目录：
　　一、什么是kafka?
　　二、kafka的官方网站在哪里？
　　三、在哪里下载？需要哪些组件的支持？
　　四、如何安装？
　　五、FAQ
　　六、扩展阅读
 
　　一、什么是kafka?
　　kafka是LinkedIn开发并开源的一个分布式MQ系统，现在是Apache的一个孵化项目。在它的主页描述kafka为一个高吞吐量的分布式（能将消息分散到不同的节点上）MQ。Kafka仅仅由7000行Scala编写，据了解，Kafka每秒可以生产约25万消息（50 MB），每秒处理55万消息（110 MB）。
　　kafka目前支持多种客户端语言：java，python，c++，php等等。
　　kafka集群的简要图解如下，producer写入消息，consumer读取消息：
 
　　kafka设计目标
    • 高吞吐量是其核心设计之一。
    • 数据磁盘持久化：消息不在内存中cache，直接写入到磁盘，充分利用磁盘的顺序读写性能。
    • zero-copy：减少IO操作步骤。
    • 支持数据批量发送和拉取。
    • 支持数据压缩。
    • Topic划分为多个partition，提高并行处理能力。
 
　　kafka名词解释和工作方式：
    • Producer ：消息生产者，就是向kafka broker发消息的客户端。
    • Consumer ：消息消费者，向kafka broker取消息的客户端
    • Topic ：可以理解为一个队列。
    • Consumer Group （CG）：这是kafka用来实现一个topic消息的广播（发给所有的consumer）和单播（发给任意一个consumer）的手段。一个topic可以有多个CG。topic的消息会复制（不是真的复制，是概念上的）到所有的CG，但每个CG只会把消息发给该CG中的一个consumer。如果需要实现广播，只要每个consumer有一个独立的CG就可以了。要实现单播只要所有的consumer在同一个CG。用CG还可以将consumer进行自由的分组而不需要多次发送消息到不同的topic。
    • Broker ：一台kafka服务器就是一个broker。一个集群由多个broker组成。一个broker可以容纳多个topic。
    • Partition：为了实现扩展性，一个非常大的topic可以分布到多个broker（即服务器）上，一个topic可以分为多个partition，每个partition是一个有序的队列。partition中的每条消息都会被分配一个有序的id（offset）。kafka只保证按一个partition中的顺序将消息发给consumer，不保证一个topic的整体（多个partition间）的顺序。
    • Offset：kafka的存储文件都是按照offset.kafka来命名，用offset做名字的好处是方便查找。例如你想找位于2049的位置，只要找到2048.kafka的文件即可。当然the first offset就是00000000000.kafka
 
　　kafak系统扩展性：
    • kafka使用zookeeper来实现动态的集群扩展，不需要更改客户端（producer和consumer）的配置。broker会在zookeeper注册并保持相关的元数据（topic，partition信息等）更新。
    • 而客户端会在zookeeper上注册相关的watcher。一旦zookeeper发生变化，客户端能及时感知并作出相应调整。这样就保证了添加或去除broker时，各broker间仍能自动实现负载均衡。
 
　　kafak和zookeeper的关系：
    • Producer端使用zookeeper用来"发现"broker列表,以及和Topic下每个partition leader建立socket连接并发送消息.
    • Broker端使用zookeeper用来注册broker信息,已经监测partition leader存活性.
    • Consumer端使用zookeeper用来注册consumer信息,其中包括consumer消费的partition列表等,同时也用来发现broker列表,并和partition leader建立socket连接,并获取消息.
 
　　二、kafka的官方网站在哪里？
 
　　三、在哪里下载？需要哪些组件的支持？
　　kafka2.9.2在下面的地址可以下载：
 
　　需要zookeeper的支持，相关安装及下载，可以参考这篇文章《ubuntu12.04+hadoop2.2.0+zookeeper3.4.5+hbase0.96.2+hive0.13.1分布式环境部署》
 
　　四、如何安装？
　　1、解压kafka_2.9.2-0.8.1.1.tgz，本文中解压到/home/hadoop目录下
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root@m1:/home/hadoop/kafka_2.9.2-0.8.1.1# pwd
/home/hadoop/kafka_2.9.2-0.8.1.1
　　2、修改server.properties配置文件。这里使用zookeeper的部分，请参考可以参考这篇文章《ubuntu12.04+hadoop2.2.0+zookeeper3.4.5+hbase0.96.2+hive0.13.1分布式环境部署》中的配置，见下方第123行：
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root@m1:/home/hadoop/kafka_2.9.2-0.8.1.1# cat config/server.properties
# Licensed to the Apache Software Foundation (ASF) under one or more
# contributor license agreements.  See the NOTICE file distributed with
# this work for additional information regarding copyright ownership.
# The ASF licenses this file to You under the Apache License, Version 2.0
# (the "License"); you may not use this file except in compliance with
# the License.  You may obtain a copy of the License at
#
#    http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# see kafka.server.KafkaConfig for additional details and defaults
 
