├── .gitignore
├── .project
├── LICENSE
├── README.md
├── build.sbt
├── project
├── plugins.sbt
├── project
│ └── target
│ │ └── config-classes
│ │ ├── $b3d102560a63b15ab385.cache
│ │ └── $bc6d6b0c9d8db494e759.cache
└── target
│ ├── config-classes
│ ├── $06ba21d58b2b689ca77f.cache
│ ├── $0f13e50b2717a7c7d5d3.cache
│ ├── $1ad477331c05baea072a.cache
│ ├── $1b51683a36d7ea63985c.cache
│ ├── $2da92b15db480aede577.cache
│ ├── $3336d4fd058011bcd6d0.cache
│ ├── $8171d171761c9aab4896.cache
│ ├── $82a7ccabc69b86382cc6.cache
│ ├── $8b48e77a94c99a225a63.cache
│ ├── $9dddc03dcd2da481bec2.cache
│ ├── $a78697fc1714f8c8f33b.cache
│ ├── $ae4d651a65c05a1b1fca.cache
│ ├── $b9e8fc9ef9d16d4e7d4b.cache
│ ├── $ca20669757765057b05f.cache
│ ├── $db28efac0bdc63c5a993.cache
│ ├── $e084bbb9b3c78e4f0508.cache
│ └── $f693f8f2fa5a7035bdda.cache
│ ├── resolution-cache
│ ├── default
│ │ ├── spark-beetweenness-build
│ │ │ └── scala_2.10
│ │ │ │ └── sbt_0.13
│ │ │ │ └── 0.1-SNAPSHOT
│ │ │ │ ├── resolved.xml.properties
│ │ │ │ └── resolved.xml.xml
│ │ └── spark-betweenness-build
│ │ │ └── scala_2.10
│ │ │ └── sbt_0.13
│ │ │ └── 0.1-SNAPSHOT
│ │ │ ├── resolved.xml.properties
│ │ │ └── resolved.xml.xml
│ └── reports
│ │ ├── default-spark-beetweenness-build-compile-internal.xml
│ │ ├── default-spark-beetweenness-build-compile.xml
│ │ ├── default-spark-beetweenness-build-docs.xml
│ │ ├── default-spark-beetweenness-build-optional.xml
│ │ ├── default-spark-beetweenness-build-plugin.xml
│ │ ├── default-spark-beetweenness-build-pom.xml
│ │ ├── default-spark-beetweenness-build-provided.xml
│ │ ├── default-spark-beetweenness-build-runtime-internal.xml
│ │ ├── default-spark-beetweenness-build-runtime.xml
│ │ ├── default-spark-beetweenness-build-scala-tool.xml
│ │ ├── default-spark-beetweenness-build-sources.xml
│ │ ├── default-spark-beetweenness-build-test-internal.xml
│ │ ├── default-spark-beetweenness-build-test.xml
│ │ ├── default-spark-betweenness-build-compile-internal.xml
│ │ ├── default-spark-betweenness-build-compile.xml
│ │ ├── default-spark-betweenness-build-docs.xml
│ │ ├── default-spark-betweenness-build-optional.xml
│ │ ├── default-spark-betweenness-build-plugin.xml
│ │ ├── default-spark-betweenness-build-pom.xml
│ │ ├── default-spark-betweenness-build-provided.xml
│ │ ├── default-spark-betweenness-build-runtime-internal.xml
│ │ ├── default-spark-betweenness-build-runtime.xml
│ │ ├── default-spark-betweenness-build-scala-tool.xml
│ │ ├── default-spark-betweenness-build-sources.xml
│ │ ├── default-spark-betweenness-build-test-internal.xml
│ │ ├── default-spark-betweenness-build-test.xml
│ │ ├── ivy-report.css
│ │ └── ivy-report.xsl
│ └── streams
│ ├── $global
│ ├── $global
│ │ └── $global
│ │ │ └── streams
│ │ │ └── out
│ ├── dependencyPositions
│ │ └── $global
│ │ │ └── streams
│ │ │ └── update_cache_2.10
│ │ │ ├── input_dsp
│ │ │ └── output_dsp
│ ├── ivyConfiguration
│ │ └── $global
│ │ │ └── streams
│ │ │ └── out
│ ├── ivySbt
│ │ └── $global
│ │ │ └── streams
│ │ │ └── out
│ ├── projectDescriptors
│ │ └── $global
│ │ │ └── streams
│ │ │ └── out
│ └── update
│ │ └── $global
│ │ └── streams
│ │ ├── out
│ │ └── update_cache_2.10
│ │ ├── inputs
│ │ └── output
│ ├── compile
│ ├── $global
│ │ └── $global
│ │ │ └── discoveredMainClasses
│ │ │ └── data
│ ├── compile
│ │ └── $global
│ │ │ └── streams
│ │ │ └── out
│ ├── compileIncremental
│ │ └── $global
│ │ │ └── streams
│ │ │ ├── export
│ │ │ └── out
│ ├── copyResources
│ │ └── $global
│ │ │ └── streams
│ │ │ ├── copy-resources
│ │ │ └── out
│ ├── dependencyClasspath
│ │ └── $global
│ │ │ └── streams
│ │ │ └── export
│ ├── exportedProducts
│ │ └── $global
│ │ │ └── streams
│ │ │ └── export
│ ├── externalDependencyClasspath
│ │ └── $global
│ │ │ └── streams
│ │ │ └── export
│ ├── internalDependencyClasspath
│ │ └── $global
│ │ │ └── streams
│ │ │ └── export
│ ├── managedClasspath
│ │ └── $global
│ │ │ └── streams
│ │ │ └── export
│ ├── unmanagedClasspath
│ │ └── $global
│ │ │ └── streams
│ │ │ └── export
│ └── unmanagedJars
│ │ └── $global
│ │ └── streams
│ │ └── export
│ └── runtime
│ ├── dependencyClasspath
│ └── $global
│ │ └── streams
│ │ └── export
│ ├── exportedProducts
│ └── $global
│ │ └── streams
│ │ └── export
│ ├── externalDependencyClasspath
│ └── $global
│ │ └── streams
│ │ └── export
│ ├── fullClasspath
│ └── $global
│ │ └── streams
│ │ └── export
│ ├── internalDependencyClasspath
│ └── $global
│ │ └── streams
│ │ └── export
│ ├── managedClasspath
│ └── $global
│ │ └── streams
│ │ └── export
│ ├── unmanagedClasspath
│ └── $global
│ │ └── streams
│ │ └── export
│ └── unmanagedJars
│ └── $global
│ └── streams
│ └── export
├── python
└── kBC.py
└── src
├── functional-test
└── scala
│ └── com
│ └── centrality
│ └── kBC
│ └── LocalRunner.scala
├── main
└── scala
│ └── com
│ └── centrality
│ └── kBC
│ ├── KBetweenness.scala
│ └── kBCDriver.scala
└── test
└── scala
└── com
└── centrality
└── kBC
└── KBetweennessTest.scala
/.gitignore:
--------------------------------------------------------------------------------
1 | .cache
2 | target/
3 |
--------------------------------------------------------------------------------
/.project:
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1 |
2 |
3 | spark-betweenness
4 |
5 |
6 |
7 |
8 |
9 | org.scala-ide.sdt.core.scalabuilder
10 |
11 |
12 |
13 |
14 |
15 | org.scala-ide.sdt.core.scalanature
16 | org.eclipse.jdt.core.javanature
17 |
18 |
19 |
--------------------------------------------------------------------------------
/LICENSE:
--------------------------------------------------------------------------------
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/README.md:
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1 | # spark-betweenness
2 |
3 | k Betweenness Centrality (kBC) algorithm for Spark using GraphX
4 |
5 | ## Details
6 |
7 | Computing k Betweenness Centrality (kBC) on arbitraty graphs using GraphX.
