Zuozhi Wang

Orcid: 0009-0003-4466-8096

According to our database1, Zuozhi Wang authored at least 15 papers between 2017 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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PhD thesis 
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Links

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Bibliography

2023
Udon: Efficient Debugging of User-Defined Functions in Big Data Systems with Line-by-Line Control.
Proc. ACM Manag. Data, December, 2023

Tempura: a general cost-based optimizer framework for incremental data processing (Journal Version).
VLDB J., November, 2023

Building a Collaborative Data Analytics System: Opportunities and Challenges.
Proc. VLDB Endow., 2023

2022
Optimizing Machine Learning Inference Queries with Correlative Proxy Models.
Proc. VLDB Endow., 2022

Demonstration of Accelerating Machine Learning Inference Queries with Correlative Proxy Models.
Proc. VLDB Endow., 2022

Fries: Fast and Consistent Runtime Reconfiguration in Dataflow Systems with Transactional Guarantees.
Proc. VLDB Endow., 2022

Demonstration of Collaborative and Interactive Workflow-Based Data Analytics in Texera.
Proc. VLDB Endow., 2022

Fries: Fast and Consistent Runtime Reconfiguration in Dataflow Systems with Transactional Guarantees (Extended Version).
CoRR, 2022

Reshape: Adaptive Result-aware Skew Handling for Exploratory Analysis on Big Data.
CoRR, 2022

2020
Tempura: A General Cost-Based Optimizer Framework for Incremental Data Processing.
Proc. VLDB Endow., 2020

Demonstration of Interactive Runtime Debugging of Distributed Dataflows in Texera.
Proc. VLDB Endow., 2020

Amber: A Debuggable Dataflow System Based on the Actor Model.
Proc. VLDB Endow., 2020

Tempura: A General Cost Based Optimizer Framework for Incremental Data Processing (Extended Version).
CoRR, 2020

Grosbeak: A Data Warehouse Supporting Resource-Aware Incremental Computing.
Proceedings of the 2020 International Conference on Management of Data, 2020

2017
A Demonstration of TextDB: Declarative and Scalable Text Analytics on Large Data Sets.
Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017


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