1、如何用flink的table和sql​构建pom文件

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构建pom文件

<?xml version="1.0" encoding="UTF-8"?>
<project xmlns="http://maven.apache.org/POM/4.0.0"
         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
    <modelVersion>4.0.0</modelVersion>

    <groupId>org.example</groupId>
    <artifactId>flinksqldemo</artifactId>
    <version>1.0-SNAPSHOT</version>


    <properties>
        <!-- Encoding -->
        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
        <project.reporting.outputEncoding>UTF-8</project.reporting.outputEncoding>

        <scala.binary.version>2.11</scala.binary.version>
        <scala.version>2.11.8</scala.version>
        <kafka.version>0.10.2.1</kafka.version>
        <flink.version>1.12.0</flink.version>
        <hadoop.version>2.7.3</hadoop.version>

        <!-- scope 本地调试时注销 设定为默认的 compile 打包时设定为 provided -->
        <setting.scope>compile</setting.scope>
    </properties>

    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.plugins</groupId>
                <artifactId>maven-compiler-plugin</artifactId>
                <configuration>
                    <source>8</source>
                    <target>8</target>
                </configuration>
            </plugin>
        </plugins>
    </build>



    <dependencies>
        <!--flink start-->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-table-planner-blink_2.11</artifactId>
            <version>1.12.0</version>

        </dependency>

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink.version}</version>
            <scope>${setting.scope}</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_2.11</artifactId>
            <version>${flink.version}</version>
            <scope>${setting.scope}</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_2.11</artifactId>
            <version>${flink.version}</version>
            <scope>${setting.scope}</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka-0.10_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-scala_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>${setting.scope}</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-filesystem_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <!--<dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-statebackend-rocksdb_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>-->
        <!-- flink end-->

        <!-- kafka start -->
        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka_${scala.binary.version}</artifactId>
            <version>${kafka.version}</version>
            <scope>${setting.scope}</scope>
        </dependency>
        <!-- kafka end-->

        <!-- hadoop start -->
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-common</artifactId>
            <version>${hadoop.version}</version>
            <scope>${setting.scope}</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-hdfs</artifactId>
            <version>${hadoop.version}</version>
            <scope>${setting.scope}</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.hadoop</groupId>
            <artifactId>hadoop-client</artifactId>
            <version>${hadoop.version}</version>
            <scope>${setting.scope}</scope>
        </dependency>
        <!-- hadoop end -->

        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-api</artifactId>
            <version>1.7.25</version>
        </dependency>
        <dependency>
            <groupId>com.alibaba</groupId>
            <artifactId>fastjson</artifactId>
            <version>1.2.72</version>
        </dependency>
        <dependency>
            <groupId>redis.clients</groupId>
            <artifactId>jedis</artifactId>
            <version>2.7.3</version>
        </dependency>
        <dependency>
            <groupId>com.google.guava</groupId>
            <artifactId>guava</artifactId>
            <version>29.0-jre</version>
        </dependency>

    </dependencies>

</project>

2、编写代码

package com.jd.data;

import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.streaming.api.datastream.DataStream;
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.bridge.java.StreamTableEnvironment;

public class test {
    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        DataStreamSource<String> stream = env.readTextFile("/Users/liuhaijing/Desktop/flinktestword/aaa.txt");
//        DataStreamSource<String> stream = env.socketTextStream("localhost", 8888);

        SingleOutputStreamOperator<SensorReading> map = stream.map(new MapFunction<String, SensorReading>() {

            public SensorReading map(String s) throws Exception {
                String[] split = s.split(",");
                return new SensorReading(split[0], split[1], split[2]);
            }
        });



        StreamTableEnvironment tableEnv = StreamTableEnvironment.create(env);
//        使用 table api
//        Table table = tableEnv.fromDataStream(map);
//        table.printSchema();
//        Table select = table.select("a,b");

//        使用 sql api
        tableEnv.createTemporaryView("test", map);
        Table select = tableEnv.sqlQuery(" select a, b from test");


        DataStream<SensorReading2> sensorReading2DataStream = tableEnv.toAppendStream(select, SensorReading2.class);
        sensorReading2DataStream.map(new MapFunction<SensorReading2, Object>() {
            @Override
            public Object map(SensorReading2 value) throws Exception {
                System.out.println(value.a+"   "+ value.b);
                return null;
            }
        });
        env.execute();


    }
}

package com.jd.data;

public class SensorReading {
    public String a;
    public String b;
    public String c;

    public SensorReading(){

    }

    public SensorReading(String a, String b, String c) {
        this.a = a;
        this.b = b;
        this.c = c;
    }

    public String getA() {
        return a;
    }

    public void setA(String a) {
        this.a = a;
    }

    public String getB() {
        return b;
    }

    public void setB(String b) {
        this.b = b;
    }

    public String getC() {
        return c;
    }

    public void setC(String c) {
        this.c = c;
    }
}

package com.jd.data;

public class SensorReading2 {
    public String a;
    public String b;

    public SensorReading2(){

    }

    public SensorReading2(String a, String b) {
        this.a = a;
        this.b = b;
    }

    public String getA() {
        return a;
    }

    public void setA(String a) {
        this.a = a;
    }

    public String getB() {
        return b;
    }

    public void setB(String b) {
        this.b = b;
    }


}

注意：pojo 中属性必须是public的， 包含无参构造器

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