Kubernetes 运行flink（六）

概念：

Flink 由Job Manager和Task Manager两个部分组成，Job Manager负责协调流处理作业，管理作业的提交以及生命周期，并把工作分配给任务管理器。任务管理器执行实际的流处理逻辑，同一个时间只能一个活跃的Job Manager，但可以有多个Task manager。

Flink还引入Checkpoint机制，来周期性记录各种流处理操作的状态，并且进行持久化存储，在从故障恢复的时候，流处理作业可以从最新的检查点继续执行。checkpoint也是由job Manager进行协调更新。

 

1: 具体部署步骤

job Manager和task Manager都采用deployment进行部署， 另外还需要定义相应的configmap和service文件， 使其能够暴露一个端口供外界访问

 

首现配置ConfigMap

flink-configuration-configmap.yaml

apiVersion: v1
kind: ConfigMap
metadata:
  name: flink-config
  labels:
    app: flink
data:
  flink-conf.yaml: |+
    jobmanager.rpc.address: flink-jobmanager
    taskmanager.numberOfTaskSlots: 1
    blob.server.port: 6124
    jobmanager.rpc.port: 6123
    taskmanager.rpc.port: 6122
    jobmanager.heap.size: 1024m
    taskmanager.heap.size: 1024m
  log4j.properties: |+
    log4j.rootLogger=INFO, file
    log4j.logger.akka=INFO
    log4j.logger.org.apache.kafka=INFO
    log4j.logger.org.apache.hadoop=INFO
    log4j.logger.org.apache.zookeeper=INFO
    log4j.appender.file=org.apache.log4j.FileAppender
    log4j.appender.file.file=${log.file}
    log4j.appender.file.layout=org.apache.log4j.PatternLayout
    log4j.appender.file.layout.ConversionPattern=%d{yyyy-MM-dd HH:mm:ss,SSS} %-5p %-60c %x - %m%n
    log4j.logger.org.apache.flink.shaded.akka.org.jboss.netty.channel.DefaultChannelPipeline=ERROR, file

主要是把日志文件以及配置文件和创建的Pod解耦开；

相应的deployment和configMap绑定主要通过在volumes那里，configMap指定定义好的configMap的名称和items项进行定义。

jobManager-deployment.yaml

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: flink-jobmanager
spec:
  replicas: 1
  template:
    metadata:
      labels:
        app: flink
        component: jobmanager
    spec:
      containers:
      - name: jobmanager
        image: flink:latest
        workingDir: /opt/flink
        command: ["/bin/bash", "-c", "$FLINK_HOME/bin/jobmanager.sh start;\
          while :;
          do
            if [[ -f $(find log -name '*jobmanager*.log' -print -quit) ]];
              then tail -f -n +1 log/*jobmanager*.log;
            fi;
          done"]
        ports:
        - containerPort: 6123
          name: rpc
        - containerPort: 6124
          name: blob
        - containerPort: 8081
          name: ui
        livenessProbe:
          tcpSocket:
            port: 6123
          initialDelaySeconds: 30
          periodSeconds: 60
        volumeMounts:
        - name: flink-config-volume
          mountPath: /opt/flink/conf
      volumes:
      - name: flink-config-volume
        configMap:
          name: flink-config
          items:
          - key: flink-conf.yaml
            path: flink-conf.yaml
          - key: log4j.properties
            path: log4j.properties

taskmanager-deployment.yaml

apiVersion: extensions/v1beta1
kind: Deployment
metadata:
  name: flink-taskmanager
spec:
  replicas: 2
  template:
    metadata:
      labels:
        app: flink
        component: taskmanager
    spec:
      containers:
      - name: taskmanager
        image: flink:latest
        workingDir: /opt/flink
        command: ["/bin/bash", "-c", "$FLINK_HOME/bin/taskmanager.sh start; \
          while :;
          do
            if [[ -f $(find log -name '*taskmanager*.log' -print -quit) ]];
              then tail -f -n +1 log/*taskmanager*.log;
            fi;
          done"]
        ports:
        - containerPort: 6122
          name: rpc
        livenessProbe:
          tcpSocket:
            port: 6122
          initialDelaySeconds: 30
          periodSeconds: 60
        volumeMounts:
        - name: flink-config-volume
          mountPath: /opt/flink/conf/
      volumes:
      - name: flink-config-volume
        configMap:
          name: flink-config
          items:
          - key: flink-conf.yaml
            path: flink-conf.yaml
          - key: log4j.properties
            path: log4j.properties

jobmanager-service.yaml

apiVersion: v1
kind: Service
metadata:
  name: flink-jobmanager
spec:
  type: ClusterIP
  ports:
  - name: rpc
    port: 6123
  - name: blob
    port: 6124
  - name: ui
    port: 8081
  selector:
    app: flink
    component: jobmanager

安装教程地址：https://ci.apache.org/projects/flink/flink-docs-stable/ops/deployment/kubernetes.html

 

执行kubectl命令：

kubectl create -f flink-configuration-configmap.yaml

kubectl create -f jobmanager-service.yaml

kubectl create -f jobmanager-deployment.yaml

kubectl create -f taskmanager-deployment.yaml

 

2: 设置UI访问

kubectl proxy

1）运行kubectl proxy

2）前往 http://localhost:8001/api/v1/namespaces/default/services/flink-jobmanager:ui/proxy

 

kubectl port-forward

1)kubectl port-forward flink-jobmanager-845f844595-lcpxw 8081:8081

2)访问http://localhost:8081

 

相关联的项目https://github.com/lyft/flinkk8soperator