流计算中的数据延迟是什么？为什么它在流计算中很重要？

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.timestamps.BoundedOutOfOrdernessTimestampExtractor;
import org.apache.flink.streaming.api.windowing.time.Time;
public class DataLatencyExample {
    public static void main(String[] args) throws Exception {
        // 创建执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        // 创建数据流，并设置事件时间和水位线
        DataStream<Event> stream = env.fromElements(
                new Event(1, "event1", System.currentTimeMillis() - 5000),
                new Event(2, "event2", System.currentTimeMillis() - 2000),
                new Event(3, "event3", System.currentTimeMillis() - 1000)
        ).assignTimestampsAndWatermarks(new BoundedOutOfOrdernessTimestampExtractor<Event>(Time.seconds(1)) {
            @Override
            public long extractTimestamp(Event element) {
                return element.getTimestamp();
            }
        });
        // 计算数据延迟
        DataStream<Long> latency = stream.map(new LatencyCalculationFunction());
        // 打印结果
        latency.print();
        // 执行任务
        env.execute("Data Latency Example");
    }
    // 自定义事件类
    public static class Event {
        private int id;
        private String name;
        private long timestamp;
        public Event(int id, String name, long timestamp) {
            this.id = id;
            this.name = name;
            this.timestamp = timestamp;
        }
        public int getId() {
            return id;
        }
        public String getName() {
            return name;
        }
        public long getTimestamp() {
            return timestamp;
        }
    }
    // 自定义函数，用于计算数据延迟
    public static class LatencyCalculationFunction implements MapFunction<Event, Long> {
        @Override
        public Long map(Event event) throws Exception {
            // 计算数据延迟
            long latency = System.currentTimeMillis() - event.getTimestamp();
            // 返回结果
            return latency;
        }
    }
}