go---详解container/heap
目录container/heap是什么container/heap提供的方法container/heap的源码container/heap用途1. int slice类型的小根堆2. 实现优先级队列(重要:k8s优先级队列)3. 处理最小的K个数或者最大的K个数,处理海量数据container/heap是什么堆(英语:heap)是计算机科学中一类特殊的数据结构的...
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目录
container/heap是什么
堆(英语:heap)是计算机科学中一类特殊的数据结构的统称。堆通常是一个可以被看做一棵树的数组对象。堆总是满足下列性质:
-
堆中某个节点的值总是不大于或不小于其父节点的值;
-
堆总是一棵完全二叉树。
将根节点最大的堆叫做最大堆或大根堆,根节点最小的堆叫做最小堆或小根堆。
- 堆的初始化。如何初始化,构建大根堆和小根堆
- 堆的插入元素和删除元素
- 堆的排序
- 堆的向上调整函数和向下调整函数
上述4个问题搞明白之后再去看源码,会更清楚实现。
container/heap提供的方法
container/heap
为小根堆,即每个节点的值都小于它的子树的所有元素的值。heap包为实现了heap.Interface
的类型提供了堆方法:Init/Push/Pop/Remove/Fix。
由于heap.Interface
包含了sort.Interface
,所以,目标类型需要包含如下方法:Len/Less/Swap, Push/Pop。
type Interface interface {
sort.Interface
Push(x interface{}) // add x as element Len()
Pop() interface{} // remove and return element Len() - 1.
}
container/heap的源码
见文章分析:https://studygolang.com/articles/13173
func Fix(h Interface, i int) // 修改第i个元素后,调用本函数修复堆 复杂度O(log(n)),其中n等于h.Len()。
func Init(h Interface) //初始化一个堆。一个堆在使用任何堆操作之前应先初始化。复杂度为O(n)
func Pop(h Interface) interface{} //删除并返回堆h中的最小元素(不影响约束性)。
func Push(h Interface, x interface{}) //向堆h中插入元素x,并保持堆的约束性。
func Remove(h Interface, i int) interface{} //删除堆中的第i个元素,并保持堆的约束性。
container/heap用途
1. int slice类型的小根堆
// This example demonstrates an integer heap built using the heap interface.
package main
import (
"container/heap"
"fmt"
)
// An IntHeap is a min-heap of ints.
type IntHeap []int
func (h IntHeap) Len() int { return len(h) }
func (h IntHeap) Less(i, j int) bool { return h[i] < h[j] } // 小根堆 > 大根堆
func (h IntHeap) Swap(i, j int) { h[i], h[j] = h[j], h[i] }
func (h *IntHeap) Push(x interface{}) {
// Push and Pop use pointer receivers because they modify the slice's length,
// not just its contents.
*h = append(*h, x.(int))
}
func (h *IntHeap) Pop() interface{} {
old := *h
n := len(old)
x := old[n-1]
*h = old[0 : n-1]
return x
}
// This example inserts several ints into an IntHeap, checks the minimum,
// and removes them in order of priority.
func main() {
h := &IntHeap{2, 1, 5}
heap.Init(h)
heap.Push(h, 3)
fmt.Printf("minimum: %d\n", (*h)[0])
for h.Len() > 0 {
fmt.Printf("%d ", heap.Pop(h))
}
}
2. 实现优先级队列(重要:k8s优先级队列)
// This example demonstrates a priority queue built using the heap interface.
package main
import (
"container/heap"
"fmt"
)
// An Item is something we manage in a priority queue.
type Item struct {
value string // The value of the item; arbitrary.
priority int // The priority of the item in the queue.
// The index is needed by update and is maintained by the heap.Interface methods.
index int // The index of the item in the heap.
}
// A PriorityQueue implements heap.Interface and holds Items.
type PriorityQueue []*Item
func (pq PriorityQueue) Len() int { return len(pq) }
func (pq PriorityQueue) Less(i, j int) bool {
// We want Pop to give us the highest, not lowest, priority so we use greater than here.
return pq[i].priority > pq[j].priority
}
func (pq PriorityQueue) Swap(i, j int) {
pq[i], pq[j] = pq[j], pq[i]
pq[i].index = i
pq[j].index = j
}
func (pq *PriorityQueue) Push(x interface{}) {
n := len(*pq)
item := x.(*Item)
item.index = n
*pq = append(*pq, item)
}
func (pq *PriorityQueue) Pop() interface{} {
old := *pq
n := len(old)
item := old[n-1]
item.index = -1 // for safety
*pq = old[0 : n-1]
return item
}
// update modifies the priority and value of an Item in the queue.
func (pq *PriorityQueue) update(item *Item, value string, priority int) {
item.value = value
item.priority = priority
heap.Fix(pq, item.index)
}
// This example creates a PriorityQueue with some items, adds and manipulates an item,
// and then removes the items in priority order.
func main() {
// Some items and their priorities.
items := map[string]int{
"banana": 3, "apple": 2, "pear": 4,
}
// Create a priority queue, put the items in it, and
// establish the priority queue (heap) invariants.
pq := make(PriorityQueue, len(items))
i := 0
for value, priority := range items {
pq[i] = &Item{
value: value,
priority: priority,
index: i,
}
i++
}
heap.Init(&pq)
// Insert a new item and then modify its priority.
item := &Item{
value: "orange",
priority: 1,
}
heap.Push(&pq, item)
pq.update(item, item.value, 5)
// Take the items out; they arrive in decreasing priority order.
for pq.Len() > 0 {
item := heap.Pop(&pq).(*Item)
fmt.Printf("%.2d:%s ", item.priority, item.value)
}
}
3. 处理最小的K个数或者最大的K个数,处理海量数据
- 读入k个数构建大小为k的大根堆
- 依次读入剩余数据,当前数据比大根堆的堆顶数据小,替换并调整满足大根堆特性
- 当前数据如果比堆顶数据大,抛弃此数
主要是能够分析堆的初始化、排序、调整、及对堆的应用场景进行掌握。
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