Hi Xingbo, Thank you!
On Thu, May 6, 2021 at 10:01 AM Xingbo Huang <hxbks...@gmail.com> wrote: > 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 >> >
