Hi Yik San,
You can check whether the execution environment used is
`LocalStreamEnvironment` and you can get the class object corresponding to
the corresponding java object through py4j in PyFlink. You can take a look
at the example I wrote below, I hope it will help you
```
from pyflink.table import EnvironmentSettings, StreamTableEnvironment
from pyflink.datastream import StreamExecutionEnvironment
from pyflink.java_gateway import get_gateway
from py4j.java_gateway import get_java_class
def test():
env = StreamExecutionEnvironment.get_execution_environment()
table_env = StreamTableEnvironment.create(
env, environment_settings=EnvironmentSettings.new_instance()
.in_streaming_mode().use_blink_planner().build())
gateway = get_gateway()
# get the execution environment class
env_class = table_env._j_tenv.getPlanner().getExecEnv().getClass()
# get the LocalStreamEnvironment class
local_stream_environment_class = get_java_class(
gateway.jvm.org.apache.flink.streaming.api.environment.LocalStreamEnvironment)
print(env_class == local_stream_environment_class)
if __name__ == '__main__':
test()
```
Yik San Chan <evan.chanyik...@gmail.com> 于2021年5月5日周三 下午12:04写道：
> Hi,
>
> According to
> https://ci.apache.org/projects/flink/flink-docs-release-1.13/docs/dev/python/faq/
>
> > When executing jobs in mini cluster(e.g. when executing jobs in IDE)
> ... please remember to explicitly wait for the job execution to finish as
> these APIs are asynchronous.
>
> I hope my program will be able to run in both local mode as well as in
> remote mode. Therefore I hope to do something like:
>
> ```python
> result = ...
> if local_mode:
> result.wait()
> else:
> result
> ```
>
> Is there a way to tell if the program is run under local mode vs. remote
> mode?
>
> Best,
> Yik San
>
