Slick - 更新完整对象或超过 22 列

我有一张桌子user_permissions其中有 46 个权限列以及id and created_date。这个表有对应的UserPermissions class:

class UserPermission(val id: Long,
  val createdDate: Option[Timestamp],
  val permission1: Boolean,
  val permission2: Boolean,
  ...
  val permission46: Boolean)

和光滑的映射表

class UserPermissions(tag: Tag) extends Table[UserPermission](tag, "users_permissions") {
  def * = (
    id ::
    createdDate ::
    permission1 ::
    permission2 ::
    ...
    permission46 ::
    HNil).shaped <> (
    { case x => UserPermission(
         x(0), x(1), x(2), ... x(47))
    },
    {
       UserPermission.unapply _
    }
  }
  ... <columns defined here>
)

现在我想更新由以下标识的 UserPermission 集id。我的功能是：

object UserPermissions {
  val userPermissions = TableQuery[UserPermissions]

  def update(userPermission: UserPermission)(implicit session: Session) = {
    userPermissions.filter(_.id === userPermission.id.get).update(userPermission)
  }
}

这不起作用并抛出异常：

play.api.Application$$anon$1: Execution exception[[SQLServerException: Cannot update identity column 'id'.]]

这是有道理的，因为 Slick 生成的 SQL 是：

update "users_permissions" set "id" = ?, "created_date" = ?, ...

问题1所以我的第一个问题是我无法更新完整的UserPermission有光滑的物体. 如果我能解决这个问题那就太好了.

由于我无法更新完整对象，所以我想yield我想要更新的列然后触发更新查询。代码如下所示：

def update(obj: UserPermission)(implicit session: Session) = {
    val query = for {
      p <- userPermissions
      if p.id === obj.id.get
    } yield (p.permission1, p.permission2, ... p.permission46)
    query.update(obj.permission1, obj.permission2, ... obj.permission46)
}

问题2 Now slick 没有更新 46 列query.update()功能。它一次只能处理 22 列。我怎样才能更新我的UserPermissions object?

我能想到的一个糟糕的解决方案是第一次更新 22，然后第二次更新 22，然后在第三次查询中更新 2。这将是我不想要的 3 db 更新查询。

我的问题有什么解决办法吗？

依赖关系是：

scalaVersion := "2.11.4"

"com.typesafe.play" %% "play-slick" % "0.8.1"
"com.typesafe.slick" %% "slick-extensions" % "2.1.0"

Stefan Zeiger，Slick 的主角，said https://groups.google.com/forum/#!msg/scalaquery/qjNW8P7VQJ8/ntqCkz0S4WIJ我们不能。不过，他建议我们在 22+ 列的平面表上嵌套投影：

// 2 classes for the nested structure
case class Part(i1: Int, i2: Int, i3: Int, i4: Int, i5: Int, i6: Int)
case class Whole(id: Int, p1: Part, p2: Part, p3: Part, p4: Part)

// Note that it's a Table[Int] -- we only map the primary key in *
object T extends Table[Int]("t_wide") {
  def id = column[Int]("id", O.PrimaryKey)
  def p1i1 = column[Int]("p1i1")
  def p1i2 = column[Int]("p1i2")
  def p1i3 = column[Int]("p1i3")
  def p1i4 = column[Int]("p1i4")
  def p1i5 = column[Int]("p1i5")
  def p1i6 = column[Int]("p1i6")
  def p2i1 = column[Int]("p2i1")
  def p2i2 = column[Int]("p2i2")
  def p2i3 = column[Int]("p2i3")
  def p2i4 = column[Int]("p2i4")
  def p2i5 = column[Int]("p2i5")
  def p2i6 = column[Int]("p2i6")
  def p3i1 = column[Int]("p3i1")
  def p3i2 = column[Int]("p3i2")
  def p3i3 = column[Int]("p3i3")
  def p3i4 = column[Int]("p3i4")
  def p3i5 = column[Int]("p3i5")
  def p3i6 = column[Int]("p3i6")
  def p4i1 = column[Int]("p4i1")
  def p4i2 = column[Int]("p4i2")
  def p4i3 = column[Int]("p4i3")
  def p4i4 = column[Int]("p4i4")
  def p4i5 = column[Int]("p4i5")
  def p4i6 = column[Int]("p4i6")
  // This is just the default projection -- It doesn't have to contain all columns
  def * = id
  // Instead, we use nested tuples for a full projection:
  def all = (
    id,
    (p1i1, p1i2, p1i3, p1i4, p1i5, p1i6),
    (p2i1, p2i2, p2i3, p2i4, p2i5, p2i6),
    (p3i1, p3i2, p3i3, p3i4, p3i5, p3i6),
    (p4i1, p4i2, p4i3, p4i4, p4i5, p4i6)
  )
  // And override create_* to get the DDL for all columns.
  // Yeah, this is ugly. It used to be much simpler in ScalaQuery.
  // We can add a helper method to simplify it.
  override def create_* =
    all.shaped.packedNode.collect {
      case Select(Ref(IntrinsicSymbol(in)), f: FieldSymbol) if in == this => f
    }.toSeq.distinct
}

T.ddl.create
// Insert into T.all. The extra ".shaped" call is needed because we cannot
// get the types in an implicit conversion due to SI-3346
T.all.shaped.insert(
  0,
  (11, 12, 13, 14, 15, 16),
  (21, 22, 23, 24, 25, 26),
  (31, 32, 33, 34, 35, 36),
  (41, 42, 43, 44, 45, 46)
)

// Get the nested tuples in a query
val q1 = T.map(_.all)
println(q1.first)

// Map the result to the case classes
val i2 = q1.mapResult { case (id, p1, p2, p3, p4) =>
  Whole(id, Part.tupled.apply(p1), Part.tupled.apply(p2), Part.tupled.apply(p3), Part.tupled.apply(p4))
}
println(i2.first)

现在是一个test https://github.com/slick/slick/blob/006d8a71b629099712e53ca04abc156b50818684/slick-testkit/src/main/scala/com/typesafe/slick/testkit/tests/JdbcMapperTest.scala#L144在 Slick 包括一个版本3 https://github.com/slick/slick/blob/master/slick-testkit/src/main/scala/com/typesafe/slick/testkit/tests/JdbcMapperTest.scala。至于更新：

val oData = Whole(0,
  Part(11, 12, 13, 14, 15, 16),
  Part(21, 22, 23, 24, 25, 26),
  Part(31, 32, 33, 34, 35, 36),
  Part(41, 42, 43, 44, 45, 46)
)
val oData2 = Whole(10,
  Part(111, 12, 13, 14, 15, 16),
  Part(121, 22, 23, 24, 25, 26),
  Part(131, 32, 33, 34, 35, 36),
  Part(141, 42, 43, 44, 45, 46)
)

ts.ddl.create

ts.insert(oData)
assertEquals(oData, ts.first)

ts.filter(_.p1i2 === 12).update(oData2)
assertEquals(oData2, ts.first)

具有 Slick 投影的嵌套对象可以展平为您带入或带走的单个对象。