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你可能喜欢kafka2.9.2的伪分布式集群安装和demo(javaapi)测试
1、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
1.1、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。
1.2、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.kafka
1.3、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。
1.4、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.
2、kafka的官方网站在哪里?
http://kafka.apache.org/
3、在哪里?需要哪些组件的支持?
kafka2.9.2在下面的地址可以下载：
https://www.apache.org/dyn/closer.cgi?path=/kafka/0.8.1.1/kafka_2.9.2-0.8.1.1.tgz
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》
4、如何安装?
4.1、解压kafka_2.9.2-0.8.1.1.tgz
本文中解压到/home/hadoop目录下
root@m1:/home/hadoop/kafka_2.9.2-0.8.1.1# pwd
/home/hadoop/kafka_2.9.2-0.8.1.1
4.2、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：
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=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=
# 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=
############################# 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=
# The maximum size of a log segment file. When this size is reached a new log segment will be created.
log.segment.bytes=
# 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:.0.1:.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=m1:1,s1:1
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=1000000
4.3、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
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：
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 &
root@m1:/home/hadoop# [ 10:03:11,210] INFO Verifying properties (kafka.utils.VerifiableProperties)
[ 10:03:11,261] INFO Property advertised.host.name is overridden to m1 (kafka.utils.VerifiableProperties)
[ 10:03:11,261] INFO Property broker.id is overridden to 1 (kafka.utils.VerifiableProperties)
[ 10:03:11,264] INFO Property host.name is overridden to m1 (kafka.utils.VerifiableProperties)
[ 10:03:11,264] INFO Property log.cleaner.enable is overridden to false (kafka.utils.VerifiableProperties)
[ 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)
[ 10:03:11,265] INFO Property log.retention.check.interval.ms is overridden to 60000 (kafka.utils.VerifiableProperties)
[ 10:03:11,265] INFO Property log.retention.hours is overridden to 168 (kafka.utils.VerifiableProperties)
[ 10:03:11,265] INFO Property log.segment.bytes is overridden to
(kafka.utils.VerifiableProperties)
[ 10:03:11,265] INFO Property num.io.threads is overridden to 8 (kafka.utils.VerifiableProperties)
[ 10:03:11,266] INFO Property num.network.threads is overridden to 2 (kafka.utils.VerifiableProperties)
[ 10:03:11,266] INFO Property num.partitions is overridden to 2 (kafka.utils.VerifiableProperties)
[ 10:03:11,267] INFO Property port is overridden to 9092 (kafka.utils.VerifiableProperties)
[ 10:03:11,267] INFO Property socket.receive.buffer.bytes is overridden to 1048576 (kafka.utils.VerifiableProperties)
[ 10:03:11,268] INFO Property socket.request.max.bytes is overridden to
(kafka.utils.VerifiableProperties)
[ 10:03:11,268] INFO Property socket.send.buffer.bytes is overridden to 1048576 (kafka.utils.VerifiableProperties)
[ 10:03:11,268] INFO Property zookeeper.connect is overridden to m1:1,s1:1 (kafka.utils.VerifiableProperties)
[ 10:03:11,269] INFO Property zookeeper.connection.timeout.ms is overridden to 1000000 (kafka.utils.VerifiableProperties)
[ 10:03:11,302] INFO [Kafka Server 1], starting (kafka.server.KafkaServer)
[ 10:03:11,303] INFO [Kafka Server 1], Connecting to zookeeper on m1:1,s1:1 (kafka.server.KafkaServer)
[ 10:03:11,335] INFO Starting ZkClient event thread. (org.I0Itec.zkclient.ZkEventThread)
