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社区首页 >专栏 >细谈Slick(6)- Projection:ProvenShape,强类型的Query结果类型

细谈Slick(6)- Projection:ProvenShape,强类型的Query结果类型

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发布2018-01-05 11:02:37
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发布2018-01-05 11:02:37
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  在Slick官方文档中描述:连接后台数据库后,需要通过定义Projection,即def * 来进行具体库表列column的选择和排序。通过Projection我们可以选择库表中部分列、也可以增加一些自定义列computed column。具体来说Projection提供了数据库表列与Scala值的对应。例如def * = (column1,column2)把库表的column1和column2与(Int,String)对应,column1[Int],column2[String]。也可以说是与定义column的类参数进行对应。从Slick源代码中我们可以找到Projection定义:

代码语言:javascript
复制
abstract class AbstractTable[T](val tableTag: Tag, val schemaName: Option[String], val tableName: String) extends Rep[T] {
  /** The client-side type of the table as defined by its * projection */
  type TableElementType
...
  /** The * projection of the table used as default for queries and inserts.
    * Should include all columns as a tuple, HList or custom shape and optionally
    * map them to a custom entity type using the <> operator.
    * The `ProvenShape` return type ensures that
    * there is a `Shape` available for translating between the `Column`-based
    * type in * and the client-side type without `Column` in the table's type
    * parameter. */
  def * : ProvenShape[T]
...
}

我们看到Projection是个ProvenShape[T]类。再看看ProvenShape是怎么定义的:

代码语言:javascript
复制
/** A limited version of ShapedValue which can be constructed for every type
  * that has a valid shape. We use it to enforce that a table's * projection
  * has a valid shape. A ProvenShape has itself a Shape so it can be used in
  * place of the value that it wraps for purposes of packing and unpacking. */
trait ProvenShape[U] {
  def value: Any
  val shape: Shape[_ <: FlatShapeLevel, _, U, _]
  def packedValue[R](implicit ev: Shape[_ <: FlatShapeLevel, _, U, R]): ShapedValue[R, U]
  def toNode = packedValue(shape).toNode
}

object ProvenShape {
  /** Convert an appropriately shaped value to a ProvenShape */
  implicit def proveShapeOf[T, U](v: T)(implicit sh: Shape[_ <: FlatShapeLevel, T, U, _]): ProvenShape[U] =
    new ProvenShape[U] {
      def value = v
      val shape: Shape[_ <: FlatShapeLevel, _, U, _] = sh.asInstanceOf[Shape[FlatShapeLevel, _, U, _]]
      def packedValue[R](implicit ev: Shape[_ <: FlatShapeLevel, _, U, R]): ShapedValue[R, U] = ShapedValue(sh.pack(value).asInstanceOf[R], sh.packedShape.asInstanceOf[Shape[FlatShapeLevel, R, U, _]])
    }

  /** The Shape for a ProvenShape */
  implicit def provenShapeShape[T, P](implicit shape: Shape[_ <: FlatShapeLevel, T, T, P]): Shape[FlatShapeLevel, ProvenShape[T], T, P] = new Shape[FlatShapeLevel, ProvenShape[T], T, P] {
    def pack(value: Mixed): Packed =
      value.shape.pack(value.value.asInstanceOf[value.shape.Mixed]).asInstanceOf[Packed]
    def packedShape: Shape[FlatShapeLevel, Packed, Unpacked, Packed] =
      shape.packedShape.asInstanceOf[Shape[FlatShapeLevel, Packed, Unpacked, Packed]]
    def buildParams(extract: Any => Unpacked): Packed =
      shape.buildParams(extract.asInstanceOf[Any => shape.Unpacked])
    def encodeRef(value: Mixed, path: Node) =
      value.shape.encodeRef(value.value.asInstanceOf[value.shape.Mixed], path)
    def toNode(value: Mixed): Node =
      value.shape.toNode(value.value.asInstanceOf[value.shape.Mixed])
  }
}

从implicit def proveShapeOf[T,U](v:T):ProvenShape[U]可以得出对于任何T,如果能提供Shape[_,_,T,U,_]的隐式实例implicit instance的话就能构建出ProvenShape[U]。我们再看看什么是Shape: 

