java - 如何使用 java 创建一个简单的 spark graphframe？

Question

基本上我是一名 Java 开发人员，现在我有机会在 Spark 上工作，我学习了 Spark API 的基础知识，例如 SparkConfig、SparkContaxt、RDD、SQLContaxt、DataFrame、DataSet，然后我能够执行一些简单的操作使用 RDD、SQL 进行简单转换....但是当我尝试使用 java 来锻炼一些示例 graphframe 应用程序时，我无法成功并且我浏览了很多 youtube 教程、论坛和 stackoverflow 线程，但没有找到我找不到的地方任何直接的建议或解决方案。实际上，当我尝试为 GraphFrame 类创建一个对象并且我已经下载了接收 jar(graphframes-0.2.0-spark2.0-s_2.11.jar ) 也是，但现在仍然面临问题我想把我的分析放到我到达的地方，因为我对 Spark 还很陌生，我无法继续前进，所以如果有人帮助我，这对所有人都非常有帮助。提前致谢。异常(exception)是我面临The constructor GraphFrame(DataFrame, DataFrame) is undefined

import java.io.IOException;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;

import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
import org.apache.spark.sql.DataFrame;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.RowFactory;
import org.apache.spark.sql.SQLContext;
import org.apache.spark.sql.types.DataTypes;
import org.apache.spark.sql.types.StructField;
import org.apache.spark.sql.types.StructType;
import org.apache.spark.storage.StorageLevel;
import org.graphframes.GraphFrame;

import com.fasterxml.jackson.core.JsonParseException;
import com.fasterxml.jackson.databind.JsonMappingException;

public class SparkJavaGraphFrameOne {

    public static void main(String[] args) throws JsonParseException, JsonMappingException, IOException{

        SparkConf conf = new SparkConf().setAppName("test").setMaster("local");

        JavaSparkContext sc = new JavaSparkContext(conf);
        SQLContext sqlContext = new org.apache.spark.sql.SQLContext(sc);

        JavaRDD<Row> verRow = sc.parallelize(Arrays.asList(RowFactory.create(1,"A"),RowFactory.create(2,"B")));
        JavaRDD<Row> edgRow = sc.parallelize(Arrays.asList(RowFactory.create(1,2,"Edge")));     

        List<StructField> verFields = new ArrayList<StructField>();
        verFields.add(DataTypes.createStructField("id",DataTypes.IntegerType, true));
        verFields.add(DataTypes.createStructField("name",DataTypes.StringType, true));

        List<StructField> EdgFields = new ArrayList<StructField>();
        EdgFields.add(DataTypes.createStructField("fromId",DataTypes.IntegerType, true));
        EdgFields.add(DataTypes.createStructField("toId",DataTypes.IntegerType, true));
        EdgFields.add(DataTypes.createStructField("name",DataTypes.StringType, true));

        StructType verSchema = DataTypes.createStructType(verFields);
        StructType edgSchema = DataTypes.createStructType(EdgFields);

        DataFrame verDF = sqlContext.createDataFrame(verRow, verSchema);
        DataFrame edgDF = sqlContext.createDataFrame(edgRow, edgSchema);

        GraphFrame g = new GraphFrame(verDF,edgDF);
        g.vertices().show();
        g.edges().show();
        g.persist(StorageLevel.MEMORY_AND_DISK());
    }

}

Answer 1

我使用 Spark 2.0.0 和 GraphFrame 0.2.0 在 Java 中编写了示例程序。该程序基于 http://graphframes.github.io/quick-start.html#start-using-graphframes 中给出的示例程序.希望这会有所帮助。

pom.xml

<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>com.abaghel.examples.spark</groupId>
<artifactId>spark-graphframe</artifactId>
<version>1.0.0-SNAPSHOT</version>

<dependencies>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-core_2.11</artifactId>
        <version>2.0.0</version>
    </dependency>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-graphx_2.11</artifactId>
        <version>2.0.0</version>
    </dependency>
    <dependency>
        <groupId>org.apache.spark</groupId>
        <artifactId>spark-sql_2.11</artifactId>
        <version>2.0.0</version>
    </dependency>
    <dependency>
        <groupId>graphframes</groupId>
        <artifactId>graphframes</artifactId>
        <version>0.2.0-spark2.0-s_2.11</version>
    </dependency>
</dependencies>

