第十章 Flink专题之代码开发细节

业务需求：统计下列单词并打印输出

hadoop spark flink
hadoop spark flink
hadoop spark flink
hadoop spark flink
hadoop spark flink
hadoop spark flink

package flink.demo;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;

public class WordCount0 {
    public static void main(String[] args) throws Exception {
        // 1、创建执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        // 2、读取 文件数据 数据
        DataStreamSource inputDataStream = env.readTextFile("H:\flink_demo\flink_test\src\main\resources\wordcount.txt");

        // 3、计算
        SingleOutputStreamOperator> resultDataStream = inputDataStream.flatMap(new FlatMapFunction>() {
            @Override
            public void flatMap(String input, Collector> collector) throws Exception {
                String[] words = input.split(" ");
                for (String word : words) {
                    collector.collect(new Tuple2<>(word, 1));
                }
            }
        }).keyBy(0)
                .sum(1);

        // 4、输出
        resultDataStream.print();

        // 5、启动 env
        env.execute();
    }
}

运行结果

优化点：把数据看成对象，遇到字段较多的数据操作比较方便 2.1、自定义对象数据结构

public class WordAndCount {

    private String word;
    private int count;

    public WordAndCount() {
    }

    public WordAndCount(String word, int count) {
        this.word = word;
        this.count = count;
    }

    public String getWord() {
        return word;
    }

    public void setWord(String word) {
        this.word = word;
    }

    public int getCount() {
        return count;
    }

    public void setCount(int count) {
        this.count = count;
    }

    @Override
    public String toString() {
        return "WordAndCount{" +
                "word='" + word + ''' +
                ", count=" + count +
                '}';
    }
}

public class WordCount {
    public static void main(String[] args) throws Exception {
        // 1、创建执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        // 2、读取数据
        DataStreamSource inputDataStream = env.readTextFile("H:\flink_demo\flink_test\src\main\resources\wordcount.txt");

        // 3、扁平化 + 分组 + sum
        SingleOutputStreamOperator resultData = inputDataStream.flatMap(new FlatMapFunction() {
            @Override
            public void flatMap(String line, Collector out) throws Exception {
                String[] fields = line.split(" ");
                for (String word : fields) {
                    out.collect(new WordAndCount(word, 1));
                }
            }
        }).keyBy("word").sum("count");

        resultData.print();

        // 4、启动 env
        env.execute();
    }
}

运行结果

优化：业务逻辑核心算子单独实现，代码便于阅读 3.1、自定义对象的数据结构

public class WordAndCount {

    private String word;
    private int count;

    public WordAndCount() {
    }

    public WordAndCount(String word, int count) {
        this.word = word;
        this.count = count;
    }

    public String getWord() {
        return word;
    }

    public void setWord(String word) {
        this.word = word;
    }

    public int getCount() {
        return count;
    }

    public void setCount(int count) {
        this.count = count;
    }

    @Override
    public String toString() {
        return "WordAndCount{" +
                "word='" + word + ''' +
                ", count=" + count +
                '}';
    }
}

public static class SplitLine implements FlatMapFunction{

    @Override
    public void flatMap(String line, Collector out) throws Exception {
        String[] fields = line.split(" ");
        for (String word : fields) {
            out.collect(new WordAndCount(word, 1));
        }
    }
}

public static void main(String[] args) throws Exception {
    // 1、创建执行环境
    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    env.setParallelism(1);
    // 2、读取数据
    DataStreamSource inputDataStream = env.readTextFile("H:\flink_demo\flink_test\src\main\resources\wordcount.txt");

    // 3、扁平化 + 分组 + sum
    SingleOutputStreamOperator resultData = inputDataStream.flatMap(new SplitLine()).keyBy("word").sum("count");

    // 4、打印输出
    resultData.print();

    // 5、启动 env
    env.execute();
}

运行结果

优化点：flink建议如果程序中需要传入参数，使用它提供的ParameterTool。 4.1、自定义对象的数据结构

public class WordAndCount {

    private String word;
    private int count;

    public WordAndCount() {
    }

    public WordAndCount(String word, int count) {
        this.word = word;
        this.count = count;
    }

    public String getWord() {
        return word;
    }

    public void setWord(String word) {
        this.word = word;
    }

    public int getCount() {
        return count;
    }

    public void setCount(int count) {
        this.count = count;
    }

    @Override
    public String toString() {
        return "WordAndCount{" +
                "word='" + word + ''' +
                ", count=" + count +
                '}';
    }
}

public static class SplitLine implements FlatMapFunction{

    @Override
    public void flatMap(String line, Collector out) throws Exception {
        String[] fields = line.split(" ");
        for (String word : fields) {
            out.collect(new WordAndCount(word, 1));
        }
    }
}

public static void main(String[] args) throws Exception {
    // 1、创建执行环境
    StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
    env.setParallelism(1);
    // 2、读取数据
    //flink提供的工具类，获取传递的参数
    ParameterTool parameterTool = ParameterTool.fromArgs(args);
    String path = parameterTool.get("path");
    DataStreamSource dataStream = env.readTextFile(path);

