Collections.sort(dataList); 这里报错了-Go服务器开发

Collections.sort(dataList); 报错的原因可能是因为 Tuple2<String, Long> 不是自然可排序的类型，或者你需要定义一个比较器来指定如何排序。由于 Tuple2 可能没有实现 Comparable 接口，因此你需要提供一个自定义的比较逻辑。

下面是修改后的代码示例，使用了自定义比较器来对 Tuple2<String, Long> 按照第二个值进行排序：

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;
import scala.Tuple2;

import java.util.ArrayList;
import java.util.Collections;
import java.util.Comparator;
import java.util.List;

public class YourFlinkJob {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        
        // 假设你的输入数据为 DataStream<Tuple2<String, Long>>
        DataStream<Tuple2<String, Long>> inputData = ...; // 获取输入数据

        // 进行 keyBy 和 reduce 操作
        DataStream<Tuple2<String, Long>> reducedData = inputData
            .keyBy(k -> k.f0)
            .reduce(new ReduceFunction<Tuple2<String, Long>>() {
                @Override
                public Tuple2<String, Long> reduce(Tuple2<String, Long> value1, Tuple2<String, Long> value2) throws Exception {
                    return Tuple2.of(value1.f0,value1.f1 + value2.f1);
                }
            });

        // 在这里处理和获取 top 500000 的元素
        DataStream<Tuple2<String, Long>> top500kData = reducedData
            .process(new TopNProcessFunction(500000)); // 自定义 Top N 逻辑

        // 输出 top 500k 到另一个文件中
        top500kData.writeAsText("output/top500k.txt", FileSystem.WriteMode.OVERWRITE);

        // 最终输出 reduced 数据到另一个文件中 
        reducedData.writeAsText("output/reduced_data.txt", FileSystem.WriteMode.OVERWRITE);

        env.execute("Your Flink Job");
    }

    // 自定义 Process Function 实现 Top N 功能
    public static class TopNProcessFunction extends ProcessFunction<Tuple2<String, Long>, Tuple2<String, Long>> {

        private final int n;

        public TopNProcessFunction(int n) {
            this.n = n;
        }

        private List<Tuple2<String, Long>> dataList = new ArrayList<>();

        @Override
        public void processElement(Tuple2<String, Long> value, Context ctx,
                                   Collector<Tuple2<String, Long>> out) throws Exception {

            dataList.add(value);

            if (dataList.size() > n) {
                Collections.sort(dataList, new Comparator<Tuple2<String, Long>>() {
                    @Override
                    public int compare(Tuple2<String, Long> o1, Tuple2<String, Long> o2) {
                        return o1.f1.compareTo(o2.f1); // 按照第二个值排序（从小到大）
                    }
                });
                
                dataList.remove(dataList.size() - 1); // 移除最后一条（即最小的那个）
            }

           for (Tuple2 <String ,Long> item : dataList){
               out.collect(item);
           }
       }
   }
}