Flink 初探

一、前言
随着新兴的大数据处理框架不断推陈出新，storm已经逐渐淡出了人们的视野，storm的社区已经有近3年无人维护。storm已经被Flink替代，接下来，我们就以Flink框架作为大数据处理的核心框架进行研究，并把storm中的代码移植到Flink中。

先分析一下Flink的优势，了解一下选用Flink的优势和必要性。
具体的Flink优势和特点，可以从网上进行搜索去查看。具体内容，参考以下几个链接：
https://www.infoq.cn/article/fRt1RF1pxu_ZtmeObOoJ

本文主要以实战为主，先构建Flink的运行环境，通过实际运行代码来感受和分析Flink。

二、helloworld 初试
1.1 搭建运行环境

使用docker快速搭建和启动Flink环境。docker的具体使用，请网上自行检索。
docker-compose.yml

version: "2.1"
services:
  jobmanager:
    image: flink
    expose:
      - "6123"
    ports:
      - "8081:8081"
    command: jobmanager
    environment:
      - JOB_MANAGER_RPC_ADDRESS=jobmanager
 
  taskmanager:
    image: flink
    expose:
      - "6121"
      - "6122"
    depends_on:
      - jobmanager
    command: taskmanager
    links:
      - "jobmanager:jobmanager"
    environment:
      - JOB_MANAGER_RPC_ADDRESS=jobmanager

1.2 编写 helloword
maven工程配置文件：pom.xml

<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>com.tchen</groupId>
  <artifactId>flink</artifactId>
  <version>0.0.1-SNAPSHOT</version>
  <packaging>jar</packaging>

  <name>flink</name>
  <url>http://maven.apache.org</url>

  <properties>
		<project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
		<flink.version>1.7.0</flink.version>
		<java.version>1.8</java.version>
		<scala.binary.version>2.11</scala.binary.version>
		<maven.compiler.source>${java.version}</maven.compiler.source>
		<maven.compiler.target>${java.version}</maven.compiler.target>
	</properties>

	<repositories>
		<repository>
			<id>apache.snapshots</id>
			<name>Apache Development Snapshot Repository</name>
			<url>https://repository.apache.org/content/repositories/snapshots/</url>
			<releases>
				<enabled>false</enabled>
			</releases>
			<snapshots>
				<enabled>true</enabled>
			</snapshots>
		</repository>
	</repositories>

	<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>

	<build>
		<plugins>

			<!-- Java Compiler -->
			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-compiler-plugin</artifactId>
				<version>3.1</version>
				<configuration>
					<source>${java.version}</source>
					<target>${java.version}</target>
				</configuration>
			</plugin>

			<!-- We use the maven-shade plugin to create a fat jar that contains all necessary dependencies. -->
			<!-- Change the value of <mainClass>...</mainClass> if your program entry point changes. -->
			<plugin>
				<groupId>org.apache.maven.plugins</groupId>
				<artifactId>maven-shade-plugin</artifactId>
				<version>3.0.0</version>
				<executions>
					<!-- Run shade goal on package phase -->
					<execution>
						<phase>package</phase>
						<goals>
							<goal>shade</goal>
						</goals>
						<configuration>
							<artifactSet>
								<excludes>
									<exclude>org.apache.flink:force-shading</exclude>
									<exclude>com.google.code.findbugs:jsr305</exclude>
									<exclude>org.slf4j:*</exclude>
									<exclude>log4j:*</exclude>
								</excludes>
							</artifactSet>
							<filters>
								<filter>
									<!-- Do not copy the signatures in the META-INF folder.
									Otherwise, this might cause SecurityExceptions when using the JAR. -->
									<artifact>*:*</artifact>
									<excludes>
										<exclude>META-INF/*.SF</exclude>
										<exclude>META-INF/*.DSA</exclude>
										<exclude>META-INF/*.RSA</exclude>
									</excludes>
								</filter>
							</filters>
							<transformers>
								<transformer implementation="org.apache.maven.plugins.shade.resource.ManifestResourceTransformer">
									<mainClass>com.dalong.app.StreamingJob</mainClass>
								</transformer>
							</transformers>
						</configuration>
					</execution>
				</executions>
			</plugin>
		</plugins>

