Triangle Enumeration on Massive Graphs using AWS Lambda Functions




Yu, Tengkai

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Triangle enumeration is a fundamental task in graph data analysis with many applications. Recently, Park et al. proposed a distributed algorithm, PTE (Pre-partitioned Triangle Enumeration), that, unlike previous works, scales well using multiple high end machines and can handle very large real-world networks. This work presents a serverless implementation of the PTE algorithm using the AWS Lambda platform. Our experiments take advantage of the high concurrency of the Lambda instances to compete with the expensive server-based experiments of Park et al. Our analysis shows the trade-off between the time and cost of triangle enumeration and the numbers of tasks generated by the distributed algorithm. Our results reveal the importance of using a higher number of tasks in order to improve the efficiency of PTE. Such an analysis can only be performed using a large number of workers which is indeed possible using AWS Lambda but not easy to achieve using few servers as in the case of Park et al.



triangle enumeration, massive graphs, distributed system, AWS Lambda