MacroBase: Prioritizing Attention in Fast Data
Summary: MacroBase prioritizes end-user attention in high-volume fast data streams and acts as a search engine for fast data. It delivers accurate, scalable classifications with explanations over groups, powered by a reservoir sampler and heavy-hitters sketch that reach up to 2M events/sec per core and see deployment in telematics. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Peter Bailis
- 2. Edward Gan
- 3. Samuel Madden
- 4. Deepak Narayanan
- 5. Kexin Rong
- 6. Sahaana Suri
Incoming Citations (Sorted by Pagerank)
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Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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| 11,756 | Prioritizing Attention in Fast Data: Principles and Promise | 2017 | CIDR | 4.1945683e-05 |