activity
20122023
most citedFLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation

16 citations · 45 across the 8 of their papers we have counts for

collaborators

8 papers

cs.DC2023★ 5 cited

Quiver: Supporting GPUs for Low-Latency, High-Throughput GNN Serving with Workload Awareness

Zeyuan Tan, Xiulong Yuan, Congjie He +7

Systems for serving inference requests on graph neural networks (GNN) must combine low latency with high throughout, but they face irregular computation due to skew in the number o…

cs.DB2022★ 12 cited

Fine-Grained Modeling and Optimization for Intelligent Resource Management in Big Data Processing

Chenghao Lyu, Qi Fan, Fei Song +8

Big data processing at the production scale presents a highly complex environment for resource optimization (RO), a problem crucial for meeting performance goals and budgetary cons…

cs.DB2022

Banyan: A Scoped Dataflow Engine for Graph Query Service

Li Su, Xiaoming Qin, Zichao Zhang +6

Graph query services (GQS) are widely used today to interactively answer graph traversal queries on large-scale graph data. Existing graph query engines focus largely on optimizing…

cs.DB2021★ 1 cited

REPOSE: Distributed Top-k Trajectory Similarity Search with Local Reference Point Tries

Bolong Zheng, Lianggui Weng, Xi Zhao +3

Trajectory similarity computation is a fundamental component in a variety of real-world applications, such as ridesharing, road planning, and transportation optimization. Recent ad…

cs.DB2020★ 16 cited

FLAT: Fast, Lightweight and Accurate Method for Cardinality Estimation

Rong Zhu, Ziniu Wu, Yuxing Han +5

Query optimizers rely on accurate cardinality estimation (CardEst) to produce good execution plans. The core problem of CardEst is how to model the rich joint distribution of attri…

cs.AR2020★ 11 cited

MicroRec: Efficient Recommendation Inference by Hardware and Data Structure Solutions

Wenqi Jiang, Zhenhao He, Shuai Zhang +9

Deep neural networks are widely used in personalized recommendation systems. Unlike regular DNN inference workloads, recommendation inference is memory-bound due to the many random…

cs.DB2020

Tempura: A General Cost Based Optimizer Framework for Incremental Data Processing (Extended Version)

Zuozhi Wang, Kai Zeng, Botong Huang +10

Incremental processing is widely-adopted in many applications, ranging from incremental view maintenance, stream computing, to recently emerging progressive data warehouse and inte…

cs.DB2012

Early Accurate Results for Advanced Analytics on MapReduce

Nikolay Laptev, Kai Zeng, Carlo Zaniolo

Approximate results based on samples often provide the only way in which advanced analytical applications on very massive data sets can satisfy their time and resource constraints.…