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Hybrid Edge Partitioner: Partitioning Large Power-Law Graphs under Memory Constraints

Summary: Hybrid Edge Partitioner (HEP) partitions large power-law graphs under memory constraints by splitting edges into two subsets: in-memory NE++ partitioning and streaming partitioning. This tunable memory-overhead approach delivers high partition quality and accelerates Spark/GraphX workloads vs. pure in-memory or streaming methods. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
6190
Venue
SIGMOD
Year
2021
Pagerank
5.2595857e-05
Overall Rank
5,949 | 58.62%
DOI
10.1145/3448016.3457300

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