8 |
9 | ### Steps
10 |
11 | 1. Using Pregel API to create small k-graphlets
12 | 2. Local betweenness contribution calculation for each vertex to other vertices using Brandes algorithm for calculating BC.
13 | 3. Aggregating results (reduce) from all vertices to conclude each vertex betweenness score.
14 | 4. Assemble a graph similar to the original graph that contains the kBC score for each node.
15 |
16 | ### Notes
17 |
18 | The method above illustrated that spark-betweenness works best for graphs with a large diameter.
19 | We actually hold all k-graphlets in memory for Brandes calculation as they are the core of parallelizing this algorithm.
20 | Therefore, we manage to compute kBC on millions of nodes and vertices with large diameter graphs (such as road networks), but fail miserabely to do so on small diameter graphs (such as social networks).
21 |
22 | ## Requirements
23 |
24 | Spark 1.5+.
25 |
26 | Scala 2.10.
27 |
28 | ## Linking
29 |
30 | You can link against this library (for Spark 1.5+) in your program at the following coordinates:
31 |
32 | Using SBT:
33 |
34 | ```
35 | libraryDependencies += "com.centrality" %% "spark-betweenness" % "1.0.0"
36 | ```
37 |
38 | This library can also be added to Spark jobs launched through `spark-shell` or `spark-submit` by using the `--packages` command line option.
39 | For example, to include it when starting the spark shell:
40 |
41 | ```
42 | $ bin/spark-shell --packages com.centrality:spark-betweenness_2.10:1.0.0
43 | ```
44 |
45 | Unlike using `--jars`, using `--packages` ensures that this library and its dependencies will be added to the classpath.
46 | The `--packages` argument can also be used with `bin/spark-submit`.
47 |
48 | This library is cross-published for Scala 2.10, so 2.11 users should replace 2.10 with 2.11 in the commands listed above.
49 |
50 | ## Usage
51 |
52 | ### Scala API
53 |
54 | ```scala
55 | // import needed for the .avro method to be added
56 | import com.centrality.kBC.KBetweenness
57 |
58 | val graph = Graph(users, relationships, defaultUser)
59 |
60 | // Run kBC to get result graph
61 | val kBCGraph =
62 | KBetweenness.run(graph, k)
63 | ```
64 |
65 | ### Running kBC from command line
66 |
67 | You can run kBC directly form command line using spark-submit.
68 |
69 | Parameters for kBC :
70 | - **k** size of k-graphlets for kBC
71 | - **numEdgePartitions** number of partitions when loading graph, recommended ( **num-executors** * 2 ) - 6
72 | - **inputDir** HDFS input dir location
73 | - **outputDir** HDFS output dir location
74 | - **inputFileName** input file name containing edge_list for graph (as stated in GraphX GraphLoader.edgeListFile)
75 |
76 | ```bash
77 | /usr/lib/spark/bin/spark-submit --class com.centrality.kBC.kBCDriver --executor-cores 1 --executor-memory 10000M --master yarn-cluster --num-executors 28 --conf spark.driver.memory=10000m --conf spark.driver.extraJavaOptions="-Xms4000m -Xmx10000m" --conf spark.executor.extraJavaOptions="-verbose:gc -XX:+PrintGCDetails -XX:+PrintGCTimeStamps" --conf spark.kryo.registrationRequired=false --conf spark.serializer=org.apache.spark.serializer.KryoSerializer --conf spark.yarn.maxAppAttempts=1 --conf spark.task.maxFailures=10 /tmp/kbc_2.10-1.0.jar 4 50 /tmp/input/ /tmp/output/ loc-brightkite_edges.txt
78 | ```
79 |
80 | When using kBC this way, it is highly recommended to tune these parameters for your own benefit :
81 |
82 | - **executor-cores** recommended to 1
83 | - **executor-memory**
84 | - **num-executors** as far as memory of the cluster grants, given each executor needs X **executor-memory**
85 | - **spark.driver.extraJavaOptions** tune memory requirements
86 | - **spark.executor.extraJavaOptions** tune GC if needed
87 | - **spark.task.maxFailures** recommended larger than 1, tasks fail for out of memory sometimes for large graphs if tuning isn't right
88 |
89 | ## Building From Source
90 | This library is built with [SBT](http://www.scala-sbt.org/0.13/docs/Command-Line-Reference.html),
91 | which is automatically downloaded by the included shell script. To build a JAR file simply run
92 | `sbt package` from the project root.
93 |
94 | ## More Information
95 | See the research report that led to this project with more details and comparisons to other frameworks [here](http://www.slideshare.net/DanielMarcous/distributed-kbetweenness-spark)
96 |
97 | ##Credits
98 |
99 | Written and maintained by :
100 |
101 | Daniel Marcous
102 |
103 | Yotam Sandbank
104 |
105 |
106 |
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/build.sbt:
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1 | name := "spark-betweenness"
2 |
3 | organization := "com.centrality"
4 |
5 | version := "1.0"
6 |
7 | scalaVersion := "2.10.4"
8 |
9 | crossScalaVersions := Seq("2.10.5", "2.11.7")
10 |
11 | libraryDependencies += "org.scalatest" % "scalatest_2.10" % "2.2.4" % "test"
12 |
13 | spName := "dmarcous/spark-betweenness"
14 |
15 | sparkVersion := "1.5.2"
16 |
17 | sparkComponents += "graphx"
18 |
19 | spAppendScalaVersion := true
20 |
21 | EclipseKeys.eclipseOutput := Some("target/eclipse")
22 |
23 | /********************
24 | * Release settings *
25 | ********************/
26 |
27 | credentials += Credentials(Path.userHome / ".sbtcredentials")
28 |
29 | spShortDescription := "k Betweenness Centrality algorithm for Spark using GraphX"
30 |
31 | spDescription := """Computing k Betweenness Centrality (kBC) on arbitrary graphs using GraphX.
32 | |Uses Pregel API for k-graphlet generation and Brandes algorithm for kBC score contribution for each vertex in parallel.
