Differentially Private Stream Processing at Scale*
Summary: Presents DP-SQLP, the first production-scale differentially private stream aggregation system implemented atop Spanner/F1 with a Spark-like streaming runtime and deployed for Google Shopping/Trends. Key ideas: a user-level DP key-selection for unbounded/billion-key domains with preemptive non-enumerative execution plus continual-observation DP histograms, yielding ≥16× error reduction over baselines. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Bing Zhang
- 2. Vadym Doroshenko
- 3. Peter Kairouz
- 4. Thomas Steinke
- 5. Abhradeep Thakurta
- 6. Ziyin Ma
- 7. Eidan Cohen
- 8. Himani Apte
- 9. Jodi Spacek
Incoming Citations (Sorted by Pagerank)
Showing 1 of 1 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 5,885 | Continual Observation of Joins under Differential Privacy | 2024 | SIGMOD | 5.2880878e-05 |
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Outgoing Citations (Sorted by Pagerank)
Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 432 | Flexible Time Management in Data Stream Systems | 2004 | PODS | 0.00023368424 |
| 538 | The Dataflow Model: A Practical Approach to Balancing Correctness, Latency, and Cost in Massive-Scale, Unbounded, Out-of-Order Data Processing | 2015 | VLDB | 0.00020678804 |
| 3,355 | F1 Query: Declarative Querying at Scale | 2018 | VLDB | 7.1829142e-05 |
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