############################# Server Basics #############################
 
# The id of the broker. This must be set to a unique integer for each broker.
#整数，建议根据ip区分,这里我是使用zookeeper中的id来设置
broker.id=1
 
############################# Socket Server Settings #############################
 
# The port the socket server listens on
#broker用于接收producer消息的端口
port=9092
#port=44444
 
# Hostname the broker will bind to. If not set, the server will bind to all interfaces
#broker的hostname
host.name=m1
 
# 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().
#这个是配置PRODUCER/CONSUMER连上来的时候使用的地址
advertised.host.name=m1
 
# 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=2
  
# 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=1048576
 
# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=1048576
 
# 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
#kafka存放消息文件的路径
log.dirs=/home/hadoop/kafka_2.9.2-0.8.1.1/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.
#topic的默认分区数
num.partitions=2
 
############################# 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
#kafka接收日志的存储目录(目前我们保存7天数据log.retention.hours=168)
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=536870912
 
# 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=60000
 
# 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=m1:2181,m2:2181,s1:2181,s2:2181
 
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=1000000
　　3、启动zookeeper和kafka
　　　　1)zookeeper的启动，请参考这篇文章《ubuntu12.04+hadoop2.2.0+zookeeper3.4.5+hbase0.96.2+hive0.13.1分布式环境部署》
　　　　启动后可以用以下命令在每台机器上查看状态：
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root@m1:/home/hadoop# /home/hadoop/zookeeper-3.4.5/bin/zkServer.sh status
JMX enabled by default
Using config: /home/hadoop/zookeeper-3.4.5/bin/../conf/zoo.cfg
Mode: leader
　　　　2)在m1,m2,m3,m4的机器上启动kafka，在这之前请先将m1上的kafka复制到另外三台机器上，复制后，记得更改server.properties配置文件中的host名称为当前所在机器。以下代码是在m1上执行后的效果：
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root@m1:/home/hadoop# /home/hadoop/kafka_2.9.2-0.8.1.1/bin/kafka-server-start.sh /home/hadoop/kafka_2.9.2-0.8.1.1/config/server.properties &
[1] 31823
root@m1:/home/hadoop# [2014-08-05 10:03:11,210] INFO Verifying properties (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,261] INFO Property advertised.host.name is overridden to m1 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,261] INFO Property broker.id is overridden to 1 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,264] INFO Property host.name is overridden to m1 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,264] INFO Property log.cleaner.enable is overridden to false (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,264] INFO Property log.dirs is overridden to /home/hadoop/kafka_2.9.2-0.8.1.1/kafka-logs (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,265] INFO Property log.retention.check.interval.ms is overridden to 60000 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,265] INFO Property log.retention.hours is overridden to 168 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,265] INFO Property log.segment.bytes is overridden to 536870912 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,265] INFO Property num.io.threads is overridden to 8 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,266] INFO Property num.network.threads is overridden to 2 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,266] INFO Property num.partitions is overridden to 2 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,267] INFO Property port is overridden to 9092 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,267] INFO Property socket.receive.buffer.bytes is overridden to 1048576 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,268] INFO Property socket.request.max.bytes is overridden to 104857600 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,268] INFO Property socket.send.buffer.bytes is overridden to 1048576 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,268] INFO Property zookeeper.connect is overridden to m1:2181,m2:2181,s1:2181,s2:2181 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,269] INFO Property zookeeper.connection.timeout.ms is overridden to 1000000 (kafka.utils.VerifiableProperties)
[2014-08-05 10:03:11,302] INFO [Kafka Server 1], starting (kafka.server.KafkaServer)
[2014-08-05 10:03:11,303] INFO [Kafka Server 1], Connecting to zookeeper on m1:2181,m2:2181,s1:2181,s2:2181 (kafka.server.KafkaServer)
[2014-08-05 10:03:11,335] INFO Starting ZkClient event thread. (org.I0Itec.zkclient.ZkEventThread)
