If you’re willing to tolerate an error rate of just 1% or 2%, storing your findings in a probabilistic data structure like a Bloom filter will save you significant amounts of both time and space. And the usefulness of such filters is not confined to search engines: Bloom filters have shipped with a number of recent web browsers to check URLs against a list of known malicious websites, and they are also an important part of cryptocurrencies like Bitcoin.
