[FLINK-18598][python][docs] Add instructions for asynchronous execute in PyFlink doc.

docs/dev/python/faq.md

@@ -52,6 +52,21 @@ $ source venv/bin/activate
 $ python xxx.py
 {% endhighlight %}
 
+**Note:** When executing jobs in mini-cluster asynchronously (e.g. TableEnvironment.execute_sql, StatementSet.execute, 
+etc in the Python Table API; StreamExecutionEnvironment.execute_async in the Python DataStream API), remember to  get a 
+`JobClient` to wait for the execution to be finished, or the program will exit directly before the submitted job is 
+finished. Please refer to the code snippet bellow:
+
+{% highlight python %}
+# execute SQL / Table API query asynchronously
+t_result = table_env.execute_sql(...)
+t_result.get_job_client().get_job_execution_result().result()
+
+# execute DataStream Job asynchronously
+job_client = stream_execution_env.execute_async('My DataStream Job')
+job_client.get_job_execution_result().result()
+{% endhighlight %}
+
 #### Cluster
 
 {% highlight shell %}

docs/dev/python/faq.zh.md

@@ -51,6 +51,20 @@ $ source venv/bin/activate
 $ python xxx.py
 {% endhighlight %}
 
+**注意:** 当在 mini-cluster 环境异步执行作业的时 (如 Python Table API 的 TableEnvironment.execute_sql, StatementSet.execute, 
+和 Python DataStream API 的 StreamExecutionEnvironment.execute_async)，记得用返回的 `JobClient` 等待作业结束，否则程序会在已提
+交的作业执行完之前就结束退出，以致无法观测到已提交作业的执行结果。请参考如下代码：
+
+{% highlight python %}
+# 异步执行 SQL / Table API 查询
+t_result = table_env.execute_sql(...)
+t_result.get_job_client().get_job_execution_result().result()
+
+# 异步提交 DataStream 作业
+job_client = stream_execution_env.execute_async('My DataStream Job')
+job_client.get_job_execution_result().result()
+{% endhighlight %}
+
 #### 集群（Cluster）
 
 {% highlight shell %}