1、注意
使用 GlobalWindows 需要自定义 Trigger，否则窗口中的数据不会被计算。
2、代码示例
import org.apache.flink.streaming.api.datastream.DataStreamSource;
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.GlobalWindows;
import org.apache.flink.streaming.api.windowing.triggers.Trigger;
import org.apache.flink.streaming.api.windowing.triggers.TriggerResult;
import org.apache.flink.streaming.api.windowing.windows.GlobalWindow;
import org.apache.flink.util.Collector;public class _05_WindowAssignerGlobal {public static void main(String[] args) throws Exception {StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();DataStreamSource<String> input = env.socketTextStream("localhost", 8888);// 此窗口模式仅在指定了自定义的 trigger 时有用，否则计算不会发生，因为全局窗口没有天然的终点去触发其中积累的数据input.keyBy(e -> e)// 多并行 Task.window(GlobalWindows.create()).trigger(new Trigger<String, GlobalWindow>() {@Overridepublic TriggerResult onElement(String s, long l, GlobalWindow globalWindow, TriggerContext triggerContext) throws Exception {return null;}@Overridepublic TriggerResult onProcessingTime(long l, GlobalWindow globalWindow, TriggerContext triggerContext) throws Exception {return null;}@Overridepublic TriggerResult onEventTime(long l, GlobalWindow globalWindow, TriggerContext triggerContext) throws Exception {return null;}@Overridepublic void clear(GlobalWindow globalWindow, TriggerContext triggerContext) throws Exception {}}).apply(new WindowFunction<String, String, String, GlobalWindow>() {@Overridepublic void apply(String s, GlobalWindow globalWindow, Iterable<String> iterable, Collector<String> collector) throws Exception {for (String res : iterable) {collector.collect(res);}}}).print();env.execute();}
}
)
