Scott McMahon on Fast and Easy Stream Processing

The SDJUG meets every 3rd Tuesday of the month.

6:30 - Equipment setup and mixer - Food provided by Hazelcast
7:00 - Meeting begins, announcements
7:15 - Speaker: Scott McMahon on "Fast and Easy Stream Processing"
8:00- Short Break
8:10 - Speaker: Scott McMahon on "Fast and Easy Stream Processing"
9:00 - Drawings - final announcements Meeting Ends, tear down, mixer
9:30 - Official Stop

Abstract:
Join us at this meetup and learn about core techniques in stream processing and how to get started building a stream processing application. We will be showcasing real world use cases and demos.

You will learn all about directed acyclic graph (DAG) and why it's so powerful for Big Data processing. We will walk you through the evolution of Big Data computing, from sequential to DAG, as well as other techniques such as SP/SC, Cooperative Multithreading, Data Locality, In-Memory sources and sinks, and WaitFree algorithms that power Big Data processing.

This talk will also feature an introduction to Hazelcast JET, an open source, DAG-based in-memory real time streaming and batch processing engine. With Hazelcast Jet, you can use data stores such as HDFS, Kafka, Hazelcast In-Memory Data Grid and more. We will also review the major differences between Hazelcast Jet, Spark, Twitter Heron, Flink, and Kafka Streams.

We will walk you through writing a sample application and show how you can be up and running in less than a hundred lines of Java code. Demo applications will feature Twitter Cryptocurrency Sentiment Analysis and real-time worldwide commercial aircraft monitoring.

Speaker Bio:
Scott McMahon is a Senior Solutions Architect at Hazelcast, based in Portland, with over 20 years of software development and enterprise consulting experience. Before specializing in Hazelcast's In-Memory Data Grid and Stream Processing technologies, he built big data analytics platforms and business process management systems for many of the world’s leading corporations.