双十二流计算推荐

import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.api.common.functions.MapFunction;

public class WebsiteTrafficCounter {
    public static void main(String[] args) throws Exception {
        // 创建流处理环境
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // 从Kafka读取数据流
        DataStream<String> trafficData = env.addSource(new FlinkKafkaConsumer<>("website_traffic", new SimpleStringSchema(), properties));

        // 数据处理：将每条记录映射为访问次数
        DataStream<Integer> visitCounts = trafficData.map(new MapFunction<String, Integer>() {
            @Override
            public Integer map(String value) {
                return 1; // 每条记录代表一次访问
            }
        });

        // 聚合计算总访问次数
        DataStream<Integer> totalVisits = visitCounts.sum(0);

        // 输出结果
        totalVisits.print();

        // 执行程序
        env.execute("Website Traffic Counter");
    }
}