Data Partitioning (Streaming)

Data Partitioning in streaming involves distributing incoming data events across multiple parallel instances of processing operators based on a specific key within the data (e.g., user ID, sensor ID). This is essential for achieving scalability, as it allows processing load to be spread across multiple nodes or cores. Correct partitioning is crucial for stateful operations like joins and aggregations to ensure related data is processed together.