[2014-08-05 10:03:11,348] INFO Client environment:zookeeper.version=3.3.3-1203054, built on 11/17/2011 05:47 GMT (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,348] INFO Client environment:host.name=m1 (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,349] INFO Client environment:java.version=1.7.0_65 (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,349] INFO Client environment:java.vendor=Oracle Corporation (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,349] INFO Client environment:java.home=/usr/lib/jvm/java-7-oracle/jre (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,349] INFO Client environment:java.class.path=.:/usr/lib/jvm/java-7-oracle/lib/tools.jar:/usr/lib/jvm/java-7-oracle/lib/dt.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../core/build/dependant-libs-2.8.0/*.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../perf/build/libs//kafka-perf_2.8.0*.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../clients/build/libs//kafka-clients*.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../examples/build/libs//kafka-examples*.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../contrib/hadoop-consumer/build/libs//kafka-hadoop-consumer*.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../contrib/hadoop-producer/build/libs//kafka-hadoop-producer*.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/jopt-simple-3.2.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/kafka_2.9.2-0.8.1.1.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/kafka_2.9.2-0.8.1.1-javadoc.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/kafka_2.9.2-0.8.1.1-scaladoc.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/kafka_2.9.2-0.8.1.1-sources.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/log4j-1.2.15.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/metrics-core-2.2.0.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/scala-library-2.9.2.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/slf4j-api-1.7.2.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/snappy-java-1.0.5.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/zkclient-0.3.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../libs/zookeeper-3.3.4.jar:/home/hadoop/kafka_2.9.2-0.8.1.1/bin/../core/build/libs/kafka_2.8.0*.jar (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,350] INFO Client environment:java.library.path=:/usr/local/lib:/usr/java/packages/lib/amd64:/usr/lib64:/lib64:/lib:/usr/lib (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,350] INFO Client environment:java.io.tmpdir=/tmp (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,350] INFO Client environment:java.compiler=<NA> (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,350] INFO Client environment:os.name=Linux (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,350] INFO Client environment:os.arch=amd64 (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,351] INFO Client environment:os.version=3.11.0-15-generic (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,351] INFO Client environment:user.name=root (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,351] INFO Client environment:user.home=/root (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,351] INFO Client environment:user.dir=/home/hadoop (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,352] INFO Initiating client connection, connectString=m1:2181,m2:2181,s1:2181,s2:2181 sessionTimeout=6000 watcher=org.I0Itec.zkclient.ZkClient@51f782b8 (org.apache.zookeeper.ZooKeeper)
[2014-08-05 10:03:11,380] INFO Opening socket connection to server m2/192.168.1.51:2181 (org.apache.zookeeper.ClientCnxn)
[2014-08-05 10:03:11,386] INFO Socket connection established to m2/192.168.1.51:2181, initiating session (org.apache.zookeeper.ClientCnxn)
[2014-08-05 10:03:11,398] INFO Session establishment complete on server m2/192.168.1.51:2181, sessionid = 0x247a3e09b460000, negotiated timeout = 6000 (org.apache.zookeeper.ClientCnxn)
[2014-08-05 10:03:11,400] INFO zookeeper state changed (SyncConnected) (org.I0Itec.zkclient.ZkClient)
[2014-08-05 10:03:11,652] INFO Loading log 'test-1' (kafka.log.LogManager)
[2014-08-05 10:03:11,681] INFO Recovering unflushed segment 0 in log test-1. (kafka.log.Log)
[2014-08-05 10:03:11,711] INFO Completed load of log test-1 with log end offset 137 (kafka.log.Log)
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
[2014-08-05 10:03:11,747] INFO Loading log 'idoall.org-0' (kafka.log.LogManager)
[2014-08-05 10:03:11,748] INFO Recovering unflushed segment 0 in log idoall.org-0. (kafka.log.Log)
[2014-08-05 10:03:11,754] INFO Completed load of log idoall.org-0 with log end offset 5 (kafka.log.Log)
[2014-08-05 10:03:11,760] INFO Loading log 'test-0' (kafka.log.LogManager)
[2014-08-05 10:03:11,765] INFO Recovering unflushed segment 0 in log test-0. (kafka.log.Log)
[2014-08-05 10:03:11,777] INFO Completed load of log test-0 with log end offset 151 (kafka.log.Log)
[2014-08-05 10:03:11,779] INFO Starting log cleanup with a period of 60000 ms. (kafka.log.LogManager)
[2014-08-05 10:03:11,782] INFO Starting log flusher with a default period of 9223372036854775807 ms. (kafka.log.LogManager)
[2014-08-05 10:03:11,800] INFO Awaiting socket connections on m1:9092. (kafka.network.Acceptor)
[2014-08-05 10:03:11,802] INFO [Socket Server on Broker 1], Started (kafka.network.SocketServer)
[2014-08-05 10:03:11,890] INFO Will not load MX4J, mx4j-tools.jar is not in the classpath (kafka.utils.Mx4jLoader$)
[2014-08-05 10:03:11,919] INFO 1 successfully elected as leader (kafka.server.ZookeeperLeaderElector)
