Companies need a data-processing solution that increases the speed of business agility, not one that is complicated by too many technology requirements. This requires a system that delivers continuous/real-time data-processing capabilities for the new business reality.
Stream processing is a hot topic right now, especially for any organization looking to provide insights faster. But what does it mean for users of Java applications, microservices, and in-memory computing?
In this webinar, we will cover the evolution of stream processing and in-memory related to big data technologies and why it is the logical next step for in-memory processing projects.
Setting up servers and configuring software can get in the way of the problems you are trying to solve. With Hazelcast Cloud we take all of those pain points away.
Watch this webinar to learn how you can instantly fire up and then work with Hazelcast Cloud from anywhere in the world. With our auto-generated client stubs for Java, Go, Node.js, Python and .NET, we can have you connected and coding in less than a minute!
Through conceptual overviews, demos, and hands-on practice, you will learn to create stream processing pipelines using Java and Hazelcast Jet. This class is for advanced Java programmers who want to take their first steps in understanding and working with stream processing as well as for those who are already experienced in building the data processing applications and want to learn more about working with streaming data.
By the end of the course, you will have built and run distributed streaming pipelines to transform, enhance, and aggregate streaming data. You will also be able to discuss various stream processing options in terms of solving real-world, business-related problems.
The course includes the following lessons:
Note that stream processing pipelines are built using Java lambdas. If you are not familiar with this type of coding, you may not be able to complete many of the hands-on exercises without referring to the sample solutions.