Queuing theory models: for latency objectives • Control theory models: e.g., PID controller • Rule-based models, e.g. if CPU utilization > 70% => scale out • Analytical dataflow-based models Action Predictive: at-once for all operators 8 ??? Vasiliki Kalavri | Boston University 2020 Queuing theory models 9 • Metrics • service time and waiting time per tuple and per task • total time spent processing predictive, at-once for all operators ??? Vasiliki Kalavri | Boston University 2020 Queuing theory models 9 • Metrics • service time and waiting time per tuple and per task • total time spent processing

maintains state: • rolling aggregations • window contents • input offsets • machine learning models State in dataflow computations 3 Vasiliki Kalavri | Boston University 2020 Logic State maintains state: • rolling aggregations • window contents • input offsets • machine learning models State in dataflow computations 3 Vasiliki Kalavri | Boston University 2020 Logic State maintains state: • rolling aggregations • window contents • input offsets • machine learning models State in dataflow computations 3 Vasiliki Kalavri | Boston University 2020 4 Distributed streaming

analytics … Building a stream processor… 8 ? Vasiliki Kalavri | Boston University 2020 Basic Stream Models Vasiliki Kalavri | Boston University 2020 A stream can be viewed as a massive, dynamic, one-dimensional previously emitted items 12:01 12:02 12:00 18 32 8 32 32 32 8 72 64 80 base derived Which basic models do base and derived streams correspond to? Vasiliki Kalavri | Boston University 2020 Results as Boston University 2020 Summary Today you learned: • stream representations, stream processing models • streaming applications and use-cases • different approaches to data management • the relational

maintains state: • rolling aggregations • window contents • input offsets • machine learning models State in dataflow computations 2 Vasiliki Kalavri | Boston University 2020 • No explicit state

Database Theory (ICDT’05). • Yan-Nei Law, Haixun Wang, and Carlo Zaniolo. Query languages and data models for database sequences and data streams. In Proceedings of the Thirtieth international conference