[2014-08-05 10:03:12,359] INFO New leader is 1 (kafka.server.ZookeeperLeaderElector$LeaderChangeListener)
[2014-08-05 10:03:12,387] INFO Registered broker 1 at path /brokers/ids/1 with address m1:9092. (kafka.utils.ZkUtils$)
[2014-08-05 10:03:12,392] INFO [Kafka Server 1], started (kafka.server.KafkaServer)
[2014-08-05 10:03:12,671] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall.org,0],[test,0],[test,1] (kafka.server.ReplicaFetcherManager)
[2014-08-05 10:03:12,741] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall.org,0],[test,0],[test,1] (kafka.server.ReplicaFetcherManager)
[2014-08-05 10:03:25,327] INFO Partition [test,0] on broker 1: Expanding ISR for partition [test,0] from 1 to 1,2 (kafka.cluster.Partition)
[2014-08-05 10:03:25,334] INFO Partition [test,1] on broker 1: Expanding ISR for partition [test,1] from 1 to 1,2 (kafka.cluster.Partition)
[2014-08-05 10:03:26,905] INFO Partition [test,1] on broker 1: Expanding ISR for partition [test,1] from 1,2 to 1,2,3 (kafka.cluster.Partition)
　　4、测试kafka的状态
　　　　1)在m1上创建一个idoall_testTopic主题
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#KAFKA有几个，replication-factor就填几个
root@m1:/home/hadoop# /home/hadoop/kafka_2.9.2-0.8.1.1/bin/kafka-topics.sh --create --topic idoall_testTopic --replication-factor 4 --partitions 2 --zookeeper m1:2181
Created topic "idoall_testTopic".
[2014-08-05 10:08:29,315] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall_testTopic,0] (kafka.server.ReplicaFetcherManager)
[2014-08-05 10:08:29,334] INFO Completed load of log idoall_testTopic-0 with log end offset 0 (kafka.log.Log)
[2014-08-05 10:08:29,373] INFO Created log for partition [idoall_testTopic,0] in /home/hadoop/kafka_2.9.2-0.8.1.1/kafka-logs with properties {segment.index.bytes -> 10485760, file.delete.delay.ms -> 60000, segment.bytes -> 536870912, flush.ms -> 9223372036854775807, delete.retention.ms -> 86400000, index.interval.bytes -> 4096, retention.bytes -> -1, cleanup.policy -> delete, segment.ms -> 604800000, max.message.bytes -> 1000012, flush.messages -> 9223372036854775807, min.cleanable.dirty.ratio -> 0.5, retention.ms -> 604800000}. (kafka.log.LogManager)
[2014-08-05 10:08:29,384] WARN Partition [idoall_testTopic,0] on broker 1: No checkpointed highwatermark is found for partition [idoall_testTopic,0] (kafka.cluster.Partition)
[2014-08-05 10:08:29,415] INFO Completed load of log idoall_testTopic-1 with log end offset 0 (kafka.log.Log)
[2014-08-05 10:08:29,416] INFO Created log for partition [idoall_testTopic,1] in /home/hadoop/kafka_2.9.2-0.8.1.1/kafka-logs with properties {segment.index.bytes -> 10485760, file.delete.delay.ms -> 60000, segment.bytes -> 536870912, flush.ms -> 9223372036854775807, delete.retention.ms -> 86400000, index.interval.bytes -> 4096, retention.bytes -> -1, cleanup.policy -> delete, segment.ms -> 604800000, max.message.bytes -> 1000012, flush.messages -> 9223372036854775807, min.cleanable.dirty.ratio -> 0.5, retention.ms -> 604800000}. (kafka.log.LogManager)
[2014-08-05 10:08:29,422] WARN Partition [idoall_testTopic,1] on broker 1: No checkpointed highwatermark is found for partition [idoall_testTopic,1] (kafka.cluster.Partition)
[2014-08-05 10:08:29,430] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall_testTopic,1] (kafka.server.ReplicaFetcherManager)
[2014-08-05 10:08:29,438] INFO Truncating log idoall_testTopic-1 to offset 0. (kafka.log.Log)
[2014-08-05 10:08:29,473] INFO [ReplicaFetcherManager on broker 1] Added fetcher for partitions ArrayBuffer([[idoall_testTopic,1], initOffset 0 to broker id:2,host:m2,port:9092] ) (kafka.server.ReplicaFetcherManager)
[2014-08-05 10:08:29,475] INFO [ReplicaFetcherThread-0-2], Starting  (kafka.server.ReplicaFetcherThread)
　　　　2)在m1上查看刚才创建的idoall_testTopic主题
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root@m1:/home/hadoop# /home/hadoop/kafka_2.9.2-0.8.1.1/bin/kafka-topics.sh --list --zookeeper m1:2181  
idoall_testTopic
　　　　3)在m2上发送消息至kafka（m2模拟producer），发送消息“hello idoall.org”
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root@m2:/home/hadoop# /home/hadoop/kafka_2.9.2-0.8.1.1/bin/kafka-console-producer.sh --broker-list m1:9092 --sync --topic idoall_testTopic
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
hello idoall.org
　　　　4)在s1上开启一个消费者（s1模拟consumer），可以看到刚才发送的消息
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root@s1:/home/hadoop# /home/hadoop/kafka_2.9.2-0.8.1.1/bin/kafka-console-consumer.sh --zookeeper m1:2181 --topic idoall_testTopic --from-beginning
SLF4J: Failed to load class "org.slf4j.impl.StaticLoggerBinder".
SLF4J: Defaulting to no-operation (NOP) logger implementation
SLF4J: See http://www.slf4j.org/codes.html#StaticLoggerBinder for further details.
hello idoall.org
　　　　5)删除掉一个Topic，这里我们测试创建一个idoall的主题，再删除掉
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root@m1:/home/hadoop# /home/hadoop/kafka_2.9.2-0.8.1.1/bin/kafka-topics.sh --create --topic idoall --replication-factor 4 --partitions 2 --zookeeper m1:2181         
Created topic "idoall".
[2014-08-05 10:38:30,862] INFO Completed load of log idoall-1 with log end offset 0 (kafka.log.Log)
