今日总结

标签：总结 java -- flink 如下所示 apache 今日

Flink是Apache软件基金会的一个顶级项目，是为分布式、高性能、随时可用以及准确的流处理应用程序打造的开源流处理框架，并且可以同时支持实时计算和批量计算。Flink起源于Stratosphere 项目，该项目是在2010年到2014年间由柏林工业大学、柏林洪堡大学和哈索普拉特纳研究所联合开展的。2014年4月，Stratosphere代码被贡献给Apache软件基金会，成为Apache软件基金会孵化器项目。之后，团队的大部分创始成员离开大学，共同创办了一家名为Data Artisans的公司。在项目孵化期间，为了避免与另外一个项目发生重名，Stratosphere被重新命名为Flink。在德语中，Flink是“快速和灵巧”的意思，使用这个词作为项目名称，可以彰显流计算框架的速度快和灵活性强的特点。
本教程首先介绍Flink的安装，然后以WordCount程序为实例来介绍Flink编程方法。

一. 安装Flink

Flink的运行需要Java环境的支持，因此，在安装Flink之前，请先参照相关资料安装Java环境（比如Java8）。然后，到Flink官网下载安装包，比如下载得到的安装文件为flink-1.9.1-bin-scala_2.11.tgz，并且保存在Linux系统中（假设当前使用hadoop用户名登录了Linux系统，并且安装文件被保存到了“/home/hadoop/Downloads”目录下）。
也可以直接点击这里从百度云盘下载软件（提取码：ziyu）。进入百度网盘后，进入“软件”目录，找到flink-1.9.1-bin-scala_2.11.tgz文件，下载到本地。

然后，使用如下命令对安装文件进行解压缩：

cd /home/hadoop/Downloads
sudo tar -zxvf flink-1.9.1-bin-scala_2.11.tgz -C /usr/local

Shell 命令

修改目录名称，并设置权限，命令如下：

cd /usr/local
sudo mv ./ flink-1.9.1 ./flink
sudo chown -R hadoop:hadoop ./flink

Shell 命令

Flink对于本地模式是开箱即用的，如果要修改Java运行环境，可以修改“/usr/local/flink/conf/flink-conf.yaml”文件中的env.java.home参数，设置为本地Java的绝对路径。
使用如下命令添加环境变量：

vim ~/.bashrc

Shell 命令

在.bashrc文件中添加如下内容：

export FLINK_HOME=/usr/local/flink
export PATH=$FLINK_HOME/bin:$PATH

保存并退出.bashrc文件，然后执行如下命令让配置文件生效：

source ~/.bashrc

Shell 命令

使用如下命令启动Flink：

cd /usr/local/flink
./bin/start-cluster.sh

Shell 命令

使用jps命令查看进程：

$ jps
17942 TaskManagerRunner
18022 Jps
17503 StandaloneSessionClusterEntrypoint

如果能够看到TaskManagerRunner和StandaloneSessionClusterEntrypoint这两个进程，就说明启动成功。
Flink的JobManager同时会在8081端口上启动一个Web前端，可以在浏览器中输入“http://localhost:8081”来访问。
Flink安装包中自带了测试样例，这里可以运行WordCount样例程序来测试Flink的运行效果，具体命令如下：

cd /usr/local/flink/bin
./flink run /usr/local/flink/examples/batch/WordCount.jar

Shell 命令

执行上述命令以后，如果执行成功，应该可以看到类似如下的屏幕信息：

Starting execution of program
Executing WordCount example with default input data set.
Use --input to specify file input.
Printing result to stdout. Use --output to specify output path.
(a,5)
(action,1)
(after,1)
(against,1)
(all,2)
……

二. 编程实现WordCount程序

编写WordCount程序主要包括以下几个步骤：
（1）安装Maven
（2）编写代码
（3）使用Maven打包Java程序
（4）通过flink run命令运行程序

