阿龙学堂-SparkGraphx基本操作篇-第一篇
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2022-07-14 21:57:47
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0、需求实现
我们要构建一个由 GraphX 项目上的各种协作者组成的属性图。vertex 属性可能包含用户名和职业。我们可以使用描述协作者之间关系的字符串来注释边:
1、加载已有测试数据
1.1、加载依赖
<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
<modelVersion>4.0.0</modelVersion>
<groupId>cn.along.com</groupId>
<artifactId>along-root</artifactId>
<version>1.0-SNAPSHOT</version>
<properties>
<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
<spark.version>2.0.2</spark.version>
<hbase.version>1.3.1</hbase.version>
<hadoop.version>2.7.5</hadoop.version>
<scala.version>2.11.8</scala.version>
</properties>
<dependencies>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-core_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-sql_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.apache.spark</groupId>
<artifactId>spark-mllib_2.11</artifactId>
<version>${spark.version}</version>
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-library</artifactId>
<version>${scala.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-compiler</artifactId>
<version>${scala.version}</version>
<scope>provided</scope>
</dependency>
<dependency>
<groupId>org.scala-lang</groupId>
<artifactId>scala-reflect</artifactId>
<version>${scala.version}</version>
<scope>provided</scope>
</dependency>
</dependencies>
<build>
<sourceDirectory>src/main/scala</sourceDirectory>
<testSourceDirectory>src/test/scala</testSourceDirectory>
<finalName>networdcount</finalName>
<plugins>
<plugin>
<groupId>org.apache.maven.plugins</groupId>
<artifactId>maven-assembly-plugin</artifactId>
<configuration>
<archive>
<manifest>
<mainClass>cn.itcast.streaming.WorldCount</mainClass>
</manifest>
</archive>
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
</configuration>
</plugin>
</plugins>
</build>
</project>
1.2、代码实现
def main(args: Array[String]): Unit = {
//准备环境
val conf: SparkConf = new SparkConf().setAppName("test1").setMaster("local[4]")
val sc = new SparkContext(conf)
sc.setLogLevel("WARN")
//读取数据
val vertex: RDD[(VertexId, (String, String))] = sc.parallelize(Array(
(3L, ("rxin", "stu")),
(2L, ("istoic", "prof")),
(5L, ("franklin", "prof")),
(7L, ("jgzal", "postdoc"))))
//准备顶点
//准备边
val edge: RDD[Edge[String]] = sc.parallelize(Array(Edge(3L, 7L, "collab"),
Edge(5L, 3L, "Adavisor"), Edge(2L, 5L, "Collaeage"), Edge(8L, 7L, "PI")))
//构建图
val defaultUser = ("wilson", "Missing")
val graph = Graph(vertex, edge, defaultUser)
//顶点集合
val vertices: VertexRDD[(String, String)] = graph.vertices
//边集合
val edges: EdgeRDD[String] = graph.edges
//释放资源
sc.stop()
}
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