我想使用Kafka将apache服务器日志加载到hdfs 创建主题：
./kafka-topics.sh --create --zookeeper 10.25.3.207:2181 --replication-factor 1 --partitions 1 --topic lognew
拖尾apache访问日志目录：
tail -f /var/log/httpd/access_log |./kafka-console-producer.sh --broker-list 10.25.3.207:6667 --topic lognew
在另一个终端（kafka bin）启动消费者：
./kafka-console-consumer.sh --zookeeper 10.25.3.207:2181 --topic lognew --from-beginning
camus.properties文件配置为：
# Needed Camus properties, more cleanup to come
# final top-level data output directory, sub-directory will be dynamically created for each topic pulled
etl.destination.path=/user/root/topics
# HDFS location where you want to keep execution files, i.e. offsets, error logs, and count files
etl.execution.base.path=/user/root/exec
# where completed Camus job output directories are kept, usually a sub-dir in the base.path
etl.execution.history.path=/user/root/camus/exec/history
# Kafka-0.8 handles all zookeeper calls
#zookeeper.hosts=
#zookeeper.broker.topics=/brokers/topics
#zookeeper.broker.nodes=/brokers/ids
# Concrete implementation of the Encoder class to use (used by Kafka Audit, and thus optional for now) `camus.message.encoder.class=com.linkedin.camus.etl.kafka.coders.DummyKafkaMessageEncoder`
# Concrete implementation of the Decoder class to use
#camus.message.decoder.class=com.linkedin.camus.etl.kafka.coders.LatestSchemaKafkaAvroMessageDecoder
# Used by avro-based Decoders to use as their Schema Registry
#kafka.message.coder.schema.registry.class=com.linkedin.camus.example.schemaregistry.DummySchemaRegistry
