<![CDATA[
###解压缩
`tar -zxvf kafka_2.10-0.8.2.2.tgz`
###重命名
`mv kafka_2.10-0.8.2.2 kafka`
###修改配置文件
修改服务器的config/server.properties。
broker.id：标识当前的server在集群中的id，唯一，填数字（非负数）。
host.name：当前server host name，唯一，填服务器IP。
zookeeper.connect：连接zookeeper的集群。
log.dirs：log的存储目录，记得创建对应的目录。
```
############################# 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 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
host.name=192.168.101.56
# 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=/liguodong/install/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
num.partitions=2
# 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
# By default the log cleaner is disabled and the log retention policy will default to just delete segments after their retention expires.
# 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 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=localhost:2181
zookeeper.connect=192.168.101.56:2181,192.168.101.10:2181,192.168.101.71:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000
```
创建日志目录：`mkdir -p /liguodong/install/tmp/kafka-logs`
通过"scp -r"把配置好的kafka目录copy到其他几台server上：
eg:
`scp -r kafka/ root@192.168.101.71:/liguodong/install/`
修改每一台server的对应的配置文件：
主要是修改其中的broker.id和host.name属性，都必须唯一。
###启动集群
zookeeper为独立安装，先启动zookeeper集群: `bin/zkServer.sh start`
查看状态：`bin/zkServer.sh status`
启动kafka集群,每台机器上执行命令：`nohup bin/kafka-server-start.sh config/server.properties &`
创建topic：
`bin/kafka-topics.sh --create --zookeeper 192.168.101.56:2181,192.168.101.10:2181,192.168.101.71:2181 --replication-factor 3 --partitions 1 --topic mykafka`
查看Topic：
`bin/kafka-topics.sh --list --zookeeper 192.168.101.56:2181,192.168.101.10:2181,192.168.101.71:2181`
查看详细信息：
`bin/kafka-topics.sh --describe --zookeeper 192.168.101.56:2181,192.168.101.10:2181,192.168.101.71:2181`
```
Topic:mykafka PartitionCount:1 ReplicationFactor:3 Configs:
Topic: mykafka Partition: 0 Leader: 0 Replicas: 0,2,1 Isr: 0,2,1
```
leader：负责处理消息的读和写，leader是从所有节点中随机选择的.
replicas：列出了所有的副本节点，不管节点是否在服务中.
isr：是正在服务中的节点.
**一台server发送消息：**
`bin/kafka-console-producer.sh --broker-list 192.168.101.56:9092,192.168.101.10:9092,192.168.101.71:9092 --topic mykafka`
**另一台server接收消息：**
`bin/kafka-console-consumer.sh --zookeeper 192.168.101.56:2181,192.168.101.10:2181,192.168.101.71:2181 --topic mykafka --from-beginning`
###测试Kafka的容错能力
```
bin/kafka-topics.sh --describe --zookeeper 192.168.101.56:2181,192.168.101.10:2181,192.168.101.71:2181
Topic:mykafka PartitionCount:1 ReplicationFactor:3 Configs:
Topic: mykafka Partition: 0 Leader: 0 Replicas: 0,2,1 Isr: 0,2,1
```
Broker 0作为leader运行，现在我们kill掉它：
```
[root@hadoop kafka]# jps
15339 Jps
12424 QuorumPeerMain
12585 Kafka
[root@hadoop kafka]# kill -9 12585
```
另外一个节点被选做了leader, node 0不再出现在 in-sync 副本列表中：
```
[root@hadoop kafka]# bin/kafka-topics.sh --describe --zookeeper 192.168.101.56:2181,192.168.101.10:2181,192.168.101.71:2181
Topic:mykafka PartitionCount:1 ReplicationFactor:3 Configs:
Topic: mykafka Partition: 0 Leader: 2 Replicas: 0,2,1 Isr: 2,1
```
虽然最初负责续写消息的leader down掉了，但之前的消息还是可以消费的：
```
[root@localhost kafka]# bin/kafka-console-consumer.sh --zookeeper 192.168.101.56:2181,192.168.101.10:2181,192.168.101.71:2181 --topic mykafka --from-beginning
dsdsf
liguodong ggg
liguodong good
kkkk
```
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