Phase 5Intermediate6 of 12 in Bloom Filters

Storage Engines and the Edge

Why every LSM-tree database keeps a Bloom filter per SSTable, how RocksDB, Cassandra, HBase and Parquet configure them, and how CDNs use filters to avoid caching one-hit wonders.

Bloom filters earn most of their keep deep inside databases: they let a read skip files that can't contain a key, turning many disk reads into one. The same idea shows up at CDN edges and in columnar file formats.

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3 topics ~23 min 4 code blocks & diagrams

Start with the first topic

5.1

LSM Trees and SSTable Filters

An LSM tree writes to a MemTable, flushes sorted immutable SSTables to disk, and compacts them over time. A point read may have to look in many SSTables; a Bloom filter per SSTable (kept in memory) says "definitely not here" for most of them, so a lookup costs about one disk read instead of dozens.

8 min 1 diagram 1 code practice

5.2

Bloom Filters in Real Databases and Formats

RocksDB (bits per key, full, blocked and Ribbon filters, prefix filters), LevelDB, Cassandra (bloom_filter_fp_chance per table), HBase (ROW/ROWCOL filters per HFile), ScyllaDB, Parquet (split-block Bloom filters per column chunk) and PostgreSQL's bloom index extension all use membership filters to avoid I/O. Know the knobs.

7 min 1 code practice

5.3

CDNs and Edge Filtering

CDNs use Bloom filters at edge nodes to avoid work: caching an object only on its second request (filtering out one-hit wonders, as Akamai described), checking whether content IDs exist before hitting origin, and shipping compact blocklists. Edge filters must be small, versioned and synchronised.

8 min 1 diagram practice

Command Palette

LSM Trees and SSTable Filters

Bloom Filters in Real Databases and Formats

CDNs and Edge Filtering