Flink on K8S集群搭建及StreamPark平台安装

1.环境准备

1.1 介绍

在使用 Flink&Spark 时发现从编程模型, 启动配置到运维管理都有很多可以抽象共用的地方, 目前streampark提供了一个flink一站式的流处理作业开发管理平台, 从流处理作业开发到上线全生命周期都做了支持, 是一个一站式的流出来计算平台。
未来spark开发也在规划范围内，目前还不支持

1.2 下载

StreamPark安装包下载：https://streampark.apache.org/download
StreamPark官网：https://streampark.apache.org/docs/intro
最新版为2.1.2，本次安装为2.1.2版本

1.3 已有组件及版本

序号名称配置1K8S(TEK)CPU:316,Me:361.57G,Storage:349.1G,Pods:3253,IP:3*273 (v1.26.1)2NFS(CFS)40G磁盘（目前，可扩充）3Harbor(容器仓库）未知4flinkflink-(1.13.0/1.14.4/1.16.2)5StreamPark2.1.26Mysql5.7

2.挂载与权限

2.1 k8s挂载

找运维开通权限，主要是kubectl的权限

下载kubectl
权限文件：/root/.kube/config

2.2 nfs挂载

找运维要服务ip

#挂载前，请确保系统中已经安装了nfs-utils或nfs-commonsudo yum install nfs-utils
#创建待挂载目标目录mkdir<待挂载目标目录>mkdir /localfolder/
#挂载文件系统#挂载 CFS 根目录#以下命令可以到 CFS 控制台-文件系统详情-挂载点详情中获取，由于部分旧版本文件系统不支持 noresvport 参数，具体挂载命令请以控制台建议命令为主。配置 norevsport 参数后，在网络重连时使用新的 TCP 端口，可以保障在网络异常到恢复期间、客户端和文件系统的连接不会中断，建议启用该参数。#另，部分旧版本 Linux 内核需要使用 vers=4 挂载，若使用 vers=4.0 挂载有异常，可以尝试修改为 vers=4。sudomount-t nfs -overs=4.0,noresvport <挂载点 IP>:/ <待挂载目录>sudomount-t nfs -overs=4.0,noresvport 10.0.24.4:/ /localfolder
#挂载 CFS 子目录#以下命令可以到 CFS 控制台-文件系统详情-挂载点详情中获取，由于部分旧版本文件系统不支持 noresvport 参数，具体挂载命令请以控制台建议命令为主。配置 norevsport 参数后，在网络重连时使用新的 TCP 端口，可以保障在网络异常到恢复期间、客户端和文件系统的连接不会中断，建议启用该参数。#另，部分旧版本 Linux 内核需要使用 vers=4 挂载，若使用 vers=4.0 挂载有异常，可以尝试修改为 vers=4。sudomount-t nfs -overs=4.0,noresvport 10.0.24.4:/subfolder /localfolder

腾讯nfs(CFS)使用文档：https://cloud.tencent.com/document/product/582/11523

2.3 Harbor

需要找运维开通权限

此处注意：项目库要公开才可以使用

3.测试Flink

在k8s为flink单独开通命名空间，并创建相应账户

kubectl create clusterrolebinding flink-role-bind --clusterrole=edit --serviceaccount=flink:flink

在有k8s操作权限的节点运行flink-session

bin/flink run \-e kubernetes-session \-Dkubernetes.namespace=flink \
-Dkubernetes.rest-service.exposed.type=NodePort \
-Dkubernetes.cluster-id=flink-cluster \-c WordCount1 \
/data/package/jar/flink_test-1.0-SNAPSHOT.jar
#参考配置
bin/kubernetes-session.sh \-Dkubernetes.namespace=flink \
-Dkubernetes.jobmanager.service-account=flink \
-Dkubernetes.rest-service.exposed.type=NodePort \
-Dkubernetes.cluster-id=flink-cluster \-Dkubernetes.jobmanager.cpu=0.2\-Djobmanager.memory.process.size=1024m \
-Dresourcemanager.taskmanager-timeout=3600000\-Dkubernetes.taskmanager.cpu=0.2\-Dtaskmanager.memory.process.size=1024m \-Dtaskmanager.numberOfTaskSlots=1

