Flink-Connectors(连接器)（2）Redis

flink 提供了专门操作redis 的RedisSink，使用起来更方便，而且不用我们考虑性能的问题，接下来将主要介绍RedisSink 如何使用

https://bahir.apache.org/docs/flink/current/flink-streaming-redis/

必要依赖

<dependency>
    <groupId>org.apache.bahir</groupId>
    <artifactId>flink-connector-redis_2.11</artifactId>
    <version>1.0</version>
    <exclusions>
        <exclusion>
            <artifactId>flink-streaming-java_2.11</artifactId>
            <groupId>org.apache.flink</groupId>
        </exclusion>
        <exclusion>
            <artifactId>flink-runtime_2.11</artifactId>
            <groupId>org.apache.flink</groupId>
        </exclusion>
        <exclusion>
            <artifactId>flink-core</artifactId>
            <groupId>org.apache.flink</groupId>
        </exclusion>
        <exclusion>
            <artifactId>flink-java</artifactId>
            <groupId>org.apache.flink</groupId>
        </exclusion>
    </exclusions>
</dependency>

RedisSink 的核心类是RedisMapper， 其是一个接口，使用时我们要编写自己的redis 操作类实现这个接口中的三个方法

1.getCommandDescription() ：

设置使用的redis 数据结构类型，和key 的名称，通过RedisCommand 设置数据结构类型

2.String getKeyFromData(T data)：

设置value 中的键值对key的值

3.String getValueFromData(T data);

设置value 中的键值对value的值

代码示例

package com.leilei;

import com.alibaba.fastjson.JSON;
import lombok.AllArgsConstructor;
import lombok.Data;
import lombok.NoArgsConstructor;
import org.apache.flink.api.common.functions.FlatMapFunction;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.common.typeinfo.TypeInformation;
import org.apache.flink.api.common.typeinfo.Types;
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.api.functions.source.RichSourceFunction;
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 org.apache.flink.util.Collector;

/**
 * @author lei
 * @version 1.0
 * @date 2021/3/14 14:24
 * @desc flink redis-connector
 */
public class FlinkConnectorRedis {
    public static void main(String[] args) {
        StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        DataStreamSource<VehicleAlarm> alarmSource = env.addSource(new AlarmSource());
        SingleOutputStreamOperator<Tuple2<String, String>> source = alarmSource.map(new MapFunction<VehicleAlarm, VehicleAlarm>() {
            @Override
            public VehicleAlarm map(VehicleAlarm value) throws Exception {
                value.setZone(value.getZone().toUpperCase());
                return value;
            }
        }).flatMap(new FlatMapFunction<VehicleAlarm, Tuple2<String, String>>() {
            @Override
            public void flatMap(VehicleAlarm value, Collector<Tuple2<String, String>> out) throws Exception {
                out.collect(Tuple2.of(value.getLicensePlate() + value.getZone(), JSON.toJSONString(value)));
            }
        });
        // redis 连接器配置
        FlinkJedisPoolConfig conf = new FlinkJedisPoolConfig.Builder()
                .setHost("xxx")
                .setDatabase(0)
                .setPassword("lei123456").build();
        // 输出到redis
        source.addSink(new RedisSink<>(conf, new RedisExampleMapper()));
        try {
            env.execute("redis-sink-1");
        } catch (Exception e) {
            e.printStackTrace();
        }
    }

    /**
     * 输出到redis具体实现 （选择存入类型，以及指定KEY Value）
     */
    public static class RedisExampleMapper implements RedisMapper<Tuple2<String, String>> {
        /**
         * redis 操作方式  RedisCommand.SET 则为普通String
         * @return
         */
        @Override
        public RedisCommandDescription getCommandDescription() {
            return new RedisCommandDescription(RedisCommand.SET);
        }

        /**
         * 从数据中指定Key
         * @param data
         * @return
         */
        @Override
        public String getKeyFromData(Tuple2<String, String> data) {
            return data.f0;
        }

        /**
         * 从数据中指定value
         * @param data
         * @return
         */
        @Override
        public String getValueFromData(Tuple2<String, String> data) {
            return data.f1;
        }
    }


    @Data
    @NoArgsConstructor
    @AllArgsConstructor
    public static class VehicleAlarm {
        private String id;
        private String licensePlate;
        private String plateColor;
        private Long deviceTime;
        private String zone;
    }

    /**
     * 自定义数据源
     */
    public static class AlarmSource extends RichSourceFunction<VehicleAlarm> {

        @Override
        public void run(SourceContext<VehicleAlarm> ctx) throws Exception {
            long id = System.currentTimeMillis() / 10000;
            VehicleAlarm vehicleAlarm = new VehicleAlarm(String.valueOf(id), "川A" + id,
                    "紫", System.currentTimeMillis(), "sc");
            ctx.collect(vehicleAlarm);
            Thread.sleep(10000);
        }

        @Override
        public void cancel() {

        }
    }
}

标签：flink,Flink,redis,Connectors,连接器,import,apache,org,public
来源： https://blog.csdn.net/leilei1366615/article/details/115643322