首先，声明，kafka集群是搭建在hadoop1、hadoop2和hadoop3机器上。
kafka_2.10-0.8.1.1.tgz的1或3节点集群的下载、安装和配置（图文详细教程）绝对干货
如下分别是各自的配置信息。（网上说，还需要配置zookeeper.properties，其实不需要，因为，zookeeper集群那边已经配置好了。）
[hadoop@hadoop1 config]$ pwd /home/hadoop/kafka/config [hadoop@hadoop1 config]$ ll total 32 -rw-r--r-- 1 hadoop hadoop 1199 Sep 3 2015 consumer.properties -rw-r--r-- 1 hadoop hadoop 3846 Sep 3 2015 log4j.properties -rw-r--r-- 1 hadoop hadoop 2228 Sep 3 2015 producer.properties -rw-r--r-- 1 hadoop hadoop 5712 May 1 10:00 server.properties -rw-r--r-- 1 hadoop hadoop 3325 Sep 3 2015 test-log4j.properties -rw-r--r-- 1 hadoop hadoop 993 Sep 3 2015 tools-log4j.properties -rw-r--r-- 1 hadoop hadoop 1023 Sep 3 2015 zookeeper.properties [hadoop@hadoop1 config]$ vim server.properties
# Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # see kafka.server.KafkaConfig for additional details and defaults ############################# Server Basics ############################# # The id of the broker. This must be set to a unique integer for each broker. broker.id=1 ############################# Socket Server Settings ############################# # The port the socket server listens on port=9092 # Hostname the broker will bind to. If not set, the server will bind to all interfaces host.name=192.168.80.121 # Hostname the broker will advertise to producers and consumers. If not set, it uses the # value for "host.name" if configured. Otherwise, it will use the value returned from # java.net.InetAddress.getCanonicalHostName(). #advertised.host.name=<hostname routable by clients> # The port to publish to ZooKeeper for clients to use. If this is not set, # it will publish the same port that the broker binds to. #advertised.port=<port accessible by clients> # The number of threads handling network requests num.network.threads=3 # The number of threads doing disk I/O num.io.threads=8 # The send buffer (SO_SNDBUF) used by the socket server socket.send.buffer.bytes=102400 # The receive buffer (SO_RCVBUF) used by the socket server socket.receive.buffer.bytes=102400 # The maximum size of a request that the socket server will accept (protection against OOM) socket.request.max.bytes=104857600 ############################# Log Basics ############################# # A comma seperated list of directories under which to store log files log.dirs=/home/kafka-logs # The default number of log partitions per topic. More partitions allow greater # parallelism for consumption, but this will also result in more files across # the brokers. num.partitions=5 # The number of threads per data directory to be used for log recovery at startup and flushing at shutdown. # This value is recommended to be increased for installations with data dirs located in RAID array. num.recovery.threads.per.data.dir=1 ############################# Log Flush Policy ############################# # Messages are immediately written to the filesystem but by default we only fsync() to sync # the OS cache lazily. The following configurations control the flush of data to disk. # There are a few important trade-offs here: # 1. Durability: Unflushed data may be lost if you are not using replication. # 2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush. # 3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to exceessive seeks. # The settings below allow one to configure the flush policy to flush data after a period of time or # every N messages (or both). This can be done globally and overridden on a per-topic basis. # The number of messages to accept before forcing a flush of data to disk #log.flush.interval.messages=10000 # The maximum amount of time a message can sit in a log before we force a flush #log.flush.interval.ms=1000 ############################# Log Retention Policy ############################# # The following configurations control the disposal of log segments. The policy can # be set to delete segments after a period of time, or after a given size has accumulated. # A segment will be deleted whenever *either* of these criteria are met. Deletion always happens # from the end of the log. # The minimum age of a log file to be eligible for deletion log.retention.hours=168 # A size-based retention policy for logs. Segments are pruned from the log as long as the remaining # segments don't drop below log.retention.bytes. #log.retention.bytes=1073741824 # The maximum size of a log segment file. When this size is reached a new log segment will be created. log.segment.bytes=1073741824 # The interval at