4.安装StreamPark

4.1 streampark（k8s)镜像打包

#编译
./build #注意maven 镜像配置，要不找不到依赖包同时要安装npm#测试npm是否安装npm-v#streampark安装包添加mysql连接包cp /data/module/streampart_2.12-2.1.2/lib/mysql-connector-java-8.0.30.jar lib/
#配置maven配置拷贝cp /data/module/maven-3.6.3/conf/settings.xml /data/module/docker/streampark-docker/
#修改application.yml
profiles.active: mysql #[h2,pgsql,mysql]
lark-url: https://open.feishu.cn
workspace:
    local: /opt/streampark_workspace
#配置application-mysql.ymltee /data/module/docker/streampark-docker/streampark-2.1.2/conf/application-mysql.yml <<-'EOF'
spring.datasource.driver-class-name: com.mysql.cj.jdbc.Driver
streampark.docker.http-client.docker-host: ${DOCKER_HOST:}
streampark.maven.settings: ${MAVEN_SETTINGS_PATH:/root/.m2/settings.xml}
streampark.workspace.local: ${WORKSPACE_PATH:/opt/streampark_workspace}
EOF# 编写Dockerfile#需要提前准备kubectl、settings.xml 、config（kubectl的密钥）tee docker<<-'EOF'
FROM flink:1.17.1-scala_2.12-java8
WORKDIR /opt/streampark/
ADD ./streampark-2.1.2/ /opt/streampark/
ADD ./kubectl /opt/streampark/
ADD ./settings.xml /root/.m2/
USER root
RUN sed -i -e 's/eval $NOHUP/eval/' bin/streampark.sh \
    && sed -i -e 's/>> "$APP_OUT" 2>&1 "&"//' bin/streampark.sh \
    && install -o root -g root -m 0755 kubectl /usr/local/bin/kubectl \
    && mkdir -p ~/.kube
WORKDIR /opt/streampark/
ADD ./config /root/.kube/
RUN chown -R flink /opt/streampark/
EXPOSE 10000
EOF#构建镜像docker build -f Dockerfile -t apache/streampark-flink:2.1.2 .#推送镜像到仓库docker tag apache/streampark-flink:2.1.2 storage/bigdata/streampark-flink:2.1.2
docker push  storage/bigdata/streampark-flink:2.1.2
docker tag apache/streampark-flink:2.1.2-rc4 storage/bigdata/streampark-flink:2.1.2-rc4
docker push  storage/bigdata/streampark-flink:2.1.2-rc4

