flink经典实战案例_flink实战

一、java版flink-wordcount-离线计算版

1.1maven构建flink，加入依赖

<!-- flink包依赖配置-start -->
     <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-java</artifactId>
        <version>${flink.version}</version>
        <!--  <scope>provided</scope> -->
     </dependency>
     <dependency>
        <groupId>org.apache.flink</groupId>
        <artifactId>flink-clients_${scala.version}</artifactId>
        <version>${flink.version}</version>
     </dependency>
     <!-- flink包依赖配置-end -->
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1.2 java实现flink wordCount的代码编写

1.2.1代码编写

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.core.fs.FileSystem.WriteMode;
import org.apache.flink.util.Collector;

/**
* Flink实现离线数据DataSet版本的WordCount经典案例
*
*
*/
public class FlinkWordCount4DataSet {
    public static void main(String[] args) throws Exception {
        // 创建Flink的代码执行离线数据流上下文环境变量
        ExecutionEnvironment env = ExecutionEnvironment
                .getExecutionEnvironment();
        // 定义从本地文件系统当中文件路径
        String filePath = "";
        if (args == null || args.length == 0) {
            filePath = "D:\\temp\\input.txt";
        } else {
            filePath = args[0];
        }
        // 获取输入文件对应的DataSet对象
        DataSet<String> inputLineDataSet = env.readTextFile(filePath);

        // 对数据集进行多个算子处理，按空白符号分词展开，并转换成(word, 1)二元组进行统计
        DataSet<Tuple2<String, Integer>> resultSet = inputLineDataSet
                .flatMap(
                        new FlatMapFunction<String, Tuple2<String, Integer>>()
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