33 | |Works best for graphs with small diameter.""".stripMargin
34 |
35 | spHomepage := "https://github.com/dmarcous/spark-betweenness"
36 |
37 | licenses += ("Apache-2.0", url("http://www.apache.org/licenses/LICENSE-2.0"))
38 |
39 | pomExtra :=
40 | https://github.com/dmarcous/spark-betweenness
41 |
42 | git@github.com:dmarcous/spark-betweenness.git
43 | scm:git:git@github.com:dmarcous/spark-betweenness.git
44 |
45 |
46 |
47 | dmarcous
48 | Daniel Marcous
49 | https://github.com/dmarcous
50 |
51 |
52 | yotamsandbank
53 | Yotam Sandbank
54 | https://github.com/yotamsandbank
55 |
56 |
57 |
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/project/plugins.sbt:
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1 | resolvers += "bintray-spark-packages" at "https://dl.bintray.com/spark-packages/maven/"
2 |
3 | addSbtPlugin("org.spark-packages" % "sbt-spark-package" % "0.2.3")
4 |
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1 | #default#spark-beetweenness-build;0.1-SNAPSHOT resolved revisions
2 | #Mon Feb 29 12:03:31 IST 2016
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1 | #default#spark-betweenness-build;0.1-SNAPSHOT resolved revisions
2 | #Wed Mar 02 11:21:49 IST 2016
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1 | /*
2 | * Licensed to the Apache Software Foundation (ASF) under one or more
3 | * contributor license agreements. See the NOTICE file distributed with
4 | * this work for additional information regarding copyright ownership.
5 | * The ASF licenses this file to You under the Apache License, Version 2.0
6 | * (the "License"); you may not use this file except in compliance with
7 | * the License. You may obtain a copy of the License at
8 | *
9 | * http://www.apache.org/licenses/LICENSE-2.0
10 | *
11 | * Unless required by applicable law or agreed to in writing, software
12 | * distributed under the License is distributed on an "AS IS" BASIS,
13 | * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
14 | * See the License for the specific language governing permissions and
15 | * limitations under the License.
16 | *
17 | */
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21 | font-size:small;
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34 | }
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45 |
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47 | border-style:solid;
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49 | }
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60 |
61 | #confmenu {
62 | color: #000;
63 | border-bottom: 2px solid black;
64 | margin: 12px 0px 0px 0px;
65 | padding: 0px;
66 | z-index: 1;
67 | padding-left: 10px
68 | }
69 |
70 | #confmenu li {
71 | display: inline;
72 | overflow: hidden;
73 | list-style-type: none;
74 | }
75 |
76 | #confmenu a, a.active {
77 | color: #DEDECF;
78 | background: #898B5E;
79 | font: bold 1em "Trebuchet MS", Arial, sans-serif;
80 | border: 2px solid black;
81 | padding: 2px 5px 0px 5px;
82 | text-decoration: none;
83 | }
84 |
85 | /*
86 | background: #ABAD85 #CED4BD
87 | background: #DEE4CD
88 | */
89 |
90 | #confmenu a.active {
91 | color: #7A9437;
92 | background: #DEE4CD;
93 | border-bottom: 3px solid #DEE4CD;
94 | }
95 |
96 | #confmenu a:hover {
97 | color: #fff;
98 | background: #ADC09F;
99 | }
100 |
101 | #confmenu a:visited {
102 | color: #DEDECF;
103 | }
104 |
105 | #confmenu a.active:visited {
106 | color: #7A9437;
107 | }
108 |
109 | #confmenu a.active:hover {
110 | background: #DEE4CD;
111 | color: #DEDECF;
112 | }
113 |
114 | #content {
115 | background: #DEE4CD;
116 | padding: 20px;
117 | border: 2px solid black;
118 | border-top: none;
119 | z-index: 2;
120 | }
121 |
122 | #content a {
123 | text-decoration: none;
124 | color: #E8E9BE;
125 | }
126 |
127 | #content a:hover {
128 | background: #898B5E;
129 | }
130 |
131 |
132 | h2 {
133 | margin-bottom:2px;
134 | font-size:medium;
135 |
136 | border-color:#7A9437;
137 | border-style:solid;
138 | border-width:0 0 2px 0;
139 | }
140 |
141 | h3 {
142 | margin-top:30px;
143 | margin-bottom:2px;
144 | padding: 5 5 5 0;
145 | font-size: 24px;
146 | border-style:solid;
147 | border-width:0 0 2px 0;
148 | }
149 |
150 | h4 {
151 | margin-bottom:2px;
152 | margin-top:2px;
153 | font-size:medium;
154 |
155 | border-color:#7A9437;
156 | border-style:dashed;
157 | border-width:0 0 1px 0;
158 | }
159 |
160 | h5 {
161 | margin-bottom:2px;
162 | margin-top:2px;
163 | margin-left:20px;
164 | font-size:medium;
165 | }
166 |
167 | span.resolved {
168 | padding-left: 15px;
169 | font-weight: 500;
170 | font-size: small;
171 | }
172 |
173 |
174 | #content table {
175 | border-collapse:collapse;
176 | width:90%;
177 | margin:auto;
178 | margin-top: 5px;
179 | }
180 | #content thead {
181 | background-color:#CED4BD;
182 | border:1px solid #7A9437;
183 | }
184 | #content tbody {
185 | border-collapse:collapse;
186 | background-color:#FFFFFF;
187 | border:1px solid #7A9437;
188 | }
189 |
190 | #content th {
191 | font-family:monospace;
192 | border:1px solid #7A9437;
193 | padding:5px;
194 | }
195 |
196 | #content td {
197 | border:1px dotted #7A9437;
198 | padding:0 3 0 3;
199 | }
200 |
201 | #content table a {
202 | color:#7A9437;
203 | text-decoration:none;
204 | }
205 |
206 | #content table a:hover {
207 | background-color:#CED4BD;
208 | color:#7A9437;
209 | }
210 |
211 |
212 |
213 | table.deps {
214 | border-collapse:collapse;
215 | width:90%;
216 | margin:auto;
217 | margin-top: 5px;
218 | }
219 |
220 | table.deps thead {
