence library for Java and Kotlin with RxJava and Java 8 streams support. It uses annotations (both custom and JPA) to process your entities and generate some infrastructure code called “model”.

So given a Book interface:

@Entity
@Table(name = "books")

interface Book : Persistable {
    @get:Key @get:Generated
    val id: Long

    val isbn: String
    val author: String
    val title: String

    val publishDate: LocalDate
}

 

You can instantiate and persist it by using generated BookEntity class:

//given
val book = BookEntity().apply {
    setIsbn("1449373321")
    setPublishDate(LocalDate.of(2017, Month.APRIL, 11))
    setTitle("Designing Data-Intensive Applications")
    setAutor("Martin Kleppmann")
}

// when
val persistedBook = dataStore.insert(book)

And the use SQL DSL to fetch data and map the results back to entities:

// then
val books = dataStore.select(Book::class).where(Book::id eq  book.id).get().toList()

assertThat(books).containsExactly(persistedBook)

This was really close to our needs! We like the idea of having annotations on the entities combined with the rich SQL DSL. Also the RxJava bindings and lazy Kotlin sequences support looks promising. On the other side, there are few minor issues related to immutable classes support:

  • immutable interface approach needs to be backed up with this generated, mutablexxxEntity class
  • there are some restrictions: e.g. you cannot use them to map relations to other entities (just foreign keys by ids)
  • @Generated also doesn’t work for ids in data classes.

You can check example project using Requery in requery branch of krush-example project on GitHub.

Exposed

Another approach which given you rich SQL DSL support is Exposed — a Kotlin-only persistence layer maintained by the JetBrains team. It comes in two flavors: active-record DAO and lightweight SQL DSL. As we are not the fans of active records, we tried the SQL DSL flavor. It works by creating additional mapping code using Kotlin objects and extension functions:

object  BookTable : Table("books") {
    val id: Column<Long> = long("id").promaryKey().autoIncrement()
    val isbn: Column<String> = varchar("isbn". 255)
    val autor: Column<String> = varchar("author". 255)
    val title: Column<String> = varchar("title". 255)
    val publishDate: Column<LocalDate> = date("publishDate")
}

Then you can refer to these Column properties to create type-safe queries and map results using Kotlin collections API:

val titles: List<String> = BookTable
        .select { BookTable.author like "Martin K%" }
        .map { it[BookTable.title] }

As you can see, Exposed is not a full-blown ORM — there is no direct mapping to/from your domain classes into these Table objects, but it’s not hard to write simple mapping functions for that. You can also benefit from Kotlin null-types support and write bindings for your own types by using Kotlin’s extension functions. We wrote some time ago this article about our approach to using Exposed in our projects.

Krush

We really like the Kotlin-first feeling combined with great flexibility of Exposed, but at some time we were tired of writing these table mappings manually. We thought that it would be nice to generate them from JPA-compatible annotations, in similar way it’s done in Requery. This ended with building a library called Krush, which we’re announcing today ;)

Krush consist of two components:

  • annotation-processor which generates Exposed mappings by reading (a subset of) standard JPA annotations found on entity classes
  • utility functions for persisting entities and mapping from/to Exposed objects

So given this entity:

@Entity
@Table(name = "books")

data class Book(
    @Id @GeneratedValue
    val id: Long? = null,

    val isbn: String,
    val author: String,
    val title: String,
    val publishDate: LocalDate
)

Krush will generate BookTable object which allows to persist it like this:

//given
val book = Book(
        isbn = "1449373321", publishDate = LocalDate.of(2017, Month.APRIL, 11),
        title = "Designing Data-Intensive Applications", author = "Martin Kleppmann"
)
val persistedBook = BookTable.insert(book)
assertThat(persistedBook.id).isNotNull()

And write queries using type-safe DSL just like you were using plain Exposed:

val bookId = book.id ?: throw IllegalargumentException( )
val fetchedBook = BookTable.select { BookTable.id eq bookId }.singleOrNull()?.toBook( )
assertThat(fetchedBook).isEqualTo(book)

val selectedBooks = BookTable
        .select { BookTable.author like "Martin Kx" }
        .toBookList()

assertThat(selectedBooks).containsOnly(book)

That’s it! You can find more details and supported features in the README of Krush repository or in some example projects.

Enjoy! Looking for feedback from the community!

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Log4j and MDC in Grails

Log4j provides very useful feature: MDC - mapped diagnostic context. It can be used to store data in context of current thread. It may sound scary a bit but idea is simple.

My post is based on post http://burtbeckwith.com/blog/?p=521 from Burt Beckwith's excellent blog, it's definitely worth checking if you are interested in Grails.

Short background story...


Suppose we want to do logging our brand new shopping system and we want to have in each log customer's shopping basket number. And our system can be used at once by many users who can perform many transactions, actions like adding items and so on. How can we achieve that? Of course we can add basket number in every place where we do some logging but this task would be boring and error-prone. 

Instead of this we can use MDC to store variable with basket number in map. 

In fact MDC can be treated as map of custom values for current thread that can be used by logger. 


How to do that with Grails?


Using MDC with Grails is quite simple. All we need to do is to create our own custom filter which works for given urls and puts our data in MDC.

Filters in Grails are classes in directory grails-app/conf/* which names end with *Filters.groovy postfix. We can create this class manually or use Grails command: 
grails create-filters info.rnowak.App.Basket

In result class named BasketFilters will be created in grails-app/conf/info/rnowak/UberApp.

Initially filter class looks a little bit empty:
class BasketFilters {
def filters = {
all(controller:'*', action:'*') {
before = {

}
after = { Map model ->

}
afterView = { Exception e ->

}
}
}
}
All we need to do is fill empty closures, modify filter properties and put some data into MDC.

all is the general name of our filter, as class BasketFilters (plural!) can contain many various filters. You can name it whatever you want, for this post let assume it will be named basketFilter

Another thing is change of filter parameters. According to official documentation (link) we can customize our filter in many ways. You can specify controller to be filtered, its actions, filtered urls and so on. In our example you can stay with default option where filter is applied to every action of every controller. If you are interested in filtering only some urls, use uri parameter with expression describing desired urls to be filtered.

Three closures that are already defined in template have their function and they are started in these conditions:

  • before - as name says, it is executed before filtered action takes place
  • after - similarly, it is called after the action
  • afterView - called after rendering of the actions view
Ok, so now we know what are these mysterious methods and when they are called. But what can be done within them? In official Grails docs (link again) under section 7.6.3 there is a list of properties that are available to use in filter.

With that knowledge, we can proceed to implementing filter.

Putting something into MDC in filter


What we want to do is quite easy: we want to retrieve basket number from parameters and put it into MDC in our filter:
class BasketFilters {
def filters = {
basketFilter(controller:'*', action:'*') {
before = {
MDC.put("basketNumber", params.basketNumber ?: "")
}
after = { Map model ->
MDC.remove("basketNumber")
}
}
}
}

We retrieve basket number from Grails params map and then we put in map under specified key ("basketNumber" in this case), which will be later used in logger conversion pattern. It is important to remove custom value after processing of action to avoid leaks.

So we are putting something into MDC. But how make use of it in logs?


We can refer to custom data in MDC in conversion patter using syntax: %X{key}, where key is our key we used in filter to put data, like:
def conversionPattern = "%d{yyyy-MM-dd HH:mm:ss} %-5p %t [%c{1}] %X{basketNumber} - %m%n"


And that's it :) We've put custom data in log4j MDC and successfully used it in logs to display interesting values.