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 …

Modern Stream Processing Engines (SPEs) process large data volumes under tight latency
constraints. Many SPEs execute processing pipelines using message passing on shared …

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 …

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 overlap** windows and, therefore, cause …

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 …

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 …

Window aggregations and windowed joins are central operators of modern real-time
analytic workloads and significantly impact the performance of stream processing systems …

Window aggregation is a core operation in data stream processing. Existing aggregation
techniques focus on reducing latency, eliminating redundant computations, or minimizing …