ubuntu18.04 flink-1.9.0 Standalone集群搭建

集群规划

	Master JobManager	Standby JobManager	Task Manager	Zookeeper
flink01	√			√
flink02		√		√
flink03		√	√	√
flink04		√	√	√

前置准备

克隆4台虚拟机

网络配置

vim /etc/netplan/01-network-manager-all.yaml 修改配置文件

集群网络配置如下:

# flink01
network:
  version: 2
  renderer: NetworkManager

  ethernets:
    ens33:
        dhcp4: no
        dhcp6: no
        addresses: [192.168.180.160/24]
        gateway4: 192.168.180.2
        nameservers:
            addresses: [114.114.114.114, 8.8.8.8]

 # flink02
 network:
  version: 2
  renderer: NetworkManager

  ethernets:
    ens33:
        dhcp4: no
        dhcp6: no
        addresses: [192.168.180.161/24]
        gateway4: 192.168.180.2
        nameservers:
            addresses: [114.114.114.114, 8.8.8.8]

# flink03
network:
  version: 2
  renderer: NetworkManager

  ethernets:
    ens33:
        dhcp4: no
        dhcp6: no
        addresses: [192.168.180.162/24]
        gateway4: 192.168.180.2
        nameservers:
            addresses: [114.114.114.114, 8.8.8.8]

   #flink04
   network:
  version: 2
  renderer: NetworkManager

  ethernets:
    ens33:
        dhcp4: no
        dhcp6: no
        addresses: [192.168.180.163/24]
        gateway4: 192.168.180.2
        nameservers:
            addresses: [114.114.114.114, 8.8.8.8]

能 ping 通 baidu 连上 xshell 即可, 连不上的可能是防火墙问题, ubuntu 用的防火墙是ufw, selinux 默认是disabled, 正常来说应该不会连不上。

修改 hostname 及 hosts文件

vim /etc/hostname 修改 hostname 为 flink01

vim /etc/hosts 修改 host文件

127.0.0.1       localhost
192.168.180.160    flink01
192.168.180.161    flink02
192.168.180.162    flink03
192.168.180.163    flink04

# The following lines are desirable for IPv6 capable hosts
::1     ip6-localhost ip6-loopback
fe00::0 ip6-localnet
ff00::0 ip6-mcastprefix
ff02::1 ip6-allnodes
ff02::2 ip6-allrouters

JDK配置
- 如果没有配置jdk请参考https://www.cnblogs.com/ronnieyuan/p/11461377.html
  - 如果之前有下过别的版本的jdk请将jdk的tar包解压到/usr/lib/jvm,然后再修改配置文件并选择jdk

免密登录

root@flink01:~# ssh-keygen -t rsa -P ""
Generating public/private rsa key pair.
Enter file in which to save the key (/root/.ssh/id_rsa): 
Created directory '/root/.ssh'.
Your identification has been saved in /root/.ssh/id_rsa.
Your public key has been saved in /root/.ssh/id_rsa.pub.
The key fingerprint is:
SHA256:2P9NCcuEljhcWBndG8FBoAxOeGbZDIHIdw06r3bbsug root@flink01
The key's randomart image is:
+---[RSA 2048]----+
|   . . o*Oo+.=+o |
|    o ++*==.. +  |
|     .o=o +    o |
|       * o o  .  |
|      . S + o    |
|       . + o o . |
|      o . . o o  |
|     . o.o . o   |
|     .E oo. . .  |
+----[SHA256]-----+

在~目录下vim .ssh/authorized_keys:

将5台虚拟机公钥都存入该文件中, 每台的authorized_keys都一致

ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDZGR9+3bTIq6kZ5c+1O2mvyPBM790/0QUuVcjPSREK1pMpyyKRu6CUaBlTOM8JJzkCnEe7DVKY8lV2q7Zv7VVXTLI2dKuUmo0oMSGo5ABvfjGUJfFWdNkqgrPgT+Opl/1kIqr6wTGGCJsRx+Nfkic31WhnPij2IM/Zpqu88kiXmUbaNwBDM5jaRqB/nk7DW4aMwF5oeX6LvEuI1SVmY3DH0w6Cf1EDtOyYG1f9Vof8ao88JOwRZazTNbBdsVcPKDbtvovs/lP+CrtwmAcGFGZSjA22I0dc9ek0puQ5pNUgindpb9egJJFoGhtduut6OfmmvbB8u9PjdBkHcp3Vof4j root@flink01

ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDMgNUIzT1YRTGX5E4MiWyQ9UxfQ1pRwCSMy3wqJOuyqv/kW5VsL0BS1VAwtSS9FqCBon3lT0zfgPEkscDdKugMtpgSeREjbQQJSDYPQGyCsHcXQgne5dfaWbvLvaFbNO1G5wqW6E3zC5zy85mSdg9qg8NmqYwyz0O8WSRottuAMHfhoNkHemdrIHhVBBZeKxFbsiXxiWi1EQJUYhYWU1LAqcpiIgFhjAGJkH91qULmm8FxkbB3ytcMlkFBNbcr3UkN5EK0VGV/Ly1qgs9UmXtS7xb5Lw5RlqjUMvwc28oHZYSfPRS1TL/oaFBZSIIGPjudke5wsBwNnzHGE44sTWUt root@flink02

ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDRYkED/hA9nqmCBClIByAIcrT94edjno1HXn/KIgrCXy0aoIfsgY5FDr/3iZgaEdvnDz1woyKyj5gqkYxdQw0vLiJGOefgSC4yx7j6vKaK+2aSxJD+DLFB6toFAlyfWziTnyoPj3hPhlpSdG1P4YSEpMub5p1gVsEX9+vRvyazIabsbY9YsCsv/WDs3aAYyalfuvN+AXTrXI8di+AGgsjbwmo0/VQWQfItHY+WdTGcfBQQ8Ad9UX2wVRQPXq7gHh3LlBWKZnB+nZxavnI/G9Lo9w9MODSBgxfCfKNu6fpnpcvh8u+AqmT6rNKZg5NuZWW16siGvLNReSnWn7KwHzzD root@flink03

ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAABAQDkBQxFdKvg2MzGl1eFeDO1iqL2+fdJ9b4ktU9fjO/APEkumbftfrDTgJAnQhcXMsU7RjCJ+Zwt/dpeGhql3o7hXuhjQiUXf+8GXYre8cw9+xaYmaVhCZYbpcFiSrd/8TK3qv+gf21YIT7iQEFEl384qxPbyoU4Lm+M/1aY3m4gHvELv3jfg8oVBypxgaAJpJj9ZnnA0zN470cod1E67yVbfIkoSTy8BXd8UhVedYODD1ddaFX8MF53acUdJgLCGzh4axxivlGqdXWB7lhjbBvjllt2LYb7hW+O1qyCFNiRx/+zR9dSu5ZSW3QNg2EP/ljcCjDWa7AHgTvw6BYkdpj1 root@flink04

依次测试免密登录是否成功

成功案例：

root@flink01:~# ssh [email protected]
Welcome to Ubuntu 18.04.2 LTS (GNU/Linux 4.18.0-17-generic x86_64)

 * Documentation:  https://help.ubuntu.com
 * Management:     https://landscape.canonical.com
 * Support:        https://ubuntu.com/advantage


 * Canonical Livepatch is available for installation.
   - Reduce system reboots and improve kernel security. Activate at:
     https://ubuntu.com/livepatch

273 packages can be updated.
272 updates are security updates.

