Cuckoo Heavy Keeper and the balancing act of maintaining heavy hitters in stream processing
Summary: Introduces Cuckoo Heavy Keeper (CHK), an inverted sketch distinguishing frequent vs infrequent items to unlock new throughput/memory/accuracy tradeoffs. Its parallel framework yields 1.7–5.7× throughput and up to 10^4× accuracy gains with near-linear scale-up. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 7 of 7 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 402 | Mergeable Summaries | 2012 | PODS | 0.00024196343 |
| 472 | Bottom-Up Computation of Sparse and Iceberg CUBEs | 1999 | SIGMOD | 0.00022346384 |
| 597 | Computing Iceberg Queries Efficiently | 1998 | VLDB | 0.00019475592 |
| 835 | Finding Frequent Items in Data Streams | 2008 | VLDB | 0.00016109621 |
| 1,584 | Augmented Sketch: Faster and More Accurate Stream Processing | 2016 | SIGMOD | 0.00011255801 |
| 3,486 | Holistic UDAFs at Streaming Speeds | 2004 | SIGMOD | 7.0502199e-05 |
| 4,618 | Approximate Frequency Counts over Data Streams | 2012 | VLDB | 6.0446717e-05 |
Previous
Page 1 / 1
Next