flink入门之scala实现异步IO访问redis及踩坑记录(2)

我们在flink入门之scala实现异步IO访问redis及踩坑记录(1)中采用jedis来模拟异步读取redis，那么在本篇，我们要采用redis的高级客户端lettuce，这个客户端很强大，支持异步操作，如果想具体了解的请移步：
Redis高级客户端Lettuce详解

首先我们导入依赖：

		<dependency>
            <groupId>io.lettuce</groupId>
            <artifactId>lettuce-core</artifactId>
            <version>5.0.5.RELEASE</version>
		</dependency>

然后我们也是用AsyncDataStream的orderedWait方法（其中kafkaDs是从kafka读进来的数据流）：

AsyncDataStream.orderedWait(kafkaDs, new AsyncRedisRead, 30L, TimeUnit.SECONDS, 1000)

自定义异步读取函数：

class AsyncRedisRead extends RichAsyncFunction[Obj1, Obj1] {
     

    private var redisClient: RedisClient = _
    private var connection: StatefulRedisConnection[String, String] = _
    private var async: RedisAsyncCommands[String, String] = _

    override def open(parameters: Configuration): Unit = {
     
      super.open(parameters)
      val redisUri = "redis://10.xx.xx.xxx"
      redisClient = RedisClient.create(redisUri)
      connection = redisClient.connect()
      async = connection.async()
    }

    override def asyncInvoke(input: Obj1, resultFuture: ResultFuture[Obj1]): Unit = {
     
      async.keys(s"flink*").thenAccept(new Consumer[java.util.List[String]] {
     
        override def accept(t: List[String]): Unit = {
     
          if (t.isEmpty) {
     
            resultFuture.complete(Iterable[Obj1](input))
          }
          else {
     
            var seq = Seq[Obj1]()
            //遍历列表
            for (i <- 0 until t.size()) {
     
                val member= t.get(i)
                val infoArray = member.split("_")
                val ruleId = infoArray(3)
                val userId = infoArray(4)
                val suspectId = infoArray(5)
                val alarmStatus = infoArray(6)
                seq = seq :+ Obj1(input.uuid, input.wifiList, ruleId, userId, suspectId)               
            }
            resultFuture.complete(seq)
          }
        }
      })
    }

    override def close(): Unit = {
     
      super.close()
      if (redisClient != null) redisClient.shutdown()
      if (connection != null) connection.close()
    }
  }

看上去很简单，但是这里必须要注意一点：
ResultFuture在第一次调用ResultFuture.complete时就执行完成了。随后的所有complete调用都将被忽略！！！

所以当我们想要把一个集合循环遍历返回数据时，切记不要这样写：

		for (i <- 0 until t.size()) {
     
                val member= t.get(i)
                val infoArray = member.split("_")
                val ruleId = infoArray(3)
                val userId = infoArray(4)
                val suspectId = infoArray(5)
                val alarmStatus = infoArray(6)
                resultFuture.complete(Iterable[Obj1](Obj1(input.uuid, input.wifiList, ruleId, userId, suspectId)))
            }

这样写的话，在遍历第一条数据执行完complete后，后面的数据就不会再通过complete返回了。

至此Flink异步维表读取redis的相关操作就是这样，如有不妥的地方，欢迎留言指正