Your Hardware Enablement Stack (HWE) is supported until April 2023.
Last login: Sun Oct 27 11:11:26 2019 from 192.168.180.160
root@flink02:~#

集群搭建

Zookeeper 搭建

上传 tar 包并解压到指定目录并修改解压后的目录名称

tar -zxvf apache-zookeeper-3.5.5-bin.tar.gz -C /opt/ronnie/

cd /opt/ronnie

mv apache-zookeeper-3.5.5-bin/ zookeeper-3.5.5

创建并修改zookeeper配置文件

cd zookeeper-3.5.5/conf/ 进入Zookeeper配置文件目录
cp zoo_sample.cfg zoo.cfg 拷贝一份zoo_sample.cfg 为 zoo.cfg

vim zoo.cfg 修改配置文件

# 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=/opt/ronnie/zookeeper-3.5.5/data/zk
dataLogDir=/opt/ronnie/zookeeper-3.5.5/data/log
# 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=flink01:2888:3888
server.2=flink02:2888:3888
server.3=flink03:2888:3888
server.4=flink04:2888:3888

创建data目录:

mkdir -p /opt/ronnie/zookeeper-3.5.5/data

mkdir -p /opt/ronnie/zookeeper-3.5.5/data/log

mkdir -p /opt/ronnie/zookeeper-3.5.5/data/zk

cd zk/, 创建myid, 四台虚拟机flink01, flink02, flink03, flink04 分别对应 myid 1,2,3,4

添加环境变量

vim ~/.bashrc , 完成后 source ~/.bashrc

# Zookeeper
export ZOOKEEPER_HOME=/opt/ronnie/zookeeper-3.5.5
export PATH=$ZOOKEEPER_HOME/bin:$PATH

将Zookeeper目录传送给其他几台虚拟机(记得改myid)

cd /opt/ronnie
scp -r zookeeper-3.5.5/ [email protected]:/opt/ronnie/
scp -r zookeeper-3.5.5/ [email protected]:/opt/ronnie/
scp -r zookeeper-3.5.5/ [email protected]:/opt/ronnie/

启动Zookeeper: zkServer.sh start
检查Zookeeper 状态: zkServer.sh status

有显示该节点状态就表示启动成功了

root@flink01:~# zkServer.sh status
ZooKeeper JMX enabled by default
Using config: /opt/ronnie/zookeeper-3.5.5/bin/../conf/zoo.cfg
Client port found: 2181. Client address: localhost.
Mode: follower

报错请查看日志定位错误

Hadoop集群搭建(主要还是为了hdfs, On-Yarn后面再弄)

集群分配

	NN-1	NN-2	DN	ZK	ZKFC	JN
flink01	*		*	*	*	*
flink02		*	*	*	*	*
flink03			*	*		*
flink04			*	*		*

上传tar包并解压到指定路径:

   tar -zxvf hadoop-3.1.2.tar.gz -C /opt/ronnie

vim /opt/ronnie/hadoop-3.1.2/etc/hadoop/hadoop-env.sh 将环境文件中的jdk路径替换为本机jdk路径

export JAVA_HOME=/usr/lib/jvm/jdk1.8

vim /opt/ronnie/hadoop-3.1.2/etc/hadoop/mapred-env.sh, 添加:
```
export JAVA_HOME=/usr/lib/jvm/jdk1.8
```
vim /opt/ronnie/hadoop-3.1.2/etc/hadoop/yarn-env.sh,添加:
```
export JAVA_HOME=/usr/lib/jvm/jdk1.8
```

vim /opt/ronnie/hadoop-3.1.2/etc/hadoop/core-site.xml 修改core-site文件

<configuration>
        <property>
                <name>fs.defaultFS</name>
                <value>hdfs://ronnie</value>
        </property>
        <property>
                <name>ha.zookeeper.quorum</name>
                <value>flink01:2181,flink02:2181,flink03:2181,flink04:2181</value>
        </property>
        <property>
                <name>hadoop.tmp.dir</name>
                <value>/var/ronnie/hadoop/ha</value>
         </property>
</configuration>

