Flink Java Demo（Windows）

关于Flink相关的概念性东西就不说了，网上都有，官网也很详尽。本文主要记录一下Java使用Flink的简单例子。

首先，去官网下载Flink的zip包（链接就不提供了，你已经是个成熟的程序员了，该有一定的搜索能力了），解压后放到你想放的地方。

进入主目录后，是这样子的

 

image.png

你可以简单的看下其目录结构，然后就回到你喜欢的IDE创建一个工程吧。

使用IDEA创建一个maven项目，然后加入相应的依赖即可。也可以按照Flink官网的方式去创建一个maven工程，然后导入你喜欢的IDE。下面是官网的quickstart里的maven依赖。

    <dependencies>
        <!-- Apache Flink dependencies -->
        <!-- These dependencies are provided, because they should not be packaged into the JAR file. -->
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
            <scope>provided</scope>
        </dependency>

        <!-- Add connector dependencies here. They must be in the default scope (compile). -->

        <!-- Example:

        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka-0.10_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        -->

        <!-- Add logging framework, to produce console output when running in the IDE. -->
        <!-- These dependencies are excluded from the application JAR by default. -->
        <dependency>
            <groupId>org.slf4j</groupId>
            <artifactId>slf4j-log4j12</artifactId>
            <version>1.7.7</version>
            <scope>runtime</scope>
        </dependency>
        <dependency>
            <groupId>log4j</groupId>
            <artifactId>log4j</artifactId>
            <version>1.2.17</version>
            <scope>runtime</scope>
        </dependency>
    </dependencies>

创建工程后我们就可以写代码了，以下的例子和官网上的差不多，直接上代码

package org.myorg.quickstart;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.windowing.time.Time;
import org.apache.flink.util.Collector;

/**
 * Skeleton for a Flink Streaming Job.
 *
 * <p>For a tutorial how to write a Flink streaming application, check the
 * tutorials and examples on the <a href="http://flink.apache.org/docs/stable/">Flink Website</a>.
 *
 * <p>To package your appliation into a JAR file for execution, run
 * 'mvn clean package' on the command line.
 *
 * <p>If you change the name of the main class (with the public static void main(String[] args))
 * method, change the respective entry in the POM.xml file (simply search for 'mainClass').
 */
public class StreamingJob {

    public static void main(String[] args) throws Exception {
        // set up the streaming execution environment
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        /*
         * Here, you can start creating your execution plan for Flink.
         *
         * Start with getting some data from the environment, like
         *  env.readTextFile(textPath);
         *
         * then, transform the resulting DataStream<String> using operations
         * like
         *  .filter()
         *  .flatMap()
         *  .join()
         *  .coGroup()
         *
         * and many more.
         * Have a look at the programming guide for the Java API:
         *
         * http://flink.apache.org/docs/latest/apis/streaming/index.html
         *
         */

        DataStream<String> text = env.socketTextStream("127.0.0.1", 9000);
        DataStream<Tuple2<String, Integer>> dataStream = text.flatMap(new FlatMapFunction<String, Tuple2<String, Integer>>() {
            @Override
            public void flatMap(String s, Collector<Tuple2<String, Integer>> collector) throws Exception {
                String[] tokens = s.toLowerCase().split("\W+");

                for (String token : tokens) {
                    if (token.length() > 0) {
                        collector.collect(new Tuple2<String, Integer>(token, 1));
                    }
                }
            }
        }).keyBy(0).timeWindow(Time.seconds(5)).sum(1);

        dataStream.print();
        // execute program
        env.execute("Java WordCount from SocketTextStream Example");
    }
}

大家都是文化人，注释已经很详尽了，就不翻译了，唯一需要注意的是，IDEA好像不支持它的lambda表达式，所以我这里没有直接变lambda。

接下来就是激动人心的运行环节，Windows需要安装个瑞士军刀来支持nc命令（直接在官网下个zip包，解压，配置到环境变量即可）。在命令行中执行 nc -l -p 9000，然后运行上边那个程序（如果先运行程序会因为连接不到socket报错）

 

image.png

随便输入，然后在IDEA的console中可以看到如下的结果。

 

image.png

以上因为没启动Flink服务，所以不需要像其他博主那样，去localhost:8081的webUI中进行监控
，StreamExecutionEnvironment.getExecutionEnvironment()会创建一个LocalEnvironment然后在Java虚拟机上执行。

Windows单机模式下启动Flink相当简单，进入到bin目录，直接双击start-cluster.bat，会启动Flink的JobManager和TaskManager两个服务。如果想将上述程序提交到Flink，需要执行maven命令打成jar包，然后在命令行中，进入到bin目录下执行 flink.bat run xxxx/xxx/xxx.jar 即可，输出结果会在TaskManager的服务窗口中输出。

作者：瓜尔佳_半阙
链接：https://www.jianshu.com/p/f8b66afd32bf
來源：简书
简书著作权归作者所有，任何形式的转载都请联系作者获得授权并注明出处。