which log segments are checked to see if they can be deleted according # to the retention policies log.retention.check.interval.ms=300000 # By default the log cleaner is disabled and the log retention policy will default to just delete segments after their retention expires. # If log.cleaner.enable=true is set the cleaner will be enabled and individual logs can then be marked for log compaction. log.cleaner.enable=false export HBASE_MANAGES_ZK=false offsets.storage=kafka dual.commit.enabled=true delete.topic.enable=true ############################# Zookeeper ############################# # Zookeeper connection string (see zookeeper docs for details). # This is a comma separated host:port pairs, each corresponding to a zk # server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002". # You can also append an optional chroot string to the urls to specify the # root directory for all kafka znodes. zookeeper.connect=192.168.80.121:2181,192.168.80.122:2181,192.168.80.123:2181 # Timeout in ms for connecting to zookeeper zookeeper.connection.timeout.ms=6000
# Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # see kafka.server.KafkaConfig for additional details and defaults ############################# Server Basics ############################# # The id of the broker. This must be set to a unique integer for each broker. broker.id=2 ############################# Socket Server Settings ############################# # The port the socket server listens on port=9092 # Hostname the broker will bind to. If not set, the server will bind to all interfaces host.name=192.168.80.122 # Hostname the broker will advertise to producers and consumers. If not set, it uses the # value for "host.name" if configured. Otherwise, it will use the value returned from # java.net.InetAddress.getCanonicalHostName(). #advertised.host.name=<hostname routable by clients> # The port to publish to ZooKeeper for clients to use. If this is not set, # it will publish the same port that the broker binds to. #advertised.port=<port accessible by clients> # The number of threads handling network requests num.network.threads=3 # The number of threads doing disk I/O num.io.threads=8 # The send buffer (SO_SNDBUF) used by the socket server socket.send.buffer.bytes=102400 # The receive buffer (SO_RCVBUF) used by the socket server socket.receive.buffer.bytes=102400 # The maximum size of a request that the socket server will accept (protection against OOM) socket.request.max.bytes=104857600 ############################# Log Basics ############################# # A comma seperated list of directories under which to store log files log.dirs=/home/kafka-logs # The default number of log partitions per topic. More partitions allow greater # parallelism for consumption, but this will also result in more files across # the brokers. num.partitions=5 # The number of threads per data directory to be used for log recovery at startup and flushing at shutdown. # This value is recommended to be increased for installations with data dirs located in RAID array. num.recovery.threads.per.data.dir=1 ############################# Log Flush Policy ############################# # Messages are immediately written to the filesystem but by default we only fsync() to sync # the OS cache lazily. The following configurations control the flush of data to disk. # There are a few important trade-offs here: # 1. Durability: Unflushed data may be lost if you are not using replication. # 2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush. # 3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to exceessive seeks. # The settings below allow one to configure the flush policy to flush data after a period of time or # every N messages (or both). This can be done globally and overridden on a per-topic basis. # The number of messages to accept before forcing a flush of data to disk #log.flush.interval.messages=10000 # The maximum amount of time a message can sit in a log before we force a flush #log.flush.interval.ms=1000 ############################# Log Retention Policy ############################# # The following configurations control the disposal of log segments. The policy can # be set to delete segments after a period of time, or after a given size has accumulated. # A segment will be deleted whenever *either* of these criteria are met. Deletion always happens # from the end of the log. # The minimum age of a log file to be eligible for deletion log.retention.hours=168 # A