seatunnel k8s运行zeta引擎(local-mode模式)
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。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。4.将镜像load进k8s,这里用的minikube做演示。执行过install-plugin后的lib目录包含如下。6
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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_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
minikube image ls
查看镜像
6.创建seatunnel.streaming.conf
如下所示
env {
execution.parallelism = 1
job.mode = "STREAMING"
checkpoint.interval = 2000
}
source {
FakeSource {
result_table_name = "fake"
row.num = 160000
schema = {
fields {
name = "string"
age = "int"
}
}
}
}
transform {
}
sink {
Console {}
}
7.创建configmap
kubectl create cm seatunnel-config \
--from-file=seatunnel.streaming.conf=seatunnel.streaming.conf
8.创建seatunnel.yaml如下示例
apiVersion: v1
kind: Pod
metadata:
name: seatunneltest
spec:
containers:
- name: seatunnel
image: seatunnel:2.3.3
command: ["/bin/sh","-c","/opt/seatunnel/bin/seatunnel.sh --config /data/seatunnel.streaming.conf -e local"]
volumeMounts:
- name: seatunnel-config
mountPath: /data/seatunnel.streaming.conf
subPath: seatunnel.streaming.conf
volumes:
- name: seatunnel-config
configMap:
name: seatunnel-config
items:
- key: seatunnel.streaming.conf
path: seatunnel.streaming.conf
~
执行
kubectl apply -f seatunnel.yaml
查看pod结果如下
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