University of Cagliari
Data Stream Management System - Supporting Complex Event Processing
02 July 2012
Scuola di Dottorato in Scienze Matematiche e Informatiche
Il Prof. Carlo Zaniolo (University of California at Los Angeles – UCLA, USA) terrà il giorno lunedì 2 luglio 2012 dalle ore 15.00 alle ore 18.00 presso il Dipartimento di Matematica e Informatica, via Ospedale 72, Aula Magna Matematica, un seminario dal titolo:
DATA STREAM MANAGEMENT SYSTEMS
Supporting Complex Event Processing
Il seminario si svolgerà in lingua inglese.
Il corso è aperto a tutti gli interessati, inclusi gli studenti delle lauree magistrali.
Everyone is invited to join the course.
Abstract
In the age of the Internet, massive amounts of information are continuously exchanged as data streams that are then processed by on-line applications of increasing complexity. For such advanced applications, a store-now and process-later approach cannot be used because of real time (or quasi real-time) requirements and excessive data rates. Therefore, current research seeks to develop a new generation of information management systems, called Data Stream Management Systems (DSMS), that can support complex applications on massive data streams with Quality of Service (QoS) guarantees. This work has produced novel techniques, research prototypes, startup companies, and the successful deployment of DSMS in many applications, including network traffic analysis, transaction log analysis, intrusion detection, credit-card fraud detection, click stream analysis, and algorithmic trading.
Since many such applications involve both streaming data and stored data, the approach taken by most DSMS consists in expressing continuous queries on data streams using extensions of SQL. But significant changes in the language and its implementation are needed, since DSMS must support persistent queries on ordered streams of transient tuples-instead of the transient queries on unordered sets of persistent tuples of relational DBMS. In particular, only monotonic queries and non-blocking operators can be used. Also, the unbounded streams must be represented by synopses, such as windows containing the most recent tuples in the streams. Thus the semantics of basic operators such as joins and aggregates must be revised for windows. At the implementation level, we have new query optimization techniques that seek to minimize response time and memory utilization. Load shedding techniques based on samples and sketches are used to achieve QoS under overload conditions. This short course, will cover these techniques, and the main DSMS systems, with a focus on Complex Event Processing (CEP) such as data mining and advanced analytics.
Since many such applications involve both streaming data and stored data, the approach taken by most DSMS consists in expressing continuous queries on data streams using extensions of SQL. But significant changes in the language and its implementation are needed, since DSMS must support persistent queries on ordered streams of transient tuples-instead of the transient queries on unordered sets of persistent tuples of relational DBMS. In particular, only monotonic queries and non-blocking operators can be used. Also, the unbounded streams must be represented by synopses, such as windows containing the most recent tuples in the streams. Thus the semantics of basic operators such as joins and aggregates must be revised for windows. At the implementation level, we have new query optimization techniques that seek to minimize response time and memory utilization. Load shedding techniques based on samples and sketches are used to achieve QoS under overload conditions. This short course, will cover these techniques, and the main DSMS systems, with a focus on Complex Event Processing (CEP) such as data mining and advanced analytics.
Referente: Prof. Maurizio Atzori - atzori@unica.it