代码语言:javascript
复制
/** A type class that encodes the unpacking `Mixed => Unpacked` of a
 * `Query[Mixed]` to its result element type `Unpacked` and the packing to a
 * fully packed type `Packed`, i.e. a type where everything which is not a
 * transparent container is wrapped in a `Column[_]`.
 *
 * =Example:=
 * - Mixed: (Column[Int], Column[(Int, String)], (Int, Option[Double]))
 * - Unpacked: (Int, (Int, String), (Int, Option[Double]))
 * - Packed: (Column[Int], Column[(Int, String)], (Column[Int], Column[Option[Double]]))
 * - Linearized: (Int, Int, String, Int, Option[Double])
 */
abstract class Shape[Level <: ShapeLevel, -Mixed, Unpacked_, Packed_] {...}

上面的Mixed就是ProvenShape的T,Unpacked就是U。如此看来T代表Query[T]的T,而U就是返回结果类型了。如果我们能提供T的Shape隐式实例就能把U升格成ProvenShape[U]。我们来看看Slick官方文件上的例子:

代码语言:javascript
复制
  import scala.reflect.ClassTag
  // A custom record class
  case class Pair[A, B](a: A, b: B)

  // A Shape implementation for Pair
  final class PairShape[Level <: ShapeLevel, M <: Pair[_,_], U <: Pair[_,_] : ClassTag, P <: Pair[_,_]](
                                                                     val shapes: Seq[Shape[_, _, _, _]])
    extends MappedScalaProductShape[Level, Pair[_,_], M, U, P] {
    def buildValue(elems: IndexedSeq[Any]) = Pair(elems(0), elems(1))
    def copy(shapes: Seq[Shape[_ <: ShapeLevel, _, _, _]]) = new PairShape(shapes)
  }

  implicit def pairShape[Level <: ShapeLevel, M1, M2, U1, U2, P1, P2](
                implicit s1: Shape[_ <: Level, M1, U1, P1], s2: Shape[_ <: Level, M2, U2, P2]
               ) = new PairShape[Level, Pair[M1, M2], Pair[U1, U2], Pair[P1, P2]](Seq(s1, s2))


  // Use it in a table definition
  class A(tag: Tag) extends Table[Pair[Int, String]](tag, "shape_a") {
    def id = column[Int]("id", O.PrimaryKey)
    def s = column[String]("s")
    def * = Pair(id, s)
  }
  val as = TableQuery[A]

现在Projection可以写成Pair(id,s)。也就是说因为有了implicit def pairShape[...](...):PairShape所以Pair(id,s)被升格成ProvenShape[Pair]。这样Query的返回类型就是Seq[Pair]了。实际上Slick本身提供了Tuple、Case Class、HList等类型的默认Shape隐式实例,所以我们可以把Projection直接写成 def * = (...) 或 Person(...) 或 Int::String::HNil。下面是Tuple的默认Shape:

代码语言:javascript
复制
trait TupleShapeImplicits {
  @inline
  implicit final def tuple1Shape[Level <: ShapeLevel, M1, U1, P1](implicit u1: Shape[_ <: Level, M1, U1, P1]): Shape[Level, Tuple1[M1], Tuple1[U1], Tuple1[P1]] =
    new TupleShape[Level, Tuple1[M1], Tuple1[U1], Tuple1[P1]](u1)
  @inline
  implicit final def tuple2Shape[Level <: ShapeLevel, M1,M2, U1,U2, P1,P2](implicit u1: Shape[_ <: Level, M1, U1, P1], u2: Shape[_ <: Level, M2, U2, P2]): Shape[Level, (M1,M2), (U1,U2), (P1,P2)] =
    new TupleShape[Level, (M1,M2), (U1,U2), (P1,P2)](u1,u2)
...

