Bloom Filter
A Bloom filter is a space-efficient probabilistic data structure used to test whether an element is a member of a set. It can return false positives (indicating an element is in the set when it is not) but never false negatives, making it ideal for scenarios where memory is limited and occasional errors are acceptable. It works by using multiple hash functions to map elements to bits in a bit array.
Developers should learn Bloom filters when building applications that require fast membership queries on large datasets with limited memory, such as web caches, spell checkers, or network routers. They are particularly useful in distributed systems for reducing disk or network I/O, like in databases (e.g., Apache Cassandra) to avoid expensive lookups for non-existent keys. However, they are not suitable for applications requiring exact results, such as financial transactions.