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Towards Effective Partition Management for Large Graphs

Summary: Proposes Sedge, a self-evolving distributed graph manager with primary-plus-dynamic-secondary partitions to cut cross-machine traffic. Uses linear/sublinear workload analytics to adapt partitions in real time to locality-prone queries (BFS, random walk, SPARQL), boosting response time and throughput on commodity clusters. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
4612
Venue
SIGMOD
Year
2012
Pagerank
9.724402e-05
Overall Rank
1,803 | 87.64%
DOI
10.1145/2213836.2213895

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{yang_sigmod12,
        title = {{Towards Effective Partition Management for Large Graphs}},
        author = {Yang, Shengqi and Yan, Xifeng and Zong, Bo and Khan, Arijit},
        series = {{SIGMOD} '12},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2213836.2213895},
        url = {https://dl.acm.org/doi/10.1145/2213836.2213895},
        year = {2012}
}

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