大数据处理框架之:Storm + Kafka + zookeeper 集群

ゞ浴缸里的玫瑰 2022-04-17 05:21 274阅读 0赞

# Storm kafka zookeeper 集群 #

我们知道storm的作用主要是进行流式计算，对于源源不断的均匀数据流流入处理是非常有效的，而现实生活中大部分场景并不是均匀的数据流，而是时而多时而少的数据流入，这种情况下显然用批量处理是不合适的，如果使用storm做实时计算的话可能因为数据拥堵而导致服务器挂掉，应对这种情况，使用kafka作为消息队列是非常合适的选择，kafka可以将不均匀的数据转换成均匀的消息流，从而和storm比较完善的结合，这样才可以实现稳定的流式计算。  
　　storm和kafka结合，实质上无非是之前我们说过的计算模式结合起来，就是数据先进入kafka生产者，然后storm作为消费者进行消费，最后将消费后的数据输出或者保存到文件、数据库、分布式存储等等，具体框图如下：![在这里插入图片描述][734555-20160318155456521-191268812.png]  
　　这张图片摘自博客地址：[http://www.cnblogs.com/tovin/p/3974417.html][http_www.cnblogs.com_tovin_p_3974417.html] 在此感谢作者的奉献

## 一、环境安装前准备： ##

（1）准备三台机器：操作系统centos7  
（2）JDK: jdk-8u191-linux-x64.tar.gz 可以到官网下载: wget [https://download.oracle.com/otn-pub/java/jdk/8u191-b12/2787e4a523244c269598db4e85c51e0c/jdk-8u191-linux-x64.tar.gz][https_download.oracle.com_otn-pub_java_jdk_8u191-b12_2787e4a523244c269598db4e85c51e0c_jdk-8u191-linux-x64.tar.gz]  
（3）zookeeper：zookeeper-3.4.13 wget [http://archive.apache.org/dist/zookeeper/zookeeper-3.4.13/zookeeper-3.4.13.tar.gz][http_archive.apache.org_dist_zookeeper_zookeeper-3.4.13_zookeeper-3.4.13.tar.gz]  
（4）kafka: kafka\_2.11-2.0.0 wget [http://mirrors.hust.edu.cn/apache/kafka/2.0.0/kafka\_2.11-2.0.0.tgz][http_mirrors.hust.edu.cn_apache_kafka_2.0.0_kafka_2.11-2.0.0.tgz]  
（5）storm:apache-storm-1.2.2.tar.gz wget [http://www.apache.org/dist/storm/apache-storm-1.2.2/apache-storm-1.2.2.tar.gz][http_www.apache.org_dist_storm_apache-storm-1.2.2_apache-storm-1.2.2.tar.gz]  
（6）进行解压 配置环境变量 vi /ect/profile

# JAVA_HOME
    export JAVA_HOME=/usr/local/java/jdk1.8.0_191
    export CLASSPATH=.:$JAVA_HOME/jre/lib/rt.jar:$JAVA_HOME/lib/dt.jar:$JAVA_HOME/lib/tools.jar
    export ZOOKEEPER_HOME=/usr/local/java/zookeeper-3.4.13
    export PATH=$PATH:$ZOOKEEPER_HOME/bin/:$JAVA_HOME/bin
    #KAFKA_HOME
    export KAFKA_HOME=/usr/local/java/kafka_2.11-2.0.0
    export PATH=$PATH:$KAFKA_HOME/bin
    # STORM_HOME
    export STORM_HOME=/usr/local/java/apache-storm-1.2.2
    export PATH=.:${ JAVA_HOME}/bin:${ ZK_HOME}/bin:${ STORM_HOME}/bin:$PATH

环境变量需要重启生效 source /ect/profile

## 二、zookeeper集群安装(三台机器上都需要安装) ##

（1）tar -zxvf zookeeper-3.4.13.tar.gz  
（2）cd /usr/local/java/zookeeper-3.4.13/conf 进入解压后zk conf目录  
（3）mv zoo\_sample.cfg zoo.cfg 拷贝文件 为 zoo.cfg  
（4）**配置zoo.cfg**