vim /opt/ronnie/hadoop-3.1.2/etc/hadoop/hdfs-site.xml

<configuration>
        <property>
                <name>dfs.nameservices</name>
                <value>ronnie</value>
        </property>
        <property>
                <name>dfs.ha.namenodes.ronnie</name>
                <value>nn1,nn2</value>
        </property>
        <property>
                <name>dfs.namenode.rpc-address.ronnie.nn1</name>
                <value>flink01:8020</value>
        </property>
        <property>
                <name>dfs.namenode.rpc-address.ronnie.nn2</name>
                <value>flink02:8020</value>
        </property>
        <property>
                <name>dfs.namenode.http-address.ronnie.nn1</name>
                <value>flink01:50070</value>
        </property>
        <property>
                <name>dfs.namenode.http-address.ronnie.nn2</name>
                <value>flink02:50070</value>
        </property>
        <property>
                <name>dfs.namenode.shared.edits.dir</name>
                <value>qjournal://flink01:8485;flink02:8485;flink03:8485;flink04:8485/ronnie</value>
        </property>
        <property>
                <name>dfs.journalnode.edits.dir</name>
                <value>/var/ronnie/hadoop/ha/jn</value>
        </property>
        <property>
                <name>dfs.client.failover.proxy.provider.ronnie</name>
                <value>org.apache.hadoop.hdfs.server.namenode.ha.ConfiguredFailoverProxyProvider</value>
        </property>
        <property>
                <name>dfs.ha.fencing.methods</name>
                <value>sshfence</value>
        </property>
        <property>
                <name>dfs.ha.fencing.ssh.private-key-files</name>
                <value>/root/.ssh/id_dsa</value>
        </property>
        <property>
                <name>dfs.ha.automatic-failover.enabled</name>
                <value>true</value>
        </property>
</configuration>

vim /opt/ronnie/hadoop-3.1.2/etc/hadoop/workers修改工作组
```
flink01
flink02
flink03
flink04
```

vim /opt/ronnie/hadoop-3.1.2/sbin/start-dfs.sh

vim /opt/ronnie/hadoop-3.1.2/sbin/stop-dfs.sh

在文件顶部头文件之后添加:

HDFS_DATANODE_USER=root

HADOOP_SECURE_DN_USER=hdfs

HDFS_NAMENODE_USER=root

HDFS_SECONDARYNAMENODE_USER=root

HDFS_JOURNALNODE_USER=root

HDFS_ZKFC_USER=root

vim /opt/ronnie/hadoop-3.1.2/sbin/start-yarn.sh

vim /opt/ronnie/hadoop-3.1.2/sbin/stop-yarn.sh

在文件顶部头文件之后添加:
```
YARN_RESOURCEMANAGER_USER=root

HADOOP_SECURE_DN_USER=yarn

YARN_NODEMANAGER_USER=root
```

将文件发送给其他三台虚拟机:

scp -r /opt/ronnie/hadoop-3.1.2/ root@flink02:/opt/ronnie/
scp -r /opt/ronnie/hadoop-3.1.2/ root@flink03:/opt/ronnie/
scp -r /opt/ronnie/hadoop-3.1.2/ root@flink04:/opt/ronnie/

vim ~/.bashrc 添加hadoop路径

#HADOOP VARIABLES
export HADOOP_HOME=/opt/ronnie/hadoop-3.1.2
export PATH=$PATH:$HADOOP_HOME/bin
export PATH=$PATH:$HADOOP_HOME/sbin
export HADOOP_MAPRED_HOME=$HADOOP_HOME
export HADOOP_COMMON_HOME=$HADOOP_HOME
export HADOOP_HDFS_HOME=$HADOOP_HOME
export YARN_HOME=$HADOOP_HOME
export HADOOP_COMMON_LIB_NATIVE_DIR=$HADOOP_HOME/lib/native
export HADOOP_OPTS="-Djava.library.path=$HADOOP_HOME/lib"

source ~/.bashrc 使新配置生效(记得每台都要改)

hadoop version查看版本，显示如下则hadoop路径配置成功:

root@flink01:~# hadoop version
Hadoop 3.1.2
Source code repository https://github.com/apache/hadoop.git -r 1019dde65bcf12e05ef48ac71e84550d589e5d9a
Compiled by sunilg on 2019-01-29T01:39Z
Compiled with protoc 2.5.0
From source with checksum 64b8bdd4ca6e77cce75a93eb09ab2a9
This command was run using /opt/ronnie/hadoop-3.1.2/share/hadoop/common/hadoop-common-3.1.2.jar

