Scala编写批处理和流处理wordcount

这部分，我们在idea上使用Maven编写Scala程序实现批处理wordcount功能。

pow文件依赖配置

pow文件需要如下依赖，这里注意scala版本必须要和flink安装包适配的版本一致：

<dependencies>
       <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-scala_2.11</artifactId>
            <version>1.10.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-scala_2.11</artifactId>
            <version>1.10.1</version>
        </dependency>
</dependencies>

<build>
      <plugins>
            <plugin>
                <groupId>net.alchim31.maven</groupId>
                <artifactId>scala-maven-plugin</artifactId>
                <version>4.4.0</version>
                <executions>
                    <execution>
                        <goals>
                            <goal>compile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>

            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>3.3.0</version>
                <configuration>
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>single</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
    </plugins>
</build>

批处理wordcount

之后我们准备好输入文本，并编写相应Scala代码：

hello.txt文本如下：

hello world
hello flink
hello scala
how are you
fine thank you
and you

scala文件WordCount脚本代码如下：

package com.example.wc

import org.apache.flink.api.scala.ExecutionEnvironment
import org.apache.flink.api.scala._

//批处理的word count
object WordCount {
  def main(args: Array[String]): Unit = {
    //创建一个批处理
    val env: ExecutionEnvironment = ExecutionEnvironment.getExecutionEnvironment

    //从文件中读取数据
    val inputPath:String = "/Users/wenhuan/IdeaProjects/FlinkTutorial/src/main/resources/hello.txt"
    val inputDataSet:DataSet[String] = env.readTextFile(inputPath)

    //对数据进行转换处理统计，先分词
    val resultDataSet:DataSet[(String,Int)] = inputDataSet
      .flatMap(_.split(" "))
      .map((_,1))
      .groupBy(0)
      .sum(1)

    //打印输出
    resultDataSet.print()
  }
}

流处理wordcount

scala文件WordCount脚本代码如下：

package com.example.wc

import org.apache.flink.api.java.utils.ParameterTool
import org.apache.flink.streaming.api.scala.StreamExecutionEnvironment
import org.apache.flink.streaming.api.scala._


// 流式处理word count
object StreamWordCount {
  def main(args: Array[String]): Unit = {
    //创建流处理的执行环境
    val env:StreamExecutionEnvironment = StreamExecutionEnvironment.getExecutionEnvironment
    //设置并行度
    //env.setParallelism(2)

    //从外部命令中提取参数，作为socket主机名和端口号
    val paramTool:ParameterTool = ParameterTool.fromArgs(args)
    val host:String = paramTool.get("host")
    val port:Int = paramTool.getInt("port")

    //接收一个socket文本流
    val inputDataStream:DataStream[String] = env.socketTextStream(host,port)
    //进行转化处理统计
    val resultDataStream:DataStream[(String,Int)] = inputDataStream
      .flatMap(x => x.split(" "))
      .filter(_.nonEmpty)
      .map((_,1))
      .keyBy(0)
      .sum(1)

    resultDataStream.print()

    //启动任务执行
    env.execute("stream word count")
  }
}

idea运行时需要配置Program arguments如下：

--host localhost --port 7777

开启本地nc -lk服务：

nc -lk 7777

然后执行上述代码即可。

任务提交执行

flink任务提交执行有两种方式，第一种是在网页直接提交，另一种是命令行方式。

命令行方式

提交任务命令如下：

./bin/flink run -c com.example.wc.StreamWordCount -p 1 ./FlinkTutorial-1.0-SNAPSHOT-jar-with-dependencies.jar --host localhost --port 7777

查看当前正在运行任务命令如下：

./bin/flink list

停止正在运行任务的命令如下:

./bin/flink cancel <jobid>