滚动窗口（Tumbling Windows） 滚动窗口有固定的大小，是一种对数据进行均匀切片的划分方式。窗口之间没有重叠，也不会有间隔，是“首尾相接”的状态。滚动窗口可以基于时间定义，也可以基于数据个数定义；需要的参数只有一个，就是窗口的大小（window size）。

demo演示：

场景：接收通过socket发送过来的数据，每30秒触发一次窗口计算逻辑

（1）准备一个实体对象，消息对象

package com.pojo;import java.io.Serializable;/** * Created by lj on 2022-07-05. */public class WaterSensor implements Serializable {    private String id;    private long ts;    private int vc;    public WaterSensor(){    }    public WaterSensor(String id,long ts,int vc){        this.id = id;        this.ts = ts;        this.vc = vc;    }    public int getVc() {        return vc;    }    public void setVc(int vc) {        this.vc = vc;    }    public String getId() {        return id;    }    public void setId(String id) {        this.id = id;    }    public long getTs() {        return ts;    }    public void setTs(long ts) {        this.ts = ts;    }}

（2）编写socket代码，模拟数据发送

package com.producers;import java.io.BufferedWriter;import java.io.IOException;import java.io.OutputStreamWriter;import java.net.ServerSocket;import java.net.Socket;import java.util.Random;/** * Created by lj on 2022-07-05. */public class Socket_Producer {    public static void main(String[] args) throws IOException {        try {            ServerSocket ss = new ServerSocket(9999);            System.out.println("启动 server ....");            Socket s = ss.accept();            BufferedWriter bw = new BufferedWriter(new OutputStreamWriter(s.getOutputStream()));            String response = "java,1,2";            //每 2s 发送一次消息            int i = 0;            Random r=new Random();               String[] lang = {"flink","spark","hadoop","hive","hbase","impala","presto","superset","nbi"};            while(true){                Thread.sleep(2000);                response= lang[r.nextInt(lang.length)] + "," + i + "," + i+"
";                System.out.println(response);                try{                    bw.write(response);                    bw.flush();                    i++;                }catch (Exception ex){                    System.out.println(ex.getMessage());                }            }        } catch (IOException | InterruptedException e) {            e.printStackTrace();        }    }}

（3）从socket端接收数据，并设置30秒触发执行一次窗口运算

package com.examples;import com.pojo.WaterSensor;import org.apache.flink.api.common.functions.MapFunction;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.table.api.Table;import org.apache.flink.table.api.Tumble;import org.apache.flink.table.api.bridge.java.StreamTableEnvironment;import org.apache.flink.types.Row;import static org.apache.flink.table.api.Expressions.$;import static org.apache.flink.table.api.Expressions.lit;/** * Created by lj on 2022-07-06. * * 滚动窗口（Tumbling Windows） 滚动窗口有固定的大小，是一种对数据进行均匀切片的划分方式。窗口之间没有重叠，也不会有间隔， * 是“首尾相接”的状态。滚动窗口可以基于时间定义，也可以基于数据个数定义；需要的参数只有一个， * 就是窗口的大小（window size）。 */public class Flink_Group_Window_Tumble {    public static void main(String[] args) throws Exception {        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();        env.setParallelism(1);        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);        DataStreamSource streamSource = env.socketTextStream("127.0.0.1", 9999,"
");        SingleOutputStreamOperator waterDS = streamSource.map(new MapFunction() {            @Override            public WaterSensor map(String s) throws Exception {                String[] split = s.split(",");                return new WaterSensor(split[0], Long.parseLong(split[1]), Integer.parseInt(split[2]));            }        });        // 将流转化为表        Table table = tableEnv.fromDataStream(waterDS,                $("id"),                $("ts"),                $("vc"),                $("pt").proctime());        tableEnv.createTemporaryView("EventTable", table);        Table result = tableEnv.sqlQuery(                "SELECT " +                        "id, " +                //window_start, window_end,                        "COUNT(ts) ,SUM(ts)" +                        "FROM TABLE( " +                        "TUMBLE( TABLE EventTable , " +                        "DESCRIPTOR(pt), " +                        "INTERVAL '30' SECOND)) " +                        "GROUP BY id , window_start, window_end"        );//        tableEnv.toChangelogStream(result).print("count");//        tableEnv.toDataStream(result).print("toDataStream");//        tableEnv.toAppendStream(result, Row.class).print("toAppendStream");           //追加模式        tableEnv.toRetractStream(result, Row.class).print("toRetractStream");       //缩进模式        env.execute();    }}

（4）效果演示