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Erebus: Explaining the Outputs of Data Streaming Queries

Summary: Erebus is the first system for explaining missing answers in data streams, extending beyond why-provenance by letting users declare runtime expectations and detecting divergence under streaming constraints (limited storage, unbounded input). It synthesizes compact explanations for absent results with low overheads on both low- and high-end devices, validated on real workloads. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13080
Venue
VLDB
Year
2023
Pagerank
4.5768015e-05
Overall Rank
8,140 | 43.38%
DOI
10.14778/3565816.3565825

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
10,024 LPStream: Fine-grained Lazy Provenance for Stream Processing 2026 SIGMOD 4.1945683e-05
10,546 Evaluating Continuous Queries with Inconsistency Annotations 2025 VLDB 4.1945683e-05
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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