Given a large set of CSV files with thousands of paragraphs each, how would you detect duplicates within each file, and how would you scale this solution for many files?

To detect duplicate paragraphs within a large CSV file, I would first normalize the text by converting it to lowercase and removing punctuation. Then, I'd use a hashing technique, such as SHA-256, to generate a unique hash for each paragraph. Storing these hashes in a set or hash table allows for efficient O(1) average time complexity lookups to identify duplicates. For scaling this solution across many files, I would leverage distributed computing frameworks like Apache Spark. Spark can process files in parallel across a cluster, applying the hashing and duplicate detection logic to each partition of the data. This distributed approach significantly reduces processing time and handles large datasets effectively.