边聚类系数 (EdgeClusterCoefficientBatchOp)

Java 类名：com.alibaba.alink.operator.batch.graph.EdgeClusterCoefficientBatchOp

Python 类名：EdgeClusterCoefficientBatchOp

功能介绍

对于给定的图，对于图中的每条边，分别输出边的两个顶点的度，两个顶点的公共邻点数目，以及该边的聚类系数。
聚类系数的计算公式为 commonNeighbor / min(neighobr1, neighbor2)

参数说明

名称	中文名称	描述	类型	是否必须？	取值范围	默认值
edgeSourceCol	边表中起点所在列	边表中起点所在列	String	✓	所选列类型为 [INTEGER, LONG, STRING]
edgeTargetCol	边表中终点所在列	边表中终点所在列	String	✓	所选列类型为 [INTEGER, LONG, STRING]
asUndirectedGraph	是否为无向图	是否为无向图	Boolean			true

代码示例

Python 代码

from pyalink.alink import *

import pandas as pd

useLocalEnv(1)

df = pd.DataFrame([[1.0, 2.0],\
[1.0, 3.0],\
[3.0, 2.0],\
[5.0, 2.0],\
[3.0, 4.0],\
[4.0, 2.0],\
[5.0, 4.0],\
[5.0, 1.0],\
[5.0, 3.0],\
[5.0, 6.0],\
[5.0, 8.0],\
[7.0, 6.0],\
[7.0, 1.0],\
[7.0, 5.0],\
[8.0, 6.0],\
[8.0, 4.0]])

data = BatchOperator.fromDataframe(df, schemaStr="source double, target double")
EdgeClusterCoefficientBatchOp()\
    .setEdgeSourceCol("source")\
    .setEdgeTargetCol("target")\
    .linkFrom(data)\
    .print()

Java 代码

import org.apache.flink.types.Row;

import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import com.alibaba.alink.testutil.AlinkTestBase;
import org.junit.Test;

import java.util.Arrays;

public class EdgeClusterCoefficientBatchOpTest extends AlinkTestBase {
	@Test
	public void test() throws Exception {
		Row[] rows = new Row[] {
			Row.of(1.0, 2.0),
			Row.of(1.0, 3.0),
			Row.of(3.0, 2.0),
			Row.of(5.0, 2.0),
			Row.of(3.0, 4.0),
			Row.of(4.0, 2.0),
			Row.of(5.0, 4.0),
			Row.of(5.0, 1.0),
			Row.of(5.0, 3.0),
			Row.of(5.0, 6.0),
			Row.of(5.0, 8.0),
			Row.of(7.0, 6.0),
			Row.of(7.0, 1.0),
			Row.of(7.0, 5.0),
			Row.of(8.0, 6.0),
			Row.of(8.0, 4.0)
		};
		MemSourceBatchOp dataSource = new MemSourceBatchOp(Arrays.asList(rows), "source double,target double");
		BatchOperator res = new EdgeClusterCoefficientBatchOp()
			.setEdgeSourceCol("source")
			.setEdgeTargetCol("target")
			.linkFrom(dataSource);
		res.print();
	}
}

运行结果

ndoe1	node2	neighbor1	neighbor2	commonNeighbor	edgeClusterCoefficient
7.0000	1.0000	3	4	1	0.3333
3.0000	1.0000	4	4	2	0.5000
6.0000	7.0000	3	3	1	0.3333
7.0000	5.0000	3	7	2	0.6667
4.0000	5.0000	4	7	3	0.7500
3.0000	5.0000	4	7	3	0.7500
1.0000	5.0000	4	7	3	0.7500
6.0000	5.0000	3	7	2	0.6667
8.0000	5.0000	3	7	2	0.6667
2.0000	5.0000	4	7	3	0.7500
3.0000	4.0000	4	4	2	0.5000
4.0000	8.0000	4	3	1	0.3333
6.0000	8.0000	3	3	1	0.3333
4.0000	2.0000	4	4	2	0.5000
3.0000	2.0000	4	4	3	0.7500
1.0000	2.0000	4	4	2	0.5000