A Bloom filter is a space-efficient probabilistic data structure

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Name Summary
Bloom filter is based on multiple hashing, instead of one  
Bloom filters are usually periodically rebuilt  
By default, you can’t remove element from bloom filter  
Reference YouTube: Bloom Filters

Q: What are the typical use cases of bloom filter?

  • Cache filtering: Google Bigtable, Apache HBase and Apache Cassandra and PostgreSQL[11] use Bloom filters to reduce the disk lookups for non-existent rows or columns.
  • Search engine: Microsoft Bing (search engine) uses multi-level hierarchical Bloom filters for its search index.
  • Web browser: The Google Chrome web browser used to use a Bloom filter to identify malicious URLs.
  • Data synchronization: Bloom filters can be used for approximate data synchronization.
  • Bitcoin uses Bloom filters to speed up wallet synchronization

Q: How we know bloom filter needs to be rebuilt?


Q: How to resize bloom filter, if false positive ratio is too high?


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