37、Flink 的 WindowAssigner之会话窗口示例

1、处理时间

无需设置水位线和时间间隔。

bash 复制代码
input.keyBy(e -> e)
                .window(ProcessingTimeSessionWindows.withGap(Time.minutes(10)))
                .apply(new WindowFunction<String, String, String, TimeWindow>() {
                    @Override
                    public void apply(String s, TimeWindow timeWindow, Iterable<String> iterable, Collector<String> collector) throws Exception {
                        for (String string : iterable) {
                            collector.collect(string);
                        }
                    }
                })
                .print();

2、事件时间

需设置水位线和时间间隔。

bash 复制代码
// 事件时间需要设置水位线策略和时间戳
        SingleOutputStreamOperator<Tuple2<String, Long>> map = input.map(new MapFunction<String, Tuple2<String, Long>>() {
            @Override
            public Tuple2<String, Long> map(String input) throws Exception {
                String[] fields = input.split(",");
                return new Tuple2<>(fields[0], Long.parseLong(fields[1]));
            }
        });

        SingleOutputStreamOperator<Tuple2<String, Long>> watermarks = map.assignTimestampsAndWatermarks(WatermarkStrategy.<Tuple2<String, Long>>forBoundedOutOfOrderness(Duration.ofSeconds(0))
                .withTimestampAssigner(new SerializableTimestampAssigner<Tuple2<String, Long>>() {
                    @Override
                    public long extractTimestamp(Tuple2<String, Long> input, long l) {
                        return input.f1;
                    }
                }));

        // 设置了固定间隔的 event-time 会话窗口
        watermarks.keyBy(e -> e.f0)
                .window(EventTimeSessionWindows.withGap(Time.minutes(10)))
                .apply(new WindowFunction<Tuple2<String, Long>, String, String, TimeWindow>() {
                    @Override
                    public void apply(String s, TimeWindow timeWindow, Iterable<Tuple2<String, Long>> iterable, Collector<String> collector) throws Exception {
                        for (Tuple2<String, Long> stringLongTuple2 : iterable) {
                            collector.collect(stringLongTuple2.f0);
                        }
                    }
                })
                .print();

3、固定间隔和动态间隔

bash 复制代码
EventTimeSessionWindows.withGap(Time.minutes(10));

EventTimeSessionWindows.withDynamicGap(new SessionWindowTimeGapExtractor<Tuple2<String, Long>>() {
                    @Override
                    public long extract(Tuple2<String, Long> element) {
                        return element.f1 + 2000L;
                    }
                });

4、完整代码示例

bash 复制代码
import org.apache.flink.api.common.eventtime.SerializableTimestampAssigner;
import org.apache.flink.api.common.eventtime.WatermarkStrategy;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.windowing.WindowFunction;
import org.apache.flink.streaming.api.windowing.assigners.EventTimeSessionWindows;
import org.apache.flink.streaming.api.windowing.assigners.ProcessingTimeSessionWindows;
import org.apache.flink.streaming.api.windowing.assigners.SessionWindowTimeGapExtractor;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.streaming.api.windowing.windows.TimeWindow;
import org.apache.flink.util.Collector;

import java.time.Duration;

public class _04_WindowAssignerSession {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        DataStreamSource<String> input = env.socketTextStream("localhost", 8888);

        // 测试时限制了分区数,生产中需要设置空闲数据源
        env.setParallelism(2);

        // 事件时间需要设置水位线策略和时间戳
        SingleOutputStreamOperator<Tuple2<String, Long>> map = input.map(new MapFunction<String, Tuple2<String, Long>>() {
            @Override
            public Tuple2<String, Long> map(String input) throws Exception {
                String[] fields = input.split(",");
                return new Tuple2<>(fields[0], Long.parseLong(fields[1]));
            }
        });

        SingleOutputStreamOperator<Tuple2<String, Long>> watermarks = map.assignTimestampsAndWatermarks(WatermarkStrategy.<Tuple2<String, Long>>forBoundedOutOfOrderness(Duration.ofSeconds(0))
                .withTimestampAssigner(new SerializableTimestampAssigner<Tuple2<String, Long>>() {
                    @Override
                    public long extractTimestamp(Tuple2<String, Long> input, long l) {
                        return input.f1;
                    }
                }));

