Synopses for Massive Data: Samples, Histograms, Wavelets, Sketches

DOI10.1561/1900000004zbMath1257.68062OpenAlexW2022858489MaRDI QIDQ2903466

Graham Cormode, Minos Garofalakis, Chris Jermaine, Peter J. Haas

Publication date: 10 August 2012

Published in: Foundations and Trends in Databases (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1561/1900000004

zbMATH Keywords

waveletsrandom sampleshistogramsmassive datasketchesapproximate query processingsynopses data

Mathematics Subject Classification ID

Sampling theory, sample surveys (62D05) Database theory (68P15) Data structures (68P05)

Related Items (10)

Summary Data Structures for Massive Data ⋮ Compressive statistical learning with random feature moments ⋮ The geometry of off-the-grid compressed sensing ⋮ Unnamed Item ⋮ Adaptive Online First-Order Monitoring ⋮ Real-valued embeddings and sketches for fast distance and similarity estimation ⋮ Making big data small ⋮ Learned sketches for frequency estimation ⋮ A survey of challenges for runtime verification from advanced application domains (beyond software) ⋮ Private aggregation from fewer anonymous messages

Uses Software

• KernSmooth

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