Add local mode for SQLFlow

[lhw362950217]

As discussed before, we'd better add a local mode for SQLFlow, because:

1. users may want a more light weight installation way, for just try out SQLFlow on her/his PC
2. developer may want a simpler way to debug the compiler and the generated code

Some thought about the local mode:

1. We can exclude Kubernetes from the framework, just generate a python file to run docker at local
2. We need to provide a mechanism to get track of the jobs and their log like in workflow mode
   • user submit a SQL program from Jupyter Notebook/CLI
   • SQLFlow server compile the program and generate a python file
   • SQLFlow server starts a process to run the python file
   • SQLFlow server returns a process id or a log file name as an identifier of the current task(the same way as workflow mode)
   • client poll the log using the identifier returned by SQLFlow server
3. If we go to an extreme of the local mode, we may only provide a compiler binary, which generate a python file, users can run the python code to do ml tasks, like discussed in this issue

[brightcoder01]

1. We can exclude Kubernetes from the framework, just generate a python file to run docker at local

Do we need Minikube here?

1. We need to provide a mechanism to get track of the jobs and their log like in workflow mode

   • user submit a SQL program from Jupyter Notebook/CLI

   • SQLFlow server compile the program and generate a python file

   • SQLFlow server starts a process to run the python file

   • SQLFlow server returns a process id or a log file name as an identifier of the current task(the same way as workflow mode)

   • client poll the log using the identifier returned by SQLFlow server

We need a sqlflowserver here, I believe it runs in a pod in Minikube.

[lhw362950217]

1. We can exclude Kubernetes from the framework, just generate a python file to run docker at local

Do we need Minikube here?

1. We need to provide a mechanism to get track of the jobs and their log like in workflow mode

   • user submit a SQL program from Jupyter Notebook/CLI
   • SQLFlow server compile the program and generate a python file
   • SQLFlow server starts a process to run the python file
   • SQLFlow server returns a process id or a log file name as an identifier of the current task(the same way as workflow mode)
   • client poll the log using the identifier returned by SQLFlow server

We need a sqlflowserver here, I believe it runs in a pod in Minikube.

SQLFlow server can run directly on a native machine, or in a Docker container. So, we may get rid of Minikube.