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Streaming Graph Partitioning: An Experimental Study

Summary: Taxonomy and experiments on online streaming graph partitioning using a unified Flink runtime. Findings: low-cut partitioners excel for communication-heavy workloads but incur higher costs; model-agnostic approaches favor locality with lower costs in data-parallel graphs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
11832
Venue
VLDB
Year
2018
Pagerank
8.9260308e-05
Overall Rank
2,221 | 84.77%
DOI
10.14778/3236187.3236208

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{abbas_vldb18,
        title = {{Streaming Graph Partitioning: An Experimental Study}},
        author = {Abbas, Zainab and Kalavri, Vasiliki and Carbone, Paris and Vlassov, Vladimir},
        journal = {PVLDB},
        series = {{VLDB} '18},
        volume = {11},
        number = {11},
        pages = {1590--1603},
        doi = {10.14778/3236187.3236208},
        url = {https://doi.org/10.14778/3236187.3236208},
        year = {2018}
}

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