TinkerPop中使用Spark on Yarn模式运行OLA

作者: Woople | 来源:发表于2019-12-07 21:33 被阅读0次

TinkerPop中可以结合SparkGraphComputer和HadoopGraph实现使用大数据集群资源分布式对图进行OLAP。官方文档只是介绍了使用The Gremlin Console进行OLAP，但是实际的生产环境中通常还是需要写程序打成jar包来执行的。本文将介绍如何使用java -cp的方式执行程序实现spark on yarn。

客户端程序

将官网提供的样例Using CloneVertexProgram改造成java程序，业务逻辑很简单，加载hdfs上的原始数据文件tinkerpop-modern.json(官方提供)生成图，然后通过CloneVertexProgram复制这个图并将复制后的图以json的格式再存储到hdfs中。

public class HadoopGraphSparkComputerDemo {
    public static void main(String[] args) throws Exception {
        FileConfiguration configuration = new PropertiesConfiguration();
        configuration.load(new File(args[0]));

        final Configuration hadoopConfig = new Configuration(false);

        if ("kerberos".equalsIgnoreCase(hadoopConfig.get("hadoop.security.authentication"))) {//1

            UserGroupInformation.setConfiguration(hadoopConfig);
            try {
                UserGroupInformation userGroupInformation =
                        UserGroupInformation.loginUserFromKeytabAndReturnUGI(configuration.getString("user.principal"), configuration.getString("user.keytab"));
                UserGroupInformation.setLoginUser(userGroupInformation);

                System.out.println("Login successfully!");
            } catch (Exception e) {
                e.printStackTrace();
            }
        }

        HadoopGraph graph = HadoopGraph.open(configuration);
        graph.compute(SparkGraphComputer.class).program(CloneVertexProgram.build().create()).submit().get();
    }
}

适配Kerberos环境
最后一行就是执行复制图的操作

配置文件

创建一个配置文件hadoop-graphson.properties，内容如下

# the graph class
gremlin.graph=org.apache.tinkerpop.gremlin.hadoop.structure.HadoopGraph
# 输入输出都是json格式
gremlin.hadoop.graphReader=org.apache.tinkerpop.gremlin.hadoop.structure.io.graphson.GraphSONInputFormat
gremlin.hadoop.graphWriter=org.apache.tinkerpop.gremlin.hadoop.structure.io.graphson.GraphSONOutputFormat
# 输入数据源的路径
gremlin.hadoop.inputLocation=/tmp/tinkerpop-modern.json
#输出结果的路径
gremlin.hadoop.outputLocation=/tmp/output
# if the job jars are not on the classpath of every hadoop node, then they must be provided to the distributed cache at runtime
gremlin.hadoop.jarsInDistributedCache=true

####################################
# SparkGraphComputer Configuration #
####################################
spark.master=yarn
#SparkGraphComputer只支持client模式
spark.submit.deployMode=client
#spark on yarn运行时依赖jar包的路径
spark.yarn.jars=/tmp/graph-jars/*.jar
spark.driver.extraJavaOptions=-Dhdp.version=2.6.0.3-8
spark.yarn.am.extraJavaOptions=-Dhdp.version=2.6.0.3-8

spark.serializer=org.apache.spark.serializer.KryoSerializer
spark.kryo.registrator=org.apache.tinkerpop.gremlin.spark.structure.io.gryo.GryoRegistrator
user.principal=user@AA.COM
user.keytab=/tmp/hdfs.headless.keytab

程序编译

将必要的依赖都定义在pom文件中，然后使用maven-dependency-plugin插件在编译的时候会将依赖的jar放到lib目录

<?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>com.woople</groupId>
    <artifactId>graph-tutorials</artifactId>
    <version>1.0-SNAPSHOT</version>