221 | background-color:#CED4BD;
222 | border:1px solid #7A9437;
223 | }
224 | table.deps tbody {
225 | border-collapse:collapse;
226 | background-color:#FFFFFF;
227 | border:1px solid #7A9437;
228 | }
229 |
230 | table.deps th {
231 | font-family:monospace;
232 | border:1px solid #7A9437;
233 | padding:2;
234 | }
235 |
236 | table.deps td {
237 | border:1px dotted #7A9437;
238 | padding:0 3 0 3;
239 | }
240 |
241 |
242 |
243 |
244 |
245 | table.header {
246 | border:0;
247 | width:90%;
248 | margin:auto;
249 | margin-top: 5px;
250 | }
251 |
252 | table.header thead {
253 | border:0;
254 | }
255 | table.header tbody {
256 | border:0;
257 | }
258 | table.header tr {
259 | padding:0px;
260 | border:0;
261 | }
262 | table.header td {
263 | padding:0 3 0 3;
264 | border:0;
265 | }
266 |
267 | td.title {
268 | width:150px;
269 | margin-right:15px;
270 |
271 | font-size:small;
272 | font-weight:700;
273 | }
274 |
275 | td.title:first-letter {
276 | color:#7A9437;
277 | background-color:transparent;
278 | }
279 |
280 |
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/python/kBC.py:
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1 | import networkx as nx
2 | from collections import deque
3 | import time
4 | import sys
5 | import os
6 |
7 | print('Usage: python kBC.py filename k')
8 | args = sys.argv
9 | os.chdir(sys.path[0])
10 | sg = nx.read_edgelist(args[1], nodetype=int)#, create_using = nx.DiGraph())
11 | k = int(args[2])
12 |
13 | inf = float('inf')
14 | start = time.clock()
15 |
16 |
17 | # Betweenness centrality
18 | kBC = dict({key:0 for key in sg.nodes()})
19 | for s in sg.nodes():
20 | #Structures
21 | Q = deque() #Queue
22 | S = deque() #Stack
23 | dist = dict({key:inf for key in sg.nodes()})
24 | sig = dict({key:float(0) for key in sg.nodes()})
25 | pred = dict({key:[] for key in sg.nodes()})
26 |
27 | #Initialize
28 | Q.append(s)
29 | dist[s] = 0
30 | sig[s] = 1
31 |
32 | #BFS - top-down
33 | while len(Q) > 0:
34 | v = Q.popleft()
35 | if dist[v] > k:
36 | break;
37 | S.append(v)
38 | for w in sg[v]:
39 | if dist[w] == inf:
40 | dist[w] = dist[v] + 1
41 | if dist[w] <= k:
42 | Q.append(w)
43 | if dist[w] == dist[v] + 1:
44 | sig[w] += sig[v]
45 | pred[w].append(v)
46 | #Aggregate - bottom-up
47 | delta = dict({key:float(0) for key in sg.nodes()})
48 | while len(S) > 0:
49 | v = S.pop()
50 | for w in pred[v]:
51 | delta[w] += (delta[v]+1) * sig[w] / sig[v]
52 | if v!=s:
53 | if(sg.is_directed()):
54 | kBC[v] += delta[v]
55 | else: kBC[v] += delta[v] / 2.0
56 | end = time.clock()
57 | print('My time: ' + str(end - start))
58 |
59 |
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/src/functional-test/scala/com/centrality/kBC/LocalRunner.scala:
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1 | package com.centrality.kBC
2 |
3 | import org.apache.spark.SparkConf
4 | import org.apache.spark.SparkContext
5 | import org.apache.spark.graphx.Edge
6 | import org.apache.spark.graphx.Graph
7 | import org.apache.spark.graphx.VertexId
8 | import org.apache.spark.rdd.RDD
9 |
10 | object MainRunner
11 | {
12 | def main(args: Array[String])
13 | {
14 | // Create spark context
15 | val appName="kBC"
16 | val sparkMode="local"
17 | val conf = new SparkConf().setAppName(appName).setMaster(sparkMode);
18 | val sc = new SparkContext(conf);
19 |
20 | // Create sample graph
21 | //
22 | // Create an RDD for vertices
23 | val users: RDD[(VertexId, (String, String))] =
24 | sc.parallelize(Array((3L, ("rxin", "student")), (7L, ("jgonzal", "postdoc")),
25 | (5L, ("franklin", "prof")), (2L, ("istoica", "prof"))))
26 | // Create an RDD for edges
27 | val relationships: RDD[Edge[String]] =
28 | sc.parallelize(Array(Edge(3L, 7L, "collab"), Edge(5L, 3L, "advisor"),
29 | Edge(2L, 5L, "colleague"), Edge(5L, 7L, "pi")))
30 | // Define a default user in case there are relationship with missing user
31 | val defaultUser = ("John Doe", "Missing")
32 | // Build the initial Graph
33 | val graph = Graph(users, relationships, defaultUser)
34 |
35 | val kBCGraph =
36 | KBetweenness.run(graph, 3)
37 | }
38 | }
--------------------------------------------------------------------------------
/src/main/scala/com/centrality/kBC/KBetweenness.scala:
--------------------------------------------------------------------------------
1 | package com.centrality.kBC
2 |
3 | import scala.reflect.ClassTag
4 | import org.apache.spark.Logging
5 | import org.apache.spark.rdd.PairRDDFunctions
6 | import org.apache.spark.graphx.VertexId
7 | import org.apache.spark.graphx.Edge
8 | import org.apache.spark.graphx.Graph
9 | import org.apache.spark.graphx.VertexRDD
10 | import org.apache.spark.graphx.EdgeTriplet
11 | import org.apache.spark.graphx.Pregel
12 | import org.apache.spark.graphx.EdgeDirection
13 | import scala.collection.mutable.Stack
14 | import scala.collection.mutable.Queue
15 | import scala.collection.mutable.HashMap
16 | import scala.collection.mutable.ListBuffer
17 |
18 | object KBetweenness
19 | {
20 | def run[VD: ClassTag, ED: ClassTag](
21 | graph: Graph[VD, ED], k: Int): Graph[Double, Double] =
22 | {
23 | val kGraphletsGraph =
24 | createKGraphlets(graph, k)
25 |
26 | val vertexKBcGraph =
27 | kGraphletsGraph
28 | .mapVertices((id, attr) => (id, computeVertexBetweenessCentrality(id, attr._2, attr._3)))
29 |
30 | val kBCGraph: Graph[Double, Double] =
31 | aggregateGraphletsBetweennessScores(vertexKBcGraph)
32 |
33 | kBCGraph
34 | }
35 |
