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Computer Science > Databases

arXiv:2103.14294 (cs)
[Submitted on 26 Mar 2021 (v1), last revised 29 Mar 2021 (this version, v2)]

Title:HUGE: An Efficient and Scalable Subgraph Enumeration System

Authors:Zhengyi Yang, Longbin Lai, Xuemin Lin, Kongzhang Hao, Wenjie Zhang
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Abstract:Subgraph enumeration is a fundamental problem in graph analytics, which aims to find all instances of a given query graph on a large data graph. In this paper, we propose a system called HUGE to efficiently process subgraph enumeration at scale in the distributed context. HUGE features 1) an optimiser to compute an advanced execution plan without the constraints of existing works; 2) a hybrid communication layer that supports both pushing and pulling communication; 3) a novel two-stage execution mode with a lock-free and zero-copy cache design, 4) a BFS/DFS-adaptive scheduler to bound memory consumption, and 5) two-layer intra- and inter-machine load balancing. HUGE is generic such that all existing distributed subgraph enumeration algorithms can be plugged in to enjoy automatic speed up and bounded-memory execution.
Subjects: Databases (cs.DB)
Cite as: arXiv:2103.14294 [cs.DB]
  (or arXiv:2103.14294v2 [cs.DB] for this version)
  https://doi.org/10.48550/arXiv.2103.14294

Submission history

From: Zhengyi Yang [view email]
[v1] Fri, 26 Mar 2021 06:57:23 UTC (1,455 KB)
[v2] Mon, 29 Mar 2021 11:29:08 UTC (1,435 KB)
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Zhengyi Yang
Longbin Lai
Xuemin Lin
Kongzhang Hao
Wenjie Zhang
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