    // 3、扁平化 + 分组 + sum
    SingleOutputStreamOperator resultData = dataStream.flatMap(new SplitLine()).keyBy("word").sum("count");

    // 4、打印输出
    resultData.print();

    // 5、启动 env
    env.execute();
}

参数传递

运行结果

    4.0.0

    org.example
    flinkdemo
    1.0-SNAPSHOT

    
        1.8
        2.11
        1.9.3
        1.10.0
        2.7.3
        1.2.72
        2.9.0
        5.1.35
        1.2.17
        1.7.7
        1.8
        1.8
        1.8
        UTF-8
        compile
        
        com.hainiu.Driver
    

    
        
            org.slf4j
            slf4j-log4j12
            ${slf4j.version}
            ${project.build.scope}
        

        
            log4j
            log4j
            ${log4j.version}
            ${project.build.scope}
        
        
        
            org.apache.hadoop
            hadoop-client
            ${hadoop.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-hadoop-compatibility_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-java
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-streaming-java_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-scala_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-streaming-scala_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-runtime-web_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-statebackend-rocksdb_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-hbase_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-connector-elasticsearch5_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-connector-kafka-0.10_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            org.apache.flink
            flink-connector-filesystem_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            mysql
            mysql-connector-java
            ${mysql.version}
            ${project.build.scope}
        
        
        
            redis.clients
            jedis
            ${redis.version}
            ${project.build.scope}
        
        
        
            org.apache.parquet
            parquet-avro
            ${parquet.version}
            ${project.build.scope}
        
        
            org.apache.parquet
            parquet-hadoop
            ${parquet.version}
            ${project.build.scope}
        
        
            org.apache.flink
            flink-parquet_${scala.version}
            ${flink.version}
            ${project.build.scope}
        
        
        
            com.alibaba
            fastjson
            ${fastjson.version}
            ${project.build.scope}
        
    

    
        
            
                src/main/resources
            
        
        
            
                org.apache.maven.plugins
                maven-assembly-plugin
                
                    
                        src/assembly/assembly.xml
                    
                    
                        
                            ${mainClass}
                        
                    
                
                
                    
                        make-assembly
                        package
                        
                            single
                        
                    
                
            
            
                org.apache.maven.plugins
                maven-surefire-plugin
                2.12
                
                    true
                    once
                    
                        **/**
                    
                
            
            
                org.apache.maven.plugins
                maven-compiler-plugin
                3.1
                
                    ${java.version}
                    ${java.version}
                    ${project.build.sourceEncoding}
                
            
        
    

package flink.demo;

public class WordAndCount {

    private String word;
    private int count;

    public WordAndCount() {
    }

    public WordAndCount(String word, int count) {
        this.word = word;
        this.count = count;
    }

    public String getWord() {
        return word;
    }

    public void setWord(String word) {
        this.word = word;
    }

    public int getCount() {
        return count;
    }

    public void setCount(int count) {
        this.count = count;
    }

    @Override
    public String toString() {
        return "WordAndCount{" +
                "word='" + word + ''' +
                ", count=" + count +
                '}';
    }
}

package flink.demo;

import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.java.utils.ParameterTool;
import org.apache.flink.streaming.api.datastream.DataStreamSource;
import org.apache.flink.streaming.api.datastream.SingleOutputStreamOperator;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.util.Collector;

public class WordCount {
    public static void main(String[] args) throws Exception {
        // 1、创建执行环境
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        env.setParallelism(1);
        // 2、读取数据
        //flink提供的工具类，获取传递的参数
        ParameterTool parameterTool = ParameterTool.fromArgs(args);
        String path = parameterTool.get("path");
        DataStreamSource dataStream = env.readTextFile(path);

        // 3、扁平化 + 分组 + sum
        SingleOutputStreamOperator resultData = dataStream.flatMap(new SplitLine()).keyBy("word").sum("count");

        // 4、打印输出
        resultData.print();

        // 5、启动 env
        env.execute();
    }

    // 业务逻辑抽离：核心算子单独实现
    public static class SplitLine implements FlatMapFunction{

        @Override
        public void flatMap(String line, Collector out) throws Exception {
            String[] fields = line.split(" ");
            for (String word : fields) {
                out.collect(new WordAndCount(word, 1));
            }
        }
    }
}