.首先:需要三台测试机器(由于zookeeper 的选举机制,官方推荐是3台,并且是奇数台机器,{1台机器多个端口也可以})
192.168.12.28
192.168.12.151
192.168.12.152
环境及版本
jdk : java version "1.7.0_79"
os : fedora --x86_64-22-3
zookeeper :3.4.6
kafka:2.11-0.9.0.0
storm:0.10.0
使用:连续加号(+++++)分隔配置文件内容和正文
1.搭建zookeeper集群
先到apache 的zookeeper 项目中下载包
先进入conf 目录 配置 zoo.cfg,如下
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# The number of milliseconds of each tick
tickTime=2000
# The number of ticks that the initial
# synchronization phase can take
initLimit=10
# The number of ticks that can pass between
# sending a request and getting an acknowledgement
syncLimit=5
# the directory where the snapshot is stored.
# do not use /tmp for storage, /tmp here is just
# example sakes.
dataDir=/usr/local/zookeeper-3.4.6/data
# the port at which the clients will connect
clientPort=2181
# the maximum number of client connections.
# increase this if you need to handle more clients
#这连接客户端包括(比如kafka。strom等连接,所以请注意这个连接数不要太小,导致部署失败,或者客户端连接失败)#maxClientCnxns=60
#
# 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=3
# Purge task interval in hours
# Set to "0" to disable auto purge feature192
#autopurge.purgeInterval=1
##这是zookeeper 机集群地址。第一个端口是集群之间通信的端口(监听端口,和通信端口和选举端口不能重复,否则报错地址已用),第二个是选举leader时使用的
server.1=192.168.12.28:2888:3888
server.2=192.168.12.151:2888:3888
server.3=192.168.12.152:2888:3888
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
按这个配置,配置3台测试机器
到bin 目录启动zookeeper 集群:
./zkServer.sh start
查看集群状态
./zkServer.sh status
mode:leader 说明他是leader 否则是follower
leader 挂掉后,集群会自动选举新的leader
在3台机器重复此操作
使用client 连接zookeeper集群(集群中启动的任意一台机器都可以)
./zkCli.sh --server192.168.12.28:2181
ls / 查看根目录
create /test this is test dir 创建目录
到此,zookeeper 集群搭建完毕
这是一写zookeeper 的配置信息
broker.id
|
整数,建议根据ip区分
|
|
log.dirs
|
kafka存放消息文件的路径,
|
默认/tmp/kafka-logs
|
port
|
broker用于接收producer消息的端口
|
|
zookeeper.connnect
|
zookeeper连接
|
格式为 ip1:port,ip2:port,ip3:port
|
message.max.bytes
|
单条消息的最大长度
|
|
num.network.threads
|
broker用于处理网络请求的线程数
|
如不配置默认为3,server.properties默认是2
|
num.io.threads
|
broker用于执行网络请求的IO线程数
|
如不配置默认为8,server.properties默认是2可适当增大,
|
queued.max.requests
|
排队等候IO线程执行的requests
|
默认为500
|
host.name
|
broker的hostname
|
默认null,建议写主机的ip,不然消费端不配置hosts会有麻烦
|
num.partitions
|
topic的默认分区数
|
默认1
|
log.retention.hours
|
消息被删除前保存多少小时
|
默认1周168小时
|
auto.create.topics.enable
|
是否可以程序自动创建Topic
|
默认true,建议false
|
default.replication.factor
|
消息备份数目
|
默认1不做复制,建议修改
|
num.replica.fetchers
|
用于复制leader消息到follower的IO线程数
|
默认1
|
2.搭建 kafka 集群
包地址:
tar -xzf kafka_2.11-0.9.0.0.tgz
修改 config/server.properties
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
# The id of the broker. This must be set to a unique integer for each broker.
##必须唯一
broker.id=0
############################# Socket Server Settings #############################
