👉 Window computing is a distributed computing paradigm that processes data within a limited, time-bound "window" of recent data, rather than relying on the entire dataset. This approach optimizes performance and resource utilization by focusing computation on the most relevant and recent information, typically within a specified time frame (e.g., the last 10 or 100 seconds). Unlike traditional batch processing, which analyzes data in large chunks, window computing allows for real-time or near-real-time analytics, making it ideal for applications requiring immediate insights, such as fraud detection, real-time monitoring, and predictive analytics. By limiting the scope to a window of data, it reduces computational overhead and network traffic, enabling efficient processing even with large volumes of streaming data.
