3433. Count Mentions Per User
Description
You are given an integer numberOfUsers
representing the total number of users and an array events
of size n x 3
.
Each events[i]
can be either of the following two types:
- Message Event:
["MESSAGE", "timestampi", "mentions_stringi"]
- This event indicates that a set of users was mentioned in a message at
timestampi
. - The
mentions_stringi
string can contain one of the following tokens:id<number>
: where<number>
is an integer in range[0,numberOfUsers - 1]
. There can be multiple ids separated by a single whitespace and may contain duplicates. This can mention even the offline users.ALL
: mentions all users.HERE
: mentions all online users.
- This event indicates that a set of users was mentioned in a message at
- Offline Event:
["OFFLINE", "timestampi", "idi"]
- This event indicates that the user
idi
had become offline attimestampi
for 60 time units. The user will automatically be online again at timetimestampi + 60
.
- This event indicates that the user
Return an array mentions
where mentions[i]
represents the number of mentions the user with id i
has across all MESSAGE
events.
All users are initially online, and if a user goes offline or comes back online, their status change is processed before handling any message event that occurs at the same timestamp.
Note that a user can be mentioned multiple times in a single message event, and each mention should be counted separately.
Example 1:
Input: numberOfUsers = 2, events = [["MESSAGE","10","id1 id0"],["OFFLINE","11","0"],["MESSAGE","71","HERE"]]
Output: [2,2]
Explanation:
Initially, all users are online.
At timestamp 10, id1
and id0
are mentioned. mentions = [1,1]
At timestamp 11, id0
goes offline.
At timestamp 71, id0
comes back online and "HERE"
is mentioned. mentions = [2,2]
Example 2:
Input: numberOfUsers = 2, events = [["MESSAGE","10","id1 id0"],["OFFLINE","11","0"],["MESSAGE","12","ALL"]]
Output: [2,2]
Explanation:
Initially, all users are online.
At timestamp 10, id1
and id0
are mentioned. mentions = [1,1]
At timestamp 11, id0
goes offline.
At timestamp 12, "ALL"
is mentioned. This includes offline users, so both id0
and id1
are mentioned. mentions = [2,2]
Example 3:
Input: numberOfUsers = 2, events = [["OFFLINE","10","0"],["MESSAGE","12","HERE"]]
Output: [0,1]
Explanation:
Initially, all users are online.
At timestamp 10, id0
goes offline.
At timestamp 12, "HERE"
is mentioned. Because id0
is still offline, they will not be mentioned. mentions = [0,1]
Constraints:
1 <= numberOfUsers <= 100
1 <= events.length <= 100
events[i].length == 3
events[i][0]
will be one ofMESSAGE
orOFFLINE
.1 <= int(events[i][1]) <= 105
- The number of
id<number>
mentions in any"MESSAGE"
event is between1
and100
. 0 <= <number> <= numberOfUsers - 1
- It is guaranteed that the user id referenced in the
OFFLINE
event is online at the time the event occurs.
Solutions
Solution 1: Sorting + Simulation
We sort the events in ascending order of timestamps. If the timestamps are the same, we place OFFLINE events before MESSAGE events.
Then we simulate the occurrence of events, using the online_t
array to record the next online time for each user and a variable lazy
to record the number of mentions that need to be applied to all users.
We traverse the event list and handle each event based on its type:
- If it is an ONLINE event, we update the
online_t
array. - If it is an ALL event, we increment
lazy
by one. - If it is a HERE event, we traverse the
online_t
array. If a user's next online time is less than or equal to the current time, we increment that user's mention count by one. - If it is a MESSAGE event, we increment the mention count of the mentioned user by one.
Finally, if lazy
is greater than 0, we add lazy
to the mention count of all users.
The time complexity is $O(n + m \times \log m \log M + L)$, and the space complexity is $O(n)$. Here, $n$ and $m$ are the total number of users and events, respectively, while $M$ and $L$ are the maximum value of the timestamps and the total length of all mentioned strings, respectively.
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