Sep 23–26, 2019
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Stream processing beyond streaming data

Stephan Ewen (Ververica)
2:05pm2:45pm Thursday, September 26, 2019
Location: 1A 03
Average rating: *****
(5.00, 3 ratings)

Who is this presentation for?

  • Data engineers, architects, and data scientists

Level

Intermediate

Description

Stream processing is becoming something like a “grand unifying paradigm” for data processing. Outgrowing its original space of real-time data processing, stream processing is becoming a technology that offers new approaches to data processing (including batch processing), real-time applications, and even distributed transactions.

Stephan Ewen dives into these developments from the view of Apache Flink and presents some of the major efforts in the Flink community to build a unified stream processor data processing and data-driven applications. Flink already powers many of the world’s most demanding stream processing applications. He explores the approach of Flink’s next-generation streaming runtime that offers a state-of-the-art batch processing experience and performance. A new machine learning library, built on top of a unique new API, supports many algorithms to train dynamically across static and real-time data. And he examines the new building blocks stream processing offers for data-driven applications that open a new direction to solve application consistency. You’ll see use cases from different users, showing how companies apply this broader streaming paradigm in practice.

With use cases from different users, we show how companies apply this broader streaming paradigm in practice.

Prerequisite knowledge

  • A basic understanding of stream processing (useful but not required)

What you'll learn

  • Understand the breadth of changes that stream processing is introducing to data infrastructures and to the way we build applications and which areas are most likely to be affected next
Photo of Stephan Ewen

Stephan Ewen

Ververica

Stephan Ewen is a cofounder and chief technology officer at Ververica, where he leads the development of the stream processing platform based on open source Apache Flink. He’s also a PMC member and one of the original creators of Apache Flink. Previously, Stephan worked on in-memory databases, query optimization, and distributed systems. He holds a PhD from the Berlin University of Technology.

  • Cloudera
  • O'Reilly
  • Google Cloud
  • IBM
  • Cisco
  • Dataiku
  • Intel
  • Io-Tahoe
  • MemSQL
  • Microsoft Azure
  • Oracle Cloud Infrastructure
  • SAS
  • Arcadia Data
  • BMC Software
  • Hazelcast
  • SAP
  • Amazon Web Services
  • Anaconda
  • Esri
  • Infoworks.io, Inc.
  • Kyligence
  • Pitney Bowes
  • Talend
  • Google Cloud
  • Confluent
  • DataStax
  • Dremio
  • Immuta
  • Impetus Technologies Inc.
  • Keyence
  • Kyvos Insights
  • StreamSets
  • Striim
  • Syncsort
  • SK holdings C&C

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