kafka集群安装部署

安装包准备

1、jdk1.8
2、kafka_2.12-2.3.0

安装JDK

1、下载jdk解压、配置环境变量

vi /etc/profile

export JAVA_HOME=/root/jdk1.8.0_161
export JRE_HOME=$JAVA_HOME/jre
export CLASSPATH=.:$JAVA_HOME/lib:$JRE_HOME/lib:$CLASSPATH
export PATH=$JAVA_HOME/bin:$JRE_HOME/bin:$PATH
注：JAVA_home为jdk文件的绝对路径，其他不变

2、Java -version 查看是否安装成功

java version "1.8.0_161"
Java(TM) SE Runtime Environment (build 1.8.0_161-b12)
Java HotSpot(TM) Server VM (build 25.161-b12, mixed mode)
注：内容大致这样，则证明安装成功

安装kafka

1、解压文件包

tar -xvf kafka_2.12-2.3.0.tgz 

2、添加环境变量

export KAFKA_HOME=/root/kafka
export PATH=$KAFKA_HOME/bin:$PATH

3、修改配置文件

cd /root/kafka/config

①修改server.properties文件

############################# Server Basics #############################

# The id of the broker. This must be set to a unique integer for each broker.
# broker.id=1 
**部署集群时这里可以配置集群中机器代号 

############################# 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://10.171.51.74:9092
#listeners=PLAINTEXT://:9092
port=9092
listeners=PLAINTEXT://10.171.51.74:9092
advertised.listeners=PLAINTEXT://10.171.51.74:9092
host.name=10.171.51.74
**以上配置监听部分必须配置，本机ip+9092端口**
# 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://10.171.51.74:9092
**这里也是本机ip+9092端口
# 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 separated list of directories under which to store log files
log.dirs=kafka/kafka-logs
**这里的地址需要注意，有可能会需要改，根据需要判断
# 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 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 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. "10.171.51.127:2181,10.171.51.84:2181,10.171.51.74:2181".
**这里是集群中机器的ip+2181端口
# You can also append an optional chroot string to the urls to specify the
# root directory for all kafka znodes.
zookeeper.connect=10.171.51.74:2181,10.171.51.84:2181,10.171.51.127:2181
**这里是集群中机器的ip+2181端口
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=60000
**这里建议设置长一些


############################# 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

测试kafka是否安装成功

1、启动zookeeper

/root/kafka/bin/zookeeper-server-start.sh -daemon /root/kafka/config/zookeeper.properties &
//启动文件路径 zookeeper配置文件路径
//这里在相对应文件夹下，可以节省一些指令数，但建议编写绝对路径

2、检查连接情况

jps
//查看当前服务

出现

12341 Jps
12206 QuorumPeerMain

则证明zookeeper启动成功

3、
运行

/root/kafka/bin/kafka-server-start.sh -daemon /root/kafka/config/server.properties &
//指令要点同zookeeper

4、查看服务

jps

当出现kafka则证明zookeeper及kafka启动成功

通信

所有集群所属机器配置完成后
1、在kafka01(Broker)上创建测试Tpoic：lmc
这里我们指定了1个副本、1个分区（装几个改成几）

/root/kafka/bin/kafka-topics.sh --create --bootstrap-server 10.171.51.74:9092 --replication-factor 1 --partitions 1 --topic lmc

2、发送消息

/root/kafka/bin/kafka-console-producer.sh --broker-list  10.171.51.74:9092  --topic lmc

3、消费消息

/root/kafka/bin/kafka-console-consumer.sh --bootstrap-server 10.171.51.84:9092 --topic lmc --from-beginning

总结

1、我这里是将所有的文件放在root目录下，不建议这样做
2、如遇到myid缺失的问题，在data文件下建立myid文件并赋予节点

echo ‘4’>>myid