Humboldt-Universität zu Berlin - Faculty of Mathematics and Natural Sciences - Process-Driven Architectures

Event Processing (VL/UE)

Prof. Dr. Matthias Weidlich

 

Content

Sensing of data is a major trend these days. The number of devices that are connected to the Internet and continuously emit events is growing drastically. Event processing systems are a technology that helps to make sense of these events, by filtering event data, transforming events, and matching event query patterns against a set of incoming event streams. Yet, the increasing volume, velocity, variety and distribution of event sources imposes challenges for the design and implementation of event processing systems. To cope with these requirements, various competing approaches have been proposed in the literature, each taking particular design decisions.

 

Structure

In the first part of the course, lectures and recitations will focus on the fundamental models and  algorithms of event processing systems. That includes common event models, languages for event processing, techniques to achieve robustness, and optimisations of event processing.

The second part of the course will be organised as a seminar. Each student will be asked to read a recent research paper on event processing (selection from a given list) and give a critical assessment of the approach presented in the paper in the form of a 45min presentation.

The course will be given in English. The first lecture will take place on Monday, 24th April, 2017.

 

Exam

There will be an oral exam at the end of the semester. To be eligible to take the exam, each student will be required to give a presentation (45min) on a research paper in the second part of the course. 

 

Credit Points

The course counts for 5 LP and is open for: Informatik, Master of Science (M.Sc.) Informatik, Master of Education (M.Ed.) Wirtschaftsinformatik, Master of Science (M.Sc.). The related area of specialisation is "Daten- und Wissensmanagement".

 
Students enrolled in the programme "Informatik, Diplom" may ask for an additional assignment task, which accounts for additional 3 LP.

 

Dates

VL Mo 13-15 RUD 26, Raum 1'306
UE Mo 15-17 RUD 26, Raum 1'306

 

 

 

 

Lecture Slides 

  • Lecture 1 - Events, event types, event processing networks
  • Lecture 2 - Event-driven systems
  • Lecture 3 - Relational Stream Processing (v2)
  • Lecture 4 - Streaming Joins
  • Lecture 5 - Sequence Queries (v2)
  • Lecture 6 - Optimisations and Logic-based Approaches
  • Guest Lecture by Tilmann Rabl on Benchmarking
  • Lecture 7 - Questions

     

    Recitations 

     

    Presentation Slots

    Date Topic and Presenters
       

    June 12, 2017
    1) ZStream
    David Luis Wiegandt, Markus Waas
     
    3) TRex
    Alexander Heemann, Simon Hansen
     
    4) XML Streaming
    Belhassen Ouerghi, Minxing Tang
     
    5) Linked Data Streaming
    Stephan Fahrenkrog-Petersen, Thomas Schlegel

     

    		  

    June 19, 2017
    6) Out-of-order streaming
    Steffen Przybylowicz, Leonhard Balduf
     
    7) Speculative Processing
    Matthias Menzel, Valentin Zambelli
     
    9) Imprecise CEP
    Andreas Wegge
       

    July 3, 2017
    10) Fault Tolerance
    Sophia Mühling
     
    15) Elastic Streaming
    Paul Schulze, Robert Muth

     

    		  

    July 10, 2017
    11) Incremental Aggregation
    Wadim Michaljow, Dimitar Dimitrov
     
    12) Semantic Optimisation
    Maximilian Bielefeld, Robin Ellerkmann
     
    13) Pattern Sharing
    Jan Baudis, André Niendorf 
     
    14) Handshake Join
    Matthias Höschel, Matthias Becher

     

    		  
     

    Presentation Topics 

    Note on the dates: topics 1-12 are likely to be scheduled for June 12 or June 19, 2017. The remaining topics are scheduled for July 3 or July 10, 2017.

     
    1) ZStream
    Yuan Mei and Samuel Madden. ZStream: A cost-based query processor for adaptively detecting composite events. In Proceedings of the 2009 ACM SIGMOD International Conference on Management of data (SIGMOD ’09), pages 193–206, 2009. paper link
     
    2) Secret
    Nihal Dindar, Nesime Tatbul, Renee J. Miller, Laura M. Haas, and Irina Botan. Modeling the execution semantics of stream processing engines with secret. The VLDB Journal, 22(4):421–446, 2013. paper link
     
    3) TRex
    Gianpaolo Cugola and Alessandro Margara. Complex event processing with T-REX. J. Syst. Softw., 85(8):1709–1728, 2012. paper link
     
    4) XML Streaming
    Barzan Mozafari, Kai Zeng, Carlo Zaniolo: High-performance complex event processing over XML streams. SIGMOD Conference 2012: 253-264 paper link
     
    5) Linked Data Streaming
    Omran Saleh, Stefan Hagedorn, Kai-Uwe Sattler: Complex Event Processing on Linked Stream Data. Datenbank-Spektrum 15(2): 119-129 (2015) paper link
     
    6) Out-of-order streaming
    Mo Liu, Ming Li, Denis Golovnya, Elke A. Rundensteiner, and Kajal T. Claypool. Sequence pattern query processing over out-of-order event streams. In ICDE, pages 784–795, 2009. paper link
     
    7) Speculative Processing
    Christopher Mutschler, Michael Philippsen: Adaptive Speculative Processing of Out-of-Order Event Streams. ACM Trans. Internet Techn. 14(1): 4:1-4:24 (2014) paper link
     
    8) Uncertain Events
    Segev Wasserkrug, Avigdor Gal, Opher Etzion, Yulia Turchin: Efficient Processing of Uncertain Events in Rule-Based Systems. IEEE Trans. Knowl. Data Eng. (TKDE) 24(1):45-58 (2012) paper link
     
    9) Imprecise CEP
    Haopeng Zhang, Yanlei Diao, Neil Immerman: Recognizing patterns in streams with imprecise timestamps. Inf. Syst. 38(8): 1187-1211 (2013) paper link
     
    10) Fault Tolerance
    Andre Martin, Thomas Knauth, Stephan Creutz, Diogo Becker de Brum, Stefan Weigert, Christof Fetzer, Andrey Brito: Low-Overhead Fault Tolerance for High-Throughput Data Processing Systems. ICDCS 2011: 689-699 paper link
     
    11) Incremental Aggregation
    K. Tangwongsan, M. Hirzel, S. Schneider, and K.-L. Wu. General Incremental Sliding-window Aggregation. Proc. VLDB Endow., 8(7):702–713, Feb. 2015 paper link
     
    12) Semantic Optimisation
    Luping Ding, Karen Works, Elke A. Rundensteiner: Semantic stream query optimization exploiting dynamic metadata. ICDE 2011:111-122 paper link
     
    13) Pattern Sharing
    Medhabi Ray, Chuan Lei, Elke A. Rundensteiner: Scalable Pattern Sharing on Event Streams. SIGMOD Conference 2016: 495-510 paper link
     
    14) Handshake Join
    Pratanu Roy, Jens Teubner, Rainer Gemulla: Low-Latency Handshake Join. PVLDB 7(9): 709-720 (2014) paper link
     
    15) Elastic Streaming
    Thomas Heinze, Mariam Zia, Robert Krahn, Zbigniew Jerzak, Christof Fetzer: An adaptive replication scheme for elastic data stream processing systems. DEBS 2015: 150-161 paper link
     
    16) Saber
    Alexandros Koliousis, Matthias Weidlich, Raul Castro Fernandez, Alexander L. Wolf, Paolo Costa, Peter R. Pietzuch: SABER: Window-Based Hybrid Stream Processing for Heterogeneous Architectures. SIGMOD Conference 2016: 555-569 paper link
     
     
     
     

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