705. Design HashSet
September 12, 2026 · View on GitHub
Description
Design a HashSet without using any built-in hash table libraries.
Implement MyHashSet class:
void add(key)Inserts the valuekeyinto the HashSet.bool contains(key)Returns whether the valuekeyexists in the HashSet or not.void remove(key)Removes the valuekeyin the HashSet. Ifkeydoes not exist in the HashSet, do nothing.
Example 1:
Input ["MyHashSet", "add", "add", "contains", "contains", "add", "contains", "remove", "contains"] [[], [1], [2], [1], [3], [2], [2], [2], [2]] Output [null, null, null, true, false, null, true, null, false] Explanation MyHashSet myHashSet = new MyHashSet(); myHashSet.add(1); // set = [1] myHashSet.add(2); // set = [1, 2] myHashSet.contains(1); // return True myHashSet.contains(3); // return False, (not found) myHashSet.add(2); // set = [1, 2] myHashSet.contains(2); // return True myHashSet.remove(2); // set = [1] myHashSet.contains(2); // return False, (already removed)
Constraints:
0 <= key <= 106- At most
104calls will be made toadd,remove, andcontains.
Solutions
Solution 1: Static Array Implementation
Thinking
Implement a set of keys in 10^{6} with at most $1$0^{4}$$ operations. A library map would work, but the point is to design the store.
Keys are already non-negative integers with a fixed bound, so they can be indices. A boolean array of length $1+1$ turns add, remove, and contains into a single write or read.
Space follows the value range rather than the number of keys; that is acceptable under these limits.
Directly create an array of size $1000001$, initially with each element set to false, indicating that the element does not exist in the hash set.
When adding an element to the hash set, set the corresponding position in the array to true; when deleting an element, set the corresponding position in the array to false; when checking if an element exists, directly return the value at the corresponding position in the array.
The time complexity of the above operations is .
Python3
class MyHashSet:
def __init__(self):
self.data = [False] * 1000001
def add(self, key: int) -> None:
self.data[key] = True
def remove(self, key: int) -> None:
self.data[key] = False
def contains(self, key: int) -> bool:
return self.data[key]
# Your MyHashSet object will be instantiated and called as such:
# obj = MyHashSet()
# obj.add(key)
# obj.remove(key)
# param_3 = obj.contains(key)
Java
class MyHashSet {
private boolean[] data = new boolean[1000001];
public MyHashSet() {
}
public void add(int key) {
data[key] = true;
}
public void remove(int key) {
data[key] = false;
}
public boolean contains(int key) {
return data[key];
}
}
/**
* Your MyHashSet object will be instantiated and called as such:
* MyHashSet obj = new MyHashSet();
* obj.add(key);
* obj.remove(key);
* boolean param_3 = obj.contains(key);
*/
C++
class MyHashSet {
public:
bool data[1000001];
MyHashSet() {
memset(data, false, sizeof data);
}
void add(int key) {
data[key] = true;
}
void remove(int key) {
data[key] = false;
}
bool contains(int key) {
return data[key];
}
};
/**
* Your MyHashSet object will be instantiated and called as such:
* MyHashSet* obj = new MyHashSet();
* obj->add(key);
* obj->remove(key);
* bool param_3 = obj->contains(key);
*/
Go
type MyHashSet struct {
data []bool
}
func Constructor() MyHashSet {
data := make([]bool, 1000010)
return MyHashSet{data}
}
func (this *MyHashSet) Add(key int) {
this.data[key] = true
}
func (this *MyHashSet) Remove(key int) {
this.data[key] = false
}
func (this *MyHashSet) Contains(key int) bool {
return this.data[key]
}
/**
* Your MyHashSet object will be instantiated and called as such:
* obj := Constructor();
* obj.Add(key);
* obj.Remove(key);
* param_3 := obj.Contains(key);
*/
TypeScript
class MyHashSet {
data: Array<boolean>;
constructor() {
this.data = new Array(10 ** 6 + 1).fill(false);
}
add(key: number): void {
this.data[key] = true;
}
remove(key: number): void {
this.data[key] = false;
}
contains(key: number): boolean {
return this.data[key];
}
}
/**
* Your MyHashSet object will be instantiated and called as such:
* var obj = new MyHashSet()
* obj.add(key)
* obj.remove(key)
* var param_3 = obj.contains(key)
*/
Solution 2: Array of Linked Lists
Thinking
Solution 1 buys with an array as large as the key universe; most of that space stays unused when few keys appear.
