flink run -py 和 python run 的区别

Question

I recently working on learning pyflink, but I was a little bit confused. We know that pyflink table API convert stream/batch into table and do some work on it and finally sink to where u want. However, there are several ways to create table env:

For batch example:

t_config = TableConfig()
env = ExecutionEnvironment.get_execution_environment()
t_env = BatchTableEnvironment.create(env, t_config)

and

env_settings = EnvironmentSettings.new_instance().in_batch_mode().use_blink_planner().build()
t_env = BatchTableEnvironment.create(evnironment_settings = env_settings)

but I found one of them only work for flink run -py batch.py, some other styles can be run as python batch.py for local run.

My question is what the difference of executionEnvironment and BatchTableEnvironment/StreamTableEnvironment, and when can use flink run -py and when can run by python interpreter with pyflink installed?

Thx

Answer 1

with flink run there is some configuration to set in .sh , you could consider the flink run is some bash scripts plus to the python xx itself.

for more information you could go to $FLINK_HOME/bin/flink or flink-dist/src/flink-bin/flink

Answer 2

The flink run way is used to submit jobs to run on the cluster. And the way of python xxx.py is to run the job directly in the local memory