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Join-Distinct Aggregate Estimation over Update Streams

Summary: First space-efficient algorithms for Join-Distinct (distinct-projection over joins) on general update streams (inserts+deletes), introducing JD sketches — a new class of hash-based synopses that are built per stream and combinable. Probabilistic estimators yield low-error, high-confidence estimates with small per-update time and space, backed by near-optimal lower bounds and empirical validation. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1359
Venue
PODS
Year
2005
Pagerank
4.1945683e-05
Overall Rank
12,531 | 12.83%
DOI
-

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