- Releases Notes and Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- Operation Guide
- SQL Developer Guide
- Python Developer Guide
- ETL Developer Guide
- FAQ
- Contact Us
- Releases Notes and Announcements
- Product Introduction
- Purchase Guide
- Getting Started
- Operation Guide
- SQL Developer Guide
- Python Developer Guide
- ETL Developer Guide
- FAQ
- Contact Us
Stream Compute Service supports development of batch jobs of the following types: JAR and Python.
JAR job
The following example shows how to configure the batch job execution mode in the JAR job code.
StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();env.setRuntimeMode(RuntimeExecutionMode.BATCH);
1. Change
RuntimeExecutionMode.STREAMING to RuntimeExecutionMode.BATCH in a streaming job.2. Package the modified job into a .jar file and upload it to Dependencies in the platform.
3. Use the uploaded .jar file to complete the development of the JAR batch job in the platform.
Python job
The following example shows how to configure the batch job execution mode in the Python job code.
env_settings = EnvironmentSettings.new_instance().in_batch_mode().use_blink_planner().build()table_env = TableEnvironment.create(env_settings)
1. Change
EnvironmentSettings.new_instance().in_streaming_mode() to EnvironmentSettings.new_instance().in_batch_mode() in a streaming job. For details, see Intro to the Python Table API.2. Package the modified job into a .py file and upload it to Dependencies in the platform.
3. Use the uploaded .py file to complete the development of the Python batch job in the platform.
是
否
本页内容是否解决了您的问题？