Quill

Compile-time Language Integrated Query for Scala

Quill provides a Quoted Domain Specific Language (QDSL) to express queries in Scala and execute them in a target language. The library's core is designed to support multiple target languages and the current version features support for Structured Query Language (SQL).

Boilerplate-free mapping: The database schema is mapped using simple case classes.
Quoted DSL: Queries are defined inside a quote block. Quill parses each quoted block of code (quotation) at compile time and translates them to an internal Abstract Syntax Tree (AST)
Compile-time SQL generation: The db.run call reads the quotation's AST and translates it to the target language at compile time, emitting the SQL string as a compilation message. As the query string is known at compile time, the runtime overhead is very low and similar to using the database driver directly.
Compile-time query validation: If configured, the query is verified against the database at compile time and the compilation fails if it is not valid.

Index

Quotation
Mirror sources
Compile-time quotations
Parametrized quotations
Schema
Queries
Actions
Dynamic queries
Extending quill
- Infix
- Custom encoding
Sources
Acknowledgments
License

Quotation

The QDSL allows the user to write plain Scala code, leveraging scala's syntax and type system. Quotations are created using the quote method and can contain any excerpt of code that uses supported operations. To create quotations, first import quote and some other auxiliary methods:

import io.getquill._

A quotation can be a simple value:

val pi = quote(3.14159)

And be used within another quotation:

case class Circle(radius: Float)

val areas = quote {
  query[Circle].map(c => pi * c.radius * c.radius)
}

Quotations can also contain high-order functions:

val area = quote {
  (c: Circle) => pi * c.radius * c.radius
}

val areas = quote {
  query[Circle].map(c => area(c))
}

Quill's normalization engine applies reduction steps before translating the quotation to the target language. The correspondent normalized quotation for both versions of the areas query is:

val areas = quote {
  query[Circle].map(c => 3.14159 * c.radius * c.radius)
}

Scala doesn't have support for high-order functions with type parameters. Quill supports anonymous classes with an apply method for this purpose:

val existsAny = quote {
  new {
    def apply[T](xs: Query[T])(p: T => Boolean) =
    	xs.filter(p(_)).nonEmpty
  }
}

val q = quote {
  query[Circle].filter { c1 => 
    existsAny(query[Circle])(c2 => c2.radius > c1.radius)
  }
}

Mirror sources

Sources represent the database and provide an execution interface for queries. Quill provides mirror sources for test purposes. Please refer to sources for information on how to create normal sources.

Instead of running the query, mirror sources return a structure with the information that would be used to run the query. There are two mirror source versions:

io.getquill.source.mirror.mirrorSource: Mirrors the quotation AST
io.getquill.source.sql.mirror.mirrorSource: Mirrors the SQL query

This documentation uses the SQL mirror in its examples under the db name:

val db = io.getquill.source.sql.mirror.mirrorSource

Compile-time quotations

Quotations are both compile-time and runtime values. Quill uses a type refinement to store the quotation's AST as an annotation available at compile-time and the q.ast method exposes the AST as runtime value.

It is important to avoid giving explicit types to quotations when possible. For instance, this quotation can't be read at compile-time as the type refinement is lost:

val q: Quoted[Query[Circle]] = quote {
  query[Circle].filter(c => c.radius > 10)
}

db.run(q) // Dynamic query

Quill falls back to runtime normalization and query generation if the quotation's AST can be read at compile-time. Please refer to dynamic queries for more information

Parametrized quotations

Quotations are designed to be self-contained, without references to runtime values outside their scope. If a quotation needs to receive a runtime value, it needs to be done by defining the quotation as a function:

val q = quote {
  (i: Int) =>
    query[Circle].filter(r => r.radius > i)
}

The runtime value can be specified when running it:

db.run(q).using(10) // SELECT r.radius FROM Circle r WHERE r.radius > ?

The method run is a bridge between the compile-time quotations and the runtime execution.