#客户端连接的时候请按照此地址连接, 同一个地址,不同表示方式会导致生产和消费 的使用异常
listeners=PLAINTEXT://192.168.12.28:9092
# The port the socket server listens on
##客户端连接kafka的端口
#port=9092
# Hostname the broker will bind to. If not set, the server will bind to all interfaces
#host.name=localhost
# 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
//这个不要设置到机器的临时目录,否则启动可能会报错
log.dirs=/usr/local/kafka_2.11-0.9.0.0/data
# 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
# 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.
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
##kafka 是基于 zookeeper 的,保存kafka的数据信息、配置,读取偏移等
zookeeper.connect=192.168.12.28:2181,192.168.12.151:2181,192.168.12.152:2181
# Timeout in ms for connecting to zookeeper
zookeeper.connection.timeout.ms=6000
把此配置应用到3台测试机,注意:broker.id不能唯一
进入 bin 目录
启动 kafka (后面的参数是kafka 的配置文件目录,启动失败会立即报错)
./kafka-server-start.sh ../config/server.properties
启动3台kafka集群
测试kafka集群:
先创建一个test主题,
./kafka-topics.sh --create --zookeeper 192.168.12.28:2181 --replication-factor 1 --partitions 1 --topic test
查看创建的主题信息
./kafka-topics.sh --zookeeper 192.168.12.28:2181 --describe --topic testtopic
====================================================================
Topic:testtopic PartitionCount:1 ReplicationFactor:1 Configs:
Topic: testtopic Partition: 0 Leader: 4 Replicas: 4 Isr: 4
====================================================================
Partition : 分区
L eader :负责读写指定分区的节点
Replicas : 复制该分区log的节点列表
Isr : "in-sync" replicas,当前活跃的副本列表(是一个子集),并且可能成为Leader
通过Kafka自带的bin/kafka-console-producer.sh和bin/kafka-console-consumer.sh脚本,来验证演示如果发布消息、消费消息。
在一个终端,启动Producer,并向我们上面创建的名称为testtopic的Topic中生产消息,执行如下脚本:
bin/kafka-console-producer.sh --broker-list 192.168.12.28:9092,192.168.12.151:9092,192.168.12.152:9092 --topic testtopic
在另一个终端,启动Consumer,并订阅我们上面创建的名称为testtopic5的Topic中生产的消息,执行如下脚本
bin/kafka-console-consumer.sh --zookeeper 192.168.12.28:2181,192.168.12.151:2181,192.168.12.152:2181 --from-beginning --topic testtopic
可以在Producer终端上输入字符串消息行,然后回车(一行一条数据),就可以在Consumer终端上看到消费者消费的消息内容。
也可以参考Kafka的Producer和Consumer的Java API,通过API编码的方式来实现消息生产和消费的处理逻辑。
到此,kafka集群搭建完毕(具体详细的参数配置请查看文档)
3.搭建storm 集群
tar -zxvf apache-storm-0.10.0.tar.gz
cd apache-storm-0.10.0/conf
修改配置 storm.yaml
1)storm 依赖 zookeeper
如果Zookeeper集群使用的不是默认端口,那么还需要storm.zookeeper.port选项。
2) storm.local.dir: Nimbus和Supervisor进程用于存储少量状态,如jars、confs等的本地磁盘目录,需要提前创建该目录并给以足够的访问权限。然后在storm.yaml中配置该目录,如:
storm.local.dir: "/home/admin/storm/workdir"
3) java.library.path: Storm使用的本地库(ZMQ和JZMQ)加载路径,默认为”/usr/local/lib:/opt/local/lib:/usr/lib”,一般来说ZMQ和JZMQ默认安装在/usr/local/lib 下,因此不需要配置即可。
4) nimbus.host: Storm集群Nimbus机器地址(存在单点问题),各个Supervisor工作节点需要知道哪个机器是Nimbus,以便下载Topologies的jars、confs等文件
5) supervisor.slots.ports: 对于每个Supervisor工作节点,需要配置该工作节点可以运行的worker数量。每个worker占用一个单独的端口用于接收消息,该配置选项即用于定义哪些端口是可被worker使用的。默认情况下,每个节点上可运行4个workers,分别在6700、6701、6702和6703端口,如:supervisor.slots.ports:- 6700- 6701- 6702- 6703
+++++++++++++++++++++++++++++++++++++++++++++++
########### These MUST be filled in for a storm configuration
storm.zookeeper.servers:
- "192.168.12.28"
- "192.168.12.151"
- "192.168.12.152"
nimbus.host: "192.168.12.28"
storm.local.dir: "/usr/local/apache-storm-0.10.0/workdata"
supervisor.slots.ports:
- 6700
- 6701
#
#
# ##### These may optionally be filled in:
#
## List of custom serializations
# topology.kryo.register:
# - org.mycompany.MyType
# - org.mycompany.MyType2: org.mycompany.MyType2Serializer
#
## List of custom kryo decorators
# topology.kryo.decorators:
# - org.mycompany.MyDecorator
#
## Locations of the drpc servers
# drpc.servers:
# - "server1"
# - "server2"
## Metrics Consumers
# topology.metrics.consumer.register:
# - class: "backtype.storm.metric.LoggingMetricsConsumer"
# parallelism.hint: 1
# - class: "org.mycompany.MyMetricsConsumer"
# parallelism.hint: 1
# argument:
# - endpoint: "metrics-collector.mycompany.org"
+++++++++++++++++++++++++++++++++++++++++++++++++++++++++
三台测试机的配置相同即可,现在启动storm
cd ../bin/
./storm nimbus 启动主节点//指定的主节点机器启动
./storm supervisor 启动工作子节点
./storm ui 启动storm 自带的监控UI, 使用host:8080访问
自此,storm 集群搭建完毕
4.kafka + storm 继承
刚发现这竟然没写,周末补
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