Stream Processing and Real-time analytics have caught the interest of the industry lately. Many use cases are nowadays waiting for relevant and efficient solutions to be developed. Such use cases include event-driven marketing, dynamic network management & optimization, real-time recommendation, context-aware applications and real-time fraud detection.

In the past years, researchers and practitioners in the area of data stream management [1, 2, 3] and Complex Event Processing (CEP) [4, 5, 6] have developed systems to process unbounded streams of data and quickly detect situations of interest.

Nowadays, big data technologies provide a new ecosystem to foster research in this area. Highly scalable distributed stream processors and the convergence of batch and stream engines (such as Apache Spark [9] or Apache Flink [10]) open new doors for highly scalable and distributed real-time analytics. Going further, those technologies also provide a solid foundation for real-time analytics algorithms that are complementary to the CEP in the use cases required by the industry. As a result, we also encourage submissions studying scalable on-line learning and incremental learning on stream processing infrastructure.

Finally, the maturity of the Real-time technologies have seen emerging new architecture patterns in Event-Driven Architecture or in Data architecture that leverage Stream Processing framework [7,8]. In the same way, the Internet of things has seen a lot of interesting use cases in stream architecture and mining. We also encourage submissions studying the usage of stream processing in new innovative architectures.

After the success of the first edition this workshop, co-located with the IEEE Big Data 2016, this second edition is an excellent opportunity to gather together actors from academia and industry to discuss, to explore and to refine new opportunities and use cases in the area. The workshop will benefit to both researchers and practitioners interested in the latest researches in real-time and stream processing. The workshop will showcase prototypes or products leveraging big data technologies as well as models, efficient algorithms for scalable complex event processors and context detection engines, or new architecture leveraging stream processing.

Research Topics

The topics of interest include but are not limited to:



It has been a while since you left the easy days of batch processing behind: the lazy ETL jobs that had all night to run, the relaxed SLAs that let you take lunches like Ron Swanson, the government's working hours: the salad days of your data processing career. Those days are over now, and producing real-time results on streaming data is the new order of the day. Two seconds is the new overnight.
Apache Kafka is a de facto standard streaming data processing platform, being widely deployed as a messaging system, and having a robust data integration framework (Kafka Connect) and stream processing API (Kafka Streams) to meet the needs that common attend real-time message processing.
On top of that, Kafka now offers KSQL, a declarative, SQL-like stream processing language. What once took some moderately sophisticated Java code can now be done at the command line with a familiar and eminently approachable syntax. Come to this talk for an overview of KSQL with live coding on live streaming data.


Viktor Gamov is a Solution Architect at Confluent, the company behind the Apache Kafka streaming platform. Viktor has comprehensive knowledge and expertise in enterprise application architecture leveraging open source technologies and enjoys helping different organizations build low latency, scalable and highly available distributed systems. He is also co-organizer of Princeton JUG and a co-author of O’Reilly’s “Enterprise Web Development.” He is a professional conference speaker on Distributed Systems, Java, and JS topics, and is a regular at the most prestigious events including JavaOne, Devoxx, OSCON, Qcon and others, blogging and producing podcasts “Razbor Poletov” (in Russian) and DevRelRad.
Follow Viktor on Twitter : .


The workshop is held on Monday December 11





Workshop Keynote 1: The rise of Stream Processing for data management & micro service Architecture

Sabri Skhiri, EURA NOVA


Workshop Keynote 2: KSQL on Kafka stream: streaming data management

Viktor Gamov, CONFLUENT


ABC: a Practicable Sketch Framework for Non-uniform Multisets

Junzhi Gong, Tong Yang, Yang Zhou, Dongsheng Yang, Shigang Chen, Bin Cui, and Xiaoming Li


Online Mining for Association Rules and Collective Anomalies in Data Streams

Shaaban Abbady, Cheng-Yuan Ke, Jennifer Lavergne, Jian Chen, Vijay Raghavan, and Ryan Benton


A Study of a Video Analysis Framework Using Kafka and Spark Streaming

Ayae Ichinose, Atsuko Takefusa, Hidemoto NAKADA, and Masato Oguchi


Coffee Break


RASP: Real-time Network Analytics with Distributed NoSQL Stream Processing

Georgios Touloupas, Ioannis Konstantinou, and Nectarios Koziris


Towards a Unified Storage and Ingestion Architecture for Stream Processing

Ovidiu-Cristian Marcu, Alexandru Costan, Gabriel Antoniu, Maria Perez, Radu Tudoran, Stefano Bortoli, and Bogdan Nicolae


Smart Distributed Query Execution over Data Streams

Salman Ahmed Shaikh and Hiroyuki Kitagawa


Harnessing the Power of Hashtags in Tweet Analytics

Vibhuti Gupta and Rattikorn Hewett


Predicting Concept Drift via Dynamic Naïve Bayes

Qian Zhao, Chris Klaue, and Chih Lai


Closing Remarks



October 1October 10, 2017
November 1, 2017
November 15, 2017


Your paper should be written in English and formatted to IEEE Computer Society Proceedings Manuscript Formatting Guidelines (Templates). The length of the paper should not exceed 6 pages.

All accepted papers will be published in the Workshop Proceedings by the IEEE Computer Society Press



  • Sabri Skhiri
  • Albert Bifet
    Télécom Paris Tech, FR
  • Alessandro Margara
    Politecnico di Milano, IT


  • Till Rohrmann
    Data Artisans, DE
  • Maosong Fu
    Twitter, US
  • Nam-Luc Tran
    IBA, BE
  • Amine Ghrab
  • Thomas Peel
  • Guido Salvaneschi
    TU Darmstadt, DE
  • Fabricio Enembreck
    Pontifícia Universidade Católica do Paraná, BR
  • Matteo Migliavacca
    University of Kent, UK
  • José del Campo Ávila
    Universidad de Málaga, ES