回到主题,下面是一个典型的Slick数据库表读取例子:

代码语言:javascript
复制
 1   class TupleTypedPerson(tag: Tag) extends Table[(
 2      Option[Int],String,Int,Option[String])](tag,"PERSON") {
 3     def id = column[Int]("id",O.PrimaryKey,O.AutoInc)
 4     def name = column[String]("name")
 5     def age = column[Int]("age")
 6     def alias = column[Option[String]]("alias")
 7     def * = (id.?,name,age,alias)
 8   }
 9   val tupleTypedPerson = TableQuery[TupleTypedPerson]
10 
11   val db = Database.forURL("jdbc:h2:mem:test1;DB_CLOSE_DELAY=-1", driver = "org.h2.Driver")
12   val createSchemaAction = tupleTypedPerson.schema.create
13   Await.ready(db.run(createSchemaAction),Duration.Inf)
14   val initDataAction = DBIO.seq {
15     tupleTypedPerson ++= Seq(
16       (Some(0),"Tiger Chan", 45, Some("Tiger_XC")),
17       (Some(0),"Johnny Cox", 17, None),
18       (Some(0),"Cathy Williams", 18, Some("Catty")),
19       (Some(0),"David Wong", 43, None)
20     )
21   }
22   Await.ready(db.run(initDataAction),Duration.Inf)
23   val queryAction = tupleTypedPerson.result
24 
25   Await.result(db.run(queryAction),Duration.Inf).foreach {row =>
26     println(s"${row._1.get} ${row._2} ${row._4.getOrElse("")}, ${row._3}")
27   }

在这个例子的表结构定义里默认的Projection是个Tuple。造成的后果是返回的结果行不含字段名,只有字段位置。使用这样的行数据很容易错误对应,或者重复确认正确的列值会影响工作效率。如果返回的结果类型是Seq[Person]这样的话:Person是个带属性的对象如case class,那么我们就可以通过IDE提示的字段名称来选择字段了。上面提过返回结果类型可以通过ProvenShape来确定,如果能实现ProvenShape[A] => ProvenShape[B]这样的转换处理,那么我们就可以把返回结果行类型从Tuple变成有字段名的类型了:

代码语言:javascript
复制
 1   class Person(val id: Option[Int], 
 2                val name: String, val age: Int, val alias: Option[String])
 3   def toPerson(t: (Option[Int],String,Int,Option[String])) = new Person (
 4     t._1,t._2,t._3,t._4
 5   )
 6   def fromPerson(p: Person) = Some((p.id,p.name,p.age,p.alias))
 7   class TupleMappedPerson(tag: Tag) extends Table[
 8     Person](tag,"PERSON") {
 9     def id = column[Int]("id",O.PrimaryKey,O.AutoInc)
10     def name = column[String]("name")
11     def age = column[Int]("age")
12     def alias = column[Option[String]]("alias")
13     def * = (id.?,name,age,alias) <> (toPerson,fromPerson)
14   }
15   val tupleMappedPerson = TableQuery[TupleMappedPerson]
16   
17   Await.result(db.run(tupleMappedPerson.result),Duration.Inf).foreach {row =>
18     println(s"${row.id.get} ${row.name} ${row.alias.getOrElse("")}, ${row.age}")
19   }

我们用<>函数进行了Tuple=>Person转换。注意toPerson和fromPerson这两个相互转换函数。如果Person是个case class,那么Person.tupled和Person.unapply就是它自备的转换函数,我们可以用case class来构建MappedProjection:

代码语言:javascript
复制
 1   case class Person(id: Option[Int]=None, name: String, age: Int, alias: Option[String])
 2 
 3   class MappedTypePerson(tag: Tag) extends Table[Person](tag,"PERSON") {
 4     def id = column[Int]("id",O.PrimaryKey,O.AutoInc)
 5     def name = column[String]("name")
 6     def age = column[Int]("age")
 7     def alias = column[Option[String]]("alias")
 8     def * = (id.?,name,age,alias) <> (Person.tupled,Person.unapply)
 9   }
10   val mappedPeople = TableQuery[MappedTypePerson]

从上面两个例子里我们似乎可以得出ProvenShape[T]的T类型就是Table[T]的T,也就是返回结果行的类型了。我们可以用同样方式来进行HList与Person转换: 