1. 安装Maven

Ubuntu中没有自带安装Maven，需要手动安装Maven。可以访问Maven官网下载安装文件，下载地址如下：
···
http://apache.fayea.com/maven/maven-3/3.3.9/binaries/apache-maven-3.3.9-bin.zip
···
下载到Maven安装文件以后，保存到“~/Downloads”目录下。然后，可以选择安装在“/usr/local/maven”目录中，命令如下：

sudo unzip ~/Downloads/apache-maven-3.3.9-bin.zip -d /usr/local
cd /usr/local
sudo mv apache-maven-3.3.9/ ./maven
sudo chown -R hadoop ./maven

Shell 命令

2. 编写代码

在Linux终端中执行如下命令，在用户主文件夹下创建一个文件夹flinkapp作为应用程序根目录：

cd ~ #进入用户主文件夹
mkdir -p ./flinkapp/src/main/java

Shell 命令

然后，使用vim编辑器在“./flinkapp/src/main/java”目录下建立三个代码文件，即WordCountData.java、WordCountTokenizer.java和WordCount.java。
WordCountData.java用于提供原始数据，其内容如下：

package cn.edu.xmu;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
public class WordCountData {
public static final String[] WORDS=new String[]{"To be, or not to be,--that is the question:--", "Whether \'tis nobler in the mind to suffer", "The slings and arrows of outrageous fortune", "Or to take arms against a sea of troubles,", "And by opposing end them?--To die,--to sleep,--", "No more; and by a sleep to say we end", "The heartache, and the thousand natural shocks", "That flesh is heir to,--\'tis a consummation", "Devoutly to be wish\'d. To die,--to sleep;--", "To sleep! perchance to dream:--ay, there\'s the rub;", "For in that sleep of death what dreams may come,", "When we have shuffled off this mortal coil,", "Must give us pause: there\'s the respect", "That makes calamity of so long life;", "For who would bear the whips and scorns of time,", "The oppressor\'s wrong, the proud man\'s contumely,", "The pangs of despis\'d love, the law\'s delay,", "The insolence of office, and the spurns", "That patient merit of the unworthy takes,", "When he himself might his quietus make", "With a bare bodkin? who would these fardels bear,", "To grunt and sweat under a weary life,", "But that the dread of something after death,--", "The undiscover\'d country, from whose bourn", "No traveller returns,--puzzles the will,", "And makes us rather bear those ills we have", "Than fly to others that we know not of?", "Thus conscience does make cowards of us all;", "And thus the native hue of resolution", "Is sicklied o\'er with the pale cast of thought;", "And enterprises of great pith and moment,", "With this regard, their currents turn awry,", "And lose the name of action.--Soft you now!", "The fair Ophelia!--Nymph, in thy orisons", "Be all my sins remember\'d."};
public WordCountData() {
}
public static DataSet<String> getDefaultTextLineDataset(ExecutionEnvironment env){
return env.fromElements(WORDS);
}
}

Java

WordCountTokenizer.java用于切分句子，其内容如下：

package cn.edu.xmu;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.util.Collector;
public class WordCountTokenizer implements FlatMapFunction<String, Tuple2<String,Integer>>{
public WordCountTokenizer(){}
public void flatMap(String value, Collector<Tuple2<String, Integer>> out) throws Exception {
String[] tokens = value.toLowerCase().split("\\W+");
int len = tokens.length;
for(int i = 0; i<len;i++){
String tmp = tokens[i];
if(tmp.length()>0){
out.collect(new Tuple2<String, Integer>(tmp,Integer.valueOf(1)));
}
}
}
}

