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这篇文章主要介绍了flink中如何实现基于k8s的环境搭建，具有一定借鉴价值，感兴趣的朋友可以参考下，希望大家阅读完这篇文章之后大有收获，下面让小编带着大家一起了解一下。
前面写了一些flink的基础组件，但是还没有说过flink的环境搭建，现在我们来说下基本的环境搭建
1. 使用StatefulSet的原因
对于Flink来说，使用sts的最大的原因是pod的hostname是有序的；这样潜在的好处有
hostname为-0和-1的pod可以直接指定为jobmanager；可以使用一个statefulset启动一个cluster，而deployment必须2个；Jobmanager和TaskManager分别独立的deployment
pod由于各种原因fail后，由于StatefulSet重新拉起的pod的hostname不变，集群recover的速度理论上可以比deployment更快（deployment每次主机名随机）
2.使用StatefulSet部署Flink
2.1 docker的entrypoint
由于要由主机名来判断是启动jobmanager还是taskmanager，因此需要在entrypoint中去匹配设置的jobmanager的主机名是否有一致
传入参数为：cluster ha；则自动根据主机名判断启动那个角色；也可以直接指定角色名称
docker-entrypoint.sh的脚本内容如下：
#!/bin/sh
# If unspecified, the hostname of the container is taken as the JobManager address
ACTION_CMD="$1"
# if use cluster model, pod ${JOB_CLUSTER_NAME}-0,${JOB_CLUSTER_NAME}-1 as jobmanager
if [ ${ACTION_CMD} == "cluster" ]; then
jobmanagers=(${JOB_MANGER_HOSTS//,/ })
ACTION_CMD="taskmanager"
for i in ${!jobmanagers[@]}
do
if [ "$(hostname -s)" == "${jobmanagers[i]}" ]; then
ACTION_CMD="jobmanager"
echo "pod hostname match jobmanager config host, change action to jobmanager."
fi
done
fi
# if ha model, replace ha configuration
if [ "$2" == "ha" ]; then
sed -i -e "s|high-availability.cluster-id: cluster-id|high-availability.cluster-id: ${FLINK_CLUSTER_IDENT}|g" "$FLINK_CONF_DIR/flink-conf.yaml"
sed -i -e "s|high-availability.zookeeper.quorum: localhost:2181|high-availability.zookeeper.quorum: ${FLINK_ZK_QUORUM}|g" "$FLINK_CONF_DIR/flink-conf.yaml"
sed -i -e "s|state.backend.fs.checkpointdir: checkpointdir|state.backend.fs.checkpointdir: hdfs:///user/flink/flink-checkpoints/${FLINK_CLUSTER_IDENT}|g" "$FLINK_CONF_DIR/flink-conf.yaml"
sed -i -e "s|high-availability.storageDir: hdfs:///flink/ha/|high-availability.storageDir: hdfs:///user/flink/ha/${FLINK_CLUSTER_IDENT}|g" "$FLINK_CONF_DIR/flink-conf.yaml"
fi
if [ ${ACTION_CMD} == "help" ]; then
echo "Usage: $(basename "$0") (cluster ha|jobmanager|taskmanager|local|help)"
exit 0
elif [ ${ACTION_CMD} == "jobmanager" ]; then
JOB_MANAGER_RPC_ADDRESS=${JOB_MANAGER_RPC_ADDRESS:-$(hostname -f)}
echo "Starting Job Manager"
sed -i -e "s/jobmanager.rpc.address: localhost/jobmanager.rpc.address: ${JOB_MANAGER_RPC_ADDRESS}/g" "$FLINK_CONF_DIR/flink-conf.yaml"
sed -i -e "s/jobmanager.heap.mb: 1024/jobmanager.heap.mb: ${JOB_MANAGER_HEAP_MB}/g" "$FLINK_CONF_DIR/flink-conf.yaml"
echo "config file: " && grep '^[^\n#]' "$FLINK_CONF_DIR/flink-conf.yaml"
exec "$FLINK_HOME/bin/jobmanager.sh" start-foreground cluster
elif [ ${ACTION_CMD} == "taskmanager" ]; then
TASK_MANAGER_NUMBER_OF_TASK_SLOTS=${TASK_MANAGER_NUMBER_OF_TASK_SLOTS:-$(grep -c ^processor /proc/cpuinfo)}
echo "Starting Task Manager"
sed -i -e "s/taskmanager.heap.mb: 1024/taskmanager.heap.mb: ${TASK_MANAGER_HEAP_MB}/g" "$FLINK_CONF_DIR/flink-conf.yaml"
sed -i -e "s/taskmanager.numberOfTaskSlots: 1/taskmanager.numberOfTaskSlots: $TASK_MANAGER_NUMBER_OF_TASK_SLOTS/g" "$FLINK_CONF_DIR/flink-conf.yaml"
echo "config file: " && grep '^[^\n#]' "$FLINK_CONF_DIR/flink-conf.yaml"
exec "$FLINK_HOME/bin/taskmanager.sh" start-foreground
elif [ ${ACTION_CMD} == "local" ]; then
echo "Starting local cluster"
exec "$FLINK_HOME/bin/jobmanager.sh" start-foreground local
fi
exec "$@"
2.2. 使用ConfigMap分发hdfs和flink配置文件
ConfigMap介绍参考：
https://kubernetes.io/docs/tasks/configure-pod-container/configure-pod-configmap/#create-configmaps-from-files
