A comparative performance evaluation of Flink

Dongwon Kim, POSTECH

A Semantic Big Data Companion

Stefano Bortoli, OKKAM - Flavio Pompermaier, OKKAM

A tale of Squirrels and Storms

Matthias Sax, HU Berlin

Apache Flink cluster deployment on Docker using Docker-Compose

Romeo Kienzler, IBM - Simon Laws, Emerging Technology

Apache Flink: from incubation to Flink 1.0 (Kesselhaus)

Kostas Tzoumas, data Artisans - Stephan Ewen, data Artisans

Apache SAMOA: Mining Big Data Streams with Apache Flink

Albert Bifet, Huawei

Applying Kappa architecture in the telecom industry

Ignacio Mulas Viela, Ericsson

Automatic Detection of Web Trackers at Telefonica Research

Vasia Kalavri, KTH

Beyond MapReduce, Scientific data processing in real-time

Christopher Hillman, University of Dundee

BigPetStore: A comprehensive blueprint for Apache Flink

Suneel Marthi, RedHat

Cascading on Apache Flink

Fabian Hueske, data Artisans

Data science lifecycle with Apache Flink and Apache Zeppelin

Moon soo Lee, NFLabs

Declarative Machine Learning with the Samsara DSL

Sebastian Schelter, TU Berlin

Everyday Flink

Michael Häusler, ResearchGate

Fault Tolerance and Recovery of Flink Jobs

Till Rohrmann, data Artisans

Flink – a convenient abstraction layer for YARN?

Vyacheslav Zholudev, ResearchGate

Flink and Spark: Similarities and Differences

Slim Baltagi, Capital One

Flink? Yet another streaming framework?

Alexander Kolb, Otto Group

Google Cloud Dataflow and Flink, making streaming the default for data processing Cloud and on-premises (Kesselhaus)

William Vambenepe, Google

Google Cloud Dataflow on top of Apache Flink

Maximilian Michels, data Artisans

Gradoop: Scalable Graph Analytics with Apache Flink

Martin Junghanns, University of Leipzig

Implementing Streaming Decision Tree Using Approximative Algorithms in Flink

Anwar Rizal, Amadeus

Interactive Flink Analytics with Hopsworks and Apache Zeppelin

Jim Dowling, SICS

Juggling with Bits and Bytes – How Apache Flink operates on binary data

Fabian Hueske, data Artisans

Karamel – Reproducing distributed systems and experiments on cloud

Kamal Hakimzadeh, KTH

Lightning talks: Flink case studies (Kesselhaus)

Stefano Bortoli, OKKAM - Mohamed Amine Abdessemed, Bouygues Telecom - Ignacio Mulas Viela, Ericsson - Anwar Rizal, Amadeus - Christian Kreuzfeldt, Otto Group - Slim Baltagi, Capital One

Notions of Time – How Apache Flink Handles Time and Windows

Aljoscha Krettek, data Artisans

Procedural Programming vs. Data Flow

Mikio Braun, Zalando

Real Time Analytics at Scale – Smart Data Pipes for the Internet of Things

Assaf Araki, Intel

Real-time data integration with Flink & Apache Kafka at Bouygues Telecom

Mohamed Amine Abdessemed, Bouygues Telecom

Stale Synchronous Parallel Iterations on Flink

Nam-Luc Tran, EURANOVA

Stateful Stream processing

Marton Balassi, Hungarian Academy of Sciences

Static vs Dynamic Stream Processing

Christian Kreuzfeldt, Otto Group

Stream and Batch Processing in One System — Apache Flink’s Streaming Data Flow Engine

Ufuk Celebi, data Artisans

Training: DataSet API Hands-On and FlinkML

Maximilian Michels, data Artisans

Training: DataStream API Hands-On #1

Aljoscha Krettek, data Artisans

Training: DataStream API Hands-On #2

Aljoscha Krettek, data Artisans

Training: FlinkML Hands-On

Maximilian Michels, data Artisans

Training: Gelly School

Vasia Kalavri, KTH

Training: Intro & System Setup

Fabian Hueske, data Artisans

Using Flink with MongoDB to enhance relevancy in personalization

Marc Schwering, MongoDB



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