SpringBoot集成flink

Flink是一个批处理和流处理结合的统一计算框架，其核心是一个提供了数据分发以及并行化计算的流数据处理引擎。
最大亮点是流处理，最适合的应用场景是低时延的数据处理。
场景：高并发pipeline处理数据，时延毫秒级，且兼具可靠性。

环境搭建：

①、安装flink

https://nightlies.apache.org/flink/flink-docs-master/zh/docs/try-flink/local_installation/

②、安装Netcat

Netcat（又称为NC）是一个计算机网络工具，它可以在两台计算机之间建立 TCP/IP 或 UDP 连接。
用于测试网络中的端口，发送文件等操作。
进行网络调试和探测，也可以进行加密连接和远程管理等高级网络操作

yum install -y nc # 安装nc命令

nc -lk 8888 # 启动socket端口
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无界流之读取socket文本流

一、依赖

<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">
    <parent>
        <artifactId>springboot-demoartifactId>
        <groupId>com.etgroupId>
        <version>1.0-SNAPSHOTversion>
    parent>
    <modelVersion>4.0.0modelVersion>

    <artifactId>flinkartifactId>

    <properties>
        <maven.compiler.source>8maven.compiler.source>
        <maven.compiler.target>8maven.compiler.target>
    properties>
    <dependencies>

        <dependency>
            <groupId>org.springframework.bootgroupId>
            <artifactId>spring-boot-starter-webartifactId>
        dependency>

        <dependency>
            <groupId>org.springframework.bootgroupId>
            <artifactId>spring-boot-autoconfigureartifactId>
        dependency>
        <dependency>
            <groupId>org.springframework.bootgroupId>
            <artifactId>spring-boot-starter-testartifactId>
            <scope>testscope>
        dependency>
        
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-streaming-javaartifactId>
            <version>1.17.0version>
        dependency>
        
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-javaartifactId>
            <version>1.17.0version>
        dependency>

        
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-clientsartifactId>
            <version>1.17.0version>
        dependency>

        
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-connector-baseartifactId>
            <version>1.17.0version>
        dependency>

        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-connector-filesartifactId>
            <version>1.17.0version>
        dependency>
        
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-connector-kafkaartifactId>
            <version>1.17.0version>
        dependency>
        <dependency>
            <groupId>org.apache.flinkgroupId>
            <artifactId>flink-runtime-webartifactId>
            <version>1.17.0version>
        dependency>


    dependencies>
    <build>
        <plugins>
            <plugin>
                <groupId>org.apache.maven.pluginsgroupId>
                <artifactId>maven-shade-pluginartifactId>
                <executions>
                    <execution>
                        <phase>packagephase>
                        <goals>
                            <goal>shadegoal>
                        goals>
                        <configuration>
                            <transformers>
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
                                    <resource>META-INF/spring.handlersresource>
                                transformer>
                                <transformer
                                        implementation="org.springframework.boot.maven.PropertiesMergingResourceTransformer">
                                    <resource>META-INF/spring.factoriesresource>
                                transformer>
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.AppendingTransformer">
                                    <resource>META-INF/spring.schemasresource>
                                transformer>
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.ServicesResourceTransformer" />
                                <transformer
                                        implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
                                    <mainClass>com.et.flink.job.SocketJobmainClass>
                                transformer>
                            transformers>
                        configuration>
                    execution>
                executions>
            plugin>
        plugins>
    build>

project>
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二、SoketJob

public class SocketJob{
	
	public static void main(String[] args)throws Exception{
		
		// 创建执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        // 指定并行度,默认电脑线程数
        env.setParallelism(3);
        // 读取数据socket文本流 指定监听 IP 端口 只有在接收到数据才会执行任务
        DataStreamSource<String> socketDS = env.socketTextStream("172.24.4.193", 8888);

        // 处理数据: 切换、转换、分组、聚合 得到统计结果
        SingleOutputStreamOperator<Tuple2<String, Integer>> sum = socketDS
                .flatMap(
                        (String value, Collector<Tuple2<String, Integer>> out) -> {
                            String[] words = value.split(" ");
                            for (String word : words) {
                                out.collect(Tuple2.of(word, 1));
                            }
                        }
                )
                .setParallelism(2)
                // // 显式地提供类型信息:对于flatMap传入Lambda表达式，系统只能推断出返回的是Tuple2类型，而无法得到Tuple2。只有显式设置系统当前返回类型，才能正确解析出完整数据
                .returns(new TypeHint<Tuple2<String, Integer>>() {
                })
//                .returns(Types.TUPLE(Types.STRING,Types.INT))
                .keyBy(value -> value.f0)
                .sum(1);


        // 输出
        sum.print();

        // 执行
        env.execute();
	}
}
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测试：

启动socket流：

nc -l 8888
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本地执行：直接ideal启动main程序，在socket流中输入

abc bcd cde
bcd cde fgh
cde fgh hij
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集群执行：
执行maven打包，将打包的jar上传到集群中