deployment.md

部署与运行

seatunnel 依赖Java运行环境和Spark，详细的seatunnel 安装步骤参考安装seatunnel

下面重点说明不同平台的运行方式:

在本地以local方式运行seatunnel

./bin/start-seatunnel.sh --master local[4] --deploy-mode client --config ./config/application.conf

在Spark Standalone集群上运行seatunnel

# client 模式
./bin/start-seatunnel.sh --master spark://207.184.161.138:7077 --deploy-mode client --config ./config/application.conf

# cluster 模式
./bin/start-seatunnel.sh --master spark://207.184.161.138:7077 --deploy-mode cluster --config ./config/application.conf

在Yarn集群上运行seatunnel

# client 模式
./bin/start-seatunnel.sh --master yarn --deploy-mode client --config ./config/application.conf

# cluster 模式
./bin/start-seatunnel.sh --master yarn --deploy-mode cluster --config ./config/application.conf

在Mesos上运行seatunnel

# cluster 模式
./bin/start-seatunnel.sh --master mesos://207.184.161.138:7077 --deploy-mode cluster --config ./config/application.conf

---

start-seatunnel.sh 的master, deploy-mode参数的含义与Spark master, deploy-mode相同， 可参考: Spark Submitting Applications

如果要指定seatunnel运行时占用的资源大小，或者其他Spark参数，可以在--config指定的配置文件里面指定：

spark {
  spark.executor.instances = 2
  spark.executor.cores = 1
  spark.executor.memory = "1g"
  ...
}
...

关于如何配置seatunnel, 请见seatunnel 配置