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Scala实现Kafka生产者与消费者实例

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测试文本内容:(hanzi.txt)

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(一)maven构建

<?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">
    <parent>
        <artifactId>SSO-Scala</artifactId>
        <groupId>org.jy.data.yh.bigdata.drools.scala</groupId>
        <version>1.0-SNAPSHOT</version>
    </parent>
    <modelVersion>4.0.0</modelVersion>

    <groupId>org.jy.bigdata.drools.scala.kafka.freq</groupId>
    <artifactId>SSO-Scala-kafka-streaming</artifactId>
    <!--<version>1.0-SNAPSHOT</version>-->
    <name>SSO-Scala-kafka-streaming</name>

    <properties>
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <maven.compiler.source>1.8</maven.compiler.source>
        <maven.compiler.target>1.8</maven.compiler.target>
        <scala.version>2.11.8</scala.version>
        <spark.version>2.4.0</spark.version>
    </properties>

    <repositories>
        <repository>
            <id>repos</id>
            <name>Repository</name>
            <url>http://maven.aliyun.com/nexus/content/groups/public</url>
        </repository>
        <repository>
            <id>scala-tools.org</id>
            <name>Scala-Tools Maven2 Repository</name>
            <url>http://scala-tools.org/repo-releases</url>
        </repository>
    </repositories>

    <pluginRepositories>
        <pluginRepository>
            <id>repos</id>
            <name>Repository</name>
            <url>http://maven.aliyun.com/nexus/content/groups/public</url>
        </pluginRepository>
        <pluginRepository>
            <id>scala-tools.org</id>
            <name>Scala-Tools Maven2 Repository</name>
            <url>http://scala-tools.org/repo-releases</url>
        </pluginRepository>
    </pluginRepositories>

    <dependencies>
        <!--Spark Core核心依赖-->
        <dependency> <!-- Spark ,依赖的Scala版本为Scala 2.12.x版本 (View all targets) 否则会报错
                           java.lang.NoSuchMethodError: scala.Predef$.refArrayOps([Ljava/lang/Object;)[Ljava/lang/Object; -->
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-core_2.11</artifactId>
            <version>2.4.0</version>
            <!--<scope>provided</scope>--><!--运行时提供,打包不添加,Spark集群已自带-->
        </dependency>
        <!-- Spark SQL核心依赖-->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-sql_2.11</artifactId>
            <version>2.4.0</version>
            <!--<scope>provided</scope>--><!--运行时提供,打包不添加,Spark集群已自带-->
        </dependency>
        <!-- Spark Streaming依赖包-->
        <dependency>
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming_2.11</artifactId>
            <version>2.4.0</version>
            <!--<scope>provided</scope>--><!--运行时提供,打包不添加,Spark集群已自带-->
        </dependency>
        <dependency><!-- Spark Streaming with Kafka 版本要与scala匹配-->
            <groupId>org.apache.spark</groupId>
            <artifactId>spark-streaming-kafka-0-10_2.11</artifactId>
            <version>${spark.version}</version>
        </dependency>
        <dependency><!-- Mysql -->
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>5.1.31</version>
        </dependency>
        <!--数据库连接池-->
        <dependency>
            <groupId>c3p0</groupId>
            <artifactId>c3p0</artifactId>
            <version>0.9.1.2</version>
        </dependency>
        <dependency><!-- JSON -->
            <groupId>io.spray</groupId>
            <artifactId>spray-json_2.10</artifactId>
            <version>1.3.2</version>
        </dependency>
        <dependency><!-- Http -->
            <groupId>org.scalaj</groupId>
            <artifactId>scalaj-http_2.10</artifactId>
            <version>2.3.0</version>
        </dependency>
        <dependency><!-- Time Parse -->
            <groupId>joda-time</groupId>
            <artifactId>joda-time</artifactId>
            <version>2.9.4</version>
        </dependency>

        <dependency><!-- Log -->
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
            <version>1.2.17</version>
        </dependency>
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.12</version>
        </dependency>
        <!-- 2.12.x需要与spark的2.12对应-->
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
        </dependency>
    </dependencies>

    <build>
        <finalName>SSO-Analysis-system</finalName>
        <sourceDirectory>src/main/scala</sourceDirectory>
        <testSourceDirectory>src/test/scala</testSourceDirectory>
        <plugins>
            <!-- 混合Scala/Java编译-->
            <plugin><!--Scala编译插件 -->
                <groupId>org.scala-tools</groupId>
                <artifactId>maven-scala-plugin</artifactId>
                <version>2.15.2</version>
                <executions>
                    <execution>
                        <id>scala-compile-first</id>
                        <goals>
                            <goal>compile</goal>
                        </goals>
                        <configuration>
                            <includes>
                                <include>**/*.scala</include>
                            </includes>
                        </configuration>
                    </execution>
                    <execution>
                        <id>scala-test-compile</id>
                        <goals>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <version>3.1</version>
                <configuration>
                    <source>1.8</source><!-- 设置Java源-->
                    <target>1.8</target>
                </configuration>
            </plugin>