size-based retention policy for logs. Segments are pruned from the log as long as the remaining # segments don't drop below log.retention.bytes. #log.retention.bytes=1073741824 # The maximum size of a log segment file. When this size is reached a new log segment will be created. log.segment.bytes=1073741824 # The interval at which log segments are checked to see if they can be deleted according # to the retention policies log.retention.check.interval.ms=300000 # By default the log cleaner is disabled and the log retention policy will default to just delete segments after their retention expires. # If log.cleaner.enable=true is set the cleaner will be enabled and individual logs can then be marked for log compaction. log.cleaner.enable=false export HBASE_MANAGES_ZK=false offsets.storage=kafka dual.commit.enabled=true delete.topic.enable=true ############################# Zookeeper ############################# # Zookeeper connection string (see zookeeper docs for details). # This is a comma separated host:port pairs, each corresponding to a zk # server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002". # You can also append an optional chroot string to the urls to specify the # root directory for all kafka znodes. zookeeper.connect=192.168.80.121:2181,192.168.80.122:2181,192.168.80.123:2181 # Timeout in ms for connecting to zookeeper zookeeper.connection.timeout.ms=6000
# Licensed to the Apache Software Foundation (ASF) under one or more # contributor license agreements. See the NOTICE file distributed with # this work for additional information regarding copyright ownership. # The ASF licenses this file to You under the Apache License, Version 2.0 # (the "License"); you may not use this file except in compliance with # the License. You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. # see kafka.server.KafkaConfig for additional details and defaults ############################# Server Basics ############################# # The id of the broker. This must be set to a unique integer for each broker. broker.id=3 ############################# Socket Server Settings ############################# # The port the socket server listens on port=9092 # Hostname the broker will bind to. If not set, the server will bind to all interfaces host.name=192.168.80.123 # Hostname the broker will advertise to producers and consumers. If not set, it uses the # value for "host.name" if configured. Otherwise, it will use the value returned from # java.net.InetAddress.getCanonicalHostName(). #advertised.host.name=<hostname routable by clients> # The port to publish to ZooKeeper for clients to use. If this is not set, # it will publish the same port that the broker binds to. #advertised.port=<port accessible by clients> # The number of threads handling network requests num.network.threads=3 # The number of threads doing disk I/O num.io.threads=8 # The send buffer (SO_SNDBUF) used by the socket server socket.send.buffer.bytes=102400 # The receive buffer (SO_RCVBUF) used by the socket server socket.receive.buffer.bytes=102400 # The maximum size of a request that the socket server will accept (protection against OOM) socket.request.max.bytes=104857600 ############################# Log Basics ############################# # A comma seperated list of directories under which to store log files log.dirs=/home/kafka-logs # The default number of log partitions per topic. More partitions allow greater # parallelism for consumption, but this will also result in more files across # the brokers. num.partitions=5 # The number of threads per data directory to be used for log recovery at startup and flushing at shutdown. # This value is recommended to be increased for installations with data dirs located in RAID array. num.recovery.threads.per.data.dir=1 ############################# Log Flush Policy ############################# # Messages are immediately written to the filesystem but by default we only fsync() to sync # the OS cache lazily. The following configurations control the flush of data to disk. # There are a few important trade-offs here: # 1. Durability: Unflushed data may be lost if you are not using replication. # 2. Latency: Very large flush intervals may lead to latency spikes when the flush does occur as there will be a lot of data to flush. # 3. Throughput: The flush is generally the most expensive operation, and a small flush interval may lead to exceessive seeks. # The settings below allow one to configure the flush policy to