环境准备

1. zookeeper集群环境

   kafka是依赖于zookeeper注册中心的一款分布式消息对列，所以需要有zookeeper单机或者集群环境。

2. 三台服务器：

172.16.18.198 k8s-n1172.16.18.199 k8s-n2 172.16.18.200 k8s-n3

1. 下载kafka安装包

http://kafka.apache.org/downloads 中下载，目前最新版本的kafka已经到2.2.0,我这里之前下载的是kafka_2.11-2.2.0.tgz.

安装kafka集群

1.上传压缩包到三台服务器解压缩到/opt/目录下

tar -zxvf kafka_2.11-2.2.0.tgz -C /opt/ ls -s kafka_2.11-2.2.0 kafka

2.修改 server.properties

############################# 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://your.host.name:9092listeners=PLAINTEXT://k8s-n1:9092# 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://k8s-n1:9092# 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 networknum.network.threads=3# The number of threads that the server uses for processing requests, which may include disk I/Onum.io.threads=8# The send buffer (SO_SNDBUF) used by the socket serversocket.send.buffer.bytes=102400# The receive buffer (SO_RCVBUF) used by the socket serversocket.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 separated list of directories under which to store log fileslog.dirs=/var/applog/kafka/# 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############################# 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=1transaction.state.log.replication.factor=1transaction.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 excessive 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 disklog.flush.interval.messages=10000# The maximum amount of time a message can sit in a log before we force a flushlog.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 agelog.retention.hours=24# 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 policieslog.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=k8s-n1:2181,k8s-n2:2181,k8s-n3:2181# Timeout in ms for connecting to zookeeperzookeeper.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=0delete.topic.enable=true

 

拷贝两份到k8s-n2,k8s-n3

[root@k8s-n2 config]# cat server.properties broker.id=1listeners=PLAINTEXT://k8s-n2:9092advertised.listeners=PLAINTEXT://k8s-n2:9092[root@k8s-n3 config]# cat server.propertiesbroker.id=2listeners=PLAINTEXT://k8s-n3:9092advertised.listeners=PLAINTEXT://k8s-n3:9092

1. 添加环境变量 在/etc/profile 中添加

export ZOOKEEPER_HOME=/opt/kafka_2.11-2.2.0export PATH=$PATH:$ZOOKEEPER_HOME/bin

source /etc/profile 重载生效

1. 启动kafka

kafka-server-start.sh config/server.properties &

Zookeeper+Kafka集群测试

1.创建topic:

kafka-topics.sh --create --zookeeper k8s-n1:2181, k8s-n2:2181, k8s-n3:2181 --replication-factor 3 --partitions 3 --topic test

2.显示topic

kafka-topics.sh --describe --zookeeper k8s-n1:2181, k8s-n2:2181, k8s-n3:2181 --topic test

3.列出topic

kafka-topics.sh --list --zookeeper k8s-n1:2181, k8s-n2:2181, k8s-n3:2181 test

创建 producer(生产者);

kafka-console-producer.sh --broker-list k8s-n1:9092 --topic test hello

创建 consumer（消费者）

kafka-console-consumer.sh --bootstrap-server k8s-n1:9092 --topic test --from-beginninghello

至此，kafka集群搭建就已经完成了。