flink wordcount示例

pom

完整pom

<?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.msb</groupId>
    <artifactId>StudyFlink</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <flink.version>1.9.2</flink.version>
        <scala.version>2.11.8</scala.version>
        <redis.version>3.2.0</redis.version>
        <hbase.version>1.3.3</hbase.version>
        <mysql.version>5.1.44</mysql.version>
    </properties>
    <dependencies>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-scala_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-scala_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.scala-lang</groupId>
            <artifactId>scala-library</artifactId>
            <version>${scala.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>2.6.5</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.bahir</groupId>
            <artifactId>flink-connector-redis_2.11</artifactId>
            <version>1.0</version>
        </dependency>
        <dependency>
            <groupId>redis.clients</groupId>
            <artifactId>jedis</artifactId>
            <version>${redis.version}</version>
        </dependency>
        <dependency>
            <groupId>mysql</groupId>
            <artifactId>mysql-connector-java</artifactId>
            <version>${mysql.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-client</artifactId>
            <version>${hbase.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-common</artifactId>
            <version>${hbase.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.hbase</groupId>
            <artifactId>hbase-server</artifactId>
            <version>${hbase.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-filesystem_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-statebackend-rocksdb_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-api-scala-bridge_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>

    </dependencies>

    <build>
        <plugins>
            <!-- 在maven项目中既有java又有scala代码时配置 maven-scala-plugin 插件打包时可以将两类代码一起打包 -->
            <plugin>
                <groupId>org.scala-tools</groupId>
                <artifactId>maven-scala-plugin</artifactId>
                <version>2.15.2</version>
                <executions>
                    <execution>
                        <goals>
                            <goal>compile</goal>
                            <goal>testCompile</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>

            <!-- maven 打jar包需要插件 -->
            <plugin>
                <artifactId>maven-assembly-plugin</artifactId>
                <version>2.4</version>
                <configuration>
                    <!-- 设置false后是去掉 MySpark-1.0-SNAPSHOT-jar-with-dependencies.jar 后的 “-jar-with-dependencies” -->
                    <!--<appendAssemblyId>false</appendAssemblyId>-->
                    <descriptorRefs>
                        <descriptorRef>jar-with-dependencies</descriptorRef>
                    </descriptorRefs>
                </configuration>
                <executions>
                    <execution>
                        <id>make-assembly</id>
                        <phase>package</phase>
                        <goals>
                            <goal>assembly</goal>
                        </goals>
                    </execution>
                </executions>
            </plugin>
        </plugins>
    </build>
</project>

scala代码

完整代码

package com.zxl.stream

import org.apache.flink.streaming.api.scala.{DataStream, StreamExecutionEnvironment}
import org.apache.flink.streaming.api.scala._

object WordCount {
  def main(args: Array[String]): Unit = {

    //准备环境
    /**
      * createLocalEnvironment 创建一个本地执行的环境  local
      * createLocalEnvironmentWithWebUI 创建一个本地执行的环境  同时还开启Web UI的查看端口  8081
      * getExecutionEnvironment 根据你执行的环境创建上下文，比如local  cluster
      */
    val env = StreamExecutionEnvironment.getExecutionEnvironment
    /**
      * DataStream：一组相同类型的元素 组成的数据流
      * 如果数据源是scoket  并行度只能是1
      */
    val initStream:DataStream[String] = env.socketTextStream("node01",8888)
    val wordStream = initStream.flatMap(_.split(" ")).setParallelism(3)
    val pairStream = wordStream.map((_,1)).setParallelism(3)
    val keyByStream = pairStream.keyBy(0)
    val restStream = keyByStream.sum(1).setParallelism(3)
    restStream.print()

    /**
      * 6> (msb,1)
      * 1> (,,1)
      * 3> (hello,1)
      * 3> (hello,2)
      * 6> (msb,2)
      * 默认就是有状态的计算
      * 6>  代表是哪一个线程处理的
      * 相同的数据一定是由某一个thread处理
      **/
    //启动Flink 任务
    env.execute("first flink job")
  }
}

启动测试

本地启动

先启动8888端口

nc -lk 8888

运行main方法

实时输入数据，就会进行流计算

默认就是有状态的计算：上次的计算结果给保留了。

      * 6> (msb,1)
      * 1> (,,1)
      * 3> (hello,1)
      * 3> (hello,2)
      * 6> (msb,2)
      * 默认就是有状态的计算
      * 6>  代表是哪一个线程处理的
      * 相同的数据一定是由某一个thread处理

线程数并不是越多越好，线程多了可能启动线程的时间比执行计算用的时间还要多。
并行度为1，只启东一个线程来处理：

此时前面就没有线程号了：

集群环境运行jar

package打包

选择这个jar包：不要选择带依赖的，因为集群环境中已经有这些jar包了，否则就重复了

使用命令提交任务

将jar包上传到节点上，执行如下命令：

• -c 指定主类
• -d 守护进程方式运行

flink run -c 主类 -d jar包路径

查看web ui的Running Jobs

发送数据：

点进去：

可以看到输出：

使用web ui提交任务

可以关闭web ui提交任务：默认是true开启的

vim conf/flink-conf.yaml
web.submit.enable: false #关闭

查看日志