下载地址：http://mirrors.cnnic.cn/apache/kafka/0.9.0.1/kafka_2.10-0.9.0.1.tgz

分别在三台服务器（new-cdh15、new-cdh16、new-cdh17）上安装kafka：

1、解压

[hadoop@new-cdh15 soft]$ tar -zvxf kafka_2.10-0.9.0.1.tgz

2、修改配置

修改每台服务器的config/server.properties

broker.id：  唯一，填数字，可以填写ip 最后一个字段 15/16/17 host.name：唯一，填服务器IP

zookeeper.connect=new-cdh12:2181,new-cdh13:2181,new-cdh15:2181,new-cdh16:2181,new-cdh17:2181

log.dirs=/hadoop/tmp/kafka-logs :store log files

详细文档

[hadoop@new-cdh15 kafka_2.10-0.9.0.1]$ cat config/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=15

############################# Socket Server Settings #############################

listeners=PLAINTEXT://:9092

# 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=new-cdh15

# 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=

# 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=

# 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=/hadoop/tmp/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=1

# 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

############################# 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=new-cdh12:2181,new-cdh13:2181,new-cdh15:2181,new-cdh16:2181,new-cdh17:2181

# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000

3、启动kafka

[hadoop@new-cdh15 kafka_2.10-0.9.0.1]$ bin/kafka-server-start.sh config/server.properties &

5、加入环境变量

[hadoop@new-cdh15 kafka_2.10-0.9.0.1]$ vi ~/.bash_profile
# .bash_profile

# Get the aliases and functions
if [ -f ~/.bashrc ]; then
. ~/.bashrc
fi

# User specific environment and startup programs

#set zookeeper environment
export ZOOKEEPER_HOME=/hadoop/soft/zookeeper-3.4.5-cdh5.7.0
export KAFKA_HOME=/hadoop/soft/kafka_2.10-0.9.0.1
PATH=PATH:PATH:HOME/bin:ZOOKEEPER_HOME/bin:ZOOKEEPER\_HOME/bin:ZOOKEEPER_HOME/conf:$KAFKA_HOME/bin

export PATH

6、测试kafka

创建topic

[hadoop@new-cdh15 kafka_2.10-0.9.0.1]$ bin/kafka-topics.sh --create --zookeeper new-cdh12:2181,new-cdh13:2181,new-cdh15:2181,new-cdh16:2181,new-cdh17:2181 --replication-factor 3 --partitions 1 --topic mykafka3
Created topic “mykafka3”.

查看topic

bin/kafka-topics.sh --list --zookeeper new-cdh12:2181,new-cdh13:2181,new-cdh15:2181,new-cdh16:2181,new-cdh17:2181
mykafka
mykafka1
mykafka3
mykafkatest

在 new-cdh15 发送 topic

[hadoop@new-cdh15 kafka_2.10-0.9.0.1]$ bin/kafka-console-producer.sh --broker-list new-cdh15:9092 --topic mykafka3

asdasd
sad
asdas
dsa
dasas
dasasad

在new-cdh16 接收 topic:

[hadoop@new-cdh16 kafka_2.10-0.9.0.1]$ bin/kafka-console-consumer.sh --zookeeper new-cdh12:2181,new-cdh13:2181,new-cdh15:2181,new-cdh16:2181,new-cdh17:2181 --topic mykafka3 --from-beginning

asdasd
sad
asdas
dsa
dasas
dasasad

测试OK 建议安装 kafka manager 通过网页来监管 kafka