消息中间件系列教程(21) -Kafka- 集群搭建(自带Zookeeper)

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简介: 消息中间件系列教程(21) -Kafka- 集群搭建(自带Zookeeper)

在前面一篇文章中《消息中间件系列教程(20) -Kafka-集群搭建》,我们分别搭建了Zookeeper和Kafka来实现Kafka的集群。其实Kfaka里面的压缩包里面包含了Zookeeper,可以在里面配置,本文基于上一篇博客来讲解。

1.首先新建kafka的日志目录和zookeeper数据目录(3台服务器同样操作)

mkdir /usr/local/kafka/zookeeper       
mkdir /usr/local/kafka/log             
mkdir /usr/local/kafka/log/zookeeper    
mkdir /usr/local/kafka/log/kafka

2.进入config目录下,修改zookeeper.properties配置文件(3台服务器同样操作)

cd /usr/local/kafka/config/
vi zookeeper.properties

修改内容如下:

tickTime=2000
initLimit=10
syncLimit=5
dataDir=/usr/local/kafka/zookeeper
clientPort=2181
server.0=192.168.162.131:2888:3888
server.1=192.168.162.132:2888:3888
server.2=192.168.162.133:2888:3888

3.zookeeper数据目录添加myid配置(3台服务器按zookeeper.properties的标识设置对应的id,比如192.168.162.131的id为0)

cd /usr/local/kafka/zookeeper
vi myid

4. 进入config目录下,修改server.properties文件(3台服务器除了broker.id、advertised.listeners,其它的都一样)

############################# Server Basics #############################
# The id of the broker. This must be set to a unique integer for each broker.
broker.id=0
############################# 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 = listener_name://host_name:port
#   EXAMPLE:
listeners=PLAINTEXT://192.168.162.131:9092
#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
# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details
#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL
# The number of threads that the server uses for receiving requests from the network and sending responses to the network
num.network.threads=3
# The number of threads that the server uses for processing requests, which may include 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=/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
############################# Internal Topic Settings  #############################
# The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state"
# For anything other than development testing, a value greater than 1 is recommended for to ensure availability such as 3.
offsets.topic.replication.factor=1
transaction.state.log.replication.factor=1
transaction.state.log.min.isr=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 due to age
log.retention.hours=168
# A size-based retention policy for logs. Segments are pruned from the log unless the remaining
# segments drop below log.retention.bytes. Functions independently of log.retention.hours.
#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=192.168.162.131:2181,192.168.162.132:2181,192.168.162.133:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000
############################# Group Coordinator Settings #############################
# The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.
# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.
# The default value for this is 3 seconds.
# We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=0

5. 启动Zookeeper(kafka启动时先启动zookeeper,再启动kafka,关闭时相反,先关闭kafka,再关闭zookeeper)

cd /usr/local/kafka/bin/
./zookeeper-server-start.sh -daemon ../config/zookeeper.properties

6.查看Zookeeper是否启动成功

ps -ef|grep zookeeper

如果现实如下信息,表示启动成功

7.启动kafka

cd /usr/local/kafka/bin/
./kafka-server-start.sh -daemon ../config/server.properties

8.查看kafka是否启动成功

ps -ef|grep kafka

如果现实如下信息,表示启动成功

9.使用Zookeeper可视化工具,可以看到zookeeper新增了3个kafka broker节点:

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