Flink -sql 处理时间的窗口

1.flink 窗口的分类

1.1 分类

2. 先看基于处理时间的窗口

2.1 处理时间的滚动窗口

2.1.1 先可以看看官网的描述

·https://ci.apache.org/projects/flink/flink-docs-master/docs/dev/table/tableapi/

proctime() 需要注意的是这个指定的处理时间

package com.wudl.flink.sql;

import com.wudl.flink.bean.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;

/**
 * @ClassName : Flink_Group_Window  --  基于处理时间的混动窗口
 * @Description : Flink sql 窗口
 * @Author :wudl
 * @Date: 2021-08-04 23:13
 */

public class Flink_Group_Window {
    
    
    public static void main(String[] args) throws Exception {
    
    

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        StreamTableEnvironment tableEnvironment = StreamTableEnvironment.create(env);
        DataStreamSource<String> streamSource = env.socketTextStream("192.168.1.180", 9999);
        SingleOutputStreamOperator<WaterSensor> waterDS = streamSource.map(new MapFunction<String, WaterSensor>() {
    
    
            @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 = tableEnvironment.fromDataStream(waterDS,
                $("id"),
                $("ts"),
                $("vc"),
                $("pt").proctime());

        // 开窗滚动窗口计算wordCound
        Table result = table.window(Tumble.over(lit(5).seconds()).on($("pt")).as("tw"))
                .groupBy($("id"), $("tw"))
                .select($("id"), $("id").count());

        // 将结果表转化为流进行输出

        tableEnvironment.toAppendStream(result, Row.class).print();
        env.execute();
    }
}

3.基于处理时间的滑动窗口

package com.wudl.flink.sql;

import com.wudl.flink.bean.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.Slide;
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;

/**
 * @ClassName : 基于处理时间的滑动窗口
 * @Description : Flink sql 窗口
 * @Author :wudl
 * @Date: 2021-08-04 23:13
 */

public class Flink_Group_Sliding_Window {
    
    
    public static void main(String[] args) throws Exception {
    
    

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        StreamTableEnvironment tableEnvironment = StreamTableEnvironment.create(env);
        DataStreamSource<String> streamSource = env.socketTextStream("192.168.1.180", 9999);
        SingleOutputStreamOperator<WaterSensor> waterDS = streamSource.map(new MapFunction<String, WaterSensor>() {
    
    
            @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 = tableEnvironment.fromDataStream(waterDS,
                $("id"),
                $("ts"),
                $("vc"),
                $("pt").proctime());

        // 开窗滑动窗口计算wordCound
        Table result = table.window(Slide.over(lit(5).seconds())
                .every(lit(2).seconds())
                .on($("pt"))
                .as("sw"))
                .groupBy($("id"),$("sw"))
                .select($("id"), $("id").count());

        // 将结果表转化为流进行输出
        
        tableEnvironment.toAppendStream(result, Row.class).print();
        env.execute();
    }
}

4. 基于处理时间的会话窗口

package com.wudl.flink.sql;

import com.wudl.flink.bean.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.Session;
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;

/**
 * @ClassName : Flink_Group_Window  --  基于处理时间的会话窗口
 * @Description : Flink sql 窗口
 * @Author :wudl
 * @Date: 2021-08-04 23:13
 */

public class Flink_Group_session_Window {
    
    
    public static void main(String[] args) throws Exception {
    
    

        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        StreamTableEnvironment tableEnvironment = StreamTableEnvironment.create(env);
        DataStreamSource<String> streamSource = env.socketTextStream("192.168.1.180", 9999);
        SingleOutputStreamOperator<WaterSensor> waterDS = streamSource.map(new MapFunction<String, WaterSensor>() {
    
    
            @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 = tableEnvironment.fromDataStream(waterDS,
                $("id"),
                $("ts"),
                $("vc"),
                $("pt").proctime());

        // 开窗滚动窗口计算wordCound
        Table result = table.window(Session.withGap(lit(5).seconds()).on($("pt")).as("sw"))
                .groupBy($("id"), $("sw"))
                .select($("id"), $("id").count());

        // 将结果表转化为流进行输出

        tableEnvironment.toAppendStream(result, Row.class).print();
        env.execute();
    }
}