Flink SQL in Action, Low latency decision for Bot and Flink goes Cloud Native

Bonjour à tous,

Nous avons le plaisir de vous recevoir chez Critéo le 14 novembre prochain pour 3 "Fast Data" talks avec Apache Flink:

• Fabian Hueske (dataArtisans) montrera Flink SQL en Action,
• Benjamin Fabre et Philippe Loulidi (DataDome) présenteront leur retour d'expérience sur la mise en place d'une stack Kafka/Flink à faible latence dans le cadre d'une solution de Bot Management,
• Pierre Bittner (WeeFin) donnera son retour d'XP sur l'utilisation de Flink avec les services managés d'AWS (EKS, Kinesis,.. ).

Merci beaucoup à Critéo de sponsoriser ce meetup et de nous héberger. Un espace networking sera disponible jusque 22h.

Détails des présentations:

Flink SQL in Action par Fabian Hueske (@fhueske) - PMC member of @ApacheFlink - Co-Founder of @DataArtisans

Abstract:
Stream processing is rapidly adopted by the enterprise. While in the past, stream processing frameworks mostly provided Java or Scala-based APIs, stream processing with SQL is recently gaining a lot of attention because it makes stream processing accessible to non-programmers and significantly reduces the effort to solve common tasks.

About three years ago, the Apache Flink community started adding SQL support to process static and streaming data in a unified fashion. Today, Flink SQL powers production systems at Alibaba, Huawei, Lyft, and Uber.

In this talk, I will discuss the current state of Flink’s SQL support and explain the importance of Flink’s unified approach to process static and streaming data. Once the basics are covered, I will present common real-world use cases ranging from low-latency ETL to pattern detection and demonstrate how easily they can be addressed by Flink SQL.

Duration: ≈ 40 minutes