一、standalone 模式

1.1上传依赖包打开配置文件

解压依赖包通过文件传输工具上传到 opt目录下

[root@localhost ~]# cd /
[root@localhost /]# ls
bin  boot  dev  etc  home  jdk  lib  lib64  media  mnt  mydata  opt  proc  root  run  sbin  srv  swapfile  sys  tmp  usr  vagrant  var
[root@localhost /]# cd opt/flink-1.10.1-bin-scala_2.12/
[root@localhost flink-1.10.1-bin-scala_2.12]# ls
flink-1.10.1
[root@localhost flink-1.10.1-bin-scala_2.12]# cd flink-1.10.1/
[root@localhost flink-1.10.1]# ls
bin  conf  examples  lib  LICENSE  licenses  log  NOTICE  opt  plugins  README.txt
[root@localhost flink-1.10.1]# vi conf/flink-conf.yaml

1.2 主要配置文件 flink-conf.yaml 中主要配置介绍

1.3?启动及 jobmanager管理页面显示

bin目录下

./start-cluster.sh 启动? 该脚本会依赖其它脚本，如果没权限那就 chmod 777 文件名

启动成功后访问当前机器 8081端口这个是配置在master文件中的

访问成功页面如下

二、job的提交运行（前端页面方式）

把本地的maven项目编译打包，本地主要代码如下?

package wcTest;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

public class FlinStreamSocketWordCountPrintTest {

    public static void main(String[] args) throws Exception {

        //get runtime environment
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        //read content into dataset from file
        DataStream<String> stringDataSet = env.socketTextStream(args[0],Integer.parseInt(args[1]));


        //count word appeared times
        DataStream<Tuple2<String, Integer>> sum = stringDataSet.flatMap((FlatMapFunction<String, Tuple2<String, Integer>>) (value, collector) -> {

            String[] words = value.split(" ");
            for (String word : words) {
                collector.collect(new Tuple2<>(word, 1));
            }
        }).returns(Types.TUPLE(Types.STRING, Types.INT)).
                keyBy(0).sum(1)
                .setParallelism(2);

        //print content of dataset
        sum.print().setParallelism(1);

        env.execute();

    }

}

?在flink前端首页添加job 配置参数