Algorithms for Windowed Aggregations and Joins on Distributed Stream Processing Systems
Window aggregations and windowed joins are central operators of modern real-time
analytic workloads and significantly impact the performance of stream processing systems …
analytic workloads and significantly impact the performance of stream processing systems …
Big data analytics applying the fusion approach of multicriteria decision making with deep learning algorithms
SLV Papineni, S Yarlagadda, H Akkineni… - arXiv preprint arXiv …, 2021 - arxiv.org
Data is evolving with the rapid progress of population and communication for various types
of devices such as networks, cloud computing, Internet of Things (IoT), actuators, and …
of devices such as networks, cloud computing, Internet of Things (IoT), actuators, and …
Cpix: Real-time analytics over out-of-order data streams by incremental sliding-window aggregation
Stream processing is used in various fields. In the field of big data, stream aggregation is a
popular processing technique, but it suffers serious setbacks when the order of events (eg …
popular processing technique, but it suffers serious setbacks when the order of events (eg …
Generating reproducible out-of-order data streams
Evaluating modern stream processing systems in a reproducible manner requires data
streams with different data distributions, data rates, and real-world characteristics such as …
streams with different data distributions, data rates, and real-world characteristics such as …
O (1)-Time Complexity for Fixed Sliding-Window Aggregation Over Out-of-Order Data Streams
Sliding-window aggregation is one of the core operations in processing and analyzing data
streams, but it seriously suffers from the unordered events or elements from data streams …
streams, but it seriously suffers from the unordered events or elements from data streams …