基于kubernetes构建spark集群(RC模式)

基于kubernetes部署spark的两种方式

• 方式一：使用kubernetes作为集群管理器(Cluster Manager)，类似与mesos和yarn，使用方式可搜索github查看running-on-kubernetes。但这个部署方式，一是还不成熟(目前Deprecated)，不推荐在生产环境使用.
• 方式二：standalone的方式，即便是不用集群也能很方便的调用sbin下的脚本来部署，而使用k8s有几点好处，一是提高机器使用率(一般服务器资源白天使用率较高，晚上空闲，刚好能拿来跑数据)；二是方便一键扩容，一键升级；三是能复用本身在k8s集群上做好的监控以及日志收集.

因此，我们选择使用第二种方式部署集群，写到这里时候spark 为2.4.x版本。假设为ecc电商项目构建spark集群，规划如下

1、spark rbac配置

创建rbac账户，并分配资源权限，Pod服务账户创建参考；

cat > ecc-spark-rbac.yaml << EOF
---
apiVersion: v1
kind: Namespace
metadata:
  name: ecc-spark-cluster
  labels:
    name: ecc-spark-cluster
---
#基于namespace创建服务账户spark-cdp
apiVersion: v1
kind: ServiceAccount
metadata:
  name: spark-cdp
  namespace: ecc-spark-cluster

---
#创建角色资源权限
apiVersion: rbac.authorization.k8s.io/v1
kind: Role
metadata:
  name: spark-cdp
  namespace: ecc-spark-cluster
rules:
  - apiGroups:
      - ""
    resources:
      - pods
    verbs:
      - '*'
  - apiGroups:
      - ""
    resources:
      - configmaps
    verbs:
      - '*'
  - apiGroups:
      - ""
    resources:
      - services
      - secrets
    verbs:
      - create
      - get
      - delete
  - apiGroups:
      - extensions
    resources:
      - ingresses
    verbs:
      - create
      - get
      - delete
  - apiGroups:
      - ""
    resources:
      - nodes
    verbs:
      - get
  - apiGroups:
      - ""
    resources:
      - resourcequotas
    verbs:
      - get
      - list
      - watch
  - apiGroups:
      - ""
    resources:
      - events
    verbs:
      - create
      - update
      - patch
  - apiGroups:
      - apiextensions.k8s.io
    resources:
      - customresourcedefinitions
    verbs:
      - create
      - get
      - update
      - delete
  - apiGroups:
      - admissionregistration.k8s.io
    resources:
      - mutatingwebhookconfigurations
      - validatingwebhookconfigurations
    verbs:
      - create
      - get
      - update
      - delete
  - apiGroups:
      - sparkoperator.k8s.io
    resources:
      - sparkapplications
      - scheduledsparkapplications
      - sparkapplications/status
      - scheduledsparkapplications/status
    verbs:
      - '*'
  - apiGroups:
      - scheduling.volcano.sh
    resources:
      - podgroups
      - queues
      - queues/status
    verbs:
      - get
      - list
      - watch
      - create
      - delete
      - update

---
#服务账户spark-cdp绑定角色
apiVersion: rbac.authorization.k8s.io/v1
kind: RoleBinding
metadata:
  name: spark-cdp
  namespace: ecc-spark-cluster
roleRef:
  apiGroup: rbac.authorization.k8s.io
  kind: Role
  name: spark-cdp
subjects:
  - kind: ServiceAccount
    name: spark-cdp
    
EOF

2、spark pv,pvc

• 构建pv
  挂载NFS，定义pv访问模式(accessModes)和存储容量(capacity)；

cat >ecc-spark-pv.yaml <<EOF
apiVersion: v1
kind: PersistentVolume
metadata:
  name: ecc-spark-pv-static
  namespace: ecc-spark-cluster
spec:
  capacity:
    storage: 10Gi
  accessModes:
    #访问三种模式：ReadWriteOnce,ReadOnlyMany,ReadWriteMany
    - ReadWriteOnce
  nfs:
    path: /data/nfs
    server: 192.168.0.135
    
EOF

• 构建pvc

cat >ecc-spark-pvc.yaml <<EOF
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: ecc-spark-pvc-static
  namespace: ecc-spark-cluster
spec:
  accessModes:
    #匹配模式
    - ReadWriteOnce
  resources:
    requests:
      storage: 10Gi

EOF

3、spark master创建

spark master分为两个部分，一个是类型为ReplicationController的主体，命名为ecc-spark-master.yaml，另一部分为一个service，暴露master的7077端口给slave使用。
（1）可调节参数

