Kafka研究【一】：bring up环境

kafka是干什么的，有和特性，我这里就不多说，详情自己研究官方文档。

0. 背景介绍

我需要在三台机器上分别部署kafka broker的实例，构建成一个集群。
kafka的broker集群，是基于zookeeper作为协调器或者资源同步管理器的，主要是记录High Level Offset标记信息的。 另外，zookeeper还用作broker的选主以及partition的选主。
三台机器上分别安装zookeeper和kafka。

10.90.7.2　　　　Linux localhost.localdomain 2.6.-.el5 # SMP Fri Jul  :: EDT  x86_64 x86_64 x86_64 GNU/Linux
10.90.2.101 　　Linux bogon 3.10.-.el7.x86_64 # SMP Thu Jan  :: EST  x86_64 x86_64 x86_64 GNU/Linux
10.90.2.102    Linux localhost.localdomain 3.10.-.el7.x86_64 # SMP Thu Jan  :: EST  x86_64 x86_64 x86_64 GNU/Linux

1. 软件下载
下载kafka 1.0.1版本
https://www.apache.org/dyn/closer.cgi?path=/kafka/1.0.1/kafka_2.11-1.0.1.tgz
遵循我一贯的原则，为了生产环境的稳定性，不会去首先使用最新版本，当前这个是次新版本。最新的版本是1.1.0，Released March 28, 2018。
下载zookeeper 3.4.9
https://archive.apache.org/dist/zookeeper/zookeeper-3.4.9/zookeeper-3.4.9.tar.gz
这个是当前稳定运行的版本，是次新版，最新的版本，有几个alpha和beta的，版本好最高达到3.5.4了。

2. 软件安装
2.1 zookeeper安装，三台服务器构建最小集群，保证paxos的选主算法正常运行。配置很简单，下面就只是将配置数据贴出来。

# The number of milliseconds of each tick
tickTime=
# The number of ticks that the initial
# synchronization phase can take
initLimit=
# The number of ticks that can pass between
# sending a request and getting an acknowledgement
syncLimit=
# the directory where the snapshot is stored.
# do not use /tmp for storage, /tmp here is just
# example sakes.
dataDir=/opt/shihuc/zookeeper-3.4./zkData/data
dataLogDir=/opt/shihuc/zookeeper-3.4./zkData/logs
# the port at which the clients will connect
clientPort=
# the maximum number of client connections.
# increase this if you need to handle more clients
maxClientCnxns=
#
# 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=
# Purge task interval in hours
# Set to "" to disable auto purge feature
autopurge.purgeInterval=

server.=10.90.7.2::
server.=10.90.2.101::
server.=10.90.2.102::

注意，在每一台zookeeper所在的机器对应配置文件dataDir所在的路径下创建myid，myid文件存放zookeeper服务器的编号（正如配置文件中server.x中的x，本案例中x是1,2,3）。

启动zookeeper，查看启动脚本的帮助信息：

[root@localhost bin]# ./zkServer.sh
ZooKeeper JMX enabled by default
Using config: /opt/shihuc/zookeeper-3.4./bin/../conf/zoo.cfg
Usage: ./zkServer.sh {start|start-foreground|stop|restart|status|upgrade|print-cmd}

正常启动操作（三台机器，都做相同操作）：

[root@localhost bin]# ./zkServer.sh start
ZooKeeper JMX enabled by default
Using config: /opt/shihuc/zookeeper-3.4./bin/../conf/zoo.cfg
Starting zookeeper ... STARTED

检查几个zookeeper的状态：

[root@localhost bin]# ./zkServer.sh status   #---10.90.7.2
ZooKeeper JMX enabled by default
Using config: /opt/shihuc/zookeeper-3.4./bin/../conf/zoo.cfg
Mode: leader
[root@localhost bin]# ./zkServer.sh status   #---10.90.2.101
ZooKeeper JMX enabled by default
Using config: /opt/shihuc/zookeeper-3.4./bin/../conf/zoo.cfg
Mode: follower
[root@localhost bin]# ./zkServer.sh status   #---10.90.2.102
ZooKeeper JMX enabled by default
Using config: /opt/shihuc/zookeeper-3.4./bin/../conf/zoo.cfg
Mode: follower

2.2 安装kafka

安装很简单，直接将下载的kafka软件的包解压即可，然后配置一下config下面的server.properties文件，主要是修改log路径以及zookeeper的监听地址。然后运行bin下面的kafka-server-start.sh即可。

配置信息：

# 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.
broker.id=0

############################# Socket Server Settings #############################

# The address the socket server listens on. It will get the value returned from
# java.net.InetAddress.getCanonicalHostName() if not configured.
#   FORMAT:
#     listeners = listener_name://host_name:port
#   EXAMPLE:
#     listeners = PLAINTEXT://your.host.name:9092
listeners=PLAINTEXT://:9092

# Hostname and port the broker will advertise to producers and consumers. If not set,
# it uses the value for "listeners" if configured.  Otherwise, it will use the value
# returned from java.net.InetAddress.getCanonicalHostName().
#advertised.listeners=PLAINTEXT://your.host.name:9092

