流式计算 新购活动

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

public class StreamingJob {
    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> stream = env.addSource(new FlinkKafkaConsumer<>("topic", new SimpleStringSchema(), properties));

        // 数据处理逻辑
        DataStream<ResultType> results = stream.map(new MapFunction<String, ResultType>() {
            @Override
            public ResultType map(String value) throws Exception {
                // 处理每一条数据
                return process(value);
            }
        });

        // 输出结果到外部系统，如数据库或文件
        results.addSink(new JdbcSink("INSERT INTO results (column) VALUES (?)", statement -> {
            statement.setString(1, result.getColumn());
        }));

        // 执行任务
        env.execute("Real-time Streaming Job");
    }

    private static ResultType process(String data) {
        // 实现具体的数据处理逻辑
        return new ResultType(data);
    }
}