《高级》Flink异步io链接Redis--Java和Scala版

最近发现好多小伙伴不知道如何异步链接redis

我准备了两个版本 java版本和scala版本

直接上代码，大部分同学看了应该会懂

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先看java版本

import com.alibaba.fastjson.JSON;import org.apache.flink.api.common.serialization.SimpleStringSchema;import org.apache.flink.configuration.Configuration;import org.apache.flink.streaming.api.datastream.AsyncDataStream;import org.apache.flink.streaming.api.datastream.DataStream;import org.apache.flink.streaming.api.environment.StreamExecutionEnvironment;import org.apache.flink.streaming.api.functions.async.ResultFuture;import org.apache.flink.streaming.api.functions.async.RichAsyncFunction;import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer08;import redis.clients.jedis.Jedis;import redis.clients.jedis.JedisPool;import redis.clients.jedis.JedisPoolConfig;import java.util.Collections;import java.util.Properties;import java.util.concurrent.CompletableFuture;import java.util.concurrent.TimeUnit;import java.util.function.Supplier;
public class AsynFlinkRedisJava {
        public static void main(String args[]) throws Exception{
            final StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();        env.enableCheckpointing(500);        Properties props = new Properties();        props.setProperty("bootstrap.servers", "localhost:9092");        props.setProperty("zookeeper.connect", "localhost:2181");        props.setProperty("group.id", "flink-kafka");        FlinkKafkaConsumer08 consumer = new FlinkKafkaConsumer08("flink1", new SimpleStringSchema(), props);        DataStream stream = env.addSource(consumer);        DataStream resultStream = AsyncDataStream.unorderedWait(stream, new AsyncRedis(),1000, TimeUnit.MICROSECONDS, 100);        resultStream.print();        env.execute("kaishi");    }}class AsyncRedis extends RichAsyncFunction {
        private transient JedisPool pool;    @Override    public void open(Configuration parameters) throws Exception {
            super.open(parameters);        pool= new JedisPool(new JedisPoolConfig(), "localhost", 6379);    }    @Override    public void asyncInvoke(String input, final ResultFuture resultFuture) throws Exception {
            CompletableFuture.supplyAsync(new Supplier() {
                @Override            public String get() {
                    try {
                        String imei = JSON.parseObject(input).get("imei").toString();                    Jedis jedis = pool.getResource();                    String result = jedis.hget("DC_IMEI_APPID",imei);                    pool.returnResource(jedis);                    return result;                } catch (Exception e) {
                        System.out.println(e);                    return null;                }            }        }).thenAccept( (String dbResult) -> {
                resultFuture.complete(Collections.singleton(dbResult));        });    }}

再看scala版本：

import java.util.Propertiesimport org.apache.flink.api.common.serialization.SimpleStringSchemaimport org.apache.flink.streaming.api.scala.{AsyncDataStream, DataStream, StreamExecutionEnvironment, _}import org.apache.flink.streaming.connectors.kafka.FlinkKafkaConsumer08import com.alibaba.fastjson.JSONimport redis.clients.jedis.{Jedis, JedisPool, JedisPoolConfig}import java.util.concurrent.TimeUnitimport org.apache.flink.streaming.api.scala.async.{AsyncFunction, ResultFuture}import scala.concurrent.{ExecutionContext, Future}object AsynFlinkRedis {
      def main(args: Array[String]): Unit = {
        val env = StreamExecutionEnvironment.getExecutionEnvironment    val properties = new Properties()    //kafka位置 老版本的 kafka是配置zookeeper地址    properties.setProperty("bootstrap.servers","localhost:9092")    properties.setProperty("zookeeper.connect","localhost:2181")    val topic = "flink1"    properties.setProperty("group.id", "test-flink")    val kafkStream = new FlinkKafkaConsumer08(topic,new SimpleStringSchema(),properties)    val stream = env.addSource(kafkStream)    stream.print()    val resultStream=AsyncDataStream.unorderedWait(stream,new RedisAsyncFunction(), 1000, TimeUnit.MILLISECONDS, 100)    resultStream.print()    env.execute()  }}class RedisAsyncFunction extends  AsyncFunction[String,String]{
       lazy  val pool = new JedisPool(new JedisPoolConfig,"localhost",6379)  override def asyncInvoke(input: String, resultFuture: ResultFuture[String]): Unit = {
        Future {
          //获取kafka日志的imei号      val imei = JSON.parseObject(input).get("imei").toString      //从redis中获取imei对应的userid      println(pool.getNumActive)      val jedis = pool.getResource      val useridJson =jedis.hget("DC_IMEI_APPID",imei)      print(useridJson)      resultFuture.complete(Seq(useridJson))      pool.returnResource(jedis)    }(ExecutionContext.global)}}

kafka练习日志：

{"accStatus":"NULL","addr":"","alertType":"stayAlert","fenceId":"NULL","gpsTime":"2019-01-29 23:45:01","iccid":"NULL","imei":"868620190220000","imsi":"NULL","lat":"46.795862","lng":"134.011538","offlineTime":"NULL","postTime":"2019-01-30 00:00:00","time":"NULL","type":"DEVICE"}

redis测试数据：

hset DC_IMEI_APPID 868620190220000 "{\"allFullId\":\"1,130396,130395,129659\",\"appId\":\"TRACKER\",\"userId\":\"129659\",\"mcType\":\"GT06N\",\"timeZone\":\"UTCA08:00\"}"