Introduction to Stream Processing with Hazelcast
Next week it’s our Introduction to Stream Processing event in conjunction with Hazelcast and the Hazelcast Joint User Group. At the session Neil Stevenson, Senior Solution Architect at Hazelcast will discuss ‘Easy and Fast Stream Processing’.
In this session we’ll learn all about directed acyclic graph (DAG) and why it’s so powerful for Big Data processing. We’ll walk 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 the third generation of Big Data processing.
Before the talk we chatted to Neil to find out a bit more about what we can expect.
Who do you think should come along?
Developers and architects looking to gain an understanding of both the theory and practicalities surrounding stream processing.
What do you think are the three most interesting questions that this event will answer?
Why are streams important?
What are the performance implications?
What does this mean for architecture?
Why do you think this presentation is important for people?
Data is getting bigger, we’re collecting more and more of it at a faster and faster rate. So what we need is a paradigm shift that enables us to process the input stream prior to storage. This is the key difference of stream processing, we store the output not the input.
Any advice for junior developers entering the industry?
If you’ve been asked to do something, ask yourself why the company needs it. Try and wear a business and a technical hat. That should provide you with the bigger picture which will help you get a better result. Technology never stops developing, if you think you’ve got a handle on it, something new will appear which will provide new challenges. Ride the wave and enjoy it.
If you’d like to join us, the session is happening next Wednesday, 7th November, 18:00 @ David Game College, EC3N 2ET. You can find the full details and register here.