    <dependencies>
        <dependency><!--required-->
            <groupId>org.apache.tinkerpop</groupId>
            <artifactId>gremlin-core</artifactId>
            <version>3.4.4</version>
        </dependency>
        <dependency><!--required-->
            <groupId>org.apache.tinkerpop</groupId>
            <artifactId>tinkergraph-gremlin</artifactId>
            <version>3.4.4</version>
        </dependency>
        <dependency><!--required-->
            <groupId>org.apache.tinkerpop</groupId>
            <artifactId>spark-gremlin</artifactId>
            <version>3.4.4</version>
        </dependency>
        <dependency><!--required-->
            <groupId>org.apache.tinkerpop</groupId>
            <artifactId>hadoop-gremlin</artifactId>
            <version>3.4.4</version>
        </dependency>
        <dependency><!--required-->
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-yarn_2.11</artifactId>
            <version>2.4.0</version>
        </dependency>
        <dependency><!--required-->
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-reflect</artifactId>
            <version>2.11.8</version>
        </dependency>
        <dependency><!--required-->
            <groupId>com.sun.jersey</groupId>
            <artifactId>jersey-core</artifactId>
            <version>1.9</version>
        </dependency>
        <dependency><!--required-->
            <groupId>com.sun.jersey</groupId>
            <artifactId>jersey-client</artifactId>
            <version>1.9</version>
        </dependency>

        <dependency>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
            <version>1.2.17</version>
        </dependency>

        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>1.7.28</version>
        </dependency>
        <dependency>
            <groupId>ch.qos.logback</groupId>
            <artifactId>logback-classic</artifactId>
            <version>1.2.3</version>
        </dependency>
        <dependency>
            <groupId>ch.qos.logback</groupId>
            <artifactId>logback-core</artifactId>
            <version>1.2.3</version>
        </dependency>
    </dependencies>
    <build>
        <defaultGoal>package</defaultGoal>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-resources-plugin</artifactId>
                <configuration>
                    <encoding>UTF-8</encoding>
                </configuration>
                <executions>
                    <execution>
                        <goals>
                            <goal>copy-resources</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <version>3.2.2</version>
                <executions>
                    <execution>
                        <id>eclipse-add-source</id>
                        <goals>
                            <goal>add-source</goal>
                        </goals>
                    </execution>
                    <execution>
                        <id>scala-compile-first</id>
                        <phase>process-resources</phase>
                        <goals>
                            <goal>compile</goal>
                        </goals>
                    </execution>
                    <execution>
                        <id>scala-test-compile-first</id>
                        <phase>process-test-resources</phase>
                        <goals>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                    <execution>
                        <id>attach-scaladocs</id>
                        <phase>verify</phase>
                        <goals>
                            <goal>doc-jar</goal>
                        </goals>
                    </execution>
                </executions>
                <configuration>
                    <scalaVersion>2.11.8</scalaVersion>
                    <recompileMode>incremental</recompileMode>
                    <useZincServer>true</useZincServer>
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.5.1</version>
                <executions>
                    <execution>
                        <phase>compile</phase>
                        <goals>
                            <goal>compile</goal>
                        </goals>
                    </execution>
                </executions>
                <configuration>
                    <source>8</source>
                    <target>8</target>
                </configuration>
            </plugin>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-dependency-plugin</artifactId>
                <version>3.1.1</version>
                <executions>
                    <execution>
                        <id>copy-dependencies</id>
                        <phase>prepare-package</phase>
                        <goals>
                            <goal>copy-dependencies</goal>
                        </goals>
                        <configuration>
                            <outputDirectory>${project.build.directory}/lib</outputDirectory>
                            <overWriteReleases>false</overWriteReleases>
                            <overWriteSnapshots>false</overWriteSnapshots>
                            <overWriteIfNewer>true</overWriteIfNewer>
                        </configuration>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

部署运行

将上一步编译时在lib下生成的所有依赖的jar放到spark.yarn.jars所指定的hdfs路径
将生成的lib文件夹、graph-tutorials-1.0-SNAPSHOT.jar放到运行环境，例如/opt/graph-tutorials
把hadoop-graphson.properties、core-site.xml、hdfs-site.xml和yarn-site.xml放到指定目录，例如/opt/graph-tutorials/conf
cd /opt/graph-tutorials然后执行java -cp lib/*:conf:graph-tutorials-1.0-SNAPSHOT.jar com.woople.tinkerpop.gremlin.HadoopGraphSparkComputerDemo hadoop-graphson.properties

总结

在调试过程中遇到的问题主要是hadoop相关配置文件加载不到，jar包冲突，缺少类等问题。需要注意的是要根据tinkerpop的版本选择spark版本。本文完整示例请参考graph-tutorials。

TinkerPop中使用Spark on Yarn模式运行OLA

客户端程序

配置文件

程序编译

部署运行

总结

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