我目前正致力于编写一个Samza脚本,该脚本将仅从Kafka主题中获取数据并将数据输出到另一个Kafka主题。我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$.main(JobRunner.scala:48)
at org.apache.samza.job.JobRunner.main(JobRunner.scala)
Caused by: org.apache.kafka.common.errors.TimeoutException: Failed to update metadata after 193 ms
我不完全确定如何配置或让脚本编写所需的Kafka元数据。下面是我的StreamTask代码和属性文件。在属性文件中,我添加了元数据部分,以查看这是否有助于此后的过程,但无济于事。这是正确的方向,还是我完全错过了什么?
import org.apache.samza.task.StreamTask;
import org.apache.samza.task.MessageCollector;
import org.apache.samza.task.TaskCoordinator;
import org.apache.samza.system.SystemStream;
import org.apache.samza.system.IncomingMessageEnvelope;
import org.apache.samza.system.OutgoingMessageEnvelope;
/*
* Take all messages received and send them to
* a Kafka topic called "words"
*/
public class TestStreamTask implements StreamTask{
private static final SystemStream OUTPUT_STREAM = new SystemStream("kafka" , "words"); // create new system stream for kafka topic "words"
@Override
public void process(IncomingMessageEnvelope envelope, MessageCollector collector, TaskCoordinator coordinator){
String message = (String) envelope.getMessage(); // pull message from stream
for(String word : message.split(" "))
collector.send(new OutgoingMessageEnvelope(OUTPUT_STREAM, word, 1)); // output messsage to new system stream for kafka topic "words"
}
}
# Job
job.factory.class=org.apache.samza.job.yarn.YarnJobFactory
job.name=test-words
# YARN
yarn.package.path=file://${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
答案 0 :(得分:0)
这个问题是关于Kafka 0.8的,如果我没记错的话,它应该不受支持。
这个事实,再加上人们有时但不是一直都遇到这个问题的背景(近年来似乎没有人对此感到挣扎),这使我非常有信心升级到最新版本Kafka将解决问题。