网上找资料复习学习的时候留意点:
报错

Exception in thread "main" org.apache.flink.api.common.functions.InvalidTypesException: The return type of function 'main(Flink01_WordCount_Batch.java:32)' could not be determined automatically, due to type erasure. You can give type information hints by using the returns(...) method on the result of the transformation call, or by letting your function implement the 'ResultTypeQueryable' interface.
    at org.apache.flink.api.java.DataSet.getType(DataSet.java:178)
    at org.apache.flink.api.java.DataSet.groupBy(DataSet.java:701)
    at com.keke.day01.Flink01_WordCount_Batch.main(Flink01_WordCount_Batch.java:38)
Caused by: org.apache.flink.api.common.functions.InvalidTypesException: The generic type parameters of 'Tuple2' are missing. In many cases lambda methods don't provide enough information for automatic type extraction when Java generics are involved. An easy workaround is to use an (anonymous) class instead that implements the 'org.apache.flink.api.common.functions.MapFunction' interface. Otherwise the type has to be specified explicitly using type information.
    at org.apache.flink.api.java.typeutils.TypeExtractionUtils.validateLambdaType(TypeExtractionUtils.java:351)
    at org.apache.flink.api.java.typeutils.TypeExtractor.getUnaryOperatorReturnType(TypeExtractor.java:523)
    at org.apache.flink.api.java.typeutils.TypeExtractor.getMapReturnTypes(TypeExtractor.java:147)
    at org.apache.flink.api.java.DataSet.map(DataSet.java:216)
    at com.keke.day01.Flink01_WordCount_Batch.main(Flink01_WordCount_Batch.java:32)

案例:

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.typeinfo.Types;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.operators.*;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.util.Collector;

public class Flink01_WordCount_Batch {

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

        //1.获取执行环境
        ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();



        //2.读取文件数据
        DataSource<String> input = env.readTextFile("input2");

        //3.压平
        FlatMapOperator<String, String> wordDS = input.flatMap(new MyFlatMapFunc());

        //4.将单词转换为元组
//        MapOperator<String, Tuple2<String, Integer>> wordToOneDS = wordDS.map((MapFunction<String, Tuple2<String, Integer>>) value -> {
//            return new Tuple2<>(value, 1);
//            //return Tuple2.of(value, 1);
//        }).returns(Types.TUPLE(Types.STRING, Types.INT));

        MapOperator<String, Tuple2<String, Integer>> wordToOneDS = wordDS.map((MapFunction<String, Tuple2<String, Integer>>) value -> {
            return new Tuple2<>(value, 1);
            //return Tuple2.of(value, 1);
        }); //当Lambda表达式使用 java 泛型的时候, 由于泛型擦除的存在, 需要显示的声明类型信息

        //5.分组
        UnsortedGrouping<Tuple2<String, Integer>> groupBy = wordToOneDS.groupBy(0);

        //6.聚合
        AggregateOperator<Tuple2<String, Integer>> result = groupBy.sum(1);

        //7.打印结果
        result.print();

    }

    //自定义实现压平操作的类
    public static class MyFlatMapFunc implements FlatMapFunction<String, String> {
        @Override
        public void flatMap(String value, Collector<String> out) throws Exception {
            //按照空格切割
            String[] words = value.split(" ");
            //遍历words,写出一个个的单词
            for (String word : words) {
                out.collect(word);
            }
        }
    }

}

当Lambda表达式使用 java 泛型的时候, 由于泛型擦除的存在, 需要显示的声明类型信息

returns(Types.TUPLE(Types.STRING, Types.INT))