# Used by the committer to arrange .avro files into a partitioned scheme. This will be the default partitioner for all
# topic that do not have a partitioner specified
#etl.partitioner.class=com.linkedin.camus.etl.kafka.coders.DefaultPartitioner
# Partitioners can also be set on a per-topic basis
#etl.partitioner.class.<topic-name>=com.your.custom.CustomPartitioner
# all files in this dir will be added to the distributed cache and placed on the classpath for hadoop tasks
# hdfs.default.classpath.dir=
# max hadoop tasks to use, each task can pull multiple topic partitions
mapred.map.tasks=30
# max historical time that will be pulled from each partition based on event timestamp
kafka.max.pull.hrs=1
# events with a timestamp older than this will be discarded.
kafka.max.historical.days=3
# Max minutes for each mapper to pull messages (-1 means no limit)
kafka.max.pull.minutes.per.task=-1
# if whitelist has values, only whitelisted topic are pulled. nothing on the blacklist is pulled
#kafka.blacklist.topics=
kafka.whitelist.topics=lognew
log4j.configuration=true
# Name of the client as seen by kafka
kafka.client.name=camus
# Fetch Request Parameters
#kafka.fetch.buffer.size=
#kafka.fetch.request.correlationid=
#kafka.fetch.request.max.wait=
#kafka.fetch.request.min.bytes=
# Connection parameters.
kafka.brokers=10.25.3.207:6667
#kafka.timeout.value=
#Stops the mapper from getting inundated with Decoder exceptions for the same topic
#Default value is set to 10
max.decoder.exceptions.to.print=5
#Controls the submitting of counts to Kafka
#Default value set to true
post.tracking.counts.to.kafka=true
monitoring.event.class=class.that.generates.record.to.submit.counts.to.kafka
# everything below this point can be ignored for the time being, will provide more documentation down the road
##########################
etl.run.tracking.post=false
#kafka.monitor.tier=
#etl.counts.path=
kafka.monitor.time.granularity=10
etl.hourly=hourly
etl.daily=daily
etl.ignore.schema.errors=false
# configure output compression for deflate or snappy. Defaults to deflate
etl.output.codec=deflate
etl.deflate.level=6
#etl.output.codec=snappy
etl.default.timezone=America/Los_Angeles
etl.output.file.time.partition.mins=60
etl.keep.count.files=false
etl.execution.history.max.of.quota=.8
mapred.output.compress=true
mapred.map.max.attempts=1
kafka.client.buffer.size=20971520
kafka.client.so.timeout=60000
#zookeeper.session.timeout=
#zookeeper.connection.timeout=
执行以下命令时出错：
hadoop jar camus-example-0.1.0-SNAPSHOT-shaded.jar com.linkedin.camus.etl.kafka.CamusJob -P camus.properties
以下是错误：
[CamusJob] - Fetching metadata from broker 10.25.3.207:6667 with client id camus for 0 topic(s) []
[CamusJob] - failed to create decoder
com.linkedin.camus.coders.MessageDecoderException: com.linkedin.camus.coders.MessageDecoderException: java.lang.NullPointerException
at com.linkedin.camus.etl.kafka.coders.MessageDecoderFactory.createMessageDecoder(MessageDecoderFactory.java:28)
at com.linkedin.camus.etl.kafka.mapred.EtlInputFormat.createMessageDecoder(EtlInputFormat.java:390)
at com.linkedin.camus.etl.kafka.mapred.EtlInputFormat.getSplits(EtlInputFormat.java:264)
at org.apache.hadoop.mapreduce.JobSubmitter.writeNewSplits(JobSubmitter.java:301)
at org.apache.hadoop.mapreduce.JobSubmitter.writeSplits(JobSubmitter.java:318)
at org.apache.hadoop.mapreduce.JobSubmitter.submitJobInternal(JobSubmitter.java:196)
at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1290)
at org.apache.hadoop.mapreduce.Job$10.run(Job.java:1287)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:415)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1657)
at org.apache.hadoop.mapreduce.Job.submit(Job.java:1287)
at com.linkedin.camus.etl.kafka.CamusJob.run(CamusJob.java:280)
at com.linkedin.camus.etl.kafka.CamusJob.run(CamusJob.java:608)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:70)
at org.apache.hadoop.util.ToolRunner.run(ToolRunner.java:84)
at com.linkedin.camus.etl.kafka.CamusJob.main(CamusJob.java:572)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
at java.lang.reflect.Method.invoke(Method.java:606)
at org.apache.hadoop.util.RunJar.run(RunJar.java:221)
at org.apache.hadoop.util.RunJar.main(RunJar.java:136)
Caused by: com.linkedin.camus.coders.MessageDecoderException: java.lang.NullPointerException
at com.linkedin.camus.etl.kafka.coders.KafkaAvroMessageDecoder.init(KafkaAvroMessageDecoder.java:40)
at com.linkedin.camus.etl.kafka.coders.MessageDecoderFactory.createMessageDecoder(MessageDecoderFactory.java:24)
... 22 more
Caused by: java.lang.NullPointerException
at java.lang.Class.forName0(Native Method)
at java.lang.Class.forName(Class.java:195)
at com.linkedin.camus.etl.kafka.coders.KafkaAvroMessageDecoder.init(KafkaAvroMessageDecoder.java:31)
... 23 more
[CamusJob] - Discarding topic (Decoder generation failed) : avrotopic
[CamusJob] - failed to create decoder
请建议可以采取哪些措施来解决此问题。 提前致谢
Deepthy
答案 0 :(得分：0)
我从来没有使用加缪。但我相信这是一个与Kafka相关的错误，它与你如何编码/解码消息有关。我相信堆栈跟踪中的重要行是
Caused by: com.linkedin.camus.coders.MessageDecoderException: java.lang.NullPointerException
at com.linkedin.camus.etl.kafka.coders.KafkaAvroMessageDecoder.init(KafkaAvroMessageDecoder.java:40)
at com.linkedin.camus.etl.kafka.coders.MessageDecoderFactory.createMessageDecoder(MessageDecoderFactory.java:24)
你是如何告诉Kafka使用你的Avro编码的？您已在配置中注释掉以下行
#kafka.message.coder.schema.registry.class=com.linkedin.camus.example.schemaregistry.DummySchemaRegistry
那么你在代码中的其他地方设置了吗？如果您不这样做，我建议取消注释该配置值，并将其设置为您尝试解码/编码的任何avro类。
使用正确的类路径可能需要一些调试，但我相信这是一个容易解决的问题。
修改 在回复你的评论时，我有几个自己的评论。