pankajkoti commented on code in PR #32310:
URL: https://github.com/apache/airflow/pull/32310#discussion_r1249395981


##########
docs/apache-airflow/core-concepts/executor/local.rst:
##########
@@ -47,3 +47,14 @@ Arguably, 
:class:`~airflow.executors.sequential_executor.SequentialExecutor` cou
 parallelism of just 1 worker, i.e. ``self.parallelism = 1``.
 This option could lead to the unification of the executor implementations, 
running
 locally, into just one 
:class:`~airflow.executors.local_executor.LocalExecutor` with multiple modes.
+
+.. note::
+
+   When using the ``@task`` decorator with multiple Schedulers configured with 
``executor = LocalExecutor`` in the [core] section of airflow.cfg, each 
scheduler will run a LocalExecutor. This means tasks would be processed in a 
distributed fashion across the machines running the Schedulers. 

Review Comment:
   Does this apply only when using the @task decorator? Or it is a general 
behaviour. If general, can we remove the leading part of the sentence which 
mentions about the case for @task decorator?



##########
docs/apache-airflow/core-concepts/executor/local.rst:
##########
@@ -47,3 +47,14 @@ Arguably, 
:class:`~airflow.executors.sequential_executor.SequentialExecutor` cou
 parallelism of just 1 worker, i.e. ``self.parallelism = 1``.
 This option could lead to the unification of the executor implementations, 
running
 locally, into just one 
:class:`~airflow.executors.local_executor.LocalExecutor` with multiple modes.
+
+.. note::
+
+   When using the ``@task`` decorator with multiple Schedulers configured with 
``executor = LocalExecutor`` in the [core] section of airflow.cfg, each 
scheduler will run a LocalExecutor. This means tasks would be processed in a 
distributed fashion across the machines running the Schedulers. 

Review Comment:
   ```suggestion
      When using the ``@task`` decorator with multiple Schedulers configured 
with ``executor = LocalExecutor`` in the ``[core]`` section of your 
``airflow.cfg``, each scheduler will run a LocalExecutor. This means tasks 
would be processed in a distributed fashion across the machines running the 
Schedulers. 
   ```



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