我正在尝试从控制台Kafka生产者到Hadoop文件系统(HDFS)建立一个简单的数据管道。我正在使用64位Ubuntu虚拟机,并为Hadoop和Kafka创建了单独的用户,正如我所遵循的指南所建议的那样。使用控制台消费者在Kafka中使用生成的输入并且HDFS似乎已启动并运行。
现在我想使用Flume将输入传输到HDFS。我使用以下配置文件:
tier1.sources = source1
tier1.channels = channel1
tier1.sinks = sink1
tier1.sources.source1.type = org.apache.flume.source.kafka.KafkaSource
tier1.sources.source1.zookeeperConnect = 127.0.0.1:2181
tier1.sources.source1.topic = test
tier1.sources.source1.groupId = flume
tier1.sources.source1.channels = channel1
tier1.sources.source1.interceptors = i1
tier1.sources.source1.interceptors.i1.type = timestamp
tier1.sources.source1.kafka.consumer.timeout.ms = 2000
tier1.channels.channel1.type = memory
tier1.channels.channel1.capacity = 10000
tier1.channels.channel1.transactionCapacity = 1000
tier1.sinks.sink1.type = hdfs
tier1.sinks.sink1.hdfs.path = hdfs://flume/kafka/%{topic}/%y-%m-%d
tier1.sinks.sink1.hdfs.rollInterval = 5
tier1.sinks.sink1.hdfs.rollSize = 0
tier1.sinks.sink1.hdfs.rollCount = 0
tier1.sinks.sink1.hdfs.fileType = DataStream
tier1.sinks.sink1.channel = channel1
现在我用以下命令运行Flume
bin/flume-ng agent --conf ./conf -f conf/flume.conf -Dflume.root.logger=DEBUG,console -n tier1
我一遍又一遍地在控制台输出中得到相同的异常:
2017-10-19 12:17:04,279 (lifecycleSupervisor-1-2) [DEBUG - org.apache.kafka.clients.NetworkClient.handleConnections(NetworkClient.java:467)] Completed connection to node 2147483647
2017-10-19 12:17:04,279 (lifecycleSupervisor-1-2) [DEBUG - org.apache.kafka.common.network.Selector.poll(Selector.java:307)] Connection with Ubuntu-Sandbox/127.0.1.1 disconnected
java.io.EOFException
at org.apache.kafka.common.network.NetworkReceive.readFromReadableChannel(NetworkReceive.java:83)
at org.apache.kafka.common.network.NetworkReceive.readFrom(NetworkReceive.java:71)
at org.apache.kafka.common.network.KafkaChannel.receive(KafkaChannel.java:153)
at org.apache.kafka.common.network.KafkaChannel.read(KafkaChannel.java:134)
at org.apache.kafka.common.network.Selector.poll(Selector.java:286)
at org.apache.kafka.clients.NetworkClient.poll(NetworkClient.java:256)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.clientPoll(ConsumerNetworkClient.java:320)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:213)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:193)
at org.apache.kafka.clients.consumer.internals.ConsumerNetworkClient.poll(ConsumerNetworkClient.java:163)
at org.apache.kafka.clients.consumer.internals.AbstractCoordinator.ensureActiveGroup(AbstractCoordinator.java:222)
at org.apache.kafka.clients.consumer.internals.ConsumerCoordinator.ensurePartitionAssignment(ConsumerCoordinator.java:311)
at org.apache.kafka.clients.consumer.KafkaConsumer.pollOnce(KafkaConsumer.java:890)
at org.apache.kafka.clients.consumer.KafkaConsumer.poll(KafkaConsumer.java:853)
at org.apache.flume.source.kafka.KafkaSource.doStart(KafkaSource.java:529)
at org.apache.flume.source.BasicSourceSemantics.start(BasicSourceSemantics.java:83)
at org.apache.flume.source.PollableSourceRunner.start(PollableSourceRunner.java:71)
at org.apache.flume.lifecycle.LifecycleSupervisor$MonitorRunnable.run(LifecycleSupervisor.java:249)
at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:511)
at java.util.concurrent.FutureTask.runAndReset(FutureTask.java:308)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$301(ScheduledThreadPoolExecutor.java:180)
at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:294)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1149)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:624)
at java.lang.Thread.run(Thread.java:748)
阻止Flume的唯一方法就是杀死Java进程。
我认为它可能与Hadoop和Kafka的单独用户有关,但即使在使用Kafka用户运行所有内容时,我也会得到相同的结果。我也没有在网上找到任何有关EOFException方法的内容,考虑到我刚刚遵循“入门”指南并使用了非常标准的配置,这很奇怪。
也许它与前一行(“Ubuntu-Sandbox / 127.0.1.1已断开连接”)有关,因此我的VM配置?
非常感谢任何帮助!
答案 0 :(得分:0)
您是否考虑过使用Kafka Connect(Apache Kafka的一部分)和HDFS connector?人们普遍认为这已经取代了Flume。它易于使用,具有与Flume类似的基于文件的配置。