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Qing Guo
Bespin
Commits
d06a4179
Commit
d06a4179
authored
Feb 25, 2021
by
cs451
Browse files
multi source sequential pagerank added
parent
a06ec81b
Changes
1
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Inline
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src/main/java/io/bespin/java/mapreduce/pagerank/SequentialPersonalizedPageRank.java
View file @
d06a4179
...
...
@@ -14,7 +14,7 @@
* limitations under the License.
*/
package
io.bespin.java.mapreduce.pagerank
;
package
ca.uwaterloo.cs451.a4
;
import
com.google.common.base.Function
;
import
edu.uci.ics.jung.algorithms.cluster.WeakComponentClusterer
;
...
...
@@ -32,10 +32,11 @@ import java.io.IOException;
import
java.io.InputStreamReader
;
import
java.util.PriorityQueue
;
import
java.util.Set
;
import
java.util.ArrayList
;
/**
* <p>
* Program that computes
personalized
PageRank for a graph using the <a
* Program that computes PageRank for a graph using the <a
* href="https://github.com/jrtom/jung">JUNG</a> package. Program takes two command-line
* arguments: the first is a file containing the graph data, and the second is the random jump
* factor (a typical setting is 0.15).
...
...
@@ -49,8 +50,10 @@ import java.util.Set;
* lines will simply contain one token, the source node id).
* </p>
*
* @author Ali Abedi
* @author Jimmy Lin
*/
public
class
SequentialPersonalizedPageRank
{
private
SequentialPersonalizedPageRank
()
{}
...
...
@@ -58,15 +61,18 @@ public class SequentialPersonalizedPageRank {
@Option
(
name
=
"-input"
,
metaVar
=
"[path]"
,
required
=
true
,
usage
=
"input path"
)
String
input
;
@Option
(
name
=
"-source"
,
metaVar
=
"[node]"
,
required
=
true
,
usage
=
"source node
(i.e., destination of the random jump)
"
)
String
source
;
@Option
(
name
=
"-source
s
"
,
metaVar
=
"[node]"
,
required
=
true
,
usage
=
"source node
s set. Comma seperated.
"
)
String
source
s
;
@Option
(
name
=
"-jump"
,
metaVar
=
"[num]"
,
usage
=
"random jump factor"
)
float
alpha
=
0.15f
;
}
public
static
void
main
(
String
[]
argv
)
throws
IOException
{
// Keeping track of source nodes
ArrayList
sources
=
new
ArrayList
();
final
Args
args
=
new
Args
();
CmdLineParser
parser
=
new
CmdLineParser
(
args
,
ParserProperties
.
defaults
().
withUsageWidth
(
100
));
...
...
@@ -78,6 +84,12 @@ public class SequentialPersonalizedPageRank {
System
.
exit
(-
1
);
}
String
[]
tmp
=
args
.
sources
.
split
(
","
);
for
(
int
i
=
0
;
i
<
tmp
.
length
;
i
++)
{
sources
.
add
(
tmp
[
i
]);
}
int
edgeCnt
=
0
;
DirectedSparseGraph
<
String
,
Integer
>
graph
=
new
DirectedSparseGraph
<>();
...
...
@@ -94,12 +106,15 @@ public class SequentialPersonalizedPageRank {
}
data
.
close
();
if
(!
graph
.
containsVertex
(
args
.
source
))
{
System
.
err
.
println
(
"Error: source node not found in the graph!"
);
System
.
exit
(-
1
);
for
(
int
i
=
0
;
i
<
sources
.
size
();
i
++){
if
(!
graph
.
containsVertex
((
String
)
sources
.
get
(
i
)))
{
System
.
err
.
println
(
"Error: source node not found in the graph!"
);
System
.
exit
(-
1
);
}
}
WeakComponentClusterer
<
String
,
Integer
>
clusterer
=
new
WeakComponentClusterer
<>();
Set
<
Set
<
String
>>
components
=
clusterer
.
apply
(
graph
);
...
...
@@ -107,16 +122,16 @@ public class SequentialPersonalizedPageRank {
System
.
out
.
println
(
"Number of edges: "
+
graph
.
getEdgeCount
());
System
.
out
.
println
(
"Number of nodes: "
+
graph
.
getVertexCount
());
System
.
out
.
println
(
"Random jump factor: "
+
args
.
alpha
);
System
.
out
.
println
(
"Source nodes: "
+
args
.
sources
);
// Compute personalized PageRank.
PageRankWithPriors
<
String
,
Integer
>
ranker
=
new
PageRankWithPriors
<>(
graph
,
new
Function
<
String
,
Double
>()
{
@Override
public
Double
apply
(
String
vertex
)
{
return
vertex
.
equals
(
args
.
source
)
?
1.0
:
0
;
return
sources
.
contains
(
vertex
)
?
1.0
/
(
float
)
sources
.
size
()
:
0
;
}
},
args
.
alpha
);
// Note that the Altiscale cluster is still on Java 7, so we don't have lambdas.
ranker
.
evaluate
();
// Use priority queue to sort vertices by PageRank values.
...
...
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