Schema

The database schema is represented by case classes. By default, quill uses the class and field names as the database identifiers:

case class Circle(radius: Float)

val q = quote {
  query[Circle].filter(c => c.radius > 1)
}

db.run(q) // SELECT c.radius FROM Circle c WHERE c.radius > 1

Alternatively, the identifiers can be customized:

val circles = quote {
  query[Circle]("circle_table", _.radius -> "radius_column")
}

val q = quote {
  circles.filter(c => c.radius > 1)
}

db.run(q) 
// SELECT c.radius_column FROM circle_table c WHERE c.radius_column > 1

If multiple tables require custom identifiers, it is good practice to define a schema object with all table queries to be reused across multiple queries:

case class Circle(radius: Int)
case class Rectangle(length: Int, width: Int)
object schema {
  val circles = quote {
    query[Circle]("circle_table", 
      _.radius -> "radius_column")
  }
  val rectangles = quote {
    query[Rectangle]("rectangle_table", 
      _.length -> "length_column", 
      _.width -> "width_column")
  }
}

Queries

The overall abstraction of quill queries is use database tables as if they were in-memory collections. Scala for-comprehensions provide syntatic sugar to deal with this kind of monadic operations:

case class Person(id: Int, name: String, age: Int)
case class Contact(personId: Int, phone: String)

val q = quote {
  for {
    p <- query[Person] if(p.id == 999)
    c <- query[Contact] if(c.personId == p.id)
  } yield {
    (p.name, c.phone)
  }
}

db.run(q) 
// SELECT p.name, c.phone FROM Person p, Contact c WHERE (p.id = 999) AND (c.personId = p.id)

Quill normalizes the quotation and translates the monadic joins to applicative joins in SQL, generating a database-friendly query that avoids nested queries.

Any of the following features can be used together with the others and/or within a for-comprehension:

filter

val q = quote {
  query[Person].filter(p => p.age > 18)
}

db.run(q)
// SELECT p.id, p.name, p.age FROM Person p WHERE p.age > 18

map

val q = quote {
  query[Person].map(p => p.name)
}

db.run(q)
// SELECT p.name FROM Person p

flatMap

val q = quote {
  query[Person].filter(p => p.age > 18).flatMap(p => query[Contact].filter(c => c.personId == p.id))
}

db.run(q)
// SELECT c.personId, c.phone FROM Person p, Contact c WHERE (p.age > 18) AND (c.personId = p.id)

sortBy

val q = quote {
  query[Person].sortBy(p => p.age)
}

db.run(q)
// SELECT p.id, p.name, p.age FROM Person p ORDER BY p.age

drop/take

val q = quote {
  query[Person].drop(2).take(1)
}

db.run(q)
// SELECT x.id, x.name, x.age FROM Person x LIMIT 1 OFFSET 2

groupBy

val q = quote {
  query[Person].groupBy(p => p.age).map {
    case (age, people) =>
      (age, people.size)
  }
}

db.run(q)
// SELECT p.age, COUNT(*) FROM Person p GROUP BY p.age

union

val q = quote {
  query[Person].filter(p => p.age > 18).union(query[Person].filter(p => p.age > 60))
}

db.run(q)
// SELECT x.id, x.name, x.age FROM (SELECT id, name, age FROM Person p WHERE p.age > 18 
// UNION SELECT id, name, age FROM Person p1 WHERE p1.age > 60) x

unionAll/++

val q = quote {
  query[Person].filter(p => p.age > 18).unionAll(query[Person].filter(p => p.age > 60))
}

db.run(q) 
// SELECT x.id, x.name, x.age FROM (SELECT id, name, age FROM Person p WHERE p.age > 18 
// UNION ALL SELECT id, name, age FROM Person p1 WHERE p1.age > 60) x

val q2 = quote {
  query[Person].filter(p => p.age > 18) ++ query[Person].filter(p => p.age > 60)
}