		<pluginManagement>
			<plugins>

				<!-- This improves the out-of-the-box experience in Eclipse by resolving some warnings. -->
				<plugin>
					<groupId>org.eclipse.m2e</groupId>
					<artifactId>lifecycle-mapping</artifactId>
					<version>1.0.0</version>
					<configuration>
						<lifecycleMappingMetadata>
							<pluginExecutions>
								<pluginExecution>
									<pluginExecutionFilter>
										<groupId>org.apache.maven.plugins</groupId>
										<artifactId>maven-shade-plugin</artifactId>
										<versionRange>[3.0.0,)</versionRange>
										<goals>
											<goal>shade</goal>
										</goals>
									</pluginExecutionFilter>
									<action>
										<ignore/>
									</action>
								</pluginExecution>
								<pluginExecution>
									<pluginExecutionFilter>
										<groupId>org.apache.maven.plugins</groupId>
										<artifactId>maven-compiler-plugin</artifactId>
										<versionRange>[3.1,)</versionRange>
										<goals>
											<goal>testCompile</goal>
											<goal>compile</goal>
										</goals>
									</pluginExecutionFilter>
									<action>
										<ignore/>
									</action>
								</pluginExecution>
							</pluginExecutions>
						</lifecycleMappingMetadata>
					</configuration>
				</plugin>
			</plugins>
		</pluginManagement>
	</build>

	<!-- This profile helps to make things run out of the box in IntelliJ -->
	<!-- Its adds Flink's core classes to the runtime class path. -->
	<!-- Otherwise they are missing in IntelliJ, because the dependency is 'provided' -->
	<profiles>
		<profile>
			<id>add-dependencies-for-IDEA</id>

			<activation>
				<property>
					<name>idea.version</name>
				</property>
			</activation>

			<dependencies>
				<dependency>
					<groupId>org.apache.flink</groupId>
					<artifactId>flink-java</artifactId>
					<version>${flink.version}</version>
					<scope>compile</scope>
				</dependency>
				<dependency>
					<groupId>org.apache.flink</groupId>
					<artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
					<version>${flink.version}</version>
					<scope>compile</scope>
				</dependency>
			</dependencies>
		</profile>
	</profiles>
  
</project>

java程序：helloworld.java

package com.tchen.flink.helloworld;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.functions.ReduceFunction;
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;

public class SocketWindowWordCount {

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

        // 输入tcp流
        final int port;
        final String host;
        port = 9008; // nc监听的tcp端口
        host = "10.10.50.70"; // docker宿主机ip

        // get the execution environment
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        // get input data by connecting to the socket
        DataStream<String> text = env.socketTextStream(host, port, "\n");

        // parse the data, group it, window it, and aggregate the counts
        DataStream<WordWithCount> windowCounts = text
                .flatMap(new FlatMapFunction<String, WordWithCount>() {
//                    @Override
                    public void flatMap(String value, Collector<WordWithCount> out) {
                        for (String word : value.split("\\s")) {
                            out.collect(new WordWithCount(word, 1L));
                        }
                    }
                })
                .keyBy("word")
                .timeWindow(Time.seconds(5), Time.seconds(1))
                .reduce(new ReduceFunction<WordWithCount>() {
//                    @Override
                    public WordWithCount reduce(WordWithCount a, WordWithCount b) {
                        return new WordWithCount(a.word, a.count + b.count);
                    }
                });

        // print the results with a single thread, rather than in parallel
        windowCounts.print().setParallelism(1);

        env.execute("Socket Window WordCount");
    }

    // Data type for words with count
    public static class WordWithCount {

        public String word;
        public long count;

        public WordWithCount() {}

        public WordWithCount(String word, long count) {
            this.word = word;
            this.count = count;
        }

        @Override
        public String toString() {
            return word + " : " + count;
        }
    }
}

三、本地调试
示例代码：FlinkLocal.java

package com.tchen.flink.local;

import org.apache.flink.api.common.JobExecutionResult;
import org.apache.flink.api.common.functions.FilterFunction;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;

public class FlinkLocal {

	public static void main(String[] args) throws Exception {
	    ExecutionEnvironment env = ExecutionEnvironment.createLocalEnvironment();

	    DataSet<String> data = env.readTextFile("file:///d:/flink-data.txt");

	    data
	        .filter(new FilterFunction<String>() {
	            public boolean filter(String value) {
	                return value.startsWith("http://");
	            }
	        })
	        .writeAsText("file:///d:/flink-data-out.txt");

	    JobExecutionResult res = env.execute();
	}
}

参考资料：

官方：
https://ci.apache.org/projects/flink/flink-docs-release-1.9/getting-started/tutorials/local_setup.html
https://github.com/apache/flink/blob/master/flink-examples/flink-examples-streaming/pom.xml
https://flink-docs-cn.gitbook.io/project/05-ying-yong-kai-fa/batch-dataset-api/ben-di-zhi-hang

https://www.iamle.com/archives/2572.html
https://juejin.im/post/5c4f16dbe51d454f342fb7e7
https://www.infoq.cn/article/zbBAGroBgtytDiBs*Xq9