36 | def createKGraphlets[VD: ClassTag, ED: ClassTag](graph: Graph[VD, ED], k: Int): Graph[(Double, List[VertexId], List[(VertexId, VertexId)]), Double] =
37 | {
38 | val graphContainingGraphlets : Graph[(Double, List[VertexId], List[(VertexId, VertexId)]), Double] =
39 | graph
40 | // Init edges to hold - Edge Betweenness to 0.0
41 | .mapTriplets[Double]({x: EdgeTriplet[VD, ED] => (0.0) })
42 | // Init vertices to hold - Vertex betweenness (0.0), and K distance Edge list (empty)
43 | .mapVertices( (id, attr) => (0.0, List[VertexId](id), List[(VertexId, VertexId)]()))
44 | //.reverse // Because GraphX is directed and we want graphlets containing all vertices a vertex might effect
45 | .cache()
46 |
47 | def vertexProgram(id: VertexId, attr: (Double, List[VertexId], List[(VertexId, VertexId)]), msgSum: (List[VertexId], List[(VertexId, VertexId)])): (Double, List[VertexId], List[(VertexId, VertexId)]) =
48 | (attr._1, attr._2.union(msgSum._1).distinct, attr._3.union(msgSum._2).distinct)
49 | def sendMessage(edge: EdgeTriplet[(Double, List[VertexId], List[(VertexId, VertexId)]), Double]) : Iterator[(VertexId, (List[VertexId], List[(VertexId, VertexId)]))]=
50 | Iterator((edge.dstId, (edge.srcAttr._2.:+(edge.srcId) , edge.srcAttr._3.+:(edge.srcId, edge.dstId))),
51 | (edge.srcId, (edge.dstAttr._2.:+(edge.dstId) , edge.dstAttr._3.+:(edge.srcId, edge.dstId)))
52 | )
53 | def messageCombiner(a: (List[VertexId], List[(VertexId, VertexId)]), b: (List[VertexId], List[(VertexId, VertexId)])): (List[VertexId], List[(VertexId, VertexId)]) =
54 | (a._1.union(b._1) , a._2.union(b._2) )
55 | // The initial message received by all vertices in PageRank
56 | val initialMessage = (List[VertexId](), List[(VertexId, VertexId)]())
57 |
58 | // Execute pregel for k iterations, get all vertices/edges in distance k for every node
59 | Pregel(graphContainingGraphlets, initialMessage, k, activeDirection = EdgeDirection.Both)(
60 | vertexProgram, sendMessage, messageCombiner)
61 | //.reverse // return to originial directon
62 | }
63 |
64 | def computeVertexBetweenessCentrality(id: VertexId, vlist: List[VertexId], elist: List[(VertexId, VertexId)]): List[(VertexId, Double)] =
65 | {
66 | // Init data structures
67 | val s = Stack[VertexId]()
68 | val q = Queue[VertexId]()
69 |
70 | val dist = new HashMap[VertexId, Double]()
71 | val sigma = new HashMap[VertexId, Double]()
72 | val delta = new HashMap[VertexId, Double]()
73 | val predecessors = new HashMap[VertexId, ListBuffer[VertexId]]()
74 | val neighbourMap : HashMap[VertexId, List[VertexId]] = getNeighbourMap(vlist,elist)
75 | val medBC = new ListBuffer[(VertexId, Double)]()
76 |
77 | for (vertex <- vlist)
78 | {
79 | dist.put(vertex, Double.MaxValue)
80 | sigma.put(vertex, 0.0)
81 | delta.put(vertex, 0.0)
82 | predecessors.put(vertex, ListBuffer[VertexId]())
83 | }
84 |
85 | // Init values before first iteration
86 | dist(id) = 0.0
87 | sigma(id) = 1.0
88 | q.enqueue(id)
89 |
90 | // Go over all queued vertices
91 | while (!(q.isEmpty))
92 | {
93 | val v = q.dequeue()
94 | s.push(v)
95 | // Go over v's neighbours
96 | for (w <- neighbourMap(v))
97 | {
98 | if (dist(w) == Double.MaxValue)
99 | {
100 | dist(w) = dist(v) + 1.0
101 | q.enqueue(w)
102 | }
103 | if(dist(w) == (dist(v) + 1.0))
104 | {
105 | sigma(w) += sigma(v)
106 | predecessors(w).+=(v)
107 | }
108 | }
109 | }
110 |
111 | while (!(s.isEmpty))
112 | {
113 | val v = s.pop()
114 | for (w <- predecessors(v))
115 | {
116 | delta(w) += (sigma(w) / sigma(v)) * (delta(v) + 1.0)
117 | }
118 | if (v != id)
119 | {
120 | medBC.append((v, delta(v)))
121 | }
122 | }
123 |
124 | medBC.toList
125 | }
126 |
127 | def getNeighbourMap(vlist: List[VertexId], elist: List[(VertexId, VertexId)]): HashMap[VertexId, List[VertexId]] =
128 | {
129 | val neighbourList = new HashMap[VertexId, List[VertexId]]()
130 |
131 | vlist.foreach { case(v) =>
132 | {val nlist = (elist.filter{case(e) => ((e._1 == v) || (e._2 == v))})
133 | .map{case(e) => {if (e._1 == v) e._2 else e._1 }}
134 | neighbourList.+=((v,nlist.distinct))
135 | }
136 | }
137 |
138 | neighbourList
139 | }
140 |
141 | def aggregateGraphletsBetweennessScores(vertexKBcGraph: Graph[(VertexId, List[(VertexId, Double)]), Double]): Graph[Double, Double] =
142 | {
143 | val DEFAULT_BC = 0.0
144 |
145 | val kBCAdditions =
146 | vertexKBcGraph
147 | .vertices
148 | .flatMap{case(v, (id, listkBC)) =>
149 | (listkBC.map{case(w, kBC)=>(w, kBC)})}
150 |
151 | val verticeskBC =
152 | kBCAdditions
153 | .reduceByKey(_ + _)
154 |
155 | val kBCGraph =
156 | vertexKBcGraph
157 | .outerJoinVertices(verticeskBC)({case(v_id,(g_id,g_medkBC),kBC) => (kBC.getOrElse(DEFAULT_BC))})
158 |
159 | kBCGraph
160 | }
161 |
162 | }
--------------------------------------------------------------------------------
/src/main/scala/com/centrality/kBC/kBCDriver.scala:
--------------------------------------------------------------------------------
1 | package com.centrality.kBC
2 |
3 | import java.util.Calendar
4 |
5 | import org.apache.spark.SparkConf
6 | import org.apache.spark.SparkContext
7 | import org.apache.spark.graphx.GraphLoader
8 | import org.apache.spark.graphx.PartitionStrategy
9 |
10 | object kBCDriver
11 | {
12 | def main(args: Array[String])
13 | {
14 | // Create spark context
15 | val appName="kBCDriver"
16 | val conf = new SparkConf().setAppName(appName)//.setMaster(master)
17 | val sc = new SparkContext(conf)
18 |
19 | // Graph partition params
20 | val DEFAULT_K = 2
21 | val DEFAULT_EDGE_PARTITIONS=60
22 | val DEFAULT_CANONICAL_ORIENTATION=true
