###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 ```