即使在批处理模式下，也无法并行处理字和行，因为嵌套 groupBy （或 keyBy )在flink中不支持。但是，如果您需要以下批字计数的流式版本：

lines
  .flatMap(line => (lineId,word,1))
  .groupBy(0)
  .reduceGroup {aggregateWords}

哪里 aggregateWords 迭代该特定键的单词并对它们进行计数，然后可以按以下方式实现：对于每一行，您在末尾发出单词和一个特殊记录，然后使用一个带有自定义触发器的globalwindow，该触发器在收到特殊记录后触发。
以前批处理作业的流式版本可能如下所示：

public static void main(String[] args) throws Exception {
    final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    env.fromElements("foo bar baz foo", "yes no no yes", "hi hello hi hello")
            .flatMap(new FlatMapFunction<String, Tuple3<Double, String, Integer>>() {
                @Override
                public void flatMap(String s, Collector<Tuple3<Double, String, Integer>> collector) throws Exception {
                    String[] words = s.split("\\W+");
                    Double lineId = Math.random();
                    for (String w : words) {
                        collector.collect(Tuple3.of(lineId, w, 1));
                    }
                    collector.collect(Tuple3.of(lineId, "\n", 1));
                }
            })
            .keyBy(0)
            .window(GlobalWindows.create())
            .trigger(new Trigger<Tuple3<Double, String, Integer>, GlobalWindow>() {
                @Override
                public TriggerResult onElement(Tuple3<Double, String, Integer> element, long l, GlobalWindow globalWindow, TriggerContext triggerContext) throws Exception {
                    if (element.f1.equals("\n")) {
                        return TriggerResult.FIRE;
                    }
                    return TriggerResult.CONTINUE;
                }
                @Override
                public TriggerResult onProcessingTime(long l, GlobalWindow globalWindow, TriggerContext triggerContext) throws Exception {
                    return TriggerResult.CONTINUE;
                }
                @Override
                public TriggerResult onEventTime(long l, GlobalWindow globalWindow, TriggerContext triggerContext) throws Exception {
                    return TriggerResult.CONTINUE;
                }
            })
            .fold(new HashMap<>(), new FoldFunction<Tuple3<Double, String, Integer>, HashMap<String, Integer>>() {
                @Override
                public HashMap<String, Integer> fold(HashMap<String, Integer> hashMap, Tuple3<Double, String, Integer> tuple3) throws Exception {
                    if (!tuple3.f1.equals("\n")) {
                        hashMap.put(tuple3.f1, hashMap.getOrDefault(tuple3.f1, 0) + 1);
                    }
                    return hashMap;
                }
            }).print();
    env.execute("Test");
}

输出：

{bar=1, foo=2, baz=1}
{no=2, yes=2}
{hi=2, hello=2}