23 | val k = args(0).toInt
24 | println("k : " + k)
25 | val canonicalOrientation = DEFAULT_CANONICAL_ORIENTATION
26 | val numEdgePartitions = args(1).toInt
27 |
28 | // Input params
29 | val DEFAULT_INPUT_DIR="/tmp/input/"
30 | val DEFAULT_INPUT_FILE_NAME="edge_list.txt"
31 | val inputDir = args(2)
32 | val inputFileName = args(4)
33 | val inputPath = inputDir+inputFileName
34 | println("inputPath : " + inputPath)
35 |
36 | // Output params
37 | val DEFAULT_OUTPUT_DIR="/tmp/output/"
38 | val DEFAULT_V_OUTPUT_FILE=List(inputFileName,"kbc",k,"vertices").mkString("_")+".txt"
39 | val DEFAULT_E_OUTPUT_FILE=List(inputFileName,"kbc",k,"edges").mkString("_")+".txt"
40 | val outputDir = args(3)
41 | val outputVerticesFileName = sc.hadoopConfiguration.get("outputVerticesFileName", DEFAULT_V_OUTPUT_FILE)
42 | val outputEdgesFileName = sc.hadoopConfiguration.get("outputEdgesFileName", DEFAULT_E_OUTPUT_FILE)
43 | val outputVerticesPath = sc.hadoopConfiguration.get("outputVerticesPath", outputDir+outputVerticesFileName)
44 | val outputEdgesPath = sc.hadoopConfiguration.get("outputEdgesPath", outputDir+outputEdgesFileName)
45 | println("outputVerticesPath : " + outputVerticesPath)
46 | println("outputEdgesPath : " + outputEdgesPath)
47 |
48 | // Read graph
49 | val graph = GraphLoader.edgeListFile(sc, inputPath, canonicalOrientation, numEdgePartitions).partitionBy(PartitionStrategy.EdgePartition2D)
50 | println(Calendar.getInstance().getTime().toString + " vertices : " + graph.vertices.count())
51 | println(Calendar.getInstance().getTime().toString + " edges : " + graph.edges.count())
52 |
53 | // Run kBC
54 | println(Calendar.getInstance().getTime().toString + ": start kBC")
55 | val kBCGraph =
56 | KBetweenness.run(graph, k)
57 |
58 | // Save graph to file
59 | println(Calendar.getInstance().getTime().toString + ": saving results ")
60 | kBCGraph.vertices.coalesce(1).saveAsTextFile(outputVerticesPath)
61 | kBCGraph.edges.coalesce(1).saveAsTextFile(outputEdgesPath)
62 | }
63 | }
--------------------------------------------------------------------------------
/src/test/scala/com/centrality/kBC/KBetweennessTest.scala:
--------------------------------------------------------------------------------
1 | package com.centrality.kBC
2 |
3 | import scala.collection.mutable.HashMap
4 |
5 | import org.apache.spark.SparkConf
6 | import org.apache.spark.SparkContext
7 | import org.apache.spark.graphx.Edge
8 | import org.apache.spark.graphx.Graph
9 | import org.apache.spark.graphx.VertexId
10 | import org.apache.spark.rdd.RDD
11 | import org.scalatest.FlatSpec
12 | import org.scalatest.Matchers.contain
13 | import org.scalatest.Matchers.convertToAnyShouldWrapper
14 | import org.scalatest.Matchers.equal
15 |
16 | class KBetweennessTest extends FlatSpec
17 | {
18 | val appName="kBC"
19 | val sparkMode="local"
20 | val conf = new SparkConf().setAppName(appName).setMaster(sparkMode);
21 | val sc = new SparkContext(conf);
22 |
23 | val vertices: RDD[(VertexId, Int)] =
24 | sc.parallelize(Array(
25 | (1L, 0),
26 | (2L, 0),
27 | (3L, 0),
28 | (4L, 0),
29 | (5L, 0),
30 | (6L, 0),
31 | (7L, 0)
32 | ))
33 | // Create an RDD for edges
34 | val edges: RDD[Edge[Int]] =
35 | sc.parallelize(Array(
36 | Edge(1L, 2L, 0),
37 | Edge(1L, 3L, 0),
38 | Edge(2L, 4L, 0),
39 | Edge(3L, 4L, 0),
40 | Edge(3L, 5L, 0),
41 | Edge(4L, 6L, 0),
42 | Edge(5L, 7L, 0)
43 | ))
44 | val defaultVertex = 0
45 | // Build the initial Graph
46 | val graph = Graph(vertices, edges, defaultVertex)
47 |
48 | " getNeighbourMap " should " return neighbour map for graph" in
49 | {
50 | val vlist : List[VertexId] =
51 | List(1L, 2L, 3L, 4L, 5L, 6L, 7L)
52 | val elist : List[(VertexId, VertexId)] =
53 | List((1L,2L),(1L,3L),(2L,4L),(3L,4L),(3L,5L),(4L,6L),(5L,7L))
54 | val neighbourList : HashMap[VertexId, List[VertexId]] =
55 | KBetweenness.getNeighbourMap(vlist, elist)
56 |
57 | neighbourList(1L) should contain only (2L, 3L)
58 | neighbourList(2L) should contain only (1L, 4L)
59 | neighbourList(3L) should contain only (1L, 4L, 5L)
60 | neighbourList(4L) should contain only (2L, 3L, 6L)
61 | neighbourList(5L) should contain only (3L, 7L)
62 | neighbourList(6L) should contain only (4L)
63 | neighbourList(7L) should contain only (5L)
64 | }
65 |
66 | " createKGraphlets " should " return 1 graphlets" in
67 | {
68 | val k = 1
69 |
70 | val kGraphletsGraph =
71 | KBetweenness.createKGraphlets(graph, k)
72 |
73 | val graphlets = kGraphletsGraph.vertices.collect()
74 |
75 | val sortedGraphlets =
76 | graphlets.toList.sortWith((x,y) => x._1 < y._1)
77 |
78 | sortedGraphlets(0)._1 should equal (1L)
79 | sortedGraphlets(0)._2._1 should equal (0.0)
80 | sortedGraphlets(0)._2._2 should contain only (1L, 2L, 3L)
81 | sortedGraphlets(0)._2._3 should contain only ((1L,2L), (1L,3L))
82 |
83 | sortedGraphlets(1)._1 should equal (2L)
84 | sortedGraphlets(1)._2._1 should equal (0.0)
85 | sortedGraphlets(1)._2._2 should contain only (1L, 2L, 4L)
86 | sortedGraphlets(1)._2._3 should contain only ((1L,2L), (2L,4L))
87 |
88 | sortedGraphlets(2)._1 should equal (3L)
89 | sortedGraphlets(2)._2._1 should equal (0.0)
90 | sortedGraphlets(2)._2._2 should contain only (1L, 3L, 4L, 5L)
91 | sortedGraphlets(2)._2._3 should contain only ((1L,3L), (3L,4L), (3L,5L))
92 |
93 | sortedGraphlets(3)._1 should equal (4L)
94 | sortedGraphlets(3)._2._1 should equal (0.0)
95 | sortedGraphlets(3)._2._2 should contain only (2L, 3L, 4L, 6L)
96 | sortedGraphlets(3)._2._3 should contain only ((2L,4L), (3L,4L), (4L,6L))
