大数据_Kafka_搭建Kafka伪集群(本地集群）

这里假设大家已经装好了Kafka的环境，并对kafka的知识有基本的了解。

下面直接讲解如何搭建一个本地的伪集群：（里面用到了zookeeper 伪集群 ）

搭建Zookeeper伪集群可以参考：http://blog.csdn.net/u010003835/article/details/52215054

集群配置：

Step1 将配置文件拷贝多份

cp config/server.properties config/server-1.properties

cp config/server.properties config/server-2.properties
cp config/server.properties config/server-3.properties

Step2: 修改 每个server 的配置文件  server-x.properties

下面仅列出了修改的配置文件的需要修改的参数,最后面有一份完整的配置文件。

config/server-1.properties:

    host.name=10.200.22.222

    broker.id=1

    port=9093

    log.dir=/tmp/kafka-logs-1

    zookeeper.connect=master:2182,master:2183,master:2184

config/server-2.properties:

    host.name=10.200.22.222

    broker.id=2

    port=9094

    log.dir=/tmp/kafka-logs-2

    zookeeper.connect=master:2182,master:2183,master:2184

config/server-3.properties:

    host.name=10.200.22.222

    broker.id=2

    port=9095

    log.dir=/tmp/kafka-logs-3
   zookeeper.connect=master:2182,master:2183,master:2184

注意：

1.真正集群要设置host.name和advertised.host.name这两个属性(博主感觉只要host.name就行了,没上业务,不好评论)

2.host.name 一定要配成真实IP 如 10.200.22.222

一份完整的配置文件：

server-1.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.
# 集群中Kafka的唯一标识，类似于Zookeeper 的 myid 作用
broker.id=1

# 提供服务的端口号
port=9093

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

# The address the socket server listens on. It will get the value returned from
# java.net.InetAddress.getCanonicalHostName() if not configured.
#   FORMAT:
#     listeners = security_protocol://host_name:port
#   EXAMPLE:
#     listeners = PLAINTEXT://your.host.name:9092
#listeners=PLAINTEXT://:9092

# Hostname and port the broker will advertise to producers and consumers. If not set,
# it uses the value for "listeners" if configured.  Otherwise, it will use the value
# returned from java.net.InetAddress.getCanonicalHostName().
#advertised.listeners=PLAINTEXT://your.host.name:9092

# 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

host.name=10.200.22.222

############################# Log Basics #############################

# A comma seperated list of directories under which to store log files
log.dirs=/usr/local/kafka/kafka_data/server1/

# 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=3

# 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

#The kafka data backups num
#Kafka 数据备份的个数
default.replication.factor=2

############################# 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=master:2182,master:2183,master:2184

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

Step3:启动伪集群的各个server

JMX_PORT=9997 bin/kafka-server-start.sh -daemon config/server-1.properties 

JMX_PORT=9998 bin/kafka-server-start.sh -daemon config/server-2.properties 

JMX_PORT=9999 bin/kafka-server-start.sh -daemon config/server-3.properties 
伪分布式集群启动要加：JMX_PORT=
(否则之后的生产者消费者校验程序会出问题)

后台启动参数：-daemon

Step4:搭建成功

完成以上3步就算搭建成功了。这里提供一个生产消费Demo,进行检测 （Java Maven项目）  

http://pan.baidu.com/s/1eS9IzSI

密码：yqp7

自己修改参数即可

Step5:生产消费源码展示