Stingy Sketch: A Sketch Framework for Accurate and Fast Frequency Estimation
Haoyu Li, Qizhi Chen, Yixin Zhang, Tong Yang, Bin Cui
摘要
Recording the frequency of items in highly skewed data streams is a fundamental and hot problem in recent years. The literature demonstrates that sketch is the most promising solution. The typical metrics to measure a sketch are accuracy and speed, but existing sketches make only trade-offs between the two dimensions. Our proposed solution is a new sketch framework called Stingy sketch with two key techniques: Bit-pinching Counter Tree ( BCTree ) and Prophet Queue ( PQueue ) which optimizes both the accuracy and speed. The key idea of BCTree is to split a large fixed-size counter into many small nodes of a tree structure, and to use a precise encoding to perform carry-in operations with low processing overhead. The key idea of PQueue is to use pipelined prefetch technique to make most memory accesses happen in L2 cache without losing precision. Importantly, the two techniques are cooperative so that Stingy sketch can improve accuracy and speed simultaneously. Extensive experimental results show that Stingy sketch is up to 50% more accurate than the SOTA of accuracy-oriented sketches and is up to 33% faster than the SOTA of speed-oriented sketches.
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引用它的顶会 Paper16
- BitMatcher: Bit-level Counter Adjustment for SketchesQilong Shi, Chengjun Jia, Wenjun Li, Zaoxing Liu 等ICDE 2024 · 被引用 22 次
- Communication Efficient Distributed Training with Distributed LionBo Liu, Lemeng Wu, Lizhang Chen, Kaizhao Liang 等NeurIPS 2024 · 被引用 21 次
- JoinSketch: A Sketch Algorithm for Accurate and Unbiased Inner-Product EstimationFeiyu Wang, Qizhi Chen, Yuanpeng Li, Tong Yang 等SIGMOD 2023 · 被引用 20 次
- NeoMem: Hardware/Software Co-Design for CXL-Native Memory TieringZhe Zhou, Yiqi Chen, Tao Zhang, Yang Wang 等MICRO 2024 · 被引用 17 次
- Local Differentially Private Heavy Hitter Detection in Data Streams with Bounded MemoryXiaochen Li, Weiran Liu, Jian Lou, Yuan Hong 等SIGMOD 2024 · 被引用 13 次
它引用的顶会 Paper9
- WavingSketch: An Unbiased and Generic Sketch for Finding Top-k Items in Data StreamsJizhou Li, Zikun Li, Yifei Xu, Shiqi Jiang 等KDD 2020 · 被引用 96 次
- Correlation Sketches for Approximate Join-Correlation QueriesAécio S. R. Santos, Aline Bessa, Fernando Chirigati, Christopher Musco 等SIGMOD 2021 · 被引用 45 次
- SALSA: Self-Adjusting Lean Streaming AnalyticsRan Ben Basat, Gil Einziger, Michael Mitzenmacher, Shay VargaftikICDE 2021 · 被引用 45 次
- COMPASS: Online Sketch-based Query Optimization for In-Memory DatabasesYesdaulet Izenov, Asoke Datta, Florin Rusu, Jun Hyung ShinSIGMOD 2021 · 被引用 34 次
- Building Fast and Compact Sketches for Approximately Multi-Set Multi-Membership QueryingRundong Li, Pinghui Wang, Jiongli Zhu, Junzhou Zhao 等SIGMOD 2021 · 被引用 20 次
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