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Node2Vec游走 (Node2VecWalkBatchOp)

Java 类名：com.alibaba.alink.operator.batch.graph.Node2VecWalkBatchOp

Python 类名：Node2VecWalkBatchOp

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
sourceCol 起始点列名 用来指定起始点列 String ✓ 所选列类型为 [INTEGER, LONG, STRING]
targetCol 中止点点列名 用来指定中止点列 String ✓ 所选列类型为 [INTEGER, LONG, STRING]
walkLength 游走的长度 随机游走完向量的长度 Integer ✓
walkNum 路径数目 每一个起始点游走出多少条路径 Integer ✓
delimiter 分隔符 用来分割字符串 String “ ”
isToUndigraph 是否转无向图 选为true时，会将当前图转成无向图，然后再游走 Boolean false
p 算法参数P 控制随机游走序列的跳转概率 Double 1.0
q 算法参数Q 控制随机游走序列的跳转概率 Double 1.0
samplingMethod 起始点列名 用来指定起始点列 String “ALIAS”
weightCol 权重列名 权重列对应的列名 String 所选列类型为 [BIGDECIMAL, BIGINTEGER, BYTE, DOUBLE, FLOAT, INTEGER, LONG, SHORT] null

代码示例

Python 代码

from pyalink.alink import *

import pandas as pd

useLocalEnv(1)

df = pd.DataFrame([
    [1, 1, 1.0],
    [1, 2, 1.0],
    [2, 3, 1.0],
    [3, 4, 1.0],
    [4, 2, 1.0],
    [3, 1, 1.0],
    [2, 4, 1.0],
    [4, 1, 1.0]])

source = BatchOperator.fromDataframe(df, schemaStr="start int, dest int, weight double")

n2vWalkBatchOp = Node2VecWalkBatchOp() \
                .setWalkNum(4) \
                .setWalkLength(50) \
                .setDelimiter(",") \
                .setSourceCol("start") \
                .setTargetCol("dest") \
                .setIsToUndigraph(True) \
                .setWeightCol("weight")

n2vWalkBatchOp.linkFrom(source).print()

Java 代码

import org.apache.flink.types.Row;

import com.alibaba.alink.operator.batch.BatchOperator;
import com.alibaba.alink.operator.batch.graph.Node2VecWalkBatchOp;
import com.alibaba.alink.operator.batch.source.MemSourceBatchOp;
import org.junit.Test;

import java.util.Arrays;
import java.util.List;

public class Node2VecWalkBatchOpTest {
	@Test
	public void testNode2VecWalkBatchOp() throws Exception {
		List <Row> df = Arrays.asList(
			Row.of(1, 1, 1.0),
			Row.of(1, 2, 1.0),
			Row.of(2, 3, 1.0),
			Row.of(3, 4, 1.0),
			Row.of(4, 2, 1.0),
			Row.of(3, 1, 1.0),
			Row.of(2, 4, 1.0)
		);
		BatchOperator <?> source = new MemSourceBatchOp(df, "start int, dest int, weight double");
		BatchOperator <?> n2vWalkBatchOp = new Node2VecWalkBatchOp()
			.setWalkNum(4)
			.setWalkLength(50)
			.setDelimiter(",")
			.setSourceCol("start")
			.setTargetCol("dest")
			.setIsToUndigraph(true)
			.setWeightCol("weight");
		n2vWalkBatchOp.linkFrom(source).print();
	}
}

运行结果

path
3,2,1,1,4,2,3,4,2,1,3,1,1,1,3,1,3,4,1,2,4,3,2,1,1,3,2,4,3,4,1,4,2,1,2,1,4,3,1,2,1,3,4,2,4,3,2,3,4,1
2,3,2,4,2,1,2,3,2,3,2,4,3,1,2,3,4,2,4,2,3,2,3,2,4,2,1,3,1,4,1,1,4,2,1,2,4,1,3,1,1,3,4,2,4,2,3,4,2,4
4,2,1,4,1,1,1,2,3,4,2,3,2,3,2,4,1,2,3,2,1,2,4,3,1,1,2,4,3,4,2,4,1,2,4,3,1,4,2,4,2,1,3,4,2,1,2,4,3,4
4,3,1,1,1,3,4,3,4,1,2,4,2,3,2,1,1,1,2,3,4,1,2,4,3,4,3,1,4,2,3,2,4,1,1,1,3,1,3,2,4,2,4,3,1,1,1,3,2,1
4,3,1,1,3,2,3,1,4,1,2,1,3,4,3,4,2,1,2,4,2,3,4,2,4,2,4,2,3,1,4,3,2,4,1,2,3,2,1,1,3,1,1,4,1,4,1,4,1,2
1,3,4,1,2,3,1,3,4,2,1,4,3,2,1,3,1,4,1,4,3,1,4,2,1,2,3,4,3,4,2,3,4,3,4,1,1,1,1,2,4,1,2,4,1,2,4,2,3,1
3,4,1,4,1,2,1,3,2,4,2,1,2,3,1,4,1,2,4,2,4,3,4,3,2,3,2,1,2,1,1,1,4,2,3,4,1,1,4,2,3,4,3,1,4,3,4,1,4,3
2,3,1,3,4,1,1,1,4,3,4,1,2,3,2,1,1,3,4,3,2,3,1,3,4,3,2,1,4,3,1,1,2,4,2,1,3,1,3,1,2,3,1,4,3,2,1,2,1,1
1,2,1,3,1,4,2,3,2,1,3,4,2,4,3,4,2,4,2,1,4,3,2,3,4,1,4,2,1,4,1,3,4,2,1,4,1,4,3,1,3,2,4,1,1,4,1,1,2,3
1,2,4,2,1,2,4,3,4,3,4,3,1,2,1,2,3,2,3,4,2,4,3,2,3,2,3,1,1,1,4,2,1,4,1,2,1,2,1,1,2,4,2,1,4,2,3,1,1,4
3,4,1,1,1,2,4,2,4,1,1,1,2,3,2,4,2,1,2,3,4,1,1,3,4,1,2,4,3,2,1,1,4,1,2,1,2,4,2,4,1,3,4,2,1,3,4,3,2,1
3,2,3,4,3,1,2,4,2,4,1,2,3,4,3,1,2,4,3,2,3,2,3,2,3,4,3,2,4,3,4,2,4,3,1,1,4,1,4,1,3,1,2,3,4,1,4,3,4,2
1,4,2,4,1,4,1,2,1,1,2,3,1,4,3,4,1,3,1,3,4,2,4,3,2,3,2,3,4,1,3,2,3,4,2,3,4,1,2,4,2,3,4,3,2,3,1,4,2,3
2,4,3,1,1,3,1,2,4,2,4,3,2,1,2,4,3,2,3,1,1,3,2,1,3,1,4,1,3,1,1,1,1,2,1,3,1,1,3,4,2,1,2,1,1,2,4,3,1,2
4,2,1,4,3,2,1,1,3,1,4,1,3,2,4,2,4,2,4,3,4,1,3,4,2,3,2,1,3,1,1,1,4,2,1,2,4,1,4,2,1,4,1,2,4,2,1,4,1,2
2,4,1,4,3,2,1,3,1,3,1,4,1,2,4,1,3,4,2,1,1,3,1,3,1,1,1,1,1,2,4,1,4,3,1,2,1,2,4,1,3,4,1,2,3,1,4,2,4,3