代码语言:javascript
复制
 1   def hlistToPerson(hl: Option[Int]::String::Int::(Option[String])::HNil) =
 2     new Person(hl(0),hl(1),hl(2),hl(3))
 3   def personToHList(p: Person) = Some(p.id::p.name::p.age::p.alias::HNil)
 4   class HListPerson(tag: Tag) extends Table[Person](tag,"PERSON") {
 5     def id = column[Int]("id",O.PrimaryKey,O.AutoInc)
 6     def name = column[String]("name")
 7     def age = column[Int]("age")
 8     def alias = column[Option[String]]("alias")
 9     def * = (id.?)::name::age::alias::HNil <> (hlistToPerson,personToHList)
10   }
11   val hlistPerson = TableQuery[HListPerson]
12   Await.result(db.run(hlistPerson.result),Duration.Inf).foreach {row =>
13     println(s"${row.id.get} ${row.name} ${row.alias.getOrElse("")}, ${row.age}")
14   }

同样,必须首先实现hlistToPerson和personToHList转换函数。现在Table的类型参数必须是Person。上面的Projection都是对Table默认Projection的示范。实际上我们可以针对每个Query来自定义Projection,如下:

代码语言:javascript
复制
1  case class YR(name: String, yr: Int)
2 
3   val qYear = for {
4     p <- hlistPerson
5   } yield ((p.name, p.age) <> (YR.tupled,YR.unapply))
6 
7   Await.result(db.run(qYear.result),Duration.Inf).foreach {row =>
8     println(s"${row.name} ${row.yr}")
9   }

上面这个例子里我们构建了基于case class YR的projection。在join table query情况下只能通过这种方式来构建Projection,看看下面这个例子:

代码语言:javascript
复制
 1   case class Title(id: Int, title: String)
 2   class PersonTitle(tag: Tag) extends Table[Title](tag,"TITLE") {
 3     def id = column[Int]("id")
 4     def title = column[String]("title")
 5     def * = (id,title) <> (Title.tupled,Title.unapply)
 6   }
 7   val personTitle = TableQuery[PersonTitle]
 8   val createTitleAction = personTitle.schema.create
 9    Await.ready(db.run(createTitleAction),Duration.Inf)
10    val initTitleData = DBIO.seq {
11      personTitle ++= Seq(
12        Title(1,"Manager"),
13        Title(2,"Programmer"),
14        Title(3,"Clerk")
15      )
16    }
17    Await.ready(db.run(initTitleData),Duration.Inf)
18  
19   case class Titles(id: Int, name: String, title: String)
20   val qPersonWithTitle = for {
21     p <- hlistPerson
22     t <- personTitle if p.id === t.id
23   } yield ((p.id,p.name,t.title) <> (Titles.tupled,Titles.unapply))
24   Await.result(db.run(qPersonWithTitle.result),Duration.Inf).foreach {row =>
25     println(s"${row.id} ${row.name}, ${row.title}")
26   }

现在对任何形式的Query结果我们都能使用强类型(strong typed)的字段名称来进行操作了。

下面是本次示范的源代码:

