Hadoop 无法使用Kafka命令行向Kafka主题/制作人发送json推文事件

我已经创建了一个python脚本

raw\u tweets\u stream.py

，使用twitter api来流式传输twitter数据。twitter上的json数据通过下面的脚本传递给kafka producer

---

---

raw_json_tweets

是为这些tweets创建的卡夫卡主题。python脚本

raw_tweets_stream.py

运行正常，但在将其发送给卡夫卡制作人时抛出错误。我正在使用HortonWorksHDP2.3.1沙盒，我已经确保zookeeper和kafka已经启动

---

/usr/hdp/current/kafka broker/bin/kafka-topics.sh--zookeer localhost:2181--description--topic raw\u json\u tweets

Topic:raw_json_tweets      PartitionCount:1        ReplicationFactor:1     Configs:
            Topic: raw_json_tweets     Partition: 0    Leader: 0       Replicas: 0     Isr: 0

错误：

[2016-08-25 22:36:26,212] ERROR Failed to send requests for topics raw_json_tweets with correlation ids in [57,64] (kafka.producer.async.DefaultEventHandler)
[2016-08-25 22:36:26,213] ERROR Error in handling batch of 131 events (kafka.producer.async.ProducerSendThread)
kafka.common.FailedToSendMessageException: Failed to send messages after 3 tries.
        at kafka.producer.async.DefaultEventHandler.handle(DefaultEventHandler.scala:91)
        at kafka.producer.async.ProducerSendThread.tryToHandle(ProducerSendThread.scala:105)
        at kafka.producer.async.ProducerSendThread$$anonfun$processEvents$3.apply(ProducerSendThread.scala:88)
        at kafka.producer.async.ProducerSendThread$$anonfun$processEvents$3.apply(ProducerSendThread.scala:68)
        at scala.collection.immutable.Stream.foreach(Stream.scala:547)
        at kafka.producer.async.ProducerSendThread.processEvents(ProducerSendThread.scala:67)
        at kafka.producer.async.ProducerSendThread.run(ProducerSendThread.scala:45)
[2016-08-25 22:36:27,217] WARN Fetching topic metadata with correlation id 65 for topics [Set(json_tweets1)] from broker [BrokerEndPoint(0,localhost,2181)] failed (kafka.client.ClientUtils$)
java.io.EOFException: Received -1 when reading from channel, socket has likely been closed.
        at kafka.utils.CoreUtils$.read(CoreUtils.scala:193)
        at kafka.network.BoundedByteBufferReceive.readFrom(BoundedByteBufferReceive.scala:54)
        at kafka.network.Receive$class.readCompletely(Transmission.scala:56)
        at kafka.network.BoundedByteBufferReceive.readCompletely(BoundedByteBufferReceive.scala:29)
        at kafka.network.BlockingChannel.receive(BlockingChannel.scala:131)
        at kafka.producer.SyncProducer.liftedTree1$1(SyncProducer.scala:77)
        at kafka.producer.SyncProducer.kafka$producer$SyncProducer$$doSend(SyncProducer.scala:74)
        at kafka.producer.SyncProducer.send(SyncProducer.scala:115)
        at kafka.client.ClientUtils$.fetchTopicMetadata(ClientUtils.scala:59)
        at kafka.producer.BrokerPartitionInfo.updateInfo(BrokerPartitionInfo.scala:82)
        at kafka.producer.BrokerPartitionInfo.getBrokerPartitionInfo(BrokerPartitionInfo.scala:49)
        at kafka.producer.async.DefaultEventHandler.kafka$producer$async$DefaultEventHandler$$getPartitionListForTopic(DefaultEventHandler.scala:188)
        at kafka.producer.async.DefaultEventHandler$$anonfun$partitionAndCollate$1.apply(DefaultEventHandler.scala:152)
        at kafka.producer.async.DefaultEventHandler$$anonfun$partitionAndCollate$1.apply(DefaultEventHandler.scala:151)
        at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
        at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
        at kafka.producer.async.DefaultEventHandler.partitionAndCollate(DefaultEventHandler.scala:151)
        at kafka.producer.async.DefaultEventHandler.dispatchSerializedData(DefaultEventHandler.scala:96)
        at kafka.producer.async.DefaultEventHandler.handle(DefaultEventHandler.scala:73)
        at kafka.producer.async.ProducerSendThread.tryToHandle(ProducerSendThread.scala:105)
        at kafka.producer.async.ProducerSendThread$$anonfun$processEvents$3.apply(ProducerSendThread.scala:88)
        at kafka.producer.async.ProducerSendThread$$anonfun$processEvents$3.apply(ProducerSendThread.scala:68)
        at scala.collection.immutable.Stream.foreach(Stream.scala:547)
        at kafka.producer.async.ProducerSendThread.processEvents(ProducerSendThread.scala:67)
        at kafka.producer.async.ProducerSendThread.run(ProducerSendThread.scala:45)

---

更新：解决方案

---

转到Ambari Services，并将Kafka日志目录更改为

/tmp/Kafka logs

修改原始脚本以包含正确的端口和主机名

python raw_tweets_stream.py

Topic:raw_json_tweets      PartitionCount:1        ReplicationFactor:1     Configs:
            Topic: raw_json_tweets     Partition: 0    Leader: 0       Replicas: 0     Isr: 0

已验证是否使用控制台使用者将事件发送到kafka主题

/usr/hdp/2.3.0.0-2557/kafka/bin/kafka-console-consumer.sh-zookeer sandbox.hortonworks.com:2181-topic raw_json_tweets-从头开始

---

看起来你把

--代理列表

指向zookeeper（

2181

），而你需要指向卡夫卡代理，其默认端口是Ambari上的

9092

或

6667

。

谢谢你指出@Binary Nerd。我用正确的端口9092更新了kafka代理，但仍然抛出错误。以下是错误的一部分-->[2016-08-26 13:24:12718]错误未能按主题、分区整理消息，原因是：从代理[ArrayBuffer（BrokerEndPoint（0，localhost，9092））]获取主题[Set（raw_json_tweets）]的主题元数据失败（kafka.producer.async.DefaultEventHandler）。。java.nio.channels.closedchannelexception根据Hortonworks文档，如果您使用的是Ambari，默认端口是

6667

，或许可以尝试一下-您是对的。hortonworks的正确端口为6667（也验证了这一点，并将其发送至ambari Services）。修改脚本以包含正确的端口

6667

和完整的主机名

sandbox.hortonworks.com

。。工作得很有魅力

python raw_tweets_stream.py/usr/hdp/current/kafka broker/bin/kafka-console-producer.sh--代理列表sandbox.hortonworks.com:6667--主题raw_json_tweets