我目前正在编写一个samza脚本,它只从一个kafka主题中获取数据,并将数据输出到另一个kafka主题。我已经写了一个非常基本的streamtask,但是在执行时我遇到了一个错误。
错误如下:
Exception in thread "main" org.apache.samza.SamzaException: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 193 ms.
at org.apache.samza.coordinator.stream.CoordinatorStreamSystemProducer.send(CoordinatorStreamSystemProducer.java:112)
at org.apache.samza.coordinator.stream.CoordinatorStreamSystemProducer.writeConfig(CoordinatorStreamSystemProducer.java:129)
at org.apache.samza.job.JobRunner.run(JobRunner.scala:79)
at org.apache.samza.job.JobRunner$.main(JobRunner.scala:48)
at org.apache.samza.job.JobRunner.main(JobRunner.scala)
Caused by: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 193 ms
我不完全确定如何配置或让脚本编写所需的kafka元数据。下面是我的streamtask和属性文件的代码。在properties文件中,我添加了metadata部分,以查看这是否有助于以后的处理,但没有效果。这是正确的方向还是我完全遗漏了什么?
import org.apache.samza.task.StreamTask;
import org.apache.samza.task.MessageCollector;
import org.apache.samza.task.TaskCoordinator;
import org.apache.samza.system.SystemStream;
import org.apache.samza.system.IncomingMessageEnvelope;
import org.apache.samza.system.OutgoingMessageEnvelope;
/*
* Take all messages received and send them to
* a Kafka topic called "words"
* /
public class TestStreamTask implements StreamTask{
private static final SystemStream OUTPUT_STREAM = new SystemStream("kafka" , "words"); // create new system stream for kafka topic "words"
@Override
public void process(IncomingMessageEnvelope envelope, MessageCollector collector, TaskCoordinator coordinator){
String message = (String) envelope.getMessage(); // pull message from stream
for(String word : message.split(" "))
collector.send(new OutgoingMessageEnvelope(OUTPUT_STREAM, word, 1)); // output messsage to new system stream for kafka topic "words"
}
}
# Job
job.factory.class=org.apache.samza.job.yarn.YarnJobFactory
job.name=test-words
# YARN
yarn.package.path=file://${basedir}/target/${project.artifactId}-${pom.version}-dist.tar.gz
# Task
task.class=samza.examples.wikipedia.task.TestStreamTask
task.inputs=kafka.test
task.checkpoint.factory=org.apache.samza.checkpoint.kafka.KafkaCheckpointManagerFactory
task.checkpoint.system=kafka
task.checkpoint.replication.factor=1
# Metrics
metrics.reporters=snapshot,jmx
metrics.reporter.snapshot.class=org.apache.samza.metrics.reporter.MetricsSnapshotReporterFactory
metrics.reporter.snapshot.stream=kafka.metrics
metrics.reporter.jmx.class=org.apache.samza.metrics.reporter.JmxReporterFactory
# Serializers
serializers.registry.string.class=org.apache.samza.serializers.StringSerdeFactory
serializers.registry.metrics.class=org.apache.samza.serializers.MetricsSnapshotSerdeFactory
# Systems
systems.kafka.samza.factory=org.apache.samza.system.kafka.KafkaSystemFactory
systems.kafka.samza.msg.serde=string
systems.kafka.consumer.zookeeper.connect=localhost:2181/
systems.kafka.consumer.auto.offset.reset=largest
systems.kafka.producer.bootstrap.servers=localhost:9092
# Metadata
systems.kafka.metadata.bootstrap.servers=localhost:9092
1条答案
按热度按时间bvjxkvbb1#
这个问题是关于Kafka0.8的,如果我没有弄错的话,它应该是不受支持的。
这一事实,再加上人们有时会遇到这个问题,但不是一直遇到这个问题(近年来似乎没有人在与这个问题作斗争),让我非常有信心升级到Kafka的最新版本将解决这个问题。