The LogLog and HyperLogLog algorithms are a probabilistic way to calculate the approximate cardinality, or distinct elements, in some set using a small amount o

The LogLog and HyperLogLog algorithms are a probabilistic way to calculate the approximate cardinality, or distinct elements, in some set using a small amount of memory. I think it’s pretty awesome because it still works even if there are duplicate elements in the set. This counting bloom filter lets us estimate about how many times we’ve encountered a particular element in some huge set using a relatively small amount of memory. So we’re answering two different questions with these guys: Counting bloom filter: About how many times has a particular element shown up in this set? (Hyper)LogLog: About how many unique elements are in this set?