Q：为什么使用ConfigMap
A：由于hadoop配置文件在不同的环境不一样，不方便打包到镜像里面；因此合适的方式就只有2种，使用ConfigMap和Pod的InitContainer。使用InitContainer的话，可以wget获取远程的一个配置文件，但是这样还需要依赖一个配置服务。相比而已，ConfigMap更简单。
创建ConfigMap
[root@rc-mzgjg ~]# kubectl create configmap hdfs-conf --from-file=hdfs-site.xml --from-file=core-site.xml
[root@rc-mzgjg ~]# kubectl create configmap flink-conf --from-file=flink-conf/log4j-console.properties --from-file=flink-conf/flink-conf.yaml
使用describe命令查看创建的名词为hdfs-conf的ConfigMap，会显示文件的内容到控制台
[root@rc-mzgjg ~]# kubectl describe configmap hdfs-conf
Name: hdfs-conf
Namespace: default
Labels: <none>
Annotations: <none>
Data
====
core-site.xml:
通过volumeMounts使用ConfigMap
Pod的Container要使用配置文件，则可以通过volumeMounts方式挂载到Container中。如下demo所示，将配置文件挂载到/home/xxxx/conf/hadoop目录下
apiVersion: apps/v1 kind: StatefulSet metadata: name: flink-jm spec: selector: matchLabels: app: flink-jm serviceName: flink-jm replicas: 2 podManagementPolicy: Parallel template: metadata: labels: app: flink-jm spec: terminationGracePeriodSeconds: 2 containers: - name: test imagePullPolicy: Always image: ip:5000/test:latest args: ["sleep", "1d"] volumeMounts: - name: hdfs-conf mountPath: /home/xxxx/conf/hadoop volumes: - name: hdfs-conf configMap: # Provide the name of the ConfigMap containing the files you want to add to the container name: hdfs-conf
创建好Pod后，查看配置文件的挂载
[hadoop@flink-jm-0 hadoop]$ ll /home/xxxx/conf/hadoop
total 0
lrwxrwxrwx. 1 root root 20 Apr 9 06:54 core-site.xml -> ..data/core-site.xml
lrwxrwxrwx. 1 root root 20 Apr 9 06:54 hdfs-site.xml -> ..data/hdfs-site.xml
配置文件是链接到了..data目录
1.10才能支持Pod多Container的namespace共享
最初的想法是一个Pod里面多个Container，然后配置文件是其中一个Container；测试验证起数据目录并不能互相访问；如预想的配置，其中一个Container里面的image是hdfs-conf的配置文件
containers: - name: hdfs-conf imagePullPolicy: Always image: ip:5000/hdfs-dev:2.6 args: ["sleep", "1d"] - name: flink-jm imagePullPolicy: Always image: ip:5000/flink:1.4.2
实际验证，两个Container的只能共享网络，文件目录彼此看不见
“Share Process Namespace between Containers in a Pod”这个是Kubernates 1.10才开始支持，参考
https://kubernetes.io/docs/tasks/configure-pod-container/share-process-namespace/
2.3 StatefulSet的配置
Flink的配置文件和hadoop的配置文件，依赖ConfigMap来分发
环境变量名称 | 参数 | 内容 | 说明 |
|
|---|---|---|---|---|
FLINK_CLUSTER_IDENT | namespace/StatefulSet.name | default/flink-cluster | 用来做zk ha设置和hdfs checkpiont的根目录 | |
FLINK_ZK_QUORUM | env:FLINK_ZK_QUORUM | ip:2181 | HA ZK的地址 | |
JOB_MANAGER_HEAP_MB | env:JOB_MANAGER_HEAP_MB value:containers.resources.memory.limit -1024 | 512 | JM的Heap大小，由于存在Netty的堆外内存，需要小于container.resources.memory.limits；否则容易OOM kill | |
JOB_MANGER_HOSTS | StatefulSet.name-0,StatefulSet.name-1 | flink-cluster-0,flink-cluster-1 | JM的主机名，短主机名；可以不用FQDN | |
TASK_MANAGER_HEAP_MB | env:TASK_MANAGER_HEAP_MB value: containers.resources.memory.limit -1024 | 512 | TM的Heap大小，由于存在Netty的堆外内存，需要小于container.resources.memory.limits；否则容易OOM kill | |
TASK_MANAGER_NUMBER_OF_TASK_SLOTS | containers.resources.cpu.limits | 2 | TM的slot数量，根据resources.cpu.limits来设置 |
Pod的imagePullPolicy策略，测试环境Always，每次都pull，方便验证；线上则是IfNotPresent；线上如果对images做了变更，必须更改images的tag
完整的内容可以参考如下：
