我正在用我最终构建的东西来回答我自己的问题。
让我们定义一个简单的案例类和行映射器
case class User(
id: String = java.util.UUID.randomUUID().toString,
companyScopeId: String,
firstName: Option[String] = None,
lastName: Option[String] = None
)
class UserTable(tag: Tag) extends Table[User](tag,"USER") {
override def id = column[String]("id", O.PrimaryKey)
def companyScopeId = column[String]("company_scope_id", O.NotNull)
def firstName = column[Option[String]]("first_name", O.Nullable)
def lastName = column[Option[String]]("last_name", O.Nullable)
def * = (id, companyScopeId, firstName, lastName) <>
(User.tupled,User.unapply)
}
Slick 中谓词的概念
我假设“谓词”的概念可以放在TableQuery.filter 中。但是这种类型相当复杂，因为它是一个接受Table 并返回具有隐式CanBeQueryCondition 的类型的函数
不幸的是，有 3 种不同的类型都有 CanBeQueryCondition 并将它们放在一个列表中以折叠成一个谓词似乎并不容易（即 filter 很容易应用，但 && 和 @ 987654329@ 运营商很难申请（据我所知））。但幸运的是，我们似乎可以使用.? 扩展方法轻松地将Boolean 转换为Colunm[Boolean] 为Column[Option[Boolean]]。
所以让我们定义我们的谓词类型：
type TablePredicate[Item, T <: Table[Item]] = T => Column[Option[Boolean]]
折叠谓词列表（即使用连词/分离，即组合 AND 和 OR 子句）
现在我们只有一种类型，所以我们可以轻松地将谓词列表折叠成一个
// A predicate that never filter the result
def matchAll[Item, T <: Table[Item]]: TablePredicate[Item,T] = { table: T => LiteralColumn(1) === LiteralColumn(1) }
// A predicate that always filter the result
def matchNone[Item, T <: Table[Item]]: TablePredicate[Item,T] = { table: T => LiteralColumn(1) =!= LiteralColumn(1) }
def conjunction[Item, T <: Table[Item]](predicates: TraversableOnce[TablePredicate[Item, T]]): TablePredicate[Item,T] = {
if ( predicates.isEmpty ) matchAll[Item,T]
else {
predicates.reduce { (predicate1, predicate2) => table: T =>
predicate1(table) && predicate2(table)
}
}
}
def disjunction[Item, T <: Table[Item]](predicates: TraversableOnce[TablePredicate[Item, T]]): TablePredicate[Item,T] = {
if ( predicates.isEmpty ) matchNone[Item,T]
else {
predicates.reduce { (predicate1, predicate2) => table: T =>
predicate1(table) || predicate2(table)
}
}
}
动态过滤案例类
从这些谓词原语中，我们可以开始创建基于案例类的动态、可组合和类型安全的查询 DSL。
case class UserFilters(
companyScopeIds: Option[Set[String]] = None,
firstNames: Option[Set[String]] = None,
lastNames: Option[Set[String]] = None
) {
type UserPredicate = TablePredicate[User,UserTable]
def withFirstNames(firstNames: Set[String]): UserFilters = this.copy(firstNames = Some(firstNames))
def withFirstNames(firstNames: String*): UserFilters = withFirstNames(firstNames.toSet)
def withLastNames(lastNames: Set[String]): UserFilters = this.copy(lastNames = Some(lastNames))
def withLastNames(lastNames: String*): UserFilters = withLastNames(lastNames.toSet)
def withCompanyScopeIds(companyScopeIds: Set[String]): UserFilters = this.copy(companyScopeIds = Some(companyScopeIds))
def withCompanyScopeIds(companyScopeIds: String*): UserFilters = withCompanyScopeIds(companyScopeIds.toSet)
private def filterByFirstNames(firstNames: Set[String]): UserPredicate = { table: UserTable => table.firstName inSet firstNames }
private def filterByLastNames(lastNames: Set[String]): UserPredicate = { table: UserTable => table.lastName inSet lastNames }
private def filterByCompanyScopeIds(companyScopeIds: Set[String]): UserPredicate = { table: UserTable => (table.companyScopeId.? inSet companyScopeIds) }
def predicate: UserPredicate = {
// Build the list of predicate options (because filters are actually optional)
val optionalPredicates: List[Option[UserPredicate]] = List(
firstNames.map(filterByFirstNames(_)),
lastNames.map(filterByLastNames(_)),
companyScopeIds.map(filterByCompanyScopeIds(_))
)
// Filter the list to remove None's
val predicates: List[UserPredicate] = optionalPredicates.flatten
// By default, create a conjunction (AND) of the predicates of the represented by this case class
conjunction[User,UserTable](predicates)
}
}
注意.? 用于companyScopeId 字段的用法，它允许将非可选列适合我们的Slick 谓词定义
使用 DSL
val Users = TableQuery(new UserTable(_))
val filter1 = UserFilters().withLastNames("lorber","silhol").withFirstName("robert")
val filter2 = UserFilters().withFirstName("sebastien")
val filter = disjunction[User,UserTable](Set(filter1.predicate,filter2.predicate))
val users = Users.filter(filter.predicate).list
// results in
// ( last_name in ("lorber","silhol") AND first_name in ("robert") )
// OR
// ( first_name in ("sebastien") )
结论
这远非完美，但只是初稿，至少可以给你一些灵感 :) 我希望 Slick 能够更容易地构建在其他查询 DSL 中非常常见的东西（比如 Hibernate/JPA Criteria API)
另请参阅Gist 了解最新解决方案