前提条件
拥有1台CentOS7
CentOS7安装好jdk，官方文档要求java 11，使用java 8也可以。可参考 CentOS7安装jdk8
下载安装包
下载安装包
[hadoop@node1 ~]$ cd installfile/
[hadoop@node1 installfile]$ wget https://archive.apache.org/dist/flink/flink-1.17.1/flink-1.17.1-bin-scala_2.12.tgz --no-check-certificate解压安装包
[hadoop@node1 installfile]$ tar -zxvf flink-1.17.1-bin-scala_2.12.tgz -C ~/soft
创建软链接
[hadoop@node1 installfile]$ cd ~/soft/
[hadoop@node1 soft]$ ls
flink-1.18.0 hadoop hadoop-2.7.3 hbase hbase-1.7.1 jdk jdk1.8.0_271
[hadoop@node1 soft]$ ln -s flink-1.18.0 flink
[hadoop@node1 soft]$ ls
flink flink-1.18.0 hadoop hadoop-2.7.3 hbase hbase-1.7.1 jdk jdk1.8.0_271设置环境变量
[hadoop@node1 soft]$ nano ~/.bashrc 添加如下环境变量
export FLINK_HOME=~/soft/flink
export PATH=$PATH:$FLINK_HOME/bin让环境变量立即生效
[hadoop@node1 soft]$ source ~/.bashrc 验证版本号
[hadoop@node1 soft]$ flink -v
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/hadoop/soft/flink-1.17.1/lib/log4j-slf4j-impl-2.17.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/hadoop/soft/hadoop-2.7.3/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Version: 1.17.1, Commit ID: 2750d5c
配置flink
进入flink配置目录，查看flink的配置文件
[hadoop@node1 soft]$ cd $FLINK_HOME/
[hadoop@node1 flink]$ ls
bin conf examples lib LICENSE licenses log NOTICE opt plugins README.txt
[hadoop@node1 flink]$ cd conf/
[hadoop@node1 conf]$ ls
flink-conf.yaml log4j-console.properties log4j-session.properties logback-session.xml masters zoo.cfg
log4j-cli.properties log4j.properties logback-console.xml logback.xml workers配置flink-conf.yaml
[hadoop@node1 conf]$ vim flink-conf.yaml找到如下配置项，并按照如下修改，其中node1为机器主机名，请根据实际修改。
jobmanager.rpc.address: node1
jobmanager.bind-host: 0.0.0.0
taskmanager.bind-host: 0.0.0.0
taskmanager.host: node1
rest.address: node1
rest.bind-address: 0.0.0.0配置master
[hadoop@node1 conf]$ nano masters修改masters内容为
node1:8081配置workers
[hadoop@node1 conf]$ vim masters修改workers内容为
node1查看flink的命令
[hadoop@node1 conf]$ cd $FLINK_HOME/bin
[hadoop@node1 bin]$ ls
bash-java-utils.jar flink-daemon.sh kubernetes-taskmanager.sh start-cluster.sh yarn-session.sh
config.sh historyserver.sh pyflink-shell.sh start-zookeeper-quorum.sh zookeeper.sh
find-flink-home.sh jobmanager.sh sql-client.sh stop-cluster.sh
flink kubernetes-jobmanager.sh sql-gateway.sh stop-zookeeper-quorum.sh
flink-console.sh kubernetes-session.sh standalone-job.sh taskmanager.sh集群启动与停止
启动flink集群
[hadoop@node1 bin]$ start-cluster.sh
Starting cluster.
Starting standalonesession daemon on host node1.
Starting taskexecutor daemon on host node1.查看进程
[hadoop@node1 bin]$ jps
2433 TaskManagerRunner
2469 Jps
2143 StandaloneSessionClusterEntrypointWeb UI
浏览器访问
ip:8081
或者
主机名称:8081
注意：如果用windows的浏览器访问，需要先在windows的hosts文件添加ip和主机名node1的映射。
关闭flink集群
[hadoop@node1 bin]$ stop-cluster.sh
Stopping taskexecutor daemon (pid: 2433) on host node1.
Stopping standalonesession daemon (pid: 2143) on host node1.查看进程
[hadoop@node1 bin]$ jps
3239 Jps单独启动flink进程
[hadoop@node1 bin]$ jobmanager.sh start
[hadoop@node1 bin]$ taskmanager.sh start操作过程如下
[hadoop@node1 bin]$ jobmanager.sh start
Starting standalonesession daemon on host node1.
[hadoop@node1 bin]$ jps
3522 StandaloneSessionClusterEntrypoint
3593 Jps
[hadoop@node1 bin]$ taskmanager.sh start
Starting taskexecutor daemon on host node1.
[hadoop@node1 bin]$ jps
3522 StandaloneSessionClusterEntrypoint
3878 TaskManagerRunner
3910 Jps单独关闭flink进程
[hadoop@node1 bin]$ taskmanager.sh stop
[hadoop@node1 bin]$ jobmanager.sh stop操作过程如下
[hadoop@node1 bin]$ taskmanager.sh stop
Stopping taskexecutor daemon (pid: 3878) on host node1.
[hadoop@node1 bin]$ jps
3522 StandaloneSessionClusterEntrypoint
4244 Jps
[hadoop@node1 bin]$ jobmanager.sh stop
Stopping standalonesession daemon (pid: 3522) on host node1.
[hadoop@node1 bin]$ jps
4536 Jps提交应用测试
启动flink集群
[hadoop@node1 flink]$ start-cluster.sh提交flink作业
运行flink提供的wordcount案例程序
[hadoop@node1 flink]$ flink run examples/streaming/WordCount.jar
SLF4J: Class path contains multiple SLF4J bindings.
SLF4J: Found binding in [jar:file:/home/hadoop/soft/flink-1.17.1/lib/log4j-slf4j-impl-2.17.1.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: Found binding in [jar:file:/home/hadoop/soft/hadoop-2.7.3/share/hadoop/common/lib/slf4j-log4j12-1.7.10.jar!/org/slf4j/impl/StaticLoggerBinder.class]
SLF4J: See http://www.slf4j.org/codes.html#multiple_bindings for an explanation.
SLF4J: Actual binding is of type [org.apache.logging.slf4j.Log4jLoggerFactory]
Executing example with default input data.
Use --input to specify file input.
Printing result to stdout. Use --output to specify output path.
Job has been submitted with JobID 20126e9c38bfaf5651db0f068e78e37a
Program execution finished
Job with JobID 20126e9c38bfaf5651db0f068e78e37a has finished.
Job Runtime: 1999 ms查看结果
查看输出的wordcount结果的末尾10行数据
[hadoop@node1 flink]$ tail log/flink-*-taskexecutor-*.out
(nymph,1)
(in,3)
(thy,1)
(orisons,1)
(be,4)
(all,2)
(my,1)
(sins,1)
(remember,1)
(d,4)Web UI查看提交的作业
Web UI查看作业结果
完成！enjoy it!