<repositories>
    <!-- list of other repositories -->
    <repository>
        <id>SparkPackagesRepo</id>
        <url>http://dl.bintray.com/spark-packages/maven</url>
    </repository>
 </repositories>
 <build>
    <plugins>
        <plugin>
            <groupId>org.apache.maven.plugins</groupId>
            <artifactId>maven-compiler-plugin</artifactId>
            <version>3.1</version>
            <configuration>
                <source>1.8</source>
                <target>1.8</target>
            </configuration>
        </plugin>
    </plugins>
  </build>
</project>

SparkGraphFrameSample.java

package com.abaghel.examples.spark.graphframe;

import java.util.ArrayList;
import java.util.List;

import org.apache.spark.sql.Dataset;
import org.apache.spark.sql.Row;
import org.apache.spark.sql.SparkSession;
import org.graphframes.GraphFrame;
import org.graphframes.lib.PageRank;
/**
 * Sample application shows how to create a GraphFrame, query it, and run the PageRank algorithm.
 * 
 * @author abaghel
 *
 */
public class SparkGraphFrameSample {

 public static void main(String[] args) {
    SparkSession spark = SparkSession.builder()
            .appName("SparkGraphFrameSample")
            .config("spark.sql.warehouse.dir", "/file:C:/temp")
            .master("local[2]")
            .getOrCreate();

    //Create a Vertex DataFrame with unique ID column "id"
    List<User> uList = new ArrayList<User>() {
        {
            add(new User("a", "Alice", 34));
            add(new User("b", "Bob", 36));
            add(new User("c", "Charlie", 30));
        }
    };

    Dataset<Row> verDF = spark.createDataFrame(uList, User.class);

    //Create an Edge DataFrame with "src" and "dst" columns
    List<Relation> rList = new ArrayList<Relation>() {
        {
            add(new Relation("a", "b", "friend"));
            add(new Relation("b", "c", "follow"));
            add(new Relation("c", "b", "follow"));
        }
    };

    Dataset<Row> edgDF = spark.createDataFrame(rList, Relation.class);

    //Create a GraphFrame
    GraphFrame gFrame = new GraphFrame(verDF, edgDF);
    //Get in-degree of each vertex.
    gFrame.inDegrees().show();
    //Count the number of "follow" connections in the graph.
    long count = gFrame.edges().filter("relationship = 'follow'").count();
    //Run PageRank algorithm, and show results.
    PageRank pRank = gFrame.pageRank().resetProbability(0.01).maxIter(5);
    pRank.run().vertices().select("id", "pagerank").show();

    //stop
    spark.stop();
  }

}

用户.java

package com.abaghel.examples.spark.graphframe;
/**
 * User class
 * 
 * @author abaghel
 *
 */
public class User {
private String id;
private String name;
private int age;

public User(){      
}

public User(String id, String name, int age) {
    super();
    this.id = id;
    this.name = name;
    this.age = age;
}

public String getId() {
    return id;
}
public void setId(String id) {
    this.id = id;
}
public String getName() {
    return name;
}
public void setName(String name) {
    this.name = name;
}
public int getAge() {
    return age;
}
public void setAge(int age) {
    this.age = age;
 }
}

关系.java

package com.abaghel.examples.spark.graphframe;
/**
 * Relation class
 * 
 * @author abaghel
 *
 */
public class Relation {

private String src;
private String dst;
private String relationship;

public Relation(){

}

public Relation(String src, String dst, String relationship) {
    super();
    this.src = src;
    this.dst = dst;
    this.relationship = relationship;
}

public String getSrc() {
    return src;
}

public void setSrc(String src) {
    this.src = src;
}

public String getDst() {
    return dst;
}

public void setDst(String dst) {
    this.dst = dst;
}

public String getRelationship() {
    return relationship;
}

public void setRelationship(String relationship) {
    this.relationship = relationship;
  }

}

控制台输出

16/08/27 22:34:45 INFO DAGScheduler: Job 10 finished: show at    SparkGraphFrameSample.java:56, took 0.938910 s
16/08/27 22:34:45 INFO CodeGenerator: Code generated in 6.599005 ms
+---+-------------------+
| id|           pagerank|
+---+-------------------+
|  a|               0.01|
|  b|0.08763274109799998|
|  c|     0.077926810699|
+---+-------------------+