Krush is a lightweight persistence layer for Kotlin based on Exposed SQL DSL. It’s similar to Requery and Micronaut-data jdbc, but designed to work idiomatically with Kotlin and immutable data classes.
It’s based on a compile-time JPA annotation processor that generates Exposed DSL table and objects mappings for you. This lets you instantly start writing type-safe SQL queries without need to write boilerplate infrastructure code.
- (type-safe) SQL-first - use type-safe SQL-like DSL in your queries, no string or method name parsing
- Minimal changes to your domain model - no need to extend external interfaces and used special types - just add annotations to your existing domain model
- Explicit fetching - you specify explicitly in query what data you want to fetch, no additional fetching after data is loaded
- No runtime magic - no proxies, lazy loading, just data classes containing data fetched from DB
- Pragmatic - easy to start, but powerful even in not trivial cases (associations, grouping queries)
Given a simple Book class:
data class Book(
val id: Long? = null,
val isbn: String,
val title: String,
val author: String,
val publishDate: LocalDate
)we can turn it into Krush entity by adding @Entity and @Id annotations:
@Entity
data class Book(
@Id @GeneratedValue
val id: Long? = null,
val isbn: String,
val title: String,
val author: String,
val publishDate: LocalDate
)When we build the project we’ll have BookTable mapping generated for us. So we can persist the Book:
val book = Book(
isbn = "1449373321", publishDate = LocalDate.of(2017, Month.APRIL, 11),
title = "Designing Data-Intensive Applications", author = "Martin Kleppmann"
)
// insert method is generated by Krush
val persistedBook = BookTable.insert(book)
assertThat(persistedBook.id).isNotNull()So we have now a Book persisted in DB with autogenerated Book.id field.
And now we can use type-safe SQL DSL to query the BookTable:
val bookId = book.id ?: throw IllegalArgumentException()
// toBook method is generated by Krush
val fetchedBook = BookTable.select { BookTable.id eq bookId }.singleOrNull()?.toBook()
assertThat(fetchedBook).isEqualTo(book)
// toBookList method is generated by Krush
val selectedBooks = (BookTable)
.select { BookTable.author like "Martin K%" }
.toBookList()
assertThat(selectedBooks).containsOnly(persistedBook)Gradle Groovy:
repositories {
mavenCentral()
}
apply plugin: 'kotlin-kapt'
dependencies {
api "pl.touk.krush:krush-annotation-processor:$krushVersion"
kapt "pl.touk.krush:krush-annotation-processor:$krushVersion"
api "pl.touk.krush:krush-runtime:$krushVersion"
}Gradle Kotlin:
repositories {
mavenCentral()
}
plugins {
kotlin("kapt") version "$kotlinVersion"
}
dependencies {
api("pl.touk.krush:krush-annotation-processor:$krushVersion")
kapt("pl.touk.krush:krush-annotation-processor:$krushVersion")
api("pl.touk.krush:krush-runtime:$krushVersion")
}Maven:
<dependencies>
<dependency>
<groupId>pl.touk.krush</groupId>
<artifactId>krush-runtime</artifactId>
<version>${krush.version}</version>
</dependency>
</dependencies>
...
<plugin>
<groupId>org.jetbrains.kotlin</groupId>
<artifactId>kotlin-maven-plugin</artifactId>
<executions>
<execution>
<id>kapt</id>
<goals>
<goal>kapt</goal>
</goals>
<configuration>
...
<annotationProcessorPaths>
<annotationProcessorPath>
<groupId>pl.touk.krush</groupId>
<artifactId>krush-annotation-processor</artifactId>
<version>${krush.version}</version>
</annotationProcessorPath>
</annotationProcessorPaths>
</configuration>
</execution>
...
