A Platform for Scalable One-Pass Analytics using MapReduce
Summary: Proposes a one-pass analytics platform that replaces MapReduce's sort-merge bottlenecks with in-memory hashing. Introduces a frequency-key technique for large key-state spaces, achieving up to 1000× fewer spills and continuous results in a Hadoop prototype. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Boduo Li (University of Massachusetts Amherst)
- 2. Edward Mazur (University of Massachusetts Amherst)
- 3. Yanlei Diao (University of Massachusetts Amherst)
- 4. Andrew McGregor (University of Massachusetts Amherst)
- 5. Prashant Shenoy (University of Massachusetts Amherst)
BibTeX Citation
@inproceedings{li_sigmod11,
title = {{A Platform for Scalable One-Pass Analytics using MapReduce}},
author = {Li, Boduo and Mazur, Edward and Diao, Yanlei and McGregor, Andrew and Shenoy, Prashant},
series = {{SIGMOD} '11},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/1989323.1989426},
url = {https://dl.acm.org/doi/10.1145/1989323.1989426},
year = {2011}
}
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