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Streaming graph partitioning
2018
Proceedings of the VLDB Endowment
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Prior studies have compared offline graph partitioning techniques across different systems. ...
Graph partitioning is an essential yet challenging task for massive graph analysis in distributed computing. ...
Among existing methods, we study streaming graph partitioning algorithms. ...
doi:10.14778/3236187.3236208
fatcat:ehsvpqdykbc35odmga2rcyvlfq
Buffered Streaming Graph Partitioning
[article]
2021
arXiv
pre-print
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We make a first step to close this gap by presenting an algorithm that computes significantly improved partitions of huge graphs using a single machine with little memory in streaming setting. ...
On the one hand, there are streaming algorithms that have been adopted to partition massive graph data on small machines. ...
Awadelkarim and Ugander [1] studied the effect of node ordering for streaming graph partitioning. ...
arXiv:2102.09384v2
fatcat:a2nfe5sh5jdotgp7cpardlb3j4
Streaming Balanced Graph Partitioning for Random Graphs
[article]
2012
arXiv
pre-print
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We model the problem of loading a graph onto a distributed cluster as computing an approximately balanced k-partitioning of a graph in a streaming fashion with only one pass over the data. ...
This matches the experimental results in [25]. ...
We finish with an experimental evaluation of the bounds attained by the theorems.
RELATED WORK Many variants of graph partitioning have been studied since the earliest days of Computer Science. ...
arXiv:1212.1121v1
fatcat:23q4x5udffexrbjn4yxcseg6oe
Streaming Graph Partitioning in the Planted Partition Model
[article]
2014
arXiv
pre-print
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In this work we contribute to the recent research line of streaming graph partitioning stantonstreaming,stanton,fennel which computes an approximately balanced k-partitioning of the vertex set of a graph ...
using a single pass over the graph stream using degree-based criteria. ...
Planted partition model. Jerrum and Sorkin [Jer98] studied the planted bisection model, a random undirected graph with an even number of vertices. ...
arXiv:1406.7570v2
fatcat:imjhgg72xzbyhoi3l2vmp2uz3q
Streaming graph partitioning for large distributed graphs
2012
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '12
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Observing that the graph has to be loaded into the cluster, we ask if the partitioning can be done at the same time with a lightweight streaming algorithm. ...
We show on a large collection of graph datasets that our heuristics are a significant improvement, with the best obtaining an average gain of 76%. ...
Contributions We provide a rigorous, empirical study of a set of natural heuristics for streaming balanced graph partitioning. ...
doi:10.1145/2339530.2339722
dblp:conf/kdd/StantonK12
fatcat:nqaphisol5bozfusje4zxuqdze
Streaming Balanced Graph Partitioning Algorithms for Random Graphs
[chapter]
2013
Proceedings of the Twenty-Fifth Annual ACM-SIAM Symposium on Discrete Algorithms
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This shift motivates the study of streaming algorithms. One type of big data is graphs. ...
The communication problem is a major motivation for studying graph partitioning. ...
Conclusions and Future Work We studied the problem of streaming balanced graph partitioning. ...
doi:10.1137/1.9781611973402.95
dblp:conf/soda/Stanton14
fatcat:52pp4ouqxvhixoussfjqcslcpe
Streaming Graph Partitioning in the Planted Partition Model
2015
Proceedings of the 2015 ACM on Conference on Online Social Networks - COSN '15
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In this work we contribute to the recent research line of streaming graph partitioning [30, 31, 34] which computes an approximately balanced k-partitioning of the vertex set of a graph using a single pass ...
over the graph stream using degree-based criteria. ...
EXPERIMENTAL RESULTS
Experimental setup We refer to our method as EGyPT (Efficient which stands for Graph ParTitioning). ...
doi:10.1145/2817946.2817950
dblp:conf/cosn/Tsourakakis15
fatcat:y3m4zokqxbfd5chq3dgwd66xr4
Heterogeneous Environment Aware Streaming Graph Partitioning
2015
IEEE Transactions on Knowledge and Data Engineering
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With the increasing availability of graph data and widely adopted cloud computing paradigm, graph partitioning has become an efficient pre-processing technique to balance the computing workload and cope ...
Since the cost of partitioning the entire graph is strictly prohibitive, there are some recent tentative works towards streaming graph partitioning which run faster, are easily parallelized, and can be ...