db.run(q2) 
// SELECT x.id, x.name, x.age FROM (SELECT id, name, age FROM Person p WHERE p.age > 18 
// UNION ALL SELECT id, name, age FROM Person p1 WHERE p1.age > 60) x

aggregation

val r = quote {
  query[Person].map(p => p.age)
}

db.run(r.min) // SELECT MIN(p.age) FROM Person p
db.run(r.max) // SELECT MAX(p.age) FROM Person p
db.run(r.avg) // SELECT AVG(p.age) FROM Person p
db.run(r.sum) // SELECT SUM(p.age) FROM Person p
db.run(r.size) // SELECT COUNT(p.age) FROM Person p

isEmpty/nonEmpty

val q = quote {
  query[Person].filter{ p1 => 
    query[Person].filter(p2 => p2.id != p1.id && p2.age == p1.age).isEmpty
  }
}

db.run(q) 
// SELECT p1.id, p1.name, p1.age FROM Person p1 WHERE 
// NOT EXISTS (SELECT * FROM Person p2 WHERE (p2.id <> p1.id) AND (p2.age = p1.age))

val q2 = quote {
  query[Person].filter{ p1 => 
    query[Person].filter(p2 => p2.id != p1.id && p2.age == p1.age).nonEmpty
  }
}

db.run(q2)
// SELECT p1.id, p1.name, p1.age FROM Person p1 WHERE 
// EXISTS (SELECT * FROM Person p2 WHERE (p2.id <> p1.id) AND (p2.age = p1.age))

outer joins

val q = quote {
  query[Person].leftJoin(query[Contact]).on((p, c) => c.personId == p)
}

db.run(q) 
// SELECT p.id, p.name, p.age, c.personId, c.phone 
// FROM Person p LEFT JOIN Contact c ON c.personId = p

val q2 = quote {
  query[Person].rightJoin(query[Contact]).on((p, c) => c.personId == p)
}

db.run(q2) 
// SELECT p.id, p.name, p.age, c.personId, c.phone 
// FROM Person p RIGHT JOIN Contact c ON c.personId = p

val q3 = quote {
  query[Person].fullJoin(query[Contact]).on((p, c) => c.personId == p)
}

db.run(q3) 
// SELECT p.id, p.name, p.age, c.personId, c.phone 
// FROM Person p FULL JOIN Contact c ON c.personId = p

Actions

Database actions are defined using quotations as well. These actions don't have a collection-like API but rather a custom DSL to express inserts, deletes and updates.

insert

val a = quote {
  (personId: Int, phone: String) =>
    query[Contact].insert(_.personId -> personId, _.phone -> phone)
}

db.run(a).using(List((999, "+1510488988"))) 
// INSERT INTO Contact (personId,phone) VALUES (?, ?)

Note: Actions receive a List of tuples as they are batched by default.

update

val a = quote {
  (id: Int, age: Int) =>
    query[Person].filter(p => p.id == id).update(_.age -> age)
}

db.run(a).using(List((999, 18)))
// UPDATE Person SET age = ? WHERE id = ?

delete

val a = quote {
  query[Person].filter(p => p.name == "").delete
}

db.run(a) 
// DELETE FROM Person WHERE name = ''

Dynamic queries

Quill's default operation mode is compile-time, but there are queries that have their structure defined only at runtime. Quill automatically falls back to runtime normalization and query generation if the query's structure is not static. Example:

sealed trait QueryType
case object Minor extends QueryType
case object Senior extends QueryType

def people(t: QueryType): Quoted[Query[Person]] =
  t match {
    case Minor => quote {
      query[Person].filter(p => p.age < 18)
    }
    case Senior => quote {
      query[Person].filter(p => p.age > 65)
    }
  }

db.run(people(Minor)) 
// SELECT p.id, p.name, p.age FROM Person p WHERE p.age < 18

db.run(people(Senior)) 
// SELECT p.id, p.name, p.age FROM Person p WHERE p.age > 65

Extending quill

Infix

Infix is a very flexible mechanism to use non-supported features without having to use plain SQL queries. It allows insertion of arbitrary SQL strings within quotations.

