👉 PDT, or Probabilistic Data Structures for Text, is a family of data structures designed to efficiently manage and query large volumes of text data with probabilistic queries. Unlike traditional data structures that guarantee exact results, PDTs provide approximate answers to queries with a specified probability of correctness, making them highly scalable and suitable for real-time applications where exact results are not always necessary. Key components of PDTs include Bloom filters, which quickly determine whether an element is likely to be in a set; data structures like Prefix Trees (Tries) and Suffix Arrays, which support efficient prefix matching and substring queries; and more advanced structures like Counting Bloom filters and HyperLogLogs, which estimate counts and cardinalities. By leveraging these probabilistic techniques, PDTs enable rapid and cost-effective text processing in scenarios where storage and computational resources are limited.
