一.flink整体介绍及wordcount案例代码

1.1整体介绍

从上到下包含有界无界流 支持状态 特点 与spark对比 应用场景 架构分层

 1.2示例代码

了解了后就整个demo吧

数据源准备 这里直接用的文本文件

gradle中的主要配置

group = 'com.example'
version = '0.0.1-SNAPSHOT'java {sourceCompatibility = '11'
}repositories {mavenCentral()
}dependencies {implementation group: 'org.apache.flink', name: 'flink-streaming-java', version: '1.17.0'implementation group: 'org.apache.flink', name: 'flink-clients', version: '1.17.0'}

 代码

package com.example.flinktest.test;import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;public class FlinkTurotial1_17 {public static void main(String[] args) throws Exception {//todo 1.创建执行环境StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();env.setParallelism(1);//todo 2.读取数据DataStreamSource<String> stringDataStreamSource = env.readTextFile("D:\\juege\\code\\hope-backend\\opentech\\src\\main\\resources\\flinkTextSource.txt");//todo 3.进行数据处理 先 flatmap 再 keyby 再 sum 再打印输出stringDataStreamSource.flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {@Overridepublic void flatMap(String s, Collector<Tuple2<String, Integer>> collector) throws Exception {String[] words = s.split(" ");for (String word : words) {if ("".equals(word)) {continue;}collector.collect(new Tuple2<>(word, 1));}}}).keyBy(0).sum(1).print();//todo 4.执行任务env.execute("pantouyu");}}

运行后控制台效果如下

二.flink部署（集群 standalone yarn）