Flink 系例 之 Connectors 连接 Redis
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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.x
flink.version: 1.11.1
redis:3.2
示例数据源 (项目码云下载)
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
*/publicclass DataStreamSource
/**
* 官方文档:https://bahir.apache.org/docs/flink/current/flink-streaming-redis/
*/publicstaticvoid 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;
@Overridepublicvoid 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();
@Overridepublicvoid 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
*/publicclass DataStreamSink
/**
* 官方文档:https://bahir.apache.org/docs/flink/current/flink-streaming-redis/
*/publicstaticvoid main(String[] args) throws Exception
final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
//1.写入数据到流中String [] words = newString[]"props","student","build","name","execute";
DataStream<Tuple2<String, Integer>> sourceStream = env.fromElements(words).map(new MapFunction<String, Tuple2<String, Integer>>()
@Overridepublic 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>>()
@Overridepublic RedisCommandDescription getCommandDescription()
returnnew RedisCommandDescription(RedisCommand.SET, null);
//通过实例化传参,设置hash值的key//return new RedisCommandDescription(RedisCommand.HSET, key);
@OverridepublicString getKeyFromData(Tuple2<String, Integer> tuple2)
return tuple2.f0;
@OverridepublicString getValueFromData(Tuple2<String, Integer> tuple2)
return tuple2.f1.toString();
));
env.execute("flink redis sink");
数据展示
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