97 |
98 | sortedGraphlets(4)._1 should equal (5L)
99 | sortedGraphlets(4)._2._1 should equal (0.0)
100 | sortedGraphlets(4)._2._2 should contain only (3L, 5L, 7L)
101 | sortedGraphlets(4)._2._3 should contain only ((3L,5L), (5L,7L))
102 |
103 | sortedGraphlets(5)._1 should equal (6L)
104 | sortedGraphlets(5)._2._1 should equal (0.0)
105 | sortedGraphlets(5)._2._2 should contain only (4L, 6L)
106 | sortedGraphlets(5)._2._3 should contain only ((4L,6L))
107 |
108 | sortedGraphlets(6)._1 should equal (7L)
109 | sortedGraphlets(6)._2._1 should equal (0.0)
110 | sortedGraphlets(6)._2._2 should contain only (5L, 7L)
111 | sortedGraphlets(6)._2._3 should contain only ((5L,7L))
112 | }
113 |
114 | it should " return 3 graphlets" in
115 | {
116 | val k = 3
117 |
118 | val kGraphletsGraph =
119 | KBetweenness.createKGraphlets(graph, k)
120 |
121 | val graphlets = kGraphletsGraph.vertices.collect()
122 |
123 | val sortedGraphlets =
124 | graphlets.toList.sortWith((x,y) => x._1 < y._1)
125 |
126 | sortedGraphlets(0)._1 should equal (1L)
127 | sortedGraphlets(0)._2._1 should equal (0.0)
128 | sortedGraphlets(0)._2._2 should contain only (1L, 2L, 3L, 4L, 5L, 6L, 7L)
129 | sortedGraphlets(0)._2._3 should contain only ((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L), (5L,7L))
130 |
131 | sortedGraphlets(1)._1 should equal (2L)
132 | sortedGraphlets(1)._2._1 should equal (0.0)
133 | sortedGraphlets(1)._2._2 should contain only (1L, 2L, 3L, 4L, 5L, 6L)
134 | sortedGraphlets(1)._2._3 should contain only ((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L))
135 |
136 | sortedGraphlets(2)._1 should equal (3L)
137 | sortedGraphlets(2)._2._1 should equal (0.0)
138 | sortedGraphlets(2)._2._2 should contain only (1L, 2L, 3L, 4L, 5L, 6L, 7L)
139 | sortedGraphlets(2)._2._3 should contain only ((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L), (5L,7L))
140 |
141 | sortedGraphlets(3)._1 should equal (4L)
142 | sortedGraphlets(3)._2._1 should equal (0.0)
143 | sortedGraphlets(3)._2._2 should contain only (1L, 2L, 3L, 4L, 5L, 6L, 7L)
144 | sortedGraphlets(3)._2._3 should contain only ((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L), (5L,7L))
145 |
146 | sortedGraphlets(4)._1 should equal (5L)
147 | sortedGraphlets(4)._2._1 should equal (0.0)
148 | sortedGraphlets(4)._2._2 should contain only (1L, 2L, 3L, 4L, 5L, 6L, 7L)
149 | sortedGraphlets(4)._2._3 should contain only ((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L), (5L,7L))
150 |
151 | sortedGraphlets(5)._1 should equal (6L)
152 | sortedGraphlets(5)._2._1 should equal (0.0)
153 | sortedGraphlets(5)._2._2 should contain only (1L, 2L, 3L, 4L, 5L, 6L)
154 | sortedGraphlets(5)._2._3 should contain only ((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L))
155 |
156 | sortedGraphlets(6)._1 should equal (7L)
157 | sortedGraphlets(6)._2._1 should equal (0.0)
158 | sortedGraphlets(6)._2._2 should contain only (1L, 3L, 4L, 5L, 7L)
159 | sortedGraphlets(6)._2._3 should contain only ((1L,3L), (3L,4L), (3L,5L), (5L,7L))
160 | }
161 |
162 | "computeVertexBetweenessCentrality" should " compute betwenness scores for single vertices" in
163 | {
164 | val k = 3
165 |
166 | val vertexId1 = 1L
167 | val vertex1VList = List(1L, 2L, 3L, 4L, 5L, 6L, 7L)
168 | val vertex1EList = List((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L), (5L,7L))
169 | val vertex1KBcGraph =
170 | KBetweenness.computeVertexBetweenessCentrality(vertexId1, vertex1VList, vertex1EList)
171 |
172 | val sorted1KBcContibution =
173 | vertex1KBcGraph.toList.sortWith((x,y) => x._1 < y._1)
174 |
175 | sorted1KBcContibution(0)._1 should equal (2L)
176 | sorted1KBcContibution(0)._2 should equal (1.0)
177 | sorted1KBcContibution(1)._1 should equal (3L)
178 | sorted1KBcContibution(1)._2 should equal (3.0)
179 | sorted1KBcContibution(2)._1 should equal (4L)
180 | sorted1KBcContibution(2)._2 should equal (1.0)
181 | sorted1KBcContibution(3)._1 should equal (5L)
182 | sorted1KBcContibution(3)._2 should equal (1.0)
183 | sorted1KBcContibution(4)._1 should equal (6L)
184 | sorted1KBcContibution(4)._2 should equal (0.0)
185 | sorted1KBcContibution(5)._1 should equal (7L)
186 | sorted1KBcContibution(5)._2 should equal (0.0)
187 |
188 | val vertexId2 = 2L
189 | val vertex2VList = List(1L, 2L, 3L, 4L, 5L, 6L)
190 | val vertex2EList = List((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L))
191 | val vertex2KBcGraph =
192 | KBetweenness.computeVertexBetweenessCentrality(vertexId2, vertex2VList, vertex2EList)
193 |
194 | val sorted2KBcContibution =
195 | vertex2KBcGraph.toList.sortWith((x,y) => x._1 < y._1)
196 |
197 | sorted2KBcContibution(0)._1 should equal (1L)
198 | sorted2KBcContibution(0)._2 should equal (1.0)
199 | sorted2KBcContibution(1)._1 should equal (3L)
200 | sorted2KBcContibution(1)._2 should equal (1.0)
201 | sorted2KBcContibution(2)._1 should equal (4L)
202 | sorted2KBcContibution(2)._2 should equal (2.0)
203 | sorted2KBcContibution(3)._1 should equal (5L)
204 | sorted2KBcContibution(3)._2 should equal (0.0)
205 | sorted2KBcContibution(4)._1 should equal (6L)
206 | sorted2KBcContibution(4)._2 should equal (0.0)
207 |
208 | val vertexId3 = 3L
209 | val vertex3VList = List(1L, 2L, 3L, 4L, 5L, 6L, 7L)
210 | val vertex3EList = List((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L), (5L,7L))
211 | val vertex3KBcGraph =
212 | KBetweenness.computeVertexBetweenessCentrality(vertexId3, vertex3VList, vertex3EList)
213 |
214 | val sorted3KBcContibution =