4.2部署MySQL的pod

#k8s上创建mysql的namespace#含义：kubectl create clusterrolebinding ClusterRoleBinding名 --clusterrole=绑定的Role serviceaccount=被绑定的SA -n 命名空间
kubectl create namespace mysql
kubectl create serviceaccount mysql
kubectl create clusterrolebinding mysql-role-bind --clusterrole=edit --serviceaccount=mysql:mysql -n mysql
clusterrolebinding.rbac.authorization.k8s.io/mysql-role-bind created
#查看角色绑定
kubectl get clusterrolebinding flink-role-bind -n flink -o yaml
kubectl get clusterrolebinding mysql-role-bind -n mysql -o yaml
kubectl get clusterrolebinding mysql-role-bind -n flink -o yaml
#配置pvc和pv和nfs指定(腾讯nfs可直接使用）
apiVersion: v1
kind: PersistentVolume
metadata:
  name: data-mysql
spec:
  accessModes:
  - ReadWriteMany
  capacity:
    storage: 10Gi
  csi:
    driver: com.tencent.cloud.csi.cfs
    volumeAttributes:
      host: x x x
      path: /data_mysql
      vers: "4"
    volumeHandle: cfs   #此处需要每个pv都不相同，否则挂载两个pvc会报错
  persistentVolumeReclaimPolicy: Retain
  storageClassName: data-mysql
  volumeMode: Filesystem
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: data-mysql
  namespace: mysql
spec:
  accessModes:
  - ReadWriteMany
  resources:
    requests:
      storage: 10Gi
  storageClassName: data-mysql
#docker拉去mysql镜像并上传至镜像库docker tag mysql:5.7 storage/bigdata/mysql:5.7
docker push storage/bigdata/mysql:5.7
#查看集群的node ip
kubectl get node# 编写mysql的yaml文件，并做配置sudomkdir-p /data/module/docker/mysql/{conf,data}/
sudotee /data/module/docker/mysql/conf/pod-db-mysql.yaml <<-'EOF'
apiVersion: v1
kind: ConfigMap
metadata:
  name: conf-mysql
  namespace: mysql
data:
  mysql.cnf: |
    [mysqld]
    #Mysql服务的唯一编号 每个mysql服务Id需唯一
    server-id=1
    # 允许访问的IP网段
    bind-address=0.0.0.0
    #设置时区
    default-time_zone='+8:00'
    #数据库默认字符集,主流字符集支持一些特殊表情符号（特殊表情符占用4个字节）
    character-set-server=utf8mb4
    #数据库字符集对应一些排序等规则，注意要和character-set-server对应
    collation-server=utf8mb4_general_ci
    #设置client连接mysql时的字符集,防止乱码
    init_connect='SET NAMES utf8mb4'
    #是否对sql语句大小写敏感，1表示不敏感
    lower_case_table_names=1
    #最大连接数
    max_connections=400
    #最大错误连接数
    max_connect_errors=1000
    #TIMESTAMP如果没有显示声明NOT NULL，允许NULL值
    explicit_defaults_for_timestamp=true
    #SQL数据包发送的大小，如果有BLOB对象建议修改成1G
    max_allowed_packet=128M
    #MySQL连接闲置超过一定时间后(单位：秒)将会被强行关闭
    #MySQL默认的wait_timeout  值为8个小时, interactive_timeout参数需要同时配置才能生效
    interactive_timeout=3600
    wait_timeout=3600
---
apiVersion: v1
kind: Pod
metadata:
  name: pod-db-mysql
  namespace: mysql
spec:
        #serviceAccount: mysql
        nodeName: xxx
  hostNetwork: true #主机网络可见(会占用node端口)
  containers:
    - name: mysql-k8s
      image: storage/bigdata/mysql:5.7
      env:
        - name: TZ
          value: "Asia/Shanghai"
        - name: LANG
          value: "zh_CN.UTF-8"
        - name: MYSQL_ROOT_PASSWORD
          value: "xxxx"
      ports:
        #- containerPort: 3306
      volumeMounts:
        - mountPath: /var/lib/mysql
          subPath: mysql
          name: data-mysql
        - mountPath: /etc/mysql/conf.d
          name: conf-volume
          readOnly: true
  volumes:
                - name: data-mysql
      persistentVolumeClaim:
        claimName: data-mysql
    - name: conf-volume
      configMap:
        name: conf-mysql
EOF#kubectl delete -f /opt/module/k3s/conf/pod-db-mysql-k3s100.yaml#启动pod
kubectl apply -f /data/module/docker/mysql/conf/pod-db-mysql.yaml
kubectl delete -f /data/module/docker/mysql/conf/pod-db-mysql.yaml
# 稍等片刻
kubectl get pod -A-owide
kubectl describe pod pod-db-mysql
kubectl logs --tail=100-f pod-db-mysql -n mysql

4.3 mysql 数据库初始化

# 复制数据库文件cp-r /data/software/incubator-streampark-2.1.2-rc3/streampark-console/streampark-console-service/src/main/assembly/script/ /localnfs/data_mysql/mysql/streampark-sql/
cp-r /data/module/docker/streampark-docker/streampark-2.2.0/script/ /localnfs/data_mysql/mysql/streampark-sql/
# 创建用户及数据库# 进入mysql容器
kubectl exec-n mysql -it pod-db-mysql  -- bash#------------------------进入mysql容器----------------------------
mysql -uroot-proot
create database if not exists `streampark` character set utf8mb4 collate utf8mb4_general_ci;
create user 'xxxx'@'%' IDENTIFIED WITH mysql_native_password by 'xxx';
grant ALL PRIVILEGES ON streampark.* to 'xxxx'@'%';
flush privileges;
-- 导入数据文件
use streampark;source /var/lib/mysql/streampark-sql/schema/mysql-schema.sql
source /var/lib/mysql/streampark-sql/data/mysql-data.sql
-- 退出mysql
quit
#------------------------退出mysql容器------------------------exit#查看mysql 的建表vim /data/module/docker/streampark-docker/streampark-2.2.0/script/schema/mysql-schema.sql
vim /data/module/docker/streampark-docker/streampark-2.2.0/script/data/mysql-data.sql