# 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/java/zookeeper-3.4.13/dateDir
    dataLogDir=/usr/local/java/zookeeper-3.4.13/logs
    # 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
    #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 feature
    #autopurge.purgeInterval=1
    server.1 = 0.0.0.0:2888:3888
    server.2 = 192.168.164.134:2888:3888
    server.3 = 192.168.164.135:2888:3888

（5）创建 mkdir dataDir=/usr/local/java/zookeeper-3.4.13/dateDir  
（6）创建 mkdir dataLogDir=/usr/local/java/zookeeper-3.4.13/logs  
（7）创建 echo “1” >/usr/local/java/zookeeper-3.4.13/dateDir/myid  
（8）需要把zookeeper-3.4.13 这个目录拷贝到其他两台机器上 scp -r zookeeper-3.4.13 [root@192.168.164.134][root_192.168.164.134]:/usr/local/java/ 等待输入密码即可  
（9）server.2 和 server.3 相对应机器 /usr/local/java/zookeeper-3.4.13/dateDir/myid 改成 2 和 3  
虚拟机 互相拷贝，新增IP ，输入密码  
ssh -o StrictHostKeyChecking=no [root@192.168.164.133][root_192.168.164.133]  
（10）启动 ./bin/zkServer.sh start 三台机器都需要启动 启动过程会报错，等待三台都启动成功后  
./zkServer.sh status  
**注意：查看zookeeper集群的状态，出现Mode:follower或是Mode:leader则代表成功**

[root@hadoop bin]# ./zkServer.sh status
    ZooKeeper JMX enabled by default
    Using config: /usr/local/java/zookeeper-3.4.13/bin/../conf/zoo.cfg
    Mode: follower
    [root@hadoop bin]# 
    
    [root@hadoop bin]# ./zkServer.sh status
    ZooKeeper JMX enabled by default
    Using config: /usr/local/java/zookeeper-3.4.13/bin/../conf/zoo.cfg
    Mode: leader
    [root@hadoop bin]# 
    
    [root@hadoop bin]# ./zkServer.sh status
    ZooKeeper JMX enabled by default
    Using config: /usr/local/java/zookeeper-3.4.13/bin/../conf/zoo.cfg
    Mode: follower
    [root@hadoop bin]#

## 三、kafka集群安装（三台机器上都需要安装） ##

（1）tar -zxvf kafka\_2.11-2.0.0.tgz  
（2）cd /usr/local/java/kafka\_2.11-2.0.0/config 进入解压后 config 目录  
（3）vi server.properties 进行配置  
（4）**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.
    broker.id=1
    
    ############################# 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=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 separated list of directories under which to store log files
    log.dirs=/usr/local/java/kafka_2.11-2.0.0/logs
    
    # The default number of log partitions per topic. More partitions allow greater
    # parallelism for consumption, but this will also result in more files across
    # the brokers.
    num.partitions=1
    
    # 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
    
    ############################# 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 1 is recommended for to ensure availability such as 3.
    offsets.topic.replication.factor=1
    transaction.state.log.replication.factor=1
    transaction.state.log.min.isr=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 excessive 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 due to age
    log.retention.hours=168
    
    # 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=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
    
    ############################# 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=hadoop1:2181,hadoop2:2181,hadoop3:2181/kafka
    
    # Timeout in ms for connecting to zookeeper
    zookeeper.connection.timeout.ms=6000
    
    
    ############################# 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 3 seconds.
    # We override this to 0 here as it makes for a better out-of-the-box experience for development and testing.
    # However, in production environments the default value of 3 seconds is more suitable as this will help to avoid unnecessary, and potentially expensive, rebalances during application startup.
    group.initial.rebalance.delay.ms=0

（5）创建 mkdir log.dirs=/usr/local/java/kafka\_2.11-2.0.0/logs  
（6）需要把kafka\_2.11-2.0.0 这个目录拷贝到其他两台机器上 scp -r kafka\_2.11-2.0.0 [root@192.168.164.134][root_192.168.164.134]:/usr/local/java/ 等待输入密码即可  
（7）要修改其他两台机器 server.properties **broker.id=2 和 broker.id=3**  
ssh -o StrictHostKeyChecking=no [root@192.168.164.133][root_192.168.164.133]  
（8）启动

