大数据实验实验七：Flink初级编程实践

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大数据实验实验七：Flink初级编程实践

实验环境：Windows 10 Oracle VM VirtualBox

虚拟机：cnetos 7

Hadoop 3.3

实验内容与完成情况：

1. 使用IntelliJ IDEA工具开发WordCount程序

在Linux操作系统中安装IntelliJ IDEA，然后使用IntelliJ IDEA工具开发WordCount程序，并打包成JAR包，提交到Flink中运行。

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下载flink安装包后解压

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启动flink,

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程序原码

WordCountData

package WordCount;
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 getDefaultTextLineDataset(ExecutionEnvironment env) {
        return env.fromElements(WORDS);
    }
}

WordCountTokenizer

package WordCount;
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> {
    public void flatMap(String value, Collector> 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(tmp, Integer.valueOf(1)));
            }
        }
    }
}

WordCount

package WordCount;
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();
        }
    }
}

运行成功

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2. 数据流词频统计

使用Linux操作系统自带的NC程序模拟生成数据流，不断产生单词并发送出去。编写Fink程序对NC程序发来的单词进行实时处理，计算词频，并输出词频统计结果。要求首先在IntelliJ IDEA中开发和调试程序，然后打包成JAR包部署到Flink中运行。

编写程序

package WordCount;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
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 WordCount {
    public static void main(String[] args) throws Exception {
//定义socket的端口号
        int port;
        try {
            ParameterTool parameterTool = ParameterTool.fromArgs(args);
            port = parameterTool.getInt("port");
        } catch (Exception e) {
            System.err.println("指定port参数，默认值为9000");
            port = 9000;
        }
//获取运行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
//连接socket获取输入的数据
        DataStreamSource text = env.socketTextStream("127.0.0.1", port, "\n");
//计算数据
        DataStream windowCount = text.flatMap(new FlatMapFunction() {
                    public void flatMap(String value, Collector out) throws Exception {
                        String[] splits = value.split("\\s");
                        for (String word : splits) {
                            out.collect(new WordWithCount(word, 1L));
                        }
                    }
                })//打平操作，把每行的单词转为类型的数据
                .keyBy("word")//针对相同的word数据进行分组
                .timeWindow(Time.seconds(2), Time.seconds(1))//指定计算数据的窗口大小和滑动窗口大小
                .sum("count");
//把数据打印到控制台
        windowCount.print()
                .setParallelism(1);//使用一个并行度
//注意：因为flink是懒加载的，所以必须调用execute方法，上面的代码才会执行
        env.execute("streaming word count");
    }
    /**
     * 主要为了存储单词以及单词出现的次数
     */
    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 "WordWithCount{" +
                    "word='" + word + '\'' +
                    ", count=" + count +
                    '}';
        }
    }

运行包

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