大数据实时交互活动

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer;

public class RealTimeDataProcessing {
    public static void main(String[] args) throws Exception {
        // 设置执行环境
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 配置Kafka消费者
        FlinkKafkaConsumer<String> kafkaConsumer = new FlinkKafkaConsumer<>("input-topic", new SimpleStringSchema(), properties);

        // 从Kafka读取数据流
        DataStream<String> stream = env.addSource(kafkaConsumer);

        // 数据处理逻辑
        DataStream<String> processedStream = stream.map(new MapFunction<String, String>() {
            @Override
            public String map(String value) throws Exception {
                // 实现数据处理逻辑
                return value.toUpperCase();
            }
        });

        // 输出处理后的数据
        processedStream.print();

        // 执行程序
        env.execute("Real-time Data Processing");
    }
}