kafka简述与集群配置

一、kafka简述

 1、简介

kafka是一个高吞吐的分布式消息队列系统。特点是生产者消费者模式，先进先出（FIFO）保证顺序，自己不丢数据，默认每隔7天清理数据。消息列队常见场景：系统之间解耦合、峰值压力缓冲、异步通信。

2、集群介绍

（1）Kafka架构是由producer（消息生产者）、consumer（消息消费者）、borker(kafka集群的server，负责处理消息读、写请求，存储消息，在kafka cluster这一层这里，其实里面是有很多个broker)、topic（消息队列/分类相当于队列，里面有生产者和消费者模型）、zookeeper(元数据信息存在zookeeper中，包括：存储消费偏移量，topic话题信息，partition信息) 这些部分组成。

（2）kafka里面的消息是有topic来组织的，简单的我们可以想象为一个队列，一个队列就是一个topic，然后它把每个topic又分为很多个partition，这个是为了做并行的，在每个partition内部消息强有序，相当于有序的队列，其中每个消息都有个序号offset，比如0到12，从前面读往后面写。一个partition对应一个broker，一个broker可以管多个partition，比如说，topic有6个partition，有两个broker，那每个broker就管3个partition。这个partition可以很简单想象为一个文件，当数据发过来的时候它就往这个partition上面append，追加就行，消息不经过内存缓冲，直接写入文件，kafka和很多消息系统不一样，很多消息系统是消费完了我就把它删掉，而kafka是根据时间策略删除，而不是消费完就删除，在kafka里面没有一个消费完这么个概念，只有过期这样一个概念。

（3）producer自己决定往哪个partition里面去写，这里有一些的策略，譬如如果hash，不用多个partition之间去join数据了。consumer自己维护消费到哪个offset，每个consumer都有对应的group，group内是queue消费模型（各个consumer消费不同的partition，因此一个消息在group内只消费一次），group间是publish-subscribe消费模型，各个group各自独立消费，互不影响，因此一个消息在被每个group消费一次。

3、leader负载均衡机制

当一个broker停止或者crashes时，所有本来将它作为leader的分区将会把leader转移到其他broker上去，极端情况下，会导致同一个leader管理多个分区，导致负载不均衡，同时当这个broker重启时，如果这个broker不再是任何分区的leader,kafka的client也不会从这个broker来读取消息，从而导致资源的浪费。

kafka中有一个被称为优先副本（preferred replicas）的概念。如果一个分区有3个副本，且这3个副本的优先级别分别为0,1,2，根据优先副本的概念，0会作为leader 。当0节点的broker挂掉时，会启动1这个节点broker当做leader。当0节点的broker再次启动后，会自动恢复为此partition的leader。不会导致负载不均衡和资源浪费，这就是leader的均衡机制。

在配置文件conf/ server.properties中配置开启（默认就是开启）：

auto.leader.rebalance.enable true

 

二、集群配置

1、zookeeper安装与配置

（1）下载并解压

    去下载https://mirrors.tuna.tsinghua.edu.cn/apache/zookeeper/

   在node01 /opt/bigdata/下 解压 tar -zxvf zookeeper-3.4.6.tar.gz

（2）编辑配置

 

• 配置hosts vim /etc/hosts

192.168.172.73 node03
192.168.172.72 node02
192.168.172.71 node01

• 配置zookeeper环境变量

export ZOOKEEPER_HOME=/opt/bigdata/zookeeper-3.4.6 #zookeeper安装路径  
export PATH=$ZOOKEEPER_HOME/bin:$PATH

 

• 配置zoo.cfg

在/opt/bigdata下，复制cp zookeeper-3.4.5/conf/zoo_sample.cfg  zookeeper-3.4.5/conf/zoo.cfg 

编辑：vim zookeeper-3.4.5/conf/zoo.cfg 

# The number of milliseconds of each tick
tickTime=2000
# The number of ticks that the initial 
# synchronization phase can take
initLimit=10
# The number of ticks that can pass between 
# sending a request and getting an acknowledgement
syncLimit=5
# the directory where the snapshot is stored.
# do not use /tmp for storage, /tmp here is just 
# example sakes.
dataDir=/opt/bigdata/data/zookeeper/zkdata #zookeeper数据存放路径
dataLogDir=/opt/bigdata/data/zookeeper/zkdatalog #zookeeper日志存放路径
# the port at which the clients will connect
clientPort=2181        ##zookeeper对外通信端口

server.1=node01:2888:3888  
server.2=node02:2888:3888  
server.3=node03:2888:3888 
#
# Be sure to read the maintenance section of the 
# administrator guide before turning on autopurge.
#
# http://zookeeper.apache.org/doc/current/zookeeperAdmin.html#sc_maintenance
#
# The number of snapshots to retain in dataDir
#autopurge.snapRetainCount=3
# Purge task interval in hours
# Set to "0" to disable auto purge feature
#autopurge.purgeInterval=1