            <plugin><!-- 将所有的依赖包打入同一个jar包-->
                <artifactId>maven-assembly-plugin</artifactId>
                <configuration>
                    <appendAssemblyId>false</appendAssemblyId>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef><!--jar包的后缀名-->
                    </descriptorRefs>
                    <archive>
                        <manifest>
                            <mainClass>org.jy.bigdata.drools.scala.data.freq.main.KafkaProducer</mainClass>
                        </manifest>
                    </archive>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
            <plugin><!--Maven打包插件 -->
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-jar-plugin</artifactId>
                <version>2.4</version>
                <configuration>
                    <archive>
                        <manifest>
                            <addClasspath>true</addClasspath><!--添加类路径-->
                            <!--设置程序的入口类-->
                            <mainClass>org.jy.bigdata.drools.scala.data.freq.main.KafkaProducer</mainClass>
                        </manifest>
                    </archive>
                </configuration>
            </plugin>
        </plugins>
    </build>
</project>

(二)生产者(完整代码D:\\Bigdata-Drools-platform\\SSO-Scala\\SSO-Scala-Kafka-streaming\\hanzi.txt 该路径为本地测试文本)

package org.jy.bigdata.drools.scala.data.freq.main

import java.util.Properties
import org.apache.kafka.clients.producer.{KafkaProducer, ProducerRecord}
import scala.util.Random
/**
  * 用户生成模拟数据的生产者
  */
object KafkaProducerStream extends App {  // App为scala中的特质,实现了main方法
  @Override
  override def main(args: Array[String]): Unit = {
      val rnd = new Random()
      val events = 100000  // 一万条消息
      val props = new Properties()
      props.put("bootstrap.servers","node-1:9092,node-2:9092,node-3:9092")  // broker集群地址
      props.put("client.id","KafkaFreqGenerator")
      props.put("key.serializer","org.apache.kafka.common.serialization.StringSerializer")   // 可以序列化
      props.put("value.serializer","org.apache.kafka.common.serialization.StringSerializer")  // value 序列化

      val producer = new KafkaProducer[String,String](props) // 创建kafka对象
      val startTime = System.currentTimeMillis();// 毫秒时间

      // 读取汉字字典 /home/hadoop/tools/jsonfile/  当前工作目录
      val source = scala.io.Source.fromFile("D:\\Bigdata-Drools-platform\\SSO-Scala\\SSO-Scala-Kafka-streaming\\hanzi.txt")  // 从指定的目录读取文本文件
      val lines = try source.mkString finally source.close()  // try finally 使用技巧
      for (nEvents <- Range(0,events)){ // 循环生成一万条用户的评论数据
      // 模拟评论数据(user,comment)
        val sb = new StringBuilder()
        for(ind <- Range(0,rnd.nextInt(200))){
          sb += lines.charAt(rnd.nextInt(lines.length()))
        }
        val userName = "user_"+rnd.nextInt(100)
        //println("<message content> :"+sb.toString())
        val data = new ProducerRecord[String,String]("freqCountTopic",userName,sb.toString())   // userName --  key sb.toString()为值
        // 发送评论到kafka
        val futureCallback=producer.send(data)
        val answer = futureCallback.get()
        val topic =answer.topic();
        //println("messege has sended : "+topic)
      }
    System.out.println("send per second: "+events*1000/(System.currentTimeMillis()-startTime))
    producer.close()
  }

}

(三) 消费者实例代码

package org.jy.bigdata.drools.scala.data.freq.main

import java.time.Duration
import java.util.concurrent._
import java.util.{Collections, Properties}
import scala.collection.JavaConversions._
import org.apache.kafka.clients.consumer.{ConsumerConfig, KafkaConsumer}

/**
  * 创建消费消息的实体类
  */
class KafkaProducerConsumer(val brokers:String,
                                val groupId:String,
                                val topic:String ) {  // 伴生类
  val props  = createCunsumerConfig(brokers,groupId)
  val consumer = new KafkaConsumer[String,String](props)

  def shutdown() = {  // 关闭函数
    if(consumer != null)
      consumer.close()
  }
  // 定义类中的方法
  def createCunsumerConfig(brokers: String,groupId: String): Properties ={  // 定义类中的方法
    val props = new Properties()
    props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG,brokers) // 设置kafaka集群地址
    props.put(ConsumerConfig.GROUP_ID_CONFIG,groupId)
    props.put(ConsumerConfig.ENABLE_AUTO_COMMIT_CONFIG,"true") // 设置自动提交
    props.put(ConsumerConfig.AUTO_COMMIT_INTERVAL_MS_CONFIG,"1000")
    props.put(ConsumerConfig.SESSION_TIMEOUT_MS_CONFIG,"30000")
    props.put(ConsumerConfig.KEY_DESERIALIZER_CLASS_CONFIG,"org.apache.kafka.common.serialization.StringDeserializer")
    props.put(ConsumerConfig.VALUE_DESERIALIZER_CLASS_CONFIG,"org.apache.kafka.common.serialization.StringDeserializer")
    return props
  }
  // 定义无返回值的方法
  def run()={
    consumer.subscribe(Collections.singletonList(this.topic)) // 一个topic主题数组

    Executors.newSingleThreadExecutor.execute(new Runnable {
      override def run(): Unit = {  // 覆盖run方法
        while (true) {
          val records = consumer.poll(Duration.ofSeconds(1000)) // 1秒钟拉一次
          for (record <- records) {
            System.out.println("Received message: (" + record.key() + ", " + record.value() + ") at offset " + record.offset())
          }
        }
      }
    })
  }
}

object KafkaProducerConsumer extends App {  // 伴生对象
  override def main(args: Array[String]): Unit = {
    val brokers = "node-1:9092,node-2:9092,node-3:9092"
    val groupId ="KafkaProducerConsumerGroup"
    val topic ="freqCountTopic"
    val example = new KafkaProducerConsumer(brokers,groupId,topic)
    example.run()
  }

}

测试结果如下图

 

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