# Maps listener names to security protocols, the default is for them to be the same. See the config documentation for more details
#listener.security.protocol.map=PLAINTEXT:PLAINTEXT,SSL:SSL,SASL_PLAINTEXT:SASL_PLAINTEXT,SASL_SSL:SASL_SSL

# The number of threads that the server uses for receiving requests from the network and sending responses to the network
num.network.threads=3

# The number of threads that the server uses for processing requests, which may include disk I/O
num.io.threads=8

# The send buffer (SO_SNDBUF) used by the socket server
socket.send.buffer.bytes=

# The receive buffer (SO_RCVBUF) used by the socket server
socket.receive.buffer.bytes=

# 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
log.dirs=/opt/shihuc/kafka_2.11-1.0.1/logDir

# 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=

# 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=

############################# Internal Topic Settings  #############################
# The replication factor for the group metadata internal topics "__consumer_offsets" and "__transaction_state"
# For anything other than development testing, a value greater than  is recommended for to ensure availability such as .
offsets.topic.replication.factor=
transaction.state.log.replication.factor=
transaction.state.log.min.isr=

############################# 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:
#    . Durability: Unflushed data may be lost if you are not using replication.
#    . 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.
#    . 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=

# The maximum amount of time a message can sit in a log before we force a flush
#log.flush.interval.ms=

############################# 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 due to age
log.retention.hours=

# A size-based retention policy for logs. Segments are pruned from the log unless the remaining
# segments drop below log.retention.bytes. Functions independently of log.retention.hours.
#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=

############################# 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=10.90.7.2:2181,10.90.2.101:2181,10.90.2.102:2181

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

############################# Group Coordinator Settings #############################

# The following configuration specifies the time, in milliseconds, that the GroupCoordinator will delay the initial consumer rebalance.
# The rebalance will be further delayed by the value of group.initial.rebalance.delay.ms as new members join the group, up to a maximum of max.poll.interval.ms.
# The default value for this is  seconds.
# We override this to  here as it makes for a better out-of-the-box experience for development and testing.
# However, in production environments the default value of  seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
group.initial.rebalance.delay.ms=

启动kafka服务：

[root@localhost bin]# nohup ./kafka-server-start.sh ../config/server.properties &

对三台机器都做broker的启动操作，遇到下面的问题：

[-- ::,] INFO [TransactionCoordinator id=] Startup complete. (kafka.coordinator.transaction.TransactionCoordinator)
[-- ::,] INFO Creating /brokers/ids/ (is it secure? false) (kafka.utils.ZKCheckedEphemeral)
[-- ::,] INFO Result of znode creation is: NODEEXISTS (kafka.utils.ZKCheckedEphemeral)
[2018-06-12 14:22:39,022] FATAL [KafkaServer id=0] Fatal error during KafkaServer startup. Prepare to shutdown (kafka.server.KafkaServer)
java.lang.RuntimeException: A broker is already registered on the path /brokers/ids/0. This probably indicates that you either have configured a brokerid that is already in use, or else you have shutdown this broker and restarted it fas
ter than the zookeeper timeout so it appears to be re-registering.
        at kafka.utils.ZkUtils.registerBrokerInZk(ZkUtils.scala:440)
        at kafka.utils.ZkUtils.registerBrokerInZk(ZkUtils.scala:426)
        at kafka.server.KafkaHealthcheck.register(KafkaHealthcheck.scala:73)
        at kafka.server.KafkaHealthcheck.startup(KafkaHealthcheck.scala:53)
        at kafka.server.KafkaServer.startup(KafkaServer.scala:287)
        at kafka.server.KafkaServerStartable.startup(KafkaServerStartable.scala:38)
        at kafka.Kafka$.main(Kafka.scala:92)
        at kafka.Kafka.main(Kafka.scala)
[-- ::,] INFO [KafkaServer id=] shutting down (kafka.server.KafkaServer)
[-- ::,] INFO [SocketServer brokerId=] Stopping socket server request processors (kafka.network.SocketServer)
[-- ::,] INFO [SocketServer brokerId=] Stopped socket server request processors (kafka.network.SocketServer)
[-- ::,] INFO [Kafka Request Handler on Broker ], shutting down (kafka.server.KafkaRequestHandlerPool)
[-- ::,] INFO [Kafka Request Handler on Broker ], shut down completely (kafka.server.KafkaRequestHandlerPool)
[-- ::,] INFO [KafkaApi-] Shutdown complete. (kafka.server.KafkaApis)
[-- ::,] INFO [ExpirationReaper--topic]: Shutting down (kafka.server.DelayedOperationPurgatory$ExpiredOperationReaper)
[-- ::,] INFO [ExpirationReaper--topic]: Stopped (kafka.server.DelayedOperationPurgatory$ExpiredOperationReaper)
[-- ::,] INFO [ExpirationReaper--topic]: Shutdown completed (kafka.server.DelayedOperationPurgatory$ExpiredOperationReaper)
[-- ::,] INFO [TransactionCoordinator id=] Shutting down. (kafka.coordinator.transaction.TransactionCoordinator)
[-- ::,] INFO [ProducerId Manager ]: Shutdown complete: last producerId assigned  (kafka.coordinator.transaction.ProducerIdManager)
[-- ::,] INFO [Transaction State Manager ]: Shutdown complete (kafka.coordinator.transaction.TransactionStateManager)
[-- ::,] INFO [Transaction Marker Channel Manager ]: Shutting down (kafka.coordinator.transaction.TransactionMarkerChannelManager)

