08-heaps
Top-K with a Heap
Keep only the largest k values by maintaining a small min-heap.
Algorithm
@steps
- Store the heap in an array.
- Compare parent and child indexes instead of building explicit tree nodes.
- Swap only when the heap order is violated.
- Print the deterministic final heap state for replay comparison. @end @complexity
- Time: O(n log k)
- Space: O(k) @end
bounded heap
For top-k largest values, a min-heap of size k keeps the current cutoff at the root.
Scala DSA Implementation
basic.scala
import scala.collection.mutable.ArrayBuffer
object Main {
def listString(values: Seq[Int]): String = values.mkString("[", ", ", "]")
def heapInsert(heap: ArrayBuffer[Int], value: Int): Unit = {
heap += value
var child = heap.length - 1
while (child > 0) {
val parent = (child - 1) / 2
if (heap(parent) <= heap(child)) return
val tmp = heap(parent); heap(parent) = heap(child); heap(child) = tmp
child = parent
}
}
def heapPop(heap: ArrayBuffer[Int]): Int = {
val smallest = heap(0)
heap(0) = heap.remove(heap.length - 1)
var parent = 0
var done = false
while (!done) {
val left = parent * 2 + 1
val right = left + 1
if (left >= heap.length) done = true
else {
var child = left
if (right < heap.length && heap(right) < heap(left)) child = right
if (heap(parent) <= heap(child)) done = true
else { val tmp = heap(parent); heap(parent) = heap(child); heap(child) = tmp; parent = child }
}
}
smallest
}
def main(args: Array[String]): Unit = { val heap = ArrayBuffer.empty[Int]; for (value <- List(5, 1, 9, 3, 7, 2)) { heapInsert(heap, value); if (heap.length > 3) heapPop(heap) }; println(listString(heap.sorted(Ordering.Int.reverse))) }
}
@end @output [9, 7, 5] @end