java框架如何支持流处理，以实时处理和分析数据流？

import org.apache.flink.api.java.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;

public class FlinkWordCount {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        DataStream<String> lines = env.readTextFile("input.txt");

        DataStream<Tuple2<String, Integer>> wordCounts = lines
                .flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {
                    @Override
                    public void flatMap(String line, FlatMapCollector<Tuple2<String, Integer>> out) throws Exception {
                        for (String word : line.split(" ")) {
                            out.collect(Tuple2.of(word, 1));
                        }
                    }
                })
                .keyBy("f0")
                .sum("f1");

        wordCounts.print();

        env.execute();
    }
}

import org.springframework.boot.SpringApplication;
import org.springframework.boot.autoconfigure.SpringBootApplication;
import org.springframework.cloud.stream.annotation.EnableBinding;
import org.springframework.cloud.stream.messaging.Processor;
import org.springframework.integration.annotation.ServiceActivator;

@SpringBootApplication
@EnableBinding(Processor.class)
public class StreamProcessingApplication {

    public static void main(String[] args) {
        SpringApplication.run(StreamProcessingApplication.class, args);
    }

    @ServiceActivator(inputChannel = Processor.INPUT)
    public String uppercase(String message) {
        return message.toUpperCase();
    }
}

import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.kstream.KStream;
import org.apache.kafka.streams.KafkaStreams.State;

import java.util.Properties;

public class KafkaStreamsWordCount {

    public static void main(String[] args) {
        Properties props = new Properties();
        props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
        props.put(ConsumerConfig.GROUP_ID_CONFIG, "kafka-streams-word-count");

        StreamsBuilder builder = new StreamsBuilder();

        KStream<String, String> lines = builder.stream("input-topic");

        KStream<String, Integer> wordCounts = lines
                .flatMapValues(s -> s.split(" "))
                .groupBy((key, value) -> value)
                .count();

        wordCounts.to("output-topic");

        KafkaStreams streams = new KafkaStreams(builder.build(), props);

        streams.start();

        Runtime.getRuntime().addShutdownHook(new Thread(streams::close));

        while (streams.state() != State.RUNNING) {
            // Check the state of the streams application
        }
    }
}