??? Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 4/16: Skew mitigation ??? Vasiliki Kalavri |

Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 2/25: State Management Vasiliki Kalavri | Boston

??? Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 4/14: Stream processing optimizations ??? Vasiliki operator shares a lock with an upstream operator. • Satisfy deadlines: for applications with real-time constraints or QoS latency constraints. Batching Process multiple data elements in a single batch

Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 2/11: Windows and Triggers Vasiliki Kalavri | Boston input • e.g. joins, holistic aggregates • Compute on most recent events only • when providing real-time traffic information, you probably don't care about an accident that happened 2 hours ago • Recent

Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 1/21: Introduction Vasiliki Kalavri | Boston University 20% 7 Vasiliki Kalavri | Boston University 2020 Grading Scheme (2) Final Project (50%): • A real-time monitoring and anomaly detection framework • To be implemented individually Deliverables • Kalavri | Boston University 2020 Final Project You will use Apache Flink and Kafka to build a real-time monitoring and anomaly detection framework for datacenters. Your framework will: • Detect “suspicious”

University 2020 Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu CS 591 K1: Data Stream Processing and Analytics Spring 2020 2/06: Notions of time and progress Vasiliki Kalavri | Boston University 2020 Mobile

Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 1/23: Stream Processing Fundamentals Vasiliki Kalavri than being available in full before its processing begins. • Data streams are high-volume, real-time data that might be unbounded • we cannot store the entire stream in an accessible way • we have pre-aggregated, pre-processed streams and historical data Data Management Approaches 4 storage analytics static data streaming data Vasiliki Kalavri | Boston University 2020 DBMS vs. DSMS DBMS DSMS

??? Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 4/23: Cardinality and frequency estimation

??? Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 4/28: Graph Streaming ??? Vasiliki Kalavri | from scratch for every new edge? • Can we use graph synopses and summaries and compute graph analytics in one-pass? ??? Vasiliki Kalavri | Boston University 2020 Connectivity & Bipartite property

??? Vasiliki Kalavri | Boston University 2020 CS 591 K1: Data Stream Processing and Analytics Vasiliki (Vasia) Kalavri
 vkalavri@bu.edu Spring 2020 4/21: Sampling and filtering streams ??? Vasiliki