Apache SeaTunnel k8s 集群模式 Zeta 引擎部署指南

SeaTunnel提供了一种运行Zeta引擎(cluster-mode)的方法，可以让Kubernetes在本地运行Zeta引擎，实现更高效的应用程序部署和管理。在本文中，我们将探索SeaTunnel k8s运行zeta引擎(cluster-mode模式)的更多信息，了解如何更好地利用Zeta引擎的优势。

1. 将SeaTunnel上传至服务器上。我之前已经解压并执行过install-plugin.sh，这里为了方便，我直接用的执行过install-plugin.sh脚本之后的seatunnel做演示。

执行过install-plugin后的lib目录包含如下：

tar -zxvf apache-seatunnel-2.3.3-bin.tar.gz
sh apache-seatunnel-2.3.3/bin/install-plugin.sh
tar -czvf  apache-seatunnel-2.3.3-bin.tar.gz  apache-seatunnel-2.3.3

2. 构建seatunnel镜像。在安装seatunnel的同级文件夹下创建Dockerfile。配置如下，可自行选择版本：

   FROM openjdk:8
   ENV SEATUNNEL_HOME="/opt/seatunnel"
   ENV SEATUNNEL_VERSION="2.3.3"
   COPY /apache-seatunnel-${SEATUNNEL_VERSION}-bin.tar.gz /opt/apache-seatunnel-${SEATUNNEL_VERSION}-bin.tar.gz
   WORKDIR /opt
   RUN tar -xzvf apache-seatunnel-${SEATUNNEL_VERSION}-bin.tar.gz
   RUN mv apache-seatunnel-${SEATUNNEL_VERSION} seatunnel
   RUN rm -f /opt/apache-seatunnel-${SEATUNNEL_VERSION}-bin.tar.gz
   WORKDIR /opt/seatunnel

执行命令

docker build -t seatunnel:2.3.3 -f Dockerfile.

3. 查看镜像

docker images

如下所示镜像

4. 将镜像load进k8s，这里用的minikube做演示

   minikube image load seatunnel:2.3.3

   上述可参考：手把手教你掌握SeaTunnel k8s运行Zeta引擎本地模式的技巧

5. 创建configmap如下

   kubectl create configmap hazelcast-client  --from-file= config/hazelcast-client.yaml
   kubectl create configmap hazelcast  --from-file=config/hazelcast.yaml
   kubectl create configmap seatunnelmap  --from-file=config/seatunnel.yaml

6. 使用Reloader实现更新configmap后自动重启pod

wget https://raw.githubusercontent.com/stakater/Reloader/master/deployments/kubernetes/reloader.yaml

kubectl apply -f reloader.yaml

7. 创建seatunnel-cluster.yml如下

apiVersion: v1
kind: Service
metadata:
  name: seatunnel
spec:
  selector:
    app: seatunnel
  ports:
  - port: 5801
    name: seatunnel
  clusterIP: None
---
apiVersion: apps/v1
kind: StatefulSet
metadata:
  name: seatunnel
  annotations:
    configmap.reloader.stakater.com/reload: "hazelcast,hazelcast-client,seatunnelmap"
spec:
  serviceName: "seatunnel"
  replicas: 3
  selector:
    matchLabels:
      app: seatunnel
  template:
    metadata:
      labels:
        app: seatunnel
    spec:
      containers:
        - name: seatunnel
          image: seatunnel:2.3.3
          imagePullPolicy: IfNotPresent
          ports:
            - containerPort: 5801
              name: client
          command: ["/bin/sh","-c","/opt/seatunnel/bin/seatunnel-cluster.sh -DJvmOption=-Xms2G -Xmx2G"]
          resources:
            limits:
              cpu: "1"
              memory: 4G
            requests:
              cpu: "1"
              memory: 2G
          volumeMounts:
            - mountPath: "/opt/seatunnel/config/hazelcast.yaml"
              name: hazelcast
              subPath: hazelcast.yaml
            - mountPath: "/opt/seatunnel/config/hazelcast-client.yaml"
              name: hazelcast-client
              subPath: hazelcast-client.yaml
            - mountPath: "/opt/seatunnel/config/seatunnel.yaml"
              name: seatunnelmap
              subPath: seatunnel.yaml
      volumes:
        - name: hazelcast
          configMap:
            name: hazelcast
        - name: hazelcast-client
          configMap:
            name: hazelcast-client
        - name: seatunnelmap
          configMap:
            name: seatunnelmap

8. 执行

 kubectl apply -f seatunnel-cluster.yml

9. 修改configmap中的配置

kubectl edit cm hazelcast

修改集群地址 
这里采用的是headless service访问模式
一般pod之间访问其格式为 <pod-name>.<service-name>.<namespace>.svc.cluster.local

如下示例

• seatunnel-0.seatunnel.default.svc.cluster.local
• seatunnel-1.seatunnel.default.svc.cluster.local
• seatunnel-2.seatunnel.default.svc.cluster.local

友情提示：不要用tab，用空格 。不然会报错

kubectl edit cm hazelcast-client

kubectl edit cm seatunnelmap

此处改为自己的hdfs地址。

10. 可以看到如下

11. 待所有节点都更新完毕处于running状态后 可进入容器内查看路径是否已修改

kubectl exec -it seatunnel-0 /bin/bash
cat config/hazelcast.yaml

12. 在容器内查看日志

tail -200f logs/seatunnel-engine-server.log

我们发现集群已经正常运行.

13. 运行任务

我们可以再新打开一个连接，登录另一个pod节点执行任务来测试集群：

kubectl exec -it seatunnel-1 /bin/bash

bin/seatunnel.sh --config config/v2.streaming.conf.template

我们发现其他pod内也已经开始运行任务

原文链接：https://blog.csdn.net/weixin_41854429/article/details/132836402

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