Approximate Query Processing under Updates
Summary: Allowing small approximation yields an AQP algorithm that maintains any free-connex aggregation query in O(log n) amortized time per insertion-only update. Works in a general semiring (count/sum/avg/max/distinct), gives large practical speedups with 10% error, and logarithmic bounds for fully dynamic updates ruled out by lower bounds. (summarized by gpt-5-mini on Feb 11 2026)
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Authors
- 1. Binyang Dai
- 2. Ke Yi
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