[2014-08-05 10:38:30,864] INFO Created log for partition [idoall,1] in /home/hadoop/kafka_2.9.2-0.8.1.1/kafka-logs with properties {segment.index.bytes -> 10485760, file.delete.delay.ms -> 60000, segment.bytes -> 536870912, flush.ms -> 9223372036854775807, delete.retention.ms -> 86400000, index.interval.bytes -> 4096, retention.bytes -> -1, cleanup.policy -> delete, segment.ms -> 604800000, max.message.bytes -> 1000012, flush.messages -> 9223372036854775807, min.cleanable.dirty.ratio -> 0.5, retention.ms -> 604800000}. (kafka.log.LogManager)
[2014-08-05 10:38:30,870] WARN Partition [idoall,1] on broker 1: No checkpointed highwatermark is found for partition [idoall,1] (kafka.cluster.Partition)
[2014-08-05 10:38:30,878] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall,1] (kafka.server.ReplicaFetcherManager)
[2014-08-05 10:38:30,880] INFO Truncating log idoall-1 to offset 0. (kafka.log.Log)
[2014-08-05 10:38:30,885] INFO [ReplicaFetcherManager on broker 1] Added fetcher for partitions ArrayBuffer([[idoall,1], initOffset 0 to broker id:3,host:s1,port:9092] ) (kafka.server.ReplicaFetcherManager)
[2014-08-05 10:38:30,887] INFO [ReplicaFetcherThread-0-3], Starting  (kafka.server.ReplicaFetcherThread)
root@m1:/home/hadoop# /home/hadoop/kafka_2.9.2-0.8.1.1/bin/kafka-topics.sh --list --zookeeper m1:2181
idoall
idoall_testTopic
root@m1:/home/hadoop# /home/hadoop/kafka_2.9.2-0.8.1.1/bin/kafka-run-class.sh kafka.admin.DeleteTopicCommand --topic idoall --zookeeper m2:2181   
deletion succeeded!
root@m1:/home/hadoop# /home/hadoop/kafka_2.9.2-0.8.1.1/bin/kafka-topics.sh --list --zookeeper m1:2181                  idoall_testTopic
root@m1:/home/hadoop#
　　　　同样也可以进入到zookeeper中查看主题是否已经删除掉。
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root@m1:/home/hadoop# /home/hadoop/zookeeper-3.4.5/bin/zkCli.sh
Connecting to localhost:2181
2014-08-05 10:15:21,863 [myid:] - INFO  [main:Environment@100] - Client environment:zookeeper.version=3.4.5-1392090, built on 09/30/2012 17:52 GMT
2014-08-05 10:15:21,871 [myid:] - INFO  [main:Environment@100] - Client environment:host.name=m1
2014-08-05 10:15:21,871 [myid:] - INFO  [main:Environment@100] - Client environment:java.version=1.7.0_65
2014-08-05 10:15:21,872 [myid:] - INFO  [main:Environment@100] - Client environment:java.vendor=Oracle Corporation
2014-08-05 10:15:21,872 [myid:] - INFO  [main:Environment@100] - Client environment:java.home=/usr/lib/jvm/java-7-oracle/jre
2014-08-05 10:15:21,873 [myid:] - INFO  [main:Environment@100] - Client environment:java.class.path=/home/hadoop/zookeeper-3.4.5/bin/../build/classes:/home/hadoop/zookeeper-3.4.5/bin/../build/lib/*.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/slf4j-log4j12-1.6.1.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/slf4j-api-1.6.1.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/netty-3.2.2.Final.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/log4j-1.2.15.jar:/home/hadoop/zookeeper-3.4.5/bin/../lib/jline-0.9.94.jar:/home/hadoop/zookeeper-3.4.5/bin/../zookeeper-3.4.5.jar:/home/hadoop/zookeeper-3.4.5/bin/../src/java/lib/*.jar:/home/hadoop/zookeeper-3.4.5/bin/../conf:.:/usr/lib/jvm/java-7-oracle/lib/tools.jar:/usr/lib/jvm/java-7-oracle/lib/dt.jar
2014-08-05 10:15:21,874 [myid:] - INFO  [main:Environment@100] - Client environment:java.library.path=:/usr/local/lib:/usr/java/packages/lib/amd64:/usr/lib64:/lib64:/lib:/usr/lib
2014-08-05 10:15:21,874 [myid:] - INFO  [main:Environment@100] - Client environment:java.io.tmpdir=/tmp
2014-08-05 10:15:21,874 [myid:] - INFO  [main:Environment@100] - Client environment:java.compiler=<NA>
2014-08-05 10:15:21,875 [myid:] - INFO  [main:Environment@100] - Client environment:os.name=Linux
2014-08-05 10:15:21,875 [myid:] - INFO  [main:Environment@100] - Client environment:os.arch=amd64
2014-08-05 10:15:21,876 [myid:] - INFO  [main:Environment@100] - Client environment:os.version=3.11.0-15-generic
2014-08-05 10:15:21,876 [myid:] - INFO  [main:Environment@100] - Client environment:user.name=root
2014-08-05 10:15:21,877 [myid:] - INFO  [main:Environment@100] - Client environment:user.home=/root
2014-08-05 10:15:21,878 [myid:] - INFO  [main:Environment@100] - Client environment:user.dir=/home/hadoop
2014-08-05 10:15:21,879 [myid:] - INFO  [main:ZooKeeper@438] - Initiating client connection, connectString=localhost:2181 sessionTimeout=30000 watcher=org.apache.zookeeper.ZooKeeperMain$MyWatcher@666c211a
Welcome to ZooKeeper!
2014-08-05 10:15:21,920 [myid:] - INFO  [main-SendThread(localhost:2181):ClientCnxn$SendThread@966] - Opening socket connection to server localhost/127.0.0.1:2181. Will not attempt to authenticate using SASL (unknown error)
2014-08-05 10:15:21,934 [myid:] - INFO  [main-SendThread(localhost:2181):ClientCnxn$SendThread@849] - Socket connection established to localhost/127.0.0.1:2181, initiating session
JLine support is enabled
2014-08-05 10:15:21,966 [myid:] - INFO  [main-SendThread(localhost:2181):ClientCnxn$SendThread@1207] - Session establishment complete on server localhost/127.0.0.1:2181, sessionid = 0x147a3e1246b0007, negotiated timeout = 30000
 
