Table Of Contents

Previous topic

Getting Started

Next topic

Direct Embedding

This Page

Lifted Embedding

The lifted embedding is the standard API for type-safe queries and updates in Slick. Please see Getting Started for an introduction. This chapter describes the available features in more detail.

The name Lifted Embedding refers to the fact that you are not working with standard Scala types (as in the direct embedding) but with types that are lifted into a the scala.slick.lifted.Rep type constructor. This becomes clear when you compare the types of a simple Scala collections example

case class Coffee(name: String, price: Double)
val l: List[Coffee] = //...
val l2 = l.filter(_.price > 8.0).map(
//                  ^       ^          ^
//                  Double  Double     String

... with the types of similar code using the lifted embedding:

object Coffees extends Table[(String, Int, Double, Int, Int)]("COFFEES") {
  def name = column[String]("COF_NAME", O.PrimaryKey)
  def price = column[Double]("PRICE")
val q = Query(Coffees)
val q2 = q.filter(_.price > 8.0).map(
//                  ^       ^          ^
//          Rep[Double]  Rep[Double]  Rep[String]

All plain types are lifted into Rep. The same is true for the record type Coffees which is a subtype of Rep[(String, Int, Double, Int, Int)]. Even the literal 8.0 is automatically lifted to a Rep[Double] by an implicit conversion because that is what the > operator on Rep[Double] expects for the right-hand side.


In order to use the lifted embedding, you need to define Table objects for your database tables:

object Coffees extends Table[(String, Int, Double, Int, Int)]("COFFEES") {
  def name = column[String]("COF_NAME", O.PrimaryKey)
  def supID = column[Int]("SUP_ID")
  def price = column[Double]("PRICE")
  def sales = column[Int]("SALES")
  def total = column[Int]("TOTAL")
  def * = name ~ supID ~ price ~ sales ~ total

Note that Slick clones your table objects under the covers, so you should not add any extra state to them (extra methods are fine though). Also make sure that an actual object for a table is not defined in a static location (i.e. at the top level or nested only inside other objects) because this can cause problems in certain situations due to an overeager optimization performed by scalac. Using a val for your table (with an anonymous structural type or a separate class definition) is fine everywhere.

All columns are defined through the column method. Note that they need to be defined with def and not val due to the cloning. Each column has a Scala type and a column name for the database (usually in upper-case). The following primitive types are supported out of the box (with certain limitations imposed by the individual database drivers):

  • Boolean
  • java.sql.Blob
  • Byte
  • Array[Byte]
  • java.sql.Clob
  • java.sql.Date
  • Double
  • Float
  • Int
  • Long
  • Short
  • String
  • java.sql.Time
  • java.sql.Timestamp
  • Unit
  • java.util.UUID
  • BigDecimal

Nullable columns are represented by Option[T] where T is one of the supported primitive types.

After the column name, you can add optional column options to a column definition. The applicable options are available through the table’s O object. The following ones are defined for BasicProfile:

NotNull, Nullable
Explicitly mark the column a nullable or non-nullable when creating the DDL statements for the table. Nullability is otherwise determined from the type (Option or non-Option).
Mark the column as a (non-compound) primary key when creating the DDL statements.
Default[T](defaultValue: T)
Specify a default value for inserting data the table without this column. This information is only used for creating DDL statements so that the database can fill in the missing information.
DBType(dbType: String)
Use a non-standard database-specific type for the DDL statements (e.g. DBType("VARCHAR(20)") for a String column).
Mark the column as an auto-incrementing key when creating the DDL statements. Unlike the other column options, this one also has a meaning outside of DDL creation: Many databases do not allow non-AutoInc columns to be returned when inserting data (often silently ignoring other columns), so Slick will check if the return column is properly marked as AutoInc where needed.

