Subdomain Visit Count
Problem Descriptionā
A website domain "discuss.leetcode.com"
consists of various subdomains. At the top level, we have "com"
, at the next level, we have "leetcode.com"
and at the lowest level, "discuss.leetcode.com"
. When we visit a domain like "discuss.leetcode.com"
, we will also visit the parent domains "leetcode.com"
and "com"
implicitly.
A count-paired domain is a domain that has one of the two formats "rep d1.d2.d3"
or "rep d1.d2"
where rep
is the number of visits to the domain and d1.d2.d3 is the domain itself.
For example, "9001 discuss.leetcode.com"
is a count-paired domain that indicates that discuss.leetcode.com
was visited 9001
times.
Given an array of count-paired domains cpdomains, return an array of the count-paired domains of each subdomain in the input. You may return the answer in any order.
Example 1ā
- Input:
cpdomains = ["9001 discuss.leetcode.com"]
- Output:
["9001 leetcode.com","9001 discuss.leetcode.com","9001 com"]
- Explanation:
We only have one website domain: "discuss.leetcode.com". As discussed above, the subdomain "leetcode.com" and "com" will also be visited. So they will all be visited 9001 times.
Constraintsā
1 <= cpdomain.length <= 100
1 <= cpdomain[i].length <= 100
Approachā
Just store each & every valid substring in a HashMap with its frequency count. Update the frequency count whenever the same string is encounterd. Finally, create a new string using each key-value pair of the HashMap & add that new string to the final list.
Solution Codeā
Javaā
class Solution {
HashMap<String, Integer> hm= new HashMap<>();
public List<String> subdomainVisits(String[] cpdomains) {
List<String> result= new ArrayList<>();
for(String s: cpdomains){
addToList(s);
}
for(String s: hm.keySet()){
StringBuilder sb= new StringBuilder( Integer.toString(hm.get(s)) );
sb.append(" ");
sb.append( s );
result.add( sb.toString() );
}
return result;
}
public void addToList(String s){
String[] split1= s.split(" ");
int n= Integer.parseInt(split1[0]);
String[] split2= split1[1].split("\\.");
int l= split2.length;
for(int i=0; i<l; i++){
StringBuilder sb= new StringBuilder();
int index= i;
while(index < l){
sb.append( split2[index] );
if(index != l-1)
sb.append( "." );
index++;
}
String str= sb.toString();
hm.put( str, hm.getOrDefault( str, 0 )+n);
}
}
}
-
Time Complexity The time complexity is O(Nā L2).
-
Space Complexity The space complexity is O(1).