[ 10:03:11,348] INFO Client environment:zookeeper.version=3.3.3-1203054, built on 11/17/ GMT (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,348] INFO Client environment:host.name=m1 (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,349] INFO Client environment:java.version=1.7.0_65 (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,349] INFO Client environment:java.vendor=Oracle Corporation (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,349] INFO Client environment:java.home=/usr/lib/jvm/java-7-oracle/jre (org.apache.zookeeper.ZooKeeper)
[ 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)
[ 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)
[ 10:03:11,350] INFO Client environment:java.io.tmpdir=/tmp (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,350] INFO Client piler= (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,350] INFO Client environment:os.name=Linux (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,350] INFO Client environment:os.arch=amd64 (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,351] INFO Client environment:os.version=3.11.0-15-generic (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,351] INFO Client environment:user.name=root (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,351] INFO Client environment:user.home=/root (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,351] INFO Client environment:user.dir=/home/hadoop (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,352] INFO Initiating client connection, connectString=m1:1,s1:1 sessionTimeout=6000 watcher=org.I0Itec.zkclient.ZkClient@51f782b8 (org.apache.zookeeper.ZooKeeper)
[ 10:03:11,380] INFO Opening socket connection to server m2/192.168.1.51:2181 (org.apache.zookeeper.ClientCnxn)
[ 10:03:11,386] INFO Socket connection established to m2/192.168.1.51:2181, initiating session (org.apache.zookeeper.ClientCnxn)
[ 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)
[ 10:03:11,400] INFO zookeeper state changed (SyncConnected) (org.I0Itec.zkclient.ZkClient)
[ 10:03:11,652] INFO Loading log 'test-1' (kafka.log.LogManager)
[ 10:03:11,681] INFO Recovering unflushed segment 0 in log test-1. (kafka.log.Log)
[ 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.
[ 10:03:11,747] INFO Loading log 'idoall.org-0' (kafka.log.LogManager)
[ 10:03:11,748] INFO Recovering unflushed segment 0 in log idoall.org-0. (kafka.log.Log)
[ 10:03:11,754] INFO Completed load of log idoall.org-0 with log end offset 5 (kafka.log.Log)
[ 10:03:11,760] INFO Loading log 'test-0' (kafka.log.LogManager)
[ 10:03:11,765] INFO Recovering unflushed segment 0 in log test-0. (kafka.log.Log)
[ 10:03:11,777] INFO Completed load of log test-0 with log end offset 151 (kafka.log.Log)
[ 10:03:11,779] INFO Starting log cleanup with a period of 60000 ms. (kafka.log.LogManager)
[ 10:03:11,782] INFO Starting log flusher with a default period of 4775807 ms. (kafka.log.LogManager)
[ 10:03:11,800] INFO Awaiting socket connections on m1:9092. (kafka.network.Acceptor)
[ 10:03:11,802] INFO [Socket Server on Broker 1], Started (kafka.network.SocketServer)
[ 10:03:11,890] INFO Will not load MX4J, mx4j-tools.jar is not in the classpath (kafka.utils.Mx4jLoader$)
[ 10:03:11,919] INFO 1 successfully elected as leader (kafka.server.ZookeeperLeaderElector)
[ 10:03:12,359] INFO New leader is 1 (kafka.server.ZookeeperLeaderElector$LeaderChangeListener)
[ 10:03:12,387] INFO Registered broker 1 at path /brokers/ids/1 with address m1:9092. (kafka.utils.ZkUtils$)
[ 10:03:12,392] INFO [Kafka Server 1], started (kafka.server.KafkaServer)
[ 10:03:12,671] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall.org,0],[test,0],[test,1] (kafka.server.ReplicaFetcherManager)
[ 10:03:12,741] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall.org,0],[test,0],[test,1] (kafka.server.ReplicaFetcherManager)
[ 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)
[ 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)
[ 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)
4.4、测试kafka的状态
1)在m1上创建一个idoall_testTopic主题，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&.
