The author of the text was working on a memory fragmentation issue with a large database, specifically a Redis database. The problem arose from having over 500 million keys in the database, making it impractical to iterate through all keys to gather information about their size, TTL (time to live), and usage. To overcome this challenge, the author developed a Python script that uses random samples of the keys to estimate the required data. The script works by dividing the key range into bins and then generating a small number of random keys within each bin. It calculates the average size, TTL, and idle time for each bin, providing an estimate of the data that can be used instead of processing the entire database.