WATCHER::
 
WatchedEvent state:SyncConnected type:None path:null
[zk: localhost:2181(CONNECTED) 0] ls /
[hbase, hadoop-ha, admin, zookeeper, consumers, config, controller, storm, brokers, controller_epoch]
[zk: localhost:2181(CONNECTED) 1] ls /brokers
[topics, ids]
[zk: localhost:2181(CONNECTED) 2] ls /brokers/topics
[idoall_testTopic]
　　5、使用Eclipse来调用kafka的JAVA API来测试kafka的集群状态
　　　　1)消息生产端：Producertest.java
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package idoall.testkafka;
 
import java.util.Date;
import java.util.Properties;
import java.text.SimpleDateFormat;  
 
import kafka.javaapi.producer.Producer;
import kafka.producer.KeyedMessage;
import kafka.producer.ProducerConfig;
 
 
/**
* 消息生产端
* @author 迦壹
* @Time 2014-08-05
*/
public class Producertest {
     
     public static void main(String[] args) {
         Properties props = new Properties();
         props.put("zk.connect", "m1:2181,m2:2181,s1:2181,s2:2181");
         // serializer.class为消息的序列化类
         props.put("serializer.class", "kafka.serializer.StringEncoder");
         // 配置metadata.broker.list, 为了高可用, 最好配两个broker实例
         props.put("metadata.broker.list", "m1:9092,m2:9092,s1:9092,s2:9092");
         // 设置Partition类, 对队列进行合理的划分
         //props.put("partitioner.class", "idoall.testkafka.Partitionertest");
         // ACK机制, 消息发送需要kafka服务端确认
         props.put("request.required.acks", "1");
 
          props.put("num.partitions", "4");
         ProducerConfig config = new ProducerConfig(props);
         Producer<String, String> producer = new Producer<String, String>(config);
         for (int i = 0; i < 10; i++)
         {
           // KeyedMessage<K, V>
           // 　　K对应Partition Key的类型
           // 　　V对应消息本身的类型
//　　 topic: "test", key: "key", message: "message"
           SimpleDateFormat formatter = new SimpleDateFormat   ("yyyy年MM月dd日 HH:mm:ss SSS");      
           Date curDate = new Date(System.currentTimeMillis());//获取当前时间      
           String str = formatter.format(curDate);  
            
           String msg = "idoall.org" + i+"="+str;
           String key = i+"";
           producer.send(new KeyedMessage<String, String>("idoall_testTopic",key, msg));
         }
       }
}
　　　　2)消息消费端：Consumertest.java
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package idoall.testkafka;
 
import java.util.HashMap;
import java.util.List; 
import java.util.Map; 
import java.util.Properties; 
   
import kafka.consumer.ConsumerConfig; 
import kafka.consumer.ConsumerIterator; 
import kafka.consumer.KafkaStream; 
import kafka.javaapi.consumer.ConsumerConnector;
 