Hash by a smaller modulus into a fixed number of buckets, and store collisions in a list. Each operation hashes, then scans one short bucket.
With the memory follows the bucket count, and the expected cost stays near constant.
We can also create an array of size , where each position in the array is a linked list.
Python3
class MyHashSet:
def __init__(self):
self.size = 1000
self.data = [[] for _ in range(self.size)]
def add(self, key: int) -> None:
if self.contains(key):
return
idx = self.hash(key)
self.data[idx].append(key)
def remove(self, key: int) -> None:
if not self.contains(key):
return
idx = self.hash(key)
self.data[idx].remove(key)
def contains(self, key: int) -> bool:
idx = self.hash(key)
return any(v == key for v in self.data[idx])
def hash(self, key) -> int:
return key % self.size
# Your MyHashSet object will be instantiated and called as such:
# obj = MyHashSet()
# obj.add(key)
# obj.remove(key)
# param_3 = obj.contains(key)
Java
class MyHashSet {
private static final int SIZE = 1000;
private LinkedList[] data;
public MyHashSet() {
data = new LinkedList[SIZE];
for (int i = 0; i < SIZE; ++i) {
data[i] = new LinkedList<Integer>();
}
}
public void add(int key) {
if (contains(key)) {
return;
}
int idx = hash(key);
data[idx].addFirst(key);
}
public void remove(int key) {
if (!contains(key)) {
return;
}
int idx = hash(key);
data[idx].remove(Integer.valueOf(key));
}
public boolean contains(int key) {
int idx = hash(key);
Iterator<Integer> it = data[idx].iterator();
while (it.hasNext()) {
Integer e = it.next();
if (e == key) {
return true;
}
}
return false;
}
private int hash(int key) {
return key % SIZE;
}
}
/**
* Your MyHashSet object will be instantiated and called as such:
* MyHashSet obj = new MyHashSet();
* obj.add(key);
* obj.remove(key);
* boolean param_3 = obj.contains(key);
*/
C++
class MyHashSet {
private:
int size = 1000;
vector<list<int>> data;
public:
MyHashSet()
: data(size) {
}
void add(int key) {
if (contains(key)) {
return;
}
int idx = hash(key);
data[idx].push_back(key);
}
void remove(int key) {
if (!contains(key)) {
return;
}
int idx = hash(key);
data[idx].remove(key);
}
bool contains(int key) {
int idx = hash(key);
for (auto it = data[idx].begin(); it != data[idx].end(); it++) {
if ((*it) == key) {
return true;
}
}
return false;
}
int hash(int key) {
return key % size;
}
};
/**
* Your MyHashSet object will be instantiated and called as such:
* MyHashSet* obj = new MyHashSet();
* obj->add(key);
* obj->remove(key);
* bool param_3 = obj->contains(key);
*/
Go
type MyHashSet struct {
data []list.List
}
func Constructor() MyHashSet {
return MyHashSet{make([]list.List, 1000)}
}
func (this *MyHashSet) Add(key int) {
if this.Contains(key) {
return
}
idx := this.hash(key)
this.data[idx].PushBack(key)
}
func (this *MyHashSet) Remove(key int) {
idx := this.hash(key)
for e := this.data[idx].Front(); e != nil; e = e.Next() {
if e.Value.(int) == key {
this.data[idx].Remove(e)
}
}
}
func (this *MyHashSet) Contains(key int) bool {
idx := this.hash(key)
for e := this.data[idx].Front(); e != nil; e = e.Next() {
if e.Value.(int) == key {
return true
}
}
return false
}
func (this *MyHashSet) hash(key int) int {
return key % len(this.data)
}
/**
* Your MyHashSet object will be instantiated and called as such:
* obj := Constructor();
* obj.Add(key);
* obj.Remove(key);
* param_3 := obj.Contains(key);
*/