Every table requires a * method contatining a default projection. This describes what you get back when you return rows (in the form of a table object) from a query. Slick’s * projection does not have to match the one in the database. You can add new columns (e.g. with computed values) or omit some columns as you like. The non-lifted type corresponding to the * projection is given as a type parameter to Table. For simple, non-mapped tables, this will be a single column type or a tuple of column types.

Mapped Tables

It is possible to define a mapped table that uses a custom type for its * projection by adding a bi-directional mapping with the <> operator:

case class User(id: Option[Int], first: String, last: String)

object Users extends Table[User]("users") {
  def id = column[Int]("id", O.PrimaryKey, O.AutoInc)
  def first = column[String]("first")
  def last = column[String]("last")
  def * = id.? ~ first ~ last <> (User, User.unapply _)

It is optimized for case classes (with a simple apply method and an unapply method that wraps its result in an Option) but there is also an overload that operates directly on the mapped types.


A foreign key constraint can be defined with a table’s foreignKey method. It takes a name for the constraint, the local column (or projection, so you can define compound foreign keys), the linked table, and a function from that table to the corresponding column(s). When creating the DDL statements for the table, the foreign key definition is added to it.

object Suppliers extends Table[(Int, String, String, String, String, String)]("SUPPLIERS") {
  def id = column[Int]("SUP_ID", O.PrimaryKey)

object Coffees extends Table[(String, Int, Double, Int, Int)]("COFFEES") {
  def supID = column[Int]("SUP_ID")
  def supplier = foreignKey("SUP_FK", supID, Suppliers)(

Independent of the actual constraint defined in the database, such a foreign key can be used to navigate to the linked data with a join. For this purpose, it behaves the same as a manually defined utility method for finding the joined data:

def supplier = foreignKey("SUP_FK", supID, Suppliers)(
def supplier2 = Suppliers.where( === supID)

A primary key constraint can be defined in a similar fashion by adding a method that calls primaryKey. This is useful for defining compound primary keys (which cannot be done with the O.PrimaryKey column option):

object A extends Table[(Int, Int)]("a") {
  def k1 = column[Int]("k1")
  def k2 = column[Int]("k2")
  def * = k1 ~ k2
  def pk = primaryKey("pk_a", (k1, k2))

Other indexes are defined in a similar way with the index method. They are non-unique by default unless you set the unique parameter:

object A extends Table[(Int, Int)]("a") {
  def k1 = column[Int]("k1")
  def k2 = column[Int]("k2")
  def * = k1 ~ k2
  def idx = index("idx_a", (k1, k2), unique = true)

All constraints are discovered reflectively by searching for methods with the appropriate return types which are defined in the table. This behavior can be customized by overriding the tableConstraints method.

Data Definition Language

DDL statements for a table can be created with its ddl method. Multiple DDL objects can be concatenated with ++ to get a compound DDL object which can create and drop all entities in the correct order, even in the presence of cyclic dependencies between tables. The statements are executed with the create and drop methods:

val ddl = Coffees.ddl ++ Suppliers.ddl
db withSession {

You can use the createStatements and dropStatements methods to get the SQL code:



Primitive (non-compound, non-collection) values are representend by type Column[T] (a sub-type of Rep[R]) where a TypeMapper[T] must exist. Only some special methods for internal use and those that deal with conversions between nullable and non-nullable columns are defined directly in the Column class.

The operators and other methods which are commonly used in the lifted embedding are added through implicit conversions defined in ExtensionMethodConversions. The actual methods can be found in the classes AnyExtensionMethods, ColumnExtensionMethods, NumericColumnExtensionMethods, BooleanColumnExtensionMethods and StringColumnExtensionMethods.

Collection values are represented by the Query class (a Rep[Seq[T]]) which contains many standard collection methods like flatMap, filter, take and groupBy. Due to the two different component types of a Query (lifted and plain), the signatures for these methods are very complex but the semantics are essentially the same as for Scala collections.

Additional methods for queries of non-compound values are added via an implicit conversion to SingleColumnQueryExtensionMethods.





Inserting and Updating

Query Templates

User-Defined Functions and Types