diff --git a/problems/0347.前K个高频元素.md b/problems/0347.前K个高频元素.md
index 54be5cc4..6012e118 100644
--- a/problems/0347.前K个高频元素.md
+++ b/problems/0347.前K个高频元素.md
@@ -189,6 +189,79 @@ class Solution:
 
 Go：
 
+```go
+//方法一：小顶堆
+func topKFrequent(nums []int, k int) []int {
+    map_num:=map[int]int{}
+    //记录每个元素出现的次数
+    for _,item:=range nums{
+        map_num[item]++
+    }
+    h:=&IHeap{}
+    heap.Init(h)
+    //所有元素入堆，堆的长度为k
+    for key,value:=range map_num{
+        heap.Push(h,[2]int{key,value})
+        if h.Len()>k{
+            heap.Pop(h)
+        }
+    }
+    res:=make([]int,k)
+    //按顺序返回堆中的元素
+    for i:=0;i<k;i++{
+        res[k-i-1]=heap.Pop(h).([2]int)[0]
+    }
+    return res
+}
+
+//构建小顶堆
+type IHeap [][2]int
+
+func (h IHeap) Len()int {
+    return len(h)
+}
+
+func (h IHeap) Less (i,j int) bool {
+    return h[i][1]<h[j][1]
+}
+
+func (h IHeap) Swap(i,j int) {
+    h[i],h[j]=h[j],h[i]
+}
+
+func (h *IHeap) Push(x interface{}){
+    *h=append(*h,x.([2]int))
+}
+func (h *IHeap) Pop() interface{}{
+    old:=*h
+    n:=len(old)
+    x:=old[n-1]
+    *h=old[0:n-1]
+    return x
+}
+
+
+//方法二:利用O(logn)排序
+func topKFrequent(nums []int, k int) []int {
+    ans:=[]int{}
+    map_num:=map[int]int{}
+    for _,item:=range nums {
+        map_num[item]++
+    }
+    for key,_:=range map_num{
+        ans=append(ans,key)
+    }
+    //核心思想：排序
+    //可以不用包函数，自己实现快排
+    sort.Slice(ans,func (a,b int)bool{
+        return map_num[ans[a]]>map_num[ans[b]]
+    })
+    return ans[:k]
+}
+```
+
+
+
 
 javaScript:
 ```js