[ 10:08:29,315] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall_testTopic,0] (kafka.server.ReplicaFetcherManager)
[ 10:08:29,334] INFO Completed load of log idoall_testTopic-0 with log end offset 0 (kafka.log.Log)
[ 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 -& , file.delete.delay.ms -& 60000, segment.bytes -& , flush.ms -& 4775807, delete.retention.ms -& , index.interval.bytes -& 4096, retention.bytes -& -1, cleanup.policy -& delete, segment.ms -& , max.message.bytes -& 1000012, flush.messages -& 4775807, min.cleanable.dirty.ratio -& 0.5, retention.ms -& }. (kafka.log.LogManager)
[ 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)
[ 10:08:29,415] INFO Completed load of log idoall_testTopic-1 with log end offset 0 (kafka.log.Log)
[ 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 -& , file.delete.delay.ms -& 60000, segment.bytes -& , flush.ms -& 4775807, delete.retention.ms -& , index.interval.bytes -& 4096, retention.bytes -& -1, cleanup.policy -& delete, segment.ms -& , max.message.bytes -& 1000012, flush.messages -& 4775807, min.cleanable.dirty.ratio -& 0.5, retention.ms -& }. (kafka.log.LogManager)
[ 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)
[ 10:08:29,430] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall_testTopic,1] (kafka.server.ReplicaFetcherManager)
[ 10:08:29,438] INFO Truncating log idoall_testTopic-1 to offset 0. (kafka.log.Log)
[ 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)
[ 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
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&
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
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
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&.
[ 10:38:30,862] INFO Completed load of log idoall-1 with log end offset 0 (kafka.log.Log)
[ 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 -& , file.delete.delay.ms -& 60000, segment.bytes -& , flush.ms -& 4775807, delete.retention.ms -& , index.interval.bytes -& 4096, retention.bytes -& -1, cleanup.policy -& delete, segment.ms -& , max.message.bytes -& 1000012, flush.messages -& 4775807, min.cleanable.dirty.ratio -& 0.5, retention.ms -& }. (kafka.log.LogManager)
[ 10:38:30,870] WARN Partition [idoall,1] on broker 1: No checkpointed highwatermark is found for partition [idoall,1] (kafka.cluster.Partition)
[ 10:38:30,878] INFO [ReplicaFetcherManager on broker 1] Removed fetcher for partitions [idoall,1] (kafka.server.ReplicaFetcherManager)
[ 10:38:30,880] INFO Truncating log idoall-1 to offset 0. (kafka.log.Log)
[ 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)
[ 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_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。
root@m1:/home/hadoop# /home/hadoop/zookeeper-3.4.5/bin/zkCli.sh
Connecting to localhost:2181
10:15:21,863 [myid:] - INFO [main:Environment@100] - Client environment:zookeeper.version=3.4.5-1392090, built on 09/30/ GMT
10:15:21,871 [myid:] - INFO [main:Environment@100] - Client environment:host.name=m1
10:15:21,871 [myid:] - INFO [main:Environment@100] - Client environment:java.version=1.7.0_65
10:15:21,872 [myid:] - INFO [main:Environment@100] - Client environment:java.vendor=Oracle Corporation
10:15:21,872 [myid:] - INFO [main:Environment@100] - Client environment:java.home=/usr/lib/jvm/java-7-oracle/jre
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
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
10:15:21,874 [myid:] - INFO [main:Environment@100] - Client environment:java.io.tmpdir=/tmp
10:15:21,874 [myid:] - INFO [main:Environment@100] - Client piler=
10:15:21,875 [myid:] - INFO [main:Environment@100] - Client environment:os.name=Linux
10:15:21,875 [myid:] - INFO [main:Environment@100] - Client environment:os.arch=amd64
10:15:21,876 [myid:] - INFO [main:Environment@100] - Client environment:os.version=3.11.0-15-generic
10:15:21,876 [myid:] - INFO [main:Environment@100] - Client environment:user.name=root
10:15:21,877 [myid:] - INFO [main:Environment@100] - Client environment:user.home=/root
10:15:21,878 [myid:] - INFO [main:Environment@100] - Client environment:user.dir=/home/hadoop
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!
