Apache Data Sketches is an open-source library of probabilistic data structures designed for fast, approximate analytics on massive datasets
BigQuery now integrates Apache Data Sketches, enabling large-scale, quick, and resource-efficient approximation analytics
Sketches summarize large datasets with minimal memory and computational overhead, often requiring only a single data pass
They are ideal for non-additive aggregation tasks like count distinct, quantiles, and most-frequent items, which are costly with traditional methods
Key sketch types include Theta Sketch (distinct counting and set expressions), HyperLogLog (HLL), CPC Sketch, Tuple Sketch, KLL Sketch, REQ Sketch, T-Digest
Sketches can be merged, making them additive and highly parallelizable for distributed and scalable analytics
Using Apache Data Sketches in BigQuery helps lower query costs, simplifies architecture, and enables efficient, scalable analytics for cloud-scale data