Flink典型的任务处理过程如下所示：
Flink安装包下载地址：http://flink.apache.org/downloads.html ，选择对应Hadoop的Flink版本下载
Standalone 模式
快速入门教程地址：https://ci.apache.org/projects/flink/flink-docs-release-1.6/quickstart/setup_quickstart.html
1. 软件要求
- Java 1.8.x或更高版本，
- ssh（必须运行sshd才能使用管理远程组件的Flink脚本）
集群部署规划
节点 |
master |
worker |
zookeeper |
master |
master |
|
zookeeper |
slave1 |
|
worker |
zookeeper |
slave2 |
|
worker |
zookeeper |
docker run -p 50070:50070 -p 19888:19888 -p 8088:8088 -p 2181:2181 -p 16010:16010 -p 9092:9092 -9000：9000 --name master -ti -h master linux:hadoop
docker run -it -h slave1 --name slave1 linux:hadoop /bin/bash
docker run -it -h slave2 --name slave2 linux:hadoop /bin/bash2. 解压
tar zxvf flink-1.7.1-bin-hadoop27-scala_2.11.tgz3. 修改配置文件
[root@master conf]$ ls
flink-conf.yaml log4j-console.properties log4j-yarn-session.properties logback.xml masters sql-client-defaults.yaml
log4j-cli.properties log4j.properties logback-console.xml logback-yarn.xml slaves zoo.cfg修改flink-conf.yaml
taskmanager.numberOfTaskSlots：2
jobmanager.rpc.address:master可选配置：
- 每个JobManager（
jobmanager.heap.mb）的可用内存量， - 每个TaskManager（
taskmanager.heap.mb）的可用内存量， - 每台机器的可用CPU数量（
taskmanager.numberOfTaskSlots）， - 集群中的CPU总数（
parallelism.default）和 - 临时目录（
taskmanager.tmp.dirs）
3.1. HA配置文件
#jobmanager.rpc.address:master #在master file中配置，由zookeeper选出leader与standby
high-availability:zookeeper #指定高可用模式（必须）
high-availability.zookeeper.quorum:master:2181,slave1:2181,slave2:2181 #ZooKeeper仲裁是ZooKeeper服务器的复制组，它提供分布式协调服务（必须）
high-availability.storageDir:hdfs:///flink/ha/ #JobManager元数据保存在文件系统storageDir中，只有指向此状态的指针存储在ZooKeeper中（必须）
high-availability.zookeeper.path.root:/flink #根ZooKeeper节点，在该节点下放置所有集群节点（推荐）
high-availability.cluster-id:/flinkCluster ＃自定义集群（推荐）
state.backend: filesystem
state.checkpoints.dir: hdfs:///flink/checkpoints
state.savepoints.dir: hdfs:///flink/checkpoints修改conf/zoo.cfg
server.1=master:2888:3888
server.2=slave1:2888:3888
server.3=slave2:2888:3888修改conf/masters
master:8081修改slaves
slave1
slave24. 启动Hadoop
hadoop集群，不做演示
[root@master /]# start-dfs.sh
19/01/11 06:35:51 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
Starting namenodes on [master]
master: starting namenode, logging to /usr/local/hadoop/hadoop-2.8.3/logs/hadoop-root-namenode-master.out
slave1: starting datanode, logging to /usr/local/hadoop/hadoop-2.8.3/logs/hadoop-root-datanode-slave1.out
slave2: starting datanode, logging to /usr/local/hadoop/hadoop-2.8.3/logs/hadoop-root-datanode-slave2.out
master: starting datanode, logging to /usr/local/hadoop/hadoop-2.8.3/logs/hadoop-root-datanode-master.out
Starting secondary namenodes [0.0.0.0]
0.0.0.0: starting secondarynamenode, logging to /usr/local/hadoop/hadoop-2.8.3/logs/hadoop-root-secondarynamenode-master.out
19/01/11 06:36:14 WARN util.NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable5. 启动Zookeeper
zookeeper集群，不做演示
[root@master /]# start-zookeeper-quorum.sh
Starting zookeeper daemon on host master.
Starting zookeeper daemon on host slave1.
Starting zookeeper daemon on host slave2.6. 启动flink
[root@master /]# start-cluster.sh
Starting HA cluster with 1 masters.
Starting standalonesession daemon on host master.
Starting taskexecutor daemon on host slave1.
Starting taskexecutor daemon on host slave2.webUI
