Flink-05 Flink Java 3分钟上手 Redis FlinkJedisPoolConfig 从Kafka写入Redis FlinkKafkaConsumer消费 结果写入Redis 原创

代码仓库

会同步代码到 GitHub
https://github.com/turbo-duck/flink-demo

内容介绍

上节我们已经实现了，对Kafka数据的消费和计算，最终把结果输出到了控制台上。如下图：

Kafka In Docker

TestKafkaProducer

将数据写入到Kafka中的效果

FlinkConsumer

Flink消费Kafka的效果如下图，已经按照我们的需求进行计算了。

这节内容

本节依然使用Flink对Kafka进行消费，但与上节不同的是（上节将结果输出到控制台上），本节将把Flink计算的结果输出到Redis中进行保存（当然也可以存储到别的地方，这里以Redis为例）。

pom.xml

重点关注 flink-connector-redis_2.11 这个包。这是Redis相关的依赖。

<?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>org.example</groupId>
    <artifactId>flink-demo-01</artifactId>
    <version>1.0-SNAPSHOT</version>

    <properties>
        <maven.compiler.source>8</maven.compiler.source>
        <maven.compiler.target>8</maven.compiler.target>
        <flink.version>1.13.2</flink.version>
        <scala.binary.version>2.12</scala.binary.version>
    </properties>

    <dependencies>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-java</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-streaming-java_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-clients_${scala.binary.version}</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-kafka_2.11</artifactId>
            <version>${flink.version}</version>
        </dependency>
        <dependency>
            <groupId>org.apache.kafka</groupId>
            <artifactId>kafka-clients</artifactId>
            <version>3.0.0</version>
        </dependency>
        <dependency>
            <groupId>org.apache.flink</groupId>
            <artifactId>flink-connector-redis_2.11</artifactId>
            <version>1.1.0</version>
        </dependency>

    </dependencies>
</project>

KafkaProducer.java

生产数据存入到Kafka这种

package icu.wzk.demo05;

import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.ProducerRecord;

import java.util.Properties;

public class TestKafkaProducer {

    public static void main(String[] args) throws InterruptedException {
        Properties props = new Properties();
        props.put("bootstrap.servers", "0.0.0.0:9092");
        props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        props.put("value.serializer", "org.apache.kafka.common.serialization.StringSerializer");
        Producer<String, String> producer = new KafkaProducer<>(props);
        for (int i = 0; i < 500; i++) {
            String key = "key-" + i;
            String value = "value-" + i;
            ProducerRecord<String, String> record = new ProducerRecord<>("test", key, value);
            producer.send(record);
            System.out.println("send: " + key);
            Thread.sleep(200);
        }
        producer.close();
    }

}

StartApp

Flink消费Kafka，计算后写入到Redis中。

FlinkJedisPoolConfig

连接池的配置

MyRedisMapper

自定义的Mapper，需要实现RedisMapper

完整代码

package icu.wzk.demo05;


import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.serialization.SimpleStringSchema;
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.streaming.connectors.kafka.FlinkKafkaConsumer;
import org.apache.flink.streaming.connectors.redis.RedisSink;
import org.apache.flink.streaming.connectors.redis.common.config.FlinkJedisPoolConfig;
import org.apache.flink.streaming.connectors.redis.common.mapper.RedisCommand;
import org.apache.flink.streaming.connectors.redis.common.mapper.RedisCommandDescription;
import org.apache.flink.streaming.connectors.redis.common.mapper.RedisMapper;

import java.util.Properties;

public class StartApp {

    private static final String KAFKA_SERVER = "0.0.0.0:9092";

    private static final Integer KAFKA_PORT = 9092;

    private static final String KAFKA_TOPIC = "test";

    private static final String REDIS_SERVER = "0.0.0.0";

    private static final Integer REDIS_PORT = 6379;

    public static void main(String[] args) throws Exception {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        Properties properties = new Properties();
        properties.setProperty("bootstrap.servers", String.format("%s:%d", KAFKA_SERVER, KAFKA_PORT));
        FlinkKafkaConsumer<String> consumer = new FlinkKafkaConsumer<>(KAFKA_TOPIC, new SimpleStringSchema(), properties);
        DataStreamSource<String> data = env.addSource(consumer);

        SingleOutputStreamOperator<Tuple2<String, String>> wordData = data.map(new MapFunction<String, Tuple2<String, String>>() {
            @Override
            public Tuple2<String, String> map(String value) throws Exception {
                return new Tuple2<>("l_words", value);
            }
        });

        FlinkJedisPoolConfig conf = new FlinkJedisPoolConfig
                .Builder()
                .setHost(REDIS_SERVER)
                .setPort(REDIS_PORT)
                .build();
        RedisSink<Tuple2<String, String>> redisSink = new RedisSink<>(conf, new MyRedisMapper());
        wordData.addSink(redisSink);
        env.execute();
    }

    public static class MyRedisMapper implements RedisMapper<Tuple2<String,String>> {

        @Override
        public RedisCommandDescription getCommandDescription() {
            return new RedisCommandDescription(RedisCommand.LPUSH);
        }

        @Override
        public String getKeyFromData(Tuple2<String,String> data) {
            return data.f0;
        }

        @Override
        public String getValueFromData(Tuple2<String,String> data) {
            return data.f1;
        }
    }

}