Java

WordCount.java提供主函数，其内容如下：

package cn.edu.xmu;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.operators.AggregateOperator;
import org.apache.flink.api.java.utils.ParameterTool;
public class WordCount {
public WordCount(){}
public static void main(String[] args) throws Exception {
ParameterTool params = ParameterTool.fromArgs(args);
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
env.getConfig().setGlobalJobParameters(params);
Object text;
//如果没有指定输入路径，则默认使用WordCountData中提供的数据
if(params.has("input")){
text = env.readTextFile(params.get("input"));
}else{
System.out.println("Executing WordCount example with default input data set.");
System.out.println("Use -- input to specify file input.");
text = WordCountData.getDefaultTextLineDataset(env);
}
AggregateOperator counts = ((DataSet)text).flatMap(new WordCountTokenizer()).groupBy(new int[]{0}).sum(1);
//如果没有指定输出，则默认打印到控制台
if(params.has("output")){
counts.writeAsCsv(params.get("output"),"\n", " ");
env.execute();
}else{
System.out.println("Printing result to stdout. Use --output to specify output path.");
counts.print();
}
}
}

Java

该程序依赖Flink Java API，因此，我们需要通过Maven进行编译打包。需要新建文件pom.xml，然后，在pom.xml文件中添加如下内容，用来声明该独立应用程序的信息以及与Flink的依赖关系：

<project>
    <groupId>cn.edu.xmu</groupId>
    <artifactId>simple-project</artifactId>
    <modelVersion>4.0.0</modelVersion>
    <name>Simple Project</name>
    <packaging>jar</packaging>
    <version>1.0</version>
    <repositories>
        <repository>
            <id>jboss</id>
            <name>JBoss Repository</name>
            <url>http://repository.jboss.com/maven2/</url>
        </repository>
    </repositories>
    <dependencies>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>1.9.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_2.11</artifactId>
<version>1.9.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_2.11</artifactId>
            <version>1.9.1</version>
        </dependency>
    </dependencies>
</project>

3.使用Maven打包Java程序

为了保证Maven能够正常运行，先执行如下命令检查整个应用程序的文件结构：

cd ~/flinkapp
find .

Shell 命令

文件结构应该是类似如下的内容：

.
./src
./src/main
./src/main/java
./src/main/java/WordCountData.java
./src/main/java/WordCount.java
./src/main/java/WordCountTokenizer.java
./pom.xml

接下来，我们可以通过如下代码将整个应用程序打包成JAR包（注意：计算机需要保持连接网络的状态，而且首次运行打包命令时，Maven会自动下载依赖包，需要消耗几分钟的时间）：

cd ~/flinkapp #一定把这个目录设置为当前目录
/usr/local/maven/bin/mvn package

Shell 命令

如果屏幕返回的信息中包含“BUILD SUCCESS”，则说明生成JAR包成功。

4.通过flink run命令运行程序

最后，可以将生成的JAR包通过flink run命令提交到Flink中运行（请确认已经启动Flink），命令如下：

/usr/local/flink/bin/flink run --class cn.edu.xmu.WordCount ~/flinkapp/target/simple-project-1.0.jar

Shell 命令

执行成功后，可以在屏幕上看到词频统计结果。

三、使用IntelliJ IDEA开发调试WordCount程序

请参考相关网络资料完成IntelliJ IDEA的安装。
在开始本实验之前，首先要启动Flink。
下面介绍如何使用IntelliJ IDEA工具开发WordCount程序。
启动进入IDEA，如下图所示，新建一个项目。

执行如下图所示的操作。

如下图所示，填写GroupId和ArtifactId。这里的GroupId是dblab，ArtifactId是FlinkWordCount。

如下图所示，设置Project name为FlinkWordCount。

如果出现如下图所示内容，则点击Enable Auto-Import。

这时生成的项目目录结构如下图所示。

打开pom.xml文件，输入如下内容：

<?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>dblab</groupId>
    <artifactId>FlinkWordCount</artifactId>
    <version>1.0-SNAPSHOT</version>

    <dependencies>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>1.9.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_2.11</artifactId>
            <version>1.9.1</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_2.11</artifactId>
            <version>1.9.1</version>
        </dependency>
    </dependencies>

