26-28 November, 2019, Vilnius

Conference Starts in:

Day(s)

:

Hour(s)

:

Minute(s)

:

Second(s)

Vladimir Schreiner

Hazelcast, Czech Republic

Venue

Crowne Plaza Vilnius
(M. K. Čiurlionio str. 84, Vilnius, Lithuania).

}

Time & Date

10:00, 26 November

Language

English

Biography

Vladimir is a technical manager with an engineering background (Master’s degree in Computer science) and deep expertise in stream processing and real-time data pipelines. Ten years of building internal software platforms and development infrastructure have made him passionate about new technologies and finding ways to simplify data processing. Therefore Vladimir joined Hazelcast in 2016 and he is a product guy behind Hazelcast Jet streaming engine. He authored the Understanding Stream Processing DZone Refcard. Vladimir is also a lecturer with the Czechitas Foundation, whose mission is to inspire women and girls to explore the world of information technology.

Workshop

Stream Processing Essentials

Abstract

Take your first steps to understanding and start working with stream processing! By the end of the course, you will be able to build and run distributed streaming pipelines in Java:

  • Explain when to use streaming
  • Design a streaming application from the building blocks
  • Transform, match, correlate and aggregate continuous data
  • Scale, deploy, and operate streaming apps

We will also cover the advantages and disadvantages of the stream processing technologies available when approaching real-world problems.

Agenda

Part 1: Stream Processing Overview

  • Streaming: what is it and where did it come from
  • How streaming fits into the architecture
  • Continuous data pipelines
  • Use-Cases
  • The architecture of current streaming frameworks

Part 2: Transforming a Stream of Data (Lab)

  • Connectivity
  • Transforming and filtering

Part 3: Enrichment (lab)

  • Local and remote lookup services
  • Caching for performance

Part 4: Aggregations (lab)

  • Stateful Streaming
  • Batch x windowed aggregations
  • Time-series data and late events

Part 5: Scaling and Operations (lab)

  • Going distributed
  • Embedded and Remote cluster setups
  • Elasticity and fault tolerance
  • Upgrading the running job
  • Monitoring and diagnostics

Part 6: Q&A and Conclusion

Objectives

This workshop is designed for Java Developers who want to take their first steps to understanding and start working with stream processing.

Target audience

Java Engineers.

Technical requirements

Bring your laptop, prepared with:

  • A recent Java 8 JDK or newer
  • Your IDE of choice installed – IntelliJ Idea, Eclipse, NetBeans, etc.
  • Download lab code from https://github.com/hazelcast/hazelcast-jet-training and import it to the IDE as a Maven project
  • Build the labs using Maven to get the dependencies

Attendees should be familiar with Java 8 concepts and APIs (collections, concurrency, lambdas). No prior knowledge of data processing is required.