At a high level, we can consider state in stream processing as memory in operators that remembers information about past input and can be used to influence the processing of future input.In contrast, operators in stateless stream processing only consider their current inputs, without further context and knowledge about the past. A simple example to illustrate this difference: let us consider a source stream that emits events with schema e = {event_id:int, event_value:int}. Our goal is, for each event, to extract and output the event_value. We can easily achieve this with a simple source-map-sink pipeline, where the map function extracts the event_value from the event and emits it downstream to an outputting sink. This is an instance of stateless stream processing.In this case, our map function obviously needs some way to remember the event_value from a past event — and so this is an instance of stateful stream processing.For high throughput and low latency in this setting, network communications among t