Flink1.10入门：自定义Redis的Sink函数

一、概述

    这篇文章需要完成的是将实时数据写到Redis，我这里自定义了Ridis对应的Sink函数，为了方便直接从socket端接收数据，operator处理后，直接写入redis中，由于比较简单，详细内容直接看实例代码即可。

软件版本：

    flink1.10

    redis5.0.5

二、代码实战

1.添加redis对应pom依赖

 <dependency>    <groupId>org.apache.bahir</groupId>    <artifactId>flink-connector-redis_2.11</artifactId>    <version>1.0</version></dependency>

2.主函数代码：

package com.hadoop.ljs.flink110.redis;import org.apache.flink.api.common.functions.FilterFunction;import org.apache.flink.api.common.functions.MapFunction;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;import scala.Tuple2;/** * @author: Created By lujisen * @company ChinaUnicom Software JiNan * @date: 2020-05-02 10:30 * @version: v1.0 * @description: com.hadoop.ljs.flink110.redis */public class RedisSinkMain {    public static void main(String[] args) throws Exception {        StreamExecutionEnvironment senv =StreamExecutionEnvironment.getExecutionEnvironment();
        DataStream<String> source = senv.socketTextStream("localhost", 9000);        DataStream<String> filter = source.filter(new FilterFunction<String>() {            @Override            public boolean filter(String value) throws Exception {                if (null == value || value.split(",").length != 2) {                    return false;                }                return true;            }        });        DataStream<Tuple2<String, String>> keyValue = filter.map(new MapFunction<String, Tuple2<String, String>>() {            @Override            public Tuple2<String, String> map(String value) throws Exception {
                String[] split = value.split(",");
                return new Tuple2<>(split[0], split[1]);            }        });        //创建redis的配置 单机redis用FlinkJedisPoolConfig,集群redis需要用FlinkJedisClusterConfig        FlinkJedisPoolConfig redisConf = new FlinkJedisPoolConfig.Builder().setHost("worker2.hadoop.ljs").setPort(6379).setPassword("123456a?").build();
        keyValue.addSink(new RedisSink<Tuple2<String, String>>(redisConf, new RedisMapper<Tuple2<String, String>>() {            @Override            public RedisCommandDescription getCommandDescription() {                return new RedisCommandDescription(RedisCommand.HSET,"table1");            }            @Override            public String getKeyFromData(Tuple2<String, String> data) {                return data._1;            }            @Override            public String getValueFromData(Tuple2<String, String> data) {                return data._2;            }        }));        /*启动执行*/        senv.execute();    }}

3.函数测试

1).window端scoket发送数据

2.redis结果验证