错误原因是server.properties文件中的broker.id的值，在集群环境下重复了，即，一个kafka的集群环境下，broker.id的值是不能重复的，必须唯一。就算kafka服务在不同机器上。

3. 验证环境

3.1 创建一个topic

在10.90.2.102上操作：

[root@localhost bin]# ./kafka-topics.sh --create --zookeeper 10.90.7.2:,10.90.2.101:,10.90.2.102: --replication-factor  --partitions  --topic first
Created topic "first".

同一台机器上重复操作：

[root@localhost bin]# ./kafka-topics.sh --create --zookeeper 10.90.7.2:,10.90.2.101:,10.90.2.102: --replication-factor  --partitions  --topic first
Error while executing topic command : Topic 'first' already exists.
[-- ::,] ERROR org.apache.kafka.common.errors.TopicExistsException: Topic 'first' already exists.
 (kafka.admin.TopicCommand$)

在10.90.7.2机器上创建相同的topic：

[root@localhost bin]# ./kafka-topics.sh --create --zookeeper 10.90.7.2:,10.90.2.101:,10.90.2.102: --replication-factor  --partitions  --topic first
Error while executing topic command : Topic 'first' already exists.
[-- ::,] ERROR org.apache.kafka.common.errors.TopicExistsException: Topic 'first' already exists.
 (kafka.admin.TopicCommand$)

同一个名称的topic，在一个kafka的集群环境下，不能重复创建。

3.2 创建一个kafka的生产者

在10.90.2.101上操作：

[root@localhost bin]# ./kafka-console-producer.sh --broker-list 10.90.7.2:,10.90.2.101:,10.90.2.102: --topic first
>
[-- ::,] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id  : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient)
[-- ::,] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id  : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient)
[-- ::,] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id  : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient)
[-- ::,] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id  : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient)
[-- ::,] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id  : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient)
[-- ::,] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id  : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient)
[-- ::,] WARN [Producer clientId=console-producer] Error while fetching metadata with correlation id  : {first=LEADER_NOT_AVAILABLE} (org.apache.kafka.clients.NetworkClient)

经过反复测试验证环境配置信息，最终参考了他人的经验，是kafka的server.properties的配置错误。主要是下面的内容配置有问题：

listeners=PLAINTEXT://:9092

将这句注释掉，然后在配置文件中添加下面的两行配置，指明当前broker的地址：

port=
host.name=10.90.7.2 #依据具体的服务器，配置相应的服务器的IP地址即可。

修改后，再次重启kafka服务，重新在某台服务器上启动消息生产者服务，例如在10.90.2.102上：

[root@localhost bin]# ./kafka-console-producer.sh --broker-list 10.90.7.2:,10.90.2.101:,10.90.2.102: --topic first
>hello
>good
>

然后在另外一台服务器上，启动消息消费者，例如在10.90.7.2上：

[root@localhost bin]# ./kafka-console-consumer.sh --bootstrap-server 10.90.7.2:,10.90.2.101:,10.90.2.102: --topic
hello
good

到此为止，kafka生产者消费者，在控制台下消息收发正常，说明kafka的环境配置成功。

3.3 查看不同的topic下的broker信息

[root@localhost bin]# ./kafka-topics.sh --describe --zookeeper 10.90.7.2:,10.90.2.101:,10.90.2.102: --topic first
Topic:first     PartitionCount:        ReplicationFactor:     Configs:
        Topic: first    Partition:     Leader:        Replicas: ,, Isr: ,,
[root@localhost bin]# ./kafka-topics.sh --describe --zookeeper 10.90.7.2:,10.90.2.101:,10.90.2.102: --topic second
Topic:second    PartitionCount:        ReplicationFactor:     Configs:
        Topic: second   Partition:     Leader:        Replicas: ,, Isr: ,,
        Topic: second   Partition:     Leader:        Replicas: ,, Isr: ,,

这是输出解释。第一行给出了各个分区的概况，分区有几个就有几行分区详细信息介绍。（我创建了两个topic，一个是first，只有一个分区；一个是second，两个分区）

Leader　　　是负责当前分区的所有读写请求。每个节点都将领导一个随机选择的分区。

Replicas 　　是节点列表，复制分区日志，不管他们是不是Leader或者不管它们是否还活着。

Isr 　　　　   是in-sync的集合。这是Replicas列表当前还活着的子集。

总体来说，Kafka的环境构建，还是比较容易的，配置信息，相对来说，也比较容易理解。到此，环境的bring up工作完美收工。