 
/**
* 消息消费端
* @author 迦壹
* @Time 2014-08-05
*/
public class Consumertest extends Thread{
      
     private final ConsumerConnector consumer; 
    private final String topic; 
 
    public static void main(String[] args) { 
      Consumertest consumerThread = new Consumertest("idoall_testTopic"); 
        consumerThread.start(); 
    } 
    public Consumertest(String topic) { 
        consumer =kafka.consumer.Consumer.createJavaConsumerConnector(createConsumerConfig()); 
        this.topic =topic; 
    } 
 
private static ConsumerConfig createConsumerConfig() { 
    Properties props = new Properties(); 
    // 设置zookeeper的链接地址
    props.put("zookeeper.connect","m1:2181,m2:2181,s1:2181,s2:2181"); 
    // 设置group id
    props.put("group.id", "1"); 
    // kafka的group 消费记录是保存在zookeeper上的, 但这个信息在zookeeper上不是实时更新的, 需要有个间隔时间更新
    props.put("auto.commit.interval.ms", "1000");
    props.put("zookeeper.session.timeout.ms","10000"); 
    return new ConsumerConfig(props); 
} 
 
public void run(){ 
     //设置Topic=>Thread Num映射关系, 构建具体的流
    Map<String,Integer> topickMap = new HashMap<String, Integer>(); 
    topickMap.put(topic, 1); 
    Map<String, List<KafkaStream<byte[],byte[]>>>  streamMap=consumer.createMessageStreams(topickMap); 
    KafkaStream<byte[],byte[]>stream = streamMap.get(topic).get(0); 
    ConsumerIterator<byte[],byte[]> it =stream.iterator(); 
    System.out.println("*********Results********"); 
    while(it.hasNext()){ 
        System.err.println("get data:" +new String(it.next().message())); 
        try { 
            Thread.sleep(1000); 
        } catch (InterruptedException e) { 
            e.printStackTrace(); 
        } 
    } 
} 
}
　　　　3)在Eclipse查看java代码效果，在这之前先在其中一台机器(我使用的s1)，开启消费者，同时观察eclipse和s1上的消费者是否都收到了消息。最后结果如下图：
----------两张图片之间的分隔线----------
 
　　　　可以看到，刚好10条信息，没有丢失。不过消息因为均衡的原因，并非是有序的，在Kafka只提供了分区内部的有序性，不能跨partition. 每个分区的有序性，结合按Key分partition的能力对大多应用都够用了。（如何按key进行分partition，在文章末尾提供的Eclpise代码中有个Partitionertest.java提供了一个Demo）
 
　　6、在命令行下打包java文件，测试kafka
　　　　1)修改工程目录中的pom.xml文件
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<project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
  xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
  <modelVersion>4.0.0</modelVersion>
  <groupId>idoall.testkafka</groupId>
  <artifactId>idoall.testkafka</artifactId>
  <version>0.0.1-SNAPSHOT</version>
  <packaging>jar</packaging>
  <name>idoall.testkafka</name>
  <url>http://maven.apache.org</url>
  <properties>
    <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
  </properties>
  <dependencies>
    <dependency>
      <groupId>junit</groupId>
      <artifactId>junit</artifactId>
      <version>3.8.1</version>
      <scope>test</scope>
    </dependency>
    <dependency>
      <groupId>log4j</groupId>
      <artifactId>log4j</artifactId>
      <version>1.2.14</version>
    </dependency>
    <dependency>
      <groupId>com.sksamuel.kafka</groupId>
      <artifactId>kafka_2.10</artifactId>
      <version>0.8.0-beta1</version>
    </dependency>
  </dependencies>
  <build> 
        <finalName>idoall.testkafka</finalName> 
        <plugins> 
            <plugin> 
                <groupId>org.apache.maven.plugins</groupId> 
                <artifactId>maven-compiler-plugin</artifactId> 
                <version>2.0.2</version> 
                <configuration> 
                    <source>1.5</source> 
                    <target>1.5</target> 
                    <encoding>UTF-8</encoding> 
                </configuration> 
            </plugin> 
            <plugin> 
                <artifactId>maven-assembly-plugin</artifactId> 
                <version>2.4</version> 
                <configuration> 
                    <descriptors> 
                        <descriptor>src/main/src.xml</descriptor> 
                    </descriptors> 
                    <descriptorRefs> 
                        <descriptorRef>jar-with-dependencies</descriptorRef> 
                    </descriptorRefs> 
                </configuration> 
                <executions> 
                    <execution> 
                        <id>make-assembly</id> <!-- this is used for inheritance merges --> 
                        <phase>package</phase> <!-- bind to the packaging phase --> 
                        <goals> 
                            <goal>single</goal> 
                        </goals> 
                    </execution> 
                </executions> 
            </plugin> 
        </plugins> 
    </build>
</project>
　　　　2)修改工程目录中的src/main/src.xml文件
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<?xml version="1.0" encoding="UTF-8"?>
<assembly xmlns="http://maven.apache.org/plugins/maven-assembly-plugin/assembly/1.1.0"
          xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
          xsi:schemaLocation="http://maven.apache.org/plugins/maven-assembly-plugin/assembly/1.1.0 http://maven.apache.org/xsd/assembly-1.1.0.xsd ">
    <id>jar-with-dependencies</id>
    <formats>
        <format>jar</format>
    </formats>
    <includeBaseDirectory>false</includeBaseDirectory>
    <dependencySets>
        <dependencySet>
            <unpack>false</unpack>
            <scope>runtime</scope>
        </dependencySet>
    </dependencySets>
    <fileSets>
        <fileSet>
            <directory>/lib</directory>
        </fileSet>
    </fileSets>
</assembly>
　　　　3)制作依赖包，在工程目录执行mvn package，得到idoall.testkafka-jar-with-dependencies.jar，下面是部分执行后的结果：
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Running idoall.testkafka.idoall.testkafka.AppTest
Tests run: 1, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.004 sec
 
