Fast and Easy Stream Processing with Hazelcast Jet
This talk is 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 a demo app.
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 and other stream engines like Spark, 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.