我正在使用一个库,它提供了一个通过数据库结果进行页面处理的TraversableT。我希望避免将整个事件加载到内存中,因此我尝试将其转换为StreamT。
据我所知,内置的"asStream“方法将整个可遍历的代码加载到缓冲区中,这违背了我的目的。我的尝试(下面)击中了一个大的结果的StackOverflowException,我不知道为什么。有人能帮我了解一下发生了什么吗?谢谢!
def asStream[T](traversable: => Traversable[T]): Stream[T] = {
if (traversable.isEmpty) Empty
else {
lazy val head = traversable.head
lazy val tail = asStream(traversable.tail)
head #:: tail
}
}下面是一个完整的示例,它根据@SCouto的建议复制这个
import scala.collection.immutable.Stream.Empty
object StreamTest {
def main(args: Array[String]) = {
val bigVector = Vector.fill(90000)(1)
val optionStream = asStream(bigVector).map(v => Some(v))
val zipped = optionStream.zipAll(optionStream.tail, None, None)
}
def asStream[T](traversable: => Traversable[T]): Stream[T] = {
@annotation.tailrec
def loop(processed: => Stream[T], pending: => Traversable[T]): Stream[T] = {
if (pending.isEmpty) processed
else {
lazy val head = pending.head
lazy val tail = pending.tail
loop(processed :+ head, tail)
}
}
loop(Empty, traversable)
}
}编辑:在@SCouto的一些有趣的想法之后,我了解到这也可以用蹦床来完成,以将结果保持为一个按原来顺序排列的StreamT。
object StreamTest {
def main(args: Array[String]) = {
val bigVector = Range(1, 90000).toVector
val optionStream = asStream(bigVector).map(v => Some(v))
val zipped = optionStream.zipAll(optionStream.tail, None, None)
zipped.take(10).foreach(println)
}
def asStream[T](traversable: => Traversable[T]): Stream[T] = {
sealed trait Traversal[+R]
case class More[+R](result: R, next: () => Traversal[R]) extends Traversal[R]
case object Done extends Traversal[Nothing]
def next(currentTraversable: Traversable[T]): Traversal[T] = {
if (currentTraversable.isEmpty) Done
else More(currentTraversable.head, () => next(currentTraversable.tail))
}
def trampoline[R](body: => Traversal[R]): Stream[R] = {
def loop(thunk: () => Traversal[R]): Stream[R] = {
thunk.apply match {
case More(result, next) => Stream.cons(result, loop(next))
case Done => Stream.empty
}
}
loop(() => body)
}
trampoline(next(traversable))
}
}发布于 2018-06-04 12:40:49
试试这个:
def asStream[T](traversable: => Traversable[T]): Stream[T] = {
@annotation.tailrec
def loop(processed: Stream[T], pending: Traversable[T]): Stream[T] = {
if (pending.isEmpty) processed
else {
lazy val head = pending.head
lazy val tail = pending.tail
loop(head #:: processed, tail)
}
}
loop(Empty, traversable)
}要点是确保递归调用是递归函数的最后一个动作。
为了确保这一点,可以同时使用嵌套方法(在示例中称为loop )和tailrec注释,以确保方法是尾安全的。
您可以在这个令人敬畏的答案( 这里 )中找到有关尾部rec 这里的信息
编辑问题是,我们在流的末尾添加了元素。如果您将它作为Stream的头添加,就像在您的示例中一样,它将很好地工作。我更新了密码。请进行测试,并让我们知道结果。
我的测试:
scala> val optionStream = asStream(Vector.fill(90000)(1)).map(v => Some(v))
optionStream: scala.collection.immutable.Stream[Some[Int]] = Stream(Some(1), ?)
scala> val zipped = optionStream.zipAll(optionStream.tail, None, None)
zipped: scala.collection.immutable.Stream[(Option[Int], Option[Int])] = Stream((Some(1),Some(1)), ?)EDIT2:
根据您的评论,并考虑您所说的fpinscala的例子。我觉得这可能对你有帮助。重点是创建一个带有延迟计算的案例类结构。其中头部是一个单一的元素,而尾巴是可遍历的。
sealed trait myStream[+T] {
def head: Option[T] = this match {
case MyEmpty => None
case MyCons(h, _) => Some(h())
}
def tail: myStream[T] = this match {
case MyEmpty => MyEmpty
case MyCons(_, t) => myStream.cons(t().head, t().tail)
}
}
case object MyEmpty extends myStream[Nothing]
case class MyCons[+T](h: () => T, t: () => Traversable[T]) extends myStream[T]
object myStream {
def cons[T](hd: => T, tl: => Traversable[T]): myStream[T] = {
lazy val head = hd
lazy val tail = tl
MyCons(() => head, () => tail)
}
def empty[T]: myStream[T] = MyEmpty
def apply[T](as: T*): myStream[T] = {
if (as.isEmpty) empty
else cons(as.head, as.tail)
}
}一些快速测试:
val bigVector = Vector.fill(90000)(1)
myStream.cons(bigVector.head, bigVector.tail)
res2: myStream[Int] = MyCons(<function0>,<function0>)回收头:
res2.head
res3: Option[Int] = Some(1)而尾巴:
res2.tail
res4: myStream[Int] = MyCons(<function0>,<function0>)EDIT3
执行部分的蹦床解决方案:
def asStream[T](traversable: => Traversable[T]): Stream[T] = {
sealed trait Traversal[+R]
case class More[+R](result: R, next: () => Traversal[R]) extends Traversal[R]
case object Done extends Traversal[Nothing]
def next(currentTraversable: Traversable[T]): Traversal[T] = {
if (currentTraversable.isEmpty) Done
else More(currentTraversable.head, () => next(currentTraversable.tail))
}
def trampoline[R](body: => Traversal[R]): Stream[R] = {
def loop(thunk: () => Traversal[R]): Stream[R] = {
thunk.apply match {
case More(result, next) => Stream.cons(result, loop(next))
case Done => Stream.empty
}
}
loop(() => body)
}
trampoline(next(traversable))
}
}https://stackoverflow.com/questions/50680472
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