4.4 创建StreamPark的pod

#k8s上创建mysql的namespace#含义：kubectl create clusterrolebinding ClusterRoleBinding名 --clusterrole=绑定的Role serviceaccount=被绑定的SA -n 命名空间
kubectl create namespace streampark
kubectl create serviceaccount streampark
kubectl create clusterrolebinding streampark-role-bind --clusterrole=edit --serviceaccount=streampark:streampark -n streampark
clusterrolebinding.rbac.authorization.k8s.io/mysql-role-bind created
#配置pvc和pv和nfs指定vim pv-pvc-streampark.yaml
apiVersion: v1
kind: PersistentVolume
metadata:
  name: data-streampark
spec:
  accessModes:
  - ReadWriteMany
  capacity:
    storage: 10Gi
  csi:
    driver: com.tencent.cloud.csi.cfs
    volumeAttributes:
      host: xxx
      path: /data_streampark
      vers: "4"
    volumeHandle: cfs    #此处需要每个pv都不相同，否则挂载两个pvc会报错
  persistentVolumeReclaimPolicy: Retain
  storageClassName: data-streampark
  volumeMode: Filesystem
---
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: data-streampark
  namespace: streampark
spec:
  accessModes:
  - ReadWriteMany
  resources:
    requests:
      storage: 10Gi
  storageClassName: data-streampark
#执行
kubectl apply -f /data/module/docker/k8s/pv-pvc-streampark.yaml
kubectl delete -f /data/module/docker/k8s/pv-pvc-streampark.yaml
# 在xxx 上执行,在指定 节点 xxx 安装StreamParksudotee /data/pod-app-streampark.yaml <<-'EOF'
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: pod-app-streampark
  name: pod-app-streampark
  namespace: streampark
spec:
  replicas: 1
  selector:
    matchLabels:
      app: pod-app-streampark
  template:
    metadata:
      labels:
        app: pod-app-streampark
    spec:
      nodeName: xxx
      hostNetwork: true #主机网络可见(会占用node端口)
      containers:
        - name: streampark
          image: storage/bigdata/streampark-flink:2.1.2-rc4
          imagePullPolicy: Always
          env:
            - name: TZ
              value: "Asia/Shanghai"
            - name: LANG
              value: "zh_CN.UTF-8"
            - name: SPRING_PROFILES_ACTIVE
              value: "mysql"
            - name: SPRING_DATASOURCE_URL
              value: "jdbc:mysql://xxx:3306/streampark?useSSL=false&useUnicode=true&characterEncoding=UTF-8&allowPublicKeyRetrieval=false&useJDBCCompliantTimezoneShift=true&useLegacyDatetimeCode=false&serverTimezone=GMT%2B8"
            - name: SPRING_DATASOURCE_USERNAME
              value: "xxxx"
            - name: SPRING_DATASOURCE_PASSWORD
              value: "xxxx"
            - name: DOCKER_HOST
              value: "tcp://xxx:2375"
            - name: DEBUG_OPTS #调试端口参数
              value: "-agentlib:jdwp=transport=dt_socket,server=y,suspend=n,address=*:10001"
          ports:
            #- containerPort: 10000
          volumeMounts:
            - mountPath: /root/.kube
              subPath: .kube
              name: conf-volume
            - mountPath: /opt/streampark_workspace
              subPath: streampark_workspace
              name: data-volume
          command: ["sh","-c","bash bin/startup.sh debug"]
      volumes:
        - name: conf-volume
          hostPath:
            path: /root
            type: DirectoryOrCreate
        - name: data-volume
          nfs:
            path: /data_streampark
            server: xxx
EOF#kubectl delete -f /opt/module/k3s/conf/pod-app-streampark-k3s100.yaml#启动pod
kubectl apply -f /data/pod-app-streampark.yaml
kubectl delete -f /data/pod-app-streampark.yaml
# 稍等片刻
kubectl get pod -A-o wide -n mysql
kubectl describe pod pod-app-streampark-k3s100
kubectl logs --tail=1000-f pod-app-streampark -n mysql
# 进入mysql容器中创建用户及数据库
kubectl exec-n mysql -it pod-app-streampark  -- bash#-c streampark-k3s100# 为默认命名空间添加权限 kubectl create clusterrolebinding flink-role-binding-default --clusterrole=edit --serviceaccount=flink_dev:default
kubectl create clusterrolebinding flink-role-binding-default --clusterrole=edit --serviceaccount=default:default

标签： flink kubernetes 大数据

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