Java is famous of its paradigm – Write once, Run anywhere – which was defined in 1995 by Sun Microsystems to illustrate the cross-platform benefits of the Java language. Apache Beam follows the similar principle but in regard to cross-platform data processing engines – Write pipeline once and Run it on every data processing engine . Beam achieves that by leveraging a conception of Beam Runner – the programming framework, which is responsible to translate a pipeline, written in Beam model way, into a code that can be run on required processing engine, like Apache Spark, Apache Flink, Google Dataflow, etc. All translations actually happen in runtime – users don’t even need to recompile their code to change a runner if all dependencies were already provided in compile time. Therefore, Beam already supports a bunch of different runners that can be easily used to run a user’s pipeline on different platforms. However, the classical runner translates user code only from and to the same SD