FlinkConnectors怎么连接Redis
这篇文章主要介绍“Flink Connectors怎么连接redis”，在日常操作中，相信很多人在Flink Connectors怎么连接Redis问题上存在疑惑，小编查阅了各式资料，整理出简单好用的操作方法，希望对大家解答”Flink Connectors怎么连接Redis”的疑惑有所帮助！接下来，请跟着小编一起来学习吧！
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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.xflink.version: 1.11.1redis：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> dataStream = env.addSource(new RichSourceFunction>(){
private JedisPool jedisPool = null;
@Override
public void run(SourceContext> 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> sourceStream = env.fromElements(words).map(new MapFunction>() {
@Override
public Tuple2 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>(){
@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 tuple2) {
return tuple2.f0;
}
@Override
public String getValueFromData(Tuple2 tuple2) {
return tuple2.f1.toString();
}
}));
env.execute("flink redis sink");
}
} 数据展示
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