In Section 4, we present heterogeneous environment modeling and our graph partitioning approach. Section 5 lists the experimental study. And finally we conclude this work in Section 6. ...
doi:10.1109/tkde.2014.2377743
fatcat:ic5md2ju2rfydmbj5vvtptsumm
Boosting Vertex-Cut Partitioning for Streaming Graphs
2016
2016 IEEE International Congress on Big Data (BigData Congress)
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We introduce an efficient platform for boosting streaming graph partitioning algorithms. Our solution, called HoVerCut, is Horizontally and Vertically scalable. ...
While the algorithms for streaming graph partitioning are proved promising, they fall short of creating timely partitions when applied on large graphs. ...
INTRODUCTION Graph partitioning is an NP-Complete problem with a long history in graph theory [1] , [2] . ...
doi:10.1109/bigdatacongress.2016.10
dblp:conf/bigdata/SajjadPRVH16
fatcat:hqoc7zi755cifl66qwz3sauina
S-PowerGraph: Streaming Graph Partitioning for Natural Graphs by Vertex-Cut
[article]
2015
arXiv
pre-print
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Hence, streaming graph partitioning (SGP) methods, which can partition graphs in an online way, have recently attracted great attention in distributed computation. ...
In distributed computation, graph partitioning (GP) methods assign the vertices or edges of a graph to different machines in a balanced way so that some distributed algorithms can be adapted for. ...
CONCLUSION In this paper we have studied streaming graph partitioning by vertex-cut. ...
arXiv:1511.02586v1
fatcat:ahsgyfktmzh63ivzn6o7nggkee
Online and on-demand partitioning of streaming graphs
2015
2015 IEEE International Conference on Big Data (Big Data)
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In this work, we present a framework that enables partitioning of evolving graphs whose elements (nodes and edges) are streamed in an arbitrary order. ...
The partitioning algorithm we present manages to create partitions from streaming graphs with low memory usage, but can also adapt partitions overtime based on different application needs such as minimizing ...
RELATED WORK Graph partitioning is a well studied NP-hard problem [3] . ...
doi:10.1109/bigdata.2015.7363735
dblp:conf/bigdataconf/FilippidouK15
fatcat:cu77nosc45dq7k4di6r5yr3qoa
Edge Property Based Stream Order Reduce the Performance of Stream Edge Graph Partition
2019
Journal of Physics, Conference Series
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stream order on stream edge graph partition algorithms. ...
the quality of stream edge graph partition. ...
In this study,we propose two stream edge order models and extensively study the performance of stream edge graph partition with stream order. ...
doi:10.1088/1742-6596/1395/1/012010
fatcat:m3iyhpulvfhd3je2g7ljk6w5v4
COLA: Optimizing Stream Processing Applications via Graph Partitioning
[chapter]
2009
Lecture Notes in Computer Science
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Our algorithm computes a hierarchical partitioning of the operator graph based on a minimum-ratio cut subroutine. ...
We experimentally compare our algorithm with several other reasonable alternative schemes, highlighting the effectiveness of our approach. ...
An important property of validity is that it will persist as we continue the graph partitioning process. ...
doi:10.1007/978-3-642-10445-9_16
fatcat:zofw4apffbfi5mecql4t7mx4gu
ADWISE: Adaptive Window-based Streaming Edge Partitioning for High-Speed Graph Processing
[article]
2018
arXiv
pre-print
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Existing graph partitioning algorithms minimize partitioning latency by assigning individual graph edges to partitions in a streaming manner --- at the cost of reduced partitioning quality. ...
In this paper, we propose ADWISE, a novel window-based streaming partitioning algorithm that increases the partitioning quality by always choosing the best edge from a set of edges for assignment to a ...
However, as a benchmark we selected the best partitioning algorithm for many graphs, i.e., HDRF, based on an experimental comparison of a wide range of single-edge streaming partitioning algorithms [7 ...
arXiv:1712.08367v2
fatcat:bfrsqrayejfaxfxahpypy7i6iy
Workload scheduling in distributed stream processors using graph partitioning
2015
2015 IEEE International Conference on Big Data (Big Data)
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We also found that the performance advantage increases with message size, providing an important insight for stream-processing approaches based on micro-batching. ...
We also found that the performance advantage increases with message size, providing an important insight for stream-processing approaches based on micro-batching. ...
In this study, we present a workload scheduler for taskbased distributed stream processing systems that is based on a graph partitioning algorithm. ...
doi:10.1109/bigdata.2015.7363749
dblp:conf/bigdataconf/FischerB15
fatcat:o2ce7c6rovhlbetbypfrleg2ty
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