flush data after a period of time or # every N messages (or both). This can be done globally and overridden on a per-topic basis. # The number of messages to accept before forcing a flush of data to disk #log.flush.interval.messages=10000 # The maximum amount of time a message can sit in a log before we force a flush #log.flush.interval.ms=1000 ############################# Log Retention Policy ############################# # The following configurations control the disposal of log segments. The policy can # be set to delete segments after a period of time, or after a given size has accumulated. # A segment will be deleted whenever *either* of these criteria are met. Deletion always happens # from the end of the log. # The minimum age of a log file to be eligible for deletion log.retention.hours=168 # A size-based retention policy for logs. Segments are pruned from the log as long as the remaining # segments don't drop below log.retention.bytes. #log.retention.bytes=1073741824 # The maximum size of a log segment file. When this size is reached a new log segment will be created. log.segment.bytes=1073741824 # The interval at which log segments are checked to see if they can be deleted according # to the retention policies log.retention.check.interval.ms=300000 # By default the log cleaner is disabled and the log retention policy will default to just delete segments after their retention expires. # If log.cleaner.enable=true is set the cleaner will be enabled and individual logs can then be marked for log compaction. log.cleaner.enable=false export HBASE_MANAGES_ZK=false offsets.storage=kafka dual.commit.enabled=true delete.topic.enable=true ############################# Zookeeper ############################# # Zookeeper connection string (see zookeeper docs for details). # This is a comma separated host:port pairs, each corresponding to a zk # server. e.g. "127.0.0.1:3000,127.0.0.1:3001,127.0.0.1:3002". # You can also append an optional chroot string to the urls to specify the # root directory for all kafka znodes. zookeeper.connect=192.168.80.121:2181,192.168.80.122:2181,192.168.80.123:2181 # Timeout in ms for connecting to zookeeper zookeeper.connection.timeout.ms=6000
Kafka的3节点集群详细启动步骤
第一步、首先启动kafka进程
[hadoop@hadoop1 kafka]$ nohup bin/kafka-server-start.sh config/server.properties > kafka.log 2>&1 &
[2] 4609
[hadoop@hadoop2 kafka]$ nohup bin/kafka-server-start.sh config/server.properties > kafka.log 2>&1 &
[2] 10077
[hadoop@hadoop3 kafka]$ nohup bin/kafka-server-start.sh config/server.properties > kafka.log 2>&1 &
[1] 8079
第二步、创建topics
[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --create --topic t-behavior --replication-factor 3 --partitions 3
或者
[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181 --create --topic t-behavior --replication-factor 3 --partitions 3
第三步：查看topic 和 topic详情
[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --list
t-behavior
[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --describe --topic t-behavior
或者
[hadoop@hadoop1 bin]$
./kafka-topics.sh --zookeeper hadoop1:2181 --list
t-behavior
[hadoop@hadoop1 bin]$ ./kafka-topics.sh --zookeeper hadoop1:2181 --describe --topic t-behavior
Topic:t-behavior PartitionCount:1 ReplicationFactor:3 Configs:
Topic: t-behavior Partition: 0 Leader: 3 Replicas: 3,2,1 Isr: 3,1,2
第四步：开启Kafka producer生产者（在hadoop1和hadoop2和hadoop3都可以）
模拟producer发送消息
用命令行的方式手动的往kafka的topic里面发送消息：
[hadoop@hadoop2 bin]$ ./kafka-console-producer.sh --broker-list hadoop1:9092,hadoop1:9092,hadoop1:9092 --topic t-behavior
[2015-09-24 14:03:24,616] WARN Property topic is not valid (kafka.utils.VerifiableProperties)
This is Kafka producer.
Hello
或者
[hadoop@hadoop2 bin]$ ./kafka-console-producer.sh --broker-list hadoop1:9092 --topic t-behavior
第五步:开启Kafka consumer消费者（在hadoop1和hadoop2和hadoop3都可以）
[hadoop@hadoop3 bin]$./kafka-console-consumer.sh --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --topic t-behavior --from-beginning
This is Kafka producer.
Hello
或者
[hadoop@hadoop3 bin]$./kafka-console-consumer.sh --zookeeper hadoop1:2181 --topic t-behavior
第六步：停止kafka
cd $KAFKA_HOME/bin
./kafka-server-stop.sh
或者找到kafka的进程，直接kill掉即可。
彻底删除topic：
1、删除kafka存储目录（server.properties文件log.dirs配置，默认为"/tmp/kafka-logs"）相关topic目录
2、如果配置了delete.topic.enable=true直接通过命令删除，如果命令删除不掉，直接通过zookeeper-client 删除掉broker下的topic即可。
[hadoop@hadoop1 bin]$ ./kafka-topics.sh --delete --zookeeper hadoop1:2181,hadoop2:2181,hadoop3:2181 --topic t-behavior
其实啊，现在越来越多的优秀插件出来了。
可以不需这么命令行去做了，直接界面化多么的好！