        // 设置了固定间隔的 event-time 会话窗口
        watermarks.keyBy(e -> e.f0)
                .window(EventTimeSessionWindows.withGap(Time.minutes(10)))
                .apply(new WindowFunction<Tuple2<String, Long>, String, String, TimeWindow>() {
                    @Override
                    public void apply(String s, TimeWindow timeWindow, Iterable<Tuple2<String, Long>> iterable, Collector<String> collector) throws Exception {
                        for (Tuple2<String, Long> stringLongTuple2 : iterable) {
                            collector.collect(stringLongTuple2.f0);
                        }
                    }
                })
                .print();

        // 设置了动态间隔的 event-time 会话窗口
        watermarks.keyBy(e -> e.f0)
                .window(EventTimeSessionWindows.withDynamicGap(new SessionWindowTimeGapExtractor<Tuple2<String, Long>>() {
                    @Override
                    public long extract(Tuple2<String, Long> element) {
                        return element.f1 + 2000L;
                    }
                }))
                .apply(new WindowFunction<Tuple2<String, Long>, String, String, TimeWindow>() {
                    @Override
                    public void apply(String s, TimeWindow timeWindow, Iterable<Tuple2<String, Long>> iterable, Collector<String> collector) throws Exception {
                        for (Tuple2<String, Long> stringLongTuple2 : iterable) {
                            collector.collect(stringLongTuple2.f0);
                        }
                    }
                })
                .print();

        // 设置了固定间隔的 processing-time session 窗口
        input.keyBy(e -> e)
                .window(ProcessingTimeSessionWindows.withGap(Time.minutes(10)))
                .apply(new WindowFunction<String, String, String, TimeWindow>() {
                    @Override
                    public void apply(String s, TimeWindow timeWindow, Iterable<String> iterable, Collector<String> collector) throws Exception {
                        for (String string : iterable) {
                            collector.collect(string);
                        }
                    }
                })
                .print();

        // 设置了动态间隔的 processing-time 会话窗口
        input.keyBy(e -> e)
                .window(ProcessingTimeSessionWindows.withDynamicGap(new SessionWindowTimeGapExtractor<String>() {
                    @Override
                    public long extract(String s) {
                        return System.currentTimeMillis() / 1000;
                    }
                }))
                .apply(new WindowFunction<String, String, String, TimeWindow>() {
                    @Override
                    public void apply(String s, TimeWindow timeWindow, Iterable<String> iterable, Collector<String> collector) throws Exception {
                        for (String string : iterable) {
                            collector.collect(string);
                        }
                    }
                })
                .print();

        env.execute();
    }
}
相关推荐
得物技术3 天前
从埋点需求到规则资产:Hermes Agent 重构得物数仓工作流
大数据·llm·ai编程
久美子3 天前
AI驱动数仓建设的Harness工程实践——本体建模、知识分层与上下文工程
大数据
大树884 天前
金刚石散热越强,管路越先见顶
大数据·运维·服务器·人工智能·ai
大志哥1234 天前
ES和Logstash日志链路系统上线后遭遇切片爆炸(解决)
大数据·elasticsearch
果丁智能4 天前
物联网智能锁赋能集中式住宿:身份核验与远程权限管控的全链路技术实践
大数据·人工智能·物联网·智能家居
ApacheSeaTunnel4 天前
实战演示 | 基于 Apache SeaTunnel 与 Apache DolphinScheduler 实现 MySQL 到 Doris 离线定时增量同步
大数据·mysql·开源·doris·数据集成·seatunnel·数据同步
weixin_397574094 天前
PDF复杂表格的1:1还原引擎:跨页表格自动拼接技术实战
大数据·人工智能·pdf
极光代码工作室4 天前
基于数据仓库的电商数据分析平台
大数据·hadoop·python·spark·数据可视化
秋名山码民4 天前
Graph RAG 深度解析:从向量检索到知识推理的技术演进
大数据·人工智能·rag
m0_380167144 天前
面向开发者的Top10加密货币数据API(2026年最新)
大数据·人工智能·区块链