1、处理时间
无需设置水位线和时间间隔。
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。
// 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
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
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();
}
}
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