Results :
 
Tests run: 1, Failures: 0, Errors: 0, Skipped: 0
 
[INFO]
[INFO] --- maven-jar-plugin:2.4:jar (default-jar) @ idoall.testkafka ---
[INFO] Building jar: /Users/lion/Documents/_my_project/java/idoall.testkafka/target/idoall.testkafka.jar
[INFO]
[INFO] --- maven-assembly-plugin:2.4:single (make-assembly) @ idoall.testkafka ---
[INFO] Reading assembly descriptor: src/main/src.xml
[WARNING] The assembly id jar-with-dependencies is used more than once.
[INFO] Building jar: /Users/lion/Documents/_my_project/java/idoall.testkafka/target/idoall.testkafka-jar-with-dependencies.jar
[INFO] Building jar: /Users/lion/Documents/_my_project/java/idoall.testkafka/target/idoall.testkafka-jar-with-dependencies.jar
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 9.074 s
[INFO] Finished at: 2014-08-05T12:22:47+08:00
[INFO] Final Memory: 63M/836M
[INFO] ------------------------------------------------------------------------
　　　　4)编译文件，进入到工程目录，执行命令
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3
liondeMacBook-Pro:idoall.testkafka lion$ pwd
/Users/lion/Documents/_my_project/java/idoall.testkafka
liondeMacBook-Pro:idoall.testkafka lion$ javac -classpath target/idoall.testkafka-jar-with-dependencies.jar -d . src/main/java/idoall/testkafka/*.java
　　　　5)执行编译后的文件。分别打开两个窗口，一个用来消费，一个用来生产。可以看到消费窗口可以正常显示消息。
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java -classpath .:target/idoall.testkafka-jar-with-dependencies.jar idoall.testkafka.Producertest
 
java -classpath .:target/idoall.testkafka-jar-with-dependencies.jar idoall.testkafka.Consumertest

----------两张图片之间的分隔线----------
 
　　五、FAQ
　　1、如果在创建主题时出现下面的错误 ，那就是启动的brokers的个数达不到你所指定的--replication-factor值：
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Error while executing topic command replication factor: 3 larger than available brokers: 1
kafka.admin.AdminOperationException: replication factor: 3 larger than available brokers: 1
        at kafka.admin.AdminUtils$.assignReplicasToBrokers(AdminUtils.scala:70)
        at kafka.admin.AdminUtils$.createTopic(AdminUtils.scala:155)
        at kafka.admin.TopicCommand$.createTopic(TopicCommand.scala:86)
        at kafka.admin.TopicCommand$.main(TopicCommand.scala:50)
        at kafka.admin.TopicCommand.main(TopicCommand.scala)
　　2、如果出现下面的错误，可以先启动kafka，再启动hadoop中的zkfc(DFSZKFailoverController)：
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Java HotSpot(TM) 64-Bit Server VM warning: INFO: os::commit_memory(0x00000000c0130000, 986513408, 0) failed; error='Cannot allocate memory' (errno=12)
#
# There is insufficient memory for the Java Runtime Environment to continue.
# Native memory allocation (malloc) failed to allocate 986513408 bytes for committing reserved memory.
# An error report file with more information is saved as:
# /home/hadoop/hs_err_pid13558.log
　　六、扩展阅读
 
　　文章中Eclipse工程文件的下载地址：http://pan.baidu.com/s/1i3kQEFz
 
---------------------------------------
博文作者：迦壹
转载声明：可以转载, 但必须以超链接形式标明文章原始出处和作者信息及版权声明，谢谢合作！
---------------------------------------

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