flink对文档一列统计前10top打包执行代码

以下是使用Flink对文档中的一列进行统计，并输出前10个最大值的打包执行代码：

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.tuple.Tuple2;

import java.util.Collections;

public class Top10Words {

    public static void main(String[] args) throws Exception {
        final ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();

        DataSet<String> text = env.readTextFile("path/to/input/file");

        DataSet<Tuple2<String, Integer>> counts =
                text.flatMap((String line, Collector<Tuple2<String, Integer>> out) -> {
                    for (String word : line.split(" ")) {
                        if (word.length() > 0) {
                            out.collect(new Tuple2<>(word, 1));
                        }
                    }
                })
                .groupBy(0)
                .reduce((ReduceFunction<Tuple2<String, Integer>>) (t1, t2) -> new Tuple2<>(t1.f0, t1.f1 + t2.f1));

        DataSet<Tuple2<String, Integer>> topCounts = counts
                .map(new MapFunction<Tuple2<String, Integer>, Tuple2<String, Integer>>() {
                    @Override
                    public Tuple2<String, Integer> map(Tuple2<String, Integer> value) throws Exception {
                        return value;
                    }
                })
                .sortPartition(1, org.apache.flink.api.common.operators.Order.DESCENDING)
                .setParallelism(1)
                .first(10);

        topCounts.print();
    }
}

在这个示例中，我们使用了Flink的DataSet API来读取文本文件，将每个单词映射为一个键值对（单词, 1），并通过reduce操作将每个单词的计数相加。然后我们将结果按照计数排序，并输出前10个最大值。在执行时，我们需要将代码打包成一个jar文件，并在集群上执行。