Sessions

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


×

Thanks!

We've added you to our Newsletter.

Feel free to unsubscribe at any time through the link provider in the bottom of our e-mails.

×

You're already on the list

×