# headless service for statefulset apiVersion: v1 kind: Service metadata: name: flink-cluster labels: app: flink-cluster spec: clusterIP: None ports: - port: 8080 name: ui selector: app: flink-cluster --- # create flink statefulset apiVersion: apps/v1 kind: StatefulSet metadata: name: flink-cluster spec: selector: matchLabels: app: flink-cluster serviceName: flink-cluster replicas: 4 podManagementPolicy: Parallel template: metadata: labels: app: flink-cluster spec: terminationGracePeriodSeconds: 2 containers: - name: flink-cluster imagePullPolicy: Always image: ip:5000/flink:1.4.2 args: ["cluster", "ha"] volumeMounts: - name: hdfs-conf mountPath: /home/xxxx/conf/hadoop - name: flink-conf mountPath: /home/xxxx/conf/flink - name: flink-log mountPath: /home/xxxx/logs resources: requests: memory: "1536Mi" cpu: 1 limits: memory: "1536Mi" cpu: 2 env: - name: JOB_MANGER_HOSTS value: "flink-cluster-0,flink-cluster-1" - name: FLINK_CLUSTER_IDENT value: "default/flink-cluster" - name: TASK_MANAGER_NUMBER_OF_TASK_SLOTS value: "2" - name: FLINK_ZK_QUORUM value: "ip:2181" - name: JOB_MANAGER_HEAP_MB value: "512" - name: TASK_MANAGER_HEAP_MB value: "512" ports: - containerPort: 6124 name: blob - containerPort: 6125 name: query - containerPort: 8080 name: flink-ui volumes: - name: hdfs-conf configMap: # Provide the name of the ConfigMap containing the files you want to add to the container name: hdfs-conf - name: flink-conf configMap: name: flink-conf - name: flink-log hostPath: # directory location on host path: /tmp # this field is optional type: Directory
3. 测试环境对外暴露Flink UI
由于测试环境使用Flannel进行网络通信，在K8S集群外部无法访问到Flink UI的IP和端口，因此需要通过NodePort方式将内部IP映射出来。配置如下：
# only for test k8s cluster # use service to expose flink jobmanager 0's web port apiVersion: v1 kind: Service metadata: labels: app: flink-cluster statefulset.kubernetes.io/pod-name: flink-cluster-0 name: flink-web-0 namespace: default spec: ports: - port: 8080 protocol: TCP targetPort: 8080 selector: app: flink-cluster statefulset.kubernetes.io/pod-name: flink-cluster-0 type: NodePort --- # use service to expose flink jobmanager 1's web port apiVersion: v1 kind: Service metadata: labels: app: flink-cluster statefulset.kubernetes.io/pod-name: flink-cluster-1 name: flink-web-1 namespace: default spec: ports: - port: 8080 protocol: TCP targetPort: 8080 selector: app: flink-cluster statefulset.kubernetes.io/pod-name: flink-cluster-1 type: NodePort
4. 服务部署状态
执行完前面操作后，可以查看到当前的StatefulSet状态
[root@rc-mzgjg ~]# kubectl get sts flink-cluster -o wide
NAME DESIRED CURRENT AGE CONTAINERS IMAGES
flink-cluster 4 4 1h flink-cluster ip:5000/flink:1.4.2
容器的Pod状态
[root@rc-mzgjg ~]# kubectl get pod -l app=flink-cluster -o wide
NAME READY STATUS RESTARTS AGE IP NODE
flink-cluster-0 1/1 Running 0 1h ip1 ip5
flink-cluster-1 1/1 Running 0 1h ip2 ip6
flink-cluster-2 1/1 Running 0 1h ip3 ip7
flink-cluster-3 1/1 Running 0 1h ip4 ip8
相关的Service信息
[root@rc-mzgjg ~]# kubectl get svc -l app=flink-cluster -o wide
NAME TYPE CLUSTER-IP EXTERNAL-IP PORT(S) AGE SELECTOR
flink-cluster ClusterIP None <none> 8080/TCP 2h app=flink-cluster
flink-web-0 NodePort 10.254.8.103 <none> 8080:30495/TCP 1h app=flink-cluster,statefulset.kubernetes.io/pod-name=flink-cluster-0
flink-web-1 NodePort 10.254.172.158 <none> 8080:30158/TCP 1h app=flink-cluster,statefulset.kubernetes.io/pod-name=flink-cluster-1
根据Service的信息；可以通过任何一个k8s node的ip地址加PORT来访问Flink UI
这里主要说一下，在搭建的过程中遇到了一个和权限相关的问题
错误日志如下
ERROR setFile(null,true) call failed
FileNotFoundException:no such file or directory
原因：是因为flink服务缺少日志目录的权限
修改方式：
1.adduser flink 添加相应的用户
2.chown -R flink:flink /home/xxxx/logs
感谢你能够认真阅读完这篇文章，希望小编分享的“flink中如何实现基于k8s的环境搭建”这篇文章对大家有帮助，同时也希望大家多多支持亿速云，关注亿速云行业资讯频道，更多相关知识等着你来学习!
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