10:15:21,920 [myid:] - INFO [main-SendThread(localhost:2181):ClientCnxn$SendThread@966] - Opening socket connection to server localhost/127.0.0.1:2181. Will not attempt to authenticate using SASL (unknown error)
10:15:21,934 [myid:] - INFO [main-SendThread(localhost:2181):ClientCnxn$SendThread@849] - Socket connection established to localhost/127.0.0.1:2181, initiating session
JLine support is enabled
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 = 0x147a3e, negotiated timeout = 30000
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]
4.5、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
package idoall.
import java.util.D
import java.util.P
import java.text.SimpleDateF
import kafka.javaapi.producer.P
import kafka.producer.KeyedM
import kafka.producer.ProducerC
* 消息生产端
* @author 迦壹
public class Producertest {
public static void main(String[] args) {
Properties props = new Properties();
props.put(&zk.connect&, &m1:1,s1:1&);
// 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&, &m1:2,s1:2&);
// 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 producer = new Producer(config);
for (int i = 0; i & 10; i++)
// KeyedMessage
// 　　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+&=&+
String key = i+&&;
producer.send(new KeyedMessage(&idoall_testTopic&,key, msg));
2)消息消费端：Consumertest.java
package idoall.
import java.util.HashM
import java.util.L
import java.util.M
import java.util.P
import kafka.consumer.ConsumerC
import kafka.consumer.ConsumerI
import kafka.consumer.KafkaS
import kafka.javaapi.consumer.ConsumerC
* 消息消费端
* @author 迦壹
public class Consumertest extends Thread{
private final ConsumerC
private final S
public static void main(String[] args) {
Consumertest consumerThread = new Consumertest(&idoall_testTopic&);
consumerThread.start();
public Consumertest(String topic) {
consumer =kafka.consumer.Consumer.createConsumerConnector(createConsumerConfig());
this.topic =
private static ConsumerConfig createConsumerConfig() {
Properties props = new Properties();
// 设置zookeeper的链接地址
props.put(&zookeeper.connect&,&m1:1,s1:1&);
// 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(&mit.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 topickMap = new HashMap();
topickMap.put(topic, 1);
Map&& streamMap=consumer.createMessageStreams(topickMap);
KafkaStreamstream = streamMap.get(topic).get(0);
ConsumerIterator it =stream.iterator();
System.out.println(&*********Results********&);
while(it.hasNext()){
System.err.println(&get data:& +new String(it.next().message()));
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：
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
4.6、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
idoall.testkafka
idoall.testkafka
0.0.1-SNAPSHOT
idoall.testkafka
http://maven.apache.org
com.sksamuel.kafka
kafka_2.10
0.8.0-beta1
idoall.testkafka
org.apache.maven.plugins
maven-compiler-plugin
maven-assembly-plugin
src/main/src.xml
jar-with-dependencies
make-assembly
2)修改工程目录中的src/main/src.xml文件
jar-with-dependencies
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：
Running idoall.testkafka.idoall.testkafka.AppTest
Tests run: 1, Failures: 0, Errors: 0, Skipped: 0, Time elapsed: 0.004 sec
Tests run: 1, Failures: 0, Errors: 0, Skipped: 0
[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] --- 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: T12:22:47+08:00
[INFO] Final Memory: 63M/836M
[INFO] ------------------------------------------------------------------------
4)编译文件，进入到工程目录，执行命令
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。
java -classpath .:target/idoall.testkafka-jar-with-dependencies.jar idoall.testkafka.Producertest
java -classpath .:target/idoall.testkafka-jar-with-dependencies.jar idoall.testkafka.Consumertest
5.1、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：
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)
5.2、如果出现下面的错误，可以先启动kafka，再启动hadoop中的zkfc(DFSZKFailoverController)：
Java HotSpot(TM) 64-Bit Server VM warning: INFO: os::commit_memory(0x408, 0) error='Cannot allocate memory' (errno=12)
# There is insufficient memory for the Java Runtime Environment to continue.
# Native memory allocation (malloc) failed to allocate
bytes for committing reserved memory.
# An error report file with more information is saved as:
# /home/hadoop/hs_err_pid13558.log
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container: s,
size: '1000,90',
display: 'inlay-fix'
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container: s,
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container: s,
size: '1000,90',
display: 'inlay-fix'
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container: s,
size: '1000,90',
display: 'inlay-fix'
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container: s,
size: '1000,90',
display: 'inlay-fix'