启动集群:
- 启动Zookeeper
```
zkServer.sh start
```
- 在 flink01, flink02, flink03, flink04上启动journalnode
```
hadoop-daemon.sh start journalnode
```
- jps 查看进程
```
root@flink01:~# jps
2842 QuorumPeerMain
3068 Jps
3004 JournalNode
```
- 在两台NameNode中选一台进行格式化(这里选flink01)
  - hdfs namenode -format
  - hdfs --daemon start 启动 namenode
- 在另一台NameNode上同步格式化后的相关信息
  - hdfs namenode -bootstrapStandby
- 格式化zkfc
  - hdfs zkfc -formatZK
- 启动 hdfs 集群
  - start-dfs.sh
- 打开50070端口:
- hdfs搭建成功

Flink 集群搭建

上传 tar 包并解压到指定目录

这次发生了一个问题, rz -E上传乱码了, 解决方案: rz -be 上传

解压到指定目录

 tar zxvf flink-1.9.0-bin-scala_2.12.tgz -C /opt/ronnie/

vim /opt/ronnie/flink-1.9.0/conf/flink-conf.yaml 修改flink配置文件：

# JobManager的rpc地址
jobmanager.rpc.address: flink01

# The RPC port where the JobManager is reachable.
# rpc 端口号

  jobmanager.rpc.port: 6123

# The heap size for the JobManager JVM

# JobManager的 JVM 的堆的大小

jobmanager.heap.size: 1024m

# The heap size for the TaskManager JVM

# TaskManager 的 堆的大小

taskmanager.heap.size: 1024m

# The number of task slots that each TaskManager offers. Each slot runs one parallel pipeline.

# 每个TaskManager提供的任务槽的数量, 每个槽运行一条并行的管道

taskmanager.numberOfTaskSlots: 1

# The parallelism used for programs that did not specify and other parallelism.

# 程序的并行度

parallelism.default: 1

# 高可用配置

high-availability: zookeeper

high-availability.zookeeper.quorum: flink01:2181,flink01:2181,flink03:2181,flink04:2181

high-availability.zookeeper.path.root: /flink

high-availability.cluster-id: /default_one

# 这个必须是NameNode的8020

high-availability.zookeeper.storageDir: hdfs://flink01:8020/flink/ha

vim /opt/ronnie/flink-1.9.0/conf/masters
```
flink01:8081
flink02:8081
```
vim /opt/ronnie/flink-1.9.0/conf/slaves
```
flink03
flink04
```

start-cluster.sh 后jps发现没有对应jobManager进程，查看flink日志发现报错:

UnsupportedFileSystemSchemeException: Hadoop is not in the classpath/dependencies.

需要去官网下载Pre-bundled Hadoop
将jar包上传至 flink 目录下的 lib目录
```
cd /opt/ronnie/flink-1.9.0/lib
```

将 jar 包发送至其他三台虚拟机

scp flink-shaded-hadoop-2-uber-2.8.3-7.0.jar root@flink02:`pwd`
scp flink-shaded-hadoop-2-uber-2.8.3-7.0.jar root@flink03:`pwd`
scp flink-shaded-hadoop-2-uber-2.8.3-7.0.jar root@flink03:`pwd`

start-cluster.sh 启动 flink 集群, jps查看有对应的StandaloneSessionClusterEntrypoint进程后, 打开8081端口

1572747194753

1572747236737

1572747252202

运行一下自带的wordCount测试一下

/opt/ronnie/flink-1.9.0
flink run examples/streaming/WordCount.jar

执行结果:

Starting execution of program
Executing WordCount example with default input data set.
Use --input to specify file input.
Printing result to stdout. Use --output to specify output path.
Program execution finished
Job with JobID 2262c186bb5072917e79e2d081e9fab3 has finished.
Job Runtime: 1311 ms

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