[root@hadoop java]# cd kafka_2.11-2.0.0
    [root@hadoop kafka_2.11-2.0.0]# cd bin/
    [root@hadoop bin]#  ./bin/kafka-server-start.sh -daemon ./config/server.properties

## 四、storm集群安装（三台机器上都需要安装） ##

（1）tar -zxvf apache-storm-1.2.2.tar.gz  
（2）cd /usr/local/java/apache-storm-1.2.2/conf 进入解压后conf 目录  
（3）vi storm.yaml 进行配置  
（4）**storm.yaml**

# 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.
    
    ########### These MUST be filled in for a storm configuration
     storm.zookeeper.servers:
         - "hadoop1"
         - "hadoop2"
         - "hadoop3"
     storm.zookeeper.port: 2181
     nimbus.seeds: ["hadoop1"]
     storm.local.dir: "/usr/local/java/apache-storm-1.2.2/logs"
     supervisor.slots.ports:
         - 6700
         - 6701
         - 6702
         - 6703
    # nimbus.seeds: ["host1", "host2", "host3"]
    # 
    # 
    # ##### 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
    ## max.retain.metric.tuples
    ## - task queue will be unbounded when max.retain.metric.tuples is equal or less than 0.
    ## whitelist / blacklist
    ## - when none of configuration for metric filter are specified, it'll be treated as 'pass all'.
    ## - you need to specify either whitelist or blacklist, or none of them. You can't specify both of them.
    ## - you can specify multiple whitelist / blacklist with regular expression
    ## expandMapType: expand metric with map type as value to multiple metrics
    ## - set to true when you would like to apply filter to expanded metrics
    ## - default value is false which is backward compatible value
    ## metricNameSeparator: separator between origin metric name and key of entry from map
    ## - only effective when expandMapType is set to true
    # topology.metrics.consumer.register:
    #   - class: "org.apache.storm.metric.LoggingMetricsConsumer"
    #     max.retain.metric.tuples: 100
    #     parallelism.hint: 1
    #   - class: "org.mycompany.MyMetricsConsumer"
    #     max.retain.metric.tuples: 100
    #     whitelist:
    #       - "execute.*"
    #       - "^__complete-latency$"
    #     parallelism.hint: 1
    #     argument:
    #       - endpoint: "metrics-collector.mycompany.org"
    #     expandMapType: true
    #     metricNameSeparator: "."
    
    ## Cluster Metrics Consumers
    # storm.cluster.metrics.consumer.register:
    #   - class: "org.apache.storm.metric.LoggingClusterMetricsConsumer"
    #   - class: "org.mycompany.MyMetricsConsumer"
    #     argument:
    #       - endpoint: "metrics-collector.mycompany.org"
    #
    # storm.cluster.metrics.consumer.publish.interval.secs: 60
    
    # Event Logger
    # topology.event.logger.register:
    #   - class: "org.apache.storm.metric.FileBasedEventLogger"
    #   - class: "org.mycompany.MyEventLogger"
    #     arguments:
    #       endpoint: "event-logger.mycompany.org"
    
    # Metrics v2 configuration (optional)
    #storm.metrics.reporters:
    #  # Graphite Reporter
    #  - class: "org.apache.storm.metrics2.reporters.GraphiteStormReporter"
    #    daemons:
    #        - "supervisor"
    #        - "nimbus"
    #        - "worker"
    #    report.period: 60
    #    report.period.units: "SECONDS"
    #    graphite.host: "localhost"
    #    graphite.port: 2003
    #
    #  # Console Reporter
    #  - class: "org.apache.storm.metrics2.reporters.ConsoleStormReporter"
    #    daemons:
    #        - "worker"
    #    report.period: 10
    #    report.period.units: "SECONDS"
    #    filter:
    #        class: "org.apache.storm.metrics2.filters.RegexFilter"
    #        expression: ".*my_component.*emitted.*"

（5）创建 mkdir /usr/local/java/apache-storm-1.2.2/logs  
（6）需要把apache-storm-1.2.2 这个目录拷贝到其他两台机器上 scp -r kafka\_2.11-2.0.0 [root@192.168.164.134][root_192.168.164.134]:/usr/local/java/ 等待输入密码即可  
（7）启动 storm

