Abstract
In this paper, we study the problem of choosing among partitioning strategies in distributed graph processing systems. To this end, we evaluate and characterize both the performance and resource usage of different partitioning strategies under various popular distributed graph processing systems, applications, input graphs, and execution environments. Through our experiments, we found that no single partitioning strategy is the best fit for all situations, and that the choice of partitioning strategy has a significant effect on resource usage and application run-time. Our experiments demonstrate that the choice of partitioning strategy depends on (1) the degree distribution of input graph, (2) the type and duration of the application, and (3) the cluster size. Based on our results, we present rules of thumb to help users pick the best partitioning strategy for their particular use cases. We present results from each system, as well as from all partitioning strategies implemented in one common system (PowerLyra).
| Original language | English (US) |
|---|---|
| Pages (from-to) | 493-504 |
| Number of pages | 12 |
| Journal | Proceedings of the VLDB Endowment |
| Volume | 10 |
| Issue number | 5 |
| DOIs | |
| State | Published - Jan 1 2016 |
| Event | 43rd International Conference on Very Large Data Bases, VLDB 2017 - Munich, Germany Duration: Aug 28 2017 → Sep 1 2017 |
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ASJC Scopus subject areas
- Computer Science (miscellaneous)
- Computer Science(all)
Cite this
An experimental comparison of partitioning strategies in distributed graph processing. / Verma, Shiv; Leslie, Luke M.; Shin, Yosub; Gupta, Indranil.
In: Proceedings of the VLDB Endowment, Vol. 10, No. 5, 01.01.2016, p. 493-504.Research output: Contribution to journal › Conference article
}
TY - JOUR
T1 - An experimental comparison of partitioning strategies in distributed graph processing
AU - Verma, Shiv
AU - Leslie, Luke M.
AU - Shin, Yosub
AU - Gupta, Indranil
PY - 2016/1/1
Y1 - 2016/1/1
N2 - In this paper, we study the problem of choosing among partitioning strategies in distributed graph processing systems. To this end, we evaluate and characterize both the performance and resource usage of different partitioning strategies under various popular distributed graph processing systems, applications, input graphs, and execution environments. Through our experiments, we found that no single partitioning strategy is the best fit for all situations, and that the choice of partitioning strategy has a significant effect on resource usage and application run-time. Our experiments demonstrate that the choice of partitioning strategy depends on (1) the degree distribution of input graph, (2) the type and duration of the application, and (3) the cluster size. Based on our results, we present rules of thumb to help users pick the best partitioning strategy for their particular use cases. We present results from each system, as well as from all partitioning strategies implemented in one common system (PowerLyra).
AB - In this paper, we study the problem of choosing among partitioning strategies in distributed graph processing systems. To this end, we evaluate and characterize both the performance and resource usage of different partitioning strategies under various popular distributed graph processing systems, applications, input graphs, and execution environments. Through our experiments, we found that no single partitioning strategy is the best fit for all situations, and that the choice of partitioning strategy has a significant effect on resource usage and application run-time. Our experiments demonstrate that the choice of partitioning strategy depends on (1) the degree distribution of input graph, (2) the type and duration of the application, and (3) the cluster size. Based on our results, we present rules of thumb to help users pick the best partitioning strategy for their particular use cases. We present results from each system, as well as from all partitioning strategies implemented in one common system (PowerLyra).
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UR - http://www.scopus.com/inward/citedby.url?scp=85020390625&partnerID=8YFLogxK
U2 - 10.14778/3055540.3055543
DO - 10.14778/3055540.3055543
M3 - Conference article
AN - SCOPUS:85020390625
VL - 10
SP - 493
EP - 504
JO - Proceedings of the VLDB Endowment
JF - Proceedings of the VLDB Endowment
SN - 2150-8097
IS - 5
ER -