https://ci.apache.org/projects/flink/flink-docs-release-1.12/dev/datastream_execution_mode.html


Execution Mode (Batch/Streaming)


By enabling BATCH execution, we allow Flink to apply additional optimizations that we can only do when we know that our input is bounded. 
输入有界，启用BATCH执行，允许Flink应用额外的优化 

The BATCH execution mode can only be used for Jobs/Flink Programs that are bounded. 

STREAMING execution mode,can be used for both bounded and unbounded jobs.

execution.runtime-mode
STREAMING: The classic DataStream execution mode (default)
BATCH: Batch-style execution on the DataStream API
AUTOMATIC: Let the system decide based on the boundedness of the sources

bin/flink run -Dexecution.runtime-mode=BATCH examples/streaming/WordCount.jar

StreamExecutionEnvironment env = StreamExecutionEnvironment.getExecutionEnvironment();
env.setRuntimeMode(RuntimeExecutionMode.BATCH);


Task scheduling and network shuffles work differently for BATCH and STREAMING execution mode. 
Mostly due to the fact that we know our input data is bounded in BATCH execution mode, 
which allows Flink to use more efficient data structures and algorithms.


BATCH作业可以在更少的资源上执行(就TaskManagers的可用插槽而言)，因为系统可以一个接一个顺序执行任务

In BATCH mode, the configured state backend is ignored.