For instance, quill doesn't support the FOR UPDATE SQL feature. It can still be used through infix:

val forUpdate = quote {
  new {
    def apply[T](q: Query[T]) = infix"$q FOR UPDATE".as[Query[T]]
  }
}

val a = quote {
  query[Person].filter(p => p.age < 18)
}

db.run(forUpdate(a)) 
// SELECT p.id, p.name, p.age FROM (SELECT * FROM Person p WHERE p.age < 18 FOR UPDATE) p

The forUpdate quotation can be reused for multiple queries.

The same approach can be used for RETURNING ID:

val returningId = quote {
  new {
    def apply[T](a: Action[T]) = infix"$a RETURNING ID".as[Action[T]]
  }
}

val a = quote {
  query[Person].insert(_.name -> "John", _.age -> 21)
}

db.run(returningId(a))
// INSERT INTO Person (name,age) VALUES ('John', 21) RETURNING ID

A custom database function can also be used through infix:

val myFunction = quote {
  (i: Int) => infix"MY_FUNCTION($i)".as[Int]
}

val q = quote {
  query[Person].map(p => myFunction(p.age))
}

db.run(q) 
// SELECT MY_FUNCTION(p.age) FROM Person p

Custom encoding

Quill uses Encoders to encode runtime values defined with the using method and Decoders to parse the query return value. The library has some encoders and decoders built-in and it is possible to provide new ones.

If the correspondent database type is already supported, use mappedEncoding:

case class CustomValue(i: Int)

implicit val decodeCustomValue = mappedEncoding[CustomValue, Int](_.i)
implicit val encodeCustomValue = mappedEncoding[Int, CustomValue](CustomValue(_))

If the database type is not supported, it is possible to provide "raw" encoders and decoders:

import io.getquill.source.mirror.Row

implicit val customValueEncoder = 
  new db.Encoder[CustomValue] {
    def apply(index: Int, value: CustomValue, row: Row) = 
      ??? // database-specific implementation
  }

implicit val customValueDecoder = 
  new db.Decoder[CustomValue] {
    def apply(index: Int, row: Row) = 
      ??? // database-specific implementation
  }

Sources

Sources represent the database and provide an execution interface for queries. Example:

import io.getquill.naming.SnakeCase
import io.getquill.source.jdbc.JdbcSource
import io.getquill.source.sql.idiom.MySQLDialect

object db extends JdbcSource[MySQLDialect, SnakeCase]

Dialect

The SQL dialect to be used by the source is defined by the first type parameter. Some source types are specific to a database and thus not require it.

Quill has two built-in dialects:

io.getquill.source.sql.idiom.MySQLDialect
io.getquill.source.sql.idiom.PostgresDialect

Naming strategy

The second type parameter defines the naming strategy to be used when translating identifiers (table and column names) to SQL.

strategy	example
`io.getquill.naming.Literal`	some_ident -> some_ident
`io.getquill.naming.Escape`	some_ident -> "some_ident"
`io.getquill.naming.UpperCase`	some_ident -> SOME_IDENT
`io.getquill.naming.LowerCase`	SOME_IDENT -> some_ident
`io.getquill.naming.SnakeCase`	someIdent -> some_ident
`io.getquill.naming.CamelCase`	some_ident -> someIdent

Multiple transformations can be defined using mixin. For instance, the naming strategy

SnakeCase with UpperCase

produces this transformation:

someIdent -> SOME_IDENT

The transformations are applied from left to right.

