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/bash

2. 解压

tar zxvf flink-1.7.1-bin-hadoop27-scala_2.11.tgz

3. 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
slave2

4. 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 applicable

5. 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