</executions>
</plugin>- JetBrains Exposed
- JPA annotations 2.1
- generates table mappings and functions for mapping from/to data classes
- type-safe SQL DSL without reading schema from existing database (code-first)
- explicit association fetching (via
leftJoin/innerJoin) - multiple data types support, including type aliases
- custom data type support (with
@Converter), also for wrapped auto-generated ids - you can still persist associations not directly reflected in domain model (eq. article favorites)
However, Krush is not a full-blown ORM library. This means following JPA features are not supported:
- lazy association fetching
- dirty checking
- caching
- versioning / optimistic locking
Given following entity:
@Entity
data class Reservation(
@Id
val uid: UUID = UUID.randomUUID(),
@Enumerated(EnumType.STRING)
val status: Status = Status.FREE,
val reservedAt: LocalDateTime? = null,
val freedAt: LocalDateTime? = null
) {
fun reserve() = copy(status = Status.RESERVED, reservedAt = LocalDateTime.now())
fun free() = copy(status = Status.FREE, freedAt = LocalDateTime.now())
}
enum class Status { FREE, RESERVED }you can call Exposed update with generated from metod to overwrite it's data:
val reservation = Reservation().reserve().let(ReservationTable::insert)
val freedReservation = reservation.free()
ReservationTable.update({ ReservationTable.uid eq reservation.uid }) { it.from(freedReservation) }
val updatedReservation = ReservationTable.select({ ReservationTable.uid eq reservation.uid }).singleOrNull()?.toReservation()
assertThat(updatedReservation?.status).isEqualTo(Status.FREE)
assertThat(updatedReservation?.reservedAt).isEqualTo(reservation.reservedAt)
assertThat(updatedReservation?.freedAt).isEqualTo(freedReservation.freedAt)For simple cases you can still use Exposed native update syntax:
val freedAt = LocalDateTime.now()
ReservationTable.update({ ReservationTable.uid eq reservation.uid }) {
it[ReservationTable.status] = Status.FREE
it[ReservationTable.freedAt] = freedAt
}Other Exposed features are supported as well, like, replace:
val reservation = Reservation().reserve()
ReservationTable.replace { it.from(reservation) }
val freedReservation = reservation.free()
ReservationTable.replace { it.from(freedReservation) }
val allReservations = ReservationTable.selectAll().toReservationList()
assertThat(allReservations).containsExactly(freedReservation)and batchInsert/batchReplace:
val reservation1 = Reservation().reserve()
val reservation2 = Reservation().reserve()
ReservationTable.batchInsert(
listOf(reservation1, reservation2), body = { this.from(it) }
)
val allReservations = ReservationTable.selectAll().toReservationList()
assertThat(allReservations)
.containsExactly(reservation1, reservation2)
}@Entity
@Table(name = "articles")
data class Article(
@Id @GeneratedValue
val id: Long? = null,
@Column(name = "title")
val title: String,
@ManyToMany
@JoinTable(name = "article_tags")
val tags: List<Tag> = emptyList()
)
@Entity
@Table(name = "tags")
data class Tag(
@Id @GeneratedValue
val id: Long? = null,
@Column(name = "name")
val name: String
)Persisting
val tag1 = Tag(name = "jvm")
val tag2 = Tag(name = "spring")
val tags = listOf(tag1, tag2).map(TagTable::insert)
val article = Article(title = "Spring for dummies", tags = tags)
val persistedArticle = ArticleTable.insert(article)Querying and fetching
val (selectedArticle) = (ArticleTable leftJoin ArticleTagsTable leftJoin TagTable)
.select { TagTable.name inList listOf("jvm", "spring") }
.toArticleList()
assertThat(selectedArticle).isEqualTo(persistedArticle)Update logic for associations not implemented (yet!) - you have to manually add/remove records from ArticleTagsTable.
Krush exposes some helpful wrappers for user classes to easily convert them to specific columns in database, e.g.
@JvmInline
value class MyStringId(val raw: String)
@JvmInline
value class MyUUID(val raw: UUID)
@JvmInline
value class MyVersion(val raw: Int)
enum class MyState { ACTIVE, INACTIVE }
fun Table.myStringId(name: String) = stringWrapper(name, ::MyStringId) { it.raw }
fun Table.myUUID(name: String) = uuidWrapper(name, ::MyUUID) { it.raw }
fun Table.myVersion(name: String) = integerWrapper(name, ::MyVersion) { it.raw }
fun Table.myState(name: String) = booleanWrapper(name, { if (it) MyState.ACTIVE else MyState.INACTIVE }) {
when (it) {
MyState.ACTIVE -> true
MyState.INACTIVE -> false
}
}
object MyTable : Table("test") {
val id = myStringId("my_id").nullable()
val uuid = myUUID("my_uuid").nullable()
val version = myVersion("my_version").nullable()
val state = myState("my_state").nullable()
}Postgresql allows usage of nonstandard clause DISTINCT ON in queries.
Krush provides custom distinctOn extension method which can be used as first parameter in custom slice extension method.
Postgresql specific extensions needs krush-runtime-postgresql dependency in maven or gradle
Example code:
@JvmInline
value class MyStringId(val raw: String)
@JvmInline
value class MyVersion(val raw: Int)
fun Table.myStringId(name: String) = stringWrapper(name, ::MyStringId) { it.raw }
fun Table.myVersion(name: String) = integerWrapper(name, ::MyVersion) { it.raw }
object MyTable : Table("test") {
val id = myStringId("my_id").nullable()
val version = myVersion("my_version").nullable()
val content = jsonb("content").nullable()
}
fun findNewestContentVersion(id: MyStringId): String? =
MyTable
.slice(MyTable.id.distinctOn(), MyTable.content)
.select { MyTable.id eq id }
.orderBy(MyTable.id to SortOrder.ASC, MyTable.version to SortOrder.DESC)
.map { it[MyTable.content] }
.firstOrNull()when findNewestContentVersion(MyStringId("123")) is called will generate SQL:
SELECT DISTINCT ON (test.my_id) TRUE, test.my_id, test."content"
FROM test
WHERE test.my_id = '123'
ORDER BY test.my_id ASC, test.my_version DESC
Special thanks to Łukasz Jędrzejewski for original idea of using Exposed in our projects.
Krush is published under Apache License 2.0.
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