Stream Processing Engines (SPEs) execute long-running queries on unbounded data streams. They follow an interpretation-based processing model and do not perform runtime …
Window aggregation is a core operation in data stream processing. Existing aggregation techniques focus on reducing latency, eliminating redundant computations, and minimizing …
In this paper, we present the first comprehensive survey of window types for stream processing systems which have been presented in research and commercial systems. We …
Window aggregation queries are a core part of streaming applications. To support window aggregation efficiently, stream processing engines face a trade-off between exploiting …
Computing aggregates over windows is at the core of virtually every stream processing job. Typical stream processing applications involve overlapping windows and, therefore, cause …
Window aggregations and windowed joins are central operators of modern real-time analytic workloads and significantly impact the performance of stream processing systems …
Efficient video processing is a critical component in many IoMT applications to detect events of interest. Presently, many window optimization techniques have been proposed in event …
Window aggregation is a core operation in data stream processing. Existing aggregation techniques focus on reducing latency, eliminating redundant computations, or minimizing …
Sliding-window aggregation derives a user-defined summary of the most-recent portion of a data stream. For in-order streams, each window change can be handled in O (1) time even …