Configuration

Sources must be defined as object and the object name is used as the key to obtain configurations using the typesafe config library.

quill-jdbc

MySQL

sbt dependencies

libraryDependencies ++= Seq(
  "mysql" % "mysql-connector-java" % "5.1.36",
  "io.getquill" %% "quill-jdbc" % "0.1.0"
)

source definition

import io.getquill.naming.SnakeCase
import io.getquill.source.jdbc.JdbcSource
import io.getquill.source.sql.idiom.MySQLDialect

object db extends JdbcSource[MySQLDialect, SnakeCase]

application.properties

db.dataSourceClassName=com.mysql.jdbc.jdbc2.optional.MysqlDataSource
db.dataSource.url=jdbc:mysql://host/database
db.dataSource.user=root
db.dataSource.password=root
db.dataSource.cachePrepStmts=true
db.dataSource.prepStmtCacheSize=250
db.dataSource.prepStmtCacheSqlLimit=2048

Postgres

sbt dependencies

libraryDependencies ++= Seq(
  "org.postgresql" % "postgresql" % "9.4-1206-jdbc41",
  "io.getquill" %% "quill-jdbc" % "0.1.0"
)

source definition

import io.getquill.naming.SnakeCase
import io.getquill.source.jdbc.JdbcSource
import io.getquill.source.sql.idiom.PostgresDialect

object db extends JdbcSource[PostgresDialect, SnakeCase]

application.properties

db.dataSourceClassName=org.postgresql.ds.PGSimpleDataSource
db.dataSource.user=root
db.dataSource.password=root
db.dataSource.databaseName=database
db.dataSource.portNumber=5432
db.dataSource.serverName=host

Please refer to HikariCP's documentation for a detailed explanation of the available configurations.

quill-async

MySQL Async

sbt dependencies

libraryDependencies ++= Seq(
  "io.getquill" %% "quill-async" % "0.1.0"
)

source definition

import io.getquill.naming.SnakeCase
import io.getquill.source.async.mysql.MysqlAsyncSource

object db extends MysqlAsyncSource[SnakeCase]

application.properties

db.host=host
db.port=3306
db.user=root
db.password=root
db.database=database
db.poolMaxQueueSize=4
db.poolMaxObjects=4
db.poolMaxIdle=999999999
db.poolValidationInterval=100

Postgres Async

sbt dependencies

libraryDependencies ++= Seq(
  "io.getquill" %% "quill-async" % "0.1.0"
)

source definition

import io.getquill.naming.SnakeCase
import io.getquill.source.async.postgres.PostgresAsyncSource

object db extends PostgresAsyncSource[SnakeCase]

application.properties

db.host=host
db.port=5432
db.user=root
db.password=root
db.database=database
db.poolMaxQueueSize=4
db.poolMaxObjects=4
db.poolMaxIdle=999999999
db.poolValidationInterval=100

quill-finagle-mysql

sbt dependencies

libraryDependencies ++= Seq(
  "io.getquill" %% "quill-finagle-mysql" % "0.1.0"
)

source definition

import io.getquill.naming.SnakeCase
import io.getquill.source.finagle.mysql.FinagleMysqlSource

object db extends FinagleMysqlSource[SnakeCase]

application.properties

testDB.dest=localhost:3306
testDB.user=root
testDB.password=root
testDB.database=database

Slick comparison

Please refer to SLICK.md for a detailed comparison between Quill and Slick.

Acknowledgments

The project was created having Philip Wadler's talk "A practical theory of language-integrated query" as its initial inspiration. The development was heavily influenced by the following papers:

License

See the LICENSE file for details.

Name		Name	Last commit message	Last commit date
Latest commit History 431 Commits
project		project
quill-async/src		quill-async/src
quill-core/src		quill-core/src
quill-finagle-mysql/src		quill-finagle-mysql/src
quill-jdbc/src		quill-jdbc/src
quill-sql/src		quill-sql/src
.gitignore		.gitignore
.travis.yml		.travis.yml
LICENSE.txt		LICENSE.txt
README.md		README.md
SLICK.md		SLICK.md
build.sbt		build.sbt
example.gif		example.gif
quill.png		quill.png
version.sbt		version.sbt

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