#在192.168.164.133  启动 
    [root@hadoop apache-storm-1.2.2]# cd bin/
    [root@hadoop bin]# ./storm nimbus >/dev/null 2>&1 &
    
    [root@hadoop apache-storm-1.2.2]# cd bin/
    [root@hadoop bin]# ./storm ui &

在其他两台机器启动

#在192.168.164.134, 192.168.164.135 启动 
    [root@hadoop apache-storm-1.2.2]# cd bin/
    [root@hadoop bin]# ./storm supervisor >/dev/null 2>&1 &

（8）访问 [http://192.168.164.133:8080/][http_192.168.164.133_8080]  
![在这里插入图片描述][watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2xpcnVpemk_size_16_color_FFFFFF_t_70]

## 五、虚拟机 centos7 一些注意 ##

（1）修改了hosts 需要重启 service network restart

127.0.0.1   hadoop1
    192.168.164.134 hadoop2
    192.168.164.135 hadoop3

（2）防火墙配置

1、通过systemctl status firewalld查看firewalld状态，发现当前是dead状态，即防火墙未开启
    2、通过systemctl start firewalld开启防火墙，没有任何提示即开启成功。
    3、再次通过systemctl status firewalld查看firewalld状态，显示running即已开启了
    4、systemctl stop firewalld 关闭防火墙
    5、开启以下端口
    			 firewall-cmd --zone=public --add-port=2888/tcp --permanent
    			 firewall-cmd --zone=public --add-port=3888/tcp --permanent
     		 	 firewall-cmd --zone=public --add-port=2181/tcp --permanent
     		 	 firewall-cmd --zone=public --add-port=8080/tcp --permanent
     		 	  firewall-cmd --zone=public --add-port=9092/tcp --permanent
    6、firewall-cmd --reload 重新启动防火墙
    7、firewall-cmd --list-all  查询开放端口
    8、sudo iptables -F  把虚拟机中的防火墙给清了一下

（3）安装 telnet centos、ubuntu安装telnet命令的方法

yum list telnet*                   列出telnet相关的安装包
    yum install telnet-server          安装telnet服务
    yum install telnet.*               安装telnet客户端

### github 源码下载地址：[https://github.com/liruizi/storm\_Kafka\_demo][https_github.com_liruizi_storm_Kafka_demo] ###

[734555-20160318155456521-191268812.png]: /images/20220417/77149eed40be4f628b7be6b00b8dded1.png
[http_www.cnblogs.com_tovin_p_3974417.html]: http://www.cnblogs.com/tovin/p/3974417.html
[https_download.oracle.com_otn-pub_java_jdk_8u191-b12_2787e4a523244c269598db4e85c51e0c_jdk-8u191-linux-x64.tar.gz]: https://download.oracle.com/otn-pub/java/jdk/8u191-b12/2787e4a523244c269598db4e85c51e0c/jdk-8u191-linux-x64.tar.gz
[http_archive.apache.org_dist_zookeeper_zookeeper-3.4.13_zookeeper-3.4.13.tar.gz]: http://archive.apache.org/dist/zookeeper/zookeeper-3.4.13/zookeeper-3.4.13.tar.gz
[http_mirrors.hust.edu.cn_apache_kafka_2.0.0_kafka_2.11-2.0.0.tgz]: http://mirrors.hust.edu.cn/apache/kafka/2.0.0/kafka_2.11-2.0.0.tgz
[http_www.apache.org_dist_storm_apache-storm-1.2.2_apache-storm-1.2.2.tar.gz]: http://www.apache.org/dist/storm/apache-storm-1.2.2/apache-storm-1.2.2.tar.gz
[root_192.168.164.134]: mailto:root@192.168.164.134
[root_192.168.164.133]: mailto:root@192.168.164.133
[http_192.168.164.133_8080]: http://192.168.164.133:8080/
[watermark_type_ZmFuZ3poZW5naGVpdGk_shadow_10_text_aHR0cHM6Ly9ibG9nLmNzZG4ubmV0L2xpcnVpemk_size_16_color_FFFFFF_t_70]: /images/20220417/1fee0cdb1dba476487d32ffd11b0446f.png
[https_github.com_liruizi_storm_Kafka_demo]: https://github.com/liruizi/storm_Kafka_demo