代码语言:javascript
复制
  1 import slick.collection.heterogeneous.{ HList, HCons, HNil }
  2 import slick.collection.heterogeneous.syntax._
  3 import slick.driver.H2Driver.api._
  4 
  5 import scala.concurrent.ExecutionContext.Implicits.global
  6 import scala.concurrent.duration._
  7 import scala.concurrent.{Await, Future}
  8 
  9 
 10 object chkProjection {
 11   
 12   class TupleTypedPerson(tag: Tag) extends Table[(
 13      Option[Int],String,Int,Option[String])](tag,"PERSON") {
 14     def id = column[Int]("id",O.PrimaryKey,O.AutoInc)
 15     def name = column[String]("name")
 16     def age = column[Int]("age")
 17     def alias = column[Option[String]]("alias")
 18     def * = (id.?,name,age,alias)
 19   }
 20   val tupleTypedPerson = TableQuery[TupleTypedPerson]
 21 
 22   val db = Database.forURL("jdbc:h2:mem:test1;DB_CLOSE_DELAY=-1", driver = "org.h2.Driver")
 23   val createSchemaAction = tupleTypedPerson.schema.create
 24   Await.ready(db.run(createSchemaAction),Duration.Inf)
 25   val initDataAction = DBIO.seq {
 26     tupleTypedPerson ++= Seq(
 27       (Some(0),"Tiger Chan", 45, Some("Tiger_XC")),
 28       (Some(0),"Johnny Cox", 17, None),
 29       (Some(0),"Cathy Williams", 18, Some("Catty")),
 30       (Some(0),"David Wong", 43, None)
 31     )
 32   }
 33   Await.ready(db.run(initDataAction),Duration.Inf)
 34 
 35   val queryAction = tupleTypedPerson.result
 36 
 37   Await.result(db.run(queryAction),Duration.Inf).foreach {row =>
 38     println(s"${row._1.get} ${row._2} ${row._4.getOrElse("")}, ${row._3}")
 39   }
 40 
 41   class Person(val id: Option[Int],
 42                val name: String, val age: Int, val alias: Option[String])
 43   def toPerson(t: (Option[Int],String,Int,Option[String])) = new Person (
 44     t._1,t._2,t._3,t._4
 45   )
 46   def fromPerson(p: Person) = Some((p.id,p.name,p.age,p.alias))
 47   class TupleMappedPerson(tag: Tag) extends Table[
 48     Person](tag,"PERSON") {
 49     def id = column[Int]("id",O.PrimaryKey,O.AutoInc)
 50     def name = column[String]("name")
 51     def age = column[Int]("age")
 52     def alias = column[Option[String]]("alias")
 53     def * = (id.?,name,age,alias) <> (toPerson,fromPerson)
 54   }
 55   val tupleMappedPerson = TableQuery[TupleMappedPerson]
 56 
 57   Await.result(db.run(tupleMappedPerson.result),Duration.Inf).foreach {row =>
 58     println(s"${row.id.get} ${row.name} ${row.alias.getOrElse("")}, ${row.age}")
 59   }
 60 
 61   def hlistToPerson(hl: Option[Int]::String::Int::(Option[String])::HNil) =
 62     new Person(hl(0),hl(1),hl(2),hl(3))
 63   def personToHList(p: Person) = Some(p.id::p.name::p.age::p.alias::HNil)
 64   class HListPerson(tag: Tag) extends Table[Person](tag,"PERSON") {
 65     def id = column[Int]("id",O.PrimaryKey,O.AutoInc)
 66     def name = column[String]("name")
 67     def age = column[Int]("age")
 68     def alias = column[Option[String]]("alias")
 69     def * = (id.?)::name::age::alias::HNil <> (hlistToPerson,personToHList)
 70   }
 71   val hlistPerson = TableQuery[HListPerson]
 72   Await.result(db.run(hlistPerson.result),Duration.Inf).foreach {row =>
 73     println(s"${row.id.get} ${row.name} ${row.alias.getOrElse("")}, ${row.age}")
 74   }
 75 
 76   case class YR(name: String, yr: Int)
 77 
 78   val qYear = for {
 79     p <- hlistPerson
 80   } yield ((p.name, p.age) <> (YR.tupled,YR.unapply))
 81 
 82   Await.result(db.run(qYear.result),Duration.Inf).foreach {row =>
 83     println(s"${row.name} ${row.yr}")
 84   }
 85 
 86   case class Title(id: Int, title: String)
 87   class PersonTitle(tag: Tag) extends Table[Title](tag,"TITLE") {
 88     def id = column[Int]("id")
 89     def title = column[String]("title")
 90     def * = (id,title) <> (Title.tupled,Title.unapply)
 91   }
 92   val personTitle = TableQuery[PersonTitle]
 93   val createTitleAction = personTitle.schema.create
 94    Await.ready(db.run(createTitleAction),Duration.Inf)
 95    val initTitleData = DBIO.seq {
 96      personTitle ++= Seq(
 97        Title(1,"Manager"),
 98        Title(2,"Programmer"),
 99        Title(3,"Clerk")
100      )
101    }
102    Await.ready(db.run(initTitleData),Duration.Inf)
103 
104   case class Titles(id: Int, name: String, title: String)
105   val qPersonWithTitle = for {
106     p <- hlistPerson
107     t <- personTitle if p.id === t.id
108   } yield ((p.id,p.name,t.title) <> (Titles.tupled,Titles.unapply))
109   Await.result(db.run(qPersonWithTitle.result),Duration.Inf).foreach {row =>
110     println(s"${row.id} ${row.name}, ${row.title}")
111   }
112   
113 
114 }
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