Husky: Towards a More Efficient and Expressive Distributed Computing Framework
Summary: Husky is an open-source, in-memory distributed framework that seeks expressive APIs and high performance for data-parallel work. It bridges and re-implements frameworks inside Husky, enabling comparable or better performance with lower development cost. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Fan Yang
- 2. Jinfeng Li
- 3. James Cheng
Incoming Citations (Sorted by Pagerank)
Showing 12 of 12 citing papers.
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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 |
|---|---|---|---|---|
| 4 | Pregel: A System for Large-Scale Graph Processing | 2010 | SIGMOD | 0.0019005923 |
| 288 | Storm @Twitter | 2014 | SIGMOD | 0.00028939871 |
| 314 | MillWheel: Fault-Tolerant Stream Processing at Internet Scale | 2013 | VLDB | 0.00028084774 |
| 328 | An Architecture for Parallel Topic Models | 2010 | VLDB | 0.0002728514 |
| 1,171 | Blogel: A Block-Centric Framework for Distributed Computation on Real-World Graphs | 2014 | VLDB | 0.00013511313 |
| 1,800 | epiC: an Extensible and Scalable System for Processing Big Data | 2014 | VLDB | 0.00010512649 |
| 2,033 | NOMAD: Non-locking, stOchastic Multi-machine algorithm for Asynchronous and Decentralized matrix completion | 2014 | VLDB | 9.7172731e-05 |
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