215 | vertex3KBcGraph.toList.sortWith((x,y) => x._1 < y._1)
216 |
217 | sorted3KBcContibution(0)._1 should equal (1L)
218 | sorted3KBcContibution(0)._2 should equal (0.5)
219 | sorted3KBcContibution(1)._1 should equal (2L)
220 | sorted3KBcContibution(1)._2 should equal (0.0)
221 | sorted3KBcContibution(2)._1 should equal (4L)
222 | sorted3KBcContibution(2)._2 should equal (1.5)
223 | sorted3KBcContibution(3)._1 should equal (5L)
224 | sorted3KBcContibution(3)._2 should equal (1.0)
225 | sorted3KBcContibution(4)._1 should equal (6L)
226 | sorted3KBcContibution(4)._2 should equal (0.0)
227 | sorted3KBcContibution(5)._1 should equal (7L)
228 | sorted3KBcContibution(5)._2 should equal (0.0)
229 |
230 | val vertexId4 = 4L
231 | val vertex4VList = List(1L, 2L, 3L, 4L, 5L, 6L, 7L)
232 | val vertex4EList = List((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L), (5L,7L))
233 | val vertex4KBcGraph =
234 | KBetweenness.computeVertexBetweenessCentrality(vertexId4, vertex4VList, vertex4EList)
235 |
236 | val sorted4KBcContibution =
237 | vertex4KBcGraph.toList.sortWith((x,y) => x._1 < y._1)
238 |
239 | sorted4KBcContibution(0)._1 should equal (1L)
240 | sorted4KBcContibution(0)._2 should equal (0.0)
241 | sorted4KBcContibution(1)._1 should equal (2L)
242 | sorted4KBcContibution(1)._2 should equal (0.5)
243 | sorted4KBcContibution(2)._1 should equal (3L)
244 | sorted4KBcContibution(2)._2 should equal (2.5)
245 | sorted4KBcContibution(3)._1 should equal (5L)
246 | sorted4KBcContibution(3)._2 should equal (1.0)
247 | sorted4KBcContibution(4)._1 should equal (6L)
248 | sorted4KBcContibution(4)._2 should equal (0.0)
249 | sorted4KBcContibution(5)._1 should equal (7L)
250 | sorted4KBcContibution(5)._2 should equal (0.0)
251 |
252 | val vertexId5 = 5L
253 | val vertex5VList = List(1L, 2L, 3L, 4L, 5L, 6L, 7L)
254 | val vertex5EList = List((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L), (5L,7L))
255 | val vertex5KBcGraph =
256 | KBetweenness.computeVertexBetweenessCentrality(vertexId5, vertex5VList, vertex5EList)
257 |
258 | val sorted5KBcContibution =
259 | vertex5KBcGraph.toList.sortWith((x,y) => x._1 < y._1)
260 |
261 | sorted5KBcContibution(0)._1 should equal (1L)
262 | sorted5KBcContibution(0)._2 should equal (0.5)
263 | sorted5KBcContibution(1)._1 should equal (2L)
264 | sorted5KBcContibution(1)._2 should equal (0.0)
265 | sorted5KBcContibution(2)._1 should equal (3L)
266 | sorted5KBcContibution(2)._2 should equal (4.0)
267 | sorted5KBcContibution(3)._1 should equal (4L)
268 | sorted5KBcContibution(3)._2 should equal (1.5)
269 | sorted5KBcContibution(4)._1 should equal (6L)
270 | sorted5KBcContibution(4)._2 should equal (0.0)
271 | sorted5KBcContibution(5)._1 should equal (7L)
272 | sorted5KBcContibution(5)._2 should equal (0.0)
273 |
274 | val vertexId6 = 6L
275 | val vertex6VList = List(1L, 2L, 3L, 4L, 5L, 6L)
276 | val vertex6EList = List((1L,2L), (1L,3L), (2L,4L), (3L,4L), (3L,5L), (4L,6L))
277 | val vertex6KBcGraph =
278 | KBetweenness.computeVertexBetweenessCentrality(vertexId6, vertex6VList, vertex6EList)
279 |
280 | val sorted6KBcContibution =
281 | vertex6KBcGraph.toList.sortWith((x,y) => x._1 < y._1)
282 |
283 | sorted6KBcContibution(0)._1 should equal (1L)
284 | sorted6KBcContibution(0)._2 should equal (0.0)
285 | sorted6KBcContibution(1)._1 should equal (2L)
286 | sorted6KBcContibution(1)._2 should equal (0.5)
287 | sorted6KBcContibution(2)._1 should equal (3L)
288 | sorted6KBcContibution(2)._2 should equal (1.5)
289 | sorted6KBcContibution(3)._1 should equal (4L)
290 | sorted6KBcContibution(3)._2 should equal (4.0)
291 | sorted6KBcContibution(4)._1 should equal (5L)
292 | sorted6KBcContibution(4)._2 should equal (0.0)
293 |
294 | val vertexId7 = 7L
295 | val vertex7VList = List(1L, 3L, 4L, 5L, 7L)
296 | val vertex7EList = List((1L,3L), (3L,4L), (3L,5L), (5L,7L))
297 | val vertex7KBcGraph =
298 | KBetweenness.computeVertexBetweenessCentrality(vertexId7, vertex7VList, vertex7EList)
299 |
300 | val sorted7KBcContibution =
301 | vertex7KBcGraph.toList.sortWith((x,y) => x._1 < y._1)
302 |
303 | sorted7KBcContibution(0)._1 should equal (1L)
304 | sorted7KBcContibution(0)._2 should equal (0.0)
305 | sorted7KBcContibution(1)._1 should equal (3L)
306 | sorted7KBcContibution(1)._2 should equal (2.0)
307 | sorted7KBcContibution(2)._1 should equal (4L)
308 | sorted7KBcContibution(2)._2 should equal (0.0)
309 | sorted7KBcContibution(3)._1 should equal (5L)
310 | sorted7KBcContibution(3)._2 should equal (3.0)
311 |
312 | }
313 |
314 | "run" should " compute betwenness centrality graph" in
315 | {
316 | val k = 3
317 | val kBCGraph =
318 | KBetweenness.run(graph, k)
319 |
320 | val verticesBetweenness =
321 | kBCGraph
322 | .vertices
323 | .collect()
324 |
325 | val sortedVBC =
326 | verticesBetweenness.sortWith((x,y) => x._1 < y._1)
327 |
328 | sortedVBC(0)._1 should equal (1L)
329 | sortedVBC(0)._2 should equal (2.0)
330 | sortedVBC(1)._1 should equal (2L)
331 | sortedVBC(1)._2 should equal (2.0)
332 | sortedVBC(2)._1 should equal (3L)
333 | sortedVBC(2)._2 should equal (14.0)
334 | sortedVBC(3)._1 should equal (4L)
335 | sortedVBC(3)._2 should equal (10.0)
336 | sortedVBC(4)._1 should equal (5L)
337 | sortedVBC(4)._2 should equal (6.0)
338 | sortedVBC(5)._1 should equal (6L)
339 | sortedVBC(5)._2 should equal (0.0)
340 | sortedVBC(6)._1 should equal (7L)
341 | sortedVBC(6)._2 should equal (0.0)
342 | }
343 |
344 | }
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