• 副本数(replicas)；
• args参数，日志打印路径；
• 挂载pvc(ecc-spark-pvc)，挂载到容器路径(/opt/usrjars)；
• resources资源分配等；

cat >ecc-spark-master.yaml <<EOF
kind: ReplicationController
apiVersion: v1
metadata:
  name: spark-master-controller
  namespace: ecc-spark-cluster
spec:
  replicas: 1
  selector:
    component: ecc-spark-master
  template:
    metadata:
      labels:
        component: ecc-spark-master
    spec:
      serviceAccountName: spark-cdp
      securityContext: {}
      dnsPolicy: ClusterFirst
      hostname: ecc-spark-master
      containers:
        - name: ecc-spark-master
          image: acpimgehub.com.cn/eccp_dev/spark:202107_YD_0714_v3.2
          imagePullPolicy: IfNotPresent
          command: ["/bin/sh"]
          args: ["-c","sh /opt/spark/sbin/start-master.sh && tail -f /opt/spark/logs/spark--org.apache.spark.deploy.master.Master-1-*"]
          ports:
            - containerPort: 7077
            - containerPort: 8080
          volumeMounts:
            - mountPath: /opt/usrjars/
              name: ecc-spark-pvc
          livenessProbe:
            failureThreshold: 9
            initialDelaySeconds: 2
            periodSeconds: 15
            successThreshold: 1
            tcpSocket:
              port: 7077
            timeoutSeconds: 10
          resources:
            requests:
              cpu: "200m"
              memory: "256Mi"
            limits:
              cpu: "1"
              memory: "1Gi"
      volumes:
        - name: ecc-spark-pvc
          persistentVolumeClaim:
            claimName: ecc-spark-pvc-static
---
kind: Service
apiVersion: v1
metadata:
  name: ecc-spark-master
  namespace: ecc-spark-cluster
spec:
  ports:
    - port: 7077
      targetPort: 7077
      name: spark
    - port: 8080
      targetPort: 8080
      name: http
  selector:
    component: ecc-spark-master

EOF

4、spark worker 创建

在启动spark worker脚本中需要传入master的地址，因为有kubernetes dns且设置了service的缘故，可以通过ecc-spark-master.ecc-spark-cluster:7077访问。
（1）可调节参数

• 副本数(replicas)，replicas设置为N即可启动N个worker；
• args参数，日志打印路径；
• 挂载pvc(ecc-spark-pvc)，挂载到容器路径(/opt/usrjars)；
• resources资源分配等；

cat >ecc-spark-worker.yaml <<EOF
kind: ReplicationController
apiVersion: v1
metadata:
  name: spark-worker-controller
  namespace: ecc-spark-cluster
spec:
  replicas: 2
  selector:
    component: ecc-spark-worker
  template:
    metadata:
      labels:
        component: ecc-spark-worker
    spec:
      serviceAccountName: spark-cdp
      securityContext: {}
      dnsPolicy: ClusterFirst
      hostname: ecc-spark-worker
      containers:
        - name: ecc-spark-worker
          image: acpimgehub.com.cn/eccp_dev/spark:202107_YD_0714_v3.2
          imagePullPolicy: IfNotPresent
          command: ["/bin/sh"]
          args: ["-c","sh /opt/spark/sbin/start-slave.sh spark://ecc-spark-master.ecc-spark-cluster:7077;tail -f /opt/spark/logs/spark--org.apache.spark.deploy.worker.Worker*"]
          ports:
            - containerPort: 8081
          volumeMounts:
            - mountPath: /opt/usrjars/
              name: ecc-spark-pvc
          resources:
            requests:
              cpu: "200m"
              memory: "128Mi"
            limits:
              cpu: "1"
              memory: "1Gi"
      volumes:
        - name: ecc-spark-pvc
          persistentVolumeClaim:
            claimName: ecc-spark-pvc-static

EOF

5、spark ui proxy

spark ui代理服务，image为elsonrodriguez/spark-ui-proxy:1.0在k8s集群里是不可或缺。它提供查看master的管理页面，并可以从master访问woker的ui页面(因每个worker都有自己的ui地址，ip分配很随机，这些ip只能在集群内部访问）。因此需要一个代理服务，从内部访问完需要的master ui页面后，返回给我们，这样我们只需要暴露一个代理的地址即可。

cat >ecc-spark-ui-proxy.yaml <<EOF
kind: ReplicationController
apiVersion: v1
metadata:
  name: spark-ui-proxy-controller
  namespace: ecc-spark-cluster
spec:
  replicas: 1
  selector:
    component: ecc-spark-ui-proxy
  template:
    metadata:
      labels:
        component: ecc-spark-ui-proxy
    spec:
      containers:
        - name: ecc-spark-ui-proxy
          image: elsonrodriguez/spark-ui-proxy:1.0
          ports:
            - containerPort: 80
          resources:
            requests:
              cpu: 100m
          args:
            - ecc-spark-master:8080
          livenessProbe:
            httpGet:
              path: /
              port: 80
            initialDelaySeconds: 120
            timeoutSeconds: 5
---
kind: Service
apiVersion: v1
metadata:
  name: ecc-spark-ui-proxy
  namespace: ecc-spark-cluster
spec:
  type: NodePort
  ports:
    - port: 80
      targetPort: 80
      nodePort: 32180
  selector:
    component: ecc-spark-ui-proxy

EOF

至此，spark整个集群搭建完毕。即可通过集群暴露的32180端口访问管理页面。