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>
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")
}
}
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：
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
