Flink 系例 之 Connectors 连接 Redis

通过使用Flink DataStream Connectors 数据流连接器连接到Redis缓存数据库，并提供数据流输入与输出操作；

示例环境

java.version: 1.8.x
flink.version: 1.11.1
redis：3.2

示例数据源 （项目码云下载）

Flink 系例 之 搭建开发环境与数据

示例模块 （pom.xml）

Flink 系例 之 DataStream Connectors 与 示例模块

数据流输入

DataStreamSource.java

package com.flink.examples.redis;

import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
import org.apache.flink.streaming.api.functions.source.RichSourceFunction;
import redis.clients.jedis.Jedis;
import redis.clients.jedis.JedisPool;
import redis.clients.jedis.JedisPoolConfig;
import redis.clients.jedis.Protocol;

/**
 * @Description 从redis中读取数据输出到DataStream数据流中
 */
public class DataStreamSource {
    /**
     * 官方文档：https://bahir.apache.org/docs/flink/current/flink-streaming-redis/
     */

    public static void main(String[] args) throws Exception {
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
        String key = "props";
        //实现RichSourceFunction抽象方法，加载数据源数据到流中
        DataStream<Tuple2<String, String>> dataStream = env.addSource(new RichSourceFunction<Tuple2<String, String>>(){
            private JedisPool jedisPool = null;
            @Override
            public void run(SourceContext<Tuple2<String, String>> ctx) throws Exception {
                jedisPool = new JedisPool(new JedisPoolConfig(), "127.0.0.1", 6379, Protocol.DEFAULT_TIMEOUT);
                Jedis jedis = jedisPool.getResource();
                try{
                    ctx.collect(Tuple2.of(key, jedis.get(key)));
                }catch(Exception e){
                    e.printStackTrace();
                }finally{
                    if (jedis != null){
                        //用完即关，内部会做判断，如果存在数据源与池，则回滚到池中
                        jedis.close();
                    }
                }
            }
            @Override
            public void cancel() {
                try {
                    super.close();
                }catch(Exception e){
                }
                if (jedisPool != null){
                    jedisPool.close();
                    jedisPool = null;
                }
            }
        });
        dataStream.print();
        env.execute("flink redis source");
    }

}

数据流输出

DataStreamSink.java

package com.flink.examples.redis;

import org.apache.commons.lang3.RandomUtils;
import org.apache.flink.api.common.functions.MapFunction;
import org.apache.flink.api.java.tuple.Tuple2;
import org.apache.flink.streaming.api.datastream.DataStream;
import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;
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;

/**
 * @Description 将数据流写入到redis中
 */
public class DataStreamSink {

    /**
     * 官方文档：https://bahir.apache.org/docs/flink/current/flink-streaming-redis/
     */

    public static void main(String[] args) throws Exception {
        final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();

        //1.写入数据到流中
        String [] words = new String[]{"props","student","build","name","execute"};
        DataStream<Tuple2<String, Integer>> sourceStream = env.fromElements(words).map(new MapFunction<String, Tuple2<String, Integer>>() {
            @Override
            public Tuple2<String, Integer> map(String v) throws Exception {
                return Tuple2.of(v, RandomUtils.nextInt(1000, 9999));
            }
        });
        sourceStream.print();

        //2.实例化FlinkJedisPoolConfig 配置redis
        FlinkJedisPoolConfig conf = new FlinkJedisPoolConfig.Builder().setHost("127.0.0.1").setPort(6379).build();

        //3.写入到redis，实例化RedisSink，并通过flink的addSink的方式将flink计算的结果插入到redis
        sourceStream.addSink(new RedisSink<>(conf, new RedisMapper<Tuple2<String, Integer>>(){
            @Override
            public RedisCommandDescription getCommandDescription() {
                return new RedisCommandDescription(RedisCommand.SET, null);
                //通过实例化传参，设置hash值的key
                //return new RedisCommandDescription(RedisCommand.HSET, key);
            }
            @Override
            public String getKeyFromData(Tuple2<String, Integer> tuple2) {
                return tuple2.f0;
            }
            @Override
            public String getValueFromData(Tuple2<String, Integer> tuple2) {
                return tuple2.f1.toString();
            }
        }));
        env.execute("flink redis sink");
    }

}

数据展示

来源：oschina

链接：https://my.oschina.net/u/437309/blog/4946403