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Tweet Counts Per Frequency

Difficulty: Medium

Problem Description

A social media company is trying to monitor activity on their site by analyzing the number of tweets that occur in select periods of time. These periods can be partitioned into smaller time chunks based on a certain frequency (every minute, hour, or day).

Implement the TweetCounts class with methods to record tweets and retrieve the count of tweets in specified time chunks.

Key Insights

  • The problem requires partitioning a time range into chunks based on a specified frequency.
  • Each chunk may contain multiple tweets, and we need to count these efficiently.
  • We can use a hash table to store the tweet counts for each tweet name and each relevant time chunk.
  • The last chunk may be shorter than the specified frequency.

Space and Time Complexity

Time Complexity:

  • O(1) for recordTweet since we are just adding to a hash table.
  • O(n) for getTweetCountsPerFrequency where n is the number of chunks created based on the time range and frequency.

Space Complexity:

  • O(k) where k is the number of unique tweet names recorded.

Solution

The solution uses a hash table (dictionary) to store the counts of tweets for each tweet name. When a tweet is recorded, it increments the count for that specific time. For retrieving counts, the time range is divided into chunks based on the specified frequency. The counts for each chunk are then calculated and returned as a list.

Code Solutions

class TweetCounts:

    def __init__(self):
        self.tweet_data = {}

    def recordTweet(self, tweetName: str, time: int) -> None:
        if tweetName not in self.tweet_data:
            self.tweet_data[tweetName] = []
        self.tweet_data[tweetName].append(time)

    def getTweetCountsPerFrequency(self, freq: str, tweetName: str, startTime: int, endTime: int) -> List[int]:
        if tweetName not in self.tweet_data:
            return []
        
        # Determine the time chunk size based on frequency
        if freq == "minute":
            chunk_size = 60
        elif freq == "hour":
            chunk_size = 3600
        elif freq == "day":
            chunk_size = 86400
        
        # Prepare the result list
        result = []
        chunk_count = (endTime - startTime) // chunk_size + 1
        
        # Create a list to count tweets in each time chunk
        counts = [0] * chunk_count
        
        # Count tweets in the provided time range
        for time in self.tweet_data[tweetName]:
            if startTime <= time <= endTime:
                chunk_index = (time - startTime) // chunk_size
                counts[chunk_index] += 1
        
        return counts
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