如下图所示，创建Package。

如下图所示，输入package的名称为“cn.edu.xmu”。

如下图所示，新建一个java class文件。

如下图所示，输入文件名称WordCountData。

WordCountData.java用于提供原始数据，其内容如下：

package cn.edu.xmu;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
public class WordCountData {
public static final String[] WORDS=new String[]{"To be, or not to be,--that is the question:--", "Whether \'tis nobler in the mind to suffer", "The slings and arrows of outrageous fortune", "Or to take arms against a sea of troubles,", "And by opposing end them?--To die,--to sleep,--", "No more; and by a sleep to say we end", "The heartache, and the thousand natural shocks", "That flesh is heir to,--\'tis a consummation", "Devoutly to be wish\'d. To die,--to sleep;--", "To sleep! perchance to dream:--ay, there\'s the rub;", "For in that sleep of death what dreams may come,", "When we have shuffled off this mortal coil,", "Must give us pause: there\'s the respect", "That makes calamity of so long life;", "For who would bear the whips and scorns of time,", "The oppressor\'s wrong, the proud man\'s contumely,", "The pangs of despis\'d love, the law\'s delay,", "The insolence of office, and the spurns", "That patient merit of the unworthy takes,", "When he himself might his quietus make", "With a bare bodkin? who would these fardels bear,", "To grunt and sweat under a weary life,", "But that the dread of something after death,--", "The undiscover\'d country, from whose bourn", "No traveller returns,--puzzles the will,", "And makes us rather bear those ills we have", "Than fly to others that we know not of?", "Thus conscience does make cowards of us all;", "And thus the native hue of resolution", "Is sicklied o\'er with the pale cast of thought;", "And enterprises of great pith and moment,", "With this regard, their currents turn awry,", "And lose the name of action.--Soft you now!", "The fair Ophelia!--Nymph, in thy orisons", "Be all my sins remember\'d."};
public WordCountData() {
}
public static DataSet<String> getDefaultTextLineDataset(ExecutionEnvironment env){
return env.fromElements(WORDS);
}
}

Java

按照刚才同样的操作，创建第2个文件WordCountTokenizer.java。
WordCountTokenizer.java用于切分句子，其内容如下：

package cn.edu.xmu;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.util.Collector;
public class WordCountTokenizer implements FlatMapFunction<String, Tuple2<String,Integer>>{
public WordCountTokenizer(){}
public void flatMap(String value, Collector<Tuple2<String, Integer>> out) throws Exception {
String[] tokens = value.toLowerCase().split("\\W+");
int len = tokens.length;
for(int i = 0; i<len;i++){
String tmp = tokens[i];
if(tmp.length()>0){
out.collect(new Tuple2<String, Integer>(tmp,Integer.valueOf(1)));
}
}
}
}

Java

按照刚才同样的操作，创建第3个文件WordCount.java。
WordCount.java提供主函数，其内容如下：

package cn.edu.xmu;
import org.apache.flink.api.java.DataSet;
import org.apache.flink.api.java.ExecutionEnvironment;
import org.apache.flink.api.java.operators.AggregateOperator;
import org.apache.flink.api.java.utils.ParameterTool;
public class WordCount {
public WordCount(){}
public static void main(String[] args) throws Exception {
ParameterTool params = ParameterTool.fromArgs(args);
ExecutionEnvironment env = ExecutionEnvironment.getExecutionEnvironment();
env.getConfig().setGlobalJobParameters(params);
Object text;
//如果没有指定输入路径，则默认使用WordCountData中提供的数据
if(params.has("input")){
text = env.readTextFile(params.get("input"));
}else{
System.out.println("Executing WordCount example with default input data set.");
System.out.println("Use -- input to specify file input.");
text = WordCountData.getDefaultTextLineDataset(env);
}
AggregateOperator counts = ((DataSet)text).flatMap(new WordCountTokenizer()).groupBy(new int[]{0}).sum(1);
//如果没有指定输出，则默认打印到控制台
if(params.has("output")){
counts.writeAsCsv(params.get("output"),"\n", " ");
env.execute();
}else{
System.out.println("Printing result to stdout. Use --output to specify output path.");
counts.print();
}
}
}