分别在node01、node02、node03下/opt/bigdata/data/zookeeper/zkdata

vim myid 新建myid文件，内容分别为1、2、3保存

（3）节点分发

在node01 /opt/bigdata下 scp远程复制，分别分发到node02、node03对应目录下

scp -r zookeeper-3.4.6 node02:`pwd`
scp -r zookeeper-3.4.6 node03:`pwd`

 

（4）启动zookeeper集群

分别在node01、node02、node03下执行 zkServer.sh start命令启动zookeeper

稍等片刻，分别在node01、node02、node03下执行zkServer.sh status命令，查看状态

[root@node01 ~]# zkServer.sh status
JMX enabled by default
Using config: /opt/bigdata/zookeeper-3.4.5/bin/../conf/zoo.cfg
Mode: leader
[root@node02 bigdata]# zkServer.sh status
JMX enabled by default
Using config: /opt/bigdata/zookeeper-3.4.5/bin/../conf/zoo.cfg
Mode: follower
[root@node03 ~]# zkServer.sh status
JMX enabled by default
Using config: /opt/bigdata/zookeeper-3.4.5/bin/../conf/zoo.cfg
Mode: follower

3、kafka安装与配置

（1）下载并解压

wget http://mirror.bit.edu.cn/apache/kafka/1.1.0/kafka_2.11-1.1.0.tgz 去下载

在node01上  /opt/bigdata/下 解压

tar zxvf kafka_2.11-1.1.0.tgz  

（2）编辑配置

在/opt/bigdata/下 vim kafka_2.11-1.1.0/config/server.properties编辑配置

这里重点修改三个参数broker.id标识本机、log.dirs是kafka接收消息存放路径、

zookeeper.connect指定连接的zookeeper集群地址

其他参数保持默认即可，也可自己根据情况修改

############################# Server Basics #############################
# The id of the broker. This must be set to a unique integer for each broker.
broker.id=1
############################# 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=localhost

# 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=<hostname routable by clients>

# 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=<port accessible by clients>

# 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=/opt/bigdata/kafka_2.11-1.1.0/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 #############################
# 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

# If log.cleaner.enable=true is set the cleaner will be enabled and individual logs can then be marked for log compaction.
log.cleaner.enable=false

############################# Zookeeper #############################
zookeeper.connect=node01:2181,node02:2181,node03:2181

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

（3）节点分发

在 /opt/bigdata下 远程复制到node01、node02对应路径下，当然复制时需要ssh免登录

scp -r  kafka_2.11-1.1.0 node02:`pwd`
scp -r  kafka_2.11-1.1.0 node03:`pwd`

分别修改server.properties对应的broker.id为2、3即可

（4）启动kafka集群

kafka集群启动前要启动zookeeper集群，若zookeeper集群没启动，首先启动

在/opt/bigdata下 ，三个节点分别执行如下命令，启动kafka集群

./kafka_2.11-1.1.0/bin/kafka-server-start.sh -daemon ./kafka_2.11-1.1.0/config/server.properties &

（5）基本操作

1)、创建topic

./kafka_2.11/bin/kafka-topics.sh --create --zookeeper node02:2181,node03:2181,node04:2181 --replication-factor 2 --partitions 2 --topic kfk_test

2)、列出创建的topic

./kafka_2.11/bin/kafka-topics.sh --list --zookeeper node02:2181,node03:2181,node04:2181

3)、生成数据

./kafka_2.11/bin/kafka-console-producer.sh -broker-list node02:9092,node03:9092,node04:9092 --topic kfk_test

4)、消费生产数据

kafka 0.9版本之前用zookeeper 
./kafka_2.11/bin/kafka-console-consumer.sh --zookeeper node02:2181,node03:2181,node04:2181 --from-beginning --topic kfk_test

kafka 0.9版本之后不推荐zookeeper方式,仍然支持，但逐渐会被取消，推荐bootstrap-server方式
./kafka_2.11/bin/kafka-console-consumer.sh --bootstrap-server node02:9092,node03:9092,node04:9092 --from-beginning --topic kfk_test

5)、查看指定topic信息

./kafka_2.11/bin/kafka-topics.sh --describe --zookeeper node02:2181,node03:2181,node04:2181 --topic kfk_test

信息如下：

Topic:kfk_test  PartitionCount:2	ReplicationFactor:2	Configs:
Topic: kfk_test	 Partition: 0	Leader: 2	Replicas: 2,4	Isr: 2,4
Topic: kfk_test	 Partition: 1	Leader: 3	Replicas: 3,2	Isr: 3,2

可以看到2个分区，2个副本

partiton： partion id 
leader：当前负责读写的lead broker id ，就是server.properties的broker.id
replicas：当前partition的所有replication broker  list 
isr：relicas的子集，只包含出于活动状态的broker